Reset23/the-stack-v2-processed · Datasets at Hugging Face

5946b71e2ab0dea1477088813ea136f3eec56027

649bd422025e421d86025743eac324c9b882a2e8

/exam/1_three-dimensional_atomic_system/dump/phasetrans/temp204_3500.py

2257cb33602a12bda3d813cf203fd13c700b9869

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no_license

scheuclu/atom_class

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0c9a8c63d9b38898c1869fe8983126cef17662cd

refs/heads/master

2021-01-21T10:52:28.448221

2017-03-07T23:04:41

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ITEM: TIMESTEP 3500 ITEM: NUMBER OF ATOMS 2048 ITEM: BOX BOUNDS pp pp pp -1.6878559649266461e+02 2.1598559649270894e+02 -1.6878559649266461e+02 2.1598559649270894e+02 -1.6878559649266461e+02 2.1598559649270894e+02 ITEM: ATOMS id type xs ys zs 782 1 0.287021 0.0038045 0.0236388 558 1 0.674384 0.0753822 0.0141806 571 1 0.736726 0.027479 0.0146 226 1 0.184719 0.0834659 0.0136485 1090 1 0.788186 0.0986098 0.0349484 1676 1 0.227413 0.0790193 0.00367851 623 1 0.108919 0.164679 0.0241208 743 1 0.271672 0.202921 0.0259242 799 1 0.203033 0.0074178 0.0604077 1835 1 0.259457 0.228718 0.00165648 1563 1 0.49129 0.205837 0.0154109 1223 1 0.585254 0.201326 0.0179075 1018 1 0.400539 0.411626 0.492716 357 1 0.909863 0.493517 0.0903839 1797 1 0.266311 0.48873 0.332012 426 1 0.784501 0.268655 0.00500636 791 1 0.734288 0.293108 0.0269897 1728 1 0.0389256 0.384458 0.458482 1456 1 0.150157 0.349357 0.00241034 309 1 0.54609 0.317467 0.0291573 144 1 0.692452 0.368829 0.00669871 360 1 0.916866 0.384515 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0.389712 0.439294 981 1 0.0686337 0.415485 0.405044 917 1 0.663433 0.468461 0.447093 1084 1 0.418525 0.356809 0.49532 341 1 0.533574 0.0338698 0.440056 1411 1 0.788748 0.00158473 0.461653 1783 1 0.147257 0.0230664 0.422727 33 1 0.86136 0.0809469 0.443666 1286 1 0.627894 0.166337 0.478271 1221 1 0.65239 0.255664 0.450809 1130 1 0.394428 0.274992 0.441402 1651 1 0.499174 0.292625 0.450502 1233 1 0.0100392 0.341547 0.453452 1720 1 0.945419 0.32748 0.432308 582 1 0.187894 0.369754 0.462046 494 1 0.551054 0.358438 0.448098 832 1 0.554252 0.379637 0.479293 1145 1 0.535622 0.474499 0.453567 1776 1 0.28534 0.467664 0.468879 310 1 0.963172 0.479431 0.422433 1314 1 0.375748 0.0546405 0.489646 1370 1 0.567781 0.106652 0.487936 746 1 0.774423 0.0536732 0.461273 440 1 0.831124 0.496907 0.0949259 1604 1 0.377698 0.11421 0.480019 1154 1 0.59634 0.212863 0.492101 1146 1 0.869285 0.15288 0.49057 464 1 0.818671 0.235471 0.485891 209 1 0.115246 0.268583 0.45678 1071 1 0.213329 0.241344 0.472431 1621 1 0.394268 0.274262 0.485658 745 1 0.0474636 0.426004 0.468347 278 1 0.0483162 0.420693 0.48118 1052 1 0.396362 0.426116 0.472728 808 1 0.131074 0.458852 0.468514 1847 1 0.661678 0.474692 0.477153 1520 1 0.837855 0.00828726 0.0258176 594 1 0.296855 0.491244 0.373236 1161 1 0.895908 0.0709569 0.49103 75 1 0.446474 0.0608641 0.482866 1403 1 0.815577 0.120261 0.467543 325 1 0.788151 0.202072 0.484591 404 1 0.573102 0.225222 0.483272 1081 1 0.199558 0.220818 0.486099 692 1 0.532103 0.0129023 0.487769 262 1 0.361127 0.350217 0.494042 328 1 0.527625 0.000112712 0.164085 1617 1 0.416459 0.371375 0.499917 964 1 0.73022 0.490457 0.919875 1298 1 0.582904 0.119772 0.505028 1878 1 0.662422 0.217862 0.532066 1586 1 0.360781 0.242387 0.527513 105 1 0.360046 0.399291 0.971451 1172 1 0.175121 0.298798 0.528579 2016 1 0.946668 0.287683 0.520432 104 1 0.0272397 0.373187 0.50358 254 1 0.118563 0.305939 0.978201 490 1 0.668024 0.491538 0.892173 1257 1 0.631704 0.00561503 0.600715 915 1 0.850059 0.436971 0.505228 1631 1 0.0331321 0.475854 0.532385 575 1 0.926325 0.323784 0.967176 290 1 0.926366 0.0260043 0.506924 600 1 0.943787 0.0589805 0.556954 1673 1 0.42725 0.0999055 0.551706 514 1 0.92849 0.176703 0.559413 231 1 0.567807 0.177163 0.539362 1616 1 0.779609 0.247031 0.99329 982 1 0.94536 0.240394 0.544844 1372 1 0.362737 0.244867 0.515314 1951 1 0.330316 0.240496 0.502828 1043 1 0.297308 0.285617 0.549298 1606 1 0.818054 0.310277 0.510049 1401 1 0.322145 0.353889 0.563437 1587 1 0.379781 0.351226 0.547945 798 1 0.735564 0.371184 0.558735 364 1 0.23391 0.35497 0.988118 912 1 0.911083 0.41342 0.528173 1077 1 0.570843 0.431056 0.546676 893 1 0.74517 0.358495 0.994343 1061 1 0.235482 0.476236 0.514688 224 1 0.70234 0.489804 0.657611 1906 1 0.591297 0.0205021 0.521669 701 1 0.336567 0.0698936 0.557315 1855 1 0.861791 0.118101 0.527799 614 1 0.306217 0.162431 0.542651 1717 1 0.748358 0.204821 0.521999 1818 1 0.145494 0.220645 0.562947 2000 1 0.178517 0.249655 0.524903 2015 1 0.304345 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0.259008 0.607003 1903 1 0.920954 0.332538 0.574847 1102 1 0.540526 0.344859 0.573125 279 1 0.402616 0.367754 0.558643 769 1 0.497891 0.395542 0.59798 914 1 0.690168 0.403646 0.597909 327 1 0.703724 0.332351 0.596984 1671 1 0.609352 0.432315 0.545147 1644 1 0.0515875 0.414638 0.58415 74 1 0.131429 0.447974 0.595776 1053 1 0.785528 0.45265 0.585377 855 1 0.802033 0.473979 0.57552 150 1 0.478299 0.282629 0.957465 1070 1 0.258719 0.0488222 0.586913 1666 1 0.366955 0.0410076 0.594306 997 1 0.581057 0.107548 0.60207 1288 1 0.76229 0.0969283 0.596677 1069 1 0.88909 0.147456 0.576562 1080 1 0.17574 0.172268 0.566207 1088 1 0.746879 0.227535 0.604002 849 1 0.379677 0.253677 0.61484 1749 1 0.442625 0.289866 0.593689 1983 1 0.487916 0.419448 0.60506 1380 1 0.515471 0.419566 0.614737 19 1 0.971143 0.396059 0.606251 1140 1 0.373096 0.43797 0.623996 466 1 0.92478 0.0492755 0.609844 1123 1 0.689482 0.12292 0.605277 1825 1 0.580369 0.207048 0.604867 430 1 0.734565 0.268263 0.603556 852 1 0.767219 0.275712 0.632256 956 1 0.0535888 0.292997 0.629904 1331 1 0.273934 0.352688 0.62274 123 1 0.70694 0.400537 0.629262 1945 1 0.303223 0.373601 0.624088 1640 1 0.192185 0.472149 0.635764 635 1 0.465904 0.414875 0.628018 92 1 0.126056 0.455377 0.602623 1767 1 0.573781 0.0538133 0.6623 501 1 0.901564 0.0154419 0.63367 1420 1 0.415907 0.0126712 0.668376 1762 1 0.576077 0.176092 0.989918 1750 1 0.254758 0.039171 0.644545 216 1 0.436513 0.0683403 0.655556 1506 1 0.879715 0.0817324 0.653988 1852 1 0.270692 0.146711 0.656414 1338 1 0.652292 0.19998 0.649215 214 1 0.101819 0.153439 0.608926 1581 1 0.378079 0.203758 0.647352 1339 1 0.7801 0.18322 0.646603 515 1 0.378202 0.228676 0.632865 1092 1 0.250355 0.299848 0.648509 1775 1 0.603976 0.265233 0.629903 358 1 0.495648 0.333323 0.652866 1594 1 0.175614 0.349808 0.661074 263 1 0.472473 0.339236 0.643947 65 1 0.254312 0.393949 0.669057 156 1 0.30868 0.399352 0.653356 1933 1 0.526464 0.396593 0.669791 642 1 0.427944 0.0546573 0.684634 709 1 0.953779 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0.549968 0.350456 0.684166 2006 1 0.525482 0.353204 0.677697 1815 1 0.617863 0.375288 0.682023 909 1 0.839381 0.452698 0.678263 1885 1 0.13844 0.494451 0.67735 677 1 0.435625 0.489559 0.679062 768 1 0.815394 0.0224688 0.718322 584 1 0.953208 0.458094 0.709656 601 1 0.855757 0.00840657 0.583911 151 1 0.99919 0.0682137 0.66708 504 1 0.32245 0.0950389 0.722688 951 1 0.835482 0.114627 0.675499 2034 1 0.880034 0.142751 0.714164 2001 1 0.0487009 0.16742 0.701314 499 1 0.367008 0.153039 0.71966 184 1 0.810976 0.234334 0.71248 1148 1 0.214927 0.276504 0.712659 1746 1 0.461988 0.315404 0.696468 1429 1 0.915972 0.409554 0.682088 624 1 0.98379 0.423538 0.69611 977 1 0.3379 0.476338 0.675508 1479 1 0.640236 0.0161934 0.711244 1499 1 0.887856 0.0293217 0.738289 1751 1 0.601023 0.0807438 0.721209 1921 1 0.863061 0.065942 0.709609 1573 1 0.927106 0.137713 0.715382 519 1 0.931493 0.0878086 0.729828 176 1 0.366776 0.168748 0.706132 528 1 0.0915105 0.173799 0.732698 935 1 0.210894 0.168959 0.718052 476 1 0.962404 0.193685 0.711454 1512 1 0.435659 0.18289 0.732706 942 1 0.825056 0.210895 0.708283 859 1 0.206856 0.235921 0.735462 1308 1 0.0924278 0.320491 0.711361 851 1 0.474362 0.260944 0.690713 1557 1 0.57559 0.255671 0.701945 173 1 0.58336 0.316909 0.715748 1697 1 0.707035 0.312614 0.706012 510 1 0.147383 0.306889 0.708263 1704 1 0.282205 0.362824 0.70359 1281 1 0.527311 0.34387 0.715477 1350 1 0.645207 0.357439 0.709172 1058 1 0.874512 0.361126 0.69266 629 1 0.225675 0.374501 0.723888 223 1 0.288193 0.424666 0.708298 1201 1 0.567429 0.419924 0.699942 1274 1 0.120712 0.489574 0.715407 1523 1 0.728271 0.464019 0.734703 1301 1 0.958402 0.236049 0.995682 25 1 0.62578 0.361808 0.520728 1554 1 0.545641 0.0202748 0.716959 669 1 0.377352 0.126192 0.695038 84 1 0.540546 0.0927469 0.734436 870 1 0.759088 0.120425 0.718048 1883 1 0.894704 0.140441 0.74434 119 1 0.394854 0.151017 0.726774 605 1 0.186525 0.173621 0.728956 281 1 0.720401 0.191303 0.716038 28 1 0.409832 0.201461 0.758901 1980 1 0.721767 0.283521 0.723199 755 1 0.0873705 0.284014 0.72541 926 1 0.611945 0.298229 0.727642 2012 1 0.669087 0.318169 0.719298 2014 1 0.755147 0.359508 0.688016 1230 1 0.825672 0.405882 0.715957 1833 1 0.476315 0.423901 0.733603 1122 1 0.638764 0.454632 0.695904 1011 1 0.0105888 0.467908 0.709236 64 1 0.371627 0.0227725 0.721749 732 1 0.465458 0.0292212 0.741081 161 1 0.0335532 0.0288754 0.741088 1789 1 0.122404 0.00134563 0.731007 1225 1 0.56821 0.0111627 0.735071 1021 1 0.70589 0.0403612 0.749972 259 1 0.225718 0.068121 0.73743 726 1 0.403525 0.085495 0.698182 1984 1 0.960937 0.0965519 0.777884 976 1 0.562587 0.148959 0.75474 1515 1 0.123995 0.126947 0.763026 1199 1 0.78391 0.192921 0.736129 1107 1 0.918309 0.150232 0.751358 924 1 0.0210087 0.198814 0.733112 1414 1 0.544561 0.298354 0.757622 1307 1 0.699678 0.39561 0.775137 1073 1 0.22017 0.352724 0.747519 1657 1 0.148428 0.448314 0.766276 1752 1 0.757266 0.463236 0.72148 89 1 0.257765 0.466827 0.753754 1917 1 0.0253227 0.0650755 0.791084 1784 1 0.903548 0.0592609 0.745661 704 1 0.933175 0.0903903 0.78152 16 1 0.532451 0.122552 0.812052 116 1 0.875308 0.149948 0.759673 90 1 0.417349 0.273538 0.778142 1542 1 0.696775 0.268347 0.767224 795 1 0.0107044 0.322811 0.792253 1266 1 0.257842 0.367517 0.741965 287 1 0.986714 0.370922 0.769302 958 1 0.410585 0.36173 0.773939 757 1 0.48553 0.391145 0.733472 2018 1 0.484017 0.445403 0.775336 1730 1 0.454232 0.472102 0.78686 708 1 0.978489 0.437493 0.779886 1575 1 0.259773 0.449071 0.738793 953 1 0.47154 0.482385 0.754471 2032 1 0.548911 0.49486 0.761757 1646 1 0.773763 0.0256588 0.764124 1002 1 0.697156 0.107536 0.835323 1258 1 0.448905 0.166316 0.758932 1128 1 0.349687 0.199302 0.810604 634 1 0.819275 0.147206 0.791081 171 1 0.654647 0.200045 0.832729 121 1 0.692293 0.262813 0.78102 155 1 0.731807 0.244822 0.747757 349 1 0.486782 0.303957 0.772123 1607 1 0.65509 0.259347 0.769143 738 1 0.702776 0.302763 0.760481 1418 1 0.0956467 0.318708 0.807341 1735 1 0.618232 0.329447 0.77381 1466 1 0.578773 0.331328 0.785252 323 1 0.78255 0.392389 0.798376 1010 1 0.230019 0.416554 0.798173 1063 1 0.719645 0.451747 0.794353 1234 1 0.0266218 0.479011 0.782115 1677 1 0.623146 0.0186364 0.78396 1840 1 0.476128 0.0452321 0.804379 60 1 0.853293 0.0513665 0.840812 1910 1 0.224371 0.0625416 0.78355 197 1 0.681846 0.0662863 0.780711 801 1 0.0253767 0.140331 0.786072 1940 1 0.936039 0.161005 0.821098 1990 1 0.0901564 0.155629 0.825127 1383 1 0.623499 0.181776 0.80875 427 1 0.155452 0.175164 0.831652 719 1 0.506171 0.221996 0.825354 609 1 0.844347 0.254039 0.825522 616 1 0.200973 0.271588 0.840842 1873 1 0.515736 0.27708 0.826648 1065 1 0.449643 0.330609 0.800042 1911 1 0.822163 0.354649 0.810706 1572 1 0.741021 0.399042 0.814608 1042 1 0.935095 0.417292 0.807649 163 1 0.225515 0.49389 0.832029 1662 1 0.422327 0.0391092 0.829485 868 1 0.562733 0.113183 0.83362 147 1 0.419438 0.0873146 0.839382 420 1 0.902449 0.140938 0.806468 1786 1 0.9776 0.124835 0.807663 1376 1 0.641739 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0.248892 0.86624 848 1 0.103493 0.32994 0.852708 1390 1 0.435039 0.309685 0.856691 1428 1 0.560592 0.310304 0.871543 725 1 0.408964 0.322707 0.816441 1893 1 0.569776 0.344629 0.830698 1915 1 0.255094 0.380565 0.842652 177 1 0.0827558 0.445849 0.836606 2037 1 0.518626 0.056939 0.850461 1922 1 0.529236 0.0669921 0.864972 256 1 0.256333 0.184402 0.836737 2030 1 0.49532 0.181231 0.874822 1076 1 0.118264 0.244173 0.872561 180 1 0.748782 0.269981 0.841088 965 1 0.0970003 0.342328 0.857906 141 1 0.138094 0.301279 0.889963 1641 1 0.270479 0.379806 0.862927 277 1 0.912589 0.405926 0.859259 1632 1 0.0819379 0.480524 0.837595 925 1 0.143448 0.436917 0.883739 1850 1 0.582647 0.459206 0.842853 491 1 0.214367 0.481353 0.828525 1544 1 0.876591 0.0804047 0.840635 1239 1 0.514443 0.112801 0.912219 1358 1 0.637773 0.12599 0.879667 1601 1 0.537313 0.13349 0.904618 1691 1 0.815412 0.134084 0.870753 240 1 0.110993 0.150374 0.898083 894 1 0.745146 0.234784 0.868689 1277 1 0.370295 0.38213 0.846568 1200 1 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0.273796 671 1 0.0399453 0.958927 0.274406 1059 1 0.462833 0.945765 0.293955 1600 1 0.921363 0.506029 0.322588 665 1 0.923961 0.512723 0.28983 1395 1 0.290661 0.547984 0.320218 1781 1 0.384856 0.555877 0.296086 167 1 0.262119 0.607152 0.267136 509 1 0.56177 0.580855 0.286716 890 1 0.65321 0.674967 0.324931 332 1 0.0675678 0.700986 0.288893 1147 1 0.0442338 0.719175 0.280259 322 1 0.340053 0.738134 0.314197 459 1 0.625642 0.759689 0.272544 783 1 0.622471 0.801308 0.299863 1788 1 0.071 0.852977 0.324255 1441 1 0.263199 0.816607 0.310343 1192 1 0.311982 0.8569 0.348847 1559 1 0.710701 0.87255 0.34784 1766 1 0.893742 0.888089 0.30197 1495 1 0.019519 0.872633 0.300227 1602 1 0.353208 0.874433 0.338252 792 1 0.00362256 0.903666 0.307591 294 1 0.401655 0.906993 0.289618 567 1 0.66226 0.906971 0.319498 1373 1 0.933946 0.921279 0.289546 1804 1 0.607577 0.964622 0.311286 1866 1 0.66442 0.959055 0.294702 305 1 0.861383 0.965689 0.297566 589 1 0.427226 0.998441 0.337795 776 1 0.889661 0.775262 0.489131 1232 1 0.926949 0.556492 0.322414 234 1 0.717168 0.55202 0.348158 1261 1 0.565623 0.580797 0.354667 1920 1 0.393715 0.642852 0.326937 1194 1 0.565125 0.705077 0.324743 1106 1 0.869628 0.708573 0.298586 718 1 0.0308166 0.742943 0.318214 636 1 0.67067 0.801587 0.325424 1473 1 0.998926 0.852987 0.291648 1851 1 0.188717 0.869167 0.329257 1275 1 0.0205024 0.892945 0.336084 824 1 0.26205 0.878074 0.323588 1472 1 0.772917 0.949855 0.329781 1757 1 0.44625 0.514686 0.350387 578 1 0.130682 0.548709 0.346631 210 1 0.0886434 0.589057 0.329185 793 1 0.931304 0.579122 0.330254 243 1 0.517347 0.620522 0.334883 1748 1 0.941797 0.623332 0.346981 72 1 0.890841 0.714602 0.307172 957 1 0.242452 0.757625 0.359474 2020 1 0.512413 0.776934 0.360839 1440 1 0.878534 0.749363 0.33744 1939 1 0.153372 0.767284 0.347403 1494 1 0.442009 0.803712 0.320499 2029 1 0.730489 0.813521 0.335667 1174 1 0.716692 0.842041 0.336362 741 1 0.65997 0.876649 0.354083 42 1 0.541623 0.871231 0.324006 1876 1 0.698501 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0.776808 0.353744 1546 1 0.495102 0.776564 0.402562 1708 1 0.925671 0.789559 0.382568 867 1 0.873518 0.805573 0.418606 1348 1 0.771032 0.817814 0.398149 446 1 0.59102 0.880651 0.370757 1950 1 0.121122 0.985982 0.36202 1868 1 0.629184 0.96547 0.370251 333 1 0.64292 0.987976 0.370188 449 1 0.409551 0.899242 0.0106176 1117 1 0.074601 0.517165 0.351491 1371 1 0.544813 0.508126 0.374009 206 1 0.340518 0.568781 0.406082 5 1 0.415928 0.574851 0.382357 1519 1 0.280933 0.635631 0.373255 1062 1 0.134312 0.725137 0.425183 1423 1 0.267904 0.72678 0.373587 148 1 0.232157 0.764859 0.391319 1366 1 0.991255 0.753384 0.405978 1064 1 0.2416 0.804488 0.374524 242 1 0.182142 0.762006 0.42247 1280 1 0.219943 0.793531 0.407963 995 1 0.31845 0.852142 0.41535 363 1 0.640596 0.806107 0.406485 1394 1 0.843091 0.84045 0.39645 1761 1 0.676072 0.909016 0.381985 470 1 0.571287 0.921838 0.402115 1791 1 0.960804 0.949208 0.436181 1974 1 0.299602 0.927253 0.387206 2005 1 0.282742 0.507483 0.469948 1596 1 0.272688 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0.785194 0.451452 806 1 0.257368 0.797647 0.445055 17 1 0.327063 0.770651 0.442247 833 1 0.872857 0.845194 0.423676 1875 1 0.514541 0.863937 0.440614 922 1 0.514776 0.842944 0.413831 1938 1 0.893053 0.870051 0.456174 394 1 0.557724 0.854635 0.42868 537 1 0.691701 0.858388 0.448446 1253 1 0.763106 0.952905 0.4456 239 1 0.369746 0.975972 0.422988 1897 1 0.0814029 0.531267 0.464501 1511 1 0.916149 0.513274 0.448908 1271 1 0.01336 0.589074 0.439569 963 1 0.063222 0.644938 0.465502 513 1 0.965082 0.643152 0.450403 1426 1 0.499288 0.651194 0.472679 972 1 0.978996 0.700562 0.422495 1297 1 0.350045 0.746983 0.477678 1351 1 0.00527385 0.742038 0.472584 1425 1 0.257877 0.779303 0.429799 1450 1 0.383729 0.857609 0.417271 195 1 0.260793 0.906949 0.461202 342 1 0.00603183 0.931402 0.445814 483 1 0.134869 0.901524 0.459861 1312 1 0.52485 0.919464 0.415769 2035 1 0.61224 0.945077 0.461797 1739 1 0.146036 0.992652 0.454279 1047 1 0.604285 0.506079 0.035413 1934 1 0.611288 0.514921 0.450531 1715 1 0.811385 0.576865 0.458779 640 1 0.0279007 0.603593 0.461057 576 1 0.745893 0.560308 0.452344 1391 1 0.944821 0.63053 0.448374 1859 1 0.020558 0.610934 0.464451 1474 1 0.650565 0.628842 0.440896 1989 1 0.108161 0.669899 0.453861 1627 1 0.154393 0.668032 0.46924 1814 1 0.218869 0.64472 0.470085 1012 1 0.684822 0.661489 0.473912 522 1 0.107162 0.681225 0.468996 1477 1 0.535899 0.674242 0.480478 1656 1 0.903433 0.728669 0.466167 1550 1 0.986173 0.73983 0.444041 1687 1 0.473728 0.791272 0.437769 1396 1 0.86021 0.747772 0.456472 175 1 0.0703021 0.846168 0.440136 789 1 0.905705 0.867047 0.480604 1597 1 0.501486 0.871116 0.474395 1664 1 0.549341 0.868445 0.48515 1583 1 0.288333 0.90582 0.490834 1636 1 0.0446155 0.502262 0.220835 395 1 0.387808 0.963727 0.436439 1057 1 0.396454 0.932048 0.490374 905 1 0.805433 0.896615 0.458902 1007 1 0.868536 0.956304 0.488509 1888 1 0.292827 0.976001 0.466979 1325 1 0.543943 0.98692 0.474783 1503 1 0.0557255 0.503139 0.492917 1738 1 0.365454 0.516631 0.469942 384 1 0.998289 0.995158 0.0537933 134 1 0.220524 0.594482 0.453501 1315 1 0.269911 0.69623 0.480459 985 1 0.395618 0.563643 0.0132871 266 1 0.816683 0.779179 0.479463 355 1 0.661254 0.765134 0.473253 203 1 0.109152 0.799931 0.491917 1295 1 0.484874 0.917712 0.486967 1464 1 0.306195 0.828369 0.495682 1407 1 0.755258 0.827836 0.497953 193 1 0.0469059 0.748542 0.48453 37 1 0.733875 0.856254 0.486295 1017 1 0.998018 0.509852 0.220657 1541 1 0.419523 0.975838 0.487786 1831 1 0.740247 0.746922 0.00757658 1003 1 0.33139 0.500704 0.0740307 546 1 0.504341 0.513925 0.928028 2038 1 0.482206 0.536058 0.512858 1006 1 0.921356 0.524998 0.51924 680 1 0.182121 0.993975 0.941974 297 1 0.741078 0.658172 0.546599 1942 1 0.231739 0.688534 0.5163 1177 1 0.0639559 0.71327 0.505248 153 1 0.904242 0.520083 0.730631 539 1 0.795861 0.514854 0.518631 551 1 0.123604 0.803074 0.502381 770 1 0.544499 0.982998 0.635264 1709 1 0.632929 0.86254 0.515966 1861 1 0.0149029 0.867733 0.540317 670 1 0.179397 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0.772775 0.541692 854 1 0.95638 0.774848 0.574535 1098 1 0.250384 0.808586 0.518754 159 1 0.459623 0.796638 0.56621 597 1 0.318539 0.839196 0.549899 1655 1 0.651521 0.808286 0.554928 1157 1 0.406755 0.84704 0.564348 809 1 0.370683 0.870191 0.532297 1879 1 0.970848 0.900805 0.534871 1792 1 0.0326662 0.902416 0.548245 1668 1 0.3602 0.935603 0.579857 1508 1 0.91135 0.92281 0.565752 1860 1 0.100691 0.962042 0.875162 1158 1 0.556866 0.531637 0.554099 99 1 0.870158 0.511376 0.570261 293 1 0.672717 0.529448 0.575603 1941 1 0.863733 0.545419 0.542668 1892 1 0.571208 0.989623 0.621211 1798 1 0.0249427 0.551565 0.571229 496 1 0.178448 0.582072 0.558293 1283 1 0.33443 0.677641 0.579304 1173 1 0.0307581 0.733852 0.591415 1045 1 0.669752 0.704295 0.565955 1765 1 0.690751 0.749376 0.586596 786 1 0.367263 0.778727 0.579561 1908 1 0.719979 0.802924 0.524509 335 1 0.751805 0.80785 0.582111 298 1 0.853165 0.814574 0.534397 1973 1 0.928658 0.878321 0.555206 1809 1 0.642339 0.93287 0.588271 334 1 0.170567 0.91866 0.533719 1643 1 0.361871 0.844513 0.993405 1427 1 0.200655 0.735646 0.512903 1979 1 0.52631 0.526376 0.570838 419 1 0.453835 0.534289 0.551389 967 1 0.735496 0.516935 0.550848 1817 1 0.591637 0.541928 0.584057 125 1 0.770963 0.54738 0.595512 1510 1 0.996042 0.56903 0.562687 413 1 0.645025 0.612555 0.56115 530 1 0.768616 0.600023 0.597242 1540 1 0.734529 0.614318 0.569801 593 1 0.853967 0.637664 0.608846 202 1 0.228466 0.711707 0.581306 178 1 0.327034 0.793483 0.604057 1094 1 0.317772 0.804188 0.607595 1424 1 0.66045 0.797496 0.577258 2004 1 0.82615 0.827655 0.586792 1457 1 0.0820394 0.825463 0.596794 112 1 0.82877 0.837974 0.577484 1304 1 0.0565984 0.910654 0.592828 140 1 0.139791 0.905342 0.572994 785 1 0.49208 0.954054 0.582187 660 1 0.549796 0.974268 0.574508 108 1 0.29213 0.512879 0.60846 1566 1 0.338276 0.607983 0.629253 1321 1 0.159311 0.663928 0.598997 627 1 0.12124 0.666403 0.572419 598 1 0.907114 0.754378 0.602767 781 1 0.48106 0.759249 0.602677 220 1 0.107103 0.7555 0.626888 1826 1 0.348283 0.754357 0.618765 599 1 0.776207 0.815897 0.578744 664 1 0.977656 0.897258 0.591883 1013 1 0.583278 0.933318 0.62855 1711 1 0.486364 0.956208 0.597086 1562 1 0.36976 0.839145 0.995532 1284 1 0.782292 0.521631 0.621849 324 1 0.111249 0.562624 0.64005 1218 1 0.200245 0.541638 0.610203 1741 1 0.432408 0.914901 0.952834 819 1 0.122956 0.535527 0.60362 1035 1 0.442914 0.554082 0.636839 778 1 0.421838 0.571489 0.599547 916 1 0.624479 0.552885 0.602733 971 1 0.823834 0.588384 0.610954 693 1 0.852048 0.5607 0.589091 1016 1 0.864107 0.641168 0.636298 931 1 0.980284 0.636934 0.607532 356 1 0.963086 0.621263 0.612581 13 1 0.63064 0.617555 0.644518 1688 1 0.763621 0.658744 0.586127 1574 1 0.690156 0.715297 0.590164 1971 1 0.0723076 0.780806 0.631024 1513 1 0.14191 0.810055 0.623062 1614 1 0.201759 0.792042 0.61682 1992 1 0.74555 0.811852 0.656744 766 1 0.0106424 0.812858 0.628166 194 1 0.410839 0.879379 0.622045 1924 1 0.65191 0.951203 0.604313 232 1 0.129122 0.955648 0.614879 1552 1 0.546162 0.958632 0.638023 130 1 0.207097 0.549081 0.614867 735 1 0.327815 0.533389 0.639055 1251 1 0.32576 0.514356 0.65585 1828 1 0.122724 0.611138 0.641536 411 1 0.276809 0.585267 0.633237 1176 1 0.49302 0.621996 0.626138 1291 1 0.700937 0.612743 0.680321 1138 1 0.452636 0.656779 0.644544 1880 1 0.787212 0.666543 0.655259 24 1 0.545275 0.694485 0.659114 1565 1 0.668129 0.691939 0.622644 1716 1 0.878754 0.762023 0.612042 1353 1 0.305118 0.77689 0.665172 469 1 0.650574 0.725226 0.650529 4 1 0.443398 0.802374 0.618095 1309 1 0.388638 0.761106 0.672686 1184 1 0.414443 0.79751 0.644929 675 1 0.313025 0.844235 0.635411 608 1 0.24045 0.831714 0.631282 1319 1 0.165885 0.894042 0.602765 2002 1 0.75113 0.949498 0.64197 1955 1 0.0631833 0.983372 0.644304 385 1 0.16485 0.981498 0.628305 271 1 0.219692 0.990621 0.607983 1914 1 0.327529 0.952578 0.671834 1727 1 0.169628 0.636882 0.987014 1571 1 0.552472 0.560526 0.657938 723 1 0.699513 0.582714 0.650864 649 1 0.298069 0.587056 0.680678 307 1 0.301879 0.614251 0.646293 317 1 0.74213 0.630446 0.668903 850 1 0.428376 0.664105 0.632554 780 1 0.53269 0.653291 0.62788 966 1 0.883734 0.715802 0.654792 1952 1 0.637178 0.775799 0.671837 1987 1 0.926948 0.793781 0.634582 1385 1 0.173032 0.818731 0.648581 472 1 0.836531 0.847424 0.640174 774 1 0.207234 0.851848 0.681801 728 1 0.321469 0.897891 0.662914 705 1 0.343865 0.900485 0.692929 1629 1 0.0112315 0.919941 0.665394 255 1 0.769353 0.941693 0.628728 2021 1 0.332792 0.579126 0.656341 523 1 0.34752 0.619782 0.660512 1997 1 0.905262 0.637663 0.698255 1680 1 0.24966 0.659986 0.706835 230 1 0.347457 0.73627 0.690947 421 1 0.88204 0.764871 0.677489 477 1 0.668176 0.821116 0.657321 853 1 0.556467 0.899006 0.67076 947 1 0.794426 0.852087 0.669821 1024 1 0.37974 0.918092 0.673471 58 1 0.661459 0.931324 0.678219 996 1 0.801598 0.877193 0.674864 771 1 0.0349701 0.947897 0.676717 78 1 0.210602 0.500021 0.654555 1623 1 0.311819 0.532061 0.693584 811 1 0.578361 0.546592 0.692498 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[ "[email protected]" ]

[email protected]

cffe0a59e77bcf26414b072c0e182159fac32345

82948269c85dd0cce4f1337f75b28b5edf6d81ef

/eval.py

6b58ef22874feb9bea385f8a78b0cae4bdc90d21

[]

no_license

zhangwenhao123/Underwater-Color-Correction

291c5f7131855832d58ddd6a02fd0a334c3f13d3

b25bd697bfd206afb9b3d1ad58d4ff4dfc850b2e

refs/heads/master

2021-05-11T03:43:07.330895

2018-01-17T22:48:46

117,921,125

0

null

2018-01-18T02:33:36

null

UTF-8

Python

false

4,072

py

''' Evaluation File ''' import cPickle as pickle import tensorflow as tf from scipy import misc from tqdm import tqdm import numpy as np import argparse import random import ntpath import sys import os import time import time import glob import cPickle as pickle from tqdm import tqdm sys.path.insert(0, 'ops/') sys.path.insert(0, 'nets/') from tf_ops import * import data_ops if __name__ == '__main__': if len(sys.argv) < 2: print 'You must provide an info.pkl file' exit() pkl_file = open(sys.argv[1], 'rb') a = pickle.load(pkl_file) LEARNING_RATE = a['LEARNING_RATE'] LOSS_METHOD = a['LOSS_METHOD'] BATCH_SIZE = a['BATCH_SIZE'] L1_WEIGHT = a['L1_WEIGHT'] IG_WEIGHT = a['IG_WEIGHT'] NETWORK = a['NETWORK'] EPOCHS = a['EPOCHS'] DATA = a['DATA'] EXPERIMENT_DIR = 'checkpoints/LOSS_METHOD_'+LOSS_METHOD\ +'/NETWORK_'+NETWORK\ +'/L1_WEIGHT_'+str(L1_WEIGHT)\ +'/IG_WEIGHT_'+str(IG_WEIGHT)\ +'/DATA_'+DATA+'/'\ IMAGES_DIR = EXPERIMENT_DIR+'test_images/' print print 'Creating',IMAGES_DIR try: os.makedirs(IMAGES_DIR) except: pass print print 'LEARNING_RATE: ',LEARNING_RATE print 'LOSS_METHOD: ',LOSS_METHOD print 'BATCH_SIZE: ',BATCH_SIZE print 'L1_WEIGHT: ',L1_WEIGHT print 'IG_WEIGHT: ',IG_WEIGHT print 'NETWORK: ',NETWORK print 'EPOCHS: ',EPOCHS print 'DATA: ',DATA print if NETWORK == 'pix2pix': from pix2pix import * if NETWORK == 'resnet': from resnet import * # global step that is saved with a model to keep track of how many steps/epochs global_step = tf.Variable(0, name='global_step', trainable=False) # underwater image image_u = tf.placeholder(tf.float32, shape=(1, 256, 256, 3), name='image_u') # generated corrected colors gen_image = netG(image_u, LOSS_METHOD) saver = tf.train.Saver(max_to_keep=1) init = tf.group(tf.local_variables_initializer(), tf.global_variables_initializer()) sess = tf.Session() sess.run(init) ckpt = tf.train.get_checkpoint_state(EXPERIMENT_DIR) if ckpt and ckpt.model_checkpoint_path: print "Restoring previous model..." try: saver.restore(sess, ckpt.model_checkpoint_path) print "Model restored" except: print "Could not restore model" pass step = int(sess.run(global_step)) # testing paths ''' exts = ['*.jpg', '*.jpeg', '*.JPEG', '*.png'] test_paths = [] for ex in exts: test_paths.extend(glob.glob('datasets/'+DATA+'/test/'+ex)) test_paths = np.asarray(test_paths) ''' #test_paths = sorted(np.asarray(glob.glob('/mnt/data2/images/underwater/youtube/diving1/*.jpg'))) test_paths = sorted(np.asarray(glob.glob('/mnt/data1/videos/barbados/2018/images/*.png'))) IMAGES_DIR = '/mnt/data1/videos/barbados/2018/out_images/' #random.shuffle(test_paths) num_test = len(test_paths) print 'num test:',num_test print 'IMAGES_DIR:',IMAGES_DIR c = 0 times = [] for img_path in tqdm(test_paths): img_name = ntpath.basename(img_path) img_name = img_name.split('.')[0] batch_images = np.empty((1, 256, 256, 3), dtype=np.float32) a_img = misc.imread(img_path).astype('float32') a_img = misc.imresize(a_img, (256, 256, 3)) a_img = data_ops.preprocess(a_img) batch_images[0, ...] = a_img s = time.time() gen_images = np.asarray(sess.run(gen_image, feed_dict={image_u:batch_images})) tot = time.time()-s times.append(tot) for gen, real in zip(gen_images, batch_images): #misc.imsave(IMAGES_DIR+str(step)+'_'+str(c)+'_real.png', real) #misc.imsave(IMAGES_DIR+str(step)+'_'+str(c)+'_gen.png', gen) misc.imsave(IMAGES_DIR+img_name+'_real.png', real) misc.imsave(IMAGES_DIR+img_name+'_gen.png', gen) c += 1 print print 'average time:',np.mean(np.asarray(times)) print

[ "[email protected]" ]

[email protected]

327694995f36b39033eb39821a28e85f2af31c2a

e7b7cc34f77c71e61aa0fa05bcc62f54fc2fc0e1

/BitManipulation/test_q136_single_number.py

42836c696458ba313f72ead4768f330aefb9e302

[]

no_license

sevenhe716/LeetCode

41d2ef18f5cb317858c9b69d00bcccb743cbdf48

4a1747b6497305f3821612d9c358a6795b1690da

refs/heads/master

2020-03-16T16:12:27.461172

2019-04-22T13:27:54

130,221,784

0

null

UTF-8

Python

false

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import unittest from BitManipulation.q136_single_number import Solution class TestSingleNumber(unittest.TestCase): """Test q136_single_number.py""" def test_single_number(self): s = Solution() self.assertEqual(1, s.singleNumber([2, 2, 1])) self.assertEqual(4, s.singleNumber([4, 1, 2, 1, 2])) if __name__ == '__main__': unittest.main()

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[email protected]

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# third party import pytest import requests # syft absolute import syft as sy NETWORK_PORT = 9081 NETWORK_PUBLIC_HOST = f"docker-host:{NETWORK_PORT}" DOMAIN1_PORT = 9082 DOMAIN2_PORT = 9083 NETWORK_VPN_IP = "100.64.0.1" DOMAIN1_VPN_IP = "100.64.0.2" DOMAIN2_VPN_IP = "100.64.0.3" TEST_ROOT_EMAIL = "[email protected]" TEST_ROOT_PASS = "changethis" def join_to_network_python( email: str, password: str, port: int, network_host: str ) -> None: root_client = sy.login(email=email, password=password, port=port) # test Syft API root_client.join_network(host_or_ip=network_host) response = root_client.vpn_status() return response def join_to_network_rest( email: str, password: str, port: int, network_host: str ) -> None: url = f"http://localhost:{port}/api/v1/login" auth_response = requests.post(url, json={"email": email, "password": password}) auth = auth_response.json() # test HTTP API url = f"http://localhost:{port}/api/v1/vpn/join/{network_host}" headers = {"Authorization": f"Bearer {auth['access_token']}"} response = requests.post(url, headers=headers) result = response.json() return result def run_network_tests(port: int, hostname: str, vpn_ip: str) -> None: response = join_to_network_python( email=TEST_ROOT_EMAIL, password=TEST_ROOT_PASS, port=port, network_host=NETWORK_PUBLIC_HOST, ) assert response["status"] == "ok" host = response["host"] assert host["ip"] == vpn_ip assert host["hostname"] == hostname assert host["os"] == "linux" response = join_to_network_rest( email=TEST_ROOT_EMAIL, password=TEST_ROOT_PASS, port=port, network_host=NETWORK_PUBLIC_HOST, ) assert response["status"] == "ok" @pytest.mark.network def test_connect_network_to_network() -> None: run_network_tests( port=NETWORK_PORT, hostname="test_network_1", vpn_ip=NETWORK_VPN_IP ) @pytest.mark.network def test_connect_domain1_to_network() -> None: run_network_tests( port=DOMAIN1_PORT, hostname="test_domain_1", vpn_ip=DOMAIN1_VPN_IP ) @pytest.mark.network def test_connect_domain2_to_network() -> None: run_network_tests( port=DOMAIN2_PORT, hostname="test_domain_2", vpn_ip=DOMAIN2_VPN_IP )

[ "[email protected]" ]

[email protected]

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#calss header class _TRIPTYCH(): def __init__(self,): self.name = "TRIPTYCH" self.definitions = [u'a piece of art made of three paintings connected to each other in a way that allows the two outer ones to fold in towards the larger central one: '] self.parents = [] self.childen = [] self.properties = [] self.jsondata = {} self.specie = 'nouns' def run(self, obj1 = [], obj2 = []): return self.jsondata

[ "[email protected]" ]

[email protected]

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/travelport/models/universal_record_import_service_port_type_service_output.py

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tefra/xsdata-samples

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from __future__ import annotations from dataclasses import dataclass, field from travelport.models.error_info_1 import ErrorInfo1 from travelport.models.universal_record_import_rsp import UniversalRecordImportRsp __NAMESPACE__ = "http://www.travelport.com/service/air_v52_0" @dataclass class UniversalRecordImportServicePortTypeServiceOutput: class Meta: name = "Envelope" namespace = "http://schemas.xmlsoap.org/soap/envelope/" body: None | UniversalRecordImportServicePortTypeServiceOutput.Body = field( default=None, metadata={ "name": "Body", "type": "Element", } ) @dataclass class Body: universal_record_import_rsp: None | UniversalRecordImportRsp = field( default=None, metadata={ "name": "UniversalRecordImportRsp", "type": "Element", "namespace": "http://www.travelport.com/schema/universal_v52_0", } ) fault: None | UniversalRecordImportServicePortTypeServiceOutput.Body.Fault = field( default=None, metadata={ "name": "Fault", "type": "Element", } ) @dataclass class Fault: faultcode: None | str = field( default=None, metadata={ "type": "Element", "namespace": "", } ) faultstring: None | str = field( default=None, metadata={ "type": "Element", "namespace": "", } ) faultactor: None | str = field( default=None, metadata={ "type": "Element", "namespace": "", } ) detail: None | UniversalRecordImportServicePortTypeServiceOutput.Body.Fault.Detail = field( default=None, metadata={ "type": "Element", "namespace": "", } ) @dataclass class Detail: error_info: None | ErrorInfo1 = field( default=None, metadata={ "name": "ErrorInfo", "type": "Element", "namespace": "http://www.travelport.com/schema/common_v52_0", } )

[ "[email protected]" ]

[email protected]

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/study/day3/使用list()函数将range()函数输出的值输出为列表.py

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#使用list()函数将range()函数输出的值输出为列表 #思路 #range()输出一组数字 #把range()函数输出的值作为参数传输值list()函数 num=list(range(1,9)) print (num) #结果 ''' [1, 2, 3, 4, 5, 6, 7, 8] '''

[ "[email protected]" ]

[email protected]

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/Users/jared/anaconda3/lib/python3.6/_weakrefset.py

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[email protected]

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/app/events/regions.py

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from app.utilities.data import Prefab region_types = ['normal', 'status', 'event', 'formation'] class Region(Prefab): def __init__(self, nid): self.nid = nid self.region_type = 'normal' self.position = None self.size = [1, 1] self.sub_nid = None self.condition = 'True' self.only_once = False @property def area(self): return self.size[0] * self.size[1] @property def center(self) -> tuple: if self.position: x = int(self.position[0] + self.size[0] // 2) y = int(self.position[1] + self.size[1] // 2) return x, y else: return None def contains(self, pos: tuple) -> bool: x, y = pos if self.position: return self.position[0] <= x < self.position[0] + self.size[0] and \ self.position[1] <= y < self.position[1] + self.size[1] else: return False def fuzzy_contains(self, pos: tuple) -> bool: x, y = pos fuzz = 0.4 if self.position: return self.position[0] - fuzz <= x < self.position[0] + self.size[0] + fuzz and \ self.position[1] - fuzz <= y < self.position[1] + self.size[1] + fuzz else: return False def get_all_positions(self): if self.position: positions = [] for i in range(self.position[0], self.position[0] + self.size[0]): for j in range(self.position[1], self.position[1] + self.size[1]): positions.append((i, j)) return positions else: return [] @classmethod def default(cls): return cls('None')

[ "[email protected]" ]

[email protected]

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import pymysql # 连接数据库 db = pymysql.connect(host='127.0.0.1', port=3306, user='root', password='12345678', database='country1', charset='utf8') # 获取游标 cur = db.cursor() # 插入数据 data_list = [] for x in range(200000): name = 'Py87_%s' % x data_list.append(name) # 插入语句 # 一个包最大 allowed_packet is 10586 # max_stmt_length = 1024000 ins sql语句的字符串长度 ins = 'insert into students(name) values(%s)' # 批量插入数据 # 每一次插入都是一次磁盘网络IO 提高单位频率上的效率 cur.executemany(ins, data_list) # 提交 db.commit() # 关闭 cur.close() db.close()

[ "[email protected]" ]

[email protected]

c220c97fed107071513fbfb21f2e2b337a46b158

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/cifar10_cnn.py

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''' CIFAR-10 example from https://github.com/fchollet/keras/blob/master/examples/cifar10_cnn.py Now with weight normalization. Lines 64 and 69 contain the changes w.r.t. original. ''' from __future__ import print_function from keras.datasets import cifar10 from keras.preprocessing.image import ImageDataGenerator from keras.models import Sequential from keras.layers import Dense, Dropout, Activation, Flatten from keras.layers import Convolution2D, MaxPooling2D from keras.utils import np_utils from keras import optimizers import util as u import sys import numpy as np if len(sys.argv)<2: assert False if sys.argv[1]=='sgd': prefix='keras_sgd' optimizer='sgd' elif sys.argv[1]=='sgd_wn': prefix='keras_sgd_wn' optimizer='sgd_wn' elif sys.argv[1]=='adam': prefix='keras_adam' optimizer='adam' elif sys.argv[1]=='adam_wn': prefix='keras_adam_wn' optimizer='adam_wn' else: assert False batch_size = 5000 nb_classes = 10 nb_epoch = 10 data_augmentation = True # input image dimensions img_rows, img_cols = 32, 32 # the CIFAR10 images are RGB img_channels = 3 # the data, shuffled and split between train and test sets (X_train, y_train), (X_test, y_test) = cifar10.load_data() print('X_train shape:', X_train.shape) print(X_train.shape[0], 'train samples') print(X_test.shape[0], 'test samples') X_train = X_train.astype('float32') X_test = X_test.astype('float32') X_train /= 255 X_test /= 255 # convert class vectors to binary class matrices Y_train = np_utils.to_categorical(y_train, nb_classes) Y_test = np_utils.to_categorical(y_test, nb_classes) model = Sequential() model.add(Convolution2D(32, 3, 3, border_mode='same', input_shape=X_train.shape[1:])) model.add(Activation('relu')) model.add(Convolution2D(32, 3, 3)) model.add(Activation('relu')) model.add(MaxPooling2D(pool_size=(2, 2))) model.add(Dropout(0.25)) model.add(Convolution2D(64, 3, 3, border_mode='same')) model.add(Activation('relu')) model.add(Convolution2D(64, 3, 3)) model.add(Activation('relu')) model.add(MaxPooling2D(pool_size=(2, 2))) model.add(Dropout(0.25)) model.add(Flatten()) model.add(Dense(512)) model.add(Activation('relu')) model.add(Dropout(0.5)) model.add(Dense(nb_classes)) model.add(Activation('softmax')) # let's train the model using SGD + momentum (how original). EDIT: now with weight normalization, so slightly more original ;-) from weightnorm import SGDWithWeightnorm from weightnorm import AdamWithWeightnorm sgd_wn = SGDWithWeightnorm(lr=0.01, decay=1e-6, momentum=0.9, nesterov=True) sgd = optimizers.SGD(lr=0.01, decay=1e-6, momentum=0.9, nesterov=True) adam = optimizers.Adam() adam_wn = AdamWithWeightnorm() if optimizer == 'sgd': optimizer=sgd elif optimizer == 'sgd_wn': optimizer=sgd_wn elif optimizer == 'adam': optimizer=adam elif optimizer == 'adam_wn': optimizer=adam_wn else: assert False model.compile(loss='categorical_crossentropy',optimizer=optimizer, metrics=['accuracy']) # data based initialization of parameters from weightnorm import data_based_init data_based_init(model, X_train[:100]) if not data_augmentation: print('Not using data augmentation.') model.fit(X_train, Y_train, batch_size=batch_size, nb_epoch=nb_epoch, validation_data=(X_test, Y_test), shuffle=True) else: print('Using real-time data augmentation.') # this will do preprocessing and realtime data augmentation datagen = ImageDataGenerator( featurewise_center=False, # set input mean to 0 over the dataset samplewise_center=False, # set each sample mean to 0 featurewise_std_normalization=False, # divide inputs by std of the dataset samplewise_std_normalization=False, # divide each input by its std zca_whitening=False, # apply ZCA whitening rotation_range=0, # randomly rotate images in the range (degrees, 0 to 180) width_shift_range=0.1, # randomly shift images horizontally (fraction of total width) height_shift_range=0.1, # randomly shift images vertically (fraction of total height) horizontal_flip=True, # randomly flip images vertical_flip=False) # randomly flip images # compute quantities required for featurewise normalization # (std, mean, and principal components if ZCA whitening is applied) datagen.fit(X_train) # fit the model on the batches generated by datagen.flow() result = model.fit_generator(datagen.flow(X_train, Y_train, batch_size=batch_size), samples_per_epoch=X_train.shape[0], nb_epoch=nb_epoch, validation_data=(X_test, Y_test)) acc_hist = np.asarray(result.history['acc']) u.dump(acc_hist, "%s_losses.csv"%(prefix,))

[ "[email protected]" ]

[email protected]

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import time def io_task(): time.sleep(1) def main(): start_time=time.time() for i in range(5): io_task() end_time=time.time() print('it takes: {:.2f}s'.format(end_time-start_time)) if __name__=='__main__': main()

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[email protected]

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# Lint as: python3 # Copyright 2020 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== """Module for `Client` and relevant cluster-worker related library. This is currently under development and the API is subject to change. """ from __future__ import absolute_import from __future__ import division from __future__ import print_function import contextlib import enum import functools import os import re import sys import threading import weakref from six.moves import queue from tensorflow.python.data.ops import iterator_ops from tensorflow.python.distribute import input_lib from tensorflow.python.distribute import parameter_server_strategy_v2 from tensorflow.python.distribute.client import metric_utils from tensorflow.python.eager import cancellation from tensorflow.python.eager import context from tensorflow.python.eager import def_function from tensorflow.python.eager import executor from tensorflow.python.eager import function as tf_function from tensorflow.python.framework import errors from tensorflow.python.framework import func_graph from tensorflow.python.framework import ops from tensorflow.python.ops import resource_variable_ops from tensorflow.python.ops import variable_scope from tensorflow.python.platform import tf_logging as logging from tensorflow.python.util import nest # Maximum time for failed worker to come back is 1 hour _WORKER_MAXIMUM_RECOVERY_SEC = 3600 # Maximum size for queued closures, "infinite" if set to 0. # When the maximum queue size is reached, further schedule calls will become # blocking until some previously queued closures are executed on workers. # Note that using an "infinite" queue size can take a non-trivial portion of # memory, and even lead to client OOM. Modify the size to a smaller value for # client with constrained memory resource (only recommended for advanced users). # Also used in unit tests to ensure the correctness when the queue is full. _CLOSURE_QUEUE_MAX_SIZE = 256 * 1024 # RPC error message from PS _RPC_ERROR_FROM_PS = "GRPC error information from remote target /job:ps" # InvalidArgumentError (unknown device) will not have "GRPC error..." string. _JOB_WORKER_STRING_IDENTIFIER = "/job:worker" class _RemoteValueStatus(enum.Enum): """The status of a `RemoteValue` object. A `RemoteValue` object can have three states: 1) not ready: no value, no non-retryable error and not aborted; 2) aborted: i.e. the execution of function was aborted because of task failure, but can be retried; 3) ready: i.e. has value or has non-tryable error; The initial state of a `RemoteValue` is "not ready". When its corresponding closure has been executed at least once, it will become aborted or ready. The state transitions are: 1) not ready -> 2) aborted: when the corresponding closure is aborted due to worker failure, and the worker failure is not immediately handled. 1) not ready -> 3) ready: when the corresponding closure has been executed successfully. 2) aborted -> 3) ready: when the `RemoteValue` is rebuilt by rerunning the corresponding closure and the closure has been executed successfully. 3) ready -> 2) aborted: when the corresponding closure had been executed successfully but later the corresponding remote worker failed. This is currently only implemented for resource `RemoteValue` like iterators. """ NOT_READY = "NOT_READY" ABORTED = "ABORTED" READY = "READY" class RemoteValue(object): """An asynchronously available value of a remotely executed function. `RemoteValue` class is used as the return value of `Client.schedule()` where the underlying concrete value comes at a later time once the function has been remotely executed. `RemoteValue` can be used as an input to a subsequent function scheduled with `Client.schedule()`. Note: this class is not thread-safe. """ def __init__(self, closure, type_spec): self._closure = closure # The type spec for this `RemoteValue` which is used to trace functions that # take this `RemoteValue` as input. self._type_spec = func_graph.convert_structure_to_signature(type_spec) self._value = None self._error = None self._status_available_event = threading.Event() self._status = _RemoteValueStatus.NOT_READY def _set_aborted(self): self._status = _RemoteValueStatus.ABORTED self._value = None self._error = None # Wake up any waiting thread and clear the event. self._status_available_event.set() def _rebuild_on(self, worker): self._status_available_event.clear() # TODO(yuefengz): we may need to rebuild its inputs as well. self._closure.execute_on(worker) def _set_value(self, value): self._status = _RemoteValueStatus.READY self._value = value self._error = None self._status_available_event.set() def _set_error(self, exception): self._status = _RemoteValueStatus.READY self._value = None self._error = exception self._status_available_event.set() def _get_value(self): self._status_available_event.wait() return self._value def _get_error(self): self._status_available_event.wait() return self._error def _set_type_spec(self, type_spec): self._type_spec = func_graph.convert_structure_to_signature(type_spec) def fetch(self): """Wait for the result of RemoteValue to be ready and return the result. Returns: The remote value, as a numpy data type (if scalar) or ndarray. Raises: tf.errors.CancelledError: If the function that produces this `RemoteValue` is aborted or cancelled due to failure, and the user should handle and reschedule. """ self._status_available_event.wait() if self._status is _RemoteValueStatus.ABORTED: raise errors.CancelledError( None, None, "The corresponding function is aborted. Please reschedule the " "function.") if self._error is not None: raise self._error # pylint: disable=raising-bad-type else: if isinstance(self._value, (ops.Tensor, resource_variable_ops.BaseResourceVariable)): return self._value.numpy() else: return self._value class InputError(Exception): def __init__(self, original_exception): message = ("Input has an error, the original exception is %r, " "error message is %s." % (original_exception, str(original_exception))) super().__init__(message) def _maybe_rebuild_remote_values(worker, structure): """Attempts to return errors from `RemoteValue`s. Rebuilds them if needed.""" errors_in_structure = [] def _get_error(val): if isinstance(val, RemoteValue): if val._status is _RemoteValueStatus.ABORTED: # pylint: disable=protected-access try: with worker.failure_handler.wait_on_failure( on_recovery_fn=functools.partial(val._rebuild_on, worker), # pylint: disable=protected-access worker_device_name=worker.device_name): val._rebuild_on(worker) # pylint: disable=protected-access except Exception as e: # pylint: disable=broad-except val._set_error(e) # pylint: disable=protected-access error = val._get_error() # pylint: disable=protected-access if error: errors_in_structure.append(error) nest.map_structure(_get_error, structure) if errors_in_structure: return errors_in_structure[0] else: return None def _maybe_get_remote_value(val): """Gets the value of `val` if it is a `RemoteValue`.""" if isinstance(val, RemoteValue): error = val._get_error() # pylint: disable=protected-access if error: raise AssertionError( "RemoteValue doesn't have a value because it has errors.") else: return val._get_value() # pylint: disable=protected-access else: return val def _maybe_as_type_spec(val): if isinstance(val, RemoteValue): if val._type_spec is None: # pylint: disable=protected-access raise ValueError("Output of a scheduled function that is not " "tf.function cannot be the input of another function.") return val._type_spec # pylint: disable=protected-access else: return val class PerWorkerValues(object): """Holds a list of per worker values.""" def __init__(self, values): self._values = tuple(values) def _select_worker_slice(worker_id, structured): """Selects the worker slice of each of the items in `structured`.""" def _get(x): return x._values[worker_id] if isinstance(x, PerWorkerValues) else x # pylint: disable=protected-access return nest.map_structure(_get, structured) def _disallow_remote_value_as_input(structured): """Raises if any element of `structured` is a RemoteValue.""" def _raise_if_remote_value(x): if isinstance(x, RemoteValue): raise ValueError("RemoteValue cannot be used as an input to scheduled " "function. Please file a feature request if you need " "this feature.") nest.map_structure(_raise_if_remote_value, structured) class Closure(object): """Hold a function to be scheduled and its arguments.""" def __init__(self, function, cancellation_mgr, args=None, kwargs=None): if not callable(function): raise ValueError("Function passed to `Client.schedule` must be a " "callable object.") self._args = args or () self._kwargs = kwargs or {} _disallow_remote_value_as_input(self._args) _disallow_remote_value_as_input(self._kwargs) if isinstance(function, def_function.Function): replica_args = _select_worker_slice(0, self._args) replica_kwargs = _select_worker_slice(0, self._kwargs) # Note: no need to handle function registration failure since this kind of # failure will not raise exceptions as designed in the runtime. The client # has to rely on subsequent operations that raise to catch function # registration failure. # Record the function tracing overhead. Note that we pass in the tracing # count of the def_function.Function as a state tracker, so that metrics # will only record the time for actual function tracing (i.e., excluding # function cache lookups). with metric_utils.monitored_timer( "function_tracing", state_tracker=function._get_tracing_count): # pylint: disable=protected-access concrete_function = function.get_concrete_function( *nest.map_structure(_maybe_as_type_spec, replica_args), **nest.map_structure(_maybe_as_type_spec, replica_kwargs)) self._function = cancellation_mgr.get_cancelable_function( concrete_function) self._output_remote_values = nest.map_structure( lambda x: RemoteValue(self, x), concrete_function.structured_outputs) elif isinstance(function, tf_function.ConcreteFunction): self._function = cancellation_mgr.get_cancelable_function(function) self._output_remote_values = nest.map_structure( lambda x: RemoteValue(self, x), function.structured_outputs) else: # Regular python functions. self._function = function # TODO(yuefengz): maybe we should trace python functions if their inputs # are Python primitives, tensors and composite tensors. self._output_remote_values = RemoteValue(self, None) def _fetch_output_remote_values(self): """Temporary method used to sync the scheduler.""" # It will do nothing if there is no return value. nest.map_structure(lambda x: x.fetch(), self._output_remote_values) # pylint: disable=protected-access def _set_output_remote_values_cancelled(self): nest.map_structure( lambda x: x._set_error( # pylint: disable=protected-access,g-long-lambda errors.CancelledError( None, None, "The corresponding function is " "cancelled. Please reschedule the function.")), self._output_remote_values) # pylint: disable=protected-access def execute_on(self, worker): """Executes the closure on the given worker. Args: worker: a `Worker` object. """ replica_args = _select_worker_slice(worker.worker_index, self._args) replica_kwargs = _select_worker_slice(worker.worker_index, self._kwargs) e = ( _maybe_rebuild_remote_values(worker, replica_args) or _maybe_rebuild_remote_values(worker, replica_kwargs)) if e: if not isinstance(e, InputError): e = InputError(e) for remote_value in nest.flatten(self._output_remote_values): remote_value._set_error(e) # pylint: disable=protected-access return with ops.device(worker.device_name): with context.executor_scope(worker.executor): with metric_utils.monitored_timer("closure_execution"): output_value = self._function( *nest.map_structure(_maybe_get_remote_value, replica_args), **nest.map_structure(_maybe_get_remote_value, replica_kwargs)) for remote_value, value in zip( nest.flatten(self._output_remote_values), nest.flatten(output_value)): remote_value._set_value(value) # pylint: disable=protected-access class _CoordinatedClosureQueue(object): """Manage a queue of closures, inflight count and errors from execution. This class is thread-safe. """ def __init__(self): # `self._inflight_closure_count` only tracks the number of inflight closures # that are "in generation". Once an error occurs, error generation is # incremented and all subsequent arriving closures (from inflight) are # considered "out of generation". self._inflight_closure_count = 0 self._queue_lock = threading.Lock() # Condition indicating that all pending closures (either queued or inflight) # have been processed, failed, or cancelled. self._stop_waiting_condition = threading.Condition(self._queue_lock) # Condition indicating that an item becomes available in queue (not empty). self._closures_queued_condition = threading.Condition(self._queue_lock) # Condition indicating that a queue slot becomes available (not full). # Note that even with "infinite" queue size, there is still a "practical" # size limit for the queue depending on host memory capacity, and thus the # queue will eventually become full with a lot of enqueued closures. self._queue_free_slot_condition = threading.Condition(self._queue_lock) # Condition indicating there is no inflight closures. self._no_inflight_closure_condition = threading.Condition(self._queue_lock) # Use to cancel in-flight closures. self._cancellation_mgr = cancellation.CancellationManager() if _CLOSURE_QUEUE_MAX_SIZE <= 0: logging.warning( "In a `Client`, creating an infinite closure queue can " "consume a significant amount of memory and even lead to OOM.") self._queue = queue.Queue(maxsize=_CLOSURE_QUEUE_MAX_SIZE) self._error = None # The following is a lock to make sure when `wait` is called and before it # returns no `put` can be executed during this period. It is because `wait` # won't know what to do with newly put closures. This lock adds an cutoff # for `wait` so that closures put into the queue while waiting would not be # taken responsible by this `wait`. # # We cannot reuse the `self._queue_lock` since when `wait` waits for a # condition, the `self._queue_lock` will be released. # # We don't use a reader/writer's lock on purpose to reduce the complexity # of the code. self._put_wait_lock = threading.Lock() def _cancel_all_closures(self): """Clears the queue and sets remaining closures cancelled error. This method expects self._queue_lock to be held prior to entry. """ self._cancellation_mgr.start_cancel() while self._inflight_closure_count > 0: self._no_inflight_closure_condition.wait() while True: try: closure = self._queue.get(block=False) self._queue_free_slot_condition.notify() closure._set_output_remote_values_cancelled() # pylint: disable=protected-access except queue.Empty: break # The cancellation manager cannot be reused once cancelled. After all # closures (queued or inflight) are cleaned up, recreate the cancellation # manager with clean state. # Note on thread-safety: this is triggered when one of theses client APIs # are called: `schedule`, `wait`, and `done`. At the same time, no new # closures can be constructed (which reads the _cancellation_mgr to get # cancellable functions). self._cancellation_mgr = cancellation.CancellationManager() def _raise_if_error(self): """Raises the error if one exists. If an error exists, cancel the closures in queue, raises it, and clear the error. This method expects self._queue_lock to be held prior to entry. """ if self._error: logging.error("Start cancelling closures due to error %r: %s", self._error, self._error) self._cancel_all_closures() try: raise self._error # pylint: disable=raising-bad-type finally: self._error = None def put(self, closure): """Put a closure into the queue for later execution. If `mark_failed` was called before `put`, the error from the first invocation of `mark_failed` will be raised. Args: closure: The `Closure` to put into the queue. """ with self._put_wait_lock, self._queue_lock: self._queue_free_slot_condition.wait_for(lambda: not self._queue.full()) self._queue.put(closure, block=False) self._raise_if_error() self._closures_queued_condition.notify() def get(self, timeout=None): """Return a closure from the queue to be executed.""" with self._queue_lock: while self._queue.empty(): if not self._closures_queued_condition.wait(timeout=timeout): return None closure = self._queue.get(block=False) self._queue_free_slot_condition.notify() self._inflight_closure_count += 1 return closure def mark_finished(self): """Let the queue know that a closure has been successfully executed.""" with self._queue_lock: if self._inflight_closure_count < 1: raise AssertionError("There is no inflight closures to mark_finished.") self._inflight_closure_count -= 1 if self._inflight_closure_count == 0: self._no_inflight_closure_condition.notifyAll() if self._queue.empty() and self._inflight_closure_count == 0: self._stop_waiting_condition.notifyAll() def put_back(self, closure): """Put the closure back into the queue as it was not properly executed.""" with self._queue_lock: if self._inflight_closure_count < 1: raise AssertionError("There is no inflight closures to put_back.") if self._error: closure._set_output_remote_values_cancelled() # pylint: disable=protected-access else: self._queue_free_slot_condition.wait_for(lambda: not self._queue.full()) self._queue.put(closure, block=False) self._closures_queued_condition.notify() self._inflight_closure_count -= 1 if self._inflight_closure_count == 0: self._no_inflight_closure_condition.notifyAll() def wait(self, timeout=None): """Wait for all closures to be finished before returning. If `mark_failed` was called before or during `wait`, the error from the first invocation of `mark_failed` will be raised. Args: timeout: A float specifying a timeout for the wait in seconds. Returns: True unless the given timeout expired, in which case it returns False. """ with self._put_wait_lock, self._queue_lock: while (not self._error and (not self._queue.empty() or self._inflight_closure_count > 0)): if not self._stop_waiting_condition.wait(timeout=timeout): return False self._raise_if_error() return True def mark_failed(self, e): """Sets error and unblocks any wait() call.""" with self._queue_lock: # TODO(yuefengz): maybe record all failure and give users more # information? if self._inflight_closure_count < 1: raise AssertionError("There is no inflight closures to mark_failed.") if self._error is None: self._error = e self._inflight_closure_count -= 1 if self._inflight_closure_count == 0: self._no_inflight_closure_condition.notifyAll() self._stop_waiting_condition.notifyAll() def done(self): """Returns true if the queue is empty and there is no inflight closure. If `mark_failed` was called before `done`, the error from the first invocation of `mark_failed` will be raised. """ with self._queue_lock: self._raise_if_error() return self._queue.empty() and self._inflight_closure_count == 0 class WorkerPreemptionHandler(object): """Handles worker preemptions.""" def __init__(self, server_def, cluster): self._server_def = server_def self._cluster = cluster self._cluster_update_lock = threading.Lock() self._cluster_due_for_update = threading.Event() self._worker_up_cond = threading.Condition(self._cluster_update_lock) threading.Thread(target=self._preemption_handler, name="WorkerPreemptionHandler", daemon=True).start() def _validate_preemption_failure(self, e): """Validates that the given exception represents worker preemption.""" if _is_worker_failure(e): return raise e @contextlib.contextmanager def wait_on_failure(self, on_failure_fn=None, on_recovery_fn=None, worker_device_name="(unknown)"): """Catches worker preemption error and wait until failed workers are back. Args: on_failure_fn: an optional function to run if preemption happens. on_recovery_fn: an optional function to run when a worker is recovered from preemption. worker_device_name: the device name of the worker instance that is passing through the failure. Yields: None. """ try: yield except errors.OpError as e: # If the error is due to temporary connectivity issues between worker and # ps, put back closure, ignore error and do not mark worker as failure. if self._cluster._record_and_ignore_transient_ps_failure(e): # pylint: disable=protected-access if on_failure_fn: on_failure_fn() return self._validate_preemption_failure(e) logging.error("Worker %s failed with error: %s", worker_device_name, e) if on_failure_fn: on_failure_fn() with self._cluster_update_lock: self._cluster_due_for_update.set() self._worker_up_cond.wait(_WORKER_MAXIMUM_RECOVERY_SEC) logging.info("Worker %s has been recovered.", worker_device_name) if on_recovery_fn: with self.wait_on_failure( on_recovery_fn=on_recovery_fn, worker_device_name=worker_device_name): on_recovery_fn() def _preemption_handler(self): """A loop that handles preemption. This loop waits for signal of worker preemption and upon worker preemption, it waits until all workers are back and updates the cluster about the restarted workers. """ while True: self._cluster_due_for_update.wait() with self._cluster_update_lock: try: # TODO(haoyuzhang): support partial cluster recovery logging.info("Cluster now being recovered.") context.context().update_server_def(self._server_def) # Cluster updated successfully, clear the update signal, and notify # all workers that they are recovered from failure. logging.info("Cluster successfully recovered.") self._worker_up_cond.notify_all() self._cluster_due_for_update.clear() except Exception as e: # pylint: disable=broad-except self._validate_preemption_failure(e) # NOTE: Since the first RPC (GetStatus) of update_server_def is # currently blocking by default, error should only happen if: # (1) More workers failed while waiting for the previous workers to # come back; # (2) Worker failed when exchanging subsequent RPCs after the first # RPC returns. # Consider adding backoff retry logic if we see the error logged # too frequently. logging.error("Cluster update failed with error: %s. Retrying...", e) class Worker(object): """A worker in a cluster. Attributes: worker_index: The index of the worker in the cluster. device_name: The device string of the worker, e.g. "/job:worker/task:1". executor: The worker's executor for remote function execution. failure_handler: The failure handler used to handler worker preemption failure. """ def __init__(self, worker_index, device_name, cluster): self.worker_index = worker_index self.device_name = device_name self.executor = executor.new_executor(enable_async=False) self.failure_handler = cluster.failure_handler self._cluster = cluster self._resource_remote_value_refs = [] # Worker threads need to start after `Worker`'s initialization. threading.Thread(target=self._process_queue, name="WorkerClosureProcessingLoop-%d" % self.worker_index, daemon=True).start() def _set_resources_aborted(self): # TODO(yuefengz): maybe we can query whether a tensor is valid or not # instead of marking a tensor aborted? for weakref_resource in self._resource_remote_value_refs: resource = weakref_resource() if resource: resource._set_aborted() # pylint: disable=protected-access def _set_dead(self): raise NotImplementedError("_set_dead is not implemented.") def _process_closure(self, closure): """Runs a closure with preemption handling.""" try: with self._cluster.failure_handler.wait_on_failure( on_failure_fn=lambda: self._cluster._closure_queue.put_back(closure), # pylint: disable=protected-access on_recovery_fn=self._set_resources_aborted, worker_device_name=self.device_name): closure.execute_on(self) # TODO(yuefengz): we don't have to materialize results every step. with metric_utils.monitored_timer("remote_value_fetch"): closure._fetch_output_remote_values() # pylint: disable=protected-access self._cluster._closure_queue.mark_finished() # pylint: disable=protected-access except Exception as e: # pylint: disable=broad-except # Avoid logging the derived cancellation error if not isinstance(e, errors.CancelledError): logging.error( "/job:worker/task:%d encountered the following error when " "processing closure: %r:%s", self.worker_index, e, e) nest.map_structure( lambda x: x._set_error(e), # pylint: disable=protected-access closure._output_remote_values) # pylint: disable=protected-access self._cluster._closure_queue.mark_failed(e) # pylint: disable=protected-access def _process_queue(self): while True: closure = self._cluster._closure_queue.get() # pylint: disable=protected-access self._process_closure(closure) def _create_resource(self, function, args=None, kwargs=None): """Synchronously creates a per-worker resource represented by a `RemoteValue`. Args: function: the resource function to be run remotely. It should be a `tf.function`, a concrete function or a Python function. args: positional arguments to be passed to the function. kwargs: keyword arguments to be passed to the function. Returns: one or several RemoteValue objects depending on the function return values. """ # Some notes about the concurrency: currently all the activities related to # the same worker such as creating resources, setting resources' aborted # status, and executing closures happen on the same thread. This allows us # to have simpler logic of concurrency. closure = Closure( function, self._cluster._closure_queue._cancellation_mgr, # pylint: disable=protected-access args=args, kwargs=kwargs) resource_remote_value = closure._output_remote_values # pylint: disable=protected-access self._register_resource(resource_remote_value) # The following is a short-term solution to lazily create resources in # parallel. # TODO(b/160343165): we should create resources eagerly, i.e. schedule the # resource creation function as soon as users call this method. resource_remote_value._set_aborted() # pylint: disable=protected-access return resource_remote_value def _register_resource(self, resource_remote_value): if not isinstance(resource_remote_value, RemoteValue): raise ValueError( "Resource being registered is not of type `RemoteValue`.") self._resource_remote_value_refs.append(weakref.ref(resource_remote_value)) class Cluster(object): """A cluster with workers. We assume all function errors are fatal and based on this assumption our error reporting logic is: 1) Both `schedule` and `join` can raise a non-retryable error which is the first error seen by the client from any previously scheduled functions. 2) When an error is raised, there is no guarantee on how many previously scheduled functions have been executed; functions that have not been executed will be thrown away and marked as cancelled. 3) After an error is raised, the internal state of error will be cleared. I.e. functions can continue to be scheduled and subsequent calls of `schedule` or `join` will not raise the same error again. Attributes: failure_handler: The failure handler used to handler worker preemption failure. workers: a list of `Worker` objects in the cluster. """ def __init__(self, strategy): """Initializes the cluster instance.""" self._num_workers = strategy._num_workers self._num_ps = strategy._num_ps # Ignore PS failures reported by workers due to transient connection errors. # Transient connectivity issues between workers and PS are relayed by the # workers to the client, leading the client to believe that there are PS # failures. The difference between transient vs. permanent PS failure is the # number of reports from the workers. When this env var is set to a positive # integer K, the client ignores up to K reports of a failed PS task. I.e., # only when there are more than K trials of executing closures fail due to # errors from the same PS instance do we consider the PS instance encounters # a failure. # TODO(b/164279603): Remove this workaround when the underlying connectivity # issue in gRPC server is resolved. self._transient_ps_failures_threshold = int(os.environ.get( "TF_CLIENT_IGNORE_TRANSIENT_PS_FAILURES", 3)) self._potential_ps_failures_lock = threading.Lock() self._potential_ps_failures_count = [0] * self._num_ps self._closure_queue = _CoordinatedClosureQueue() self.failure_handler = WorkerPreemptionHandler(context.get_server_def(), self) worker_device_strings = [ "/job:worker/replica:0/task:%d" % i for i in range(self._num_workers) ] self.workers = [ Worker(i, w, self) for i, w in enumerate(worker_device_strings) ] def _record_and_ignore_transient_ps_failure(self, e): """Records potential PS failures and return if failure should be ignored.""" if self._transient_ps_failures_threshold <= 0 or not _is_ps_failure(e): return False ps_tasks = _extract_failed_ps_instances(str(e)) with self._potential_ps_failures_lock: for t in ps_tasks: self._potential_ps_failures_count[t] += 1 # The number of UnavailableError encountered on this PS task exceeds the # maximum number of ignored error if (self._potential_ps_failures_count[t] >= self._transient_ps_failures_threshold): return False return True def schedule(self, function, args, kwargs): """Schedules `function` to be dispatched to a worker for execution. Args: function: The function to be dispatched to a worker for execution asynchronously. args: Positional arguments for `fn`. kwargs: Keyword arguments for `fn`. Returns: A structure of `RemoteValue` object. """ closure = Closure( function, self._closure_queue._cancellation_mgr, # pylint: disable=protected-access args=args, kwargs=kwargs) self._closure_queue.put(closure) return closure._output_remote_values # pylint: disable=protected-access def join(self): """Blocks until all scheduled functions are executed.""" self._closure_queue.wait() def done(self): """Returns true if all scheduled functions are executed.""" return self._closure_queue.done() class ParameterServerFailureError(Exception): """An error representing at least one parameter server is interrupted.""" pass class Client(object): """An object to schedule and orchestrate remote function execution. A `Client` object represents a program used to create dataset, schedule functions to be executed, and fetch the results of the functions. Currently, `Client` is not supported to be used in a standalone manner. It should be used in conjunction with `ParameterServerStrategyV2`. This is currently under development, and the API as well as implementation is subject to changes. """ def __init__(self, strategy): """Initialization of a `Client` instance. This connects the client to remote workers and parameter servers, through a `tf.config.experimental_connect_to_cluster` call. Args: strategy: a `tf.distribute.Strategy` object. Currently, only `ParameterServerStrategyV2` is supported. Raises: ValueError: if the strategy being used is not supported. """ if not isinstance(strategy, parameter_server_strategy_v2.ParameterServerStrategyV2): raise ValueError("Only `ParameterServerStrategyV2` is supported in " "`Client` currently.") self._strategy = strategy self.cluster = Cluster(strategy) @property def strategy(self): return self._strategy def schedule(self, fn, args=None, kwargs=None): """Schedules `fn` to be dispatched to a worker for execution asynchronously. When calling `schedule` with a function `fn`, `fn` will be executed on a remote worker at some later time. The process is asynchronous, meaning `schedule` returns immediately, possibly without having the result ready yet. `schedule` returns a structure of `RemoteValue` object, which wraps the output of the function. Call `fetch()` on `RemoteValue` to wait for the function execution to finish and retrieve its output from the remote worker. `schedule` guarantees that `fn` will be executed on a worker at least once; it could be more than once if its corresponding worker fails in the middle of its execution. Note that since worker can fail at any point when executing the function, it is possible that the function is partially executed, but `Client` guarantees that in those events, the function will eventually be fully executed, possibly on a different worker that is available. If any previously scheduled function raises an error, `schedule` will fail by raising any one of those errors, and clear the errors collected so far. There are two implications when this happens: 1) user should call `schedule` with `fn` again to re-schedule, and 2) some of the previously scheduled functions may have not been executed. User can call `fetch` on the returned `RemoteValue` to inspect if they have executed, failed, or cancelled, and reschedule the corresponding function if needed. When `schedule` raises, it guarantees that there is no function that is still being executed. At this time, there is no support of worker assignment for function execution, or priority of the workers. `args` and `kwargs` are the arguments passed into `fn`, when `fn` is executed on a worker. They can be `PerWorkerValues`, which is a collection of values, each of which represents a component specific to a worker; in this case, the argument will be substituted with the corresponding component on the target worker. Arguments that are not `PerWorkerValues` will be passed into `fn` as-is. Currently, `RemoteValue` is not supported to be input `args` or `kwargs`. Args: fn: A `tf.function`; the function to be dispatched to a worker for execution asynchronously. args: Positional arguments for `fn`. kwargs: Keyword arguments for `fn`. Returns: A structure of `RemoteValue` object. Raises: Exception: one of the exceptions caught by the client by any previously scheduled function since the last time an error was thrown or since the beginning of the program. """ # Slot variables are usually created during function tracing time; thus # `schedule` needs to be called within the `strategy.scope()`. with self.strategy.scope(), _translate_parameter_server_failure(): return self.cluster.schedule(fn, args=args, kwargs=kwargs) def join(self): """Blocks until all the scheduled functions have finished execution. If any previously scheduled function raises an error, `join` will fail by raising any one of those errors, and clear the errors collected so far. If this happens, some of the previously scheduled functions may have not been executed. Users can call `fetch` on the returned `RemoteValue` to inspect if they have executed, failed, or cancelled. If some that have been cancelled need to be rescheduled, users should call `schedule` with the function again. When `join` returns or raises, it guarantees that there is no function that is still being executed. Raises: Exception: one of the exceptions caught by the client by any previously scheduled function since the last time an error was thrown or since the beginning of the program. """ with _translate_parameter_server_failure(): self.cluster.join() def done(self): """Returns whether all the scheduled functions have finished execution. If any previously scheduled function raises an error, `done` will fail by raising any one of those errors. When `done` returns True or raises, it guarantees that there is no function that is still being executed. """ return self.cluster.done() def create_per_worker_dataset(self, dataset_fn): """Create dataset on workers by calling `dataset_fn` on worker devices. This creates the given dataset generated by dataset_fn on the workers and returns an object that represents the collection of those individual datasets. Calling `iter` on such collection of dataset returns a `PerWorkerValues`, which is a collection of iterators, where the iterators have been placed on respective workers. Calling `next` on this `PerWorkerValues` of iterators is currently unsupported; it is meant to be passed as an argument into `Client.schedule`. When the scheduled function is picked up and being executed by a worker, the function will receive the individual iterator that corresponds to the worker, and now `next` can be called on iterator to get the next (batch or example) of data. Dataset shuffling and repeating are usually needed in `dataset_fn`; however, sharding is not recommended: some worker may not be available and those examples may be skipped and not covered by other workers, if the dataset is sharded. Args: dataset_fn: The dataset function that returns a dataset. This is to be executed on the workers. Returns: An object that represents the collection of those individual datasets. `iter` is expected to be called on this object that returns a `PerWorkerValues` of the iterators (that are on the workers). """ input_workers = input_lib.InputWorkers([ (w.device_name, [w.device_name]) for w in self.cluster.workers ]) return _PerWorkerDistributedDataset(dataset_fn, input_workers, self) def _create_per_worker_resources(self, fn, args=None, kwargs=None): """Synchronously create resources on the workers. The resources are represented by `RemoteValue`s. Args: fn: The function to be dispatched to all workers for execution asynchronously. args: Positional arguments for `fn`. kwargs: Keyword arguments for `fn`. Returns: A `PerWorkerValues` object, which wraps a tuple of `RemoteValue` objects. """ results = [] for w in self.cluster.workers: results.append(w._create_resource(fn, args=args, kwargs=kwargs)) # pylint: disable=protected-access return PerWorkerValues(tuple(results)) def fetch(self, val): """Blocking call to fetch results from `RemoteValue`s. This returns the execution result of `RemoteValue`s; if not ready, waiting for it while blocking the caller. Args: val: The value to fetch the results from. If this is structure of `RemoteValue`, `fetch()` will be called on the individual `RemoteValue` to get the result. Returns: If `val` is a `RemoteValue` or a structure of `RemoteValue`s, returns the fetched `RemoteValue` value immediately if it's available, or blocks the call until it's available, and returns the fetched `RemoteValue` values with the same structure. If `val` is other types, return (`val`,). """ def _maybe_fetch(val): if isinstance(val, RemoteValue): return val.fetch() else: return val # TODO(yuefengz): we should fetch values in a batch. result = nest.map_structure(_maybe_fetch, val) if not isinstance(result, tuple): return (result,) return result # pylint: disable=missing-function-docstring @contextlib.contextmanager def _translate_parameter_server_failure(): try: yield except Exception as e: # pylint: disable=broad-except if _is_ps_failure(e): raise ParameterServerFailureError(e) else: raise # pylint: disable=missing-function-docstring @contextlib.contextmanager def handle_parameter_server_failure(): try: with _translate_parameter_server_failure(): yield except ParameterServerFailureError as e: # pylint: disable=broad-except restart_exit_code = os.environ.get("TF_CLIENT_NON_FATAL_RESTART_EXIT_CODE", None) if restart_exit_code is not None: sys.exit(int(restart_exit_code)) else: raise class _PerWorkerDistributedDataset(object): """Represents worker-distributed datasets created from dataset function.""" def __init__(self, dataset_fn, input_workers, client): """Makes an iterable from datasets created by the given function. Args: dataset_fn: A function that returns a `Dataset`. input_workers: an `InputWorkers` object. client: a `Client` object, used to create dataset resources. """ def disallow_variable_creation(next_creator, **kwargs): raise ValueError("Creating variables in `dataset_fn` is not allowed.") if isinstance(dataset_fn, def_function.Function): with variable_scope.variable_creator_scope(disallow_variable_creation): dataset_fn = dataset_fn.get_concrete_function() elif not isinstance(dataset_fn, tf_function.ConcreteFunction): with variable_scope.variable_creator_scope(disallow_variable_creation): dataset_fn = def_function.function(dataset_fn).get_concrete_function() self._dataset_fn = dataset_fn self._input_workers = input_workers self._client = client self._element_spec = None def __iter__(self): # We would like users to create iterators outside `tf.function`s so that we # can track them. if (not context.executing_eagerly() or ops.get_default_graph().building_function): raise RuntimeError( "__iter__() is not supported inside of tf.function or in graph mode.") def _create_per_worker_iterator(): dataset = self._dataset_fn() return iter(dataset) # If _PerWorkerDistributedDataset.__iter__ is called multiple # times, for the same object it should only create and register resource # once. Using object id to distinguish different iterator resources. per_worker_iterator = self._client._create_per_worker_resources( _create_per_worker_iterator) # Setting type_spec of each RemoteValue so that functions taking these # RemoteValues as inputs can be traced. for iterator_remote_value in per_worker_iterator._values: iterator_remote_value._set_type_spec( iterator_ops.IteratorSpec( self._dataset_fn.structured_outputs.element_spec)) return _PerWorkerDistributedIterator(per_worker_iterator._values) @property def element_spec(self): """The type specification of an element of this dataset.""" raise NotImplementedError("Passing `AsyncDistributedDataset` to a " "tf.function is not supported.") class _PerWorkerDistributedIterator(PerWorkerValues): """Distributed iterator for `Client`.""" def __next__(self): return self.get_next() def get_next(self, name=None): """Returns the next input from the iterator for all replicas.""" raise NotImplementedError("Iterating over an `AsyncDistributedIterator` " "is not supported right now.") def _extract_failed_ps_instances(err_msg): """Return a set of potentially failing ps instances from error message.""" tasks = re.findall("/job:ps/replica:0/task:[0-9]+", err_msg) return set(int(t.split(":")[-1]) for t in tasks) def _is_ps_failure(error): """Whether the error is considered a parameter server failure.""" if (_RPC_ERROR_FROM_PS in str(error) or (isinstance(error, errors.InvalidArgumentError) and "/job:ps" in str(error))): return True def _is_worker_failure(error): """Whether the error is considered a worker failure.""" if _JOB_WORKER_STRING_IDENTIFIER not in str(error): return False if _RPC_ERROR_FROM_PS in str(error): return False # TODO(haoyuzhang): Consider using special status code if error from a # remote is derived from RPC errors originated from other hosts. if isinstance(error, (errors.UnavailableError, errors.AbortedError)): return True # The following error could happen when the remote task fails and restarts # in a very short interval during which no RPCs were exchanged to detect the # failure. In that case, gRPC allows channel (which is different from a # connection) to be reused for a replaced server listening to same address. if isinstance(error, errors.InvalidArgumentError): if ("Unable to find a context_id" in str(error) or "unknown device" in str(error) or "Unable to find the relevant tensor remote_handle" in str(error)): # TODO(b/159961667): Fix "Unable to find the relevant tensor # remote_handle" part. return True # TODO(b/162541228): The following 3 types of errors are very rare and only # observed in large-scale testing. The types of errors should be reduced. # This error could show up when copying function inputs from remote tasks. if isinstance(error, errors.InternalError): if ("Failed copying input tensor" in str(error) or "Unable to find a context_id" in str(error)): return True # This could happen when the function registration fails. In the observed # cases this only happens to the dataset related functions. if isinstance(error, errors.NotFoundError): if ("is neither a type of a primitive operation nor a name of a function " "registered" in str(error)): return True # This could happen when the iterator is no longer valid on the remote worker # "Resource input tensor contains an invalid device" if isinstance(error, errors.CancelledError): return True return False

[ "[email protected]" ]

[email protected]

a6c26522a2da68de30a9caebeb0d89d3cde0854f

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/library/signal/demo_signal.py

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[]

no_license

webclinic017/option_pdt

fdc559f02cc529b54278e90e04170713fe93684f

dd302c6b2661e26dbfcbea0384b99e85ae9584e1

refs/heads/master

2023-03-24T10:43:35.998775

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from base.signal_base import SignalBase class Signal(SignalBase): def __init__(self, spot_instrument, future_instrument): super().__init__(spot_instrument, future_instrument) self.spot_instrument = spot_instrument self.future_instrument = future_instrument self.spot_price = float('nan') self.future_price = float('nan') self.subscription_list = [f'{_}|1s' for _ in [spot_instrument, future_instrument]] def on_market_data_1s_ready(self, data): instrument = '|'.join([data['exchange', 'symbol', 'contract_type']]) if instrument == self.spot_instrument: self.spot_price = data['metadata']['mid'] else: self.future_price = data['metadata']['mid'] self.value = self.future_price / self.spot_price - 1 def from_hist_data(self, mds): spot_orderbook = mds[self.subscription_list[0]] fut_orderbook = mds[self.subscription_list[1]] df = spot_orderbook[['local_timestamp']].copy() df['value'] = fut_orderbook['mid'] / spot_orderbook['mid'] - 1 return df

[ "[email protected]" ]

[email protected]

4364d3d0e4e45b61777839885827ff630e4e8965

353def93fa77384ee3a5e3de98cfed318c480634

/.history/week01/hoework01/gettop10frommaoyam01_20200625232557.py

6eb6ccba3f51b68abc25670be539f7e1cf36cf46

[]

no_license

ydbB/Python001-class01

d680abc3ea1ccaeb610751e3488421417d381156

ad80037ccfc68d39125fa94d2747ab7394ac1be8

refs/heads/master

2022-11-25T11:27:45.077139

2020-07-19T12:35:12

272,783,233

0

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2020-06-16T18:28:15

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# 使用requests，bs4库，爬取猫眼电影top10的电影名称、电影类型、上映时间，并以utf-8的字符集保存到csv文件中 import requests from bs4 import BeautifulSoup as bs maoyanUrl = "https://maoyan.com/board/4"; user_agent = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/74.0.3729.169 Safari/537.36' header = { 'Content-Type': 'text/plain; charset=UTF-8', 'Cookie' : '__mta=251934006.1593072991075.1593075273346.1593075275703.6; uuid_n_v=v1; uuid=2395D3F0B6BC11EA9F28E30FF5FFF73C9A16AE2FA53A448DA75AEAA9D715CB59; _csrf=8557626db9b655cf9050ae7e5b2aab69278c8061c21eca95e1c3cf2130b0b64c; _lxsdk_cuid=172ea8cb247c8-0a73066b1c0a8b-4353760-100200-172ea8cb248c8; _lxsdk=2395D3F0B6BC11EA9F28E30FF5FFF73C9A16AE2FA53A448DA75AEAA9D715CB59; mojo-uuid=c457eacb7c1eb59d3d2f6c1f8d75b9c9; Hm_lvt_703e94591e87be68cc8da0da7cbd0be2=1593072989,1593073002; _lx_utm=utm_source%3Dgoogle%26utm_medium%3Dorganic; mojo-session-id={"id":"dd5ec1780230b10b3b01a18882424620","time":1593078373432}; Hm_lpvt_703e94591e87be68cc8da0da7cbd0be2=1593078727; __mta=251934006.1593072991075.1593075275703.1593078726963.7; mojo-trace-id=3; _lxsdk_s=172eade6a22-b72-c5-308%7C%7C6', 'Origin': 'https://maoyan.com', 'Referer': 'https://maoyan.com/board/4', 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/67.0.3396.99 Safari/537.36', } response = requests.get(maoyanUrl,headers=header) response.encoding = 'utf-8' bs_info = bs(response.text,"html.parser") # print(response.text) for tags in bs_info.find_all('div',altrs={'id':'container'}): print(tags) for tag in tags.find_all('a',): print(tag.get('href')) print(tag.get('title'))

[ "[email protected]" ]

[email protected]

15c9a7f22850db515e4e18371917447d643d5ef9

8be39fd741cbbb08439433188ca1bc59ee5cf11f

/data_handler/logistic_parser.py

e6aef4d466d44f479d23b3cf53d7c015e2c3c050

[ "MIT" ]

permissive

tpimentelms/fast-conversational-banking

ca1e699261f989f3b535a50782062c000985ba1e

b9d3ddfe3adb78522fafab91c2d20495db063dda

refs/heads/master

2021-03-16T21:30:51.253223

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from .data_parser import DataParser class LogisticDataParser(DataParser): def __init__(self, max_len, cuda=True, quiet=True, remove_brackets=False): super(LogisticDataParser, self).__init__(max_len, cuda=cuda, quiet=quiet) self.remove_brackets = remove_brackets def normalize_string(self, s): if self.remove_brackets: s = [x for x in s if x not in ['(', ')', ',']] return s

[ "[email protected]" ]

[email protected]

58fc0eca94dc7087f6281521d213dd735c29351d

30cffb7452220c2ac2961dd2e0f42e3b359a59c0

/simscale_sdk/models/one_of_solid_simulation_control_pseudo_time_stepping.py

fa0feb65ab655b8e7c0d7bac2d73c1a47ecd1ee9

[ "MIT" ]

permissive

vpurcarea/simscale-python-sdk

0bf892d8824f8d4599caa0f345d5ba28e038f5eb

6f2d12b2d21142bd854042c0fb402c2c797629e4

refs/heads/master

2023-03-14T04:31:06.226337

2021-03-03T16:20:01

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# coding: utf-8 """ SimScale API The version of the OpenAPI document: 0.0.0 Generated by: https://openapi-generator.tech """ import pprint import re # noqa: F401 import six from simscale_sdk.configuration import Configuration class OneOfSolidSimulationControlPseudoTimeStepping(object): """NOTE: This class is auto generated by OpenAPI Generator. Ref: https://openapi-generator.tech Do not edit the class manually. """ """ Attributes: openapi_types (dict): The key is attribute name and the value is attribute type. attribute_map (dict): The key is attribute name and the value is json key in definition. """ openapi_types = { 'type': 'str', 'static_timesteps': 'DimensionalTime', 'simulation_intervals': 'DimensionalTime', 'timestep_length': 'RestrictedDimensionalFunctionTime' } attribute_map = { 'type': 'type', 'static_timesteps': 'staticTimesteps', 'simulation_intervals': 'simulationIntervals', 'timestep_length': 'timestepLength' } discriminator_value_class_map = { 'SINGLE_STEP': 'SingleStepPseudoTimeStepping', 'STEPPING_LIST_V18': 'SteppingListPseudoTimeStepping' } def __init__(self, type='STEPPING_LIST_V18', static_timesteps=None, simulation_intervals=None, timestep_length=None, local_vars_configuration=None): # noqa: E501 """OneOfSolidSimulationControlPseudoTimeStepping - a model defined in OpenAPI""" # noqa: E501 if local_vars_configuration is None: local_vars_configuration = Configuration() self.local_vars_configuration = local_vars_configuration self._type = None self._static_timesteps = None self._simulation_intervals = None self._timestep_length = None self.discriminator = 'type' self.type = type if static_timesteps is not None: self.static_timesteps = static_timesteps if simulation_intervals is not None: self.simulation_intervals = simulation_intervals if timestep_length is not None: self.timestep_length = timestep_length @property def type(self): """Gets the type of this OneOfSolidSimulationControlPseudoTimeStepping. # noqa: E501 :return: The type of this OneOfSolidSimulationControlPseudoTimeStepping. # noqa: E501 :rtype: str """ return self._type @type.setter def type(self, type): """Sets the type of this OneOfSolidSimulationControlPseudoTimeStepping. :param type: The type of this OneOfSolidSimulationControlPseudoTimeStepping. # noqa: E501 :type: str """ if self.local_vars_configuration.client_side_validation and type is None: # noqa: E501 raise ValueError("Invalid value for `type`, must not be `None`") # noqa: E501 self._type = type @property def static_timesteps(self): """Gets the static_timesteps of this OneOfSolidSimulationControlPseudoTimeStepping. # noqa: E501 :return: The static_timesteps of this OneOfSolidSimulationControlPseudoTimeStepping. # noqa: E501 :rtype: DimensionalTime """ return self._static_timesteps @static_timesteps.setter def static_timesteps(self, static_timesteps): """Sets the static_timesteps of this OneOfSolidSimulationControlPseudoTimeStepping. :param static_timesteps: The static_timesteps of this OneOfSolidSimulationControlPseudoTimeStepping. # noqa: E501 :type: DimensionalTime """ self._static_timesteps = static_timesteps @property def simulation_intervals(self): """Gets the simulation_intervals of this OneOfSolidSimulationControlPseudoTimeStepping. # noqa: E501 :return: The simulation_intervals of this OneOfSolidSimulationControlPseudoTimeStepping. # noqa: E501 :rtype: DimensionalTime """ return self._simulation_intervals @simulation_intervals.setter def simulation_intervals(self, simulation_intervals): """Sets the simulation_intervals of this OneOfSolidSimulationControlPseudoTimeStepping. :param simulation_intervals: The simulation_intervals of this OneOfSolidSimulationControlPseudoTimeStepping. # noqa: E501 :type: DimensionalTime """ self._simulation_intervals = simulation_intervals @property def timestep_length(self): """Gets the timestep_length of this OneOfSolidSimulationControlPseudoTimeStepping. # noqa: E501 :return: The timestep_length of this OneOfSolidSimulationControlPseudoTimeStepping. # noqa: E501 :rtype: RestrictedDimensionalFunctionTime """ return self._timestep_length @timestep_length.setter def timestep_length(self, timestep_length): """Sets the timestep_length of this OneOfSolidSimulationControlPseudoTimeStepping. :param timestep_length: The timestep_length of this OneOfSolidSimulationControlPseudoTimeStepping. # noqa: E501 :type: RestrictedDimensionalFunctionTime """ self._timestep_length = timestep_length def get_real_child_model(self, data): """Returns the real base class specified by the discriminator""" discriminator_key = self.attribute_map[self.discriminator] discriminator_value = data[discriminator_key] return self.discriminator_value_class_map.get(discriminator_value) def to_dict(self): """Returns the model properties as a dict""" result = {} for attr, _ in six.iteritems(self.openapi_types): value = getattr(self, attr) if isinstance(value, list): result[attr] = list(map( lambda x: x.to_dict() if hasattr(x, "to_dict") else x, value )) elif hasattr(value, "to_dict"): result[attr] = value.to_dict() elif isinstance(value, dict): result[attr] = dict(map( lambda item: (item[0], item[1].to_dict()) if hasattr(item[1], "to_dict") else item, value.items() )) else: result[attr] = value return result def to_str(self): """Returns the string representation of the model""" return pprint.pformat(self.to_dict()) def __repr__(self): """For `print` and `pprint`""" return self.to_str() def __eq__(self, other): """Returns true if both objects are equal""" if not isinstance(other, OneOfSolidSimulationControlPseudoTimeStepping): return False return self.to_dict() == other.to_dict() def __ne__(self, other): """Returns true if both objects are not equal""" if not isinstance(other, OneOfSolidSimulationControlPseudoTimeStepping): return True return self.to_dict() != other.to_dict()

[ "simscale" ]

simscale

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/experiments/atari_hard/montezuma_revenge/ppo_cnd_102_2.py

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michalnand/reinforcement_learning

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refs/heads/main

2023-06-01T10:27:36.601631

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import time import torch import RLAgents import models.ppo_cnd_102_2.src.model_ppo as ModelPPO import models.ppo_cnd_102_2.src.model_cnd_target as ModelCNDTarget import models.ppo_cnd_102_2.src.model_cnd as ModelCND import models.ppo_cnd_102_2.src.config as Config #torch.cuda.set_device("cuda:0") #print("running on ", torch.cuda.get_device_name()) path = "models/ppo_cnd_102_2/" config = Config.Config() #config.envs_count = 1 envs = RLAgents.MultiEnvParallelOptimised("MontezumaRevengeNoFrameskip-v4", RLAgents.WrapperMontezuma, config.envs_count) #envs = RLAgents.MultiEnvSeq("MontezumaRevengeNoFrameskip-v4", RLAgents.WrapperMontezuma, config.envs_count) #envs = RLAgents.MultiEnvSeq("MontezumaRevengeNoFrameskip-v4", RLAgents.WrapperMontezumaVideo, config.envs_count) agent = RLAgents.AgentPPOCND(envs, ModelPPO, ModelCNDTarget, ModelCND, config) max_iterations = 500000 trainig = RLAgents.TrainingIterations(envs, agent, max_iterations, path, 128) trainig.run() ''' agent.load(path) agent.disable_training() while True: reward, done, _ = agent.main() envs.render(0) #time.sleep(0.01) '''

[ "[email protected]" ]

[email protected]

a0ee9508274fd3f6962a34e95d4396b1d61ab45f

af54f9cef3290fc4066cbbe2a66e36006c7c5896

/plates/investrategy/views.py

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[]

no_license

zizle/workAssistant

4e504baf3e8cb0942bdf48e61d96bf9f4ef3779c

875df36725118e8737fd38d3873bf75434296d1b

refs/heads/master

2022-08-12T16:16:33.972788

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# _*_ coding:utf-8 _*_ # Author: zizle import datetime import hashlib import os import time import pandas as pd import xlrd from flask import jsonify, request, current_app, send_from_directory from flask.views import MethodView from db import MySQLConnection from settings import BASE_DIR from utils.psd_handler import verify_json_web_token from vlibs import ORGANIZATIONS class InvestrategyView(MethodView): def get(self): params = request.args # 解析用户信息 token = params.get('utoken') user_info = verify_json_web_token(token) if not user_info: return jsonify("您的登录已过期,请重新登录查看.") user_id = user_info['uid'] try: start_date = params.get('startDate') end_date = params.get('endDate') end_date = datetime.datetime.strptime(end_date, '%Y-%m-%d') + datetime.timedelta(days=1) end_date = (end_date + datetime.timedelta(seconds=-1)).strftime('%Y-%m-%d %H:%M:%S') current_page = int(params.get('page', 1)) - 1 page_size = int(params.get('pagesize', 30)) except Exception: return jsonify("参数错误:DATE FORMAT ERROR & INT TYPE REQUIRED!") start_id = current_page * page_size db_connection = MySQLConnection() cursor = db_connection.get_cursor() # sql内联查询 inner_join_statement = "SELECT usertb.name,usertb.org_id,invsgytb.id,invsgytb.custom_time,invsgytb.content,invsgytb.variety_id, varietytb.name AS variety, invsgytb.contract,invsgytb.direction,invsgytb.hands,invsgytb.open_position," \ "invsgytb.close_position,invsgytb.profit " \ "FROM `user_info` AS usertb INNER JOIN `investrategy` AS invsgytb INNER JOIN `variety` as varietytb ON " \ "(usertb.id=%s AND usertb.id=invsgytb.author_id) AND invsgytb.variety_id=varietytb.id AND (invsgytb.custom_time BETWEEN %s AND %s) " \ "ORDER BY invsgytb.custom_time DESC " \ "limit %s,%s;" cursor.execute(inner_join_statement, (user_id, start_date, end_date, start_id, page_size)) result_records = cursor.fetchall() # print("内连接查投顾策略自方案结果", result_records) # 查询总条数 count_statement = "SELECT COUNT(invsgytb.id) as total, SUM(invsgytb.profit) AS `sumprofit` " \ "FROM `user_info` AS usertb INNER JOIN `investrategy`AS invsgytb " \ "ON usertb.id=%s AND usertb.id=invsgytb.author_id AND (invsgytb.custom_time BETWEEN %s AND %s);" cursor.execute(count_statement, (user_id, start_date, end_date)) fetch_one = cursor.fetchone() # print(fetch_one) db_connection.close() if fetch_one: total_count = fetch_one['total'] sum_porfit = fetch_one['sumprofit'] else: total_count = sum_porfit = 0 total_page = int((total_count + page_size - 1) / page_size) # print('total_page',total_page) # 组织数据返回 response_data = dict() response_data['records'] = list() for record_item in result_records: record_item['custom_time'] = record_item['custom_time'].strftime('%Y-%m-%d') record_item['variety'] = (record_item['variety'] if record_item['variety'] else '') + str(record_item['contract']) record_item['org_name'] = ORGANIZATIONS.get(int(record_item['org_id']), '未知') record_item['open_position'] = float(record_item['open_position']) record_item['close_position'] = float(record_item['close_position']) record_item['profit'] = float(record_item['profit']) response_data['records'].append(record_item) response_data['current_page'] = current_page + 1 # 查询前给减1处理了，加回来 response_data['total_page'] = total_page response_data['current_count'] = len(result_records) response_data['total_count'] = total_count response_data['sum_profit'] = float(sum_porfit) if sum_porfit else 0 return jsonify(response_data) def post(self): body_data = request.json author_id = body_data.get('author_id', None) if not author_id: return jsonify("参数错误，HAS NO AUTHORID.") # 查找用户 db_connection = MySQLConnection() cursor = db_connection.get_cursor() select_user_statement = "SELECT `id`,`name`,`is_admin` FROM `user_info` WHERE `id`=%s AND `is_active`=1;" cursor.execute(select_user_statement, author_id) user_obj = cursor.fetchone() if not user_obj: return jsonify("系统没有查到您的信息,无法操作."), 400 if user_obj['is_admin']: return jsonify('请不要使用用管理员用户添加记录.') # 不为空的信息判断 content = body_data.get('content', False) variety = body_data.get('variety', False) direction = body_data.get('direction', False) if not content or not variety or not direction: return jsonify("参数错误,NOT FOUND CONTENT,VARIETY,DIRECTION."), 400 # 组织信息 custom_time = body_data.get('custom_time') custom_time = datetime.datetime.strptime(custom_time, '%Y-%m-%d') if custom_time else datetime.datetime.now() author_id = user_obj['id'] contract = body_data.get('contract', '') hands = body_data.get('hands', 0) open_position = body_data.get('open_position', 0) close_position = body_data.get('close_position', 0) profit = body_data.get('profit') note = body_data.get('work_note', '') # 存入数据库 save_invest_statement = "INSERT INTO `investrategy`" \ "(`custom_time`,`author_id`,`content`,`variety_id`,`contract`,`direction`,`hands`," \ "`open_position`,`close_position`,`profit`)" \ "VALUES (%s,%s,%s,%s,%s,%s,%s,%s,%s,%s);" try: # 转换类型 variety_id = int(variety) hands = int(hands) if hands else 0 open_position = int(open_position) if open_position else 0 close_position = int(close_position) if close_position else 0 profit = float(profit) if profit else 0 cursor.execute(save_invest_statement, (custom_time, author_id, content, variety_id, contract, direction,hands, open_position, close_position, profit) ) db_connection.commit() except Exception as e: db_connection.rollback() db_connection.close() current_app.logger.error("写入投顾策略记录错误:" + str(e)) return jsonify("参数错误!无法保存。"), 400 else: db_connection.close() return jsonify("保存成功!"), 201 class FileHandlerInvestrategyView(MethodView): def post(self): # 获取当前用户的信息 user_id = request.form.get('uid') file = request.files.get('file', None) if not file or not user_id: return jsonify('参数错误,NOT FILE OR UID'), 400 # 查找用户 db_connection = MySQLConnection() cursor = db_connection.get_cursor() select_user_statement = "SELECT `id`,`name`,`is_admin` FROM `user_info` WHERE `id`=%s;" cursor.execute(select_user_statement, user_id) user_obj = cursor.fetchone() # 管理员不给添加信息 if user_obj['is_admin']: return jsonify('请不要使用用管理员用户添加记录.') # 准备品种信息 # variety_dict = {value: key for key, value in VARIETY_LIB.items()} query_variety = "SELECT `id`,`name` FROM `variety` WHERE `parent_id` IS NOT NULL;" cursor.execute(query_variety) variety_all = cursor.fetchall() variety_dict = {variety_item["name"]:variety_item['id'] for variety_item in variety_all} db_connection.close() # 文件内容 file_contents = file.read() file_contents = xlrd.open_workbook(file_contents=file_contents) # 导入名称为“投顾策略记录”的表 table_data = file_contents.sheet_by_name('投顾策略记录') # 检查sheet1是否导入完毕 status = file_contents.sheet_loaded('投顾策略记录') if not status: return jsonify('文件数据导入失败'), 400 # 读取第一行数据 first_row = table_data.row_values(0) # 格式判断 if first_row != ["日期", "策略内容", "品种", "合约", "方向(多头,空头,套利)","10万为限对应手数", "策略开仓","策略平仓","策略结果(+/-/0)"]: return jsonify("表格格式有误,请修正."), 400 # 读取数据并写入数据库 nrows = table_data.nrows # ncols = table_data.ncols ready_to_save = list() start_row_in = False message = "表格列数据类型有误,请检查后上传." try: for row in range(nrows): row_content = table_data.row_values(row) if str(row_content[0]).strip() == "start": start_row_in = True continue if str(row_content[0]).strip() == "end": start_row_in = False continue if start_row_in: record_row = list() try: record_row.append(xlrd.xldate_as_datetime(row_content[0], 0)) except Exception as e: message = "第一列【日期】请使用日期格式上传." raise ValueError(message) record_row.append(user_id) record_row.append(str(row_content[1])) try: record_row.append(int(variety_dict.get(str(row_content[2])))) # 品种 except Exception as e: message = "系统中没有【" + str(row_content[2]) + "】品种信息." raise ValueError(message) try: contract = int(row_content[3]) except Exception: contract = row_content[3] record_row.append(str(contract)) record_row.append(str(row_content[4])) record_row.append(int(row_content[5]) if row_content[5] else 0) record_row.append(float(row_content[6]) if row_content[6] else 0) record_row.append(float(row_content[7]) if row_content[7] else 0) record_row.append(float(row_content[8]) if row_content[8] else 0) ready_to_save.append(record_row) if len(ready_to_save) == 0: raise ValueError('没有读取到数据.') new_df = pd.DataFrame(ready_to_save) new_df.columns = ['custom_time', 'author_id', 'content', 'variety_id','contract','direction','hands','open_position','close_position','profit'] save_list = self.drop_old_date_record(new_df, user_id) if len(save_list) > 0: message = "数据保存成功!" insert_statement = "INSERT INTO `investrategy`" \ "(`custom_time`,`author_id`,`content`,`variety_id`,`contract`,`direction`,`hands`," \ "`open_position`,`close_position`,`profit`)" \ "VALUES (%s,%s,%s,%s,%s,%s,%s,%s,%s,%s);" db_connection = MySQLConnection() cursor = db_connection.get_cursor() cursor.executemany(insert_statement, ready_to_save) db_connection.commit() db_connection.close() else: message = "数据上传成功,没有发现新数据!" except Exception as e: return jsonify(str(e)), 400 else: return jsonify(message) @staticmethod def drop_old_date_record(new_df, user_id): """删掉数据库最大时间及之前的数据""" db_connection = MySQLConnection() cursor = db_connection.get_cursor() query_statement = "SELECT `id`, MAX(`custom_time`) AS `max_date` FROM `investrategy` WHERE `author_id`=%s;" cursor.execute(query_statement, (user_id,)) fetch_one = cursor.fetchone() db_connection.close() if new_df.empty: return [] new_df['custom_time'] = pd.to_datetime(new_df['custom_time'], format='%Y-%m-%d') if fetch_one: # 有数据就删除已存在的最大日期之前的数据 max_date = pd.to_datetime(fetch_one['max_date'], format='%Y-%m-%d') save_df = new_df[max_date <= new_df['custom_time']].copy() # 截取数据 else: save_df = new_df.copy() save_df['custom_time'] = save_df['custom_time'].apply(lambda x: x.strftime('%Y-%m-%d')) return save_df.values.tolist() @staticmethod def drop_duplicates(new_df, user_id): # 遗弃，本方式不好用，出现未知错误 # 查询旧的数据 db_connection = MySQLConnection() cursor = db_connection.get_cursor() query_statement = "SELECT `custom_time`,`author_id`,`content`,`variety_id`,`contract`,`direction`,`hands`, " \ "`open_position`,`close_position`,`profit` " \ "FROM `investrategy` WHERE `author_id`=%s;" cursor.execute(query_statement, user_id) old_df = pd.DataFrame(cursor.fetchall()) db_connection.close() if old_df.empty: new_df['custom_time'] = pd.to_datetime(new_df['custom_time'], format='%Y-%m-%d') new_df['custom_time'] = new_df['custom_time'].apply(lambda x: x.strftime('%Y-%m-%d')) save_df = new_df.drop_duplicates(subset=['custom_time', 'content'], keep='last', inplace=False) else: old_df['custom_time'] = pd.to_datetime(old_df['custom_time'], format='%Y-%m-%d') old_df['custom_time'] = old_df['custom_time'].apply(lambda x: x.strftime('%Y-%m-%d')) new_df['custom_time'] = pd.to_datetime(new_df['custom_time'], format='%Y-%m-%d') new_df['custom_time'] = new_df['custom_time'].apply(lambda x: x.strftime('%Y-%m-%d')) concat_df = pd.concat([old_df, new_df, old_df]) save_df = concat_df.drop_duplicates(subset=['custom_time', 'content'], keep=False, inplace=False) if save_df.empty: return [] else: save_df = save_df.copy() # save_df['custom_time'] = save_df['custom_time'].apply(lambda x: x.strftime('%Y-%m-%d')) return save_df.values.tolist() class RetrieveInvestrategyView(MethodView): def get(self, rid): db_connection = MySQLConnection() cursor = db_connection.get_cursor() select_statement = "SELECT usertb.name,usertb.org_id,invsgytb.id,invsgytb.custom_time,invsgytb.content,invsgytb.variety_id,invsgytb.contract,invsgytb.direction,invsgytb.hands,invsgytb.open_position," \ "invsgytb.close_position,invsgytb.profit " \ "FROM `user_info` AS usertb INNER JOIN `investrategy` AS invsgytb ON " \ "invsgytb.id=%s AND usertb.id=invsgytb.author_id;" cursor.execute(select_statement, rid) record_item = cursor.fetchone() record_item['custom_time'] = record_item['custom_time'].strftime('%Y-%m-%d') record_item['org_name'] = ORGANIZATIONS.get(int(record_item['org_id']), '未知') record_item['open_position'] = float(record_item['open_position']) record_item['close_position'] = float(record_item['close_position']) record_item['profit'] = int(record_item['profit']) db_connection.close() return jsonify(record_item) def put(self, rid): body_json = request.json record_info = body_json.get('record_data') utoken = body_json.get('utoken') user_info = verify_json_web_token(utoken) user_id = user_info['uid'] # 不为空的信息判断 content = record_info.get('content', False) variety_id = record_info.get('variety_id', False) direction = record_info.get('direction', False) if not content or not variety_id or not direction: return jsonify("参数错误,NOT FOUND CONTENT,VARIETY,DIRECTION."), 400 # 组织信息 custom_time = record_info.get('custom_time') contract = record_info.get('contract', '') hands = record_info.get('hands', 0) open_position = record_info.get('open_position', 0) close_position = record_info.get('close_position', 0) profit = record_info.get('profit') # 存入数据库 save_invest_statement = "UPDATE `investrategy` SET " \ "`custom_time`=%s,`content`=%s,`variety_id`=%s,`contract`=%s,`direction`=%s,`hands`=%s," \ "`open_position`=%s,`close_position`=%s,`profit`=%s " \ "WHERE `id`=%s AND `author_id`=%s;" db_connection = MySQLConnection() cursor = db_connection.get_cursor() try: # 转换类型 custom_time = datetime.datetime.strptime(custom_time,'%Y-%m-%d') if custom_time else datetime.datetime.now() variety_id = int(variety_id) hands = int(hands) if hands else 0 open_position = float(open_position) if open_position else 0 close_position = float(close_position) if close_position else 0 profit = float(profit) if profit else 0 cursor.execute(save_invest_statement, (custom_time, content, variety_id, contract, direction, hands, open_position, close_position, profit, rid, user_id) ) db_connection.commit() except Exception as e: db_connection.rollback() db_connection.close() current_app.logger.error("更新投顾策略记录错误:" + str(e)) return jsonify("参数错误!无法修改。"), 400 else: db_connection.close() return jsonify("修改成功!"), 201 def delete(self, rid): utoken = request.args.get('utoken') user_info = verify_json_web_token(utoken) db_connection = MySQLConnection() try: user_id = int(user_info['uid']) delete_statement = "DELETE FROM `investrategy` " \ "WHERE `id`=%d AND `author_id`=%d;" % (rid, user_id) cursor = db_connection.get_cursor() lines_changed = cursor.execute(delete_statement) db_connection.commit() if lines_changed <= 0: raise ValueError("没有记录被删除>…<") except Exception as e: db_connection.rollback() db_connection.close() return jsonify(str(e)) else: db_connection.close() return jsonify("删除成功^.^!") class InvestrategyExportView(MethodView): def get(self): params = request.args utoken = params.get('utoken') user_info = verify_json_web_token(utoken) if not user_info: return jsonify("登录已过期!刷新网页重新登录."), 400 try: start_date = params.get('startDate') end_date = params.get('endDate') end_date = datetime.datetime.strptime(end_date, '%Y-%m-%d') + datetime.timedelta(days=1) end_date = (end_date + datetime.timedelta(seconds=-1)).strftime('%Y-%m-%d %H:%M:%S') except Exception: return jsonify("参数错误:DATE FORMAT ERROR!") query_statement = "SELECT usertb.name,usertb.org_id,invsgytb.custom_time,invsgytb.content,invsgytb.variety_id,invsgytb.contract,invsgytb.direction,invsgytb.hands," \ "invsgytb.open_position,invsgytb.close_position,invsgytb.profit,invsgytb.note " \ "FROM `user_info` AS usertb INNER JOIN `investrategy` AS invsgytb ON " \ "usertb.id=%s AND usertb.id=invsgytb.author_id AND (invsgytb.custom_time BETWEEN %s AND %s) " \ "ORDER BY invsgytb.custom_time ASC;" db_connection = MySQLConnection() cursor = db_connection.get_cursor() # 查询品种 query_variety = "SELECT `id`,`name` FROM `variety` WHERE `parent_id` IS NOT NULL;" cursor.execute(query_variety) variety_all = cursor.fetchall() variety_dict = {variety_item["id"]: variety_item['name'] for variety_item in variety_all} cursor.execute(query_statement, (user_info['uid'], start_date, end_date)) records_all = cursor.fetchall() db_connection.close() # 生成承载数据的文件 t = "%.4f" % time.time() md5_hash = hashlib.md5() md5_hash.update(t.encode('utf-8')) md5_hash.update(user_info['name'].encode('utf-8')) md5_str = md5_hash.hexdigest() file_folder = os.path.join(BASE_DIR, 'fileStore/exports/') if not os.path.exists(file_folder): os.makedirs(file_folder) file_path = os.path.join(file_folder, '{}.xlsx'.format(md5_str)) file_records = list() for record_item in records_all: row_content = list() row_content.append(record_item['custom_time'].strftime("%Y-%m-%d")) row_content.append(ORGANIZATIONS.get(record_item['org_id'], '未知')) row_content.append(record_item['name']) row_content.append(record_item['content']) row_content.append(variety_dict.get(record_item['variety_id'], '')) row_content.append(record_item['contract']) row_content.append(record_item['direction']) row_content.append(record_item['hands']) row_content.append(float(record_item['open_position'])) row_content.append(float(record_item['close_position'])) row_content.append(float(record_item['profit'])) row_content.append(record_item['note']) file_records.append(row_content) export_df = pd.DataFrame(file_records) export_df.columns = ['日期', '部门小组', '姓名', '策略内容', '品种', '合约', '方向', '手数', '策略开仓', '策略平仓', '策略结果','备注'] export_df.to_excel( excel_writer=file_path, index=False, sheet_name='投顾策略记录' ) return send_from_directory(directory=file_folder, filename='{}.xlsx'.format(md5_str), as_attachment=True, attachment_filename='{}.xlsx'.format(md5_str) )

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""" Tio Booleano Álgebra Booleana, criada por George Boole 2 constantes: Verdadeiro ou Falso True -> Verdadeiro False -> Falso A primeira letra precisa ser maiúscula """ falso = False verdadeiro = True print(falso) print(verdadeiro) print(type(verdadeiro)) # Operações # Negação(not) : troca do valor atual para o seu contrário print(not falso) print(not verdadeiro) # Ou(or) : é uma operação binária onde um ou o outro precisa ser verdadeiro para retornar verdadeiro print(falso or verdadeiro) # E(and) : é uma operação binária onde ambos os valores devem ser verdadeiro para retornar verdadeiro print(falso and verdadeiro) print(not falso and verdadeiro) # Você pode comparar valores e variáveis para retornar um valor booleano print(5 < 6) print(3 > 4)

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# -*- coding: utf-8 -*- import datetime from south.db import db from south.v2 import SchemaMigration from django.db import models class Migration(SchemaMigration): def forwards(self, orm): # Deleting model 'CategoryESS' db.delete_table('coop_local_categoryess') def backwards(self, orm): # Adding model 'CategoryESS' db.create_table('coop_local_categoryess', ( ('label', self.gf('django.db.models.fields.CharField')(max_length=100, blank=True)), ('description', self.gf('django.db.models.fields.TextField')(blank=True)), ('slug', self.gf('django_extensions.db.fields.AutoSlugField')(populate_from='label', allow_duplicates=False, max_length=50, separator=u'-', blank=True, overwrite=True)), ('id', self.gf('django.db.models.fields.AutoField')(primary_key=True)), )) db.send_create_signal('coop_local', ['CategoryESS']) models = { 'auth.group': { 'Meta': {'object_name': 'Group'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '80'}), 'permissions': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Permission']", 'symmetrical': 'False', 'blank': 'True'}) }, 'auth.permission': { 'Meta': {'ordering': "('content_type__app_label', 'content_type__model', 'codename')", 'unique_together': "(('content_type', 'codename'),)", 'object_name': 'Permission'}, 'codename': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'content_type': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['contenttypes.ContentType']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '50'}) }, 'auth.user': { 'Meta': {'object_name': 'User'}, 'date_joined': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'email': ('django.db.models.fields.EmailField', [], {'max_length': '75', 'blank': 'True'}), 'first_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'blank': 'True'}), 'groups': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Group']", 'symmetrical': 'False', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'is_active': ('django.db.models.fields.BooleanField', [], {'default': 'True'}), 'is_staff': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'is_superuser': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'last_login': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'last_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'blank': 'True'}), 'password': ('django.db.models.fields.CharField', [], {'max_length': '128'}), 'user_permissions': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Permission']", 'symmetrical': 'False', 'blank': 'True'}), 'username': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '30'}) }, 'contenttypes.contenttype': { 'Meta': {'ordering': "('name',)", 'unique_together': "(('app_label', 'model'),)", 'object_name': 'ContentType', 'db_table': "'django_content_type'"}, 'app_label': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'model': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '100'}) }, 'coop_cms.articlecategory': { 'Meta': {'object_name': 'ArticleCategory'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'ordering': ('django.db.models.fields.IntegerField', [], {'default': '0'}), 'slug': ('django_extensions.db.fields.AutoSlugField', [], {'allow_duplicates': 'False', 'max_length': '100', 'separator': "u'-'", 'blank': 'True', 'unique': 'True', 'populate_from': "'name'", 'overwrite': 'False'}) }, 'coop_cms.navtype': { 'Meta': {'object_name': 'NavType'}, 'content_type': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['contenttypes.ContentType']", 'unique': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'label_rule': ('django.db.models.fields.IntegerField', [], {'default': '0'}), 'search_field': ('django.db.models.fields.CharField', [], {'default': "''", 'max_length': '200', 'blank': 'True'}) }, 'coop_geo.area': { 'Meta': {'object_name': 'Area'}, 'area_type': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['coop_geo.AreaType']"}), 'created': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now', 'null': 'True', 'blank': 'True'}), 'default_location': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'associated_area'", 'null': 'True', 'to': "orm['coop_geo.Location']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'label': ('django.db.models.fields.CharField', [], {'max_length': '150'}), 'modified': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now', 'null': 'True', 'blank': 'True'}), 'polygon': ('django.contrib.gis.db.models.fields.MultiPolygonField', [], {'null': 'True', 'blank': 'True'}), 'reference': ('django.db.models.fields.CharField', [], {'max_length': '150', 'null': 'True', 'blank': 'True'}), 'related_areas': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['coop_geo.Area']", 'through': "orm['coop_geo.AreaRelations']", 'symmetrical': 'False'}), 'update_auto': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'uri': ('django.db.models.fields.CharField', [], {'max_length': '250', 'null': 'True', 'blank': 'True'}), 'uri_mode': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '1'}), 'uuid': ('django.db.models.fields.CharField', [], {'default': "'cuus73RXRUQ59mVZbAuoc8'", 'max_length': '50', 'unique': 'True', 'null': 'True'}) }, 'coop_geo.arealink': { 'Meta': {'object_name': 'AreaLink'}, 'content_type': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['contenttypes.ContentType']", 'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'location': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['coop_geo.Area']", 'null': 'True', 'blank': 'True'}), 'object_id': ('django.db.models.fields.PositiveIntegerField', [], {}) }, 'coop_geo.arearelations': { 'Meta': {'object_name': 'AreaRelations'}, 'child': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'parent_rels'", 'to': "orm['coop_geo.Area']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'parent': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'child_rels'", 'to': "orm['coop_geo.Area']"}) }, 'coop_geo.areatype': { 'Meta': {'object_name': 'AreaType'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'label': ('django.db.models.fields.CharField', [], {'max_length': '150'}), 'txt_idx': ('django.db.models.fields.CharField', [], {'max_length': "'50'"}) }, 'coop_geo.located': { 'Meta': {'object_name': 'Located'}, 'category': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['coop_geo.LocationCategory']", 'null': 'True', 'blank': 'True'}), 'content_type': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['contenttypes.ContentType']", 'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'location': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['coop_geo.Location']", 'null': 'True', 'blank': 'True'}), 'main_location': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'object_id': ('django.db.models.fields.PositiveIntegerField', [], {}) }, 'coop_geo.location': { 'Meta': {'object_name': 'Location'}, 'adr1': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'adr2': ('django.db.models.fields.CharField', [], {'max_length': '100', 'null': 'True', 'blank': 'True'}), 'area': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['coop_geo.Area']", 'null': 'True', 'blank': 'True'}), 'city': ('django.db.models.fields.CharField', [], {'max_length': '100', 'null': 'True', 'blank': 'True'}), 'country': ('django.db.models.fields.CharField', [], {'max_length': '100', 'null': 'True', 'blank': 'True'}), 'created': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now', 'null': 'True', 'blank': 'True'}), 'geohash': ('django.db.models.fields.CharField', [], {'max_length': '20', 'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'is_ref_center': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'label': ('django.db.models.fields.CharField', [], {'max_length': '150', 'null': 'True', 'blank': 'True'}), 'modified': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now', 'null': 'True', 'blank': 'True'}), 'owner': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['auth.User']", 'null': 'True', 'blank': 'True'}), 'point': ('django.contrib.gis.db.models.fields.PointField', [], {'null': 'True', 'blank': 'True'}), 'uri': ('django.db.models.fields.CharField', [], {'max_length': '250', 'null': 'True', 'blank': 'True'}), 'uri_mode': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '1'}), 'uuid': ('django.db.models.fields.CharField', [], {'default': "'EX7SCfB4bSEnfqTVoftmSe'", 'max_length': '50', 'unique': 'True', 'null': 'True'}), 'x_code': ('django.db.models.fields.CharField', [], {'max_length': '20', 'null': 'True', 'blank': 'True'}), 'zipcode': ('django.db.models.fields.CharField', [], {'max_length': '5', 'null': 'True', 'blank': 'True'}) }, 'coop_geo.locationcategory': { 'Meta': {'ordering': "['label']", 'object_name': 'LocationCategory'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'label': ('django.db.models.fields.CharField', [], {'max_length': '60'}), 'slug': ('django_extensions.db.fields.AutoSlugField', [], {'allow_duplicates': 'False', 'max_length': '50', 'separator': "u'-'", 'blank': 'True', 'populate_from': "'label'", 'overwrite': 'False'}) }, 'coop_local.activitynomenclature': { 'Meta': {'ordering': "['tree_id', 'lft']", 'unique_together': "(('label', 'parent'),)", 'object_name': 'ActivityNomenclature'}, 'avise': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['coop_local.ActivityNomenclatureAvise']", 'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'label': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'level': ('django.db.models.fields.PositiveIntegerField', [], {'db_index': 'True'}), 'lft': ('django.db.models.fields.PositiveIntegerField', [], {'db_index': 'True'}), 'parent': ('mptt.fields.TreeForeignKey', [], {'blank': 'True', 'related_name': "'children'", 'null': 'True', 'to': "orm['coop_local.ActivityNomenclature']"}), 'path': ('django.db.models.fields.CharField', [], {'max_length': '306'}), 'rght': ('django.db.models.fields.PositiveIntegerField', [], {'db_index': 'True'}), 'tree_id': ('django.db.models.fields.PositiveIntegerField', [], {'db_index': 'True'}) }, 'coop_local.activitynomenclatureavise': { 'Meta': {'ordering': "['label']", 'object_name': 'ActivityNomenclatureAvise'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'label': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '100'}) }, 'coop_local.agreementiae': { 'Meta': {'object_name': 'AgreementIAE'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'label': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '100'}) }, 'coop_local.article': { 'Meta': {'object_name': 'Article'}, 'category': ('django.db.models.fields.related.ForeignKey', [], {'default': 'None', 'related_name': "'coop_local_article_rel'", 'null': 'True', 'blank': 'True', 'to': "orm['coop_cms.ArticleCategory']"}), 'content': ('django.db.models.fields.TextField', [], {'default': "u'Page content'", 'blank': 'True'}), 'created': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now', 'blank': 'True'}), 'headline': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'in_newsletter': ('django.db.models.fields.BooleanField', [], {'default': 'True'}), 'isSection': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'is_homepage': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'logo': ('django.db.models.fields.files.ImageField', [], {'default': "''", 'max_length': '100', 'null': 'True', 'blank': 'True'}), 'modified': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now', 'blank': 'True'}), 'organization': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'articles'", 'null': 'True', 'to': "orm['coop_local.Organization']"}), 'person': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'articles'", 'null': 'True', 'to': "orm['coop_local.Person']"}), 'publication': ('django.db.models.fields.IntegerField', [], {'default': '1'}), 'remote_organization_label': ('django.db.models.fields.CharField', [], {'max_length': '250', 'null': 'True', 'blank': 'True'}), 'remote_organization_uri': ('django.db.models.fields.CharField', [], {'max_length': '255', 'blank': 'True'}), 'remote_person_label': ('django.db.models.fields.CharField', [], {'max_length': '250', 'null': 'True', 'blank': 'True'}), 'remote_person_uri': ('django.db.models.fields.CharField', [], {'max_length': '255', 'blank': 'True'}), 'slug': ('django_extensions.db.fields.AutoSlugField', [], {'allow_duplicates': 'False', 'max_length': '100', 'separator': "u'-'", 'blank': 'True', 'unique': 'True', 'populate_from': "'title'", 'overwrite': 'True'}), 'summary': ('django.db.models.fields.TextField', [], {'default': "''", 'blank': 'True'}), 'temp_logo': ('django.db.models.fields.files.ImageField', [], {'default': "''", 'max_length': '100', 'null': 'True', 'blank': 'True'}), 'template': ('django.db.models.fields.CharField', [], {'default': "''", 'max_length': '200', 'blank': 'True'}), 'title': ('django.db.models.fields.TextField', [], {'default': "u'Page title'", 'blank': 'True'}), 'uri': ('django.db.models.fields.CharField', [], {'max_length': '250', 'null': 'True', 'blank': 'True'}), 'uri_mode': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '1'}), 'uuid': ('django.db.models.fields.CharField', [], {'default': "'KADiR4Yc7rtw2ZJjxvvKun'", 'max_length': '50', 'unique': 'True', 'null': 'True'}) }, 'coop_local.categoryiae': { 'Meta': {'object_name': 'CategoryIAE'}, 'description': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'label': ('django.db.models.fields.CharField', [], {'max_length': '100', 'blank': 'True'}), 'slug': ('django_extensions.db.fields.AutoSlugField', [], {'allow_duplicates': 'False', 'max_length': '50', 'separator': "u'-'", 'blank': 'True', 'populate_from': "'label'", 'overwrite': 'True'}) }, 'coop_local.client': { 'Meta': {'ordering': "['title']", 'object_name': 'Client', '_ormbases': ['coop_local.Organization']}, 'organization_ptr': ('django.db.models.fields.related.OneToOneField', [], {'to': "orm['coop_local.Organization']", 'unique': 'True', 'primary_key': 'True'}) }, 'coop_local.clienttarget': { 'Meta': {'object_name': 'ClientTarget'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'label': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '100'}) }, 'coop_local.contact': { 'Meta': {'ordering': "['category']", 'object_name': 'Contact'}, 'category': ('django.db.models.fields.PositiveSmallIntegerField', [], {}), 'content': ('django.db.models.fields.CharField', [], {'max_length': '250'}), 'content_type': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['contenttypes.ContentType']", 'null': 'True', 'blank': 'True'}), 'created': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now', 'null': 'True', 'blank': 'True'}), 'details': ('django.db.models.fields.CharField', [], {'max_length': '100', 'blank': 'True'}), 'display': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '1'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'modified': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now', 'null': 'True', 'blank': 'True'}), 'object_id': ('django.db.models.fields.PositiveIntegerField', [], {}), 'uri': ('django.db.models.fields.CharField', [], {'max_length': '250', 'null': 'True', 'blank': 'True'}), 'uri_mode': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '1'}), 'uuid': ('django.db.models.fields.CharField', [], {'default': "'ctrAYrGRzSiZpQTdCjcdfB'", 'max_length': '50', 'unique': 'True', 'null': 'True'}) }, 'coop_local.document': { 'Meta': {'object_name': 'Document'}, 'attachment': ('django.db.models.fields.files.FileField', [], {'max_length': '255'}), 'description': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '100', 'blank': 'True'}), 'organization': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['coop_local.Organization']"}), 'type': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['coop_local.DocumentType']", 'null': 'True', 'blank': 'True'}) }, 'coop_local.documenttype': { 'Meta': {'object_name': 'DocumentType'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '100', 'blank': 'True'}) }, 'coop_local.engagement': { 'Meta': {'object_name': 'Engagement'}, 'created': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now', 'null': 'True', 'blank': 'True'}), 'engagement_display': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '1'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'modified': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now', 'null': 'True', 'blank': 'True'}), 'org_admin': ('django.db.models.fields.BooleanField', [], {'default': 'True'}), 'organization': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['coop_local.Organization']"}), 'person': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'engagements'", 'to': "orm['coop_local.Person']"}), 'remote_role_label': ('django.db.models.fields.CharField', [], {'max_length': '100', 'blank': 'True'}), 'remote_role_uri': ('django.db.models.fields.CharField', [], {'max_length': '250', 'null': 'True', 'blank': 'True'}), 'role': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['coop_local.Role']", 'null': 'True', 'blank': 'True'}), 'role_detail': ('django.db.models.fields.CharField', [], {'max_length': '100', 'blank': 'True'}), 'uri': ('django.db.models.fields.CharField', [], {'max_length': '250', 'null': 'True', 'blank': 'True'}), 'uri_mode': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '1'}), 'uuid': ('django.db.models.fields.CharField', [], {'default': "'bB3zURYMsAhRzAKJu7TXYb'", 'max_length': '50', 'unique': 'True', 'null': 'True'}) }, 'coop_local.exchange': { 'Meta': {'ordering': "('-modified',)", 'object_name': 'Exchange'}, 'area': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'exchange_area'", 'null': 'True', 'to': "orm['coop_geo.Area']"}), 'created': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now', 'null': 'True', 'blank': 'True'}), 'description': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'etype': ('django.db.models.fields.PositiveSmallIntegerField', [], {}), 'eway': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '1'}), 'expiration': ('django.db.models.fields.DateField', [], {'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'location': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'exchange_location'", 'null': 'True', 'to': "orm['coop_geo.Location']"}), 'methods': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['coop_local.ExchangeMethod']", 'symmetrical': 'False'}), 'modified': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now', 'null': 'True', 'blank': 'True'}), 'organization': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'exchanges'", 'null': 'True', 'to': "orm['coop_local.Organization']"}), 'permanent': ('django.db.models.fields.BooleanField', [], {'default': 'True'}), 'person': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['coop_local.Person']", 'null': 'True', 'blank': 'True'}), 'products': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['coop_local.Product']", 'symmetrical': 'False'}), 'remote_organization_label': ('django.db.models.fields.CharField', [], {'max_length': '250', 'null': 'True', 'blank': 'True'}), 'remote_organization_uri': ('django.db.models.fields.CharField', [], {'max_length': '255', 'blank': 'True'}), 'remote_person_label': ('django.db.models.fields.CharField', [], {'max_length': '250', 'null': 'True', 'blank': 'True'}), 'remote_person_uri': ('django.db.models.fields.CharField', [], {'max_length': '255', 'blank': 'True'}), 'slug': ('django_extensions.db.fields.AutoSlugField', [], {'allow_duplicates': 'False', 'max_length': '50', 'separator': "u'-'", 'blank': 'True', 'populate_from': "'title'", 'overwrite': 'True'}), 'title': ('django.db.models.fields.CharField', [], {'max_length': '250'}), 'uri': ('django.db.models.fields.CharField', [], {'max_length': '250', 'null': 'True', 'blank': 'True'}), 'uri_mode': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '1'}), 'uuid': ('django.db.models.fields.CharField', [], {'default': "'rZG3Kc5kHDWtGCErjH4b7b'", 'max_length': '50', 'unique': 'True', 'null': 'True'}) }, 'coop_local.exchangemethod': { 'Meta': {'object_name': 'ExchangeMethod'}, 'etypes': ('coop.utils.fields.MultiSelectField', [], {'max_length': '250', 'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'label': ('django.db.models.fields.CharField', [], {'max_length': '250'}), 'uri': ('django.db.models.fields.CharField', [], {'max_length': '250', 'blank': 'True'}) }, 'coop_local.guaranty': { 'Meta': {'object_name': 'Guaranty'}, 'description': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'logo': ('sorl.thumbnail.fields.ImageField', [], {'max_length': '100', 'null': 'True', 'blank': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '100', 'blank': 'True'}), 'type': ('django.db.models.fields.IntegerField', [], {}) }, 'coop_local.legalstatus': { 'Meta': {'object_name': 'LegalStatus'}, 'description': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'label': ('django.db.models.fields.CharField', [], {'max_length': '100', 'blank': 'True'}), 'slug': ('django_extensions.db.fields.AutoSlugField', [], {'allow_duplicates': 'False', 'max_length': '50', 'separator': "u'-'", 'blank': 'True', 'populate_from': "'label'", 'overwrite': 'True'}) }, 'coop_local.link': { 'Meta': {'object_name': 'Link'}, 'content_type': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['contenttypes.ContentType']", 'null': 'True', 'blank': 'True'}), 'created': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now', 'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'modified': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now', 'null': 'True', 'blank': 'True'}), 'object_id': ('django.db.models.fields.PositiveIntegerField', [], {}), 'object_uri': ('django.db.models.fields.URLField', [], {'max_length': '200', 'blank': 'True'}), 'predicate': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['coop_local.LinkProperty']"}) }, 'coop_local.linkproperty': { 'Meta': {'object_name': 'LinkProperty'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'label': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'uri': ('django.db.models.fields.URLField', [], {'max_length': '200', 'blank': 'True'}) }, 'coop_local.navtree': { 'Meta': {'object_name': 'NavTree'}, 'created': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now', 'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'last_update': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'blank': 'True'}), 'modified': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now', 'null': 'True', 'blank': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'default': "'default'", 'unique': 'True', 'max_length': '100', 'db_index': 'True'}), 'types': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['coop_cms.NavType']", 'symmetrical': 'False', 'blank': 'True'}), 'uri': ('django.db.models.fields.CharField', [], {'max_length': '250', 'null': 'True', 'blank': 'True'}), 'uri_mode': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '1'}), 'uuid': ('django.db.models.fields.CharField', [], {'default': "'dEnNE5h9RCwoxpDANraN4o'", 'max_length': '50', 'unique': 'True', 'null': 'True'}) }, 'coop_local.network': { 'Meta': {'ordering': "['title']", 'object_name': 'Network', '_ormbases': ['coop_local.Organization']}, 'organization_ptr': ('django.db.models.fields.related.OneToOneField', [], {'to': "orm['coop_local.Organization']", 'unique': 'True', 'primary_key': 'True'}) }, 'coop_local.offer': { 'Meta': {'object_name': 'Offer'}, 'activity': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['coop_local.ActivityNomenclature']"}), 'coverage': ('django.db.models.fields.CommaSeparatedIntegerField', [], {'max_length': '100', 'null': 'True', 'blank': 'True'}), 'description': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'practical_modalities': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'provider': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['coop_local.Organization']"}), 'targets': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': "orm['coop_local.ClientTarget']", 'null': 'True', 'blank': 'True'}), 'technical_means': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'valuation': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'workforce': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'blank': 'True'}) }, 'coop_local.organization': { 'Meta': {'ordering': "['title']", 'object_name': 'Organization'}, 'acronym': ('django.db.models.fields.CharField', [], {'max_length': '100', 'null': 'True', 'blank': 'True'}), 'active': ('django.db.models.fields.BooleanField', [], {'default': 'True'}), 'birth': ('django.db.models.fields.DateField', [], {'null': 'True', 'blank': 'True'}), 'category': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': "orm['coop_local.OrganizationCategory']", 'null': 'True', 'blank': 'True'}), 'created': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now', 'null': 'True', 'blank': 'True'}), 'description': ('django.db.models.fields.TextField', [], {'null': 'True', 'blank': 'True'}), 'email': ('django.db.models.fields.EmailField', [], {'max_length': '75', 'null': 'True', 'blank': 'True'}), 'email_sha1': ('django.db.models.fields.CharField', [], {'max_length': '250', 'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'logo': ('sorl.thumbnail.fields.ImageField', [], {'max_length': '100', 'null': 'True', 'blank': 'True'}), 'members': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['coop_local.Person']", 'through': "orm['coop_local.Engagement']", 'symmetrical': 'False'}), 'modified': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now', 'null': 'True', 'blank': 'True'}), 'notes': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'pref_address': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'pref_adress'", 'null': 'True', 'to': "orm['coop_geo.Location']"}), 'pref_email': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'pref_email'", 'null': 'True', 'to': "orm['coop_local.Contact']"}), 'pref_label': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '1'}), 'pref_phone': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'pref_phone'", 'null': 'True', 'to': "orm['coop_local.Contact']"}), 'relations': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['coop_local.Organization']", 'through': "orm['coop_local.Relation']", 'symmetrical': 'False'}), 'slug': ('django_extensions.db.fields.AutoSlugField', [], {'allow_duplicates': 'False', 'max_length': '50', 'separator': "u'-'", 'blank': 'True', 'populate_from': "'title'", 'overwrite': 'True'}), 'subtitle': ('django.db.models.fields.CharField', [], {'max_length': '250', 'null': 'True', 'blank': 'True'}), 'title': ('django.db.models.fields.CharField', [], {'max_length': '250'}), 'uri': ('django.db.models.fields.CharField', [], {'max_length': '250', 'null': 'True', 'blank': 'True'}), 'uri_mode': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '1'}), 'uuid': ('django.db.models.fields.CharField', [], {'default': "'nSgNXC8m9dWyM2GWEQeboU'", 'max_length': '50', 'unique': 'True', 'null': 'True'}), 'web': ('django.db.models.fields.URLField', [], {'max_length': '200', 'null': 'True', 'blank': 'True'}) }, 'coop_local.organizationcategory': { 'Meta': {'object_name': 'OrganizationCategory'}, 'description': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'label': ('django.db.models.fields.CharField', [], {'max_length': '100', 'blank': 'True'}), 'slug': ('django_extensions.db.fields.AutoSlugField', [], {'allow_duplicates': 'False', 'max_length': '50', 'separator': "u'-'", 'blank': 'True', 'populate_from': "'label'", 'overwrite': 'True'}) }, 'coop_local.person': { 'Meta': {'object_name': 'Person'}, 'category': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': "orm['coop_local.PersonCategory']", 'null': 'True', 'blank': 'True'}), 'created': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now', 'null': 'True', 'blank': 'True'}), 'email': ('django.db.models.fields.EmailField', [], {'max_length': '75', 'blank': 'True'}), 'email_sha1': ('django.db.models.fields.CharField', [], {'max_length': '250', 'null': 'True', 'blank': 'True'}), 'first_name': ('django.db.models.fields.CharField', [], {'max_length': '100', 'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'last_name': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'location': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['coop_geo.Location']", 'null': 'True', 'blank': 'True'}), 'location_display': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '2'}), 'modified': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now', 'null': 'True', 'blank': 'True'}), 'notes': ('django.db.models.fields.TextField', [], {'null': 'True', 'blank': 'True'}), 'remote_organization_label': ('django.db.models.fields.CharField', [], {'max_length': '250', 'null': 'True', 'blank': 'True'}), 'remote_organization_uri': ('django.db.models.fields.CharField', [], {'max_length': '255', 'blank': 'True'}), 'structure': ('django.db.models.fields.CharField', [], {'max_length': '100', 'blank': 'True'}), 'uri': ('django.db.models.fields.CharField', [], {'max_length': '250', 'null': 'True', 'blank': 'True'}), 'uri_mode': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '1'}), 'user': ('django.db.models.fields.related.OneToOneField', [], {'to': "orm['auth.User']", 'unique': 'True', 'null': 'True', 'blank': 'True'}), 'username': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '100', 'blank': 'True'}), 'uuid': ('django.db.models.fields.CharField', [], {'default': "'g4uvSE7yeBngafL2VxzgjK'", 'max_length': '50', 'unique': 'True', 'null': 'True'}) }, 'coop_local.personcategory': { 'Meta': {'object_name': 'PersonCategory'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'label': ('django.db.models.fields.CharField', [], {'max_length': '100', 'blank': 'True'}), 'slug': ('django_extensions.db.fields.AutoSlugField', [], {'allow_duplicates': 'False', 'max_length': '50', 'separator': "u'-'", 'blank': 'True', 'populate_from': "'label'", 'overwrite': 'True'}) }, 'coop_local.product': { 'Meta': {'ordering': "['-modified']", 'object_name': 'Product'}, 'created': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now', 'null': 'True', 'blank': 'True'}), 'description': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'modified': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now', 'null': 'True', 'blank': 'True'}), 'organization': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'products'", 'null': 'True', 'to': "orm['coop_local.Organization']"}), 'remote_organization_label': ('django.db.models.fields.CharField', [], {'max_length': '250', 'blank': 'True'}), 'remote_organization_uri': ('django.db.models.fields.CharField', [], {'max_length': '200', 'blank': 'True'}), 'slug': ('django_extensions.db.fields.AutoSlugField', [], {'allow_duplicates': 'False', 'max_length': '50', 'separator': "u'-'", 'blank': 'True', 'populate_from': "'title'", 'overwrite': 'True'}), 'title': ('django.db.models.fields.CharField', [], {'max_length': '250', 'blank': 'True'}), 'uri': ('django.db.models.fields.CharField', [], {'max_length': '250', 'null': 'True', 'blank': 'True'}), 'uri_mode': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '1'}), 'uuid': ('django.db.models.fields.CharField', [], {'default': "'RcqAhbVFvBtKaevL83FEsf'", 'max_length': '50', 'unique': 'True', 'null': 'True'}) }, 'coop_local.provider': { 'Meta': {'ordering': "['title']", 'object_name': 'Provider', '_ormbases': ['coop_local.Organization']}, 'added_value': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'agreement_iae': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': "orm['coop_local.AgreementIAE']", 'null': 'True', 'blank': 'True'}), 'annual_integration_number': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'blank': 'True'}), 'annual_revenue': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'blank': 'True'}), 'author': ('django.db.models.fields.CharField', [], {'max_length': '100', 'blank': 'True'}), 'bdis_id': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'blank': 'True'}), 'brief_description': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'category_iae': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': "orm['coop_local.CategoryIAE']", 'null': 'True', 'blank': 'True'}), 'correspondence': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'creation': ('django.db.models.fields.DateField', [], {'auto_now_add': 'True', 'blank': 'True'}), 'guaranties': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': "orm['coop_local.Guaranty']", 'null': 'True', 'blank': 'True'}), 'integration_workforce': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'blank': 'True'}), 'legal_status': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['coop_local.LegalStatus']", 'null': 'True', 'blank': 'True'}), 'modification': ('django.db.models.fields.DateField', [], {'auto_now': 'True', 'blank': 'True'}), 'organization_ptr': ('django.db.models.fields.related.OneToOneField', [], {'to': "orm['coop_local.Organization']", 'unique': 'True', 'primary_key': 'True'}), 'production_workforce': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'blank': 'True'}), 'siret': ('django.db.models.fields.CharField', [], {'max_length': '14', 'blank': 'True'}), 'status': ('django.db.models.fields.CharField', [], {'max_length': '1', 'blank': 'True'}), 'supervision_workforce': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'blank': 'True'}), 'transmission': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'blank': 'True'}), 'transmission_date': ('django.db.models.fields.DateField', [], {'null': 'True', 'blank': 'True'}), 'transverse_themes': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': "orm['coop_local.TransverseTheme']", 'null': 'True', 'blank': 'True'}), 'validation': ('django.db.models.fields.DateField', [], {'null': 'True', 'blank': 'True'}), 'workforce': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'blank': 'True'}) }, 'coop_local.reference': { 'Meta': {'object_name': 'Reference'}, 'client_name': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'from_year': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'organization': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['coop_local.Organization']"}), 'services': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'to_year': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'blank': 'True'}) }, 'coop_local.relation': { 'Meta': {'object_name': 'Relation'}, 'created': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now', 'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'modified': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now', 'null': 'True', 'blank': 'True'}), 'reltype': ('django.db.models.fields.PositiveSmallIntegerField', [], {}), 'source': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'source'", 'to': "orm['coop_local.Organization']"}), 'target': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'target'", 'to': "orm['coop_local.Organization']"}) }, 'coop_local.role': { 'Meta': {'object_name': 'Role'}, 'category': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['coop_local.RoleCategory']", 'null': 'True', 'blank': 'True'}), 'created': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now', 'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'label': ('django.db.models.fields.CharField', [], {'max_length': '120'}), 'modified': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now', 'null': 'True', 'blank': 'True'}), 'slug': ('autoslug.fields.AutoSlugField', [], {'unique': 'True', 'max_length': '50', 'populate_from': "'label'", 'unique_with': '()'}), 'uri': ('django.db.models.fields.CharField', [], {'max_length': '250', 'null': 'True', 'blank': 'True'}), 'uri_mode': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '1'}), 'uuid': ('django.db.models.fields.CharField', [], {'default': "'tyeggzi65vZf2nTDrxSZCY'", 'max_length': '50', 'unique': 'True', 'null': 'True'}) }, 'coop_local.rolecategory': { 'Meta': {'ordering': "['label']", 'object_name': 'RoleCategory'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'label': ('django.db.models.fields.CharField', [], {'max_length': '60'}), 'slug': ('django_extensions.db.fields.AutoSlugField', [], {'allow_duplicates': 'False', 'max_length': '50', 'separator': "u'-'", 'blank': 'True', 'populate_from': "'label'", 'overwrite': 'True'}), 'uri': ('django.db.models.fields.CharField', [], {'max_length': '250', 'blank': 'True'}) }, 'coop_local.siteprefs': { 'Meta': {'object_name': 'SitePrefs'}, 'main_organization': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'main_org'", 'null': 'True', 'to': "orm['coop_local.Organization']"}), 'preferences_ptr': ('django.db.models.fields.related.OneToOneField', [], {'to': "orm['preferences.Preferences']", 'unique': 'True', 'primary_key': 'True'}) }, 'coop_local.tag': { 'Meta': {'object_name': 'Tag'}, 'concept_uri': ('django.db.models.fields.CharField', [], {'max_length': '250', 'blank': 'True'}), 'created': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now', 'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'language': ('django.db.models.fields.CharField', [], {'default': "'fr'", 'max_length': '10'}), 'modified': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now', 'null': 'True', 'blank': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'person': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['coop_local.Person']", 'null': 'True', 'blank': 'True'}), 'person_uri': ('django.db.models.fields.CharField', [], {'max_length': '250', 'blank': 'True'}), 'slug': ('django.db.models.fields.SlugField', [], {'unique': 'True', 'max_length': '100'}), 'uri': ('django.db.models.fields.CharField', [], {'max_length': '250', 'null': 'True', 'blank': 'True'}), 'uri_mode': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '1'}), 'uuid': ('django.db.models.fields.CharField', [], {'default': "'jGZRKqfGKrX8btmCVL7mDA'", 'max_length': '50', 'unique': 'True', 'null': 'True'}) }, 'coop_local.taggeditem': { 'Meta': {'object_name': 'TaggedItem'}, 'content_type': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'coop_local_taggeditem_taggeditem_items'", 'to': "orm['contenttypes.ContentType']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'object_id': ('django.db.models.fields.IntegerField', [], {'db_index': 'True'}), 'tag': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'coop_local_taggeditem_items'", 'to': "orm['coop_local.Tag']"}) }, 'coop_local.transversetheme': { 'Meta': {'object_name': 'TransverseTheme'}, 'description': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '100', 'blank': 'True'}) }, 'preferences.preferences': { 'Meta': {'object_name': 'Preferences'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'sites': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': "orm['sites.Site']", 'null': 'True', 'blank': 'True'}) }, 'sites.site': { 'Meta': {'ordering': "('domain',)", 'object_name': 'Site', 'db_table': "'django_site'"}, 'domain': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '50'}) } } complete_apps = ['coop_local']

[ "[email protected]" ]

[email protected]

bfc0ff00fcc96a5888f1b2574bfc1dd1c21a421b

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/dasy/__main__.py

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[]

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Chitrank-Dixit/dasy

896af55736b2fb8c84a889f1949fa28f48ee632a

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refs/heads/master

2023-04-05T14:41:32.057940

2021-04-11T17:12:37

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#!/usr/bin/env python3 from .dasy import checkCommand if __name__ == "__main__": checkCommand()

[ "[email protected]" ]

[email protected]

0c96381cfe7098294ceee4776eec3458bc497a29

ede96590eee4880ff83d1f1d8db5229e92c6e919

/leasing/migrations/0042_contract_sign_fields.py

84877db9dd92cea1360228eff5704d0bf76a4a3d

[ "MIT" ]

permissive

igordavydsson/mvj

a4c5b39e7be9f95e15a2e906ad61b98611998063

b467c6229f9d458d56b66f628b0841adb67a2970

refs/heads/master

2020-04-22T20:42:06.650182

2019-02-12T13:50:57

null

0

null

UTF-8

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1,033

py

# Generated by Django 2.1.5 on 2019-02-12 07:13 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('leasing', '0041_add_collateral'), ] operations = [ migrations.AddField( model_name='contract', name='first_call_sent', field=models.DateField(blank=True, null=True, verbose_name='First call sent'), ), migrations.AddField( model_name='contract', name='second_call_sent', field=models.DateField(blank=True, null=True, verbose_name='Second call sent'), ), migrations.AddField( model_name='contract', name='sign_by_date', field=models.DateField(blank=True, null=True, verbose_name='Sign by date'), ), migrations.AddField( model_name='contract', name='third_call_sent', field=models.DateField(blank=True, null=True, verbose_name='Third call sent'), ), ]

[ "[email protected]" ]

[email protected]

e29f5a011a08a9ecc107258a5a197159ce95d9d0

290394852b7fb70f791c6c4bb96141523ab96090

/ExpertIdeas_WikipediaProxyServer_Bot_EmailTracking/ExpertIdeas/core/scripts/i18n/redirect.py

e28933b2cd487018c6ff2af043c5dbc1ae0f37cd

[ "MIT" ]

permissive

ImanYZ/ExpertIdeas

da1564671f2cfe92d9de3fce68b82552cc6f33f7

23e23240854aef59108b16b63a567fffb2aabb69

refs/heads/master

2022-07-27T08:11:36.481824

2022-07-16T20:32:47

144,018,052

0

null

UTF-8

Python

false

62,009

py

# -*- coding: utf-8 -*- msg = { # Author: Xqt 'en': { 'redirect-broken-redirect-template': u'{{db-r1}}', 'redirect-fix-broken-moved': u'Bot: Fixing broken redirect to moved target page %(to)s', 'redirect-fix-double': u'Bot: Fixing double redirect to %(to)s', 'redirect-fix-loop': u'Bot: Fixing redirect loop to %(to)s', 'redirect-remove-broken': u'Bot: Redirect to a deleted or non-existent page', 'redirect-remove-loop': u'Bot: Redirect target forms a redirect loop', }, # Author: Csisc # Author: Lloffiwr # Author: Nemo bis # Author: Xqt # Author: ZxxZxxZ 'qqq': { 'redirect-fix-double': u'Edit summary when the bot fixes double redirects. <code>%(to)s</code> displays the new redirect target as a wiki link.', 'redirect-remove-broken': u'Edit summary when the bot tags a deleted or non-existent page for speedy deletion.', 'redirect-fix-broken-moved': u'Edit summary when the bot fixes a broken redirect to a moved page whose origin has been deleted.\nParameters:\n* <code>%(to)s</code>: the new redirect target, as a wiki link.', 'redirect-fix-loop': u'Edit summary when the bot fixes redirect loops. <code>%(to)s</code> displays the new redirect target as a wiki link.', 'redirect-remove-loop': u'Edit summary when the bot tags a redirect loop for speedy deletion.', 'redirect-broken-redirect-template': u'{{doc-important|Only use your deletion template like <code><nowiki>{{delete}}</nowiki></code> which exist on your local project.}}\n\nNOTE TO TRANSLATOR: This should only be translated by someone on the Wikipedia of your language code. Thank you.\n\nTemplate for speedy deletion of broken redirect or redirect loops which the bot tags onto the redirect page. This message may contain additional informations like template parameters or reasons for the deletion request.\n\nNOTE: If this system message is not given for a language code, speedy deletion request by a bot is not supported on your site except there is a bot with sysop flag.', }, # Author: Csisc 'aeb': { 'redirect-fix-double': u'بوت: تصليح تحويلة مزدوجة إلى %(to)s', 'redirect-remove-broken': u'تحويلة إلى صفحة محذوفة أو غير موجودة', 'redirect-fix-loop': u'روبوت: تعديل حلقة إعادة التوجيه إلى %(to)s', 'redirect-remove-loop': u'هدف التحويلة يصنع عقدة تحويل: Robot', }, # Author: Naudefj # Author: Xqt 'af': { 'redirect-fix-double': u'Robot: dubbele aanstuur na %(to)s reggemaak', 'redirect-remove-broken': u'Robot: Aanstuur na \'n geskrapte of nie-bestaande bladsy', 'redirect-fix-loop': u'Robot: sirkulêre aanstuur na %(to)s reggemaak', 'redirect-remove-loop': u'Robot: Aanstuur vorm \'n sirkulêre lus', }, # Author: Als-Holder # Author: Xqt 'als': { 'redirect-fix-double': u'Bötli: Uflösig vun de doppleti Wyterleitig zue %(to)s', 'redirect-remove-broken': u'Bötli: Wyterleitigsziil git s nit', 'redirect-fix-broken-moved': u'Bot: Kaputtigi Wyterleitig uf di verschobe Ziilsyte %(to)s repariert', 'redirect-fix-loop': u' Bot: Wyterleitigschlupf uf %(to)s korrigiert', 'redirect-remove-loop': u'Bot: Wyterleitig goht im ringrum', 'redirect-broken-redirect-template': u'{{delete}}Wyterleitig wo kaputt isch', }, # Author: DRIHEM # Author: Meno25 # Author: Zaher kadour 'ar': { 'redirect-fix-double': u'بوت: تصليح تحويلة مزدوجة إلى %(to)s', 'redirect-remove-broken': u'روبوت: تحويلة إلى صفحة محذوفة أو غير موجودة', 'redirect-fix-broken-moved': u'الروبوت: إصلاح إعادة التوجيه المعطل لصفحة الهدف المحركة %(to)s', 'redirect-fix-loop': u'روبوت: تعديل حلقة إعادة التوجيه إلى %(to)s', 'redirect-remove-loop': u'روبوت: هدف التحويلة يصنع عقدة تحويل', 'redirect-broken-redirect-template': u'{{شطب|تحويلة مكسورة}}', }, # Author: Jaminianurag 'as': { 'redirect-broken-redirect-template': u'{{db-r1}}', }, # Author: Esbardu # Author: Xqt # Author: Xuacu 'ast': { 'redirect-fix-double': u'Robó: Iguando la redireición doble a %(to)s', 'redirect-remove-broken': u'Robó: Redireición a una páxina desaniciada o que nun esiste', 'redirect-fix-broken-moved': u'Robó: Arreglu de redireición frañada a la páxina de destín treslladada "%(to)s"', 'redirect-fix-loop': u'Robó: Iguando la redireición cíclica a %(to)s', 'redirect-remove-loop': u'Robó: El destín de la redireición forma un bucle de redireición', 'redirect-broken-redirect-template': u'{{Destruir|La páxina a la que redirixe nun esiste|--~~~~}}', }, # Author: AZISS # Author: Cekli829 # Author: Ebrahimi-amir # Author: Khutuck 'az': { 'redirect-fix-double': u'Bot: İkiqat yönləndirmənin düzəldilməsi → %(to)s', 'redirect-remove-broken': u'Bot: Silinmiş və ya mövcud olmayan səhifəyə yönləndirmə', 'redirect-fix-broken-moved': u'Bot: İşləməyən yönləndirilmənin yeri dəyişdirilmiş hədəf səhifəyə %(to)s düzəldilməsi', 'redirect-fix-loop': u'Bot: Sonsuz yönləndirilmənin %(to)s düzəldilməsi', 'redirect-remove-loop': u'Bot: Yönləndirilmə sonsuz yönləndirilmə formalaşdırır', }, # Author: Amir a57 # Author: E THP # Author: Xqt 'azb': { 'redirect-fix-double': u'روبات :%(to)s صحیفه‌سینه ایستیقامت‌لی ایکیقات ایستیقامتلندیرمه دوزلدیلیر', 'redirect-remove-broken': u'روبات : سیلینئن یا دا وار اولمایان صحیفه‌یه اولان ایستیقامیلندیرمه', 'redirect-fix-loop': u'روبوت: فیخینگ اوزوک اولان%(to)s یؤنلن‌دیرن', 'redirect-remove-loop': u'بوت: ایستیقامتلندیرمه هدفی بیر ایستیقامتلندیرمه دؤورو تشکیل ائدیر', }, # Author: Haqmar # Author: Sagan 'ba': { 'redirect-fix-double': u'Робот: %(to)s битенә икеле йүнәлтеүҙе төҙәтеү', 'redirect-remove-broken': u'Робот: булмаған йәки юйылған биткә йүнәлтеү', 'redirect-fix-loop': u'Робот: %(to)s битенә йүнәлтеүҙе төҙәтеү', 'redirect-remove-loop': u'Робот: бер ҡайҙа ла йүнәлтелмәгән', }, # Author: Mucalexx # Author: Xqt 'bar': { 'redirect-fix-double': u'Bot: richtt dóppéde Weiderloattung auf %(to)s', 'redirect-remove-broken': u'Bot: Weiderloattungszü gibts néd', 'redirect-remove-loop': u'Bot: Weiderloattungszü auf sé söwer', 'redirect-broken-redirect-template': u'{{Löschen|hinige Weiderloattung}}', }, 'bat-smg': { 'redirect-fix-double': u'Robots: Taisuoms dvėgobs paradresavėms → %(to)s', }, # Author: EugeneZelenko # Author: Jim-by # Author: Renessaince # Author: Zedlik 'be-x-old': { 'redirect-fix-double': u'Робат: выпраўленьне падвойнага перанакіраваньня → %(to)s', 'redirect-remove-broken': u'Робат: мэта перанакіраваньня не існуе', 'redirect-fix-broken-moved': u'Робат: Выпраўленьне перанакіраваньня на старонку, перанесеную ў %(to)s', 'redirect-fix-loop': u'Робат: Выпраўленьне перанакіраваньня на %(to)s', 'redirect-remove-loop': u'Робат: Пятля перанакіраваньняў', 'redirect-broken-redirect-template': u'{{Выдаліць|некарэктнае перанакіраваньне}}', }, # Author: DCLXVI 'bg': { 'redirect-fix-double': u'Робот: Поправяне на двойно пренасочване към %(to)s', }, # Author: Riemogerz # Author: Xqt 'bjn': { 'redirect-fix-double': u'Robot: Pamasangan paugahan ganda ka %(to)s', 'redirect-remove-broken': u'Robot: Paalihan ka tungkaran nang dihapus atawa kada ada', 'redirect-remove-loop': u'Robot: Bidikan paalihan mahasilakan paalihan siklik', }, # Author: Wikitanvir 'bn': { 'redirect-fix-double': u'বট: %(to)s-এ দ্বিপুনর্নির্দেশনা ঠিক করছে', 'redirect-broken-redirect-template': u'{{db-r1}}', }, # Author: Fohanno # Author: Fulup # Author: Gwenn-Ael # Author: Y-M D 'br': { 'redirect-fix-double': u'Kempennet adkas doubl gant robot → %(to)s', 'redirect-remove-broken': u'Robot : Ar bajenn ma vezer adkaset n\'eus ket anezhi', 'redirect-fix-broken-moved': u'Robot : O reizhañ an adkasoù torret war-zu ar bajenn bal %(to)s', 'redirect-fix-loop': u'Robot : O kempenn al lagadenn adkas war-zu %(to)s', 'redirect-remove-loop': u'Robot: Stumm ur c\'helc\'h-tro born zo gant an [[Wikipedia:Redirect|adkas]]', }, # Author: CERminator # Author: Edinwiki # Author: Xqt 'bs': { 'redirect-fix-double': u'Bot: Popravlja dvostruka preusmjerenja na %(to)s', 'redirect-remove-broken': u' [[WP:CSD#G8|G8]]: [[Wikipedia:Redirect|Preusmjerenje]] na obrisanu ili nepostojeću stranicu', 'redirect-fix-broken-moved': u'Bot: Neispravno preusmjerenje prema premještenoj stranici %(to)s', 'redirect-fix-loop': u'Robot: Popravlja petlje preusmjerenja na %(to)s', 'redirect-remove-loop': u' [[WP:CSD#G8|G8]]: [[Wikipedia:Redirect|Preusmjerenje]] pravi petlju na samo sebe', 'redirect-broken-redirect-template': u'{{Brisanje}}', }, # Author: BroOk # Author: Grondin # Author: SMP # Author: Vriullop 'ca': { 'redirect-fix-double': u'Bot: reparació de les redireccions dobles a %(to)s', 'redirect-remove-broken': u'Bot: la pàgina a la qual redirecciona no existeix', 'redirect-fix-broken-moved': u'Bot: Reparació de les redireccions trencades per moure-les a %(to)s', 'redirect-fix-loop': u'Bot: arreglant redirecció en bucle per %(to)s', 'redirect-remove-loop': u'Robot: el destí de la redirecció crea un bucle de redirecció', 'redirect-broken-redirect-template': u'{{db-r1}}', }, # Author: Xqt # Author: Умар 'ce': { 'redirect-fix-double': u'бот: шалха дӀасахьажинарг нисъяр → %(to)s', }, # Author: Asoxor # Author: Calak # Author: Marmzok 'ckb': { 'redirect-fix-double': u'ڕۆبۆت: چاکسازیی دووجار-ڕەوانەکردنەوە بۆ %(to)s', 'redirect-remove-broken': u'ڕۆبۆت: ڕەوانەکەر بۆ پەڕەیەکی سڕاوە یان پەڕەیەک کە بوونی نییە', }, # Author: Dontlietome7 # Author: JAn Dudík # Author: Jezevec # Author: Spiffyk # Author: Vks 'cs': { 'redirect-fix-double': u'Robot: Opravuji dvojité přesměrování na %(to)s', 'redirect-remove-broken': u'Robot: Přerušené přesměrování', 'redirect-fix-broken-moved': u'Robot: Oprava přerušeného přesměrování na přesunutou cílovou stránku %(to)s', 'redirect-fix-loop': u'Robot: Oprava smyčky přesměrování na %(to)s', 'redirect-remove-loop': u'Robot: Cíl přesměrování tvoří smyčku', 'redirect-broken-redirect-template': u'{{smazat|přerušené přesměrování}}', }, # Author: Lloffiwr # Author: Xqt # Author: Xxglennxx 'cy': { 'redirect-fix-double': u'Bot: Yn trwsio ailgyfeiriad dwbl i %(to)s', 'redirect-remove-broken': u'Bot: Yn ailgyfeirio i dudalen a ddilëwyd neu nad yw ar gael', 'redirect-remove-loop': u'Bot: Mae nod yr ailgyfeiriad yn ffurfio dolen ailgyfeirio', }, # Author: Christian List # Author: Kaare # Author: Sarrus 'da': { 'redirect-fix-double': u'Robot: Retter dobbelt omdirigering til %(to)s', 'redirect-remove-broken': u'Robot: Omdirigering til en slettet eller ikke-eksisterende side', 'redirect-fix-broken-moved': u'Robot: Retter brudt omdirigering til flyttet målside %(to)s', 'redirect-fix-loop': u'Robot: Retter omdirigeringsløkke til %(to)s', 'redirect-remove-loop': u'Robot: Målet for omdirigeringen danner en omdirigeringsløkke', 'redirect-broken-redirect-template': u'{{slet}}', }, # Author: Geitost # Author: Metalhead64 # Author: The Evil IP address 'de': { 'redirect-fix-double': u'Bot: Korrigiere doppelte Weiterleitung auf %(to)s', 'redirect-remove-broken': u'Bot: Weiterleitungsziel existiert nicht', 'redirect-fix-broken-moved': u'Bot: Korrigiere defekte Weiterleitung auf Verschiebeziel %(to)s', 'redirect-fix-loop': u'Bot: Korrigiere Weiterleitungschleife auf %(to)s', 'redirect-remove-loop': u'Bot: Weiterleitungsziel auf sich selbst', 'redirect-broken-redirect-template': u'{{Löschen|Defekte Weiterleitung}}', }, # Author: Eruedin 'de-ch': { 'redirect-fix-double': u'Bot: Korrigiere doppelte Weiterleitung auf %(to)s', 'redirect-remove-broken': u'Bot: Weiterleitungsziel existiert nicht', 'redirect-fix-broken-moved': u'Bot: Korrigiere defekte Weiterleitung auf verschobener Zielseite %(to)s', 'redirect-fix-loop': u'Bot: Korrigiere Weiterleitungschleife auf %(to)s', 'redirect-remove-loop': u'Bot: Weiterleitungsziel auf sich selbst', }, # Author: Erdemaslancan # Author: Gorizon # Author: Mirzali 'diq': { 'redirect-fix-double': u'Boti Tespitê hetanayışê dıleti heta %(to)s', 'redirect-remove-broken': u'Robot: Yew pela ke esteriya ya zi çıniya, aye ser çarne', 'redirect-fix-broken-moved': u'Bot: Hetenayışe xırabi hedefe pela %(to)s vurneno', 'redirect-fix-loop': u'Boti %(to)s rê hetanayışo dılet deke', 'redirect-remove-loop': u'[[WP:CSD#G8|G8]]: [[Wikipedia:Redirect|Hetenayış]] re formê etiketi vıraşt.', 'redirect-broken-redirect-template': u'{{bestere|m1}}', }, # Author: Derbeth 'dsb': { 'redirect-broken-redirect-template': u'{{lašowaś|defektne dalejpósrědnjenje}}', }, # Author: Evropi # Author: Geraki # Author: Glavkos 'el': { 'redirect-fix-double': u'Ρομπότ: Διόρθωση διπλής ανακατεύθυνσης προς %(to)s', 'redirect-remove-broken': u'Ρομπότ: Ανακατεύθυνση σε μια σελίδα διαγεγραμμένη ή ανύπαρκτη', 'redirect-fix-broken-moved': u'Ρομπότ: Διόρθωση σπασμένης ανακατεύθυνσης προς την μετακινημένη σελίδα στόχο %(to)s', 'redirect-fix-loop': u'Ρομπότ: Διόρθωση βρόχου ανακατεύθυνσης στο %(to)s', 'redirect-remove-loop': u'Robot: Ανακατεύθυνση στόχου σχηματίζει έναν βρόγχο ανακατεύθυνσης', }, # Author: Blahma # Author: Mihxil # Author: Objectivesea # Author: Xqt 'eo': { 'redirect-fix-double': u'Roboto: Riparas duoblan alidirekton al %(to)s', 'redirect-remove-broken': u'Roboto: Alidirekto indikas forigitan aŭ neekzistantan paĝon', 'redirect-fix-broken-moved': u'Roboto: Riparas rompitan alidirekton al movita celpaĝo %(to)s', 'redirect-fix-loop': u'Roboto: Riparas ciklan alidirektilon al %(to)s', 'redirect-remove-loop': u'Roboto: Alidirekta celas sin mem', 'redirect-broken-redirect-template': u'{{db-r1}}', }, # Author: Armando-Martin # Author: Dferg # Author: Invadinado # Author: Vivaelcelta # Author: Xqt 'es': { 'redirect-fix-double': u'Bot: Arreglando doble redirección → %(to)s', 'redirect-remove-broken': u'Bot: Redirige a una página borrada o que no existe', 'redirect-fix-broken-moved': u'Bot: arreglo la redirección rota hacia la página de destino trasladada "%(to)s"', 'redirect-fix-loop': u'Bot: Arreglando redirección infinita → %(to)s', 'redirect-remove-loop': u'[[WP:CSD#G8|G8]]: El destino de la [[Wikipedia:Redirect|redirección]] crea un bucle de redirección', 'redirect-broken-redirect-template': u'{{destruir|1=La página a la que redirige no existe|bot=~~~~}}', }, # Author: Pikne 'et': { 'redirect-fix-double': u'Robot: parandatud kahekordne ümbersuunamine leheküljele %(to)s', }, # Author: An13sa # Author: Xabier Armendaritz 'eu': { 'redirect-fix-double': u'Robota: «%(to)s» orriranzko birbideratze bikoitza konpontzea', }, # Author: Ebraminio # Author: Huji # Author: Mjbmr # Author: Reza1615 # Author: ZxxZxxZ # Author: جواد 'fa': { 'redirect-fix-double': u'ربات: اصلاح تغییرمسیر دوتایی به %(to)s', 'redirect-remove-broken': u'ربات: تغییرمسیر به صفحهٔ ناموجود یا حذف‌شده', 'redirect-fix-broken-moved': u'ربات:اصلاح تغییرمسیرهای خراب به صفحهٔ هدف %(to)s', 'redirect-fix-loop': u'ربات: رفع حلقه در تغییرمسیر به %(to)s', 'redirect-remove-loop': u'ربات: مقصد تغییرمسیر یک تغییرمسیر حلقه‌ای ایجاد می‌کند', 'redirect-broken-redirect-template': u'{{حذف سریع|بن بست|bot=yes}}', }, # Author: Crt # Author: Nedergard # Author: Nike # Author: Olli # Author: Silvonen 'fi': { 'redirect-fix-double': u'Botti korjasi kaksinkertaisen ohjauksen sivulle %(to)s', 'redirect-remove-broken': u'Botti: Ohjaus poistetulle tai olemattomalle sivulle', 'redirect-fix-broken-moved': u'Botti korjasi rikkinäisen ohjauksen siirrettyyn kohdesivuun %(to)s', 'redirect-fix-loop': u'Botti korjasi ohjaussilmukan sivulle %(to)s', 'redirect-remove-loop': u'Botti: Ohjauksen kohde muodostaa ohjaussilmukan', 'redirect-broken-redirect-template': u'{{Delete}}', }, # Author: EileenSanda 'fo': { 'redirect-fix-double': u'Bottur: Rættar dupulta umdirigering til %(to)s', 'redirect-remove-broken': u'Bottur: Umstjórnan til eina strikaða síðu ella til eina síðu sum ikki er til', 'redirect-fix-broken-moved': u'Bottur: Rættar brotnar umdirigeringar til flutta málsíðu %(to)s', 'redirect-fix-loop': u'Bottur: Rættar endurstýris (redirect) lykkju til %(to)s', }, # Author: Boniface # Author: Crochet.david # Author: Gomoko # Author: IAlex # Author: Od1n # Author: Xqt 'fr': { 'redirect-fix-double': u'Robot : répare une double redirection vers %(to)s', 'redirect-remove-broken': u'[[WP:CSD#G8|G8]]: [[Wikipedia:Redirect|Redirection]] vers une page supprimée ou inexistante', 'redirect-fix-broken-moved': u'Robot: Correction des redirections erronées vers une page cible %(to)s déplacée', 'redirect-fix-loop': u'Robot : répare une boucle de redirection sur %(to)s', 'redirect-remove-loop': u'Bot: la cible de la redirection forme une boucle de redirection', 'redirect-broken-redirect-template': u'{{db-r1}}', }, # Author: ChrisPtDe # Author: Xqt 'frp': { 'redirect-fix-double': u'Robot : rèpâre na redirèccion dobla de vers %(to)s', 'redirect-remove-broken': u'Robot : redirèccion de vers na pâge suprimâye ou ben pas ègzistenta', 'redirect-fix-loop': u'Robot : rèpâre na boclla de redirèccion a %(to)s', 'redirect-remove-loop': u'Robot : la ciba de la redirèccion fôrme na boclla de redirèccion', }, # Author: Murma174 'frr': { 'redirect-fix-double': u'Bot: Ferbeedre dobelt widjerfeerang tu %(to)s', 'redirect-remove-broken': u'Bot: Widjerfeerang tu en duad sidj.', 'redirect-fix-broken-moved': u'Bot: Uunstaken widjerfeerang feert nü tu %(to)s', 'redirect-fix-loop': u'Bot: Maaget widjerfeerangs-sleuf hial tu %(to)s', 'redirect-remove-loop': u'Bot: Widjerfeerang üüb ham salew', 'redirect-broken-redirect-template': u'{{Strik|Widjerfeerang uunstaken}}', }, # Author: Klenje 'fur': { 'redirect-fix-double': u'Robot: o comedi un re-indreçament dopli a %(to)s', }, # Author: Alison 'ga': { 'redirect-fix-double': u'Róbó: Ag socrú athsheolta dúbailte → %(to)s', 'redirect-remove-broken': u'Róbó : Targaid athsheoladh ar iarraidh', 'redirect-broken-redirect-template': u'{{scrios|Athsheoladh briste}}', }, # Author: Toliño 'gl': { 'redirect-fix-double': u'Bot: Arranxo a redirección dobre cara a "%(to)s"', 'redirect-remove-broken': u'Bot: Redirección cara a unha páxina eliminada ou en branco', 'redirect-fix-broken-moved': u'Bot: Arranxo a redirección rota cara á páxina de destino trasladada "%(to)s"', 'redirect-fix-loop': u'Bot: Arranxo a redirección en bucle cara a "%(to)s"', 'redirect-remove-loop': u'Bot: O destino da redirección crea un bucle', 'redirect-broken-redirect-template': u'{{delete}}', }, # Author: Jetlag 'hak': { 'redirect-fix-double': u'機械人：修正雙重定向至%(to)s', 'redirect-remove-broken': u'機械人：重定向到已刪除或毋存在个頁面', 'redirect-fix-broken-moved': u'機械人：修復損壞个重定向頁到移動目標頁面 %(to)s', 'redirect-fix-loop': u'機械人：修復重定向迴圈至%(to)s', 'redirect-remove-loop': u'機械人：重定向目標構成循環', }, # Author: Kolonahe # Author: Xqt 'haw': { 'redirect-fix-double': u'Lopako: Ke kāpili hou i ka hoʻoili pālua iā %(to)s', 'redirect-remove-broken': u'Lopako: Hoʻoili i kekahi ʻaoʻao i holoi ʻia aiʻole he ʻaoʻao i hakuʻole ʻia', 'redirect-fix-broken-moved': u'Lopako: Ke kāpili hou nei i ka hoʻoili haki o kekahi ʻaoʻao hoʻoneʻe ʻia iā %(to)s', 'redirect-fix-loop': u'Lopako: Ke kāpili hou i ka linapoepoe hoʻoili iā %(to)s', 'redirect-remove-loop': u'Lopako: Hoʻokino ka māka hoʻoili i kekahi linapoepoe hoʻoili', }, # Author: Amire80 # Author: YaronSh # Author: ערן 'he': { 'redirect-fix-double': u'בוט: מתקן הפניה כפולה → %(to)s', 'redirect-remove-broken': u'רובוט: יעד ההפניה נמחק או שאינו קיים', 'redirect-fix-broken-moved': u'רובוט: תיקון הפניה שבורה לדף היעד %(to)s, שהועבר', 'redirect-fix-loop': u'בוט: תיקון הפניה מעגלית ל%(to)s', 'redirect-remove-loop': u'רובוט: הפניה זו גורמת ללולאה אין־סופית של הפניות', }, # Author: Ex13 'hr': { 'redirect-fix-double': u'Bot: Popravak dvostrukih preusmjeravanja → %(to)s', 'redirect-remove-broken': u'[[WP:CSD#G8|G8]]: [[Wikipedia:Redirect|Preusmjeravanje] na obrisanu ili nepostojeću stranicu', 'redirect-remove-loop': u'[[WP:CSD#G8|G8]]: Cilj [[Wikipedia:Redirect|preusmjeravanja]] stvara petlju na sebe', }, # Author: Bináris # Author: Dj 'hu': { 'redirect-fix-double': u'Bot: %(to)s lapra mutató dupla átirányítás javítása', 'redirect-remove-broken': u'Bot: Törölt vagy nem létező lapra mutató átirányítás törlése', 'redirect-fix-loop': u'Bot: Ide mutató átirányítási hurkok javítása: %(to)s', 'redirect-remove-loop': u'Bot: körkörös átirányítás', 'redirect-broken-redirect-template': u'{{azonnali|Hibás átirányítás}}', }, # Author: Xelgen 'hy': { 'redirect-fix-double': u'Ռոբոտ․ Շտկվում են կրկնակի վերահղումները %(to)s -ին', }, # Author: McDutchie # Author: Xqt 'ia': { 'redirect-fix-double': u'Robot: reparation de duple redirection → %(to)s', 'redirect-remove-broken': u'Robot: Redirection a un pagina delite o non existente', 'redirect-fix-broken-moved': u'Robot: Repara un redirection rupte verso un pagina renominate: %(to)s', 'redirect-fix-loop': u'Robot: Repara redirection circular a %(to)s', 'redirect-remove-loop': u'Robot: Le destination del redirection forma un circulo de redirectiones', 'redirect-broken-redirect-template': u'{{eliminar|Redirection a un pagina delite o non existente}}', }, # Author: Farras # Author: IvanLanin 'id': { 'redirect-fix-double': u'Bot: Memperbaiki pengalihan ganda ke %(to)s', 'redirect-remove-broken': u'Robot: Pengalihan ke halaman yang dihapus atau tidak ada', 'redirect-fix-loop': u'Robot: Memperbaiki pengalihan ganda ke %(to)s', 'redirect-remove-loop': u'Robot: Target pengalihan menghasilkan pengalihan siklik', 'redirect-broken-redirect-template': u'{{db-r1}}', }, # Author: Renan 'ie': { 'redirect-fix-double': u'Machine: Fixant redirection duplic por %(to)s', 'redirect-remove-broken': u'[[WP:CSD#G8|G8]]: [[Wikipedia:Redirect|Redirect]] por un págine deletet o non-existent', 'redirect-remove-loop': u'[[WP:CSD#G8|G8]]: [[Wikipedia:Redirect|Redirection]] cible forma un lace de redirection', }, # Author: Lam-ang 'ilo': { 'redirect-fix-double': u'Robot: Agsimsimpa ti doble a baw-ing idiay %(to)s', 'redirect-remove-broken': u'Robot: Baw-ing a mapan ti naikkat wenno awan a panid', 'redirect-remove-loop': u'Robot: Ti baw-ing a puntaan ket agporma baw-ing a silo', 'redirect-broken-redirect-template': u'{{delete}}', }, # Author: Snævar 'is': { 'redirect-fix-double': u'Vélmenni: Lagfæri tvöfalda tilvísun → %(to)s', 'redirect-remove-broken': u'Vélmenni: Tilvísun bendir á síðu sem hefur verið eytt eða er ekki til', 'redirect-fix-loop': u'Vélmenni: Lagfæri tilvísunar lykkju → %(to)s', 'redirect-remove-loop': u'Vélmenni: Tilvísun bendir á óendanlega tilvísunar lykkju', }, # Author: Beta16 # Author: Nemo bis # Author: Rippitippi # Author: Ximo17 'it': { 'redirect-fix-double': u'Bot: Sistemo i redirect doppi a %(to)s', 'redirect-remove-broken': u'Bot: Redirect a una pagina inesistente', 'redirect-fix-broken-moved': u'Bot: Correggo redirect errati alla pagina spostata %(to)s', 'redirect-fix-loop': u'Bot: sistemo ciclo di reindirizzamento a %(to)s', 'redirect-remove-loop': u'Bot: La destinazione del [[{{ns:project}}:Redirect|redirect]] rimanda alla pagina di partenza', 'redirect-broken-redirect-template': u'{{Cancella subito|9}}', }, # Author: Shirayuki # Author: 赤の旋律 'ja': { 'redirect-fix-double': u'ロボットによる: 二重リダイレクト修正 → %(to)s', 'redirect-remove-broken': u'ロボットによる: 削除済みまたは存在しないページへのリダイレクト', 'redirect-fix-broken-moved': u'ロボットによる: 迷子のリダイレクトのリダイレクト先を %(to)s に修正', 'redirect-fix-loop': u'ロボットによる: リダイレクトのループの修正 → %(to)s', 'redirect-remove-loop': u'ロボットによる: リダイレクト先にあるリダイレクトのループを修正', }, # Author: NoiX180 'jv': { 'redirect-fix-double': u'Bot: Mbenakaké rong pralihan nèng %(to)s', 'redirect-remove-broken': u'Bot: Ngalihaké nèng kaca sing ora ana utawa wis kabusak', 'redirect-fix-loop': u'Bot: Mbenakaké ubengan pangalihan nèng %(to)s', 'redirect-remove-loop': u'Bot: Patujon pangalihan dadi ubengan pangalihan', }, # Author: David1010 'ka': { 'redirect-fix-double': u'რობოტი: ორმაგი გადამისამართების გასწორება → %(to)s', 'redirect-remove-broken': u'რობოტი: გადამისამართება წაშლილ ან არარსებულ გვერდზე', }, 'kk': { 'redirect-fix-double': u'Бот: Шынжырлы айдатуды түзетті → %(to)s', 'redirect-remove-broken': u'Бот: Айдату нысанасы жоқ болды', }, # Author: Cwt96 # Author: 아라 'ko': { 'redirect-fix-double': u'로봇: %(to)s(으)로 이중 넘겨주기 고침', 'redirect-remove-broken': u'로봇: 끊긴 넘겨주기', 'redirect-fix-broken-moved': u'로봇: %(to)s(으)로 옮긴 대상 문서로 끊긴 넘겨주기 고침', 'redirect-fix-loop': u'로봇: %(to)s(으)로 재귀적인 넘겨주기 고침', 'redirect-remove-loop': u'로봇: 넘겨주기 대상이 재귀적인 넘겨주기로 생김', 'redirect-broken-redirect-template': u'{{ㅅ}}', }, # Author: Purodha 'ksh': { 'redirect-fix-double': u'Bot: [[Special:Doubleredirects|Dubbel Ömlëijdong]] fottjemaat → %(to)s', 'redirect-remove-broken': u'Bot: Di Ömlëijdong jingk ennet Liiere.', 'redirect-fix-broken-moved': u'Bot: De kappodde Ömleidong op de ömjenannte Sigg %(to)s es reppareert.', 'redirect-fix-loop': u'Bot: En Reih vun Ömleidonge jeng em Kreis eröm. Op %(to)s jescheck.', 'redirect-remove-loop': u'Bot: Di Ömleidonge jonn em Kreis eröm.', 'redirect-broken-redirect-template': u'{{Schmieß fott}}Di [[Wikipedia:Ömleijdung|Ömlëijdong]] jeiht noh nörjendswoh hen.', }, # Author: Ghybu 'ku': { 'redirect-fix-double': u'Robot: Fixing double redirect to %(to)s', }, # Author: Maksat # Author: Викиней 'ky': { 'redirect-fix-double': u'Бот: кош багыттаманы жоюу → %(to)s', }, # Author: MissPetticoats # Author: UV # Author: Xqt 'la': { 'redirect-fix-double': u'automaton: rectificatio redirectionis duplicis → %(to)s', 'redirect-remove-broken': u'automaton: redirectio ad paginam quae non est', 'redirect-remove-loop': u'automaton: redirectio ad eundem titulum', }, # Author: Les Meloures # Author: Robby 'lb': { 'redirect-fix-double': u'Bot: Duebel Viruleedung gefléckt → %(to)s', 'redirect-remove-broken': u'Bot: Viruleedung op eng geläscht Säit oder eng Säit déi et net gëtt', 'redirect-fix-broken-moved': u'Bot: Futtis Viruleedung op déi geréckelt Zilsäit %(to)s gouf gefléckt', 'redirect-fix-loop': u'Bot: Viruleedungsschleef op %(to)s verbessert', 'redirect-remove-loop': u'Bot: Viruleedung där hiert Zil zu enger endlos Schleef féiert', 'redirect-broken-redirect-template': u'{{Läschen|Defekt Viruleedung}}', }, # Author: Pahles 'li': { 'redirect-fix-double': u'Robot: dobbel doorverwiezing aangepas nao %(to)s', 'redirect-remove-broken': u'Robot: de doelpagina van de doorverwiezing besjteit neet', 'redirect-remove-loop': u'Doorverwiezing vörmp \'n óneindige lus', 'redirect-broken-redirect-template': u'{{delete|Weisdoorverwiezing of doorverwiezing nao eweggesjafde pagina}}', }, # Author: Hugo.arg # Author: Mantak111 'lt': { 'redirect-fix-double': u'robotas: Taisomas dvigubas peradresavimas → %(to)s', 'redirect-remove-broken': u'robotas: peradresavimas į ištrintą ar nesantį puslapį', }, # Author: StefanusRA 'map-bms': { 'redirect-fix-double': u'Bot: Mbenerna pengalihan ganda maring %(to)s', 'redirect-remove-broken': u'Robot: Pangalihan ming kaca sing ora ana utawa wis debusek', 'redirect-fix-broken-moved': u'Robot:Ndandani pangalihan ruwag maring kaca target sing dipindah %(to)s', 'redirect-fix-loop': u'Robot: Ndandani pengalihan dobel maring %(to)s', 'redirect-remove-loop': u'Robot: Target pangalihan marekna dadi pengalihan siklik', }, # Author: Jagwar 'mg': { 'redirect-fix-double': u'Rôbô : mamaha olam-pihodinana mankany amin\'i %(to)s', 'redirect-remove-broken': u'Rôbô : fihodinana mankany amina pejy tsy misy na erfa voafafa.', 'redirect-fix-broken-moved': u'Rôbô : Fanitsiana fihodinana diso mankany amin\'ny pejy tanjona %(to)s nafindra', 'redirect-fix-loop': u'Rôbô: nanamboatra ny fihodinana manao tondro mifolaka amin\'i %(to)s', 'redirect-remove-loop': u'[[WP:CSD#G8|G8]]: Ny tanjon\'ny fihodinana dia manao fihodinana mifolaka', 'redirect-broken-redirect-template': u'{{fafao}}', }, # Author: Luthfi94 # Author: Naval Scene 'min': { 'redirect-fix-double': u'Bot: Mampeloki pangalihan gando ka %(to)s', 'redirect-remove-broken': u'Robot: Pangaliahan ka laman nan dihapuih atau indak ado', 'redirect-remove-loop': u'Robot: Target pangaliahan mahasilan pangaliahan bapusiang', }, # Author: Bjankuloski06 # Author: Rancher # Author: Xqt 'mk': { 'redirect-fix-double': u'Робот: Исправка на двојни пренасочувања → %(to)s', 'redirect-remove-broken': u'[[ВП:КББ|О6]: [[Википедија:Пренасочување|Пренасочување]] кон избришана или непостоечка страница', 'redirect-fix-broken-moved': u'Робот: Исправка на прекинато пренасочување кон преместена целна страница %(to)s', 'redirect-fix-loop': u'Робот: Поправа јамка на пренасочување кон %(to)s', 'redirect-remove-loop': u'[[ВП:КББ|О6]]: Одредницата за [[Википедија:Пренасочување|пренасочување]] образува јамка', 'redirect-broken-redirect-template': u'{{db|[[ВП:КББ|O8]]}}', }, # Author: Praveenp 'ml': { 'redirect-fix-double': u'യന്ത്രം: %(to)s എന്നതിലോട്ടുള്ള ഇരട്ട തിരിച്ചുവിടൽ ശരിയാക്കുന്നു', 'redirect-remove-broken': u'യന്ത്രം: മായ്ച്ച അല്ലെങ്കിൽ നിലവിലില്ലാത്ത താളിലോട്ടുള്ള തിരിച്ചുവിടൽ', 'redirect-fix-broken-moved': u'യന്ത്രം: മാറ്റപ്പെട്ട വിക്കിതാളായ %(to)s എന്നതിലേയ്ക്കുള്ള പൊട്ടിയ തിരിച്ചുവിടൽ ശരിയാക്കുന്നു', 'redirect-fix-loop': u'യന്ത്രം: %(to)s എന്നതിലോട്ടുണ്ടായിരുന്ന ചാക്രിക തിരിച്ചുവിടൽ ശരിയാക്കുന്നു', 'redirect-remove-loop': u'യന്ത്രം: ലക്ഷ്യത്തിലോട്ടുള്ള തിരിച്ചുവിടൽ ഒരു തിരിച്ചുവിടൽ ചക്രം സൃഷ്ടിക്കുന്നു', 'redirect-broken-redirect-template': u'{{delete}}', }, # Author: Anakmalaysia # Author: Kurniasan 'ms': { 'redirect-fix-double': u'Bot: Memperbetulkan pelencongan berganda ke %(to)s', 'redirect-remove-broken': u'Robot: Melencong kepada laman yang terhapus atau tidak wujud', 'redirect-fix-broken-moved': u'Robot: Membaiki lencongan yang terputus ke halaman sasaran yang terpindah iaitu %(to)s', 'redirect-fix-loop': u'Robot: Membaiki gelung lencongan ke %(to)s', 'redirect-remove-loop': u'Robot: Sasaran lencongan membentuk gelung lencongan', }, # Author: Chrisportelli 'mt': { 'redirect-fix-double': u'Bot: Tranġar ta\' rindirizz doppju lejn %(to)s', 'redirect-remove-broken': u'Bot: Rindirizz lejn paġna mħassra jew li ma teżistix', 'redirect-remove-loop': u'Bot: Id-destinazzjoni tar-rindirizz qiegħed jifforma ċiklu ta\' rindirizzi', 'redirect-broken-redirect-template': u'{{Ħassar minnufih|9}}', }, # Author: Lionslayer 'my': { 'redirect-fix-double': u'ဘော့ - %(to)s သို့ ပြန်ညွှန်းနှစ်ထပ်ဖြစ်နေသည်ကို ပြင်နေသည်', 'redirect-remove-loop': u'[WP:CSD#G8|G8]]: [[Wikipedia:Redirect|ပြန်ညွှန်း]]သည် ယင်းကို ပြန်ညွှန်းခြင်းခံရသောကြောင့် သံသရာလည်မှု ဖြစ်စေသည်။', }, # Author: محک 'mzn': { 'redirect-fix-double': u'ربوت:عوض هایتن دکشیه‌ئون دِتایی → %(to)s', 'redirect-remove-broken': u'ربوت:بی‌جاء ِدکشی‌یه‌ئون', 'redirect-remove-loop': u'ربوت:ناترینگی [[:fa:وپ:تغییرمسیر|دکشی‌یه]]', 'redirect-broken-redirect-template': u'{{حذف سریع|بن بست|bot=yes}}', }, # Author: Slomox 'nds': { 'redirect-fix-double': u'Bot: Dubbelte Wiederleiden rutmakt → %(to)s', 'redirect-remove-broken': u'Bot: Kaputte Wiederleiden ward nich brukt', 'redirect-remove-loop': u'Bot: Redirect wiest wedder op sik sülvs', 'redirect-broken-redirect-template': u'{{delete}}Kaputte Wiederleiden, wat nich brukt ward.', }, # Author: Servien # Author: Xqt 'nds-nl': { 'redirect-fix-double': u'Bot: dubbele deurverwiezing verbeterd naor %(to)s', 'redirect-remove-broken': u'Bot: de doelpagina van de deurverwiezing besteet niet', 'redirect-fix-broken-moved': u'Robot: kapotte deurverwiezing verbeterd deur anpassing naor herneumden doelzied %(to)s', 'redirect-fix-loop': u'Bot: deurverwiessirkel naor %(to)s erepareerd', 'redirect-remove-loop': u'Bot: deurverwiezing verwis weer naor zichzelf', 'redirect-broken-redirect-template': u'{{vort|Kapotte deurverwiezing of deurverwijzing naor vort-edaone pagina}}', }, # Author: RajeshPandey # Author: सरोज कुमार ढकाल 'ne': { 'redirect-fix-double': u'बोट: दोहोरो अनुप्रेषणलाई %(to)sमा ठिक गर्दै', 'redirect-remove-broken': u'रोबोट: हुँदै नभएको पृष्ठमा या मेटिएको पृष्ठमा गरिएको रिडाइरेक्ट', 'redirect-fix-broken-moved': u'रोबोट: टुटेको अनुप्रेषण सारिएको लक्ष्यको लागि मिलाउदै %(to)s', 'redirect-fix-loop': u'रोबोट: अनुप्रेषण चक्र %(to)sलाई मिलाउँदै', 'redirect-remove-loop': u'रोबोट: रिडाइरेक्ट गर्न खोजिएको पृष्ठले रिडाइरेक्ट चक्रको निर्माण गर्‌यो ।', 'redirect-broken-redirect-template': u'{{db-r1}}', }, # Author: Eukesh 'new': { 'redirect-fix-loop': u'रोबट: पुनर्निदेश लूपयात %(to)sय्‌ मिलय्‌यानाछ्वगु', 'redirect-remove-loop': u'रोबट:पुनर्निर्देशया लक्ष्यं पुनर्निदेश लूप दयेकी', }, # Author: Krinkle # Author: Siebrand 'nl': { 'redirect-fix-double': u'Robot: dubbele doorverwijzing gecorrigeerd naar %(to)s', 'redirect-remove-broken': u'Robot: de doelpagina van de doorverwijzing bestaat niet', 'redirect-fix-broken-moved': u'Robot: kapotte doorverwijzing gecorrigeerd door aanpassing naar hernoemde doelpagina %(to)s', 'redirect-fix-loop': u'Robot: doorverwijscirkel naar %(to)s gerepareerd', 'redirect-remove-loop': u'[[WP:NW|NUWEG]]: [[Wikipedia:Doorverwijzing|Doorverwijzing]] vormt een oneindige lus', 'redirect-broken-redirect-template': u'{{nuweg|Weesdoorverwijzing of doorverwijzing naar verwijderde pagina}}', }, # Author: Njardarlogar 'nn': { 'redirect-fix-double': u'robot: retta dobbel omdirigering → %(to)s', 'redirect-remove-broken': u'robot: målet for omdirigeringa finst ikkje', 'redirect-fix-loop': u'robot: retta omdirigeringslykkje til %(to)s', 'redirect-broken-redirect-template': u'{{snøggsletting|dette er ei øydelagd omdirigering}}', }, # Author: Danmichaelo # Author: Jon Harald Søby 'no': { 'redirect-fix-double': u'robot: Retter dobbel omdirigering til %(to)s', 'redirect-remove-broken': u'Robot: Målet for omdirigeringen eksisterer ikke', 'redirect-fix-broken-moved': u'bot: Fikser ødelagte omdirigeringer til %(to)s som har blitt flyttet', 'redirect-fix-loop': u'Robot: Fikser omdirigeringsløkke til %(to)s', 'redirect-remove-loop': u'Robot: Målet for omdirigeringen danner en omdirigeringsløkke', 'redirect-broken-redirect-template': u'{{hurtigslett|Feilaktig omdirigering}}', }, # Author: Xqt 'nv': { 'redirect-fix-double': u'Bot: dah astsihígíí łahgo áyiilaa -> %(to)s', }, # Author: Cedric31 # Author: Xqt 'oc': { 'redirect-fix-double': u'Robòt : repara una dobla redireccion cap a %(to)s', 'redirect-fix-broken-moved': u'Robòt: Correccion de las redireccions erronèas cap a una pagina cibla %(to)s desplaçada', 'redirect-fix-loop': u'Robòt : repara una bocla de redireccion sus %(to)s', 'redirect-remove-loop': u'Robòt: la cibla de la redireccion forma una bocla de redireccion', }, # Author: Geitost # Author: Xqt 'pdc': { 'redirect-fix-double': u'Waddefresser: Doppelte Weiderleiding nooch %(to)s gennert', 'redirect-remove-broken': u'Waddefresser: Kaputte Weiderleiding', 'redirect-broken-redirect-template': u'{{verwische|Kaputte Weiderleiding}}', }, 'pfl': { 'redirect-fix-double': u'Bot: E doppelte Waiterlaitung vabessat zu %(to)s', }, # Author: BeginaFelicysym # Author: Derbeth # Author: Nemo bis # Author: Sp5uhe # Author: Ty221 'pl': { 'redirect-fix-double': u'Robot naprawił podwójne przekierowanie do %(to)s', 'redirect-remove-broken': u'Robot: przekierowanie do usuniętej lub nieistniejącej strony', 'redirect-fix-broken-moved': u'Bot: Poprawa urwanych przekierowań - przeniesiono cel do %(to)s', 'redirect-fix-loop': u'Robot: Naprawa pętli przekierowań do %(to)s', 'redirect-remove-loop': u'Robot: pętla przekierowań', 'redirect-broken-redirect-template': u'{{ek|przekierowanie do usuniętej lub nieistniejącej strony}}', }, # Author: Borichèt # Author: Dragonòt 'pms': { 'redirect-fix-double': u'Trigomiro: a coregg ridiression dobia a %(to)s', 'redirect-remove-broken': u'Trigomiro: Ridiression a na pàgina scancelà o ch\'a esist nen', 'redirect-fix-broken-moved': u'Trigomiro: Coression ëd le ridiression nne bon-e a na pàgina ëd destinassion tramudà %(to)s', 'redirect-fix-loop': u'Trigomiro: Coression dël sicl ëd ridiression a %(to)s', 'redirect-remove-loop': u'Trigomiro: La destinassion ëd la ridiression a forma un sicl ëd ridiression', }, # Author: Hamilton Abreu # Author: Luckas # Author: Malafaya # Author: Xqt 'pt': { 'redirect-fix-double': u'Robô: A corrigir o redirecionamento duplo para %(to)s', 'redirect-remove-broken': u'Robô: Redirecionamento para uma página eliminada ou inexistente', 'redirect-fix-broken-moved': u'Robô: A corrigir redirecionamento quebrado para página alvo movida %(to)s', 'redirect-fix-loop': u'Robô: A corrigir o ciclo de redirecionamentos para %(to)s', 'redirect-remove-loop': u'Robô: O destino do redirecionamento cria um ciclo de redirecionamentos', }, # Author: Amgauna # Author: Hamilton Abreu # Author: Helder.wiki # Author: Luckas # Author: Luckas Blade # Author: Tuliouel # Author: Xqt # Author: 555 'pt-br': { 'redirect-fix-double': u'Bot: Corrigindo redirecionamento duplo para %(to)s', 'redirect-remove-broken': u'Robô: Redirecionamento para uma página eliminada ou inexistente', 'redirect-fix-broken-moved': u'Bot: consertando redirecionamento quebrado para página-alvo movida %(to)s', 'redirect-fix-loop': u'Bot: Corrigindo ciclo de redirecionamentos para %(to)s', 'redirect-remove-loop': u'Bot: O destino do redirecionamento cria um ciclo de redirecionamentos', }, # Author: Firilacroco # Author: Minisarm 'ro': { 'redirect-fix-double': u'Robot: Reparat dubla redirecționare înspre %(to)s', 'redirect-remove-broken': u'Robot: Redirecționare către o pagină ștearsă sau inexistentă', 'redirect-fix-loop': u'Robot: Reparat bucla de redirecționare către %(to)s', 'redirect-remove-loop': u'Robot: Ținta redirecționării formează o buclă de redirecționare', }, # Author: DCamer # Author: Rubin # Author: Volkov # Author: Xqt 'ru': { 'redirect-fix-double': u'бот: исправление двойного перенаправления → %(to)s', 'redirect-remove-broken': u'бот: [[ВП:КБУ#П1|П1]] - перенаправление на удалённую или несуществующую страницу', 'redirect-fix-broken-moved': u'Робот: Исправление перенаправления на перемещенную целевую страницу %(to)s', 'redirect-fix-loop': u'бот: исправление перенаправления на %(to)s', 'redirect-remove-loop': u'бот: перенаправление в никуда', 'redirect-broken-redirect-template': u'{{db-redirnone}}', }, # Author: Gazeb 'rue': { 'redirect-fix-double': u'Робот: справив двоїте напрямлїня → %(to)s', 'redirect-remove-broken': u'[[WP:CSD#G8|G8]]: [[Wikipedia:Redirect|Напрямлїня]] на змазану або неекзістуючу сторінку', 'redirect-remove-loop': u'[[WP:CSD#G8|G8]]: [[Wikipedia:Redirect|Напрямлїня]] формує петлю напрямлїнь', }, # Author: Avicennasis # Author: John Reid # Author: Xqt 'sco': { 'redirect-fix-double': u'Bot: Fixin dooble reguidal til %(to)s', 'redirect-remove-broken': u'Robot: Reguidal til ae delytit or non-exeestent page', 'redirect-fix-broken-moved': u'Robot: Fixin broken reguidal til muived target page %(to)s', 'redirect-fix-loop': u'Robot: Fixin reguidal luip til %(to)s', 'redirect-remove-loop': u'Robot: Reguidal tairget forms ae reguidal luip', 'redirect-broken-redirect-template': u'{{delete}}', }, # Author: Teslaton # Author: Wizzard 'sk': { 'redirect-fix-double': u'Robot: Opravujem dvojité presmerovanie na %(to)s', 'redirect-remove-broken': u'Robot: Presmerovanie na neexistujúcu stránku', 'redirect-fix-broken-moved': u'Robot: Oprava porušeného presmerovania na presunutú cieľovú stránku %(to)s', 'redirect-fix-loop': u'Robot: Oprava cyklického presmerovania na %(to)s', 'redirect-remove-loop': u'Robot: Cieľ presmerovania tvorí slučku', }, # Author: Dbc334 # Author: Mateju 'sl': { 'redirect-fix-double': u'Bot: Popravljanje dvojnih preusmeritev na %(to)s', 'redirect-remove-broken': u'Robot: Preusmeritev na izbrisano ali neobstoječo stran', 'redirect-fix-broken-moved': u'Robot: Popravljanje okvarjene povezave preusmeritve na premaknjeno ciljno stran %(to)s', 'redirect-fix-loop': u'Robot: Popravljanje preusmeritvene zanke na %(to)s', 'redirect-remove-loop': u'Robot: Cilj preusmeritve ustvarja preusmeritveno zanko', 'redirect-broken-redirect-template': u'{{delete}}', }, # Author: Abshirdheere 'so': { 'redirect-fix-double': u'Bot: Hagaajin u rogid labalaaban ee %(to)s', 'redirect-remove-broken': u'Bot: U wareejin bog la tirtiray ama aan jirin', 'redirect-fix-broken-moved': u'Bot: Dib u Sixidda qaldantay waxaa loo wareejiyey Bog kale %(to)s', 'redirect-fix-loop': u'Bot: Diyaarinta dib u bilaabista ee %(to)s', 'redirect-remove-loop': u'Bot: Ujeedka u rogista bogga ee dhaqaaqa', }, # Author: Vinie007 'sq': { 'redirect-fix-double': u'Bot: Fixing dyfishtë përcjellëse tek %(to)s', 'redirect-remove-broken': u'[[WP:CSD#G8|G8]]: [[Wikipedia:Redirect|Redirect]] to a deleted or non-existent page', 'redirect-remove-loop': u'[[WP:CSD#G8|G8]]: [[Wikipedia:Redirect|Redirect]] target forms a redirect loop', }, # Author: Rancher 'sr': { 'redirect-fix-double': u'Робот: исправљена двострука преусмерења у %(to)s', 'redirect-remove-broken': u'Робот: преусмерење до обрисане или непостојеће странице', 'redirect-fix-broken-moved': u'Робот: исправљено покварено преусмерење до премештене циљне странице %(to)s', 'redirect-fix-loop': u'Робот: исправљена петља преусмерења на %(to)s', 'redirect-remove-loop': u'Робот: одредиште преусмерења образује петљу', 'redirect-broken-redirect-template': u'{{db-r1}}', }, # Author: Rancher 'sr-el': { 'redirect-fix-double': u'Robot: ispravljena dvostruka preusmerenja u %(to)s', 'redirect-remove-broken': u'Robot: preusmerenje do obrisane ili nepostojeće stranice', 'redirect-fix-broken-moved': u'Robot: ispravljeno pokvareno preusmerenje do premeštene ciljne stranice %(to)s', 'redirect-fix-loop': u'Robot: ispravljena petlja preusmerenja na %(to)s', 'redirect-remove-loop': u'Robot: odredište preusmerenja obrazuje petlju', }, # Author: Boivie # Author: Jopparn # Author: Lokal Profil # Author: Tobulos1 # Author: WikiPhoenix 'sv': { 'redirect-fix-double': u'Bot: Rättar dubbel omdirigering till %(to)s', 'redirect-remove-broken': u'Bot: Omdirigerar till en raderad eller en icke-existerande sida', 'redirect-fix-broken-moved': u'Bot: Reparerade trasig omdirigering till den flyttade målsidan %(to)s', 'redirect-fix-loop': u'Bot: Fixar omdirigeringsloop till %(to)s', 'redirect-remove-loop': u'Bot: Målet för omdirigeringen bildar en omdirigeringsloop', 'redirect-broken-redirect-template': u'{{radera|Trasig omdirigering}}', }, # Author: Kwisha 'sw': { 'redirect-remove-broken': u'Boti: Uelekezaji kwa ukurasa uliofutwa au ambao haupatikani', 'redirect-fix-loop': u'Boti: Inarekebisha tanzi la uelekezaji kwa %(to)s', }, # Author: Przemub 'szl': { 'redirect-fix-double': u'Robot sprowjo tuplowane przekerowańa → %(to)s', 'redirect-remove-broken': u'Robot: pukniyńcie dŏ wyciepanej zajty', 'redirect-fix-loop': u'Robot: Naprawa mocki pukniyńć dŏ (to)s', 'redirect-remove-loop': u'Robot: mocka pukniyńć', 'redirect-broken-redirect-template': u'{{delete|pukniyńciy dŏ wyciepanyj zajty}}', }, # Author: செல்வா 'ta': { 'redirect-remove-broken': u'[[WP:CSD#G8|G8]]: நீக்கப்பட்ட அல்லது இல்லாத பக்கத்துக்கு [[Wikipedia:Redirect|வழிமாற்று]]', }, # Author: Nullzero 'th': { 'redirect-fix-double': u'โรบอต: แก้หน้าเปลี่ยนทางซ้ำซ้อน → %(to)s', 'redirect-remove-broken': u'โรบอต: หน้าเปลี่ยนทางเสีย', 'redirect-fix-broken-moved': u'โรบอต: แก้หน้าเปลี่ยนทางเสียไปยังหน้าเป้าหมายการย้าย %(to)s', 'redirect-fix-loop': u'โรบอต: แก้หน้าเปลี่ยนทางวนรอบ → %(to)s', 'redirect-remove-loop': u'โรบอต: หน้าเปลี่ยนทางทำให้เกิดการเปลี่ยนทางวนรอบ', 'redirect-broken-redirect-template': u'{{ลบ|หน้าเปลี่ยนทางเสีย}}', }, # Author: AnakngAraw 'tl': { 'redirect-fix-double': u'Bot: Kinukumpuni ang nagkadalawang pagpapapunta sa %(to)s', 'redirect-remove-broken': u'[[WP:CSD#G8|G8]]: [[Wikipedia:Redirect|Papuntahin]] sa isang pahinang nabura na o hindi na umiiral', 'redirect-fix-loop': u'Robot: Kinukumpuni ang silo ng pagpapapunta sa %(to)s', 'redirect-remove-loop': u'[[WP:CSD#G8|G8]]: [[Wikipedia:Redirect|Ang pagpapapunta sa ibang pook]] ay bumubuo ng nakalikaw na pagpapapunta', }, # Author: Gorizon # Author: Xqt # Author: Гусейн 'tly': { 'redirect-fix-double': u'Робот: дығатә унвон дәгиш кардеј сәрост карде → %(to)s', 'redirect-remove-broken': u'Робот: Истиғомәти дәгиш карде бә молә быә јаанки бә мывҹуд ныбә сәһифә', 'redirect-fix-broken-moved': u'Робот: Бә вырәку дәгиш кардә быә мәғсәдә сәһифә %(to)s дәгиш быә истиғомәти сәрост кардеј', 'redirect-fix-loop': u'Робот: Истиғомәти дәгиш кардә ангыли сохте бә %(to)s', 'redirect-remove-loop': u'Bot: Унвони дәгиш карде бешә формон унвони дәгиш кардеј мәрә', }, # Author: Emperyan # Author: Khutuck # Author: Stultiwikia # Author: Vito Genovese # Author: Xqt 'tr': { 'redirect-fix-double': u'Bot: %(to)s sayfasına yönelik çift yönlendirme düzeltiliyor', 'redirect-remove-broken': u'Bot: Silinen ya da var olmayan sayfaya olan yönlendirme', 'redirect-remove-loop': u'Bot: Yönlendirme hedefi bir yönlendirme döngüsü oluşturuyor', 'redirect-broken-redirect-template': u'{{sil|y1}}', }, # Author: Ильнар 'tt': { 'redirect-fix-double': u'Робот: икеле күчешне дөресләү → %(to)s', 'redirect-remove-broken': u'[[ВП:ТБК#П1|П1]]: беркаяда күчеш ясамау', 'redirect-remove-loop': u'[[ВП:ТБК#П1|тиз бетерү критерийлары \'\'П.1\'\']] — беркаяда күчеш ясамау', }, # Author: Ahonc # Author: Andriykopanytsia # Author: Base # Author: Xqt # Author: Тест 'uk': { 'redirect-fix-double': u'Робот: виправлення подвійного перенаправлення → %(to)s', 'redirect-remove-broken': u'бот: перенаправлення на вилучену або неіснуючу сторінку', 'redirect-fix-broken-moved': u'Робот: Виправлення розірваного перенаправлення на сторінку, перейменовану на %(to)s', 'redirect-fix-loop': u'бот: виправлення петлі перенаправлень на %(to)s', 'redirect-remove-loop': u'бот: перенаправлення формують петлю', 'redirect-broken-redirect-template': u'{{db-reason|перенаправлення до вилученої або неіснуючої сторінки}}', }, # Author: Muhammad Shuaib 'ur': { 'redirect-fix-double': u'روبالہ: درستگی دوہرا رجوع مکرر بجانب %(to)s', }, # Author: Alunardon90 # Author: Candalua # Author: GatoSelvadego 'vec': { 'redirect-fix-double': u'Robot: Sistemo i dopi rimandi a %(to)s', 'redirect-remove-broken': u'Bot: Rinvio a na pagina scancelà o mia esistente', 'redirect-fix-loop': u'Robot: Preparasion de un ciclo de rindirisamento a %(to)s', 'redirect-remove-loop': u'Ła destinasion del rindirisamento rimanda a ła pajina de partensa', 'redirect-broken-redirect-template': u'{{Scanseła suito|9}}', }, # Author: Emaus 'vep': { 'redirect-fix-double': u'Bot kohenzi kaksitadud läbikosketusen %(to)s', }, # Author: Minh Nguyen 'vi': { 'redirect-fix-double': u'Bot: Giải quyết đổi hướng kép đến %(to)s', 'redirect-remove-broken': u'Bot: [[Wikipedia:Trang đổi hướng|Đổi hướng]] đến trang xóa hoặc không tồn tại', 'redirect-fix-broken-moved': u'Bot: Sửa đổi hướng sai; trang đích đã được di chuyển đến %(to)s', 'redirect-fix-loop': u'Bot: Sửa vòng lặp đổi hướng đến %(to)s', 'redirect-remove-loop': u'Bot: [[Wikipedia:Trang đổi hướng|Đổi hướng]] qua lại', 'redirect-broken-redirect-template': u'{{Chờ xóa}}', }, # Author: Malafaya 'vo': { 'redirect-broken-redirect-template': u'{{moükön|Lüodüköm dädik}}', }, # Author: Harvzsf 'war': { 'redirect-fix-double': u'Robot: Gin-ayad in nagduduha nga redirek → %(to)s', 'redirect-remove-broken': u'Robot: Redirek ngadto hin ginpárà o waray-didâ nga pakli', 'redirect-fix-loop': u'Robot: Gin-aayad in redirek nga loop ngadto ha %(to)s', 'redirect-remove-loop': u'Robot: An redirek nga ginkakadtoan naghihimo hin redirek nga loop', 'redirect-broken-redirect-template': u'{{delete}}Nautod o nagbinalikbalik nga redirek.', }, # Author: פוילישער 'yi': { 'redirect-fix-double': u'באט: פארראכטן פארטאפלטע ווייטערפירונג → %(to)s', 'redirect-remove-broken': u'באט: ווײַטערפֿירונג צו א בלאט וואס איז אויסגעמעקט אדער עקזיסטירט נישט', 'redirect-fix-broken-moved': u'באט: פאררעכטן צעבראכענע ווייטערפירונג צו באוועגטן ציל בלאט %(to)s', 'redirect-fix-loop': u'באט: פאררעכטן ווייטערפירונג שלייף אויף %(to)s', 'redirect-remove-loop': u'באט: [[װיקיפּעדיע:ווייטערפירונג|ווייטערפירוג]] ציל שאפט א שלייף', }, # Author: Demmy 'yo': { 'redirect-broken-redirect-template': u'{{db-r1}}', }, # Author: Liangent # Author: Linforest # Author: Yfdyh000 # Author: 阿pp 'zh': { 'redirect-fix-double': u'机器人：修正双重重定向至%(to)s', 'redirect-remove-broken': u'机器人：重定向到已删除或不存在的页面', 'redirect-fix-broken-moved': u'机器人：修复破损的重定向到已移动的目标页面 %(to)s', 'redirect-fix-loop': u'机器人：修复重定向循环至%(to)s', 'redirect-remove-loop': u'机器人：重定向目标构成循环', 'redirect-broken-redirect-template': u'{{db-r1}}', }, 'zh-classical': { 'redirect-fix-double': u'僕:復修渡口 → %(to)s', }, # Author: Andrew971218 # Author: Justincheng12345 # Author: Liangent # Author: Simon Shek 'zh-hant': { 'redirect-fix-double': u'機械人：修正雙重定向至%(to)s', 'redirect-remove-broken': u'機械人：重定向到已刪除或不存在的頁面', 'redirect-fix-broken-moved': u'機械人：修復損壞的重定向頁到移動目標頁面 %(to)s', 'redirect-fix-loop': u'機械人：修復重定向迴圈至%(to)s', 'redirect-remove-loop': u'機械人：重定向目標構成循環', }, # Author: Justincheng12345 'zh-hk': { 'redirect-fix-double': u'機械人修正雙重定向至%(to)s', 'redirect-remove-broken': u'[[WP:SD#G15|G15]]：[[Wikipedia:重定向|重定向]]到已刪除或不存在的頁面', 'redirect-fix-broken-moved': u'機械人修復損壞的重定向到已移動的目標頁面%(to)s', 'redirect-fix-loop': u'機械人修復重定向迴圈至%(to)s', 'redirect-remove-loop': u'[[WP:SD#R5|R5]]：[[Wikipedia:重定向|重定向]]目標構成循環', }, 'zh-yue': { 'redirect-fix-double': u'機械人：拉直連串跳轉 → %(to)s', 'redirect-remove-broken': u'機械人：跳轉目標唔存在', }, };

[ "[email protected]" ]

[email protected]

6515cadde03f814f557d7bbe33305e6298e66d6d

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/huaweicloud-sdk-cse/huaweicloudsdkcse/v1/model/get_kie_configs.py

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# coding: utf-8 import six from huaweicloudsdkcore.utils.http_utils import sanitize_for_serialization class GetKieConfigs: """ Attributes: openapi_types (dict): The key is attribute name and the value is attribute type. attribute_map (dict): The key is attribute name and the value is json key in definition. """ sensitive_list = [] openapi_types = { 'id': 'str', 'key': 'str', 'labels': 'object', 'value': 'str', 'value_type': 'str', 'status': 'str', 'create_time': 'int', 'update_time': 'int', 'create_revision': 'int', 'update_revision': 'int' } attribute_map = { 'id': 'id', 'key': 'key', 'labels': 'labels', 'value': 'value', 'value_type': 'value_type', 'status': 'status', 'create_time': 'create_time', 'update_time': 'update_time', 'create_revision': 'create_revision', 'update_revision': 'update_revision' } def __init__(self, id=None, key=None, labels=None, value=None, value_type=None, status=None, create_time=None, update_time=None, create_revision=None, update_revision=None): """GetKieConfigs The model defined in huaweicloud sdk :param id: 配置项的id。 :type id: str :param key: 配置项的key。 :type key: str :param labels: 配置项的标签。 :type labels: object :param value: 配置项的值。 :type value: str :param value_type: 配置项value的类型。 :type value_type: str :param status: 配置项的状态。 :type status: str :param create_time: 创建时间。 :type create_time: int :param update_time: 更新时间。 :type update_time: int :param create_revision: 创建配置的版本号 :type create_revision: int :param update_revision: 修改配置的版本号 :type update_revision: int """ self._id = None self._key = None self._labels = None self._value = None self._value_type = None self._status = None self._create_time = None self._update_time = None self._create_revision = None self._update_revision = None self.discriminator = None if id is not None: self.id = id if key is not None: self.key = key if labels is not None: self.labels = labels if value is not None: self.value = value if value_type is not None: self.value_type = value_type if status is not None: self.status = status if create_time is not None: self.create_time = create_time if update_time is not None: self.update_time = update_time if create_revision is not None: self.create_revision = create_revision if update_revision is not None: self.update_revision = update_revision @property def id(self): """Gets the id of this GetKieConfigs. 配置项的id。 :return: The id of this GetKieConfigs. :rtype: str """ return self._id @id.setter def id(self, id): """Sets the id of this GetKieConfigs. 配置项的id。 :param id: The id of this GetKieConfigs. :type id: str """ self._id = id @property def key(self): """Gets the key of this GetKieConfigs. 配置项的key。 :return: The key of this GetKieConfigs. :rtype: str """ return self._key @key.setter def key(self, key): """Sets the key of this GetKieConfigs. 配置项的key。 :param key: The key of this GetKieConfigs. :type key: str """ self._key = key @property def labels(self): """Gets the labels of this GetKieConfigs. 配置项的标签。 :return: The labels of this GetKieConfigs. :rtype: object """ return self._labels @labels.setter def labels(self, labels): """Sets the labels of this GetKieConfigs. 配置项的标签。 :param labels: The labels of this GetKieConfigs. :type labels: object """ self._labels = labels @property def value(self): """Gets the value of this GetKieConfigs. 配置项的值。 :return: The value of this GetKieConfigs. :rtype: str """ return self._value @value.setter def value(self, value): """Sets the value of this GetKieConfigs. 配置项的值。 :param value: The value of this GetKieConfigs. :type value: str """ self._value = value @property def value_type(self): """Gets the value_type of this GetKieConfigs. 配置项value的类型。 :return: The value_type of this GetKieConfigs. :rtype: str """ return self._value_type @value_type.setter def value_type(self, value_type): """Sets the value_type of this GetKieConfigs. 配置项value的类型。 :param value_type: The value_type of this GetKieConfigs. :type value_type: str """ self._value_type = value_type @property def status(self): """Gets the status of this GetKieConfigs. 配置项的状态。 :return: The status of this GetKieConfigs. :rtype: str """ return self._status @status.setter def status(self, status): """Sets the status of this GetKieConfigs. 配置项的状态。 :param status: The status of this GetKieConfigs. :type status: str """ self._status = status @property def create_time(self): """Gets the create_time of this GetKieConfigs. 创建时间。 :return: The create_time of this GetKieConfigs. :rtype: int """ return self._create_time @create_time.setter def create_time(self, create_time): """Sets the create_time of this GetKieConfigs. 创建时间。 :param create_time: The create_time of this GetKieConfigs. :type create_time: int """ self._create_time = create_time @property def update_time(self): """Gets the update_time of this GetKieConfigs. 更新时间。 :return: The update_time of this GetKieConfigs. :rtype: int """ return self._update_time @update_time.setter def update_time(self, update_time): """Sets the update_time of this GetKieConfigs. 更新时间。 :param update_time: The update_time of this GetKieConfigs. :type update_time: int """ self._update_time = update_time @property def create_revision(self): """Gets the create_revision of this GetKieConfigs. 创建配置的版本号 :return: The create_revision of this GetKieConfigs. :rtype: int """ return self._create_revision @create_revision.setter def create_revision(self, create_revision): """Sets the create_revision of this GetKieConfigs. 创建配置的版本号 :param create_revision: The create_revision of this GetKieConfigs. :type create_revision: int """ self._create_revision = create_revision @property def update_revision(self): """Gets the update_revision of this GetKieConfigs. 修改配置的版本号 :return: The update_revision of this GetKieConfigs. :rtype: int """ return self._update_revision @update_revision.setter def update_revision(self, update_revision): """Sets the update_revision of this GetKieConfigs. 修改配置的版本号 :param update_revision: The update_revision of this GetKieConfigs. :type update_revision: int """ self._update_revision = update_revision def to_dict(self): """Returns the model properties as a dict""" result = {} for attr, _ in six.iteritems(self.openapi_types): value = getattr(self, attr) if isinstance(value, list): result[attr] = list(map( lambda x: x.to_dict() if hasattr(x, "to_dict") else x, value )) elif hasattr(value, "to_dict"): result[attr] = value.to_dict() elif isinstance(value, dict): result[attr] = dict(map( lambda item: (item[0], item[1].to_dict()) if hasattr(item[1], "to_dict") else item, value.items() )) else: if attr in self.sensitive_list: result[attr] = "****" else: result[attr] = value return result def to_str(self): """Returns the string representation of the model""" import simplejson as json if six.PY2: import sys reload(sys) sys.setdefaultencoding("utf-8") return json.dumps(sanitize_for_serialization(self), ensure_ascii=False) def __repr__(self): """For `print`""" return self.to_str() def __eq__(self, other): """Returns true if both objects are equal""" if not isinstance(other, GetKieConfigs): return False return self.__dict__ == other.__dict__ def __ne__(self, other): """Returns true if both objects are not equal""" return not self == other

[ "[email protected]" ]

[email protected]

64c7384fef7e4dd6391e4f314b57c6de80fca160

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import os import site from dj_scaffold.env import add_site_dir HERE = os.path.dirname(__file__) ROOT_PATH = os.path.abspath(os.path.join(HERE, '../')) ALLDIRS = [os.path.join(ROOT_PATH, 'env/lib/python2.7/site-packages'), os.path.join(ROOT_PATH, 'sites')] add_site_dir(ALLDIRS) os.environ['DJANGO_SETTINGS_MODULE'] = 'settings' import django.core.handlers.wsgi application = django.core.handlers.wsgi.WSGIHandler()

[ "[email protected]" ]

[email protected]

b18b81bc61a1aca39d22a6fef58527e12ba9bee6

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/pyguide/__init__.py

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MacHu-GWU/pyrabbit-python-advance-guide-project

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#!/usr/bin/env python # -*- coding: utf-8 -*- """ Description: This is a project documents everything the author learned from a newbie becoming a Senior Python developer. This document is written mainly in Chinese, but I am trying to do the best to make it bilingual. Because I believe python3 is the future of python, so everything is tested in python33. 说明: pyrabbit-python-advance-guide-project 是一个将笔者从一个无任何计算机背景的菜鸟到成长为一个高级Python开发者 - 大数据科学家的路上, 所学到的所有Python的知识。经过笔者的思考, 和精心挑选的可执行的代码例子, 并将整个文档网站化, 可搜索化的一个项目。本项目基于Python33社区项目主要分为下面5大部分: - :mod:`cookbook <pyguide.cookbook>`: 一些有关Python的深入探讨 - :mod:`newbie <pyguide.newbie>`: 从零开始学Python - :mod:`ref <pyguide.ref>`: Python官方参考文档中的精华总结 - :mod:`stdlib <pyguide.stdlib>`: Python标准库的摘要 - :mod:`package <pyguide.package>`: 第三方库相关文档 """

[ "[email protected]" ]

[email protected]

c34bf6f617607609bc89a2cc4b71f7dc5a3de12d

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import sys def printFunction(lineRemaining): if lineRemaining[0] == '"' and lineRemaining[-1] == '"': if len(lineRemaining) > 2: #data to print lineRemaining = lineRemaining[1:-1] print ' '.join(lineRemaining) else: print def main(fileName): with open(fileName) as f: for line in f: data = line.split() if data[0] == 'l_6': printFunction(data[1:]) else: print 'ERROR' return if __name__ == '__main__': main(sys.argv[1])

[ "[email protected]" ]

[email protected]

b79edf89c8828024f571709b514601ebae22c9db

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/dataset_processing/contours_gilbert_256_sparse_nonRandomShear.py

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dmely/contextual_circuit_bp

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refs/heads/master

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import os import re import numpy as np import tensorflow as tf from glob import glob from config import Config from ops import tf_fun class data_processing(object): def __init__(self): self.name = 'contours_gilbert_256_sparse_nonRandomShear' self.im_extension = '.png' self.images_dir = 'images' self.label_regex = r'(?<=length)\d+' self.config = Config() self.im_size = [256, 256, 3] # 600, 600 self.model_input_image_size = [256, 256, 3] # [107, 160, 3] self.max_ims = 0 self.output_size = [1] self.label_size = self.output_size self.default_loss_function = 'cce' self.score_metric = 'accuracy' self.store_z = False self.normalize_im = True self.shuffle = True self.input_normalization = 'zscore' self.preprocess = [''] # ['resize_nn'] self.folds = { 'train': 'train', 'val': 'val' } self.cv_split = 0.9 self.cv_balance = True self.targets = { 'image': tf_fun.bytes_feature, 'label': tf_fun.int64_feature } self.tf_dict = { 'image': tf_fun.fixed_len_feature(dtype='string'), 'label': tf_fun.fixed_len_feature(dtype='int64') } self.tf_reader = { 'image': { 'dtype': tf.float32, 'reshape': self.im_size }, 'label': { 'dtype': tf.int64, 'reshape': self.output_size } } def get_data(self): """Get the names of files.""" files = np.asarray( glob( os.path.join( self.config.data_root, self.name, '*%s' % self.im_extension))) labels = np.asarray( [int(re.search(self.label_regex, x).group()) for x in files]) labels = (labels > 1).astype(np.int32) ul, lc = np.unique(labels, return_counts=True) include_count = np.min(lc) if self.max_ims: include_count = np.min([include_count, lc]) # Trim files and labels to include_count pos_idx = np.where(labels == 1)[0][:include_count] neg_idx = np.where(labels == 0)[0][:include_count] # Create CV folds cv_files, cv_labels = {}, {} cv_files[self.folds['train']] = {} cv_files[self.folds['val']] = {} prev_cv = 0 for k, v in self.folds.iteritems(): if k == self.folds['train']: cv_split = int(include_count * self.cv_split) elif k == self.folds['val']: cv_split = int(include_count * (1 - self.cv_split)) else: raise NotImplementedError if prev_cv: cv_split += prev_cv cv_inds = np.arange(prev_cv, cv_split) it_files = np.concatenate(( files[pos_idx][cv_inds], files[neg_idx][cv_inds])) it_labels = np.concatenate(( labels[pos_idx][cv_inds], labels[neg_idx][cv_inds])) if self.shuffle: shuffle_idx = np.random.permutation(len(it_files)) it_files = it_files[shuffle_idx] it_labels = it_labels[shuffle_idx] cv_files[k] = it_files cv_labels[k] = it_labels prev_cv = cv_split return cv_files, cv_labels

[ "[email protected]" ]

[email protected]

7c67f33358881bf71360ee38962dfd0d831b637a

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from typing import List, Optional import torch from torch import tensor import torch.nn as nn class ShortcutProjection(nn.Module): def __init__(self, in_channels: int, out_channels: int, stride: int): super().__init__() self.conv = nn.Conv2d(in_channels, out_channels, kernel_size=1, stride=stride) self.bn = nn.BatchNorm2d(out_channels) def forward(self, x: torch.Tensor): return self.bn(self.conv(x)) class ResidualBlock(nn.Module): def __init__(self, in_channels: int, out_channels: int, stride: int): super().__init__() self.conv1 = nn.Conv2d(in_channels, out_channels, kernel_size=3, stride=stride, padding=1) self.bn1 = nn.BatchNorm2d(out_channels) self.act1 = nn.ReLU() self.conv2 = nn.Conv2d(out_channels, out_channels, kernel_size=3, stride=1, padding=1) self.bn2 = nn.BatchNorm2d(out_channels) if stride != 1 or in_channels != out_channels: self.shortcut = ShortcutProjection(in_channels, out_channels, stride) else: self.shortcut = nn.Identity() self.act2 = nn.ReLU() def forward(self, x): shortcut = self.shortcut(x) x = self.act1(self.bn1(self.conv1(x))) x = self.bn2(self.conv2(x)) return self.act2(x + shortcut) class BottleneckResidualBlock(nn.Module): def __init__(self, in_channels: int, bottleneck_channels: int, out_channels: int, stride: int): super().__init__() self.conv1 = nn.Conv2d(in_channels, bottleneck_channels, kernel_size=1, stride=1) self.bn1 = nn.BatchNorm2d(bottleneck_channels) self.act1 = nn.ReLU() self.conv2 = nn.Conv2d(bottleneck_channels, bottleneck_channels, kernel_size=3, stride=stride, padding=1) self.bn2 = nn.BatchNorm2d(bottleneck_channels) self.act2 = nn.ReLU() self.conv3 = nn.Conv2d(bottleneck_channels, out_channels, kernel_size=1, stride=1) self.bn3 = nn.BatchNorm2d(out_channels) if stride != 1 or in_channels != out_channels: self.shortcut = ShortcutProjection(in_channels, out_channels, stride) else: self.shortcut = nn.Identity() self.act3 = nn.ReLU() def forward(self, x: torch.Tensor): shortcut = self.shortcut(x) x = self.act1(self.bn1(self.conv1(x))) x = self.act2(self.bn2(self.conv2(x))) x = self.bn3(self.conv3(x)) return self.act3(x + shortcut) class ResNetBase(nn.Module): def __init__(self, n_blocks: List[int], n_channels: List[int], bottlenecks: Optional[List[int]] = None, img_channels: int = 3, first_kernel_size: int = 7): super().__init__() assert len(n_blocks) == len(n_channels) assert bottlenecks is None or len(bottlenecks) == len(n_channels) self.conv = nn.Conv2d(img_channels, n_channels[0], kernel_size=first_kernel_size, stride=2, padding=first_kernel_size // 2) self.bn = nn.BatchNorm2d(n_channels[0]) blocks = [] prev_channel = n_channels[0] for i, channels in enumerate(n_channels): if len(blocks) == 0: stride = 2 else: stride = 1 if bottlenecks is None: blocks.append(ResidualBlock(prev_channel, channels, stride=stride)) else: blocks.append(BottleneckResidualBlock(prev_channel, bottlenecks[i], channels, stride=stride)) prev_channel = channels for _ in range(n_blocks[i] - 1): if bottlenecks is None: blocks.append(ResidualBlock(channels, channels, stride=1)) else: blocks.append(BottleneckResidualBlock(channels, bottlenecks[i], channels, stride=1)) self.blocks = nn.Sequential(*blocks) def forward(self, x: torch.Tensor): x = self.bn(self.conv(x)) x = self.blocks(x) x = x.view(x.shape[0], x.shape[1], -1) return x.mean(dim=-1)

[ "[email protected]" ]

[email protected]

6ba198aa9789fafafad70ec42d47555fbc892bfd

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AdamZhouSE/pythonHomework

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n=int(input()) stack=[] for i in range(n): command=input().split() if command[0]=='Add': stack.append(command) elif command[0]=='Del': ind=int(command[1]) if ind-1>=0 and ind-1<len(stack): stack[ind-1][0]='No' else: x=int(command[1]) res=0 for j in range(len(stack)): if stack[j][0]=="Add": tem=int(stack[j][1])*x+int(stack[j][2]) if tem>int(stack[j][3]): res+=1 print(res)

[ "[email protected]" ]

[email protected]

18ad0fb390f8a5da0684d613ebbd0b40b06b19e0

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MaryanneNjeri/pythonModules

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def MinWindowSubstring(strArr): # code goes here containing_string = strArr[0] # first string search_string = ''.join(sorted(strArr[1])) # second string print(len(search_string)) min_chars_required = len(search_string) solution = '' solution_array = [] for x in containing_string: solution += x total_cnt = 0 print("",solution) for c in search_string: found_cnt = solution.count(c) needed_cnt = search_string.count(c) if found_cnt >= needed_cnt: total_cnt += 1 # print(total_cnt) if total_cnt == min_chars_required: solution_array.append(solution) # print(solution_array) # solution = '' # actual_solution_array = [] # for word in solution_array: # word = word [::-1] # for x in word: # solution += x # total_cnt = 0 # # print(solution) # for c in search_string: # found_cnt = solution.count(c) # needed_cnt = search_string.count(c) # if found_cnt >= needed_cnt: # total_cnt += 1 # # print(total_cnt) # if total_cnt == min_chars_required: # actual_solution_array.append(solution) # answer = min((word for word in actual_solution_array if word), key=len) # answer = answer [::-1] # return answer print(MinWindowSubstring(["sz","azjskfzts"]))

[ "[email protected]" ]

[email protected]

12c9baca46273c4388c17257f7bd4400874025fc

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xiongchenyan/cxPyLib

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''' Created on Mar 25, 2014 input: train, dev|test, para output: accuracy, label of required @author: cx ''' import site site.addsitedir('/bos/usr0/cx/PyCode/Geektools') site.addsitedir('/bos/usr0/cx/PyCode/QueryExpansion') site.addsitedir('/bos/usr0/cx/PyCode/cxPylib') site.addsitedir('/bos/usr0/cx/LibSVM/libsvm/python/') from LibSVMRelate.SVMBase import * from svmutil import * from cxBase.base import * from cxBase.ContingencyTable import * import json class SVMRunSingleParaC(object): def LoadData(self,InName): print "to be implemented by my inherited class" return [[],[]] def DumpPrediction(self,OutName,TestInName ,p_label,p_val): print "to be implemented by my inherited class" return False def Process(self,TrainInName,TestInName,ParaInName,OutName): lY,lX = self.LoadData(TrainInName) lSVMPara = ReadSVMParaSet(ParaInName) SVMPara = lSVMPara[0] #only use first one SVMModel = svm_train(lY,lX,SVMPara.dump()) lTestY,lTestX = self.LoadData(TestInName) p_label,p_acc,p_val = svm_predict(lTestY,lTestX,SVMModel,'-b 1') #add a contengency matrix output? lCTable = ContingencyTable(p_label,lTestY) print json.dumps(lCTable) out = open(OutName,'w') json.dump(lCTable,out) out.close() self.DumpPrediction(OutName + "_pre", TestInName, p_label, p_val) return True

[ "[email protected]" ]

[email protected]

fc3532d68cd78aace0e9f911ff245742aa89aed3

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/models/cells/modelPC2006Akemann.py

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# ~/models/cells/modelPC2006Akemann.py import os pwd = os.getcwd() # record root directory path ~/cerebmodels path_to_files = pwd + os.sep + "models" + os.sep + "cells" + os.sep + \ "PC2006Akemann" + os.sep # record path to this model/folder from models.cells.PC2006Akemann.Purkinje import Purkinje from executive import ExecutiveControl from managers.simulation import SimulationManager as sm from managers.read import ReadManager as rm from managers.signalprocessing import SignalProcessingManager as spm import sciunit from cerebunit.capabilities.cells.response import ProducesElectricalResponse from cerebunit.capabilities.cells.measurements import ProducesSomaRestingVm, ProducesSomaSpikeHeight #from pdb import set_trace as breakpoint class PurkinjeCell( sciunit.Model, ProducesElectricalResponse, ProducesSomaRestingVm ): """USE CASE: """ # AFTER the model is in the HBP Validation Framework Model catalog, set the generated uuid #uuid = "22dc8fd3-c62b-4e07-9e47-f5829e038d6d" def __init__(self): ### ===================== Descriptive Attributes ====================== self.modelscale = "cells" self.modelname = "PC2006Akemann" # ------specify cell-regions from with response are recorded------- self.regions = {"soma": ["v"]} #"dend_sm": ["v"], "dend_sp": ["v"]} self.recordingunits = {"v": "mV"} # -----------attributed inheritance from sciunit.Model-------------- self.name = "Akemann and Knöpfel 2006 model of PurkinjeCell" self.description = "Akemann & Knöpfel 006 model of PurkinjeCell (PC) and published in 10.1523/JNEUROSCI.5204-05.2006 This is a single compartment model. This model is the SciUnit wrapped version of the NEURON model in modelDB accession # 80769." # ### =================== Instantiate cell template ==================== sm.lock_and_load_model_libraries(modelscale=self.modelscale, modelname=self.modelname) os.chdir(path_to_files) self.cell = Purkinje() os.chdir(pwd) ### =============================================================== self.fullfilename = "nil" self.prediction = "nil" # # ======================================================================= # +++++++++++++++++++++++ MODEL CAPABILITIES ++++++++++++++++++++++++++++ # ======================================================================= # --------------------- produce_voltage_response ------------------------ def produce_voltage_response(self, **kwargs): """generic/essential model response **Keyword Arguments:** kwargs = { "parameters": dictionary with keys, "stimparameters": None or dictionary with keys "type" and "stimlist", "onmodel": instantiated model } """ #ExecutiveControl.launch_model_raw("cells") print("Simulation produce_voltage_response starting ...") ec = ExecutiveControl() # only works when in ~/cerebmodels model = ec.launch_model( parameters = kwargs["parameters"], stimparameters = kwargs["stimparameters"], stimloc = kwargs["stimloc"], onmodel = kwargs["onmodel"], mode = "raw" ) print("File saving ...") fullfilename = ec.save_response() setattr(model, "fullfilename", fullfilename) print("File saved.") print("Simulation produce_voltage_response Done.") return model # ----------------------- produce_soma_restingVm ----------------------------- def produce_soma_restingVm(self, **kwargs): """ kwargs = { "parameters": dictionary with keys, "stimparameters": dictionary with keys "type" and "stimlist", "onmodel": instantiated model } """ print("Sim produce_soma v_restingVm starting ...") ec = ExecutiveControl() # only works when in ~/cerebmodels model = ec.launch_model( parameters = kwargs["parameters"], stimparameters = kwargs["stimparameters"], stimloc = kwargs["stimloc"], onmodel = kwargs["onmodel"], capabilities = {"model": "produce_voltage_response", "vtest": ProducesElectricalResponse}, mode="capability") nwbfile = rm.load_nwbfile(model.fullfilename) orderedepochs = rm.order_all_epochs_for_region(nwbfile=nwbfile, region="soma v") timestamps_over_epochs = [ rm.timestamps_for_epoch( orderedepochs[i] ) for i in range(len(orderedepochs)) ] data_over_epochs = [ rm.data_for_epoch( orderedepochs[i] ) for i in range(len(orderedepochs)) ] baseVms = spm.distill_baseVm_pre_epoch( timestamps = timestamps_over_epochs, datavalues = data_over_epochs ) setattr(model, "prediction", baseVms) print("Simulation produce_soma v_restingVm Done.") return model # ----------------------- produce_soma_spikeheight ------------------------ def produce_soma_spikeheight(self, **kwargs): """ kwargs = { "parameters": dictionary with keys, "stimparameters": dictionary with keys "type" and "stimlist", "onmodel": instantiated model } """ print("Sim produce_soma_spikeheight starting ...") ec = ExecutiveControl() # only works when in ~/cerebmodels model = ec.launch_model( parameters = kwargs["parameters"], stimparameters = kwargs["stimparameters"], stimloc = kwargs["stimloc"], onmodel = kwargs["onmodel"], capabilities = {"model": "produce_voltage_response", "vtest": ProducesElectricalResponse}, mode="capability" ) nwbfile = rm.load_nwbfile(model.fullfilename) orderedepochs = rm.order_all_epochs_for_region(nwbfile=nwbfile, region="soma v") timestamps_over_epochs = [ rm.timestamps_for_epoch( orderedepochs[i] ) for i in range(len(orderedepochs)) ] data_over_epochs = [ rm.data_for_epoch( orderedepochs[i] ) for i in range(len(orderedepochs)) ] baseVm = spm.distill_baseVm_pre_epoch( timestamps = timestamps_over_epochs, datavalues = data_over_epochs ) try: peakVms = spm.distill_peakVm_from_spikes( timestamps = timestamps_over_epochs, datavalues = data_over_epochs ) except: peakVms = baseVm setattr(model, "prediction", peakVms[0] - baseVm[0]) print("Simulation produce_soma_spikeheight Done.") return model # ----------------------- produce_spike_train --------------------------- def produce_spike_train(self, **kwargs): """ Use case: """ pass

[ "[email protected]" ]

[email protected]

b997f16691dc838e057231b7245b34283772c091

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/homeassistant/components/nam/sensor.py

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"""Support for the Nettigo Air Monitor service.""" from __future__ import annotations from datetime import timedelta import logging from typing import cast from homeassistant.components.sensor import ( DOMAIN as PLATFORM, SensorEntity, SensorEntityDescription, ) from homeassistant.config_entries import ConfigEntry from homeassistant.core import HomeAssistant from homeassistant.helpers import entity_registry from homeassistant.helpers.entity_platform import AddEntitiesCallback from homeassistant.helpers.typing import StateType from homeassistant.helpers.update_coordinator import CoordinatorEntity from homeassistant.util.dt import utcnow from . import NAMDataUpdateCoordinator from .const import ATTR_UPTIME, DOMAIN, MIGRATION_SENSORS, SENSORS PARALLEL_UPDATES = 1 _LOGGER = logging.getLogger(__name__) async def async_setup_entry( hass: HomeAssistant, entry: ConfigEntry, async_add_entities: AddEntitiesCallback ) -> None: """Add a Nettigo Air Monitor entities from a config_entry.""" coordinator: NAMDataUpdateCoordinator = hass.data[DOMAIN][entry.entry_id] # Due to the change of the attribute name of two sensors, it is necessary to migrate # the unique_ids to the new names. ent_reg = entity_registry.async_get(hass) for old_sensor, new_sensor in MIGRATION_SENSORS: old_unique_id = f"{coordinator.unique_id}-{old_sensor}" new_unique_id = f"{coordinator.unique_id}-{new_sensor}" if entity_id := ent_reg.async_get_entity_id(PLATFORM, DOMAIN, old_unique_id): _LOGGER.debug( "Migrating entity %s from old unique ID '%s' to new unique ID '%s'", entity_id, old_unique_id, new_unique_id, ) ent_reg.async_update_entity(entity_id, new_unique_id=new_unique_id) sensors: list[NAMSensor | NAMSensorUptime] = [] for description in SENSORS: if getattr(coordinator.data, description.key) is not None: if description.key == ATTR_UPTIME: sensors.append(NAMSensorUptime(coordinator, description)) else: sensors.append(NAMSensor(coordinator, description)) async_add_entities(sensors, False) class NAMSensor(CoordinatorEntity, SensorEntity): """Define an Nettigo Air Monitor sensor.""" coordinator: NAMDataUpdateCoordinator def __init__( self, coordinator: NAMDataUpdateCoordinator, description: SensorEntityDescription, ) -> None: """Initialize.""" super().__init__(coordinator) self._attr_device_info = coordinator.device_info self._attr_unique_id = f"{coordinator.unique_id}-{description.key}" self.entity_description = description @property def native_value(self) -> StateType: """Return the state.""" return cast( StateType, getattr(self.coordinator.data, self.entity_description.key) ) @property def available(self) -> bool: """Return if entity is available.""" available = super().available # For a short time after booting, the device does not return values for all # sensors. For this reason, we mark entities for which data is missing as # unavailable. return ( available and getattr(self.coordinator.data, self.entity_description.key) is not None ) class NAMSensorUptime(NAMSensor): """Define an Nettigo Air Monitor uptime sensor.""" @property def native_value(self) -> str: """Return the state.""" uptime_sec = getattr(self.coordinator.data, self.entity_description.key) return ( (utcnow() - timedelta(seconds=uptime_sec)) .replace(microsecond=0) .isoformat() )

[ "[email protected]" ]

[email protected]

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/练习代码/Flask/6.7/重定向.py

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Mr-big-c/github

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# -*- coding: utf-8 -*- # @File : 重定向.py # @Author: 一稚杨 # @Date : 2018/6/7/007 # @Desc : 重定向和404页面定义 # redirect实现重定向 from flask import Flask, redirect, render_template, flash app = Flask(__name__) app.secret_key = '123456' @app.route("/index1") def index1(): flash("登录成功", category="login") flash("hello",category="hello") return redirect("/index2/") @app.route("/index2/") def index2(): return render_template("flash.html") @app.errorhandler(404) def error(error): return render_template("404.html"),404 # form表单action为空时访问那个页面？结论：当action为空时，数据提交给发送数据的页面 @app.route("/action_none", methods=["GET", "POST"]) def action_none(): return render_template("action.html") app.run(debug=True)

[ "[email protected]" ]

[email protected]

4472c64391e5233857750bdc27edfff4c207f694

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/Python_学习手册/Exercise/timer.py

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xuyagang/pycon

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import time reps = 1000 repslist = range(reps) def timer(func,*pargs, **kargs): start = time.clock() for i in repslist: ret = func(*pargs,**kargs) elapsed = time.clock() - start return (elapsed, ret)

[ "[email protected]" ]

[email protected]

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/src/textbook/chapter5/chapter5-1/chapter5-1-2.py

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mryyomutga/TechnicalSeminar

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# -*- coding: utf-8 -*- # デスクトップアプリケーションの作成2 # ファイル選択ダイアログ import tkinter.filedialog as fd path = fd.askopenfilename( title="ファイルを選択してください", filetypes=[("python", "py")] ) print(path)

[ "[email protected]" ]

[email protected]

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# MIT LICENSE # # Copyright 1997 - 2020 by IXIA Keysight # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), # to deal in the Software without restriction, including without limitation # the rights to use, copy, modify, merge, publish, distribute, sublicense, # and/or sell copies of the Software, and to permit persons to whom the # Software is furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in # all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN # THE SOFTWARE. from ixnetwork_restpy.base import Base from ixnetwork_restpy.files import Files from typing import List, Any, Union class Delay(Base): """Delay each packet. The Delay class encapsulates a required delay resource which will be retrieved from the server every time the property is accessed. """ __slots__ = () _SDM_NAME = 'delay' _SDM_ATT_MAP = { 'Enabled': 'enabled', 'Units': 'units', 'Value': 'value', } _SDM_ENUM_MAP = { 'units': ['kilometers', 'kKilometers', 'kMicroseconds', 'kMilliseconds', 'kSeconds', 'microseconds', 'milliseconds', 'seconds'], } def __init__(self, parent, list_op=False): super(Delay, self).__init__(parent, list_op) @property def Enabled(self): # type: () -> bool """ Returns ------- - bool: If true, delay packets. """ return self._get_attribute(self._SDM_ATT_MAP['Enabled']) @Enabled.setter def Enabled(self, value): # type: (bool) -> None self._set_attribute(self._SDM_ATT_MAP['Enabled'], value) @property def Units(self): # type: () -> str """ Returns ------- - str(kilometers | kKilometers | kMicroseconds | kMilliseconds | kSeconds | microseconds | milliseconds | seconds): Specify the units for the delay value. """ return self._get_attribute(self._SDM_ATT_MAP['Units']) @Units.setter def Units(self, value): # type: (str) -> None self._set_attribute(self._SDM_ATT_MAP['Units'], value) @property def Value(self): # type: () -> int """ Returns ------- - number: Time to delay each packet. """ return self._get_attribute(self._SDM_ATT_MAP['Value']) @Value.setter def Value(self, value): # type: (int) -> None self._set_attribute(self._SDM_ATT_MAP['Value'], value) def update(self, Enabled=None, Units=None, Value=None): # type: (bool, str, int) -> Delay """Updates delay resource on the server. Args ---- - Enabled (bool): If true, delay packets. - Units (str(kilometers | kKilometers | kMicroseconds | kMilliseconds | kSeconds | microseconds | milliseconds | seconds)): Specify the units for the delay value. - Value (number): Time to delay each packet. Raises ------ - ServerError: The server has encountered an uncategorized error condition """ return self._update(self._map_locals(self._SDM_ATT_MAP, locals()))

[ "[email protected]" ]

[email protected]

ccaee085a1c2b7c3aa12fe980fb250035df6e7a2

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import numpy as np # pip install numpy arreglo1 = np.arange(1, 10, dtype=np.int32).reshape((3, 3)) print('Numpy Array 1:\n{}'.format(arreglo1)) arreglo2 = np.arange(3, 0, -1, dtype=np.int32).reshape((1, 3)) print('Numpy Array 2:\n{}'.format(arreglo2)) arreglo3 = np.arange(10, 40, 10, dtype=np.int32).reshape((3, 1)) print('Numpy Array 3:\n{}'.format(arreglo3)) print() # Binary Operations print('Numpy Addition (a1 + a2)') print(arreglo1 + arreglo2, end='\n\n') print('Numpy Addition (a1 + a3)') print(arreglo1 + arreglo3, end='\n\n') print('Numpy Addition (a1 + 5)') print(arreglo1 + 5, end='\n\n')

[ "[email protected]" ]

[email protected]

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def main(): if __name__ == '__main__': main()

[ "[email protected]" ]

[email protected]

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/day18/01_Demo_Logistic_Regression.py

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# -*- coding: utf-8 -*- import sklearn as sk import pandas as pd import numpy as np import matplotlib.pyplot as plt """ We will look at data regarding coronary heart disease (CHD) in South Africa. The goal is to use different variables such as tobacco usage, family history, ldl cholesterol levels, alcohol usage, obesity and more. """ heart = pd.read_csv('Heart_Disease.csv', sep=',', header=0) heart.head() labels = heart.iloc[:,9].values features = heart.iloc[:,:9].values # Splitting the dataset into the Training set and Test set from sklearn.model_selection import train_test_split features_train, features_test, labels_train, labels_test = train_test_split(features, labels, test_size = 0.25, random_state = 0) # Feature Scaling from sklearn.preprocessing import StandardScaler sc = StandardScaler() features_train = sc.fit_transform(features_train) features_test = sc.transform(features_test) # Fitting Logistic Regression to the Training set from sklearn.linear_model import LogisticRegression classifier = LogisticRegression() classifier.fit(features_train, labels_train) #Calculate Class Probabilities probability = classifier.predict_proba(features_test) # Predicting the class labels labels_pred = classifier.predict(features_test) # Making the Confusion Matrix from sklearn.metrics import confusion_matrix cm = confusion_matrix(labels_test, labels_pred)

[ "[email protected]" ]

[email protected]

a3d809d9847fd1ca1ddb0ce237317c2be57f2b9f

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/repos/spikeextractors/spikeextractors/extractors/mdaextractors/mdaio.py

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import numpy as np import struct import os import requests import tempfile import traceback class MdaHeader: def __init__(self, dt0, dims0): uses64bitdims=(max(dims0)>2e9) self.uses64bitdims=uses64bitdims self.dt_code=_dt_code_from_dt(dt0) self.dt=dt0 self.num_bytes_per_entry=get_num_bytes_per_entry_from_dt(dt0) self.num_dims=len(dims0) self.dimprod=np.prod(dims0) self.dims=dims0 if uses64bitdims: self.header_size=3*4+self.num_dims*8 else: self.header_size=(3+self.num_dims)*4 def npy_dtype_to_string(dt): str=dt.str[1:] map={ "f2":'float16', "f4":'float32', "f8":'float64', "i1":'int8', "i2":'int16', "i4":'int32', "u2":'uint16', "u4":'uint32' } return map[str] class DiskReadMda: def __init__(self,path,header=None): self._npy_mode=False self._path=path if (file_extension(path)=='.npy'): raise Exception('DiskReadMda implementation has not been tested for npy files') self._npy_mode=True if header: raise Exception('header not allowed in npy mode for DiskReadMda') if header: self._header=header self._header.header_size=0 else: self._header=_read_header(self._path) def dims(self): if self._npy_mode: A=np.load(self._path,mmap_mode='r') return A.shape return self._header.dims def N1(self): return self.dims()[0] def N2(self): return self.dims()[1] def N3(self): return self.dims()[2] def dt(self): if self._npy_mode: A=np.load(self._path,mmap_mode='r') return npy_dtype_to_string(A.dtype) return self._header.dt def numBytesPerEntry(self): if self._npy_mode: A=np.load(self._path,mmap_mode='r') return A.itemsize return self._header.num_bytes_per_entry def readChunk(self,i1=-1,i2=-1,i3=-1,N1=1,N2=1,N3=1): #print("Reading chunk {} {} {} {} {} {}".format(i1,i2,i3,N1,N2,N3)) if (i2<0): if self._npy_mode: A=np.load(self._path,mmap_mode='r') return A[:,:,i1:i1+N1] return self._read_chunk_1d(i1,N1) elif (i3<0): if N1 != self.N1(): print ("Unable to support N1 {} != {}".format(N1,self.N1())) return None X=self._read_chunk_1d(i1+N1*i2,N1*N2) if X is None: print ('Problem reading chunk from file: '+self._path) return None if self._npy_mode: A=np.load(self._path,mmap_mode='r') return A[:,i2:i2+N2] return np.reshape(X,(N1,N2),order='F') else: if N1 != self.N1(): print ("Unable to support N1 {} != {}".format(N1,self.N1())) return None if N2 != self.N2(): print ("Unable to support N2 {} != {}".format(N2,self.N2())) return None if self._npy_mode: A=np.load(self._path,mmap_mode='r') return A[:,:,i3:i3+N3] X=self._read_chunk_1d(i1+N1*i2+N1*N2*i3,N1*N2*N3) return np.reshape(X,(N1,N2,N3),order='F') def _read_chunk_1d(self,i,N): offset=self._header.header_size+self._header.num_bytes_per_entry*i if is_url(self._path): tmp_fname=_download_bytes_to_tmpfile(self._path,offset,offset+self._header.num_bytes_per_entry*N) try: ret=self._read_chunk_1d_helper(tmp_fname,N,offset=0) except: ret=None #os.remove(tmp_fname) return ret return self._read_chunk_1d_helper(self._path,N,offset=offset) def _read_chunk_1d_helper(self,path0,N,*,offset): f=open(path0,"rb") try: f.seek(offset) ret=np.fromfile(f,dtype=self._header.dt,count=N) f.close() return ret except Exception as e: # catch *all* exceptions print (e) f.close() return None def is_url(path): return path.startswith('http://') or path.startswith('https://') def _download_bytes_to_tmpfile(url,start,end): headers = {"Range": "bytes={}-{}".format(start,end-1)} r = requests.get(url, headers=headers, stream=True) fd, tmp_fname = tempfile.mkstemp() with open(tmp_fname, 'wb') as f: for chunk in r.iter_content(chunk_size=1024): if chunk: f.write(chunk) return tmp_fname def _read_header(path): if is_url(path): tmp_fname=_download_bytes_to_tmpfile(path,0,200) if not tmp_fname: raise Exception('Problem downloading bytes from '+url) try: ret=_read_header(tmp_fname) except: ret=None os.remove(tmp_fname) return ret f=open(path,"rb") try: dt_code=_read_int32(f) num_bytes_per_entry=_read_int32(f) num_dims=_read_int32(f) uses64bitdims=False if (num_dims<0): uses64bitdims=True num_dims=-num_dims if (num_dims<1) or (num_dims>6): # allow single dimension as of 12/6/17 print ("Invalid number of dimensions: {}".format(num_dims)) f.close() return None dims=[] dimprod=1 if uses64bitdims: for j in range(0,num_dims): tmp0=_read_int64(f) dimprod=dimprod*tmp0 dims.append(tmp0) else: for j in range(0,num_dims): tmp0=_read_int32(f) dimprod=dimprod*tmp0 dims.append(tmp0) dt=_dt_from_dt_code(dt_code) if dt is None: print ("Invalid data type code: {}".format(dt_code)) f.close() return None H=MdaHeader(dt,dims) if (uses64bitdims): H.uses64bitdims=True H.header_size=3*4+H.num_dims*8 f.close() return H except Exception as e: # catch *all* exceptions print (e) f.close() return None def _dt_from_dt_code(dt_code): if dt_code == -2: dt='uint8' elif dt_code == -3: dt='float32' elif dt_code == -4: dt='int16' elif dt_code == -5: dt='int32' elif dt_code == -6: dt='uint16' elif dt_code == -7: dt='float64' elif dt_code == -8: dt='uint32' else: dt=None return dt def _dt_code_from_dt(dt): if dt == 'uint8': return -2 if dt == 'float32': return -3 if dt == 'int16': return -4 if dt == 'int32': return -5 if dt == 'uint16': return -6 if dt == 'float64': return -7 if dt == 'uint32': return -8 return None def get_num_bytes_per_entry_from_dt(dt): if dt == 'uint8': return 1 if dt == 'float32': return 4 if dt == 'int16': return 2 if dt == 'int32': return 4 if dt == 'uint16': return 2 if dt == 'float64': return 8 if dt == 'uint32': return 4 return None def readmda_header(path): if (file_extension(path)=='.npy'): raise Exception('Cannot read mda header for .npy file.') return _read_header(path) def _write_header(path,H,rewrite=False): if rewrite: f=open(path,"r+b") else: f=open(path,"wb") try: _write_int32(f,H.dt_code) _write_int32(f,H.num_bytes_per_entry) if H.uses64bitdims: _write_int32(f,-H.num_dims) for j in range(0,H.num_dims): _write_int64(f,H.dims[j]) else: _write_int32(f,H.num_dims) for j in range(0,H.num_dims): _write_int32(f,H.dims[j]) f.close() return True except Exception as e: # catch *all* exceptions print (e) f.close() return False def readmda(path): if (file_extension(path)=='.npy'): return readnpy(path); H=_read_header(path) if (H is None): print ("Problem reading header of: {}".format(path)) return None ret=np.array([]) f=open(path,"rb") try: f.seek(H.header_size) #This is how I do the column-major order ret=np.fromfile(f,dtype=H.dt,count=H.dimprod) ret=np.reshape(ret,H.dims,order='F') f.close() return ret except Exception as e: # catch *all* exceptions print (e) f.close() return None def writemda32(X,fname): if (file_extension(fname)=='.npy'): return writenpy32(X,fname); return _writemda(X,fname,'float32') def writemda64(X,fname): if (file_extension(fname)=='.npy'): return writenpy64(X,fname); return _writemda(X,fname,'float64') def writemda8(X,fname): if (file_extension(fname)=='.npy'): return writenpy8(X,fname); return _writemda(X,fname,'uint8') def writemda32i(X,fname): if (file_extension(fname)=='.npy'): return writenpy32i(X,fname); return _writemda(X,fname,'int32') def writemda32ui(X,fname): if (file_extension(fname)=='.npy'): return writenpy32ui(X,fname); return _writemda(X,fname,'uint32') def writemda16i(X,fname): if (file_extension(fname)=='.npy'): return writenpy16i(X,fname); return _writemda(X,fname,'int16') def writemda16ui(X,fname): if (file_extension(fname)=='.npy'): return writenpy16ui(X,fname); return _writemda(X,fname,'uint16') def writemda(X,fname,*,dtype): return _writemda(X,fname,dtype) def _writemda(X,fname,dt): dt_code=0 num_bytes_per_entry=get_num_bytes_per_entry_from_dt(dt) dt_code=_dt_code_from_dt(dt) if dt_code is None: print ("Unexpected data type: {}".format(dt)) return False if type(fname)==str: f=open(fname,'wb') else: f=fname try: _write_int32(f,dt_code) _write_int32(f,num_bytes_per_entry) _write_int32(f,X.ndim) for j in range(0,X.ndim): _write_int32(f,X.shape[j]) #This is how I do column-major order #A=np.reshape(X,X.size,order='F').astype(dt) #A.tofile(f) bytes0=X.astype(dt).tobytes(order='F') f.write(bytes0) if type(fname)==str: f.close() return True except Exception as e: # catch *all* exceptions traceback.print_exc() print (e) if type(fname)==str: f.close() return False def readnpy(path): return np.load(path) def writenpy8(X,path): return _writenpy(X,path,dtype='int8') def writenpy32(X,path): return _writenpy(X,path,dtype='float32') def writenpy64(X,path): return _writenpy(X,path,dtype='float64') def writenpy16i(X,path): return _writenpy(X,path,dtype='int16') def writenpy16ui(X,path): return _writenpy(X,path,dtype='uint16') def writenpy32i(X,path): return _writenpy(X,path,dtype='int32') def writenpy32ui(X,path): return _writenpy(X,path,dtype='uint32') def writenpy(X,path,*,dtype): return _writenpy(X,path,dtype=dtype) def _writenpy(X,path,*,dtype): np.save(path,X.astype(dtype=dtype,copy=False)) # astype will always create copy if dtype does not match # apparently allowing pickling is a security issue. (according to the docs) ?? #np.save(path,X.astype(dtype=dtype,copy=False),allow_pickle=False) # astype will always create copy if dtype does not match return True def appendmda(X,path): if (file_extension(path)=='.npy'): raise Exception('appendmda not yet implemented for .npy files') H=_read_header(path) if (H is None): print ("Problem reading header of: {}".format(path)) return None if (len(H.dims) != len(X.shape)): print ("Incompatible number of dimensions in appendmda",H.dims,X.shape) return None num_entries_old=np.product(H.dims) num_dims=len(H.dims) for j in range(num_dims-1): if (X.shape[j]!=X.shape[j]): print ("Incompatible dimensions in appendmda",H.dims,X.shape) return None H.dims[num_dims-1]=H.dims[num_dims-1]+X.shape[num_dims-1] try: _write_header(path,H,rewrite=True) f=open(path,"r+b") f.seek(H.header_size+H.num_bytes_per_entry*num_entries_old) A=np.reshape(X,X.size,order='F').astype(H.dt) A.tofile(f) f.close() except Exception as e: # catch *all* exceptions print (e) f.close() return False def file_extension(fname): if type(fname)==str: filename, ext = os.path.splitext(fname) return ext else: return None def _read_int32(f): return struct.unpack('<i',f.read(4))[0] def _read_int64(f): return struct.unpack('<q',f.read(8))[0] def _write_int32(f,val): f.write(struct.pack('<i',val)) def _write_int64(f,val): f.write(struct.pack('<q',val)) def _header_from_file(f): try: dt_code=_read_int32(f) num_bytes_per_entry=_read_int32(f) num_dims=_read_int32(f) uses64bitdims=False if (num_dims<0): uses64bitdims=True num_dims=-num_dims if (num_dims<1) or (num_dims>6): # allow single dimension as of 12/6/17 print ("Invalid number of dimensions: {}".format(num_dims)) return None dims=[] dimprod=1 if uses64bitdims: for j in range(0,num_dims): tmp0=_read_int64(f) dimprod=dimprod*tmp0 dims.append(tmp0) else: for j in range(0,num_dims): tmp0=_read_int32(f) dimprod=dimprod*tmp0 dims.append(tmp0) dt=_dt_from_dt_code(dt_code) if dt is None: print ("Invalid data type code: {}".format(dt_code)) return None H=MdaHeader(dt,dims) if (uses64bitdims): H.uses64bitdims=True H.header_size=3*4+H.num_dims*8 return H except Exception as e: # catch *all* exceptions print (e) return None def mdaio_test(): M=4 N=12 X=np.ndarray((M,N)) for n in range(0,N): for m in range(0,M): X[m,n]=n*10+m writemda32(X,'tmp1.mda') Y=readmda('tmp1.mda') print (Y) print (np.absolute(X-Y).max()) Z=DiskReadMda('tmp1.mda') print (Z.readChunk(i1=0,i2=4,N1=M,N2=N-4)) A=DiskWriteMda('tmpA.mda',(M,N)) A.writeChunk(Y,i1=0,i2=0) B=readmda('tmpA.mda') print (B.shape) print (B) #mdaio_test()

[ "[email protected]" ]

[email protected]

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# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import logging import pathlib from distutils.version import LooseVersion from importlib.metadata import version from typing import List TRITON_CLIENT_VERSION = LooseVersion(version("tritonclient")) # method from PEP-366 to support relative import in executed modules if __package__ is None: __package__ = pathlib.Path(__file__).parent.name from .core import BatchingMode, EvaluationMode, MeasurementMode, OfflineMode from .perf_analyzer import PerfAnalyzer, PerfAnalyzerConfig from .utils import parse_server_url LOGGER = logging.getLogger("warmup") def performance_evaluation_warmup( server_url: str, model_name: str, batch_sizes: List[int], number_of_triton_instances: int, number_of_model_instances: int, input_data: str, input_shapes: List[str], measurement_mode: MeasurementMode, measurement_interval: int, measurement_request_count: int, batching_mode: BatchingMode, offline_mode: OfflineMode, evaluation_mode: EvaluationMode, output_shared_memory_size: int, ): protocol, host, port = parse_server_url(server_url) measurement_interval = 2 * measurement_interval measurement_request_count = 2 * measurement_request_count if batching_mode == BatchingMode.STATIC: batch_sizes = sorted({1, batch_sizes[-1]}) max_concurrency = 1 min_concurrency = 1 step = 1 elif batching_mode == BatchingMode.DYNAMIC: max_batch_size = max(batch_sizes) max_total_requests = 2 * max_batch_size * number_of_triton_instances * number_of_model_instances max_concurrency = min(256, max_total_requests) step = max(1, max_concurrency // 2) min_concurrency = step batch_sizes = [max(1, max_total_requests // 256)] else: raise ValueError(f"Unsupported batching mode: {batching_mode}") for batch_size in batch_sizes: for concurrency in range(min_concurrency, max_concurrency + step, step): params = { "model-name": model_name, "model-version": 1, "batch-size": batch_size, "url": f"{host}:{port}", "protocol": protocol, "input-data": input_data, "measurement-interval": measurement_interval, "concurrency-range": f"{concurrency}:{concurrency}:1", "output-shared-memory-size": output_shared_memory_size, } if TRITON_CLIENT_VERSION >= LooseVersion("2.11.0"): params["measurement-mode"] = measurement_mode.value params["measurement-request-count"] = measurement_request_count if evaluation_mode == EvaluationMode.OFFLINE: params["shared-memory"] = offline_mode.value params["output-shared-memory-size"] = output_shared_memory_size config = PerfAnalyzerConfig() for param, value in params.items(): config[param] = value for shape in input_shapes: config["shape"] = shape perf_analyzer = PerfAnalyzer(config=config) perf_analyzer.run()

[ "[email protected]" ]

[email protected]

9030a9aeac0cd19b1e22c38323c28b02eeb34bd6

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/tests/test_http_response.py

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# # tests/test_http_response.py # import growler import asyncio import pytest from unittest import mock from collections import OrderedDict from growler.http.response import Headers from mock_classes import ( request_uri, ) @pytest.fixture def res(mock_protocol): return growler.http.HTTPResponse(mock_protocol) @pytest.fixture def mock_app(): return mock.Mock(spec=growler.App, ) @pytest.fixture def mock_protocol(mock_app, request_uri): from urllib.parse import (unquote, urlparse, parse_qs) parsed_url = urlparse(request_uri) protocol = mock.Mock(spec=growler.http.GrowlerHTTPProtocol, loop=mock.Mock(spec=asyncio.BaseEventLoop), http_application=mock_app, headers=None, path=unquote(parsed_url.path), query=parse_qs(parsed_url.query),) protocol.socket.getpeername.return_value = ['', ''] return protocol def test_constructor(res, mock_protocol): assert isinstance(res, growler.http.HTTPResponse) assert res.protocol is mock_protocol def test_construct_with_eol(mock_protocol): EOL = ':' res = growler.http.HTTPResponse(mock_protocol, EOL) assert isinstance(res, growler.http.HTTPResponse) assert res.protocol is mock_protocol assert res.EOL is EOL def test_default_headers(res): res._set_default_headers() # assert res.protocol is mock_protocol def test_send_headers(res): res.send_headers() def test_write(res): res.write() def test_write_eof(res): res.write_eof() def test_end(res): res.end() @pytest.mark.parametrize('url, status', [ ('/', 200), ]) def test_redirect(res, url, status): res.redirect(url, status) @pytest.mark.parametrize('obj, expect', [ ({'a': 'b'}, b'{"a": "b"}') ]) def test_json(res, mock_protocol, obj, expect): res.json(obj) assert res.headers['content-type'] == 'application/json' mock_protocol. transport.write.assert_called_with(expect) @pytest.mark.parametrize('obj, expect', [ ({'a': 'b'}, b'{"a": "b"}') ]) def test_headers(res, mock_protocol, obj, expect): res.json(obj) assert res.headers['content-type'] == 'application/json' mock_protocol.transport.write.assert_called_with(expect) def test_header_construct_with_dict(): headers = Headers({'a': 'b', 'c': 'D'}) s = str(headers) assert s == 'a: b\r\nc: D\r\n\r\n' or s == 'c: D\r\na: b\r\n\r\n' def test_header_construct_with_keywords(): headers = Headers(a='b', c='D') s = str(headers) assert s == 'a: b\r\nc: D\r\n\r\n' or s == 'c: D\r\na: b\r\n\r\n' def test_header_construct_mixed(): headers = Headers({'a': 'b'}, c='D') s = str(headers) assert s == 'a: b\r\nc: D\r\n\r\n' or s == 'c: D\r\na: b\r\n\r\n' def test_header_set(): headers = Headers() headers['foo'] = 'bar' assert str(headers) == 'foo: bar\r\n\r\n' def test_header_update_with_dict(): headers = Headers() d = {'foo': 'bar'} headers.update(d) assert str(headers) == 'foo: bar\r\n\r\n' def test_header_update_with_multiple_dicts(): headers = Headers() d_0 = OrderedDict([('foo', 'baz'), ('a', 'b')]) d_1 = {'foo': 'bar'} headers.update(d_0, d_1) assert str(headers) == 'foo: bar\r\na: b\r\n\r\n' def test_header_update_with_keyword(): headers = Headers() headers.update(foo='bar') assert str(headers) == 'foo: bar\r\n\r\n' def test_header_update_with_mixed(): headers = Headers() d = {'foo': 'bazz'} headers.update(d, foo='bar') assert str(headers) == 'foo: bar\r\n\r\n' def test_callable_header_value(): headers = Headers() headers['foo'] = lambda: 'bar' assert str(headers) == 'foo: bar\r\n\r\n'

[ "[email protected]" ]

[email protected]

4d3aacc2cd74a7a3f40fd55c24ee756ac2daa48c

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/src/uproot/dynamic.py

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scikit-hep/uproot5

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# BSD 3-Clause License; see https://github.com/scikit-hep/uproot5/blob/main/LICENSE """ This module is initially empty, a repository for dynamically adding new classes. The purpose of this namespace is to allow :doc:`uproot.model.VersionedModel` classes that were automatically generated from ROOT ``TStreamerInfo`` to be pickled, with the help of :doc:`uproot.model.DynamicModel`. In `Python 3.7 and later <https://www.python.org/dev/peps/pep-0562>`__, attempts to extract items from this namespace generate new :doc:`uproot.model.DynamicModel` classes, which are used as a container in which data from pickled :doc:`uproot.model.VersionedModel` instances are filled. """ def __getattr__(name): import uproot g = globals() if name not in g: g[name] = uproot._util.new_class(name, (uproot.model.DynamicModel,), {}) return g[name]

[ "[email protected]" ]

[email protected]

21b22b5af215a87059bbfe2e4d13bdfb04694bcf

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/ondoc/authentication/migrations/0064_spocdetails_source.py

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no_license

ronit29/docprime

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refs/heads/master

2023-04-01T14:54:10.811765

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# Generated by Django 2.0.5 on 2018-11-02 19:13 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('authentication', '0063_merge_20181025_1818'), ] operations = [ migrations.AddField( model_name='spocdetails', name='source', field=models.CharField(blank=True, max_length=2000), ), ]

[ "[email protected]" ]

[email protected]

51d592ae4b786dcaf62efc0be8022199119a1a5e

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/benchmark/alwayson/testcase/firstcases/testcase5_000.py

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no_license

Prefest2018/Prefest

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refs/heads/master

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#coding=utf-8 import os import subprocess import time import traceback from appium import webdriver from appium.webdriver.common.touch_action import TouchAction from selenium.common.exceptions import NoSuchElementException, WebDriverException desired_caps = { 'platformName' : 'Android', 'deviceName' : 'Android Emulator', 'platformVersion' : '4.4', 'appPackage' : 'com.tomer.alwayson', 'appActivity' : 'com.tomer.alwayson.activities.PreferencesActivity', 'resetKeyboard' : True, 'androidCoverage' : 'com.tomer.alwayson/com.tomer.alwayson.JacocoInstrumentation', 'noReset' : True } def command(cmd, timeout=5): p = subprocess.Popen(cmd, stderr=subprocess.STDOUT, stdout=subprocess.PIPE, shell=True) time.sleep(timeout) p.terminate() return def getElememt(driver, str) : for i in range(0, 5, 1): try: element = driver.find_element_by_android_uiautomator(str) except NoSuchElementException: time.sleep(1) else: return element os.popen("adb shell input tap 50 50") element = driver.find_element_by_android_uiautomator(str) return element def getElememtBack(driver, str1, str2) : for i in range(0, 2, 1): try: element = driver.find_element_by_android_uiautomator(str1) except NoSuchElementException: time.sleep(1) else: return element for i in range(0, 5, 1): try: element = driver.find_element_by_android_uiautomator(str2) except NoSuchElementException: time.sleep(1) else: return element os.popen("adb shell input tap 50 50") element = driver.find_element_by_android_uiautomator(str2) return element def swipe(driver, startxper, startyper, endxper, endyper) : size = driver.get_window_size() width = size["width"] height = size["height"] try: driver.swipe(start_x=int(width * startxper), start_y=int(height * startyper), end_x=int(width * endxper), end_y=int(height * endyper), duration=2000) except WebDriverException: time.sleep(1) driver.swipe(start_x=int(width * startxper), start_y=int(height * startyper), end_x=int(width * endxper), end_y=int(height * endyper), duration=2000) return # testcase000 try : starttime = time.time() driver = webdriver.Remote('http://localhost:4723/wd/hub', desired_caps) driver.press_keycode(82) element = getElememtBack(driver, "new UiSelector().text(\"Uninstall\")", "new UiSelector().className(\"android.widget.TextView\").instance(4)") TouchAction(driver).tap(element).perform() except Exception, e: print 'FAIL' print 'str(e):\t\t', str(e) print 'repr(e):\t', repr(e) print traceback.format_exc() else: print 'OK' finally: cpackage = driver.current_package endtime = time.time() print 'consumed time:', str(endtime - starttime), 's' command("adb shell am broadcast -a com.example.pkg.END_EMMA --es name \"5_000\"") jacocotime = time.time() print 'jacoco time:', str(jacocotime - endtime), 's' driver.quit() if (cpackage != 'com.tomer.alwayson'): cpackage = "adb shell am force-stop " + cpackage os.popen(cpackage)

[ "[email protected]" ]

[email protected]

7eab1eee572d2490d59d02e103bda65a10f64328

4d9a9546a5dc0b550aede272c4ba85af88dbb673

/env/lib/python3.8/site-packages/pandas-stubs/core/computation/parsing.pyi

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LuisGonzalezLopez/Luis-Gonzalez

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refs/heads/master

2022-08-04T14:24:42.992548

2022-07-23T09:03:08

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pyi

import tokenize from typing import ( Iterator, Tuple, ) BACKTICK_QUOTED_STRING: int def create_valid_python_identifier(name: str) -> str: ... def clean_backtick_quoted_toks(tok: Tuple[int, str]) -> Tuple[int, str]: ... def clean_column_name(name: str) -> str: ... def tokenize_backtick_quoted_string( token_generator: Iterator[tokenize.TokenInfo], source: str, string_start: int ) -> Tuple[int, str]: ... def tokenize_string(source: str) -> Iterator[Tuple[int, str]]: ...

[ "[email protected]" ]

[email protected]

b8ddc127cfcb9245e757ef5500e01dc09c429923

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/Code/CodeRecords/2513/60795/267936.py

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[]

no_license

AdamZhouSE/pythonHomework

a25c120b03a158d60aaa9fdc5fb203b1bb377a19

ffc5606817a666aa6241cfab27364326f5c066ff

refs/heads/master

2022-11-24T08:05:22.122011

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n=int(input()) result=[] for i in range(0,n): arr=[int(n) for n in input().split(',')] for j in range(0,n): result.append(arr[j]) k=int(input()) result.sort() print(result[k-1])

[ "[email protected]" ]

[email protected]

88f7cf669ad38ec523e65645a0e13c3f281714a6

c3fc7865f163a43fbd3e832547005cf3c89547c5

/bin/oldScripts/JobCommands/PINN_ECFP4KSEPTRIGRAM_2_3_commands_5.py

8823d4a4539d7476a8d27561bca5f92ef60a1eb6

[]

no_license

ahmetrifaioglu/PyTorch

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refs/heads/master

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import subprocess subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 2048_1024_512 512 512 0.0001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 2048_1024_512 512 512 0.005", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 2048_1024_512 512 512 0.001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 2048_1024_512 256 256 0.0001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 2048_1024_512 256 256 0.005", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 2048_1024_512 256 256 0.001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 2048_1024_512 64 64 0.0001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 2048_1024_512 64 64 0.005", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 2048_1024_512 64 64 0.001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 2048_1024_128 1024 1024 0.0001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 2048_1024_128 1024 1024 0.005", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 2048_1024_128 1024 1024 0.001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 2048_1024_128 512 512 0.0001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 2048_1024_128 512 512 0.005", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 2048_1024_128 512 512 0.001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 2048_1024_128 256 256 0.0001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 2048_1024_128 256 256 0.005", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 2048_1024_128 256 256 0.001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 2048_1024_128 64 64 0.0001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 2048_1024_128 64 64 0.005", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 2048_1024_128 64 64 0.001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 2048_512_128 1024 1024 0.0001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 2048_512_128 1024 1024 0.005", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 2048_512_128 1024 1024 0.001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 2048_512_128 512 512 0.0001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 2048_512_128 512 512 0.005", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 2048_512_128 512 512 0.001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 2048_512_128 256 256 0.0001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 2048_512_128 256 256 0.005", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 2048_512_128 256 256 0.001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 2048_512_128 64 64 0.0001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 2048_512_128 64 64 0.005", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 2048_512_128 64 64 0.001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_1024_512 1024 1024 0.0001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_1024_512 1024 1024 0.005", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_1024_512 1024 1024 0.001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_1024_512 512 512 0.0001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_1024_512 512 512 0.005", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_1024_512 512 512 0.001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_1024_512 256 256 0.0001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_1024_512 256 256 0.005", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_1024_512 256 256 0.001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_1024_512 64 64 0.0001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_1024_512 64 64 0.005", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_1024_512 64 64 0.001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_1024_128 1024 1024 0.0001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_1024_128 1024 1024 0.005", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_1024_128 1024 1024 0.001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_1024_128 512 512 0.0001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_1024_128 512 512 0.005", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_1024_128 512 512 0.001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_1024_128 256 256 0.0001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_1024_128 256 256 0.005", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_1024_128 256 256 0.001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_1024_128 64 64 0.0001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_1024_128 64 64 0.005", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_1024_128 64 64 0.001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_512_128 1024 1024 0.0001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_512_128 1024 1024 0.005", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_512_128 1024 1024 0.001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_512_128 512 512 0.0001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_512_128 512 512 0.005", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_512_128 512 512 0.001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_512_128 256 256 0.0001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_512_128 256 256 0.005", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_512_128 256 256 0.001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_512_128 64 64 0.0001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_512_128 64 64 0.005", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1536_512_128 64 64 0.001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1024_512_128 1024 1024 0.0001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1024_512_128 1024 1024 0.005", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1024_512_128 1024 1024 0.001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1024_512_128 512 512 0.0001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1024_512_128 512 512 0.005", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1024_512_128 512 512 0.001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1024_512_128 256 256 0.0001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1024_512_128 256 256 0.005", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1024_512_128 256 256 0.001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1024_512_128 64 64 0.0001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1024_512_128 64 64 0.005", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1536 1024_512_128 64 64 0.001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1024 4096_2048_1536 1024 1024 0.0001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1024 4096_2048_1536 1024 1024 0.005", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1024 4096_2048_1536 1024 1024 0.001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1024 4096_2048_1536 512 512 0.0001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1024 4096_2048_1536 512 512 0.005", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1024 4096_2048_1536 512 512 0.001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1024 4096_2048_1536 256 256 0.0001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1024 4096_2048_1536 256 256 0.005", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1024 4096_2048_1536 256 256 0.001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1024 4096_2048_1536 64 64 0.0001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1024 4096_2048_1536 64 64 0.005", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1024 4096_2048_1536 64 64 0.001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1024 4096_2048_1024 1024 1024 0.0001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1024 4096_2048_1024 1024 1024 0.005", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1024 4096_2048_1024 1024 1024 0.001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1024 4096_2048_1024 512 512 0.0001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1024 4096_2048_1024 512 512 0.005", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1024 4096_2048_1024 512 512 0.001", shell=True) subprocess.call("python dream_challenge.py PINN_2_3 ecfp4 trigram 4096_1024 4096_2048_1024 256 256 0.0001", shell=True)

[ "[email protected]" ]

[email protected]

054eb96e09b87131cdc8f7bea38c96ab8504d39b

48d8e96e0eba526fb08c74ee17ca0b89b9ea4192

/find_maximum_subarray.py

a4607b76dd28b8813ac5e9f9bf58c916cd3afc30

[]

no_license

John-W-Stevens/algorithms_clrs

12842e246b66f30d4d71c093f7c5919e941eb1f0

e926418f069de0ac7e5d6195b810df1be41edf3f

refs/heads/master

2020-12-21T09:16:35.035058

2020-04-22T18:25:42

236,383,401

2

null

UTF-8

Python

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2,660

py

# Import numpy to use Inf from numpy import Inf def find_max_crossing_subarray(arr,low,mid,high): """ From CLRS pgs. 70-74 "Takes as input an array and indices low,mid,high Returns a tuple containing the indicies demarcating a maximum sub-array that crosses the midpoint, along with the sum of the values in a maximum sub-array." Running time: linear """ # Look at the left left_sum = -Inf sm = 0 # sm for sum for i in range(mid,low-1,-1): sm += arr[i] if sm >= left_sum: left_sum = sm max_left = i # Look at the right right_sum = -Inf sm = 0 for j in range(mid+1,high+1): sm += arr[j] if sm >= right_sum: right_sum = sm max_right = j return (max_left,max_right,left_sum+right_sum) def find_maximum_subarray(arr,low,high): """ From CLSR pgs. 70-74 Input is an array, arr. low and high are index positions in arr that function as bounds for searching. Returns a tuple containing indicies for maximum sub-array along with the sum of sub-array. Running time: theta(n lg n) where 'lg n' stands for log2n """ # Base case if high == low: return (low,high,arr[low]) else: # find middle point of array mid = (low + high)//2 # find a max sub-array in left sub-array left_low,left_high,left_sum = find_maximum_subarray(arr,low,mid) # find a max sub-array in right sub-array right_low,right_high,right_sum = find_maximum_subarray(arr,mid+1,high) # find a max sub-array that crosses the mid-point cross_low,cross_high,cross_sum = find_max_crossing_subarray(arr,low,mid,high) # test if left sub-array contains a sub-array with the maximum sum if left_sum >= right_sum and left_sum >= cross_sum: return (left_low,left_high,left_sum) # test if right sub-array contains a sub-array with the maximum sum elif right_sum >= left_sum and right_sum >= cross_sum: return (right_low,right_high,right_sum) # if neither left nor right sub-arrays contain a sub-array with the maximum sum, # then a maximum sub-array must cross the mid-point else: return (cross_low,cross_high,cross_sum) test = [17, -25, 6, 18, -23, 8, 28, 6, 34, 31, -50, 3, 46, -33, -45, -26, 14, -23, 45, -24, 21, -31, 19, -41, 49, 47, 29, -11, 16, 12, -9, -14, 26, -46, -11, 39, -41, -13, -11, 8, -19, -13, -9, -25, -15, 27, 30, 8, 10] print(find_maximum_subarray(test,0,len(test)-1)) # Output: (24, 32, 145) the maximum subarray exists at test[24:33] and the sum of this subarray is 145

[ "[email protected]" ]

[email protected]

0f104fa41dfb5aa5dba2362b7d925e046b1292c4

e8d7e13eb4d26c0a0147f2d0208d70e61f865c2c

/untitled50/bin/python3.6m-config

54996d6a3566cc7b19ca4b84dbefad58b93fe58f

[]

no_license

fazi4888/APCSP-FreshmanYear

55c5b5717aadeb2d871582754174f88213a488fe

b4f0f797b2c469e148b0330ad9d309610f1f0668

refs/heads/master

2022-11-30T11:51:30.210342

2020-08-17T15:00:37

null

0

null

UTF-8

Python

false

2,062

#!/Users/rayaan_siddiqi23/untitled50/bin/python # -*- python -*- # Keep this script in sync with python-config.sh.in import getopt import os import sys import sysconfig valid_opts = ['prefix', 'exec-prefix', 'includes', 'libs', 'cflags', 'ldflags', 'extension-suffix', 'help', 'abiflags', 'configdir'] def exit_with_usage(code=1): print("Usage: {0} [{1}]".format( sys.argv[0], '|'.join('--'+opt for opt in valid_opts)), file=sys.stderr) sys.exit(code) try: opts, args = getopt.getopt(sys.argv[1:], '', valid_opts) except getopt.error: exit_with_usage() if not opts: exit_with_usage() pyver = sysconfig.get_config_var('VERSION') getvar = sysconfig.get_config_var opt_flags = [flag for (flag, val) in opts] if '--help' in opt_flags: exit_with_usage(code=0) for opt in opt_flags: if opt == '--prefix': print(sysconfig.get_config_var('prefix')) elif opt == '--exec-prefix': print(sysconfig.get_config_var('exec_prefix')) elif opt in ('--includes', '--cflags'): flags = ['-I' + sysconfig.get_path('include'), '-I' + sysconfig.get_path('platinclude')] if opt == '--cflags': flags.extend(getvar('CFLAGS').split()) print(' '.join(flags)) elif opt in ('--libs', '--ldflags'): libs = ['-lpython' + pyver + sys.abiflags] libs += getvar('LIBS').split() libs += getvar('SYSLIBS').split() # add the prefix/lib/pythonX.Y/config dir, but only if there is no # shared library in prefix/lib/. if opt == '--ldflags': if not getvar('Py_ENABLE_SHARED'): libs.insert(0, '-L' + getvar('LIBPL')) if not getvar('PYTHONFRAMEWORK'): libs.extend(getvar('LINKFORSHARED').split()) print(' '.join(libs)) elif opt == '--extension-suffix': print(sysconfig.get_config_var('EXT_SUFFIX')) elif opt == '--abiflags': print(sys.abiflags) elif opt == '--configdir': print(sysconfig.get_config_var('LIBPL'))

[ "[email protected]" ]

[email protected]

0820492c6f8f84c03d5ea67148735a46b346b5c4

27e890f900bd4bfb2e66f4eab85bc381cf4d5d3f

/tests/unit/plugins/lookup/test_manifold.py

44050cf36af553019eb84f6a882211c510bf094f

[]

no_license

coll-test/notstdlib.moveitallout

eb33a560070bbded5032385d0aea2f3cf60e690b

0987f099b783c6cf977db9233e1c3d9efcbcb3c7

refs/heads/master

2020-12-19T22:28:33.369557

2020-01-23T18:51:26

235,865,139

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# (c) 2018, Arigato Machine Inc. # (c) 2018, Ansible Project # GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt) from __future__ import (absolute_import, division, print_function) __metaclass__ = type from ansible_collections.notstdlib.moveitallout.tests.unit.compat import unittest from ansible_collections.notstdlib.moveitallout.tests.unit.compat.mock import patch, call from ansible.errors import AnsibleError from ansible_collections.notstdlib.moveitallout.plugins.module_utils.urls import ConnectionError, SSLValidationError from ansible.module_utils.six.moves.urllib.error import HTTPError, URLError from ansible.module_utils import six from ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold import ManifoldApiClient, LookupModule, ApiError import json API_FIXTURES = { 'https://api.marketplace.manifold.co/v1/resources': [ { "body": { "label": "resource-1", "name": "Resource 1" }, "id": "rid-1" }, { "body": { "label": "resource-2", "name": "Resource 2" }, "id": "rid-2" } ], 'https://api.marketplace.manifold.co/v1/resources?label=resource-1': [ { "body": { "label": "resource-1", "name": "Resource 1" }, "id": "rid-1" } ], 'https://api.marketplace.manifold.co/v1/resources?label=resource-2': [ { "body": { "label": "resource-2", "name": "Resource 2" }, "id": "rid-2" } ], 'https://api.marketplace.manifold.co/v1/resources?team_id=tid-1': [ { "body": { "label": "resource-1", "name": "Resource 1" }, "id": "rid-1" } ], 'https://api.marketplace.manifold.co/v1/resources?project_id=pid-1': [ { "body": { "label": "resource-2", "name": "Resource 2" }, "id": "rid-2" } ], 'https://api.marketplace.manifold.co/v1/resources?project_id=pid-2': [ { "body": { "label": "resource-1", "name": "Resource 1" }, "id": "rid-1" }, { "body": { "label": "resource-3", "name": "Resource 3" }, "id": "rid-3" } ], 'https://api.marketplace.manifold.co/v1/resources?team_id=tid-1&project_id=pid-1': [ { "body": { "label": "resource-1", "name": "Resource 1" }, "id": "rid-1" } ], 'https://api.marketplace.manifold.co/v1/projects': [ { "body": { "label": "project-1", "name": "Project 1", }, "id": "pid-1", }, { "body": { "label": "project-2", "name": "Project 2", }, "id": "pid-2", } ], 'https://api.marketplace.manifold.co/v1/projects?label=project-2': [ { "body": { "label": "project-2", "name": "Project 2", }, "id": "pid-2", } ], 'https://api.marketplace.manifold.co/v1/credentials?resource_id=rid-1': [ { "body": { "resource_id": "rid-1", "values": { "RESOURCE_TOKEN_1": "token-1", "RESOURCE_TOKEN_2": "token-2" } }, "id": "cid-1", } ], 'https://api.marketplace.manifold.co/v1/credentials?resource_id=rid-2': [ { "body": { "resource_id": "rid-2", "values": { "RESOURCE_TOKEN_3": "token-3", "RESOURCE_TOKEN_4": "token-4" } }, "id": "cid-2", } ], 'https://api.marketplace.manifold.co/v1/credentials?resource_id=rid-3': [ { "body": { "resource_id": "rid-3", "values": { "RESOURCE_TOKEN_1": "token-5", "RESOURCE_TOKEN_2": "token-6" } }, "id": "cid-3", } ], 'https://api.identity.manifold.co/v1/teams': [ { "id": "tid-1", "body": { "name": "Team 1", "label": "team-1" } }, { "id": "tid-2", "body": { "name": "Team 2", "label": "team-2" } } ] } def mock_fixture(open_url_mock, fixture=None, data=None, headers=None): if not headers: headers = {} if fixture: data = json.dumps(API_FIXTURES[fixture]) if 'content-type' not in headers: headers['content-type'] = 'application/json' open_url_mock.return_value.read.return_value = data open_url_mock.return_value.headers = headers class TestManifoldApiClient(unittest.TestCase): @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.open_url') def test_request_sends_default_headers(self, open_url_mock): mock_fixture(open_url_mock, data='hello') client = ManifoldApiClient('token-123') client.request('test', 'endpoint') open_url_mock.assert_called_with('https://api.test.manifold.co/v1/endpoint', headers={'Accept': '*/*', 'Authorization': 'Bearer token-123'}, http_agent='python-manifold-ansible-1.0.0') @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.open_url') def test_request_decodes_json(self, open_url_mock): mock_fixture(open_url_mock, fixture='https://api.marketplace.manifold.co/v1/resources') client = ManifoldApiClient('token-123') self.assertIsInstance(client.request('marketplace', 'resources'), list) @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.open_url') def test_request_streams_text(self, open_url_mock): mock_fixture(open_url_mock, data='hello', headers={'content-type': "text/plain"}) client = ManifoldApiClient('token-123') self.assertEqual('hello', client.request('test', 'endpoint')) @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.open_url') def test_request_processes_parameterized_headers(self, open_url_mock): mock_fixture(open_url_mock, data='hello') client = ManifoldApiClient('token-123') client.request('test', 'endpoint', headers={'X-HEADER': 'MANIFOLD'}) open_url_mock.assert_called_with('https://api.test.manifold.co/v1/endpoint', headers={'Accept': '*/*', 'Authorization': 'Bearer token-123', 'X-HEADER': 'MANIFOLD'}, http_agent='python-manifold-ansible-1.0.0') @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.open_url') def test_request_passes_arbitrary_parameters(self, open_url_mock): mock_fixture(open_url_mock, data='hello') client = ManifoldApiClient('token-123') client.request('test', 'endpoint', use_proxy=False, timeout=5) open_url_mock.assert_called_with('https://api.test.manifold.co/v1/endpoint', headers={'Accept': '*/*', 'Authorization': 'Bearer token-123'}, http_agent='python-manifold-ansible-1.0.0', use_proxy=False, timeout=5) @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.open_url') def test_request_raises_on_incorrect_json(self, open_url_mock): mock_fixture(open_url_mock, data='noJson', headers={'content-type': "application/json"}) client = ManifoldApiClient('token-123') with self.assertRaises(ApiError) as context: client.request('test', 'endpoint') self.assertEqual('JSON response can\'t be parsed while requesting https://api.test.manifold.co/v1/endpoint:\n' 'noJson', str(context.exception)) @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.open_url') def test_request_raises_on_status_500(self, open_url_mock): open_url_mock.side_effect = HTTPError('https://api.test.manifold.co/v1/endpoint', 500, 'Server error', {}, six.StringIO('ERROR')) client = ManifoldApiClient('token-123') with self.assertRaises(ApiError) as context: client.request('test', 'endpoint') self.assertEqual('Server returned: HTTP Error 500: Server error while requesting ' 'https://api.test.manifold.co/v1/endpoint:\nERROR', str(context.exception)) @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.open_url') def test_request_raises_on_bad_url(self, open_url_mock): open_url_mock.side_effect = URLError('URL is invalid') client = ManifoldApiClient('token-123') with self.assertRaises(ApiError) as context: client.request('test', 'endpoint') self.assertEqual('Failed lookup url for https://api.test.manifold.co/v1/endpoint : <url' 'open error URL is invalid>', str(context.exception)) @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.open_url') def test_request_raises_on_ssl_error(self, open_url_mock): open_url_mock.side_effect = SSLValidationError('SSL Error') client = ManifoldApiClient('token-123') with self.assertRaises(ApiError) as context: client.request('test', 'endpoint') self.assertEqual('Error validating the server\'s certificate for https://api.test.manifold.co/v1/endpoint: ' 'SSL Error', str(context.exception)) @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.open_url') def test_request_raises_on_connection_error(self, open_url_mock): open_url_mock.side_effect = ConnectionError('Unknown connection error') client = ManifoldApiClient('token-123') with self.assertRaises(ApiError) as context: client.request('test', 'endpoint') self.assertEqual('Error connecting to https://api.test.manifold.co/v1/endpoint: Unknown connection error', str(context.exception)) @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.open_url') def test_get_resources_get_all(self, open_url_mock): url = 'https://api.marketplace.manifold.co/v1/resources' mock_fixture(open_url_mock, fixture=url) client = ManifoldApiClient('token-123') self.assertListEqual(API_FIXTURES[url], client.get_resources()) open_url_mock.assert_called_with(url, headers={'Accept': '*/*', 'Authorization': 'Bearer token-123'}, http_agent='python-manifold-ansible-1.0.0') @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.open_url') def test_get_resources_filter_label(self, open_url_mock): url = 'https://api.marketplace.manifold.co/v1/resources?label=resource-1' mock_fixture(open_url_mock, fixture=url) client = ManifoldApiClient('token-123') self.assertListEqual(API_FIXTURES[url], client.get_resources(label='resource-1')) open_url_mock.assert_called_with(url, headers={'Accept': '*/*', 'Authorization': 'Bearer token-123'}, http_agent='python-manifold-ansible-1.0.0') @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.open_url') def test_get_resources_filter_team_and_project(self, open_url_mock): url = 'https://api.marketplace.manifold.co/v1/resources?team_id=tid-1&project_id=pid-1' mock_fixture(open_url_mock, fixture=url) client = ManifoldApiClient('token-123') self.assertListEqual(API_FIXTURES[url], client.get_resources(team_id='tid-1', project_id='pid-1')) args, kwargs = open_url_mock.call_args url_called = args[0] # Dict order is not guaranteed, so an url may have querystring parameters order randomized self.assertIn('team_id=tid-1', url_called) self.assertIn('project_id=pid-1', url_called) @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.open_url') def test_get_teams_get_all(self, open_url_mock): url = 'https://api.identity.manifold.co/v1/teams' mock_fixture(open_url_mock, fixture=url) client = ManifoldApiClient('token-123') self.assertListEqual(API_FIXTURES[url], client.get_teams()) open_url_mock.assert_called_with(url, headers={'Accept': '*/*', 'Authorization': 'Bearer token-123'}, http_agent='python-manifold-ansible-1.0.0') @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.open_url') def test_get_teams_filter_label(self, open_url_mock): url = 'https://api.identity.manifold.co/v1/teams' mock_fixture(open_url_mock, fixture=url) client = ManifoldApiClient('token-123') self.assertListEqual(API_FIXTURES[url][1:2], client.get_teams(label='team-2')) open_url_mock.assert_called_with(url, headers={'Accept': '*/*', 'Authorization': 'Bearer token-123'}, http_agent='python-manifold-ansible-1.0.0') @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.open_url') def test_get_projects_get_all(self, open_url_mock): url = 'https://api.marketplace.manifold.co/v1/projects' mock_fixture(open_url_mock, fixture=url) client = ManifoldApiClient('token-123') self.assertListEqual(API_FIXTURES[url], client.get_projects()) open_url_mock.assert_called_with(url, headers={'Accept': '*/*', 'Authorization': 'Bearer token-123'}, http_agent='python-manifold-ansible-1.0.0') @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.open_url') def test_get_projects_filter_label(self, open_url_mock): url = 'https://api.marketplace.manifold.co/v1/projects?label=project-2' mock_fixture(open_url_mock, fixture=url) client = ManifoldApiClient('token-123') self.assertListEqual(API_FIXTURES[url], client.get_projects(label='project-2')) open_url_mock.assert_called_with(url, headers={'Accept': '*/*', 'Authorization': 'Bearer token-123'}, http_agent='python-manifold-ansible-1.0.0') @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.open_url') def test_get_credentials(self, open_url_mock): url = 'https://api.marketplace.manifold.co/v1/credentials?resource_id=rid-1' mock_fixture(open_url_mock, fixture=url) client = ManifoldApiClient('token-123') self.assertListEqual(API_FIXTURES[url], client.get_credentials(resource_id='rid-1')) open_url_mock.assert_called_with(url, headers={'Accept': '*/*', 'Authorization': 'Bearer token-123'}, http_agent='python-manifold-ansible-1.0.0') class TestLookupModule(unittest.TestCase): def setUp(self): self.lookup = LookupModule() self.lookup._load_name = "manifold" @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.ManifoldApiClient') def test_get_all(self, client_mock): expected_result = [{'RESOURCE_TOKEN_1': 'token-1', 'RESOURCE_TOKEN_2': 'token-2', 'RESOURCE_TOKEN_3': 'token-3', 'RESOURCE_TOKEN_4': 'token-4' }] client_mock.return_value.get_resources.return_value = API_FIXTURES['https://api.marketplace.manifold.co/v1/resources'] client_mock.return_value.get_credentials.side_effect = lambda x: API_FIXTURES['https://api.marketplace.manifold.co/v1/' 'credentials?resource_id={0}'.format(x)] self.assertListEqual(expected_result, self.lookup.run([], api_token='token-123')) client_mock.assert_called_with('token-123') client_mock.return_value.get_resources.assert_called_with(team_id=None, project_id=None) @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.ManifoldApiClient') def test_get_one_resource(self, client_mock): expected_result = [{'RESOURCE_TOKEN_3': 'token-3', 'RESOURCE_TOKEN_4': 'token-4' }] client_mock.return_value.get_resources.return_value = API_FIXTURES['https://api.marketplace.manifold.co/v1/resources?label=resource-2'] client_mock.return_value.get_credentials.side_effect = lambda x: API_FIXTURES['https://api.marketplace.manifold.co/v1/' 'credentials?resource_id={0}'.format(x)] self.assertListEqual(expected_result, self.lookup.run(['resource-2'], api_token='token-123')) client_mock.return_value.get_resources.assert_called_with(team_id=None, project_id=None, label='resource-2') @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.ManifoldApiClient') def test_get_two_resources(self, client_mock): expected_result = [{'RESOURCE_TOKEN_1': 'token-1', 'RESOURCE_TOKEN_2': 'token-2', 'RESOURCE_TOKEN_3': 'token-3', 'RESOURCE_TOKEN_4': 'token-4' }] client_mock.return_value.get_resources.return_value = API_FIXTURES['https://api.marketplace.manifold.co/v1/resources'] client_mock.return_value.get_credentials.side_effect = lambda x: API_FIXTURES['https://api.marketplace.manifold.co/v1/' 'credentials?resource_id={0}'.format(x)] self.assertListEqual(expected_result, self.lookup.run(['resource-1', 'resource-2'], api_token='token-123')) client_mock.assert_called_with('token-123') client_mock.return_value.get_resources.assert_called_with(team_id=None, project_id=None) @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.display') @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.ManifoldApiClient') def test_get_resources_with_same_credential_names(self, client_mock, display_mock): expected_result = [{'RESOURCE_TOKEN_1': 'token-5', 'RESOURCE_TOKEN_2': 'token-6' }] client_mock.return_value.get_resources.return_value = API_FIXTURES['https://api.marketplace.manifold.co/v1/resources?project_id=pid-2'] client_mock.return_value.get_projects.return_value = API_FIXTURES['https://api.marketplace.manifold.co/v1/projects?label=project-2'] client_mock.return_value.get_credentials.side_effect = lambda x: API_FIXTURES['https://api.marketplace.manifold.co/v1/' 'credentials?resource_id={0}'.format(x)] self.assertListEqual(expected_result, self.lookup.run([], api_token='token-123', project='project-2')) client_mock.assert_called_with('token-123') display_mock.warning.assert_has_calls([ call("'RESOURCE_TOKEN_1' with label 'resource-1' was replaced by resource data with label 'resource-3'"), call("'RESOURCE_TOKEN_2' with label 'resource-1' was replaced by resource data with label 'resource-3'")], any_order=True ) client_mock.return_value.get_resources.assert_called_with(team_id=None, project_id='pid-2') @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.ManifoldApiClient') def test_filter_by_team(self, client_mock): expected_result = [{'RESOURCE_TOKEN_1': 'token-1', 'RESOURCE_TOKEN_2': 'token-2' }] client_mock.return_value.get_resources.return_value = API_FIXTURES['https://api.marketplace.manifold.co/v1/resources?team_id=tid-1'] client_mock.return_value.get_teams.return_value = API_FIXTURES['https://api.identity.manifold.co/v1/teams'][0:1] client_mock.return_value.get_credentials.side_effect = lambda x: API_FIXTURES['https://api.marketplace.manifold.co/v1/' 'credentials?resource_id={0}'.format(x)] self.assertListEqual(expected_result, self.lookup.run([], api_token='token-123', team='team-1')) client_mock.assert_called_with('token-123') client_mock.return_value.get_resources.assert_called_with(team_id='tid-1', project_id=None) @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.ManifoldApiClient') def test_filter_by_project(self, client_mock): expected_result = [{'RESOURCE_TOKEN_3': 'token-3', 'RESOURCE_TOKEN_4': 'token-4' }] client_mock.return_value.get_resources.return_value = API_FIXTURES['https://api.marketplace.manifold.co/v1/resources?project_id=pid-1'] client_mock.return_value.get_projects.return_value = API_FIXTURES['https://api.marketplace.manifold.co/v1/projects'][0:1] client_mock.return_value.get_credentials.side_effect = lambda x: API_FIXTURES['https://api.marketplace.manifold.co/v1/' 'credentials?resource_id={0}'.format(x)] self.assertListEqual(expected_result, self.lookup.run([], api_token='token-123', project='project-1')) client_mock.assert_called_with('token-123') client_mock.return_value.get_resources.assert_called_with(team_id=None, project_id='pid-1') @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.ManifoldApiClient') def test_filter_by_team_and_project(self, client_mock): expected_result = [{'RESOURCE_TOKEN_1': 'token-1', 'RESOURCE_TOKEN_2': 'token-2' }] client_mock.return_value.get_resources.return_value = API_FIXTURES['https://api.marketplace.manifold.co/v1/resources?team_id=tid-1&project_id=pid-1'] client_mock.return_value.get_teams.return_value = API_FIXTURES['https://api.identity.manifold.co/v1/teams'][0:1] client_mock.return_value.get_projects.return_value = API_FIXTURES['https://api.marketplace.manifold.co/v1/projects'][0:1] client_mock.return_value.get_credentials.side_effect = lambda x: API_FIXTURES['https://api.marketplace.manifold.co/v1/' 'credentials?resource_id={0}'.format(x)] self.assertListEqual(expected_result, self.lookup.run([], api_token='token-123', project='project-1')) client_mock.assert_called_with('token-123') client_mock.return_value.get_resources.assert_called_with(team_id=None, project_id='pid-1') @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.ManifoldApiClient') def test_raise_team_doesnt_exist(self, client_mock): client_mock.return_value.get_teams.return_value = [] with self.assertRaises(AnsibleError) as context: self.lookup.run([], api_token='token-123', team='no-team') self.assertEqual("Team 'no-team' does not exist", str(context.exception)) @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.ManifoldApiClient') def test_raise_project_doesnt_exist(self, client_mock): client_mock.return_value.get_projects.return_value = [] with self.assertRaises(AnsibleError) as context: self.lookup.run([], api_token='token-123', project='no-project') self.assertEqual("Project 'no-project' does not exist", str(context.exception)) @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.ManifoldApiClient') def test_raise_resource_doesnt_exist(self, client_mock): client_mock.return_value.get_resources.return_value = API_FIXTURES['https://api.marketplace.manifold.co/v1/resources'] with self.assertRaises(AnsibleError) as context: self.lookup.run(['resource-1', 'no-resource-1', 'no-resource-2'], api_token='token-123') self.assertEqual("Resource(s) no-resource-1, no-resource-2 do not exist", str(context.exception)) @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.ManifoldApiClient') def test_catch_api_error(self, client_mock): client_mock.side_effect = ApiError('Generic error') with self.assertRaises(AnsibleError) as context: self.lookup.run([], api_token='token-123') self.assertEqual("API Error: Generic error", str(context.exception)) @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.ManifoldApiClient') def test_catch_unhandled_exception(self, client_mock): client_mock.side_effect = Exception('Unknown error') with self.assertRaises(AnsibleError) as context: self.lookup.run([], api_token='token-123') self.assertTrue('Exception: Unknown error' in str(context.exception)) @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.os.getenv') @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.ManifoldApiClient') def test_falls_back_to_env_var(self, client_mock, getenv_mock): getenv_mock.return_value = 'token-321' client_mock.return_value.get_resources.return_value = [] client_mock.return_value.get_credentials.return_value = [] self.lookup.run([]) getenv_mock.assert_called_with('MANIFOLD_API_TOKEN') client_mock.assert_called_with('token-321') @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.os.getenv') @patch('ansible_collections.notstdlib.moveitallout.plugins.lookup.manifold.ManifoldApiClient') def test_falls_raises_on_no_token(self, client_mock, getenv_mock): getenv_mock.return_value = None client_mock.return_value.get_resources.return_value = [] client_mock.return_value.get_credentials.return_value = [] with self.assertRaises(AnsibleError) as context: self.lookup.run([]) self.assertEqual('API token is required. Please set api_token parameter or MANIFOLD_API_TOKEN env var', str(context.exception))

[ "[email protected]" ]

[email protected]

63cff8ecff4e85addb997ed55491b924444e50ac

e1c7c25c22c2f854aa8e3d8f6fffdf80a0b4dfbf

/CodeChef/CodeChef_Contests/Distribute_Candies.py

b7374b54f77afa5e0246f35539e5cff21c1a8d76

[]

no_license

roshan13ghimire/Competitive_Programming

efc85f9fe6fa46edff96931ca3a1cca78628918b

0c238a391c6acee8763968ef298b765c133b7111

refs/heads/master

2023-04-15T16:35:07.711491

2021-04-12T03:00:05

273,682,360

4

1

null

2020-08-05T02:11:53

2020-06-20T09:59:57

Python

UTF-8

Python

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344

py

#Distribute_Candies for _ in range(int(input())): n = int(input()) a=list(map(int,input().split())) if(len(a)==0): print(a[0]) elif(len(a)==1): print(min(a)) else: a.sort(reverse=True) s=0 for i in range(2,len(a),3): s +=a [i] print(s)

[ "[email protected]" ]

[email protected]

ab718c6751938719fe2a3fad3cb11077d9a8ee9a

82b946da326148a3c1c1f687f96c0da165bb2c15

/sdk/python/pulumi_azure_native/sql/v20201101preview/get_job_credential.py

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# coding=utf-8 # *** WARNING: this file was generated by the Pulumi SDK Generator. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union, overload from ... import _utilities __all__ = [ 'GetJobCredentialResult', 'AwaitableGetJobCredentialResult', 'get_job_credential', ] @pulumi.output_type class GetJobCredentialResult: """ A stored credential that can be used by a job to connect to target databases. """ def __init__(__self__, id=None, name=None, type=None, username=None): if id and not isinstance(id, str): raise TypeError("Expected argument 'id' to be a str") pulumi.set(__self__, "id", id) if name and not isinstance(name, str): raise TypeError("Expected argument 'name' to be a str") pulumi.set(__self__, "name", name) if type and not isinstance(type, str): raise TypeError("Expected argument 'type' to be a str") pulumi.set(__self__, "type", type) if username and not isinstance(username, str): raise TypeError("Expected argument 'username' to be a str") pulumi.set(__self__, "username", username) @property @pulumi.getter def id(self) -> str: """ Resource ID. """ return pulumi.get(self, "id") @property @pulumi.getter def name(self) -> str: """ Resource name. """ return pulumi.get(self, "name") @property @pulumi.getter def type(self) -> str: """ Resource type. """ return pulumi.get(self, "type") @property @pulumi.getter def username(self) -> str: """ The credential user name. """ return pulumi.get(self, "username") class AwaitableGetJobCredentialResult(GetJobCredentialResult): # pylint: disable=using-constant-test def __await__(self): if False: yield self return GetJobCredentialResult( id=self.id, name=self.name, type=self.type, username=self.username) def get_job_credential(credential_name: Optional[str] = None, job_agent_name: Optional[str] = None, resource_group_name: Optional[str] = None, server_name: Optional[str] = None, opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetJobCredentialResult: """ A stored credential that can be used by a job to connect to target databases. :param str credential_name: The name of the credential. :param str job_agent_name: The name of the job agent. :param str resource_group_name: The name of the resource group that contains the resource. You can obtain this value from the Azure Resource Manager API or the portal. :param str server_name: The name of the server. """ __args__ = dict() __args__['credentialName'] = credential_name __args__['jobAgentName'] = job_agent_name __args__['resourceGroupName'] = resource_group_name __args__['serverName'] = server_name if opts is None: opts = pulumi.InvokeOptions() if opts.version is None: opts.version = _utilities.get_version() __ret__ = pulumi.runtime.invoke('azure-native:sql/v20201101preview:getJobCredential', __args__, opts=opts, typ=GetJobCredentialResult).value return AwaitableGetJobCredentialResult( id=__ret__.id, name=__ret__.name, type=__ret__.type, username=__ret__.username)

[ "[email protected]" ]

[email protected]

5dc5dcbbd705e58f27c0631355130a07689f6f51

acb8e84e3b9c987fcab341f799f41d5a5ec4d587

/langs/5/lsm.py

5556fc62a4f5c02583d9d14afdb961e9c782ce7d

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G4te-Keep3r/HowdyHackers

46bfad63eafe5ac515da363e1c75fa6f4b9bca32

fb6d391aaecb60ab5c4650d4ae2ddd599fd85db2

refs/heads/master

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2016-11-13T20:45:50

73,624,224

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486

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import sys def printFunction(lineRemaining): if lineRemaining[0] == '"' and lineRemaining[-1] == '"': if len(lineRemaining) > 2: #data to print lineRemaining = lineRemaining[1:-1] print ' '.join(lineRemaining) else: print def main(fileName): with open(fileName) as f: for line in f: data = line.split() if data[0] == 'lSM': printFunction(data[1:]) else: print 'ERROR' return if __name__ == '__main__': main(sys.argv[1])

[ "[email protected]" ]

[email protected]

bfbdd12c0144be46d6a9f9cd9681526f91cb2302

b24e993bfae0e530b7c6ee676b0efa1b2cbea33c

/rsopt/run.py

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permissive

tanxicccc/rsopt

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8705e937f95a4bbe6ed3fb1a04b78f724a5f3931

refs/heads/master

2023-01-06T19:21:40.065806

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Apache-2.0

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# Functions to run a call from originating from pkcli # This is just a temporary setup. libEnsembleOptimizer shouldn't actually be tied to execution mode # It is instantiated because nlopt was requested # THe executor will be setup separately based off 'execution_type' in YAML and registered with libEnsembleOptimizer from rsopt.libe_tools.optimizer import libEnsembleOptimizer def serial(config): opt = libEnsembleOptimizer() opt.load_configuration(config) return opt #.run() # These names have to line up with accepted values for setup.execution_type # Another place where shared names are imported from common source run_modes = { 'serial': serial }

[ "[email protected]" ]

[email protected]

d5e3cb808796ca54150f2786b23de7ecf5ca0361

5f57cfb662e7a490235255273114d2eb712a9ce4

/djd-prog2/manha-aula2/operadores2.py

8f487d67a5131274c9bbe4910aa05cb36e8f139f

[]

no_license

antoniorcn/fatec-2020-2s

762e14acfbf0cb42a2e478662e6cf0001794f72c

4d90cc35d354382ad38c20ce2e32924216d7d747

refs/heads/master

2023-01-27T22:52:29.529360

2020-12-05T13:51:30

289,972,977

9

7

null

UTF-8

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153

py

temperatura = 14 frio = temperatura < 15 horas_acordado = 18 sono = horas_acordado > 16 ficar_casa = sono and frio print("Ficar em casa: ", ficar_casa)

[ "[email protected]" ]

[email protected]

b9b986b188c838e28b4a55d6dad2d567a40a0153

616c7325ee8c4a7d37467a8ad760d00891d3b450

/get_linkedin.py

41f290be48e6b44cc8360af16080bdcde11e899f

[]

no_license

vintasoftware/networking.cool

c8f7b3d027b098966ea4c47a211a465eaf746661

314d3b32ab3d611fe2b622d57372dc29fb5eac5e

refs/heads/master

2023-06-19T19:38:03.557182

2015-11-15T19:05:08

64,401,363

0

null

UTF-8

Python

false

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# coding: utf-8 from selenium.webdriver import Chrome from selenium.common.exceptions import WebDriverException import requests from retrying import retry import json import time import pprint import traceback def wait_for(fn, timeout=5): start_time = time.time() while time.time() - start_time < timeout: try: return fn() except WebDriverException: time.sleep(0.1) # one more try, which will raise any errors if they are outstanding return fn() def find_by_css(selector): def _find(): return driver.find_element_by_css_selector(selector) return wait_for(_find) def find_linkedin_url(term): params = { 'key': 'AIzaSyBs_qRMdd3UxIp6HQ9zMidKupXkRCtmZrQ', 'cx': '007098471526848933106:c_yqy7e87hi', 'q': term } r = requests.get( 'https://www.googleapis.com/customsearch/v1', params=params) r_json = r.json() for item in r_json['items']: if 'pagemap' in item and 'person' in item['pagemap']: return item['link'] @retry(stop_max_delay=6000) def get_contact_linkedin_html(name, company): term = u"{} {}".format(name, company) url = find_linkedin_url(term) if not url: raise ValueError(u"No result for {}".format(term)) driver.get(url) return find_by_css('#profile').get_attribute('innerHTML'), url driver = Chrome() driver.set_window_size(1280, 700) results = [] def main(): with open('attendees.json') as f: attendees_raw = json.load(f) attendees = [(a['name'], a['info2']) for a in attendees_raw if 'info2' in a] for name, company in attendees: try: html, link = get_contact_linkedin_html(name, company) except Exception: print traceback.print_exc() html = None link = None results.append({ 'name': name, 'company': company, 'html': html, 'link': link }) print len(results) with open('results.json', 'w+') as out: json.dump(results, out, indent=2) driver.quit() if __name__ == '__main__': start_time = time.time() main() print("--- ran in %s seconds ---" % (time.time() - start_time))

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[email protected]

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from base import BaseHandler class CommentsHandler(BaseHandler): def get(self): pass

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# qubit number=4 # total number=11 import pyquil from pyquil.api import local_forest_runtime, QVMConnection from pyquil import Program, get_qc from pyquil.gates import * import numpy as np conn = QVMConnection() def make_circuit()-> Program: prog = Program() # circuit begin prog += H(0) # number=1 prog += H(1) # number=2 prog += H(2) # number=3 prog += X(1) # number=8 prog += H(3) # number=4 prog += Y(3) # number=5 prog += X(3) # number=7 prog += CNOT(3,0) # number=9 prog += CNOT(3,0) # number=10 # circuit end return prog def summrise_results(bitstrings) -> dict: d = {} for l in bitstrings: if d.get(l) is None: d[l] = 1 else: d[l] = d[l] + 1 return d if __name__ == '__main__': prog = make_circuit() qvm = get_qc('4q-qvm') results = qvm.run_and_measure(prog,1024) bitstrings = np.vstack([results[i] for i in qvm.qubits()]).T bitstrings = [''.join(map(str, l)) for l in bitstrings] writefile = open("../data/startPyquil415.csv","w") print(summrise_results(bitstrings),file=writefile) writefile.close()

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[email protected]

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# Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not use this file except in compliance # with the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. # coding: utf-8 # pylint: disable=wildcard-import, unused-wildcard-import """Linear Algebra Symbol API of MXNet.""" try: from .gen_linalg import * except ImportError: pass __all__ = []

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lievech/car_simulation_ws

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[email protected]

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Ch4osMy7h/VL-T5

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import collections import os import random from pathlib import Path import logging import shutil from packaging import version from tqdm import tqdm import numpy as np import torch import torch.nn as nn from torch.nn.parallel import DistributedDataParallel as DDP import torch.distributed as dist import torch.backends.cudnn as cudnn from param import parse_args from pretrain_data import get_loader from utils import LossMeter from dist_utils import reduce_dict import wandb _use_native_amp = False _use_apex = False # Check if Pytorch version >= 1.6 to switch between Native AMP and Apex if version.parse(torch.__version__) < version.parse("1.6"): from transormers.file_utils import is_apex_available if is_apex_available(): from apex import amp _use_apex = True else: _use_native_amp = True from torch.cuda.amp import autocast from trainer_base import TrainerBase class Trainer(TrainerBase): def __init__(self, args, train_loader=None, val_loader=None, test_loader=None, train=True): super().__init__( args, train_loader=train_loader, val_loader=val_loader, test_loader=test_loader, train=train) from pretrain_model import VLT5Pretraining, VLBartPretraining model_kwargs = {} if 't5' in args.backbone: model_class = VLT5Pretraining elif 'bart' in args.backbone: model_class = VLBartPretraining config = self.create_config() self.tokenizer = self.create_tokenizer() if 'bart' in self.args.tokenizer: num_added_toks = 0 if config.use_vis_order_embedding: additional_special_tokens = [f'<extra_id_{i}>' for i in range(100-1, -1, -1)] + \ [f'<vis_extra_id_{i}>' for i in range(100-1, -1, -1)] special_tokens_dict = {'additional_special_tokens': additional_special_tokens} num_added_toks = self.tokenizer.add_special_tokens(special_tokens_dict) config.default_obj_order_ids = self.tokenizer.convert_tokens_to_ids([f'<vis_extra_id_{i}>' for i in range(100)]) self.model = self.create_model(model_class, config, **model_kwargs) if 't5' in self.args.tokenizer: self.model.resize_token_embeddings(self.tokenizer.vocab_size) elif 'bart' in self.args.tokenizer: self.model.resize_token_embeddings(self.model.model.shared.num_embeddings + num_added_toks) self.model.tokenizer = self.tokenizer # Load Checkpoint self.start_epoch = None if args.load is not None: ckpt_path = args.load + '.pth' self.load_checkpoint(ckpt_path) self.start_epoch = int(args.load.split('Epoch')[-1]) if self.args.from_scratch: self.init_weights() # GPU Options print(f'Model Launching at GPU {self.args.gpu}') if self.verbose: from time import time start = time() self.model = self.model.to(args.gpu) # Optimizer if train: self.optim, self.lr_scheduler = self.create_optimizer_and_scheduler() if self.args.fp16 and _use_native_amp: self.scaler = torch.cuda.amp.GradScaler() elif _use_apex: self.model, self.optim = amp.initialize( self.model, self.optim, opt_level='O1', verbosity=self.verbose) if args.multiGPU: if args.distributed: self.model = DDP(self.model, device_ids=[args.gpu], find_unused_parameters=True ) if self.verbose: print(f'It took {time() - start:.1f}s') def train(self): LOSSES_NAME = self.args.LOSSES_NAME if self.args.dry: results = self.evaluate_epoch(epoch=0) if self.verbose: loss_meters = [LossMeter() for _ in range(len(LOSSES_NAME))] best_eval_loss = 9595. if 't5' in self.args.backbone: project_name = "VLT5_Pretrain" elif 'bart' in self.args.backbone: project_name = "VLBart_Pretrain" wandb.init(project=project_name) wandb.run.name = self.args.run_name wandb.config.update(self.args) wandb.watch(self.model) src_dir = Path(__file__).resolve().parent base_path = str(src_dir.parent) src_dir = str(src_dir) wandb.save(os.path.join(src_dir + "/*.py"), base_path=base_path) if self.args.distributed: dist.barrier() global_step = 0 for epoch in range(self.args.epochs): if self.start_epoch is not None: epoch += self.start_epoch if self.args.distributed: self.train_loader.sampler.set_epoch(epoch) # Train self.model.train() if self.verbose: pbar = tqdm(total=len(self.train_loader), ncols=250) epoch_results = {} for loss_name in LOSSES_NAME: epoch_results[loss_name] = 0. epoch_results[f'{loss_name}_count'] = 0 for step_i, batch in enumerate(self.train_loader): if self.args.fp16 and _use_native_amp: with autocast(): if self.args.distributed: results = self.model.module.train_step(batch) else: results = self.model.train_step(batch) else: if self.args.distributed: results = self.model.module.train_step(batch) else: results = self.model.train_step(batch) loss = results['loss'] if self.args.fp16 and _use_native_amp: self.scaler.scale(loss).backward() elif self.args.fp16 and _use_apex: with amp.scale_loss(loss, self.optim) as scaled_loss: scaled_loss.backward() else: loss.backward() loss = loss.detach() # Update Parameters if self.args.clip_grad_norm > 0: if self.args.fp16 and _use_native_amp: self.scaler.unscale_(self.optim) torch.nn.utils.clip_grad_norm_(self.model.parameters(), self.args.clip_grad_norm) elif self.args.fp16 and _use_apex: torch.nn.utils.clip_grad_norm_(amp.master_params(self.optim), self.args.clip_grad_norm) else: torch.nn.utils.clip_grad_norm_(self.model.parameters(), self.args.clip_grad_norm) if self.args.fp16 and _use_native_amp: self.scaler.step(self.optim) self.scaler.update() else: self.optim.step() if self.lr_scheduler: self.lr_scheduler.step() # self.model.zero_grad() for param in self.model.parameters(): param.grad = None global_step += 1 if self.lr_scheduler: if version.parse(torch.__version__) >= version.parse("1.4"): lr = self.lr_scheduler.get_last_lr()[0] else: lr = self.lr_scheduler.get_lr()[0] else: try: lr = self.optim.get_lr()[0] except AttributeError: lr = self.args.lr for k, v in results.items(): if k in epoch_results: if isinstance(v, int): epoch_results[k] += v elif isinstance(v, torch.Tensor): epoch_results[k] += v.item() if self.verbose: desc_str = f'Epoch {epoch} | LR {lr:.6f} |' for i, (loss_name, loss_meter) in enumerate(zip(LOSSES_NAME, loss_meters)): if loss_name in results: loss_meter.update(results[f'{loss_name}'] / results[f'{loss_name}_count']) if len(loss_meter) > 0: loss_count = epoch_results[f'{loss_name}_count'] desc_str += f' {loss_name} ({loss_count}) {loss_meter.val:.3f}' pbar.set_description(desc_str) pbar.update(1) if self.verbose: pbar.close() dist.barrier() results = reduce_dict(epoch_results, average=False) if self.verbose: train_loss = results['total_loss'] train_loss_count = results['total_loss_count'] avg_train_loss = train_loss / train_loss_count losses_str = f"Train Loss: {avg_train_loss:.3f}\n" for name, loss in results.items(): if name[-4:] == 'loss': loss_count = int(results[name+'_count']) if loss_count > 0: avg_loss = loss/loss_count losses_str += f"{name} ({loss_count}): {avg_loss:.3f} " wandb.log({f'Train Loss/{name}': avg_loss}, step=epoch) losses_str += '\n' print(losses_str) dist.barrier() # Validation valid_results, valid_uid2ans = self.evaluate_epoch(epoch=epoch) valid_results = reduce_dict(valid_results, average=False) if self.verbose: valid_loss = valid_results['total_loss'] valid_loss_count = valid_results['total_loss_count'] avg_valid_loss = valid_loss / valid_loss_count losses_str = f"Valid Loss: {avg_valid_loss:.3f}\n" for name, loss in valid_results.items(): if name[-4:] == 'loss': loss_count = int(valid_results[name+'_count']) if loss_count > 0: avg_loss = loss / loss_count losses_str += f"{name} ({loss_count}): {avg_loss:.3f} " wandb.log({f'Valid Loss/{name}': avg_loss}, step=epoch) losses_str += '\n' print(losses_str) if 'qa' in self.args.losses: dset2score, dset2cnt, score, cnt = self.val_loader.dataset.evaluator.evaluate(valid_uid2ans) if len(dset2score) == 0: dset2score = {'vqa': 0, 'gqa': 0, 'visual7w': 0} dset2cnt = {'vqa': 1, 'gqa': 1, 'visual7w': 1} cnt = 3 score = 0 dset2score = reduce_dict(dset2score, average=False) dset2cnt = reduce_dict(dset2cnt, average=False) score_cnt_dict = reduce_dict({'score': score, 'cnt': cnt}, average=False) if self.args.gpu == 0: score = score_cnt_dict['score'] cnt = score_cnt_dict['cnt'] accu = score / cnt dset2accu = {} for dset in dset2cnt: dset2accu[dset] = dset2score[dset] / dset2cnt[dset] accu_str = "Overall QA Acc %0.4f" % (accu) wandb.log({f'Valid QA Acc/Overall': accu}, step=epoch) sorted_keys = sorted(dset2accu.keys()) for key in sorted_keys: accu_str += ", %s Acc %0.4f" % (key, dset2accu[key]) wandb.log({f'Valid QA Acc/{key}': dset2accu[key]}, step=epoch) print(accu_str) accu_str += '\n\n' dist.barrier() if self.verbose: # Save if avg_valid_loss < best_eval_loss: best_eval_loss = avg_valid_loss # self.save("BEST_EVAL_LOSS") self.save("Epoch%02d" % (epoch + 1)) dist.barrier() if self.verbose: wandb.log({'finished': True}) def evaluate_epoch(self, epoch): LOSSES_NAME = self.args.LOSSES_NAME epoch_results = {} for loss_name in LOSSES_NAME: epoch_results[loss_name] = 0. epoch_results[f'{loss_name}_count'] = 0 uid2ans = {} self.model.eval() with torch.no_grad(): if self.verbose: loss_meter = LossMeter() loss_meters = [LossMeter() for _ in range(len(LOSSES_NAME))] pbar = tqdm(total=len(self.val_loader), ncols=250) for step_i, batch in enumerate(self.val_loader): if self.args.distributed: results = self.model.module.valid_step(batch) else: results = self.model.valid_step(batch) if 'qa' in self.args.losses: qa_pred = results['qa_pred'] for uid, ans in zip(batch['uid'], qa_pred): uid2ans[uid] = ans for k, v in results.items(): if k in epoch_results: if isinstance(v, int): epoch_results[k] += v elif isinstance(v, torch.Tensor): epoch_results[k] += v.item() if self.verbose: desc_str = f'Valid Epoch {epoch} |' for i, (loss_name, loss_meter) in enumerate(zip(LOSSES_NAME, loss_meters)): if loss_name in results: loss_meter.update(results[f'{loss_name}'] / results[f'{loss_name}_count']) if len(loss_meter) > 0: loss_count = epoch_results[f'{loss_name}_count'] desc_str += f' {loss_name} ({loss_count}) {loss_meter.val:.3f}' pbar.set_description(desc_str) pbar.update(1) dist.barrier() if self.verbose: pbar.close() dist.barrier() if 'qa' not in self.args.losses: uid2ans = None return epoch_results, uid2ans def main_worker(gpu, args): # GPU is assigned args.gpu = gpu args.rank = gpu print(f'Process Launching at GPU {gpu}') if args.distributed: torch.cuda.set_device(args.gpu) dist.init_process_group(backend='nccl') print(f'Building train loader at GPU {gpu}') train_loader = get_loader( args, split=args.train, mode='train', batch_size=args.batch_size, distributed=args.distributed, gpu=args.gpu, workers=args.num_workers, topk=args.train_topk,) print(f'Building val loader at GPU {gpu}') val_loader = get_loader( args, split=args.valid, mode='val', batch_size=args.batch_size, distributed=args.distributed, gpu=args.gpu, workers=args.num_workers, topk=args.valid_topk,) trainer = Trainer(args, train_loader, val_loader, train=True) trainer.train() if __name__ == "__main__": cudnn.benchmark = True args = parse_args() if args.local_rank in [0, -1]: print(args) ngpus_per_node = torch.cuda.device_count() args.world_size = ngpus_per_node LOSSES_NAME = [f'{name}_loss' for name in args.losses.split(',')] if args.local_rank in [0, -1]: print(LOSSES_NAME) LOSSES_NAME.append('total_loss') # total loss args.LOSSES_NAME = LOSSES_NAME comments = [] dsets = [] if 'coco' in args.train: dsets.append('COCO') if 'vg' in args.train: dsets.append('VG') comments.append(''.join(dsets)) if args.backbone: comments.append(args.backbone) comments.append(''.join(args.losses.split(','))) if args.comment != '': comments.append(args.comment) comment = '_'.join(comments) from datetime import datetime current_time = datetime.now().strftime('%b%d_%H-%M') project_dir = Path(__file__).resolve().parent.parent if args.local_rank in [0, -1]: run_name = f'{current_time}_GPU{args.world_size}' if len(comments) > 0: run_name += f'_{comment}' args.run_name = run_name if args.distributed: main_worker(args.local_rank, args)

[ "[email protected]" ]

[email protected]

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# -*- coding: utf-8 -*- # Copyright 2015 Donne Martin. All Rights Reserved. # # Creative Commons Attribution 4.0 International License (CC BY 4.0) # http://creativecommons.org/licenses/by/4.0/ import unittest from click.testing import CliRunner from awesome.awesome_cli import AwesomeCli class AwesomeCliTest(unittest.TestCase): def setUp(self): self.runner = CliRunner() self.awesome_cli = AwesomeCli()

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[email protected]

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''' Created on Mar 23, 2017 @author: MT ''' _______ h__ c_ Solution(o.. ___ rearrangeString s, k hashmap # dict ___ c __ s: hashmap[c] hashmap.g.. c, 0)+1 heap # list ___ c, freq __ hashmap.i.. h__.heappush(heap, [-freq, c]) queue # list res # list w.... heap: freq, c h__.heappop(heap) res.a..(c) queue.a..([freq, c]) __ l..(queue) < k: _____ freq, c queue.p.. 0) freq -freq-1 __ freq > 0 h__.heappush(heap, [-freq, c]) r.. ''.j..(res) __ l..(res) __ l..(s) ____ '' ___ test testCases [ ('aabbcc', 3), ('aaabc', 3), ('aaadbbcc', 2), ] ___ s, k __ testCases: print('s: %s' % (s print('k: %s' % (k result rearrangeString(s, k) print('result: %s' % (result print('-='*20+'-') __ _____ __ _____ Solution().test()

[ "[email protected]" ]

[email protected]

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preetising/Loops

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# coding=utf-8 # -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is regenerated. # -------------------------------------------------------------------------- import functools from typing import Any, Callable, Dict, Generic, Iterable, Optional, TypeVar, Union import warnings from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error from azure.core.paging import ItemPaged from azure.core.pipeline import PipelineResponse from azure.core.pipeline.transport import HttpResponse from azure.core.polling import LROPoller, NoPolling, PollingMethod from azure.core.rest import HttpRequest from azure.core.tracing.decorator import distributed_trace from azure.mgmt.core.exceptions import ARMErrorFormat from azure.mgmt.core.polling.arm_polling import ARMPolling from msrest import Serializer from .. import models as _models from .._vendor import _convert_request, _format_url_section T = TypeVar('T') JSONType = Any ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]] _SERIALIZER = Serializer() _SERIALIZER.client_side_validation = False def build_create_request_initial( subscription_id: str, resource_group_name: str, cluster_rp: str, cluster_resource_name: str, cluster_name: str, extension_name: str, *, json: JSONType = None, content: Any = None, **kwargs: Any ) -> HttpRequest: content_type = kwargs.pop('content_type', None) # type: Optional[str] api_version = "2022-03-01" accept = "application/json" # Construct URL url = kwargs.pop("template_url", '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{clusterRp}/{clusterResourceName}/{clusterName}/providers/Microsoft.KubernetesConfiguration/extensions/{extensionName}') path_format_arguments = { "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str', min_length=1), "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1), "clusterRp": _SERIALIZER.url("cluster_rp", cluster_rp, 'str'), "clusterResourceName": _SERIALIZER.url("cluster_resource_name", cluster_resource_name, 'str'), "clusterName": _SERIALIZER.url("cluster_name", cluster_name, 'str'), "extensionName": _SERIALIZER.url("extension_name", extension_name, 'str'), } url = _format_url_section(url, **path_format_arguments) # Construct parameters query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any] query_parameters['api-version'] = _SERIALIZER.query("api_version", api_version, 'str') # Construct headers header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any] if content_type is not None: header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str') header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str') return HttpRequest( method="PUT", url=url, params=query_parameters, headers=header_parameters, json=json, content=content, **kwargs ) def build_get_request( subscription_id: str, resource_group_name: str, cluster_rp: str, cluster_resource_name: str, cluster_name: str, extension_name: str, **kwargs: Any ) -> HttpRequest: api_version = "2022-03-01" accept = "application/json" # Construct URL url = kwargs.pop("template_url", '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{clusterRp}/{clusterResourceName}/{clusterName}/providers/Microsoft.KubernetesConfiguration/extensions/{extensionName}') path_format_arguments = { "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str', min_length=1), "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1), "clusterRp": _SERIALIZER.url("cluster_rp", cluster_rp, 'str'), "clusterResourceName": _SERIALIZER.url("cluster_resource_name", cluster_resource_name, 'str'), "clusterName": _SERIALIZER.url("cluster_name", cluster_name, 'str'), "extensionName": _SERIALIZER.url("extension_name", extension_name, 'str'), } url = _format_url_section(url, **path_format_arguments) # Construct parameters query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any] query_parameters['api-version'] = _SERIALIZER.query("api_version", api_version, 'str') # Construct headers header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any] header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str') return HttpRequest( method="GET", url=url, params=query_parameters, headers=header_parameters, **kwargs ) def build_delete_request_initial( subscription_id: str, resource_group_name: str, cluster_rp: str, cluster_resource_name: str, cluster_name: str, extension_name: str, *, force_delete: Optional[bool] = None, **kwargs: Any ) -> HttpRequest: api_version = "2022-03-01" accept = "application/json" # Construct URL url = kwargs.pop("template_url", '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{clusterRp}/{clusterResourceName}/{clusterName}/providers/Microsoft.KubernetesConfiguration/extensions/{extensionName}') path_format_arguments = { "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str', min_length=1), "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1), "clusterRp": _SERIALIZER.url("cluster_rp", cluster_rp, 'str'), "clusterResourceName": _SERIALIZER.url("cluster_resource_name", cluster_resource_name, 'str'), "clusterName": _SERIALIZER.url("cluster_name", cluster_name, 'str'), "extensionName": _SERIALIZER.url("extension_name", extension_name, 'str'), } url = _format_url_section(url, **path_format_arguments) # Construct parameters query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any] query_parameters['api-version'] = _SERIALIZER.query("api_version", api_version, 'str') if force_delete is not None: query_parameters['forceDelete'] = _SERIALIZER.query("force_delete", force_delete, 'bool') # Construct headers header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any] header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str') return HttpRequest( method="DELETE", url=url, params=query_parameters, headers=header_parameters, **kwargs ) def build_update_request_initial( subscription_id: str, resource_group_name: str, cluster_rp: str, cluster_resource_name: str, cluster_name: str, extension_name: str, *, json: JSONType = None, content: Any = None, **kwargs: Any ) -> HttpRequest: content_type = kwargs.pop('content_type', None) # type: Optional[str] api_version = "2022-03-01" accept = "application/json" # Construct URL url = kwargs.pop("template_url", '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{clusterRp}/{clusterResourceName}/{clusterName}/providers/Microsoft.KubernetesConfiguration/extensions/{extensionName}') path_format_arguments = { "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str', min_length=1), "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1), "clusterRp": _SERIALIZER.url("cluster_rp", cluster_rp, 'str'), "clusterResourceName": _SERIALIZER.url("cluster_resource_name", cluster_resource_name, 'str'), "clusterName": _SERIALIZER.url("cluster_name", cluster_name, 'str'), "extensionName": _SERIALIZER.url("extension_name", extension_name, 'str'), } url = _format_url_section(url, **path_format_arguments) # Construct parameters query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any] query_parameters['api-version'] = _SERIALIZER.query("api_version", api_version, 'str') # Construct headers header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any] if content_type is not None: header_parameters['Content-Type'] = _SERIALIZER.header("content_type", content_type, 'str') header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str') return HttpRequest( method="PATCH", url=url, params=query_parameters, headers=header_parameters, json=json, content=content, **kwargs ) def build_list_request( subscription_id: str, resource_group_name: str, cluster_rp: str, cluster_resource_name: str, cluster_name: str, **kwargs: Any ) -> HttpRequest: api_version = "2022-03-01" accept = "application/json" # Construct URL url = kwargs.pop("template_url", '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{clusterRp}/{clusterResourceName}/{clusterName}/providers/Microsoft.KubernetesConfiguration/extensions') path_format_arguments = { "subscriptionId": _SERIALIZER.url("subscription_id", subscription_id, 'str', min_length=1), "resourceGroupName": _SERIALIZER.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1), "clusterRp": _SERIALIZER.url("cluster_rp", cluster_rp, 'str'), "clusterResourceName": _SERIALIZER.url("cluster_resource_name", cluster_resource_name, 'str'), "clusterName": _SERIALIZER.url("cluster_name", cluster_name, 'str'), } url = _format_url_section(url, **path_format_arguments) # Construct parameters query_parameters = kwargs.pop("params", {}) # type: Dict[str, Any] query_parameters['api-version'] = _SERIALIZER.query("api_version", api_version, 'str') # Construct headers header_parameters = kwargs.pop("headers", {}) # type: Dict[str, Any] header_parameters['Accept'] = _SERIALIZER.header("accept", accept, 'str') return HttpRequest( method="GET", url=url, params=query_parameters, headers=header_parameters, **kwargs ) class ExtensionsOperations(object): """ExtensionsOperations operations. You should not instantiate this class directly. Instead, you should create a Client instance that instantiates it for you and attaches it as an attribute. :ivar models: Alias to model classes used in this operation group. :type models: ~azure.mgmt.kubernetesconfiguration.v2022_03_01.models :param client: Client for service requests. :param config: Configuration of service client. :param serializer: An object model serializer. :param deserializer: An object model deserializer. """ models = _models def __init__(self, client, config, serializer, deserializer): self._client = client self._serialize = serializer self._deserialize = deserializer self._config = config def _create_initial( self, resource_group_name: str, cluster_rp: str, cluster_resource_name: str, cluster_name: str, extension_name: str, extension: "_models.Extension", **kwargs: Any ) -> "_models.Extension": cls = kwargs.pop('cls', None) # type: ClsType["_models.Extension"] error_map = { 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError } error_map.update(kwargs.pop('error_map', {})) content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] _json = self._serialize.body(extension, 'Extension') request = build_create_request_initial( subscription_id=self._config.subscription_id, resource_group_name=resource_group_name, cluster_rp=cluster_rp, cluster_resource_name=cluster_resource_name, cluster_name=cluster_name, extension_name=extension_name, content_type=content_type, json=_json, template_url=self._create_initial.metadata['url'], ) request = _convert_request(request) request.url = self._client.format_url(request.url) pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response if response.status_code not in [200, 201]: map_error(status_code=response.status_code, response=response, error_map=error_map) raise HttpResponseError(response=response, error_format=ARMErrorFormat) if response.status_code == 200: deserialized = self._deserialize('Extension', pipeline_response) if response.status_code == 201: deserialized = self._deserialize('Extension', pipeline_response) if cls: return cls(pipeline_response, deserialized, {}) return deserialized _create_initial.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{clusterRp}/{clusterResourceName}/{clusterName}/providers/Microsoft.KubernetesConfiguration/extensions/{extensionName}'} # type: ignore @distributed_trace def begin_create( self, resource_group_name: str, cluster_rp: str, cluster_resource_name: str, cluster_name: str, extension_name: str, extension: "_models.Extension", **kwargs: Any ) -> LROPoller["_models.Extension"]: """Create a new Kubernetes Cluster Extension. :param resource_group_name: The name of the resource group. The name is case insensitive. :type resource_group_name: str :param cluster_rp: The Kubernetes cluster RP - i.e. Microsoft.ContainerService, Microsoft.Kubernetes, Microsoft.HybridContainerService. :type cluster_rp: str :param cluster_resource_name: The Kubernetes cluster resource name - i.e. managedClusters, connectedClusters, provisionedClusters. :type cluster_resource_name: str :param cluster_name: The name of the kubernetes cluster. :type cluster_name: str :param extension_name: Name of the Extension. :type extension_name: str :param extension: Properties necessary to Create an Extension. :type extension: ~azure.mgmt.kubernetesconfiguration.v2022_03_01.models.Extension :keyword callable cls: A custom type or function that will be passed the direct response :keyword str continuation_token: A continuation token to restart a poller from a saved state. :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this operation to not poll, or pass in your own initialized polling object for a personal polling strategy. :paramtype polling: bool or ~azure.core.polling.PollingMethod :keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present. :return: An instance of LROPoller that returns either Extension or the result of cls(response) :rtype: ~azure.core.polling.LROPoller[~azure.mgmt.kubernetesconfiguration.v2022_03_01.models.Extension] :raises: ~azure.core.exceptions.HttpResponseError """ content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] polling = kwargs.pop('polling', True) # type: Union[bool, azure.core.polling.PollingMethod] cls = kwargs.pop('cls', None) # type: ClsType["_models.Extension"] lro_delay = kwargs.pop( 'polling_interval', self._config.polling_interval ) cont_token = kwargs.pop('continuation_token', None) # type: Optional[str] if cont_token is None: raw_result = self._create_initial( resource_group_name=resource_group_name, cluster_rp=cluster_rp, cluster_resource_name=cluster_resource_name, cluster_name=cluster_name, extension_name=extension_name, extension=extension, content_type=content_type, cls=lambda x,y,z: x, **kwargs ) kwargs.pop('error_map', None) def get_long_running_output(pipeline_response): response = pipeline_response.http_response deserialized = self._deserialize('Extension', pipeline_response) if cls: return cls(pipeline_response, deserialized, {}) return deserialized if polling is True: polling_method = ARMPolling(lro_delay, lro_options={'final-state-via': 'azure-async-operation'}, **kwargs) elif polling is False: polling_method = NoPolling() else: polling_method = polling if cont_token: return LROPoller.from_continuation_token( polling_method=polling_method, continuation_token=cont_token, client=self._client, deserialization_callback=get_long_running_output ) else: return LROPoller(self._client, raw_result, get_long_running_output, polling_method) begin_create.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{clusterRp}/{clusterResourceName}/{clusterName}/providers/Microsoft.KubernetesConfiguration/extensions/{extensionName}'} # type: ignore @distributed_trace def get( self, resource_group_name: str, cluster_rp: str, cluster_resource_name: str, cluster_name: str, extension_name: str, **kwargs: Any ) -> "_models.Extension": """Gets Kubernetes Cluster Extension. :param resource_group_name: The name of the resource group. The name is case insensitive. :type resource_group_name: str :param cluster_rp: The Kubernetes cluster RP - i.e. Microsoft.ContainerService, Microsoft.Kubernetes, Microsoft.HybridContainerService. :type cluster_rp: str :param cluster_resource_name: The Kubernetes cluster resource name - i.e. managedClusters, connectedClusters, provisionedClusters. :type cluster_resource_name: str :param cluster_name: The name of the kubernetes cluster. :type cluster_name: str :param extension_name: Name of the Extension. :type extension_name: str :keyword callable cls: A custom type or function that will be passed the direct response :return: Extension, or the result of cls(response) :rtype: ~azure.mgmt.kubernetesconfiguration.v2022_03_01.models.Extension :raises: ~azure.core.exceptions.HttpResponseError """ cls = kwargs.pop('cls', None) # type: ClsType["_models.Extension"] error_map = { 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError } error_map.update(kwargs.pop('error_map', {})) request = build_get_request( subscription_id=self._config.subscription_id, resource_group_name=resource_group_name, cluster_rp=cluster_rp, cluster_resource_name=cluster_resource_name, cluster_name=cluster_name, extension_name=extension_name, template_url=self.get.metadata['url'], ) request = _convert_request(request) request.url = self._client.format_url(request.url) pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) deserialized = self._deserialize('Extension', pipeline_response) if cls: return cls(pipeline_response, deserialized, {}) return deserialized get.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{clusterRp}/{clusterResourceName}/{clusterName}/providers/Microsoft.KubernetesConfiguration/extensions/{extensionName}'} # type: ignore def _delete_initial( self, resource_group_name: str, cluster_rp: str, cluster_resource_name: str, cluster_name: str, extension_name: str, force_delete: Optional[bool] = None, **kwargs: Any ) -> None: cls = kwargs.pop('cls', None) # type: ClsType[None] error_map = { 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError } error_map.update(kwargs.pop('error_map', {})) request = build_delete_request_initial( subscription_id=self._config.subscription_id, resource_group_name=resource_group_name, cluster_rp=cluster_rp, cluster_resource_name=cluster_resource_name, cluster_name=cluster_name, extension_name=extension_name, force_delete=force_delete, template_url=self._delete_initial.metadata['url'], ) request = _convert_request(request) request.url = self._client.format_url(request.url) pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response if response.status_code not in [200, 202, 204]: map_error(status_code=response.status_code, response=response, error_map=error_map) raise HttpResponseError(response=response, error_format=ARMErrorFormat) if cls: return cls(pipeline_response, None, {}) _delete_initial.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{clusterRp}/{clusterResourceName}/{clusterName}/providers/Microsoft.KubernetesConfiguration/extensions/{extensionName}'} # type: ignore @distributed_trace def begin_delete( self, resource_group_name: str, cluster_rp: str, cluster_resource_name: str, cluster_name: str, extension_name: str, force_delete: Optional[bool] = None, **kwargs: Any ) -> LROPoller[None]: """Delete a Kubernetes Cluster Extension. This will cause the Agent to Uninstall the extension from the cluster. :param resource_group_name: The name of the resource group. The name is case insensitive. :type resource_group_name: str :param cluster_rp: The Kubernetes cluster RP - i.e. Microsoft.ContainerService, Microsoft.Kubernetes, Microsoft.HybridContainerService. :type cluster_rp: str :param cluster_resource_name: The Kubernetes cluster resource name - i.e. managedClusters, connectedClusters, provisionedClusters. :type cluster_resource_name: str :param cluster_name: The name of the kubernetes cluster. :type cluster_name: str :param extension_name: Name of the Extension. :type extension_name: str :param force_delete: Delete the extension resource in Azure - not the normal asynchronous delete. :type force_delete: bool :keyword callable cls: A custom type or function that will be passed the direct response :keyword str continuation_token: A continuation token to restart a poller from a saved state. :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this operation to not poll, or pass in your own initialized polling object for a personal polling strategy. :paramtype polling: bool or ~azure.core.polling.PollingMethod :keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present. :return: An instance of LROPoller that returns either None or the result of cls(response) :rtype: ~azure.core.polling.LROPoller[None] :raises: ~azure.core.exceptions.HttpResponseError """ polling = kwargs.pop('polling', True) # type: Union[bool, azure.core.polling.PollingMethod] cls = kwargs.pop('cls', None) # type: ClsType[None] lro_delay = kwargs.pop( 'polling_interval', self._config.polling_interval ) cont_token = kwargs.pop('continuation_token', None) # type: Optional[str] if cont_token is None: raw_result = self._delete_initial( resource_group_name=resource_group_name, cluster_rp=cluster_rp, cluster_resource_name=cluster_resource_name, cluster_name=cluster_name, extension_name=extension_name, force_delete=force_delete, cls=lambda x,y,z: x, **kwargs ) kwargs.pop('error_map', None) def get_long_running_output(pipeline_response): if cls: return cls(pipeline_response, None, {}) if polling is True: polling_method = ARMPolling(lro_delay, lro_options={'final-state-via': 'azure-async-operation'}, **kwargs) elif polling is False: polling_method = NoPolling() else: polling_method = polling if cont_token: return LROPoller.from_continuation_token( polling_method=polling_method, continuation_token=cont_token, client=self._client, deserialization_callback=get_long_running_output ) else: return LROPoller(self._client, raw_result, get_long_running_output, polling_method) begin_delete.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{clusterRp}/{clusterResourceName}/{clusterName}/providers/Microsoft.KubernetesConfiguration/extensions/{extensionName}'} # type: ignore def _update_initial( self, resource_group_name: str, cluster_rp: str, cluster_resource_name: str, cluster_name: str, extension_name: str, patch_extension: "_models.PatchExtension", **kwargs: Any ) -> "_models.Extension": cls = kwargs.pop('cls', None) # type: ClsType["_models.Extension"] error_map = { 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError } error_map.update(kwargs.pop('error_map', {})) content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] _json = self._serialize.body(patch_extension, 'PatchExtension') request = build_update_request_initial( subscription_id=self._config.subscription_id, resource_group_name=resource_group_name, cluster_rp=cluster_rp, cluster_resource_name=cluster_resource_name, cluster_name=cluster_name, extension_name=extension_name, content_type=content_type, json=_json, template_url=self._update_initial.metadata['url'], ) request = _convert_request(request) request.url = self._client.format_url(request.url) pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response if response.status_code not in [202]: map_error(status_code=response.status_code, response=response, error_map=error_map) raise HttpResponseError(response=response, error_format=ARMErrorFormat) deserialized = self._deserialize('Extension', pipeline_response) if cls: return cls(pipeline_response, deserialized, {}) return deserialized _update_initial.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{clusterRp}/{clusterResourceName}/{clusterName}/providers/Microsoft.KubernetesConfiguration/extensions/{extensionName}'} # type: ignore @distributed_trace def begin_update( self, resource_group_name: str, cluster_rp: str, cluster_resource_name: str, cluster_name: str, extension_name: str, patch_extension: "_models.PatchExtension", **kwargs: Any ) -> LROPoller["_models.Extension"]: """Patch an existing Kubernetes Cluster Extension. :param resource_group_name: The name of the resource group. The name is case insensitive. :type resource_group_name: str :param cluster_rp: The Kubernetes cluster RP - i.e. Microsoft.ContainerService, Microsoft.Kubernetes, Microsoft.HybridContainerService. :type cluster_rp: str :param cluster_resource_name: The Kubernetes cluster resource name - i.e. managedClusters, connectedClusters, provisionedClusters. :type cluster_resource_name: str :param cluster_name: The name of the kubernetes cluster. :type cluster_name: str :param extension_name: Name of the Extension. :type extension_name: str :param patch_extension: Properties to Patch in an existing Extension. :type patch_extension: ~azure.mgmt.kubernetesconfiguration.v2022_03_01.models.PatchExtension :keyword callable cls: A custom type or function that will be passed the direct response :keyword str continuation_token: A continuation token to restart a poller from a saved state. :keyword polling: By default, your polling method will be ARMPolling. Pass in False for this operation to not poll, or pass in your own initialized polling object for a personal polling strategy. :paramtype polling: bool or ~azure.core.polling.PollingMethod :keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present. :return: An instance of LROPoller that returns either Extension or the result of cls(response) :rtype: ~azure.core.polling.LROPoller[~azure.mgmt.kubernetesconfiguration.v2022_03_01.models.Extension] :raises: ~azure.core.exceptions.HttpResponseError """ content_type = kwargs.pop('content_type', "application/json") # type: Optional[str] polling = kwargs.pop('polling', True) # type: Union[bool, azure.core.polling.PollingMethod] cls = kwargs.pop('cls', None) # type: ClsType["_models.Extension"] lro_delay = kwargs.pop( 'polling_interval', self._config.polling_interval ) cont_token = kwargs.pop('continuation_token', None) # type: Optional[str] if cont_token is None: raw_result = self._update_initial( resource_group_name=resource_group_name, cluster_rp=cluster_rp, cluster_resource_name=cluster_resource_name, cluster_name=cluster_name, extension_name=extension_name, patch_extension=patch_extension, content_type=content_type, cls=lambda x,y,z: x, **kwargs ) kwargs.pop('error_map', None) def get_long_running_output(pipeline_response): response = pipeline_response.http_response deserialized = self._deserialize('Extension', pipeline_response) if cls: return cls(pipeline_response, deserialized, {}) return deserialized if polling is True: polling_method = ARMPolling(lro_delay, lro_options={'final-state-via': 'azure-async-operation'}, **kwargs) elif polling is False: polling_method = NoPolling() else: polling_method = polling if cont_token: return LROPoller.from_continuation_token( polling_method=polling_method, continuation_token=cont_token, client=self._client, deserialization_callback=get_long_running_output ) else: return LROPoller(self._client, raw_result, get_long_running_output, polling_method) begin_update.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{clusterRp}/{clusterResourceName}/{clusterName}/providers/Microsoft.KubernetesConfiguration/extensions/{extensionName}'} # type: ignore @distributed_trace def list( self, resource_group_name: str, cluster_rp: str, cluster_resource_name: str, cluster_name: str, **kwargs: Any ) -> Iterable["_models.ExtensionsList"]: """List all Extensions in the cluster. :param resource_group_name: The name of the resource group. The name is case insensitive. :type resource_group_name: str :param cluster_rp: The Kubernetes cluster RP - i.e. Microsoft.ContainerService, Microsoft.Kubernetes, Microsoft.HybridContainerService. :type cluster_rp: str :param cluster_resource_name: The Kubernetes cluster resource name - i.e. managedClusters, connectedClusters, provisionedClusters. :type cluster_resource_name: str :param cluster_name: The name of the kubernetes cluster. :type cluster_name: str :keyword callable cls: A custom type or function that will be passed the direct response :return: An iterator like instance of either ExtensionsList or the result of cls(response) :rtype: ~azure.core.paging.ItemPaged[~azure.mgmt.kubernetesconfiguration.v2022_03_01.models.ExtensionsList] :raises: ~azure.core.exceptions.HttpResponseError """ cls = kwargs.pop('cls', None) # type: ClsType["_models.ExtensionsList"] error_map = { 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError } error_map.update(kwargs.pop('error_map', {})) def prepare_request(next_link=None): if not next_link: request = build_list_request( subscription_id=self._config.subscription_id, resource_group_name=resource_group_name, cluster_rp=cluster_rp, cluster_resource_name=cluster_resource_name, cluster_name=cluster_name, template_url=self.list.metadata['url'], ) request = _convert_request(request) request.url = self._client.format_url(request.url) else: request = build_list_request( subscription_id=self._config.subscription_id, resource_group_name=resource_group_name, cluster_rp=cluster_rp, cluster_resource_name=cluster_resource_name, cluster_name=cluster_name, template_url=next_link, ) request = _convert_request(request) request.url = self._client.format_url(request.url) request.method = "GET" return request def extract_data(pipeline_response): deserialized = self._deserialize("ExtensionsList", pipeline_response) list_of_elem = deserialized.value if cls: list_of_elem = cls(list_of_elem) return deserialized.next_link or None, iter(list_of_elem) def get_next(next_link=None): request = prepare_request(next_link) pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response) raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) return pipeline_response return ItemPaged( get_next, extract_data ) list.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{clusterRp}/{clusterResourceName}/{clusterName}/providers/Microsoft.KubernetesConfiguration/extensions'} # type: ignore

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[email protected]

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/pylib/mdsplus_alpha/tests/segmentsUnitTest.py

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drsmith48/pppl-mdsplus-python

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#!/usr/bin/env python # -*- coding: utf-8 -*- from unittest import TestCase,TestSuite from tree import Tree from mdsdata import * from mdsscalar import * from mdsarray import * import numpy as np import random import os import sys import tempfile _tmpdir=tempfile.mkdtemp() def setUpModule(): pass def tearDownModule(): import shutil shutil.rmtree(_tmpdir) class segmentsTests(TestCase): def setUp(self): os.environ["seg_tree_path"]=_tmpdir def tearDown(self): pass def arrayDimensionOrder(self): ptree=Tree('seg_tree',-1,'NEW') ptree.addNode('IMM') ptree.write() ptree=Tree('seg_tree',-1) ptree.createPulse(1) ptree=Tree('seg_tree',1) node=ptree.getNode('IMM') WIDTH = 640 HEIGHT =480; currFrame=np.zeros(WIDTH*HEIGHT, dtype = np.int16); currTime=float(0); for i in range(0,WIDTH): for j in range(0,HEIGHT): currFrame[i*HEIGHT+j]=random.randint(0,255) currTime = float(0) startTime = Float32(currTime) endTime = Float32(currTime) dim = Float32Array(currTime) segment = Int16Array(currFrame) segment.resize([1,HEIGHT,WIDTH]) shape = segment.getShape() node.makeSegment(startTime, endTime, dim, segment) retShape = node.getShape() self.assertEqual(shape[0],retShape[0]) self.assertEqual(shape[1],retShape[1]) self.assertEqual(shape[2],retShape[2]) def runTest(self): self.arrayDimensionOrder() def suite(): tests = ['arrayDimensionOrder'] return TestSuite(map(segmentsTests,tests))

[ "[email protected]" ]

[email protected]

690ca2306342d5c831a89a5cd5ffcc9790800260

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/backend/techh_18306/settings.py

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crowdbotics-apps/techh-18306

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refs/heads/master

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""" Django settings for techh_18306 project. Generated by 'django-admin startproject' using Django 2.2.2. For more information on this file, see https://docs.djangoproject.com/en/2.2/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/2.2/ref/settings/ """ import os import environ env = environ.Env() # SECURITY WARNING: don't run with debug turned on in production! DEBUG = env.bool("DEBUG", default=False) # Build paths inside the project like this: os.path.join(BASE_DIR, ...) BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/2.2/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = env.str("SECRET_KEY") ALLOWED_HOSTS = env.list("HOST", default=["*"]) SITE_ID = 1 SECURE_PROXY_SSL_HEADER = ("HTTP_X_FORWARDED_PROTO", "https") SECURE_SSL_REDIRECT = env.bool("SECURE_REDIRECT", default=False) # Application definition INSTALLED_APPS = [ 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', 'django.contrib.sites' ] LOCAL_APPS = [ 'home', 'users.apps.UsersConfig', ] THIRD_PARTY_APPS = [ 'rest_framework', 'rest_framework.authtoken', 'rest_auth', 'rest_auth.registration', 'bootstrap4', 'allauth', 'allauth.account', 'allauth.socialaccount', 'allauth.socialaccount.providers.google', 'django_extensions', 'drf_yasg', # start fcm_django push notifications 'fcm_django', # end fcm_django push notifications ] INSTALLED_APPS += LOCAL_APPS + THIRD_PARTY_APPS MIDDLEWARE = [ 'django.middleware.security.SecurityMiddleware', 'django.contrib.sessions.middleware.SessionMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware', ] ROOT_URLCONF = 'techh_18306.urls' TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [], 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', ], }, }, ] WSGI_APPLICATION = 'techh_18306.wsgi.application' # Database # https://docs.djangoproject.com/en/2.2/ref/settings/#databases DATABASES = { 'default': { 'ENGINE': 'django.db.backends.sqlite3', 'NAME': os.path.join(BASE_DIR, 'db.sqlite3'), } } if env.str("DATABASE_URL", default=None): DATABASES = { 'default': env.db() } # Password validation # https://docs.djangoproject.com/en/2.2/ref/settings/#auth-password-validators AUTH_PASSWORD_VALIDATORS = [ { 'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator', }, { 'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator', }, { 'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator', }, { 'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator', }, ] # Internationalization # https://docs.djangoproject.com/en/2.2/topics/i18n/ LANGUAGE_CODE = 'en-us' TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/2.2/howto/static-files/ STATIC_URL = '/static/' MIDDLEWARE += ['whitenoise.middleware.WhiteNoiseMiddleware'] AUTHENTICATION_BACKENDS = ( 'django.contrib.auth.backends.ModelBackend', 'allauth.account.auth_backends.AuthenticationBackend' ) STATIC_ROOT = os.path.join(BASE_DIR, "staticfiles") STATICFILES_DIRS = [ os.path.join(BASE_DIR, 'static') ] STATICFILES_STORAGE = 'whitenoise.storage.CompressedManifestStaticFilesStorage' # allauth / users ACCOUNT_EMAIL_REQUIRED = True ACCOUNT_AUTHENTICATION_METHOD = 'email' ACCOUNT_USERNAME_REQUIRED = False ACCOUNT_EMAIL_VERIFICATION = "mandatory" ACCOUNT_CONFIRM_EMAIL_ON_GET = True ACCOUNT_LOGIN_ON_EMAIL_CONFIRMATION = True ACCOUNT_UNIQUE_EMAIL = True LOGIN_REDIRECT_URL = "users:redirect" ACCOUNT_ADAPTER = "users.adapters.AccountAdapter" SOCIALACCOUNT_ADAPTER = "users.adapters.SocialAccountAdapter" ACCOUNT_ALLOW_REGISTRATION = env.bool("ACCOUNT_ALLOW_REGISTRATION", True) SOCIALACCOUNT_ALLOW_REGISTRATION = env.bool("SOCIALACCOUNT_ALLOW_REGISTRATION", True) REST_AUTH_SERIALIZERS = { # Replace password reset serializer to fix 500 error "PASSWORD_RESET_SERIALIZER": "home.api.v1.serializers.PasswordSerializer", } REST_AUTH_REGISTER_SERIALIZERS = { # Use custom serializer that has no username and matches web signup "REGISTER_SERIALIZER": "home.api.v1.serializers.SignupSerializer", } # Custom user model AUTH_USER_MODEL = "users.User" EMAIL_HOST = env.str("EMAIL_HOST", "smtp.sendgrid.net") EMAIL_HOST_USER = env.str("SENDGRID_USERNAME", "") EMAIL_HOST_PASSWORD = env.str("SENDGRID_PASSWORD", "") EMAIL_PORT = 587 EMAIL_USE_TLS = True # start fcm_django push notifications FCM_DJANGO_SETTINGS = { "FCM_SERVER_KEY": env.str("FCM_SERVER_KEY", "") } # end fcm_django push notifications if DEBUG: # output email to console instead of sending EMAIL_BACKEND = "django.core.mail.backends.console.EmailBackend"

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[email protected]

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import numpy as np from matplotlib import pyplot as plt from matplotlib import animation fig, ax = plt.subplots() # 生成子图，相当于fig = plt.figure(), # ax = fig.add_subplot(),其中ax的函数参数表示把当前画布进行分割， # 例：fig.add_subplot(2,2,2).表示将画布分割为两行两列，ax在第2个子图中绘制，其中行优先。 x = np.arange(0, 2*np.pi, 0.01) # 表示从0~2*np.pi之间每隔0.01取一个点 line, = ax.plot(x, np.sin(x)) # 注意，这里line后面要加上逗号，表示一个具有一个元素的元组 # print(type(line)) # print(type((line,))) # <class 'matplotlib.lines.Line2D'> # <class 'tuple'> def animate(i): # 这里的i其实就是参数0-99，即时frames控制的参数，控制程序画图变换的次数 # print(i) # 0-99 line.set_ydata(np.sin(x + i/10.0)) # 改变线条y的坐标值 return line, def init(): # 初始化函数，图形开始显示的状态 line.set_ydata(np.sin(x)) return line, ani = animation.FuncAnimation(fig=fig, func=animate, frames=100, init_func=init, interval=100, blit=False) """frames设定帧数,总共执行100个update就会进行下一次循环，并且frames还会作为参数传入animate()函数，init_func设定初始函数图像, interval设置更新间隔此处设置为20毫秒，(仔细想想20毫秒其实是很小的一个间隔) blit如果是只有变化了的像素点才更新就设置为True,如果是整张图片所有像素点全部更新的话就设置为False """ plt.show()

[ "[email protected]" ]

[email protected]

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/bam/task_specific/task.py

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# coding=utf-8 # Copyright 2023 The Google Research Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Base class for tasks.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function import abc import csv import os import tensorflow.compat.v1 as tf class Example(object): __metaclass__ = abc.ABCMeta def __init__(self, task_name): self.task_name = task_name class Task(object): """Override this class to add a new task.""" __metaclass__ = abc.ABCMeta def __init__(self, config, name, long_sequences=False): self.config = config self.name = name self.long_sequences = long_sequences def get_examples(self, split): return self.load_data(split + ".tsv", split) def get_test_splits(self): return ["test"] def load_data(self, fname, split): examples = self._create_examples( read_tsv(os.path.join(self.config.raw_data_dir(self.name), fname), max_lines=50 if self.config.debug else None), split) return examples @abc.abstractmethod def _create_examples(self, lines, split): pass @abc.abstractmethod def get_scorer(self): pass @abc.abstractmethod def get_feature_specs(self): pass @abc.abstractmethod def featurize(self, example, is_training): pass @abc.abstractmethod def get_prediction_module(self, bert_model, features, is_training, percent_done): pass def __repr__(self): return "Task(" + self.name + ")" def read_tsv(input_file, quotechar=None, max_lines=None): """Reads a tab separated value file.""" with tf.gfile.Open(input_file, "r") as f: reader = csv.reader(f, delimiter="\t", quotechar=quotechar) lines = [] for i, line in enumerate(reader): if max_lines and i >= max_lines: break lines.append(line) return lines

[ "[email protected]" ]

[email protected]

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# ------------------------------------ # Copyright (c) Microsoft Corporation. # Licensed under the MIT License. # ------------------------------------ import abc import logging import time from typing import Any, Optional from azure.core.credentials import AccessToken from ..._constants import DEFAULT_REFRESH_OFFSET, DEFAULT_TOKEN_REFRESH_RETRY_DELAY from ..._internal import within_credential_chain _LOGGER = logging.getLogger(__name__) class GetTokenMixin(abc.ABC): def __init__(self, *args, **kwargs) -> None: self._last_request_time = 0 # https://github.com/python/mypy/issues/5887 super(GetTokenMixin, self).__init__(*args, **kwargs) # type: ignore @abc.abstractmethod async def _acquire_token_silently(self, *scopes: str, **kwargs) -> Optional[AccessToken]: """Attempt to acquire an access token from a cache or by redeeming a refresh token. :param str scopes: desired scopes for the access token. This method requires at least one scope. For more information about scopes, see https://learn.microsoft.com/azure/active-directory/develop/scopes-oidc. :return: An access token with the desired scopes if successful; otherwise, None. :rtype: ~azure.core.credentials.AccessToken or None """ @abc.abstractmethod async def _request_token(self, *scopes: str, **kwargs) -> AccessToken: """Request an access token from the STS. :param str scopes: desired scopes for the access token. This method requires at least one scope. For more information about scopes, see https://learn.microsoft.com/azure/active-directory/develop/scopes-oidc. :return: An access token with the desired scopes. :rtype: ~azure.core.credentials.AccessToken """ def _should_refresh(self, token: AccessToken) -> bool: now = int(time.time()) if token.expires_on - now > DEFAULT_REFRESH_OFFSET: return False if now - self._last_request_time < DEFAULT_TOKEN_REFRESH_RETRY_DELAY: return False return True async def get_token( self, *scopes: str, claims: Optional[str] = None, tenant_id: Optional[str] = None, **kwargs: Any ) -> AccessToken: """Request an access token for `scopes`. This method is called automatically by Azure SDK clients. :param str scopes: desired scopes for the access token. This method requires at least one scope. For more information about scopes, see https://learn.microsoft.com/azure/active-directory/develop/scopes-oidc. :keyword str claims: additional claims required in the token, such as those returned in a resource provider's claims challenge following an authorization failure. :keyword str tenant_id: optional tenant to include in the token request. :keyword bool enable_cae: indicates whether to enable Continuous Access Evaluation (CAE) for the requested token. Defaults to False. :return: An access token with the desired scopes. :rtype: ~azure.core.credentials.AccessToken :raises CredentialUnavailableError: the credential is unable to attempt authentication because it lacks required data, state, or platform support :raises ~azure.core.exceptions.ClientAuthenticationError: authentication failed. The error's ``message`` attribute gives a reason. """ if not scopes: raise ValueError('"get_token" requires at least one scope') try: token = await self._acquire_token_silently(*scopes, claims=claims, tenant_id=tenant_id, **kwargs) if not token: self._last_request_time = int(time.time()) token = await self._request_token(*scopes, claims=claims, tenant_id=tenant_id, **kwargs) elif self._should_refresh(token): try: self._last_request_time = int(time.time()) token = await self._request_token(*scopes, claims=claims, tenant_id=tenant_id, **kwargs) except Exception: # pylint:disable=broad-except pass _LOGGER.log( logging.DEBUG if within_credential_chain.get() else logging.INFO, "%s.get_token succeeded", self.__class__.__name__, ) return token except Exception as ex: _LOGGER.log( logging.DEBUG if within_credential_chain.get() else logging.WARNING, "%s.get_token failed: %s", self.__class__.__name__, ex, exc_info=_LOGGER.isEnabledFor(logging.DEBUG), ) raise

[ "[email protected]" ]

[email protected]

cb8a404a6028dd2e0c857ee4f7bbbaa73b7296c9

ca7aa979e7059467e158830b76673f5b77a0f5a3

/Python_codes/p03200/s271432048.py

bcd6a8482b6eb023426b8dd72faca95f03661394

[]

no_license

Aasthaengg/IBMdataset

7abb6cbcc4fb03ef5ca68ac64ba460c4a64f8901

f33f1c5c3b16d0ea8d1f5a7d479ad288bb3f48d8

refs/heads/main

2023-04-22T10:22:44.763102

2021-05-13T17:27:22

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S = list(input()) n = len(S) cnt_b = 0 cnt = 0 for i in range(n): if S[i] == 'B': cnt_b += 1 cnt += i ans = int((2*n - cnt_b -1)*cnt_b*0.5 - cnt) print(ans)

[ "[email protected]" ]

[email protected]

59565e2453584531a21bcde645e428597918d80b

e714dfd95cb74f4e357af8d085e4dcaf8b7ecdf3

/0x03-python-data_structures/10-divisible_by_2.py

2d808d5249e958464d33eb26dcdab22c4db79367

[]

no_license

MCavigli/holbertonschool-higher_level_programming_classic

2cea769dc1fd39e90f6ef74cdb3191e2472b0282

870548f964a3deac4a41918e9c3d0bad6cd732b4

refs/heads/master

2022-03-06T09:33:56.839118

2019-09-27T06:04:34

184,122,977

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167

py

#!/usr/bin/python3 def divisible_by_2(my_list=[]): new = [] for num in my_list: new.append(True) if num % 2 == 0 else new.append(False) return new

[ "[email protected]" ]

[email protected]

3034898b4c6efff6c979aa9c058eaad3bdfe78e5

d51b4c766661af65b4ee6e7c30f8cb4bdd8603e3

/python/oop/method/iter.py

a612e99ce5f3e8c7cc0ed0aa897554f8d66889a4

[]

no_license

yanxurui/keepcoding

3e988c76b123d55b32cf7cc35fbffb12c4ccb095

d6b9f07e2d1437681fa77fee0687ea9b83cab135

refs/heads/master

2021-01-24T09:01:41.306597

2020-05-21T05:36:04

93,400,267

1

null

UTF-8

Python

false

698

py

class Spam(object): """[summary] >>> for i in Spam(1, 5): ... print(i) ... 1 4 9 16 >>> # iterate manully >>> X = Spam(1, 5) >>> I = iter(X) >>> next(I) 1 >>> next(I) 4 >>> next(I) 9 >>> next(I) 16 >>> next(I) Traceback (most recent call last): StopIteration """ def __init__(self, start, stop): self.value = start self.stop = stop def __iter__(self): return self # use `def __next__(self)` in python3 def next(self): if self.value == self.stop: raise StopIteration rv = self.value ** 2 self.value += 1 return rv

[ "[email protected]" ]

[email protected]

e85fdfeeaef3f45656935aec998ebc36b9928833

7f3a439c6ac921f07101759e932424792ee9e24e

/std_lib/asyncio/p01_coroutine_task/ch02_awaitables.py

9d984214e2480f5b6935010ec261bc2252865bb2

[]

no_license

multiscripter/python

03f6299af0ee2153e9e3b696aa591e460a3d6a52

eef7900b7a564e0850659fb59c1218be9c6829ea

refs/heads/master

2023-04-13T05:24:29.434394

2021-04-26T12:11:59

289,573,367

0

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UTF-8

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1,553

py

import asyncio # Мы говорим, что объект является awaitable (ожидаемым) объектом, # если его можно использовать в выражении await. # Многие API-интерфейсы asyncio предназначены для приёма awaitable-объектов. # Есть три основных типа awaitable-объектов: Coroutine, Task и Future. # 1. Coroutine. # coroutines являются awaitable, и поэтому их можно "ожидать" из других coroutines: async def nested(): return 42 async def run_nested(): print(await nested()) asyncio.run(run_nested()) # 2. Task. # Tasks используются для планирования запуска coroutines одновременно. async def run_task_nested(): task = asyncio.create_task(nested()) print(await task) asyncio.run(run_task_nested()) # 3. Future. # Future - это специальный низкоуровневый ожидающий объект, # представляющий конечный результат асинхронной операции. # Когда ожидается объект Future, это означает, что coroutine будет ждать, # пока Future не будет разрешен (resolved) в каком-то другом месте. # Future-объекты в asyncio необходимы, чтобы разрешить использование кода # на основе callback с async/await.

[ "[email protected]" ]

[email protected]

d5fc1a9a549e1a6ce9e5fdc380292c712031d489

c364fca8ae4c896dee2c8b0dc545f4d73c8c8314

/supervised_learning/0x0C-neural_style_transfer/8-neural_style.py

75a2d1e77bbd4d3bcd6a460efacec79a4944e555

[ "MIT" ]

permissive

ledbagholberton/holbertonschool-machine_learning

7672509d2dc1775bd6708430d244e8f4dd4cb169

eaf23423ec0f412f103f5931d6610fdd67bcc5be

refs/heads/master

2020-12-22T01:12:32.824436

2020-10-11T12:36:48

236,623,497

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#!/usr/bin/env python3 """class NST""" import tensorflow as tf import numpy as np tf.enable_eager_execution() class NST: """Class NST""" style_layers = ['block1_conv1', 'block2_conv1', 'block3_conv1', 'block4_conv1', 'block5_conv1'] content_layer = 'block5_conv2' def __init__(self, style_image, content_image, alpha=1e4, beta=1): """ Constructor style_image - the image used as a style reference, stored as a numpy.ndarray content_image - the image used as a content reference, stored as a numpy.ndarray alpha - the weight for content cost beta - the weight for style cost if style_image is not a np.ndarray with the shape (h, w, 3), raise a TypeError with the message 'style_image must be a numpy.ndarray with shape (h, w, 3)' if content_image is not a np.ndarray with the shape (h, w, 3), raise a TypeError with the message 'content_image must be a numpy.ndarray with shape (h, w, 3)' if alpha is not a non-negative number, raise a TypeError with the message 'alpha must be a non-negative number' if beta is not a non-negative number, raise a TypeError with the message 'beta must be a non-negative number' Sets Tensorflow to execute eagerly Sets the instance attributes: style_image - the preprocessed style image content_image - the preprocessed content image alpha - the weight for content cost beta - the weight for style cost""" if (not isinstance(style_image, np.ndarray) or len(style_image.shape) is not 3 or style_image.shape[2] is not 3): m1 = 'style_image must be a numpy.ndarray with shape (h, w, 3)' raise TypeError(m1) if (not isinstance(content_image, np.ndarray) or len(content_image.shape) is not 3 or content_image.shape[2] is not 3): m2 = 'content_image must be a numpy.ndarray with shape (h, w, 3)' raise TypeError(m2) if (alpha < 0): raise TypeError('alpha must be a non-negative number') if (beta < 0): raise TypeError('beta must be a non-negative number') self.style_image = self.scale_image(style_image) self.content_image = self.scale_image(content_image) self.alpha = alpha self.beta = beta self.load_model() self.generate_features() @staticmethod def scale_image(image): """rescales an image such that its pixels values are between 0 and 1 and its largest side is 512 pixels image - a numpy.ndarray of shape (h, w, 3) containing the image to be scaled if image is not a np.ndarray with the shape (h, w, 3), raise a TypeError with the message 'image must be a numpy.ndarray with shape (h, w, 3)' The scaled image should be a tf.tensor with the shape (1, h_new, w_new, 3) where max(h_new, w_new) == 512 and min(h_new, w_new) is scaled proportionately The image should be resized using bicubic interpolation The image’s pixel values should be rescaled from the range [0, 255] to [0, 1] Public class attributes: style_layers = ['block1_conv1', 'block2_conv1', 'block3_conv1', 'block4_conv1', 'block5_conv1'] content_layer = 'block5_conv2' Returns: the scaled image """ if (not isinstance(image, np.ndarray) or len(image.shape) is not 3 or image.shape[2] is not 3): m3 = 'image must be a numpy.ndarray with shape (h, w, 3)' raise TypeError(m3) max_dim = 512 long = max(image.shape[0], image.shape[1]) scale = max_dim/long new_h = round(image.shape[0] * scale) new_w = round(image.shape[1] * scale) image = np.expand_dims(image, axis=0) image = tf.image.resize_bicubic(image, (new_h, new_w)) image = tf.clip_by_value(image / 255, 0, 1) return image def load_model(self): """ loads the model for neural style transfer """ vgg_pre = tf.keras.applications.vgg19.VGG19(include_top=False, weights='imagenet') custom_objects = {'MaxPooling2D': tf.keras.layers.AveragePooling2D} vgg_pre.save("base_model") vgg = tf.keras.models.load_model("base_model", custom_objects=custom_objects) for layer in vgg.layers: layer.trainable = False style_outputs = [vgg.get_layer(name).output for name in self.style_layers] content_output = vgg.get_layer(self.content_layer).output model_outputs = style_outputs + [content_output] self.model = tf.keras.models.Model(vgg.input, model_outputs) @staticmethod def gram_matrix(input_layer): """ Method gram matrix input_layer-instance of tf.Tensor or tf.Variable of shape (1, h, w, c) containing the layer output whose gram matrix should be calculated if input_layer is not an instance of tf.Tensor or tf.Variable rank 4, raise a TypeError with the message input_layer must be a tensor rank 4 Returns: a tf.Tensor of shape (1, c, c) containing the gram matrix of input_layer""" if (not isinstance(input_layer, tf.Tensor) or len(input_layer.shape) != 4): raise TypeError("input_layer must be a tensor of rank 4") channels = int(input_layer.shape[-1]) a = tf.reshape(input_layer, [-1, channels]) n = tf.shape(a)[0] gram = tf.matmul(a, a, transpose_a=True) gram = tf.reshape(gram, shape=[1, -1, channels]) return gram / tf.cast(n, tf.float32) def generate_features(self): """ extracts the features used to calculate neural style cost Sets the public instance attributes: gram_style_features - a list of gram matrices calculated from the style layer outputs of the style image content_feature - the content layer output of the content image Add: model - the Keras model used to calculate cost gram_style_features - a list of gram matrices calculated from the style layer outputs of the style image content_feature - the content layer output of the content image""" num_style_layers = len(self.style_layers) # Load our images in the model VGG. It is necessary to preprocess it content_image = self.content_image style_image = self.style_image # aplico el modelo para cada imagen x = tf.keras.applications.vgg19.preprocess_input(style_image*255) y = tf.keras.applications.vgg19.preprocess_input(content_image*255) model_outputs = self.model(x) + self.model(y) # Adiciono las salidas de los modelos, por que asi son dados self.gram_style_features = [self.gram_matrix(layer) for layer in model_outputs[:num_style_layers]] self.content_feature = model_outputs[-1:] # return(gram_style_features, content_feature) def layer_style_cost(self, style_output, gram_target): """Style cost Calculates the style cost for a single layer style_output - tf.Tensor of shape (1, h, w, c) containing the layer style output of the generated image gram_target - tf.Tensor of shape (1, c, c) the gram matrix of the target style output for that layer if style_output is not an instance of tf.Tensor or tf.Variable of rank 4, raise a TypeError with the message style_output must be a tensor of rank 4 if gram_target is not an instance of tf.Tensor or tf.Variable with shape (1, c, c), raise a TypeError with the message gram_target must be a tensor of shape [1, {c}, {c}] where {c} is the number of channels in style_output Returns: the layer’s style cost""" print("1") """if (not isinstance(style_output, tf.Tensor) or not isinstance(style_output, tf.Variable) or len(style_output.shape) is not 4): raise TypeError("style_output must be a tensor of rank 4")""" channels = style_output.shape[-1] c_gram_0 = gram_target.shape[0] c_gram_1 = gram_target.shape[1] """if (not isinstance(gram_target, (tf.Tensor, tf.Variable)) or len(gram_target.shape) is not 3 or c_gram_0 != c_gram_1 or c_gram_0 != channels): raise TypeError( "gram_target must be a tensor of shape [1, {c}, {c}]")""" gram_style = self.gram_matrix(style_output) return tf.reduce_mean(tf.square(gram_style - gram_target)) def style_cost(self, style_outputs): """Calculates the style cost for generated image style_outputs: a list of tf.Tensor style outputs for the generated image if style_outputs is not a list with the same length as self.style_layers, raise a TypeError with the message style_outputs must be a list with a length of {l} where {l} is the length of self.style_layers each layer should be weighted evenly with all weights summing to 1 Returns: the style cost""" if len(style_outputs) is not len(self.style_layers): raise TypeError( "style_outputs must be a list with a length of {l}") # gram_style_features, content_feature = self.generate_features() weights = 1 / len(style_outputs) style_cost = 0 for layer in range(len(style_outputs)): x = (self.layer_style_cost(style_outputs[layer], self.gram_style_features[layer])) style_cost = style_cost + x * weights return(style_cost) def content_cost(self, content_output): """Calculates the content cost for the generated image content_output - a tf.Tensor containing the content output for the generated image if content_output is not an instance of tf.Tensor or tf.Variable with the same shape as self.content_feature, raise a TypeError with the message content_output must be a tensor of shape {s} where {s} is the shape of self.content_feature Returns: the content cost """ """if not isinstance(content_output, tf.Tensor) or\ content_output.shape is not self.content_feature.shape: raise TypeError("content_output must be a tensor of shape {}" .format(self.content_feature.shape))""" # gram_style_features, content_feature = self.generate_features() return tf.reduce_mean(tf.square(content_output - self.content_feature)) def total_cost(self, generated_image): """Calculates the total cost for the generated image generated_image - a tf.Tensor of shape (1, nh, nw, 3) containing the generated image if generated_image is not an instance of tf.Tensor or tf.Variable with the same shape as self.content_image, raise a TypeError with message generated_image must be a tensor of shape {s} where {s} is the shape of self.content_image Returns: (J, J_content, J_style) J is the total cost J_content is the content cost J_style is the style cost""" """if not isinstance(generated_image, tf.Tensor) or\ generated_image.shape is not self.content_image: raise TypeError("generated_image must be a tensor of shape {}". format(self.content_image.shape))""" """costo total = alpha * cost_content + beta * cost_style cost_content calculado con content_image & generated_image cost_style calculado con style_image & generated_image en todas las capas.""" a = generated_image*255 generated_image = tf.keras.applications.vgg19.preprocess_input(a) model_outputs = self.model(generated_image) content_output = model_outputs[-1] J_content = self.content_cost(content_output) style_outputs = model_outputs[:-1] J_style = self.style_cost(style_outputs) J = self.alpha * J_content + self.beta * J_style return(J, J_content, J_style) def compute_grads(self, generated_image): """ Calculates the gradients for the tf.Tensor generated_image of shape (1, nh, nw, 3) if generated_image is not an instance of tf.Tensor or tf.Variable with the same shape as self.content_image, raise a TypeError with the message generated_image must be a tensor of shape {s} where {s} is the shape of self.content_image Returns: gradients, J_total, J_content, J_style gradients is a tf.Tensor containing the gradients for the generated image J_total is the total cost for the generated image J_content is the content cost for the generated image J_style is the style cost for the generated image """ """if not isinstance(generated_image, tf.Tensor) or\ generated_image.shape is not self.content_image: raise TypeError("generated_image must be a tensor of shape {}". format(self.content_image.shape))""" with tf.GradientTape() as tape: J, J_content, J_style = self.total_cost(generated_image) return(tape.gradient(J, generated_image), J, J_content, J_style)

[ "[email protected]" ]

[email protected]

53c448f8e4e441f92e2aec10e29d9ca24359595a

9e988c0dfbea15cd23a3de860cb0c88c3dcdbd97

/sdBs/AllRun/pg_1412+299/sdB_PG_1412+299_lc.py

1fc949095568bba26e541e43fa821db7addabfb7

[]

no_license

tboudreaux/SummerSTScICode

73b2e5839b10c0bf733808f4316d34be91c5a3bd

4dd1ffbb09e0a599257d21872f9d62b5420028b0

refs/heads/master

2021-01-20T18:07:44.723496

2016-08-08T16:49:53

65,221,159

0

null

UTF-8

Python

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346

py

from gPhoton.gAperture import gAperture def main(): gAperture(band="NUV", skypos=[213.598708,29.684953], stepsz=30., csvfile="/data2/fleming/GPHOTON_OUTPU/LIGHTCURVES/sdBs/sdB_PG_1412+299 /sdB_PG_1412+299_lc.csv", maxgap=1000., overwrite=True, radius=0.00555556, annulus=[0.005972227,0.0103888972], verbose=3) if __name__ == "__main__": main()

[ "[email protected]" ]

[email protected]

91f7b1e95f64d31541ee7a3ad43d81110ac198fd

1d38c549c07f43cc26b7353ef95300b934eeed33

/GUI/Edit/Specy.py

fb03a7097cd0a7523d4349c7642606a3422113c2

[]

no_license

pooyagheyami/Adel3

a6354fbc5aa56a9c38a8b724c8d22bea689380a1

29e257e19fd6914de0e60c303871321e457a858b

refs/heads/master

2022-11-07T21:53:13.958369

2020-06-12T13:22:55

271,803,177

0

null

UTF-8

Python

false

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# -*- coding: utf-8 -*- ########################################################################### ## Python code generated with wxFormBuilder (version Jun 17 2015) ## http://www.wxformbuilder.org/ ## ## PLEASE DO "NOT" EDIT THIS FILE! ########################################################################### import wx import wx.xrc import wx.grid import Database.MDataGet as DG ########################################################################### ## Class MyPanel2 ########################################################################### class MyPanel2 ( wx.Panel ): def __init__( self, parent , txts , ccod ,stit): wx.Panel.__init__ ( self, parent, id = wx.ID_ANY, pos = wx.DefaultPosition, size = wx.Size( 273,256 ), style = wx.TAB_TRAVERSAL ) self.SetLayoutDirection(2) self.ccod = ccod #print self.ccod #print stit self.iData = DG.GetData(u'',u'') self.itits = self.iData.gTitel(stit) self.ispec = self.iData.gSpcy(self.ccod) self.row = len(self.itits) Vsz1 = wx.BoxSizer( wx.VERTICAL ) Hsz1 = wx.BoxSizer( wx.HORIZONTAL ) self.txt1 = wx.StaticText( self, wx.ID_ANY, txts[0], wx.DefaultPosition, wx.DefaultSize, 0 ) self.txt1.Wrap( -1 ) Hsz1.Add( self.txt1, 0, wx.ALL|wx.ALIGN_CENTER_VERTICAL, 5 ) self.fld1 = wx.TextCtrl( self, wx.ID_ANY, txts[1], wx.DefaultPosition, wx.DefaultSize, 0 ) Hsz1.Add( self.fld1, 1, wx.ALL|wx.ALIGN_CENTER_VERTICAL, 5 ) Vsz1.Add( Hsz1, 0, wx.EXPAND, 5 ) Hsz2 = wx.BoxSizer( wx.HORIZONTAL ) self.grid1 = wx.grid.Grid( self, wx.ID_ANY, wx.DefaultPosition, wx.DefaultSize, wx.STATIC_BORDER ) # Grid self.grid1.CreateGrid( self.row, 2 ) self.grid1.EnableEditing( True ) self.grid1.EnableGridLines( True ) self.grid1.EnableDragGridSize( False ) self.grid1.SetMargins( 0, 0 ) # Columns self.grid1.SetColSize( 0, 99 ) self.grid1.SetColSize( 1, 134 ) self.grid1.EnableDragColMove( False ) self.grid1.EnableDragColSize( True ) self.grid1.SetColLabelSize( 30 ) self.grid1.SetColLabelValue( 0, u"عنوان" ) self.grid1.SetColLabelValue( 1, u"مشخصه" ) self.grid1.SetColLabelAlignment( wx.ALIGN_CENTRE, wx.ALIGN_CENTRE ) # Rows self.grid1.EnableDragRowSize( True ) self.grid1.SetRowLabelSize( 19 ) self.grid1.SetRowLabelAlignment( wx.ALIGN_CENTRE, wx.ALIGN_CENTRE ) # Label Appearance # Cell Defaults self.grid1.SetDefaultCellAlignment( wx.ALIGN_LEFT, wx.ALIGN_TOP ) Hsz2.Add( self.grid1, 1, wx.ALL|wx.ALIGN_CENTER_VERTICAL|wx.EXPAND, 5 ) Vsz1.Add( Hsz2, 1, wx.EXPAND|wx.ALIGN_CENTER_HORIZONTAL, 5 ) Hsz3 = wx.BoxSizer( wx.HORIZONTAL ) self.btn1 = wx.Button( self, wx.ID_ANY, u"انصراف", wx.DefaultPosition, wx.DefaultSize, 0 ) Hsz3.Add( self.btn1, 0, wx.ALL|wx.ALIGN_CENTER_VERTICAL, 5 ) self.btn2 = wx.Button( self, wx.ID_ANY, u"ثبت شود", wx.DefaultPosition, wx.DefaultSize, 0 ) Hsz3.Add( self.btn2, 0, wx.ALL, 5 ) Vsz1.Add( Hsz3, 0, wx.ALIGN_CENTER_HORIZONTAL, 5 ) #self.iData = DG.GetData(u'',u'') #self.itits = self.iData.gTitel(stit) #self.ispec = self.iData.gSpcy(self.ccod) self.lodtit() self.SetSizer( Vsz1 ) self.Layout() self.svit = False # Connect Events self.btn1.Bind( wx.EVT_BUTTON, self.cancl ) self.btn2.Bind( wx.EVT_BUTTON, self.aplyit ) def __del__( self ): pass # Virtual event handlers, overide them in your derived class def cancl( self, event ): self.svit = False q = self.GetParent() q.Close() def aplyit( self, event ): self.svit = True #self.sData = DG.SetData(u'',u'') #idata = self.gettit() #print idata #self.savtit(idata,self.sData) q = self.GetParent() q.Close() def lodtit(self): j = 0 for t in self.itits: self.grid1.SetCellValue(j,0,t[0]) for s in self.ispec: if s[1] in t: self.grid1.SetCellValue(j,1,s[0]) j = j + 1 def gettit(self): self.spcy = [] for i in range(len(self.itits)): ispc = self.grid1.GetCellValue(i,1) if ispc != '': self.spcy.append((self.ccod,self.itits[i][1],ispc)) #print self.itits[i][1] #print self.spcy return self.spcy def RetRev(self): return self.svit

[ "[email protected]" ]

[email protected]

8ad7331a5f260ccc92a6d41401ca560c66646425

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/devel/lib/python2.7/dist-packages/pose_graph_msgs/msg/__init__.py

6847bed2af0e51e2757b804411e0db73023f67d1

[]

no_license

rishabhgks/quad_ws

723a95ccc825ddb13f2e27fb9e220cc7b03db6db

19f7a57a585ca9799b3fd11f5b80d894c5b88167

refs/heads/master

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112

py

from ._KeyedScan import * from ._PoseGraph import * from ._PoseGraphEdge import * from ._PoseGraphNode import *

[ "[email protected]" ]

[email protected]

41f673888cfffe4c1aa80b2a5a347f7f943800df

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/topic_02_syntax/examples/isdigit_isnumeric_isdecimal.py

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no_license

ryndovaira/leveluppythonlevel1_300321

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refs/heads/master

2023-06-06T07:44:15.157913

2021-06-18T11:53:35

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def check_str(my_str): print(f"mystr: {my_str}") print(f"isnumeric: {str.isnumeric(my_str)}") print(f"isdigit: {str.isdigit(my_str)}") print(f"isdecimal: {str.isdecimal(my_str)}") print("-" * 50) # isdecimal() ⊆ isdigit() ⊆ isnumeric() if __name__ == '__main__': check_str('½') check_str('ⅠⅢⅧ') check_str('⑩⑬㊿') check_str('³') check_str('🄀⒊⒏') check_str('⓪③⑧') check_str('038') check_str('０３８') # FULLWIDTH DIGIT check_str('٠١٢٣٤') # ARABIC-INDIC DIGIT check_str('-38') check_str('+38') check_str('3_8')

[ "[email protected]" ]

[email protected]

2f3807cf8f62e47c63a60a47b092def214c58a97

524756e5e03465584dcb2d04b8092fbe8840448a

/users/signals.py

61f3f6acbaa87c5bbd5887d4336cc27d40a10557

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permissive

areebbeigh/greenspace-demo

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refs/heads/master

2022-10-11T05:45:05.036097

2020-06-11T11:04:12

2020-06-11T11:41:38

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import sys from django.conf import settings def create_groups(sender, **kwargs): from django.contrib.auth.models import Group group, created = Group.objects.get_or_create(name=settings.NURSERY_MGR_GROUP) print('Created new nursery group' if created else 'Nursery group already exists')

[ "[email protected]" ]

[email protected]

9ab1dae85e9196df975840e6c6d4551650fb7216

3adec884f06eabfe50d4ab3456123e04d02b02ff

/148. Sort List.py

a2e8d101bc501c111c899032f45427524ee85d4f

[]

no_license

windmzx/pyleetcode

c57ecb855c8e560dd32cf7cf14616be2f91ba50e

d0a1cb895e1604fcf70a73ea1c4b1e6b283e3400

refs/heads/master

2022-10-05T17:51:08.394112

2020-06-09T09:24:28

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1,486

py

# Definition for singly-linked list. class ListNode: def __init__(self, x): self.val = x self.next = None class Solution: def sortList(self, head: ListNode) -> ListNode: def split(head): if head.next == None: return head p =head q=head while q != None and q.next != None: temp=p p=p.next q=q.next.next temp.next = None l=split(head) r=split(p) return merge(l,r) def merge(l1,l2): head=ListNode(-1) cur=head while l1!=None and l2!=None: if l1.val<l2.val: cur.next=l1 l1=l1.next cur=cur.next else: cur.next=l2 l2=l2.next cur=cur.next if l1!=None: cur.next=l1 if l2!=None: cur.next=l2 return head.next if head is None: return None return split(head) if __name__ == "__main__": x=Solution() li=ListNode(3) p=li p.next=ListNode(1) p=p.next p.next=ListNode(4) p=p.next p.next=ListNode(0) p=p.next p.next=ListNode(2) p=p.next p.next=ListNode(5) p=p.next re=x.sortList(li) while re!=None: print(re.val) re=re.next

[ "[email protected]" ]

[email protected]

313e25acc001a41e971e137fbcf6bee9f8d3a909

8e69eee9b474587925e22413717eb82e4b024360

/v1.0.0.test/toontown/minigame/TwoDEnemyMgr.py

2b350c515aa1c976abc5e5490424ee267024aaa9

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permissive

TTOFFLINE-LEAK/ttoffline

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bb0e91704a755d34983e94288d50288e46b68380

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2020-04-17T08:22:55

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from panda3d.core import * from direct.directnotify import DirectNotifyGlobal from direct.showbase.DirectObject import DirectObject from toontown.minigame import ToonBlitzGlobals from toontown.minigame import TwoDEnemy class TwoDEnemyMgr(DirectObject): notify = DirectNotifyGlobal.directNotify.newCategory('TwoDEnemyMgr') def __init__(self, section, enemyList): self.section = section self.enemyList = enemyList self.load() def destroy(self): self.section = None while len(self.enemies): enemy = self.enemies[0] enemy.destroy() self.enemies.remove(enemy) self.enemies = None return def load(self): if len(self.enemyList): self.enemiesNP = NodePath('Enemies') self.enemiesNP.reparentTo(self.section.sectionNP) self.enemies = [] for index in xrange(len(self.enemyList)): enemyId = self.section.getSectionizedId(index) suitAttribs = self.enemyList[index] newEnemy = TwoDEnemy.TwoDEnemy(self, enemyId, suitAttribs) newEnemy.suit.reparentTo(self.enemiesNP) self.enemies.append(newEnemy) def enterPlay(self, elapsedTime): for enemy in self.enemies: enemy.start(elapsedTime) def exitPlay(self): pass def enterPause(self): for enemy in self.enemies: enemy.enterPause() def exitPause(self): for enemy in self.enemies: enemy.exitPause()

[ "[email protected]" ]

[email protected]

10e3f86ff0569d076876a2d1d0c9d815c172bf83

811bf15a5bad488284300b6016c8b77f1e2daf24

/rllib/core/testing/tf/bc_module.py

cca3a42f4eeb2f0f78c637b944e16f7057e4c21d

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permissive

justinwyang/ray

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6c356296a01ebf3d8ad0cab6058fb8c03ccbf8f6

refs/heads/master

2023-04-28T15:57:24.167579

2023-04-22T08:28:06

172,777,393

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Apache-2.0

2020-12-04T02:39:57

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Python

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import tensorflow as tf import tensorflow_probability as tfp from typing import Any, Mapping from ray.rllib.core.rl_module.rl_module import RLModule, RLModuleConfig from ray.rllib.core.rl_module.marl_module import ( MultiAgentRLModule, MultiAgentRLModuleConfig, ) from ray.rllib.core.rl_module.tf.tf_rl_module import TfRLModule from ray.rllib.core.models.specs.typing import SpecType from ray.rllib.policy.sample_batch import SampleBatch from ray.rllib.utils.annotations import override from ray.rllib.utils.nested_dict import NestedDict class DiscreteBCTFModule(TfRLModule): def __init__(self, config: RLModuleConfig) -> None: super().__init__(config) def setup(self): input_dim = self.config.observation_space.shape[0] hidden_dim = self.config.model_config_dict["fcnet_hiddens"][0] output_dim = self.config.action_space.n layers = [] layers.append(tf.keras.Input(shape=(input_dim,))) layers.append(tf.keras.layers.ReLU()) layers.append(tf.keras.layers.Dense(hidden_dim)) layers.append(tf.keras.layers.ReLU()) layers.append(tf.keras.layers.Dense(output_dim)) self.policy = tf.keras.Sequential(layers) self._input_dim = input_dim @override(RLModule) def output_specs_exploration(self) -> SpecType: return ["action_dist"] @override(RLModule) def output_specs_inference(self) -> SpecType: return ["action_dist"] @override(RLModule) def output_specs_train(self) -> SpecType: return ["action_dist"] @override(RLModule) def _forward_inference(self, batch: NestedDict) -> Mapping[str, Any]: obs = batch[SampleBatch.OBS] action_logits = self.policy(obs) action_logits_inference = tf.argmax(action_logits, axis=-1) action_dist = tfp.distributions.Deterministic(action_logits_inference) return {"action_dist": action_dist} @override(RLModule) def _forward_exploration(self, batch: NestedDict) -> Mapping[str, Any]: return self._forward_inference(batch) @override(RLModule) def _forward_train(self, batch: NestedDict) -> Mapping[str, Any]: obs = batch[SampleBatch.OBS] action_logits = self.policy(obs) action_dist = tfp.distributions.Categorical(logits=action_logits) return {"action_dist": action_dist} @override(RLModule) def get_state(self) -> Mapping[str, Any]: return {"policy": self.policy.get_weights()} @override(RLModule) def set_state(self, state: Mapping[str, Any]) -> None: self.policy.set_weights(state["policy"]) class BCTfRLModuleWithSharedGlobalEncoder(TfRLModule): def __init__(self, encoder, local_dim, hidden_dim, action_dim): super().__init__() self.encoder = encoder self.policy_head = tf.keras.Sequential( [ tf.keras.layers.Dense( hidden_dim + local_dim, input_shape=(hidden_dim + local_dim,), activation="relu", ), tf.keras.layers.Dense(hidden_dim, activation="relu"), tf.keras.layers.Dense(action_dim), ] ) @override(RLModule) def _default_input_specs(self): return [("obs", "global"), ("obs", "local")] @override(RLModule) def _forward_inference(self, batch): return self._common_forward(batch) @override(RLModule) def _forward_exploration(self, batch): return self._common_forward(batch) @override(RLModule) def _forward_train(self, batch): return self._common_forward(batch) def _common_forward(self, batch): obs = batch["obs"] global_enc = self.encoder(obs["global"]) policy_in = tf.concat([global_enc, obs["local"]], axis=-1) action_logits = self.policy_head(policy_in) return {"action_dist": tf.distributions.Categorical(logits=action_logits)} class BCTfMultiAgentModuleWithSharedEncoder(MultiAgentRLModule): def __init__(self, config: MultiAgentRLModuleConfig) -> None: super().__init__(config) def setup(self): # constructing the global encoder based on the observation_space of the first # module module_specs = self.config.modules module_spec = next(iter(module_specs.values())) global_dim = module_spec.observation_space["global"].shape[0] hidden_dim = module_spec.model_config_dict["fcnet_hiddens"][0] shared_encoder = tf.keras.Sequential( [ tf.keras.Input(shape=(global_dim,)), tf.keras.layers.ReLU(), tf.keras.layers.Dense(hidden_dim), ] ) for module_id, module_spec in module_specs.items(): self._rl_modules[module_id] = module_spec.module_class( encoder=shared_encoder, local_dim=module_spec.observation_space["local"].shape[0], hidden_dim=hidden_dim, action_dim=module_spec.action_space.n, ) def serialize(self): # TODO (Kourosh): Implement when needed. raise NotImplementedError def deserialize(self, data): # TODO (Kourosh): Implement when needed. raise NotImplementedError

[ "[email protected]" ]

[email protected]

014fc63655d75805b73e1b4f0ca4fe2e2b051844

650b516b1214c4d44fd6f04941e87e28e9049cde

/addons/plugin.video.fanfilm/resources/lib/libraries/cache.py

7d58a18868df7128b7866218d87032edd9459070

[]

no_license

MultiWu/build

b85cc45a33b871f4ade58de8457fcd094761f385

f50a64f674b6499668e0a5758fe0879b016f5c38

refs/heads/master

2022-10-31T20:35:53.382826

2019-12-20T22:50:16

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null

2022-10-07T08:47:18

2019-12-16T19:46:39

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# -*- coding: utf-8 -*- """ Covenant Add-on This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see <http://www.gnu.org/licenses/>. """ import ast import hashlib import re import time from resources.lib.libraries import control try: from sqlite3 import dbapi2 as db, OperationalError except ImportError: from pysqlite2 import dbapi2 as db, OperationalError """ This module is used to get/set cache for every action done in the system """ cache_table = 'cache' def get(function, duration, *args): # type: (function, int, object) -> object or None """ Gets cached value for provided function with optional arguments, or executes and stores the result :param function: Function to be executed :param duration: Duration of validity of cache in hours :param args: Optional arguments for the provided function """ try: key = _hash_function(function, args) cache_result = cache_get(key) if cache_result: if _is_cache_valid(cache_result['date'], duration): return ast.literal_eval(cache_result['value'].encode('utf-8')) fresh_result = repr(function(*args)) if not fresh_result: # If the cache is old, but we didn't get fresh result, return the old cache if cache_result: return cache_result return None cache_insert(key, fresh_result) return ast.literal_eval(fresh_result.encode('utf-8')) except Exception: return None def timeout(function, *args): try: key = _hash_function(function, args) result = cache_get(key) return int(result['date']) except Exception: return None def bennu_download_get(function, timeout, *args, **table): try: response = None f = repr(function) f = re.sub('.+\smethod\s|.+function\s|\sat\s.+|\sof\s.+', '', f) a = hashlib.md5() for i in args: a.update(str(i)) a = str(a.hexdigest()) except: pass try: table = table['table'] except: table = 'rel_list' try: control.makeFile(control.dataPath) dbcon = db.connect(control.cacheFile) dbcur = dbcon.cursor() dbcur.execute("SELECT * FROM %s WHERE func = '%s' AND args = '%s'" % (table, f, a)) match = dbcur.fetchone() response = eval(match[2].encode('utf-8')) t1 = int(match[3]) t2 = int(time.time()) update = (abs(t2 - t1) / 3600) >= int(timeout) if update == False: return response except: pass try: r = function(*args) if (r == None or r == []) and not response == None: return response elif (r == None or r == []): return r except: return try: r = repr(r) t = int(time.time()) dbcur.execute( "CREATE TABLE IF NOT EXISTS %s (""func TEXT, ""args TEXT, ""response TEXT, ""added TEXT, ""UNIQUE(func, args)"");" % table) dbcur.execute("DELETE FROM %s WHERE func = '%s' AND args = '%s'" % (table, f, a)) dbcur.execute("INSERT INTO %s Values (?, ?, ?, ?)" % table, (f, a, r, t)) dbcon.commit() except: pass try: return eval(r.encode('utf-8')) except: pass def cache_get(key): # type: (str, str) -> dict or None try: cursor = _get_connection_cursor() cursor.execute("SELECT * FROM %s WHERE key = ?" % cache_table, [key]) return cursor.fetchone() except OperationalError: return None def cache_insert(key, value): # type: (str, str) -> None cursor = _get_connection_cursor() now = int(time.time()) cursor.execute( "CREATE TABLE IF NOT EXISTS %s (key TEXT, value TEXT, date INTEGER, UNIQUE(key))" % cache_table ) update_result = cursor.execute( "UPDATE %s SET value=?,date=? WHERE key=?" % cache_table, (value, now, key)) if update_result.rowcount is 0: cursor.execute( "INSERT INTO %s Values (?, ?, ?)" % cache_table, (key, value, now) ) cursor.connection.commit() def cache_clear(): try: cursor = _get_connection_cursor() for t in [cache_table, 'rel_list', 'rel_lib']: try: cursor.execute("DROP TABLE IF EXISTS %s" % t) cursor.execute("VACUUM") cursor.commit() except: pass except: pass def cache_clear_meta(): try: cursor = _get_connection_cursor_meta() for t in ['meta']: try: cursor.execute("DROP TABLE IF EXISTS %s" % t) cursor.execute("VACUUM") cursor.commit() except: pass except: pass def cache_clear_providers(): try: cursor = _get_connection_cursor_providers() for t in ['rel_src', 'rel_url']: try: cursor.execute("DROP TABLE IF EXISTS %s" % t) cursor.execute("VACUUM") cursor.commit() except: pass except: pass def cache_clear_search(): try: cursor = _get_connection_cursor_search() for t in ['tvshow', 'movies']: try: cursor.execute("DROP TABLE IF EXISTS %s" % t) cursor.execute("VACUUM") cursor.commit() except: pass except: pass def cache_clear_all(): cache_clear() cache_clear_meta() cache_clear_providers() def _get_connection_cursor(): conn = _get_connection() return conn.cursor() def _get_connection(): control.makeFile(control.dataPath) conn = db.connect(control.cacheFile) conn.row_factory = _dict_factory return conn def _get_connection_cursor_meta(): conn = _get_connection_meta() return conn.cursor() def _get_connection_meta(): control.makeFile(control.dataPath) conn = db.connect(control.metacacheFile) conn.row_factory = _dict_factory return conn def _get_connection_cursor_providers(): conn = _get_connection_providers() return conn.cursor() def _get_connection_providers(): control.makeFile(control.dataPath) conn = db.connect(control.providercacheFile) conn.row_factory = _dict_factory return conn def _get_connection_cursor_search(): conn = _get_connection_search() return conn.cursor() def _get_connection_search(): control.makeFile(control.dataPath) conn = db.connect(control.searchFile) conn.row_factory = _dict_factory return conn def _dict_factory(cursor, row): d = {} for idx, col in enumerate(cursor.description): d[col[0]] = row[idx] return d def _hash_function(function_instance, *args): return _get_function_name(function_instance) + _generate_md5(args) def _get_function_name(function_instance): return re.sub('.+\smethod\s|.+function\s|\sat\s.+|\sof\s.+', '', repr(function_instance)) def _generate_md5(*args): md5_hash = hashlib.md5() [md5_hash.update(str(arg)) for arg in args] return str(md5_hash.hexdigest()) def _is_cache_valid(cached_time, cache_timeout): now = int(time.time()) diff = now - cached_time return (cache_timeout * 3600) > diff def cache_version_check(): if _find_cache_version(): cache_clear(); cache_clear_meta(); cache_clear_providers() control.infoDialog(control.lang(32057).encode('utf-8'), sound=True, icon='INFO') def _find_cache_version(): import os versionFile = os.path.join(control.dataPath, 'cache.v') try: with open(versionFile, 'rb') as fh: oldVersion = fh.read() except: oldVersion = '0' try: curVersion = control.addon('plugin.video.fanfilm').getAddonInfo('version') if oldVersion != curVersion: with open(versionFile, 'wb') as fh: fh.write(curVersion) return True else: return False except: return False

[ "[email protected]" ]

[email protected]

553b046fb1e362b9966b86843cf88a190f17cb17

544be854639d58b111c345a55597b0580e8106d8

/example/admin.py

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no_license

arineto/django-multi-tenant-example

152abde09e5362e0ecaab9402d03aa23228f4bf3

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refs/heads/master

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from django.contrib import admin from .models import Item from multi_tenant.models import Theme from multi_tenant.models import Tenant # Register your models here. admin.site.register(Item) admin.site.register(Theme) admin.site.register(Tenant)

[ "[email protected]" ]

[email protected]

a35078d691fddc504f227125b99e73b18a3a6ad3

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/kate3/logger/admin.py

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from django.contrib import admin from logger.models import Entry class EntryAdmin(admin.ModelAdmin): list_display = ('__unicode__', 'action', 'created_at',) list_filter = ('action', 'created_at',) admin.site.register(Entry, EntryAdmin)

[ "[email protected]" ]

[email protected]

04b264c1c72261ff9d515d75793a43e17fa06c3b

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/mopidy/utils/process.py

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import logging import multiprocessing import multiprocessing.dummy from multiprocessing.reduction import reduce_connection import pickle import gobject gobject.threads_init() from mopidy import SettingsError logger = logging.getLogger('mopidy.utils.process') def pickle_connection(connection): return pickle.dumps(reduce_connection(connection)) def unpickle_connection(pickled_connection): # From http://stackoverflow.com/questions/1446004 (func, args) = pickle.loads(pickled_connection) return func(*args) class BaseProcess(multiprocessing.Process): def __init__(self, core_queue): super(BaseProcess, self).__init__() self.core_queue = core_queue def run(self): logger.debug(u'%s: Starting process', self.name) try: self.run_inside_try() except KeyboardInterrupt: logger.info(u'Interrupted by user') self.exit(0, u'Interrupted by user') except SettingsError as e: logger.error(e.message) self.exit(1, u'Settings error') except ImportError as e: logger.error(e) self.exit(2, u'Import error') except Exception as e: logger.exception(e) self.exit(3, u'Unknown error') def run_inside_try(self): raise NotImplementedError def destroy(self): self.terminate() def exit(self, status=0, reason=None): self.core_queue.put({'to': 'core', 'command': 'exit', 'status': status, 'reason': reason}) self.destroy() class BaseThread(multiprocessing.dummy.Process): def __init__(self, core_queue): super(BaseThread, self).__init__() self.core_queue = core_queue # No thread should block process from exiting self.daemon = True def run(self): logger.debug(u'%s: Starting thread', self.name) try: self.run_inside_try() except KeyboardInterrupt: logger.info(u'Interrupted by user') self.exit(0, u'Interrupted by user') except SettingsError as e: logger.error(e.message) self.exit(1, u'Settings error') except ImportError as e: logger.error(e) self.exit(2, u'Import error') except Exception as e: logger.exception(e) self.exit(3, u'Unknown error') def run_inside_try(self): raise NotImplementedError def destroy(self): pass def exit(self, status=0, reason=None): self.core_queue.put({'to': 'core', 'command': 'exit', 'status': status, 'reason': reason}) self.destroy() class GObjectEventThread(BaseThread): """ A GObject event loop which is shared by all Mopidy components that uses libraries that need a GObject event loop, like GStreamer and D-Bus. Should be started by Mopidy's core and used by :mod:`mopidy.output.gstreamer`, :mod:`mopidy.frontend.mpris`, etc. """ def __init__(self, core_queue): super(GObjectEventThread, self).__init__(core_queue) self.name = u'GObjectEventThread' self.loop = None def run_inside_try(self): self.loop = gobject.MainLoop().run() def destroy(self): self.loop.quit() super(GObjectEventThread, self).destroy()

[ "[email protected]" ]

[email protected]

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/OpenGLCffi/EGL/EXT/EXT/stream_consumer_egloutput.py

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from OpenGLCffi.EGL import params @params(api='egl', prms=['dpy', 'stream', 'layer']) def eglStreamConsumerOutputEXT(dpy, stream, layer): pass

[ "[email protected]" ]

[email protected]

fdd1c5c9ed081efbfccfd7332b2d1dc9d7131567

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Code-Institute-Submissions/renanclothestore

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""" Django settings for carapp project. Generated by 'django-admin startproject' using Django 1.11.13. For more information on this file, see https://docs.djangoproject.com/en/1.11/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/1.11/ref/settings/ """ import os # Build paths inside the project like this: os.path.join(BASE_DIR, ...) BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/1.11/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = 'rwl@k11m(xzyh+&^6=#k36hkev0)7s14n1mi7j6$!a9d7o$dh%' ALLOWED_HOSTS = ["renanclothestore.herokuapp.com", "127.0.0.1", "localhost"] SITE_ID = 4 # Application definition INSTALLED_APPS = [ 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django_forms_bootstrap', 'paypal.standard.ipn', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', 'django.contrib.sites', 'django.contrib.flatpages', 'carstore.apps.CarstoreConfig', 'accounts', 'paypal_store', 'products', ] AUTHENTICATION_BACKENDS = ( 'django.contrib.auth.backends.ModelBackend', 'accounts.backends.EmailAuth', ) LOGIN_URL = '/login/' MIDDLEWARE = [ 'django.middleware.security.SecurityMiddleware', 'whitenoise.middleware.WhiteNoiseMiddleware', 'django.contrib.sessions.middleware.SessionMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware', 'django.middleware.security.SecurityMiddleware', 'django.contrib.flatpages.middleware.FlatpageFallbackMiddleware', ] ROOT_URLCONF = 'carapp.urls' AUTH_USER_MODEL = 'accounts.User' TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [os.path.join(BASE_DIR, 'templates')], 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', ], }, }, ] WSGI_APPLICATION = 'carapp.wsgi.application' # Password validation # https://docs.djangoproject.com/en/1.11/ref/settings/#auth-password-validators AUTH_PASSWORD_VALIDATORS = [ { 'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator', }, { 'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator', }, { 'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator', }, { 'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator', }, ] # Internationalization # https://docs.djangoproject.com/en/1.11/topics/i18n/ LANGUAGE_CODE = 'en-us' TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/1.11/howto/static-files/ STATIC_URL = '/static/' STATIC_ROOT = os.path.join(BASE_DIR, 'staticfiles') STATICFILES_DIRS = ( os.path.join(BASE_DIR, "static"), ) MEDIA_ROOT = os.path.join(BASE_DIR, 'media') MEDIA_URL = '/media/'

[ "[email protected]" ]

[email protected]

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DayGitH/Python-Challenges

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""" [05/30/13] Challenge #126 [Intermediate] Perfect P'th Powers https://www.reddit.com/r/dailyprogrammer/comments/1fcpnx/053013_challenge_126_intermediate_perfect_pth/ # [](#IntermediateIcon) *(Intermediate)*: Perfect P'th Powers An integer X is a "perfect square power" if there is some integer Y such that Y^2 = X. An integer X is a "perfect cube power" if there is some integer Y such that Y^3 = X. We can extrapolate this where P is the power in question: an integer X is a "perfect p'th power" if there is some integer Y such that Y^P = X. Your goal is to find the highest value of P for a given X such that for some unknown integer Y, Y^P should equal X. You can expect the given input integer X to be within the range of an unsigned 32-bit integer (0 to 4,294,967,295). *Special thanks to the ACM collegiate programming challenges group for giving me the initial idea [here](http://uva.onlinejudge.org/index.php?option=onlinejudge&page=show_problem&problem=1563).* # Formal Inputs & Outputs ## Input Description You will be given a single integer on a single line of text through standard console input. This integer will range from 0 to 4,294,967,295 (the limits of a 32-bit unsigned integer). ## Output Description You must print out to standard console the highest value P that fits the above problem description's requirements. # Sample Inputs & Outputs ## Sample Input *Note:* These are all considered separate input examples. 17 1073741824 25 ## Sample Output *Note:* The string following the result are notes to help with understanding the example; it is NOT expected of you to write this out. 1 (17^1) 30 (2^30) 2 (5^2) """ def main(): pass if __name__ == "__main__": main()

[ "[email protected]" ]

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/rttl.py

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# http://www.pymcu.com/PlayingSounds.html # rttl.py version 1.0.1 (ported version to pyS60) # import e32 import pitchy # RTTL variable to hold RTTL song #RTTL = 'Bond:d=4,o=5,b=50:32p,16c#6,32d#6,32d#6,16d#6,8d#6,16c#6,16c#6,16c#6,16c#6,32e6,32e6,16e6,8e6,16d#6,16d#6,16d#6,16c#6,32d#6,32d#6,16d#6,8d#6,16c#6,16c#6,16c#6,16c#6,32e6,32e6,16e6,8e6,16d#6,16d6,16c#6,16c#7,c.7,16g#6,16f#6,g#.6' # A Dictionary that contains the frequencies for each note noteFreq = {'p':0,'a':3520,'a#':3729,'b':3951,'c':4186,'c#':4435,'d':4699,'d#':4978,'e':5274,'f':5588,'f#':5920,'g':6272,'g#':6645} # This function will return the default Duration, Octave, and BeatsPerMinute from the RTTL data def dob(dobData): dobVals = dobData.split(',') defaultDur = int(dobVals[0].split('=')[1]) defaultOct = int(dobVals[1].split('=')[1]) defaultBeats = int(dobVals[2].split('=')[1]) return defaultDur, defaultOct, defaultBeats # This function will return the duration per note from the RTTL note data def durSplit(noteData): for d in noteData: if ord(d) >= 97 and ord(d) <= 122: durSplit = noteData.split(d) if len(durSplit[0]) > 0: return int(durSplit[0]) return 0 # This function will return just the note for dictionary look up from the RTTL note data def noteSplit(noteData): note = '' hasDot = False for d in noteData: if ord(d) >= 97 and ord(d) <= 122: note += d if ord(d) == 35: note += d if ord(d) == 46: hasDot = True return note, hasDot # This function will return per note octave changes if specified in the RTTL note data def noteOctave(noteData): if noteData[len(noteData)-1] >= 53 and noteData[len(noteData)-1] <= 56: return 8 - int(noteData[len(noteData)-1]) else: return None def get_song_name(noktune): rttlParts = noktune.split(':') # Split the RTTL song data into it's 3 core parts return rttlParts[0] # Song Name def get_duration(noktune): rttlParts = noktune.split(':') # Split the RTTL song data into it's 3 core parts dobVals = (rttlParts[1]).split(',') defaultDur = int(dobVals[0].split('=')[1]) return defaultDur def get_octave(noktune): rttlParts = noktune.split(':') # Split the RTTL song data into it's 3 core parts dobVals = (rttlParts[1]).split(',') defaultOct = iint(dobVals[1].split('=')[1]) return defaultOct def get_bpm(noktune): rttlParts = noktune.split(':') # Split the RTTL song data into it's 3 core parts dobVals = (rttlParts[1]).split(',') defaultBeats = int(dobVals[2].split('=')[1]) return defaultBeats def play_noktune(noktune,vol): global noteFreq tune=[] rttlParts = noktune.split(':') # Split the RTTL song data into it's 3 core parts defaultDur, defaultOct, defaultBeats = dob(rttlParts[1]) # Get default Duration, Octave, and Beats Per Minute rttlNotes = rttlParts[2].split(',') # Split all the note data into a list for note in rttlNotes: # Iterate through the note list note = note.strip() # Strip out any possible pre or post spaces in the note data durVal = durSplit(note) # Determine the per note duration if not default if durVal == 0: # If there is no per note duration then use default for that note durVal = defaultDur duration = 60000 / defaultBeats / durVal * 3 # Calculate the proper duration based on Beats Per Minute and Duration Value noteStr, hasDot = noteSplit(note) # Get note for dictionary lookup and check if the note has a dot nFreq = noteFreq[noteStr] # Look up note frequency from the dictionary if hasDot == True: # if it has a dot calculate the new duration duration *= 3 / 2 octave = noteOctave(note) # Determine if there is per note octave change if octave != None: # if so calculate the new octave frequency nFreq /= octave else: # else use the default octave frequency nFreq /= defaultOct if nFreq == 0: # if nFreq is 0 then it's a pause note so pause for the required time e32.ao_sleep(float(duration / 1000.0)) else: # else play the note from the song tune.append((nFreq,duration,vol)) pitchy.play_list(tune) #play_noktune('Bond:d=4,o=5,b=50:32p,16c#6,32d#6,32d#6,16d#6,8d#6,16c#6,16c#6,16c#6,16c#6,32e6,32e6,16e6,8e6,16d#6,16d#6,16d#6,16c#6,32d#6,32d#6,16d#6,8d#6,16c#6,16c#6,16c#6,16c#6,32e6,32e6,16e6,8e6,16d#6,16d6,16c#6,16c#7,c.7,16g#6,16f#6,g#.6',3)

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#coding=UTF-8 import MySQLdb,sys,string,time,datetime,uuid,pymongo,json # from django.contrib.auth.models import User from accounts.models import UserInfo from dbmanage.myapp.models import Db_name,Db_account,Db_instance from django.conf import settings from django.core.serializers.json import DjangoJSONEncoder from dbmanage.myapp.include.encrypt import prpcrypt public_user = settings.PUBLIC_USER export_limit = int(settings.EXPORT_LIMIT) def get_mongodb_list(username,tag='tag',search=''): dbtype='mongodb' host_list = [] if len(search) ==0: if (tag=='tag'): a = UserInfo.objects.get(username=username) #如果没有对应role='read'或者role='all'的account账号，则不显示在下拉菜单中 for row in a.db_name_set.all().order_by("dbtag"): if row.db_account_set.all().filter(role__in=['read','all']): if row.instance.all().filter(role__in=['read','all']).filter(db_type=dbtype): host_list.append(row.dbtag) elif (tag=='log'): for row in Db_name.objects.values('dbtag').distinct().order_by("dbtag"): host_list.append(row['dbtag']) elif (tag=='exec'): a = UserInfo.objects.get(username=username) #如果没有对应role='write'或者role='all'的account账号，则不显示在下拉菜单中 for row in a.db_name_set.all().order_by("dbtag"): if row.db_account_set.all().filter(role__in=['write','all']): #排除只读实例 if row.instance.all().filter(role__in=['write','all']).filter(db_type=dbtype): host_list.append(row.dbtag) elif len(search) > 0: if (tag=='tag'): a = UserInfo.objects.get(username=username) #如果没有对应role='read'或者role='all'的account账号，则不显示在下拉菜单中 for row in a.db_name_set.filter(dbname__contains=search).order_by("dbtag"): if row.db_account_set.all().filter(role__in=['read','all']): if row.instance.all().filter(role__in=['read','all']).filter(db_type=dbtype): host_list.append(row.dbtag) elif (tag=='log'): for row in Db_name.objects.values('dbtag').distinct().order_by("dbtag"): host_list.append(row['dbtag']) elif (tag=='exec'): a = UserInfo.objects.get(username=username) #如果没有对应role='write'或者role='all'的account账号，则不显示在下拉菜单中 for row in a.db_name_set.filter(dbname__contains=search).order_by("dbtag"): if row.db_account_set.all().filter(role__in=['write','all']): #排除只读实例 if row.instance.all().filter(role__in=['write','all']).filter(db_type=dbtype): host_list.append(row.dbtag) return host_list def get_mongo_coninfo(hosttag,useraccount): a = Db_name.objects.filter(dbtag=hosttag)[0] # a = Db_name.objects.get(dbtag=hosttag) tar_dbname = a.dbname try: if a.instance.all().filter(role='read')[0]: tar_host = a.instance.all().filter(role='read')[0].ip tar_port = a.instance.all().filter(role='read')[0].port # 如果没有设置或没有role=read，则选择第一个读到的all实例读取 except Exception, e: tar_host = a.instance.filter(role='all')[0].ip tar_port = a.instance.filter(role='all')[0].port # tar_host = a.instance.all()[0].ip # tar_port = a.instance.all()[0].port for i in a.db_account_set.all(): if i.role != 'write' and i.role != 'admin': # find the specified account for the user if i.account.all().filter(username=useraccount): tar_username = i.user tar_passwd = i.passwd break # not find specified account for the user ,specified the public account to the user if not vars().has_key('tar_username'): for i in a.db_account_set.all(): if i.role != 'write' and i.role != 'admin': # find the specified account for the user if i.account.all().filter(username=public_user): tar_username = i.user tar_passwd = i.passwd break pc = prpcrypt() return tar_host,tar_port,tar_username,pc.decrypt(tar_passwd),tar_dbname def get_db_info(hosttag,useraccount): tar_host, tar_port, tar_username, tar_passwd, tar_dbname = get_mongo_coninfo(hosttag, useraccount) connect = pymongo.MongoClient(tar_host, int(tar_port)) db = connect[tar_dbname] try: db.authenticate(tar_username, tar_passwd) except Exception, e: pass results = db.command({'dbstats': 1}) return results def get_tb_info(hosttag,tbname,useraccount): tar_host, tar_port, tar_username, tar_passwd, tar_dbname = get_mongo_coninfo(hosttag, useraccount) connect = pymongo.MongoClient(tar_host, int(tar_port)) db = connect[tar_dbname] try: db.authenticate(tar_username, tar_passwd) except Exception, e: pass results = db.command({'collstats': tbname}) return results def get_tbindex_info(hosttag,tbname,useraccount): tar_host, tar_port, tar_username, tar_passwd, tar_dbname = get_mongo_coninfo(hosttag, useraccount) connect = pymongo.MongoClient(tar_host, int(tar_port)) db = connect[tar_dbname] try: db.authenticate(tar_username, tar_passwd) except Exception, e: pass collection = db[tbname] results = collection.index_information() return results def get_mongo_collection(hosttag,useraccount): try: tar_host, tar_port, tar_username, tar_passwd, tar_dbname = get_mongo_coninfo(hosttag, useraccount) # 此处根据tablename获取其他信息 connect = pymongo.MongoClient(tar_host, int(tar_port)) db = connect[tar_dbname] try: db.authenticate(tar_username, tar_passwd) except Exception, e: pass results = db.collection_names() except Exception, e: results,col = ([str(e)],''),['error'] return results def get_mongo_data(b,hosttag,tbname,useraccount): try: num = int(UserInfo.objects.get(username=useraccount).user_profile.export_limit) except Exception, e: num = export_limit try: tar_host, tar_port, tar_username, tar_passwd, tar_dbname = get_mongo_coninfo(hosttag, useraccount) #此处根据tablename获取其他信息 connect = pymongo.MongoClient(tar_host,int(tar_port)) db=connect[tar_dbname] try: db.authenticate(tar_username,tar_passwd) except Exception,e: pass #tablename = tablename collection = db[tbname] #a = '''{'currTime': 1477371861706}''' resulta = collection.find(eval(b),{"_id":0}).limit(num) # resulta = collection.find().limit(20) #results = db.collection_names() #获取所有tables名字 results = [] for recordjson in resulta: #resultdict = {} #for k,v in recordjson: # resultdict[k] = v.encode('gb18030') #["ObjectId('580ee6e6f3de9821b20e57db') is not JSON serializable"] results.append(json.dumps(recordjson,ensure_ascii=False,cls=DjangoJSONEncoder)) #results.append(recordjson) except Exception, e: results = (['error'],'') return results if __name__ == '__main__': #x="insert /*sdfs*/into mysql.test ;truncate table mysql.db;rename mysql.db ;rename asdf;delete from `msql`.sa set ;delete ignore from t1 mysql.test values sdasdf;insert into ysql.user values()" # print x #x=" /*! */; select /**/ #asdfasdf; \nfrom mysql_replication_history;" #x = " insert into item_infor (id,name) values(7,'t\\'e\"st');drop t * from test;" print get_mongo_data('{"_class" : "com.mongodb.BasicDBObject"}','mongodb-easemob','message','root')

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/Ass/3/gameDemo/gd_fucks/alien.py

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[]

no_license

zubairabid/ITWS2

3f0608835e79725f88fd1658b40a65f1a4a2ef47

4703aba0ada3b0a0a165155ba1177420a110decf

refs/heads/master

2021-03-27T12:47:17.522346

2018-04-15T00:11:43

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import globalset as gs class Alien: def __init__(self, x, y): self.txt = gs.alien self.x = x self.y = y self.life = gs.ALIEN_LIFE def update(self, sess): self.life -= gs.CLOCK_CYCLE if(self.life <= 0): self.remove(sess) def remove(self, sess): if(self in sess.alist): # c = 0 # for t in sess.alist: # if(self == t): # sess.alist.remove(c) # break # c += 1 sess.alist.remove(self) sess.screen[self.x][self.y] = None

[ "[email protected]" ]

[email protected]

a5a8886cd1b54a2f799c66975c4821c04172df57

6533c515c936d999c4bd8192d03d01c56172940c

/wlauto/commands/run.py

c5432efe274167162fcfca1b1422e0f8c06fc751

[ "LicenseRef-scancode-unknown-license-reference", "Apache-2.0" ]

permissive

caogao/workload-automation

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44a49db04da3224003f16bf82db0dc309422b710

refs/heads/master

2021-01-15T11:07:01.869199

2016-04-15T15:39:24

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# Copyright 2014-2015 ARM Limited # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # import os import sys import shutil import wlauto from wlauto import Command, settings from wlauto.exceptions import ConfigError from wlauto.core.agenda import Agenda from wlauto.core.execution import Executor from wlauto.utils.log import add_log_file class RunCommand(Command): name = 'run' description = 'Execute automated workloads on a remote device and process the resulting output.' def initialize(self, context): self.parser.add_argument('agenda', metavar='AGENDA', help=""" Agenda for this workload automation run. This defines which workloads will be executed, how many times, with which tunables, etc. See example agendas in {} for an example of how this file should be structured. """.format(os.path.dirname(wlauto.__file__))) self.parser.add_argument('-d', '--output-directory', metavar='DIR', default=None, help=""" Specify a directory where the output will be generated. If the directory already exists, the script will abort unless -f option (see below) is used, in which case the contents of the directory will be overwritten. If this option is not specified, then {} will be used instead. """.format(settings.output_directory)) self.parser.add_argument('-f', '--force', action='store_true', help=""" Overwrite output directory if it exists. By default, the script will abort in this situation to prevent accidental data loss. """) self.parser.add_argument('-i', '--id', action='append', dest='only_run_ids', metavar='ID', help=""" Specify a workload spec ID from an agenda to run. If this is specified, only that particular spec will be run, and other workloads in the agenda will be ignored. This option may be used to specify multiple IDs. """) self.parser.add_argument('--disable', action='append', dest='instruments_to_disable', metavar='INSTRUMENT', help=""" Specify an instrument to disable from the command line. This equivalent to adding "~{metavar}" to the instrumentation list in the agenda. This can be used to temporarily disable a troublesome instrument for a particular run without introducing permanent change to the config (which one might then forget to revert). This option may be specified multiple times. """) def execute(self, args): # NOQA self.set_up_output_directory(args) add_log_file(settings.log_file) if os.path.isfile(args.agenda): agenda = Agenda(args.agenda) settings.agenda = args.agenda shutil.copy(args.agenda, settings.meta_directory) elif '.' in args.agenda or os.sep in args.agenda: raise ConfigError('Agenda "{}" does not exist.'.format(args.agenda)) else: self.logger.debug('{} is not a file; assuming workload name.'.format(args.agenda)) agenda = Agenda() agenda.add_workload_entry(args.agenda) if args.instruments_to_disable: if 'instrumentation' not in agenda.config: agenda.config['instrumentation'] = [] for itd in args.instruments_to_disable: self.logger.debug('Updating agenda to disable {}'.format(itd)) agenda.config['instrumentation'].append('~{}'.format(itd)) basename = 'config_' for file_number, path in enumerate(settings.get_config_paths(), 1): file_ext = os.path.splitext(path)[1] shutil.copy(path, os.path.join(settings.meta_directory, basename + str(file_number) + file_ext)) executor = Executor() executor.execute(agenda, selectors={'ids': args.only_run_ids}) def set_up_output_directory(self, args): if args.output_directory: settings.output_directory = args.output_directory self.logger.debug('Using output directory: {}'.format(settings.output_directory)) if os.path.exists(settings.output_directory): if args.force: self.logger.info('Removing existing output directory.') shutil.rmtree(settings.output_directory) else: self.logger.error('Output directory {} exists.'.format(settings.output_directory)) self.logger.error('Please specify another location, or use -f option to overwrite.\n') sys.exit(1) self.logger.info('Creating output directory.') os.makedirs(settings.output_directory) os.makedirs(settings.meta_directory)

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