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mbakker7/timml
timml/equation.py
https://github.com/mbakker7/timml/blob/91e99ad573cb8a9ad8ac1fa041c3ca44520c2390/timml/equation.py#L250-L273
def equation(self): """Mix-in class that returns matrix rows for difference in head between inside and outside equals zeros Returns matrix part (nunknowns,neq) Returns rhs part nunknowns """ mat = np.empty((self.nunknowns, self.model.neq)) rhs = np.zeros(self.nunknowns) # Needs to be initialized to zero for icp in range(self.ncp): istart = icp * self.nlayers ieq = 0 for e in self.model.elementlist: if e.nunknowns > 0: qxin, qyin = e.disvecinflayers(self.xcin[icp], self.ycin[icp], self.layers, aq=self.aqin) qxout, qyout = e.disvecinflayers(self.xcout[icp], self.ycout[icp], self.layers, aq=self.aqout) mat[istart:istart + self.nlayers, ieq:ieq + e.nunknowns] = \ (qxin - qxout) * self.cosnorm[icp] + (qyin - qyout) * self.sinnorm[icp] ieq += e.nunknowns else: qxin, qyin = e.disveclayers(self.xcin[icp], self.ycin[icp], self.layers, aq=self.aqin) qxout, qyout = e.disveclayers(self.xcout[icp], self.ycout[icp], self.layers, aq=self.aqout) rhs[istart:istart + self.nlayers] -= (qxin - qxout) * self.cosnorm[icp] + (qyin - qyout) * \ self.sinnorm[icp] return mat, rhs
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python
train
spdx/tools-python
spdx/parsers/tagvalue.py
https://github.com/spdx/tools-python/blob/301d72f6ae57c832c1da7f6402fa49b192de6810/spdx/parsers/tagvalue.py#L245-L250
def p_extr_lic_name_value_1(self, p): """extr_lic_name_value : LINE""" if six.PY2: p[0] = p[1].decode(encoding='utf-8') else: p[0] = p[1]
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extr_lic_name_value : LINE
[ "extr_lic_name_value", ":", "LINE" ]
python
valid
pauleveritt/kaybee
kaybee/plugins/articles/image_type.py
https://github.com/pauleveritt/kaybee/blob/a00a718aaaa23b2d12db30dfacb6b2b6ec84459c/kaybee/plugins/articles/image_type.py#L37-L61
def env_updated(self, kb_app, sphinx_app: Sphinx, sphinx_env: BuildEnvironment, resource ): """ Make images and enter them in Sphinx's output writer """ docname = resource.docname srcdir = sphinx_app.env.srcdir source_imgpath = self.source_filename(docname, srcdir) # Copy the image to the Sphinx build directory build_dir = sphinx_app.outdir docpath = Path(docname) parent = docpath.parent target_imgpath = str(Path(build_dir, parent, self.filename)) # Does the target dir exist yet in the build dir? Probably not. If # not, make it target_dir = Path(build_dir, parent) if not target_dir.exists(): target_dir.mkdir(parents=True, exist_ok=True) shutil.copy(source_imgpath, target_imgpath)
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Make images and enter them in Sphinx's output writer
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python
train
jobovy/galpy
galpy/actionAngle/actionAngleAxi.py
https://github.com/jobovy/galpy/blob/9c5b9fe65d58835624dffe432be282060918ee08/galpy/actionAngle/actionAngleAxi.py#L108-L142
def TR(self,**kwargs): #pragma: no cover """ NAME: TR PURPOSE: Calculate the radial period for a power-law rotation curve INPUT: scipy.integrate.quadrature keywords OUTPUT: T_R(R,vT,vT)*vc/ro + estimate of the error HISTORY: 2010-12-01 - Written - Bovy (NYU) """ if hasattr(self,'_TR'): return self._TR (rperi,rap)= self.calcRapRperi(**kwargs) if nu.fabs(rap-rperi)/rap < 10.**-4.: #Rough limit self._TR= 2.*m.pi/epifreq(self._pot,self._R,use_physical=False) return self._TR Rmean= m.exp((m.log(rperi)+m.log(rap))/2.) EL= self.calcEL(**kwargs) E, L= EL TR= 0. if Rmean > rperi: TR+= integrate.quadrature(_TRAxiIntegrandSmall, 0.,m.sqrt(Rmean-rperi), args=(E,L,self._pot,rperi), **kwargs)[0] if Rmean < rap: TR+= integrate.quadrature(_TRAxiIntegrandLarge, 0.,m.sqrt(rap-Rmean), args=(E,L,self._pot,rap), **kwargs)[0] self._TR= 2.*TR return self._TR
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NAME: TR PURPOSE: Calculate the radial period for a power-law rotation curve INPUT: scipy.integrate.quadrature keywords OUTPUT: T_R(R,vT,vT)*vc/ro + estimate of the error HISTORY: 2010-12-01 - Written - Bovy (NYU)
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python
train
mitsei/dlkit
dlkit/json_/grading/sessions.py
https://github.com/mitsei/dlkit/blob/445f968a175d61c8d92c0f617a3c17dc1dc7c584/dlkit/json_/grading/sessions.py#L5012-L5032
def get_parent_gradebooks(self, gradebook_id): """Gets the parents of the given gradebook. arg: gradebook_id (osid.id.Id): the ``Id`` of a gradebook return: (osid.grading.GradebookList) - the parents of the gradebook raise: NotFound - ``gradebook_id`` is not found raise: NullArgument - ``gradebook_id`` is ``null`` raise: OperationFailed - unable to complete request raise: PermissionDenied - authorization failure *compliance: mandatory -- This method must be implemented.* """ # Implemented from template for # osid.resource.BinHierarchySession.get_parent_bins if self._catalog_session is not None: return self._catalog_session.get_parent_catalogs(catalog_id=gradebook_id) return GradebookLookupSession( self._proxy, self._runtime).get_gradebooks_by_ids( list(self.get_parent_gradebook_ids(gradebook_id)))
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Gets the parents of the given gradebook. arg: gradebook_id (osid.id.Id): the ``Id`` of a gradebook return: (osid.grading.GradebookList) - the parents of the gradebook raise: NotFound - ``gradebook_id`` is not found raise: NullArgument - ``gradebook_id`` is ``null`` raise: OperationFailed - unable to complete request raise: PermissionDenied - authorization failure *compliance: mandatory -- This method must be implemented.*
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python
train
nicferrier/md
src/mdlib/cmdln.py
https://github.com/nicferrier/md/blob/302ca8882dae060fb15bd5ae470d8e661fb67ec4/src/mdlib/cmdln.py#L1123-L1215
def _dispatch_cmd(self, handler, argv): """Introspect sub-command handler signature to determine how to dispatch the command. The raw handler provided by the base 'RawCmdln' class is still supported: def do_foo(self, argv): # 'argv' is the vector of command line args, argv[0] is # the command name itself (i.e. "foo" or an alias) pass In addition, if the handler has more than 2 arguments option processing is automatically done (using optparse): @cmdln.option('-v', '--verbose', action='store_true') def do_bar(self, subcmd, opts, *args): # subcmd = <"bar" or an alias> # opts = <an optparse.Values instance> if opts.verbose: print "lots of debugging output..." # args = <tuple of arguments> for arg in args: bar(arg) TODO: explain that "*args" can be other signatures as well. The `cmdln.option` decorator corresponds to an `add_option()` method call on an `optparse.OptionParser` instance. You can declare a specific number of arguments: @cmdln.option('-v', '--verbose', action='store_true') def do_bar2(self, subcmd, opts, bar_one, bar_two): #... and an appropriate error message will be raised/printed if the command is called with a different number of args. """ co_argcount = handler.__func__.__code__.co_argcount if co_argcount == 2: # handler ::= do_foo(self, argv) return handler(argv) elif co_argcount >= 3: # handler ::= do_foo(self, subcmd, opts, ...) try: optparser = handler.optparser except AttributeError: optparser = handler.__func__.optparser = SubCmdOptionParser() assert isinstance(optparser, SubCmdOptionParser) # apply subcommand options' defaults from config files, if any. subcmd = handler.__name__.split('do_', 1)[1] optparser.set_defaults(**self.get_option_defaults(subcmd)) optparser.set_cmdln_info(self, argv[0]) try: opts, args = optparser.parse_args(argv[1:]) except StopOptionProcessing: #TODO: this doesn't really fly for a replacement of # optparse.py behaviour, does it? return 0 # Normal command termination try: return handler(argv[0], opts, *args) except TypeError: _, ex, _ = sys.exc_info() # Some TypeError's are user errors: # do_foo() takes at least 4 arguments (3 given) # do_foo() takes at most 5 arguments (6 given) # do_foo() takes exactly 5 arguments (6 given) # do_foo() takes exactly 5 positional arguments (6 given) # Raise CmdlnUserError for these with a suitably # massaged error message. tb = sys.exc_info()[2] # the traceback object if tb.tb_next is not None: # If the traceback is more than one level deep, then the # TypeError do *not* happen on the "handler(...)" call # above. In that we don't want to handle it specially # here: it would falsely mask deeper code errors. raise msg = ex.args[0] match = _INCORRECT_NUM_ARGS_RE.search(msg) if match: msg = list(match.groups()) msg[1] = int(msg[1]) - 3 if msg[1] == 1: msg[2] = msg[2].replace("arguments", "argument") msg[3] = int(msg[3]) - 3 msg = ''.join(map(str, msg)) raise CmdlnUserError(msg) else: raise else: raise CmdlnError("incorrect argcount for %s(): takes %d, must " "take 2 for 'argv' signature or 3+ for 'opts' " "signature" % (handler.__name__, co_argcount))
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python
train
fastai/fastai
fastai/callbacks/tensorboard.py
https://github.com/fastai/fastai/blob/9fb84a5cdefe5a766cdb792b8f5d8971737b7e67/fastai/callbacks/tensorboard.py#L294-L297
def _add_gradient_scalar(self, name:str, scalar_value)->None: "Writes a single scalar value for a gradient statistic to Tensorboard." tag = self.name + '/gradients/' + name self.tbwriter.add_scalar(tag=tag, scalar_value=scalar_value, global_step=self.iteration)
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Writes a single scalar value for a gradient statistic to Tensorboard.
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python
train
GoogleCloudPlatform/datastore-ndb-python
ndb/eventloop.py
https://github.com/GoogleCloudPlatform/datastore-ndb-python/blob/cf4cab3f1f69cd04e1a9229871be466b53729f3f/ndb/eventloop.py#L182-L194
def add_idle(self, callback, *args, **kwds): """Add an idle callback. An idle callback can return True, False or None. These mean: - None: remove the callback (don't reschedule) - False: the callback did no work; reschedule later - True: the callback did some work; reschedule soon If the callback raises an exception, the traceback is logged and the callback is removed. """ self.idlers.append((callback, args, kwds))
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Add an idle callback. An idle callback can return True, False or None. These mean: - None: remove the callback (don't reschedule) - False: the callback did no work; reschedule later - True: the callback did some work; reschedule soon If the callback raises an exception, the traceback is logged and the callback is removed.
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python
train
XRDX/pyleap
pyleap/collision.py
https://github.com/XRDX/pyleap/blob/234c722cfbe66814254ab0d8f67d16b0b774f4d5/pyleap/collision.py#L66-L88
def line_cross(x1, y1, x2, y2, x3, y3, x4, y4): """ 判断两条线段是否交叉 """ # out of the rect if min(x1, x2) > max(x3, x4) or max(x1, x2) < min(x3, x4) or \ min(y1, y2) > max(y3, y4) or max(y1, y2) < min(y3, y4): return False # same slope rate if ((y1 - y2) * (x3 - x4) == (x1 - x2) * (y3 - y4)): return False if cross_product(x3, y3, x2, y2, x4, y4) * cross_product(x3, y3, x4, y4, x1, y1) < 0 or \ cross_product(x1, y1, x4, y4, x2, y2) * cross_product(x1, y1, x2, y2, x3, y3) < 0: return False # get collide point b1 = (y2 - y1) * x1 + (x1 - x2) * y1 b2 = (y4 - y3) * x3 + (x3 - x4) * y3 D = (x2 - x1) * (y4 - y3) - (x4 - x3) * (y2 - y1) D1 = b2 * (x2 - x1) - b1 * (x4 - x3) D2 = b2 * (y2 - y1) - b1 * (y4 - y3) return P(D1 / D, D2 / D)
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判断两条线段是否交叉
[ "判断两条线段是否交叉" ]
python
train
MoseleyBioinformaticsLab/ctfile
ctfile/ctfile.py
https://github.com/MoseleyBioinformaticsLab/ctfile/blob/eae864126cd9102207df5d363a3222256a0f1396/ctfile/ctfile.py#L829-L841
def add_sdfile(self, sdfile): """Add new ``SDfile`` to current ``SDfile``. :param sdfile: ``SDfile`` instance. :return: None. :rtype: :py:obj:`None`. """ if not isinstance(sdfile, SDfile): raise ValueError('Not a SDfile type: "{}"'.format(type(sdfile))) for entry_id in sdfile: self.add_molfile(molfile=sdfile[entry_id]['molfile'], data=sdfile[entry_id]['data'])
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Add new ``SDfile`` to current ``SDfile``. :param sdfile: ``SDfile`` instance. :return: None. :rtype: :py:obj:`None`.
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python
train
cathalgarvey/deadlock
deadlock/crypto.py
https://github.com/cathalgarvey/deadlock/blob/30099b476ff767611ce617150a0c574fc03fdf79/deadlock/crypto.py#L139-L167
def fancy(cls, contains, max_tries, inner=False, keepcase=False): """ Try to create a key with a chosen prefix, by starting with a 26-bit urandom number and appending with 8-byte integers until prefix matches. This function is naive, but has a max_tries argument which will abort when reached with a ValueError. TODO: make this smarter, in general. Variable byte length according to expected attempts, warnings of expected duration of iteration, etc. TODO: Implement multiprocessing to use poly-core machines fully: - Shared list, each process checks if empty every cycle, aborts if contains a value. - Successful values are pushed to list, cancelling all processes? - Server waits on all child processes then expects a list? - Ensure child processes start with different random base numbers, to avoid duplication? - Investigate server/manager aspect of multiprocessing; mini-clustering? """ contains = contains if keepcase else contains.lower() if not set(contains).issubset(base58.alphabet): raise ValueError("Cannot find contained phrase '{}' as it contains non-b58 characters".format(contains)) basenum = os.urandom(26) for i in range(max_tries): k = nacl.public.PrivateKey(basenum + i.to_bytes(6, 'big')) ukey = cls(k.public_key, k) test_uid = ukey.userID if keepcase else ukey.userID.lower() if test_uid.startswith(contains) or test_uid.endswith(contains) or (inner and contains in test_uid): return ukey else: raise ValueError("Could not create key with desired prefix '{}' in {} attempts.".format(prefix, max_tries))
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Try to create a key with a chosen prefix, by starting with a 26-bit urandom number and appending with 8-byte integers until prefix matches. This function is naive, but has a max_tries argument which will abort when reached with a ValueError. TODO: make this smarter, in general. Variable byte length according to expected attempts, warnings of expected duration of iteration, etc. TODO: Implement multiprocessing to use poly-core machines fully: - Shared list, each process checks if empty every cycle, aborts if contains a value. - Successful values are pushed to list, cancelling all processes? - Server waits on all child processes then expects a list? - Ensure child processes start with different random base numbers, to avoid duplication? - Investigate server/manager aspect of multiprocessing; mini-clustering?
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python
train
annoviko/pyclustering
pyclustering/cluster/syncnet.py
https://github.com/annoviko/pyclustering/blob/98aa0dd89fd36f701668fb1eb29c8fb5662bf7d0/pyclustering/cluster/syncnet.py#L342-L399
def show_network(self): """! @brief Shows connections in the network. It supports only 2-d and 3-d representation. """ if ( (self._ccore_network_pointer is not None) and (self._osc_conn is None) ): self._osc_conn = sync_connectivity_matrix(self._ccore_network_pointer); dimension = len(self._osc_loc[0]); if ( (dimension != 3) and (dimension != 2) ): raise NameError('Network that is located in different from 2-d and 3-d dimensions can not be represented'); from matplotlib.font_manager import FontProperties; from matplotlib import rcParams; rcParams['font.sans-serif'] = ['Arial']; rcParams['font.size'] = 12; fig = plt.figure(); axes = None; if (dimension == 2): axes = fig.add_subplot(111); elif (dimension == 3): axes = fig.gca(projection='3d'); surface_font = FontProperties(); surface_font.set_name('Arial'); surface_font.set_size('12'); for i in range(0, self._num_osc, 1): if (dimension == 2): axes.plot(self._osc_loc[i][0], self._osc_loc[i][1], 'bo'); if (self._conn_represent == conn_represent.MATRIX): for j in range(i, self._num_osc, 1): # draw connection between two points only one time if (self.has_connection(i, j) == True): axes.plot([self._osc_loc[i][0], self._osc_loc[j][0]], [self._osc_loc[i][1], self._osc_loc[j][1]], 'b-', linewidth = 0.5); else: for j in self.get_neighbors(i): if ( (self.has_connection(i, j) == True) and (i > j) ): # draw connection between two points only one time axes.plot([self._osc_loc[i][0], self._osc_loc[j][0]], [self._osc_loc[i][1], self._osc_loc[j][1]], 'b-', linewidth = 0.5); elif (dimension == 3): axes.scatter(self._osc_loc[i][0], self._osc_loc[i][1], self._osc_loc[i][2], c = 'b', marker = 'o'); if (self._conn_represent == conn_represent.MATRIX): for j in range(i, self._num_osc, 1): # draw connection between two points only one time if (self.has_connection(i, j) == True): axes.plot([self._osc_loc[i][0], self._osc_loc[j][0]], [self._osc_loc[i][1], self._osc_loc[j][1]], [self._osc_loc[i][2], self._osc_loc[j][2]], 'b-', linewidth = 0.5); else: for j in self.get_neighbors(i): if ( (self.has_connection(i, j) == True) and (i > j) ): # draw connection between two points only one time axes.plot([self._osc_loc[i][0], self._osc_loc[j][0]], [self._osc_loc[i][1], self._osc_loc[j][1]], [self._osc_loc[i][2], self._osc_loc[j][2]], 'b-', linewidth = 0.5); plt.grid(); plt.show();
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! @brief Shows connections in the network. It supports only 2-d and 3-d representation.
[ "!" ]
python
valid
respeaker/respeaker_python_library
respeaker/usb_hid/pywinusb_backend.py
https://github.com/respeaker/respeaker_python_library/blob/905a5334ccdc2d474ad973caf6a23d05c65bbb25/respeaker/usb_hid/pywinusb_backend.py#L63-L96
def getAllConnectedInterface(): """ returns all the connected CMSIS-DAP devices """ all_devices = hid.find_all_hid_devices() # find devices with good vid/pid all_mbed_devices = [] for d in all_devices: if (d.product_name.find("MicArray") >= 0): all_mbed_devices.append(d) boards = [] for dev in all_mbed_devices: try: dev.open(shared=False) report = dev.find_output_reports() if (len(report) == 1): new_board = PyWinUSB() new_board.report = report[0] new_board.vendor_name = dev.vendor_name new_board.product_name = dev.product_name new_board.serial_number = dev.serial_number new_board.vid = dev.vendor_id new_board.pid = dev.product_id new_board.device = dev new_board.device.set_raw_data_handler(new_board.rx_handler) boards.append(new_board) except Exception as e: logging.error("Receiving Exception: %s", e) dev.close() return boards
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returns all the connected CMSIS-DAP devices
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python
train
angr/claripy
claripy/vsa/valueset.py
https://github.com/angr/claripy/blob/4ed61924880af1ea8fb778047d896ec0156412a6/claripy/vsa/valueset.py#L243-L257
def copy(self): """ Make a copy of self and return. :return: A new ValueSet object. :rtype: ValueSet """ vs = ValueSet(bits=self.bits) vs._regions = self._regions.copy() vs._region_base_addrs = self._region_base_addrs.copy() vs._reversed = self._reversed vs._si = self._si.copy() return vs
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Make a copy of self and return. :return: A new ValueSet object. :rtype: ValueSet
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python
train
Azure/azure-uamqp-python
uamqp/authentication/cbs_auth.py
https://github.com/Azure/azure-uamqp-python/blob/b67e4fcaf2e8a337636947523570239c10a58ae2/uamqp/authentication/cbs_auth.py#L80-L89
def close_authenticator(self): """Close the CBS auth channel and session.""" _logger.info("Shutting down CBS session on connection: %r.", self._connection.container_id) try: _logger.debug("Unlocked CBS to close on connection: %r.", self._connection.container_id) self._cbs_auth.destroy() _logger.info("Auth closed, destroying session on connection: %r.", self._connection.container_id) self._session.destroy() finally: _logger.info("Finished shutting down CBS session on connection: %r.", self._connection.container_id)
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Close the CBS auth channel and session.
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python
train
bihealth/vcfpy
vcfpy/header.py
https://github.com/bihealth/vcfpy/blob/99e2165df30f11e0c95f3170f31bc5191d9e9e15/vcfpy/header.py#L353-L358
def get_lines(self, key): """Return header lines having the given ``key`` as their type""" if key in self._indices: return self._indices[key].values() else: return []
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Return header lines having the given ``key`` as their type
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python
train
huffpostdata/python-pollster
pollster/api.py
https://github.com/huffpostdata/python-pollster/blob/276de8d66a92577b1143fd92a70cff9c35a1dfcf/pollster/api.py#L23-L50
def charts_get(self, **kwargs): """ Charts Returns a list of Charts, ordered by creation date (newest first). A Chart is chosen by Pollster editors. One example is \"Obama job approval - Democrats\". It is always based upon a single Question. Users should strongly consider basing their analysis on Questions instead. Charts are derived data; Pollster editors publish them and change them as editorial priorities change. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.charts_get(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str cursor: Special string to index into the Array :param str tags: Comma-separated list of tag slugs. Only Charts with one or more of these tags and Charts based on Questions with one or more of these tags will be returned. :param date election_date: Date of an election, in YYYY-MM-DD format. Only Charts based on Questions pertaining to an election on this date will be returned. :return: InlineResponse200 If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('callback'): return self.charts_get_with_http_info(**kwargs) else: (data) = self.charts_get_with_http_info(**kwargs) return data
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Charts Returns a list of Charts, ordered by creation date (newest first). A Chart is chosen by Pollster editors. One example is \"Obama job approval - Democrats\". It is always based upon a single Question. Users should strongly consider basing their analysis on Questions instead. Charts are derived data; Pollster editors publish them and change them as editorial priorities change. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please define a `callback` function to be invoked when receiving the response. >>> def callback_function(response): >>> pprint(response) >>> >>> thread = api.charts_get(callback=callback_function) :param callback function: The callback function for asynchronous request. (optional) :param str cursor: Special string to index into the Array :param str tags: Comma-separated list of tag slugs. Only Charts with one or more of these tags and Charts based on Questions with one or more of these tags will be returned. :param date election_date: Date of an election, in YYYY-MM-DD format. Only Charts based on Questions pertaining to an election on this date will be returned. :return: InlineResponse200 If the method is called asynchronously, returns the request thread.
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python
train
seb-m/tss
tss.py
https://github.com/seb-m/tss/blob/ab45176b8585ba6bbbcaeffd21ec0c63f615dce0/tss.py#L212-L231
def share_secret(threshold, nshares, secret, identifier, hash_id=Hash.SHA256): """ Create nshares of the secret. threshold specifies the number of shares needed for reconstructing the secret value. A 0-16 bytes identifier must be provided. Optionally the secret is hashed with the algorithm specified by hash_id, a class attribute of Hash. This function must return a list of formatted shares or raises a TSSError exception if anything went wrong. """ if identifier is None: raise TSSError('an identifier must be provided') if not Hash.is_valid(hash_id): raise TSSError('invalid hash algorithm %s' % hash_id) secret = encode(secret) identifier = encode(identifier) if hash_id != Hash.NONE: secret += Hash.to_func(hash_id)(secret).digest() shares = generate_shares(threshold, nshares, secret) header = format_header(identifier, hash_id, threshold, len(secret) + 1) return [format_share(header, share) for share in shares]
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Create nshares of the secret. threshold specifies the number of shares needed for reconstructing the secret value. A 0-16 bytes identifier must be provided. Optionally the secret is hashed with the algorithm specified by hash_id, a class attribute of Hash. This function must return a list of formatted shares or raises a TSSError exception if anything went wrong.
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python
train
tcalmant/ipopo
pelix/framework.py
https://github.com/tcalmant/ipopo/blob/2f9ae0c44cd9c34ef1a9d50837b3254e75678eb1/pelix/framework.py#L1639-L1656
def get_service_references(self, clazz, ldap_filter=None): # type: (Optional[str], Optional[str]) -> Optional[List[ServiceReference]] """ Returns the service references for services that were registered under the specified class by this bundle and matching the given filter :param clazz: The class name with which the service was registered. :param ldap_filter: A filter on service properties :return: The list of references to the services registered by the calling bundle and matching the filters. """ refs = self.__framework.find_service_references(clazz, ldap_filter) if refs: for ref in refs: if ref.get_bundle() is not self.__bundle: refs.remove(ref) return refs
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Returns the service references for services that were registered under the specified class by this bundle and matching the given filter :param clazz: The class name with which the service was registered. :param ldap_filter: A filter on service properties :return: The list of references to the services registered by the calling bundle and matching the filters.
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python
train
sqlboy/fileseq
src/fileseq/frameset.py
https://github.com/sqlboy/fileseq/blob/f26c3c3c383134ce27d5dfe37793e1ebe88e69ad/src/fileseq/frameset.py#L880-L892
def difference(self, *other): """ Returns a new :class:`FrameSet` with elements in `self` but not in `other`. Args: other (:class:`FrameSet`): or objects that can cast to :class:`FrameSet` Returns: :class:`FrameSet`: """ from_frozenset = self.items.difference(*map(set, other)) return self.from_iterable(from_frozenset, sort=True)
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Returns a new :class:`FrameSet` with elements in `self` but not in `other`. Args: other (:class:`FrameSet`): or objects that can cast to :class:`FrameSet` Returns: :class:`FrameSet`:
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python
train
quantumlib/Cirq
cirq/circuits/circuit.py
https://github.com/quantumlib/Cirq/blob/0827da80dd7880e5b923eb69407e980ed9bc0bd2/cirq/circuits/circuit.py#L1544-L1560
def save_qasm(self, file_path: Union[str, bytes, int], header: Optional[str] = None, precision: int = 10, qubit_order: ops.QubitOrderOrList = ops.QubitOrder.DEFAULT, ) -> None: """Save a QASM file equivalent to the circuit. Args: file_path: The location of the file where the qasm will be written. header: A multi-line string that is placed in a comment at the top of the QASM. Defaults to a cirq version specifier. precision: Number of digits to use when representing numbers. qubit_order: Determines how qubits are ordered in the QASM register. """ self._to_qasm_output(header, precision, qubit_order).save(file_path)
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Save a QASM file equivalent to the circuit. Args: file_path: The location of the file where the qasm will be written. header: A multi-line string that is placed in a comment at the top of the QASM. Defaults to a cirq version specifier. precision: Number of digits to use when representing numbers. qubit_order: Determines how qubits are ordered in the QASM register.
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python
train
digidotcom/python-devicecloud
devicecloud/__init__.py
https://github.com/digidotcom/python-devicecloud/blob/32529684a348a7830a269c32601604c78036bcb8/devicecloud/__init__.py#L290-L311
def put(self, path, data, **kwargs): """Perform an HTTP PUT request of the specified path in Device Cloud Make an HTTP PUT request against Device Cloud with this accounts credentials and base url. This method uses the `requests <http://docs.python-requests.org/en/latest/>`_ library `request method <http://docs.python-requests.org/en/latest/api/#requests.request>`_ and all keyword arguments will be passed on to that method. :param str path: Device Cloud path to PUT :param int retries: The number of times the request should be retried if an unsuccessful response is received. Most likely, you should leave this at 0. :param data: The data to be posted in the body of the POST request (see docs for ``requests.post`` :raises DeviceCloudHttpException: if a non-success response to the request is received from Device Cloud :returns: A requests ``Response`` object """ url = self._make_url(path) return self._make_request("PUT", url, data=data, **kwargs)
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Perform an HTTP PUT request of the specified path in Device Cloud Make an HTTP PUT request against Device Cloud with this accounts credentials and base url. This method uses the `requests <http://docs.python-requests.org/en/latest/>`_ library `request method <http://docs.python-requests.org/en/latest/api/#requests.request>`_ and all keyword arguments will be passed on to that method. :param str path: Device Cloud path to PUT :param int retries: The number of times the request should be retried if an unsuccessful response is received. Most likely, you should leave this at 0. :param data: The data to be posted in the body of the POST request (see docs for ``requests.post`` :raises DeviceCloudHttpException: if a non-success response to the request is received from Device Cloud :returns: A requests ``Response`` object
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python
train
cmbruns/pyopenvr
src/openvr/__init__.py
https://github.com/cmbruns/pyopenvr/blob/68395d26bb3df6ab1f0f059c38d441f962938be6/src/openvr/__init__.py#L6128-L6134
def getOriginTrackedDeviceInfo(self, origin, unOriginInfoSize): """Retrieves useful information for the origin of this action""" fn = self.function_table.getOriginTrackedDeviceInfo pOriginInfo = InputOriginInfo_t() result = fn(origin, byref(pOriginInfo), unOriginInfoSize) return result, pOriginInfo
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Retrieves useful information for the origin of this action
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python
train
Ouranosinc/xclim
xclim/indices.py
https://github.com/Ouranosinc/xclim/blob/2080d139188bd8de2aeca097a025c2d89d6e0e09/xclim/indices.py#L1712-L1740
def tn_mean(tasmin, freq='YS'): r"""Mean minimum temperature. Mean of daily minimum temperature. Parameters ---------- tasmin : xarray.DataArray Minimum daily temperature [℃] or [K] freq : str, optional Resampling frequency Returns ------- xarray.DataArray Mean of daily minimum temperature. Notes ----- Let :math:`TN_{ij}` be the minimum temperature at day :math:`i` of period :math:`j`. Then mean values in period :math:`j` are given by: .. math:: TN_{ij} = \frac{ \sum_{i=1}^{I} TN_{ij} }{I} """ arr = tasmin.resample(time=freq) if freq else tasmin return arr.mean(dim='time', keep_attrs=True)
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r"""Mean minimum temperature. Mean of daily minimum temperature. Parameters ---------- tasmin : xarray.DataArray Minimum daily temperature [℃] or [K] freq : str, optional Resampling frequency Returns ------- xarray.DataArray Mean of daily minimum temperature. Notes ----- Let :math:`TN_{ij}` be the minimum temperature at day :math:`i` of period :math:`j`. Then mean values in period :math:`j` are given by: .. math:: TN_{ij} = \frac{ \sum_{i=1}^{I} TN_{ij} }{I}
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python
train
CellProfiler/centrosome
centrosome/haralick.py
https://github.com/CellProfiler/centrosome/blob/7bd9350a2d4ae1b215b81eabcecfe560bbb1f32a/centrosome/haralick.py#L205-L209
def H9(self): "Entropy." if not hasattr(self, '_H9'): self._H9 = -(self.P * np.log(self.P + self.eps)).sum(2).sum(1) return self._H9
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Entropy.
[ "Entropy", "." ]
python
train
zhmcclient/python-zhmcclient
zhmcclient/_session.py
https://github.com/zhmcclient/python-zhmcclient/blob/9657563e5d9184c51d3c903442a58b9725fdf335/zhmcclient/_session.py#L1313-L1405
def _result_object(result): """ Return the JSON payload in the HTTP response as a Python dict. Parameters: result (requests.Response): HTTP response object. Raises: zhmcclient.ParseError: Error parsing the returned JSON. """ content_type = result.headers.get('content-type', None) if content_type is None or content_type.startswith('application/json'): # This function is only called when there is content expected. # Therefore, a response without content will result in a ParseError. try: return result.json(object_pairs_hook=OrderedDict) except ValueError as exc: raise ParseError( "JSON parse error in HTTP response: {}. " "HTTP request: {} {}. " "Response status {}. " "Response content-type: {!r}. " "Content (max.1000, decoded using {}): {}". format(exc.args[0], result.request.method, result.request.url, result.status_code, content_type, result.encoding, _text_repr(result.text, 1000))) elif content_type.startswith('text/html'): # We are in some error situation. The HMC returns HTML content # for some 5xx status codes. We try to deal with it somehow, # but we are not going as far as real HTML parsing. m = re.search(r'charset=([^;,]+)', content_type) if m: encoding = m.group(1) # e.g. RFC "ISO-8859-1" else: encoding = 'utf-8' try: html_uni = result.content.decode(encoding) except LookupError: html_uni = result.content.decode() # We convert to one line to be regexp-friendly. html_oneline = html_uni.replace('\r\n', '\\n').replace('\r', '\\n').\ replace('\n', '\\n') # Check for some well-known errors: if re.search(r'javax\.servlet\.ServletException: ' r'Web Services are not enabled\.', html_oneline): html_title = "Console Configuration Error" html_details = "Web Services API is not enabled on the HMC." html_reason = HTML_REASON_WEB_SERVICES_DISABLED else: m = re.search( r'<title>([^<]*)</title>.*' r'<h2>Details:</h2>(.*)(<hr size="1" noshade>)?</body>', html_oneline) if m: html_title = m.group(1) # Spend a reasonable effort to make the HTML readable: html_details = m.group(2).replace('<p>', '\\n').\ replace('<br>', '\\n').replace('\\n\\n', '\\n').strip() else: html_title = "Console Internal Error" html_details = "Response body: {!r}".format(html_uni) html_reason = HTML_REASON_OTHER message = "{}: {}".format(html_title, html_details) # We create a minimal JSON error object (to the extent we use it # when processing it): result_obj = { 'http-status': result.status_code, 'reason': html_reason, 'message': message, 'request-uri': result.request.url, 'request-method': result.request.method, } return result_obj elif content_type.startswith('application/vnd.ibm-z-zmanager-metrics'): content_bytes = result.content assert isinstance(content_bytes, six.binary_type) return content_bytes.decode('utf-8') # as a unicode object else: raise ParseError( "Unknown content type in HTTP response: {}. " "HTTP request: {} {}. " "Response status {}. " "Response content-type: {!r}. " "Content (max.1000, decoded using {}): {}". format(content_type, result.request.method, result.request.url, result.status_code, content_type, result.encoding, _text_repr(result.text, 1000)))
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Return the JSON payload in the HTTP response as a Python dict. Parameters: result (requests.Response): HTTP response object. Raises: zhmcclient.ParseError: Error parsing the returned JSON.
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python
train
ValvePython/steam
steam/client/__init__.py
https://github.com/ValvePython/steam/blob/2de1364c47598410b572114e6129eab8fff71d5b/steam/client/__init__.py#L556-L570
def logout(self): """ Logout from steam. Doesn't nothing if not logged on. .. note:: The server will drop the connection immediatelly upon logout. """ if self.logged_on: self.logged_on = False self.send(MsgProto(EMsg.ClientLogOff)) try: self.wait_event(self.EVENT_DISCONNECTED, timeout=5, raises=True) except: self.disconnect() self.idle()
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Logout from steam. Doesn't nothing if not logged on. .. note:: The server will drop the connection immediatelly upon logout.
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python
train
CalebBell/ht
ht/conv_internal.py
https://github.com/CalebBell/ht/blob/3097ef9524c4cf0068ad453c17b10ec9ce551eee/ht/conv_internal.py#L336-L383
def turbulent_Sieder_Tate(Re, Pr, mu=None, mu_w=None): r'''Calculates internal convection Nusselt number for turbulent flows in pipe according to [1]_ and supposedly [2]_. .. math:: Nu = 0.027Re^{4/5}Pr^{1/3}\left(\frac{\mu}{\mu_s}\right)^{0.14} Parameters ---------- Re : float Reynolds number, [-] Pr : float Prandtl number, [-] mu : float Viscosity of fluid, [Pa*s] mu_w : float Viscosity of fluid at wall temperature, [Pa*s] Returns ------- Nu : float Nusselt number, [-] Notes ----- A linear coefficient of 0.023 is often listed with this equation. The source of the discrepancy is not known. The equation is not present in the original paper, but is nevertheless the source usually cited for it. Examples -------- >>> turbulent_Sieder_Tate(Re=1E5, Pr=1.2) 286.9178136793052 >>> turbulent_Sieder_Tate(Re=1E5, Pr=1.2, mu=0.01, mu_w=0.067) 219.84016455766044 References ---------- .. [1] Rohsenow, Warren and James Hartnett and Young Cho. Handbook of Heat Transfer, 3E. New York: McGraw-Hill, 1998. .. [2] Sieder, E. N., and G. E. Tate. "Heat Transfer and Pressure Drop of Liquids in Tubes." Industrial & Engineering Chemistry 28, no. 12 (December 1, 1936): 1429-35. doi:10.1021/ie50324a027. ''' Nu = 0.027*Re**0.8*Pr**(1/3.) if mu_w and mu: Nu *= (mu/mu_w)**0.14 return Nu
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r'''Calculates internal convection Nusselt number for turbulent flows in pipe according to [1]_ and supposedly [2]_. .. math:: Nu = 0.027Re^{4/5}Pr^{1/3}\left(\frac{\mu}{\mu_s}\right)^{0.14} Parameters ---------- Re : float Reynolds number, [-] Pr : float Prandtl number, [-] mu : float Viscosity of fluid, [Pa*s] mu_w : float Viscosity of fluid at wall temperature, [Pa*s] Returns ------- Nu : float Nusselt number, [-] Notes ----- A linear coefficient of 0.023 is often listed with this equation. The source of the discrepancy is not known. The equation is not present in the original paper, but is nevertheless the source usually cited for it. Examples -------- >>> turbulent_Sieder_Tate(Re=1E5, Pr=1.2) 286.9178136793052 >>> turbulent_Sieder_Tate(Re=1E5, Pr=1.2, mu=0.01, mu_w=0.067) 219.84016455766044 References ---------- .. [1] Rohsenow, Warren and James Hartnett and Young Cho. Handbook of Heat Transfer, 3E. New York: McGraw-Hill, 1998. .. [2] Sieder, E. N., and G. E. Tate. "Heat Transfer and Pressure Drop of Liquids in Tubes." Industrial & Engineering Chemistry 28, no. 12 (December 1, 1936): 1429-35. doi:10.1021/ie50324a027.
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python
train
pymupdf/PyMuPDF
fitz/fitz.py
https://github.com/pymupdf/PyMuPDF/blob/917f2d83482510e26ba0ff01fd2392c26f3a8e90/fitz/fitz.py#L3586-L3593
def rect(self): """Rectangle containing the annot""" CheckParent(self) val = _fitz.Annot_rect(self) val = Rect(val) return val
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Rectangle containing the annot
[ "Rectangle", "containing", "the", "annot" ]
python
train
openstack/networking-arista
networking_arista/ml2/mechanism_arista.py
https://github.com/openstack/networking-arista/blob/07ce6b1fc62ff74308a6eabfc4cc0ee09fb7b0fe/networking_arista/ml2/mechanism_arista.py#L253-L287
def update_port_postcommit(self, context): """Send port updates to CVX This method is also responsible for the initial creation of ports as we wait until after a port is bound to send the port data to CVX """ port = context.current orig_port = context.original network = context.network.current log_context("update_port_postcommit: port", port) log_context("update_port_postcommit: orig", orig_port) tenant_id = port['project_id'] # Device id can change without a port going DOWN, but the new device # id may not be supported if orig_port and port['device_id'] != orig_port['device_id']: self._delete_port_resources(orig_port, context.original_host) if context.status == n_const.PORT_STATUS_DOWN: if (context.original_host and context.status != context.original_status): self._delete_port_resources(orig_port, context.original_host) self._try_to_release_dynamic_segment(context, migration=True) else: self.create_tenant(tenant_id) self.create_network(network) if context.binding_levels: segments = [ level['bound_segment'] for level in context.binding_levels] self.create_segments(segments) self.create_instance(port) self.create_port(port) self.create_port_binding(port, context.host)
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Send port updates to CVX This method is also responsible for the initial creation of ports as we wait until after a port is bound to send the port data to CVX
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python
train
twisted/mantissa
xmantissa/publicweb.py
https://github.com/twisted/mantissa/blob/53e5502aba23ce99be78b27f923a276593033fe8/xmantissa/publicweb.py#L741-L753
def child_(self, ctx): """ If the root resource is requested, return the primary application's front page, if a primary application has been chosen. Otherwise return 'self', since this page can render a simple index. """ if self.frontPageItem.defaultApplication is None: return self.webViewer.wrapModel( _OfferingsFragment(self.frontPageItem)) else: return SharingIndex(self.frontPageItem.defaultApplication.open(), self.webViewer).locateChild(ctx, [''])[0]
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If the root resource is requested, return the primary application's front page, if a primary application has been chosen. Otherwise return 'self', since this page can render a simple index.
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python
train
RJT1990/pyflux
pyflux/families/poisson.py
https://github.com/RJT1990/pyflux/blob/297f2afc2095acd97c12e827dd500e8ea5da0c0f/pyflux/families/poisson.py#L243-L265
def setup(): """ Returns the attributes of this family Notes ---------- - scale notes whether family has a variance parameter (sigma) - shape notes whether family has a tail thickness parameter (nu) - skewness notes whether family has a skewness parameter (gamma) - mean_transform is a function which transforms the location parameter - cythonized notes whether the family has cythonized routines Returns ---------- - model name, link function, scale, shape, skewness, mean_transform, cythonized """ name = "Poisson" link = np.exp scale = False shape = False skewness = False mean_transform = np.log cythonized = True return name, link, scale, shape, skewness, mean_transform, cythonized
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Returns the attributes of this family Notes ---------- - scale notes whether family has a variance parameter (sigma) - shape notes whether family has a tail thickness parameter (nu) - skewness notes whether family has a skewness parameter (gamma) - mean_transform is a function which transforms the location parameter - cythonized notes whether the family has cythonized routines Returns ---------- - model name, link function, scale, shape, skewness, mean_transform, cythonized
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python
train
pypa/pipenv
pipenv/vendor/pexpect/FSM.py
https://github.com/pypa/pipenv/blob/cae8d76c210b9777e90aab76e9c4b0e53bb19cde/pipenv/vendor/pexpect/FSM.py#L228-L243
def process (self, input_symbol): '''This is the main method that you call to process input. This may cause the FSM to change state and call an action. This method calls get_transition() to find the action and next_state associated with the input_symbol and current_state. If the action is None then the action is not called and only the current state is changed. This method processes one complete input symbol. You can process a list of symbols (or a string) by calling process_list(). ''' self.input_symbol = input_symbol (self.action, self.next_state) = self.get_transition (self.input_symbol, self.current_state) if self.action is not None: self.action (self) self.current_state = self.next_state self.next_state = None
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This is the main method that you call to process input. This may cause the FSM to change state and call an action. This method calls get_transition() to find the action and next_state associated with the input_symbol and current_state. If the action is None then the action is not called and only the current state is changed. This method processes one complete input symbol. You can process a list of symbols (or a string) by calling process_list().
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python
train
pygobject/pgi
pgi/debug.py
https://github.com/pygobject/pgi/blob/2090435df6241a15ec2a78379a36b738b728652c/pgi/debug.py#L11-L31
def pprint(obj, file_=None): """Prints debug information for various public objects like methods, functions, constructors etc. """ if file_ is None: file_ = sys.stdout # functions, methods if callable(obj) and hasattr(obj, "_code"): obj._code.pprint(file_) return # classes if isinstance(obj, type) and hasattr(obj, "_constructors"): constructors = obj._constructors for names, func in sorted(constructors.items()): func._code.pprint(file_) return raise TypeError("unkown type")
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Prints debug information for various public objects like methods, functions, constructors etc.
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python
train
singularityhub/singularity-python
singularity/analysis/utils.py
https://github.com/singularityhub/singularity-python/blob/498c3433724b332f7493fec632d8daf479f47b82/singularity/analysis/utils.py#L50-L60
def update_dict(input_dict,key,value): '''update_dict will update lists in a dictionary. If the key is not included, if will add as new list. If it is, it will append. :param input_dict: the dict to update :param value: the value to update with ''' if key in input_dict: input_dict[key].append(value) else: input_dict[key] = [value] return input_dict
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update_dict will update lists in a dictionary. If the key is not included, if will add as new list. If it is, it will append. :param input_dict: the dict to update :param value: the value to update with
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python
train
LonamiWebs/Telethon
telethon/client/dialogs.py
https://github.com/LonamiWebs/Telethon/blob/1ead9757d366b58c1e0567cddb0196e20f1a445f/telethon/client/dialogs.py#L100-L142
def iter_dialogs( self, limit=None, *, offset_date=None, offset_id=0, offset_peer=types.InputPeerEmpty(), ignore_migrated=False ): """ Returns an iterator over the dialogs, yielding 'limit' at most. Dialogs are the open "chats" or conversations with other people, groups you have joined, or channels you are subscribed to. Args: limit (`int` | `None`): How many dialogs to be retrieved as maximum. Can be set to ``None`` to retrieve all dialogs. Note that this may take whole minutes if you have hundreds of dialogs, as Telegram will tell the library to slow down through a ``FloodWaitError``. offset_date (`datetime`, optional): The offset date to be used. offset_id (`int`, optional): The message ID to be used as an offset. offset_peer (:tl:`InputPeer`, optional): The peer to be used as an offset. ignore_migrated (`bool`, optional): Whether :tl:`Chat` that have ``migrated_to`` a :tl:`Channel` should be included or not. By default all the chats in your dialogs are returned, but setting this to ``True`` will hide them in the same way official applications do. Yields: Instances of `telethon.tl.custom.dialog.Dialog`. """ return _DialogsIter( self, limit, offset_date=offset_date, offset_id=offset_id, offset_peer=offset_peer, ignore_migrated=ignore_migrated )
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Returns an iterator over the dialogs, yielding 'limit' at most. Dialogs are the open "chats" or conversations with other people, groups you have joined, or channels you are subscribed to. Args: limit (`int` | `None`): How many dialogs to be retrieved as maximum. Can be set to ``None`` to retrieve all dialogs. Note that this may take whole minutes if you have hundreds of dialogs, as Telegram will tell the library to slow down through a ``FloodWaitError``. offset_date (`datetime`, optional): The offset date to be used. offset_id (`int`, optional): The message ID to be used as an offset. offset_peer (:tl:`InputPeer`, optional): The peer to be used as an offset. ignore_migrated (`bool`, optional): Whether :tl:`Chat` that have ``migrated_to`` a :tl:`Channel` should be included or not. By default all the chats in your dialogs are returned, but setting this to ``True`` will hide them in the same way official applications do. Yields: Instances of `telethon.tl.custom.dialog.Dialog`.
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python
train
dw/mitogen
mitogen/core.py
https://github.com/dw/mitogen/blob/a7fdb55e1300a7e0a5e404b09eb730cf9a525da7/mitogen/core.py#L1954-L1959
def readers(self): """ Return a list of `(fd, data)` tuples for every FD registered for receive readiness. """ return list((fd, data) for fd, (data, gen) in self._rfds.items())
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Return a list of `(fd, data)` tuples for every FD registered for receive readiness.
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python
train
agoragames/haigha
haigha/transports/event_transport.py
https://github.com/agoragames/haigha/blob/7b004e1c0316ec14b94fec1c54554654c38b1a25/haigha/transports/event_transport.py#L70-L99
def read(self, timeout=None): ''' Read from the transport. If no data is available, should return None. The timeout is ignored as this returns only data that has already been buffered locally. ''' # NOTE: copying over this comment from Connection, because there is # knowledge captured here, even if the details are stale # Because of the timer callback to dataRead when we re-buffered, # there's a chance that in between we've lost the socket. If that's # the case, just silently return as some code elsewhere would have # already notified us. That bug could be fixed by improving the # message reading so that we consume all possible messages and ensure # that only a partial message was rebuffered, so that we can rely on # the next read event to read the subsequent message. if not hasattr(self, '_sock'): return None # This is sort of a hack because we're faking that data is ready, but # it works for purposes of supporting timeouts if timeout: if self._heartbeat_timeout: self._heartbeat_timeout.delete() self._heartbeat_timeout = \ event.timeout(timeout, self._sock_read_cb, self._sock) elif self._heartbeat_timeout: self._heartbeat_timeout.delete() self._heartbeat_timeout = None return self._sock.read()
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Read from the transport. If no data is available, should return None. The timeout is ignored as this returns only data that has already been buffered locally.
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python
train
tadashi-aikawa/owlmixin
owlmixin/owlcollections.py
https://github.com/tadashi-aikawa/owlmixin/blob/7c4a042c3008abddc56a8e8e55ae930d276071f5/owlmixin/owlcollections.py#L417-L428
def map(self, func): """ :param func: :type func: (K, T) -> U :rtype: TList[U] Usage: >>> sorted(TDict(k1=1, k2=2, k3=3).map(lambda k, v: v*2)) [2, 4, 6] """ return TList([func(k, v) for k, v in self.items()])
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:param func: :type func: (K, T) -> U :rtype: TList[U] Usage: >>> sorted(TDict(k1=1, k2=2, k3=3).map(lambda k, v: v*2)) [2, 4, 6]
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python
train
fracpete/python-weka-wrapper
python/weka/core/tokenizers.py
https://github.com/fracpete/python-weka-wrapper/blob/e865915146faf40d3bbfedb440328d1360541633/python/weka/core/tokenizers.py#L42-L52
def next(self): """ Reads the next dataset row. :return: the next row :rtype: Instance """ if not self.__has_more(): raise StopIteration() else: return javabridge.get_env().get_string(self.__next())
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Reads the next dataset row. :return: the next row :rtype: Instance
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python
train
dailymuse/oz
oz/bandit/actions.py
https://github.com/dailymuse/oz/blob/4329f6a207dc9d2a8fbeb4d16d415dbe4570b5bd/oz/bandit/actions.py#L16-L19
def archive_experiment(experiment): """Archives an experiment""" redis = oz.redis.create_connection() oz.bandit.Experiment(redis, experiment).archive()
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Archives an experiment
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python
train
casacore/python-casacore
casacore/fitting/fitting.py
https://github.com/casacore/python-casacore/blob/975510861ea005f7919dd9e438b5f98a1682eebe/casacore/fitting/fitting.py#L76-L100
def init(self, n=0, ftype="real", colfac=1.0e-8, lmfac=1.0e-3, fid=0): """Set selected properties of the fitserver instance. Like in the constructor, the number of unknowns to be solved for; the number of simultaneous solutions; the ftype and the collinearity and Levenberg-Marquardt factor can be specified. Individual values can be overwritten with the :meth:`set` function. :param n: number of unknowns :param ftype: type of solution Allowed: real, complex, separable, asreal, conjugate :param colfac: collinearity factor :param lmfac: Levenberg-Marquardt factor :param fid: the id of a sub-fitter """ ftype = self._gettype(ftype) self._fitids[fid]["stat"] = False self._fitids[fid]["solved"] = False self._fitids[fid]["haserr"] = False self._fitids[fid]["fit"] = False self._fitids[fid]["looped"] = False if self._fitproxy.init(fid, n, ftype, colfac, lmfac): self._fitids[fid]["stat"] = self._getstate(fid) else: return False
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Set selected properties of the fitserver instance. Like in the constructor, the number of unknowns to be solved for; the number of simultaneous solutions; the ftype and the collinearity and Levenberg-Marquardt factor can be specified. Individual values can be overwritten with the :meth:`set` function. :param n: number of unknowns :param ftype: type of solution Allowed: real, complex, separable, asreal, conjugate :param colfac: collinearity factor :param lmfac: Levenberg-Marquardt factor :param fid: the id of a sub-fitter
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python
train
galaxyproject/pulsar
pulsar/client/staging/up.py
https://github.com/galaxyproject/pulsar/blob/9ab6683802884324652da0a9f0808c7eb59d3ab4/pulsar/client/staging/up.py#L360-L376
def find_referenced_subfiles(self, directory): """ Return list of files below specified `directory` in job inputs. Could use more sophisticated logic (match quotes to handle spaces, handle subdirectories, etc...). **Parameters** directory : str Full path to directory to search. """ if directory is None: return [] pattern = r'''[\'\"]?(%s%s[^\s\'\"]+)[\'\"]?''' % (escape(directory), escape(sep)) return self.find_pattern_references(pattern)
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Return list of files below specified `directory` in job inputs. Could use more sophisticated logic (match quotes to handle spaces, handle subdirectories, etc...). **Parameters** directory : str Full path to directory to search.
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python
train
tensorflow/probability
tensorflow_probability/python/mcmc/transformed_kernel.py
https://github.com/tensorflow/probability/blob/e87fe34111d68c35db0f9eeb4935f1ece9e1a8f5/tensorflow_probability/python/mcmc/transformed_kernel.py#L67-L74
def inverse_transform_fn(bijector): """Makes a function which applies a list of Bijectors' `inverse`s.""" if not mcmc_util.is_list_like(bijector): bijector = [bijector] def fn(state_parts): return [b.inverse(sp) for b, sp in zip(bijector, state_parts)] return fn
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Makes a function which applies a list of Bijectors' `inverse`s.
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python
test
jurismarches/chopper
chopper/extractor.py
https://github.com/jurismarches/chopper/blob/53c5489a53e3a5d205a5cb207df751c09633e7ce/chopper/extractor.py#L58-L110
def extract(self, html_contents, css_contents=None, base_url=None): """ Extracts the cleaned html tree as a string and only css rules matching the cleaned html tree :param html_contents: The HTML contents to parse :type html_contents: str :param css_contents: The CSS contents to parse :type css_contents: str :param base_url: The base page URL to use for relative to absolute links :type base_url: str :returns: cleaned HTML contents, cleaned CSS contents :rtype: str or tuple """ # Clean HTML html_extractor = self.html_extractor( html_contents, self._xpaths_to_keep, self._xpaths_to_discard) has_matches = html_extractor.parse() if has_matches: # Relative to absolute URLs if base_url is not None: html_extractor.rel_to_abs(base_url) # Convert ElementTree to string cleaned_html = html_extractor.to_string() else: cleaned_html = None # Clean CSS if css_contents is not None: if cleaned_html is not None: css_extractor = self.css_extractor(css_contents, cleaned_html) css_extractor.parse() # Relative to absolute URLs if base_url is not None: css_extractor.rel_to_abs(base_url) cleaned_css = css_extractor.to_string() else: cleaned_css = None else: return cleaned_html return (cleaned_html, cleaned_css)
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python
train
a1ezzz/wasp-general
wasp_general/uri.py
https://github.com/a1ezzz/wasp-general/blob/1029839d33eb663f8dec76c1c46754d53c1de4a9/wasp_general/uri.py#L576-L594
def validate(self, uri): """ Check that an query part of an URI is compatible with this descriptor. Return True if the URI is compatible. :param uri: an URI to check :return: bool """ if WURIComponentVerifier.validate(self, uri) is False: return False try: WStrictURIQuery( WURIQuery.parse(uri.component(self.component())), *self.__specs, extra_parameters=self.__extra_parameters ) except ValueError: return False return True
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Check that an query part of an URI is compatible with this descriptor. Return True if the URI is compatible. :param uri: an URI to check :return: bool
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python
train
klmitch/bark
bark/handlers.py
https://github.com/klmitch/bark/blob/6e0e002d55f01fee27e3e45bb86e30af1bfeef36/bark/handlers.py#L93-L107
def boolean(text): """ An alternative to the "bool" argument type which interprets string values. """ tmp = text.lower() if tmp.isdigit(): return bool(int(tmp)) elif tmp in ('t', 'true', 'on', 'yes'): return True elif tmp in ('f', 'false', 'off', 'no'): return False raise ValueError("invalid Boolean value %r" % text)
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An alternative to the "bool" argument type which interprets string values.
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python
train
kgori/treeCl
treeCl/parutils.py
https://github.com/kgori/treeCl/blob/fed624b3db1c19cc07175ca04e3eda6905a8d305/treeCl/parutils.py#L84-L115
def parallel_map(client, task, args, message, batchsize=1, background=False, nargs=None): """ Helper to map a function over a sequence of inputs, in parallel, with progress meter. :param client: IPython.parallel.Client instance :param task: Function :param args: Must be a list of tuples of arguments that the task function will be mapped onto. If the function takes a single argument, it still must be a 1-tuple. :param message: String for progress bar :param batchsize: Jobs are shipped in batches of this size. Higher numbers mean less network traffic, but longer execution time per job. :return: IPython.parallel.AsyncMapResult """ show_progress = bool(message) njobs = get_njobs(nargs, args) nproc = len(client) logger.debug('parallel_map: len(client) = {}'.format(len(client))) view = client.load_balanced_view() if show_progress: message += ' (IP:{}w:{}b)'.format(nproc, batchsize) pbar = setup_progressbar(message, njobs, simple_progress=True) if not background: pbar.start() map_result = view.map(task, *list(zip(*args)), chunksize=batchsize) if background: return map_result, client while not map_result.ready(): map_result.wait(1) if show_progress: pbar.update(min(njobs, map_result.progress * batchsize)) if show_progress: pbar.finish() return map_result
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Helper to map a function over a sequence of inputs, in parallel, with progress meter. :param client: IPython.parallel.Client instance :param task: Function :param args: Must be a list of tuples of arguments that the task function will be mapped onto. If the function takes a single argument, it still must be a 1-tuple. :param message: String for progress bar :param batchsize: Jobs are shipped in batches of this size. Higher numbers mean less network traffic, but longer execution time per job. :return: IPython.parallel.AsyncMapResult
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python
train
joshspeagle/dynesty
dynesty/utils.py
https://github.com/joshspeagle/dynesty/blob/9e482aafeb5cf84bedb896fa6f07a761d917983e/dynesty/utils.py#L150-L194
def quantile(x, q, weights=None): """ Compute (weighted) quantiles from an input set of samples. Parameters ---------- x : `~numpy.ndarray` with shape (nsamps,) Input samples. q : `~numpy.ndarray` with shape (nquantiles,) The list of quantiles to compute from `[0., 1.]`. weights : `~numpy.ndarray` with shape (nsamps,), optional The associated weight from each sample. Returns ------- quantiles : `~numpy.ndarray` with shape (nquantiles,) The weighted sample quantiles computed at `q`. """ # Initial check. x = np.atleast_1d(x) q = np.atleast_1d(q) # Quantile check. if np.any(q < 0.0) or np.any(q > 1.0): raise ValueError("Quantiles must be between 0. and 1.") if weights is None: # If no weights provided, this simply calls `np.percentile`. return np.percentile(x, list(100.0 * q)) else: # If weights are provided, compute the weighted quantiles. weights = np.atleast_1d(weights) if len(x) != len(weights): raise ValueError("Dimension mismatch: len(weights) != len(x).") idx = np.argsort(x) # sort samples sw = weights[idx] # sort weights cdf = np.cumsum(sw)[:-1] # compute CDF cdf /= cdf[-1] # normalize CDF cdf = np.append(0, cdf) # ensure proper span quantiles = np.interp(q, cdf, x[idx]).tolist() return quantiles
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Compute (weighted) quantiles from an input set of samples. Parameters ---------- x : `~numpy.ndarray` with shape (nsamps,) Input samples. q : `~numpy.ndarray` with shape (nquantiles,) The list of quantiles to compute from `[0., 1.]`. weights : `~numpy.ndarray` with shape (nsamps,), optional The associated weight from each sample. Returns ------- quantiles : `~numpy.ndarray` with shape (nquantiles,) The weighted sample quantiles computed at `q`.
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python
train
threeML/astromodels
astromodels/functions/template_model.py
https://github.com/threeML/astromodels/blob/9aac365a372f77603039533df9a6b694c1e360d5/astromodels/functions/template_model.py#L304-L407
def _custom_init_(self, model_name, other_name=None,log_interp = True): """ Custom initialization for this model :param model_name: the name of the model, corresponding to the root of the .h5 file in the data directory :param other_name: (optional) the name to be used as name of the model when used in astromodels. If None (default), use the same name as model_name :return: none """ # Get the data directory data_dir_path = get_user_data_path() # Sanitize the data file filename_sanitized = os.path.abspath(os.path.join(data_dir_path, '%s.h5' % model_name)) if not os.path.exists(filename_sanitized): raise MissingDataFile("The data file %s does not exists. Did you use the " "TemplateFactory?" % (filename_sanitized)) # Open the template definition and read from it self._data_file = filename_sanitized with HDFStore(filename_sanitized) as store: self._data_frame = store['data_frame'] self._parameters_grids = collections.OrderedDict() processed_parameters = 0 for key in store.keys(): match = re.search('p_([0-9]+)_(.+)', key) if match is None: continue else: tokens = match.groups() this_parameter_number = int(tokens[0]) this_parameter_name = str(tokens[1]) assert this_parameter_number == processed_parameters, "Parameters out of order!" self._parameters_grids[this_parameter_name] = store[key] processed_parameters += 1 self._energies = store['energies'] # Now get the metadata metadata = store.get_storer('data_frame').attrs.metadata description = metadata['description'] name = metadata['name'] self._interpolation_degree = metadata['interpolation_degree'] self._spline_smoothing_factor = metadata['spline_smoothing_factor'] # Make the dictionary of parameters function_definition = collections.OrderedDict() function_definition['description'] = description function_definition['latex'] = 'n.a.' # Now build the parameters according to the content of the parameter grid parameters = collections.OrderedDict() parameters['K'] = Parameter('K', 1.0) parameters['scale'] = Parameter('scale', 1.0) for parameter_name in self._parameters_grids.keys(): grid = self._parameters_grids[parameter_name] parameters[parameter_name] = Parameter(parameter_name, grid.median(), min_value=grid.min(), max_value=grid.max()) if other_name is None: super(TemplateModel, self).__init__(name, function_definition, parameters) else: super(TemplateModel, self).__init__(other_name, function_definition, parameters) # Finally prepare the interpolators self._prepare_interpolators(log_interp)
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Custom initialization for this model :param model_name: the name of the model, corresponding to the root of the .h5 file in the data directory :param other_name: (optional) the name to be used as name of the model when used in astromodels. If None (default), use the same name as model_name :return: none
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python
train
johnnoone/json-spec
src/jsonspec/validators/formats.py
https://github.com/johnnoone/json-spec/blob/f91981724cea0c366bd42a6670eb07bbe31c0e0c/src/jsonspec/validators/formats.py#L112-L143
def register(func=None, name=None): """ Expose compiler to factory. :param func: the callable to expose :type func: callable :param name: name of format :type name: str It can be used as a decorator:: @register(name='my:validator') def my_validator(obj): if obj is True: return obj raise ValidationError('obj is not true') or as a function:: def my_validator(obj): if obj is True: return obj raise ValidationError('obj is not true') @register(name='my:validator') """ if not name: raise CompilationError('Name is required') if not func: return partial(register, name=name) return FormatRegistry.register(name, func)
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Expose compiler to factory. :param func: the callable to expose :type func: callable :param name: name of format :type name: str It can be used as a decorator:: @register(name='my:validator') def my_validator(obj): if obj is True: return obj raise ValidationError('obj is not true') or as a function:: def my_validator(obj): if obj is True: return obj raise ValidationError('obj is not true') @register(name='my:validator')
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python
train
mryellow/maze_explorer
mazeexp/engine/player.py
https://github.com/mryellow/maze_explorer/blob/ab8a25ccd05105d2fe57e0213d690cfc07e45827/mazeexp/engine/player.py#L82-L95
def update_rotation(self, dt, buttons): """ Updates rotation and impulse direction """ assert isinstance(buttons, dict) ma = buttons['right'] - buttons['left'] if ma != 0: self.stats['battery'] -= self.battery_use['angular'] self.rotation += ma * dt * self.angular_velocity # Redirect velocity in new direction a = math.radians(self.rotation) self.impulse_dir = eu.Vector2(math.sin(a), math.cos(a))
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Updates rotation and impulse direction
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python
train
cloud9ers/gurumate
environment/lib/python2.7/site-packages/nose/suite.py
https://github.com/cloud9ers/gurumate/blob/075dc74d1ee62a8c6b7a8bf2b271364f01629d1e/environment/lib/python2.7/site-packages/nose/suite.py#L428-L453
def ancestry(self, context): """Return the ancestry of the context (that is, all of the packages and modules containing the context), in order of descent with the outermost ancestor last. This method is a generator. """ log.debug("get ancestry %s", context) if context is None: return # Methods include reference to module they are defined in, we # don't want that, instead want the module the class is in now # (classes are re-ancestored elsewhere). if hasattr(context, 'im_class'): context = context.im_class elif hasattr(context, '__self__'): context = context.__self__.__class__ if hasattr(context, '__module__'): ancestors = context.__module__.split('.') elif hasattr(context, '__name__'): ancestors = context.__name__.split('.')[:-1] else: raise TypeError("%s has no ancestors?" % context) while ancestors: log.debug(" %s ancestors %s", context, ancestors) yield resolve_name('.'.join(ancestors)) ancestors.pop()
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Return the ancestry of the context (that is, all of the packages and modules containing the context), in order of descent with the outermost ancestor last. This method is a generator.
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python
test
cltl/KafNafParserPy
KafNafParserPy/coreference_data.py
https://github.com/cltl/KafNafParserPy/blob/9bc32e803c176404b255ba317479b8780ed5f569/KafNafParserPy/coreference_data.py#L194-L201
def to_kaf(self): """ Converts the coreference layer to KAF """ if self.type == 'NAF': for node_coref in self.__get_corefs_nodes(): node_coref.set('coid',node_coref.get('id')) del node_coref.attrib['id']
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Converts the coreference layer to KAF
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python
train
tanghaibao/jcvi
jcvi/apps/grid.py
https://github.com/tanghaibao/jcvi/blob/d2e31a77b6ade7f41f3b321febc2b4744d1cdeca/jcvi/apps/grid.py#L398-L477
def run(args): """ %prog run command ::: file1 file2 Parallelize a set of commands on grid. The syntax is modeled after GNU parallel <http://www.gnu.org/s/parallel/man.html#options> {} - input line {.} - input line without extension {_} - input line first part {/} - basename of input line {/.} - basename of input line without extension {/_} - basename of input line first part {#} - sequence number of job to run ::: - Use arguments from the command line as input source instead of stdin (standard input). If file name is `t/example.tar.gz`, then, {} is "t/example.tar.gz", {.} is "t/example.tar", {_} is "t/example" {/} is "example.tar.gz", {/.} is "example.tar", {/_} is "example" A few examples: ls -1 *.fastq | %prog run process {} {.}.pdf # use stdin %prog run process {} {.}.pdf ::: *fastq # use ::: %prog run "zcat {} > {.}" ::: *.gz # quote redirection %prog run < commands.list # run a list of commands """ p = OptionParser(run.__doc__) p.set_grid_opts() p.set_params(prog="grid") opts, args = p.parse_args(args) if len(args) == 0: sys.exit(not p.print_help()) sep = ":::" if sep in args: sepidx = args.index(sep) filenames = args[sepidx + 1:] args = args[:sepidx] if not filenames: filenames = [""] else: filenames = sys.stdin if not sys.stdin.isatty() else [""] cmd = " ".join(args) cmds = [] if filenames else [(cmd, None)] for i, filename in enumerate(filenames): filename = filename.strip() noextname = filename.rsplit(".", 1)[0] prefix, basename = op.split(filename) basenoextname = basename.rsplit(".", 1)[0] basefirstname = basename.split(".")[0] firstname = op.join(prefix, basefirstname) ncmd = cmd if "{" in ncmd: ncmd = ncmd.replace("{}", filename) else: ncmd += " " + filename ncmd = ncmd.replace("{.}", noextname) ncmd = ncmd.replace("{_}", firstname) ncmd = ncmd.replace("{/}", basename) ncmd = ncmd.replace("{/.}", basenoextname) ncmd = ncmd.replace("{/_}", basefirstname) ncmd = ncmd.replace("{#}", str(i)) outfile = None if ">" in ncmd: ncmd, outfile = ncmd.split(">", 1) ncmd, outfile = ncmd.strip(), outfile.strip() ncmd = ncmd.strip() cmds.append((ncmd, outfile)) for ncmd, outfile in cmds: p = GridProcess(ncmd, outfile=outfile, extra_opts=opts.extra, grid_opts=opts) p.start()
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%prog run command ::: file1 file2 Parallelize a set of commands on grid. The syntax is modeled after GNU parallel <http://www.gnu.org/s/parallel/man.html#options> {} - input line {.} - input line without extension {_} - input line first part {/} - basename of input line {/.} - basename of input line without extension {/_} - basename of input line first part {#} - sequence number of job to run ::: - Use arguments from the command line as input source instead of stdin (standard input). If file name is `t/example.tar.gz`, then, {} is "t/example.tar.gz", {.} is "t/example.tar", {_} is "t/example" {/} is "example.tar.gz", {/.} is "example.tar", {/_} is "example" A few examples: ls -1 *.fastq | %prog run process {} {.}.pdf # use stdin %prog run process {} {.}.pdf ::: *fastq # use ::: %prog run "zcat {} > {.}" ::: *.gz # quote redirection %prog run < commands.list # run a list of commands
[ "%prog", "run", "command", ":::", "file1", "file2" ]
python
train
wind-python/windpowerlib
windpowerlib/modelchain.py
https://github.com/wind-python/windpowerlib/blob/421b316139743311b7cb68a69f6b53d2665f7e23/windpowerlib/modelchain.py#L247-L317
def wind_speed_hub(self, weather_df): r""" Calculates the wind speed at hub height. The method specified by the parameter `wind_speed_model` is used. Parameters ---------- weather_df : pandas.DataFrame DataFrame with time series for wind speed `wind_speed` in m/s and roughness length `roughness_length` in m. The columns of the DataFrame are a MultiIndex where the first level contains the variable name (e.g. wind_speed) and the second level contains the height at which it applies (e.g. 10, if it was measured at a height of 10 m). See documentation of :func:`ModelChain.run_model` for an example on how to create the weather_df DataFrame. Returns ------- wind_speed_hub : pandas.Series or numpy.array Wind speed in m/s at hub height. Notes ----- If `weather_df` contains wind speeds at different heights the given wind speed(s) closest to the hub height are used. """ if self.power_plant.hub_height in weather_df['wind_speed']: wind_speed_hub = weather_df['wind_speed'][ self.power_plant.hub_height] elif self.wind_speed_model == 'logarithmic': logging.debug('Calculating wind speed using logarithmic wind ' 'profile.') closest_height = weather_df['wind_speed'].columns[ min(range(len(weather_df['wind_speed'].columns)), key=lambda i: abs(weather_df['wind_speed'].columns[i] - self.power_plant.hub_height))] wind_speed_hub = wind_speed.logarithmic_profile( weather_df['wind_speed'][closest_height], closest_height, self.power_plant.hub_height, weather_df['roughness_length'].iloc[:, 0], self.obstacle_height) elif self.wind_speed_model == 'hellman': logging.debug('Calculating wind speed using hellman equation.') closest_height = weather_df['wind_speed'].columns[ min(range(len(weather_df['wind_speed'].columns)), key=lambda i: abs(weather_df['wind_speed'].columns[i] - self.power_plant.hub_height))] wind_speed_hub = wind_speed.hellman( weather_df['wind_speed'][closest_height], closest_height, self.power_plant.hub_height, weather_df['roughness_length'].iloc[:, 0], self.hellman_exp) elif self.wind_speed_model == 'interpolation_extrapolation': logging.debug('Calculating wind speed using linear inter- or ' 'extrapolation.') wind_speed_hub = tools.linear_interpolation_extrapolation( weather_df['wind_speed'], self.power_plant.hub_height) elif self.wind_speed_model == 'log_interpolation_extrapolation': logging.debug('Calculating wind speed using logarithmic inter- or ' 'extrapolation.') wind_speed_hub = tools.logarithmic_interpolation_extrapolation( weather_df['wind_speed'], self.power_plant.hub_height) else: raise ValueError("'{0}' is an invalid value. ".format( self.wind_speed_model) + "`wind_speed_model` must be " "'logarithmic', 'hellman', 'interpolation_extrapolation' " + "or 'log_interpolation_extrapolation'.") return wind_speed_hub
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r""" Calculates the wind speed at hub height. The method specified by the parameter `wind_speed_model` is used. Parameters ---------- weather_df : pandas.DataFrame DataFrame with time series for wind speed `wind_speed` in m/s and roughness length `roughness_length` in m. The columns of the DataFrame are a MultiIndex where the first level contains the variable name (e.g. wind_speed) and the second level contains the height at which it applies (e.g. 10, if it was measured at a height of 10 m). See documentation of :func:`ModelChain.run_model` for an example on how to create the weather_df DataFrame. Returns ------- wind_speed_hub : pandas.Series or numpy.array Wind speed in m/s at hub height. Notes ----- If `weather_df` contains wind speeds at different heights the given wind speed(s) closest to the hub height are used.
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python
train
splunk/splunk-sdk-python
examples/analytics/bottle.py
https://github.com/splunk/splunk-sdk-python/blob/a245a4eeb93b3621730418008e31715912bcdcd8/examples/analytics/bottle.py#L1630-L1641
def auth_basic(check, realm="private", text="Access denied"): ''' Callback decorator to require HTTP auth (basic). TODO: Add route(check_auth=...) parameter. ''' def decorator(func): def wrapper(*a, **ka): user, password = request.auth or (None, None) if user is None or not check(user, password): response.headers['WWW-Authenticate'] = 'Basic realm="%s"' % realm return HTTPError(401, text) return func(*a, **ka) return wrapper return decorator
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Callback decorator to require HTTP auth (basic). TODO: Add route(check_auth=...) parameter.
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python
train
ONSdigital/sdc-rabbit
sdc/rabbit/consumers.py
https://github.com/ONSdigital/sdc-rabbit/blob/985adfdb09cf1b263a1f311438baeb42cbcb503a/sdc/rabbit/consumers.py#L275-L282
def reject_message(self, delivery_tag, requeue=False, **kwargs): """Reject the message delivery from RabbitMQ by sending a Basic.Reject RPC method for the delivery tag. :param int delivery_tag: The delivery tag from the Basic.Deliver frame """ logger.info('Rejecting message', delivery_tag=delivery_tag, **kwargs) self._channel.basic_reject(delivery_tag, requeue=requeue)
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Reject the message delivery from RabbitMQ by sending a Basic.Reject RPC method for the delivery tag. :param int delivery_tag: The delivery tag from the Basic.Deliver frame
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python
train
PythonCharmers/python-future
src/future/backports/email/_header_value_parser.py
https://github.com/PythonCharmers/python-future/blob/c423752879acc05eebc29b0bb9909327bd5c7308/src/future/backports/email/_header_value_parser.py#L2259-L2287
def get_group(value): """ group = display-name ":" [group-list] ";" [CFWS] """ group = Group() token, value = get_display_name(value) if not value or value[0] != ':': raise errors.HeaderParseError("expected ':' at end of group " "display name but found '{}'".format(value)) group.append(token) group.append(ValueTerminal(':', 'group-display-name-terminator')) value = value[1:] if value and value[0] == ';': group.append(ValueTerminal(';', 'group-terminator')) return group, value[1:] token, value = get_group_list(value) group.append(token) if not value: group.defects.append(errors.InvalidHeaderDefect( "end of header in group")) if value[0] != ';': raise errors.HeaderParseError( "expected ';' at end of group but found {}".format(value)) group.append(ValueTerminal(';', 'group-terminator')) value = value[1:] if value and value[0] in CFWS_LEADER: token, value = get_cfws(value) group.append(token) return group, value
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group = display-name ":" [group-list] ";" [CFWS]
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python
train
tjomasc/snekbol
snekbol/document.py
https://github.com/tjomasc/snekbol/blob/0b491aa96e0b1bd09e6c80cfb43807dd8a876c83/snekbol/document.py#L270-L277
def _get_triplet_value_list(self, graph, identity, rdf_type): """ Get a list of values from RDF triples when more than one may be present """ values = [] for elem in graph.objects(identity, rdf_type): values.append(elem.toPython()) return values
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Get a list of values from RDF triples when more than one may be present
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python
train
raiden-network/raiden
raiden/utils/signing.py
https://github.com/raiden-network/raiden/blob/407ba15c72074e9de88771d6b9661ff4dc36bef5/raiden/utils/signing.py#L9-L23
def pack_data(abi_types, values) -> bytes: """Normalize data and pack them into a byte array""" if len(abi_types) != len(values): raise ValueError( "Length mismatch between provided abi types and values. Got " "{0} types and {1} values.".format(len(abi_types), len(values)), ) normalized_values = map_abi_data([abi_address_to_hex], abi_types, values) return decode_hex(''.join( remove_0x_prefix(hex_encode_abi_type(abi_type, value)) for abi_type, value in zip(abi_types, normalized_values) ))
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Normalize data and pack them into a byte array
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python
train
qubell/contrib-python-qubell-client
qubell/api/private/organization.py
https://github.com/qubell/contrib-python-qubell-client/blob/4586ea11d5103c2ff9607d3ed922b5a0991b8845/qubell/api/private/organization.py#L309-L329
def instance(self, id=None, application=None, name=None, revision=None, environment=None, parameters=None, submodules=None, destroyInterval=None): """ Smart method. It does everything, to return Instance with given parameters within the application. If instance found running and given parameters are actual: return it. If instance found, but parameters differs - reconfigure instance with new parameters. If instance not found: launch instance with given parameters. Return: Instance object. """ instance = self.get_or_create_instance(id, application, revision, environment, name, parameters, submodules, destroyInterval) reconfigure = False # if found: # if revision and revision is not found.revision: # reconfigure = True # if parameters and parameters is not found.parameters: # reconfigure = True # We need to reconfigure instance if reconfigure: instance.reconfigure(revision=revision, parameters=parameters) return instance
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Smart method. It does everything, to return Instance with given parameters within the application. If instance found running and given parameters are actual: return it. If instance found, but parameters differs - reconfigure instance with new parameters. If instance not found: launch instance with given parameters. Return: Instance object.
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python
train
zhanglab/psamm
psamm/massconsistency.py
https://github.com/zhanglab/psamm/blob/dc427848c4f9d109ca590f0afa024c63b685b3f4/psamm/massconsistency.py#L44-L71
def is_consistent(database, solver, exchange=set(), zeromass=set()): """Try to assign a positive mass to each compound Return True if successful. The masses are simply constrained by m_i > 1 and finding a solution under these conditions proves that the database is mass consistent. """ prob = solver.create_problem() compound_set = _non_localized_compounds(database) mass_compounds = compound_set.difference(zeromass) # Define mass variables m = prob.namespace(mass_compounds, lower=1) prob.set_objective(m.sum(mass_compounds)) # Define constraints massbalance_lhs = {reaction: 0 for reaction in database.reactions} for (compound, reaction), value in iteritems(database.matrix): if compound not in zeromass: mass = m(compound.in_compartment(None)) massbalance_lhs[reaction] += mass * value for reaction, lhs in iteritems(massbalance_lhs): if reaction not in exchange: prob.add_linear_constraints(lhs == 0) result = prob.solve_unchecked(lp.ObjectiveSense.Minimize) return result.success
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Try to assign a positive mass to each compound Return True if successful. The masses are simply constrained by m_i > 1 and finding a solution under these conditions proves that the database is mass consistent.
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python
train
InformaticsMatters/pipelines-utils
src/python/pipelines_utils/utils.py
https://github.com/InformaticsMatters/pipelines-utils/blob/058aa6eceeff28c4ae402f6f58c58720bff0298e/src/python/pipelines_utils/utils.py#L30-L32
def round_sig(x, sig): """Round the number to the specified number of significant figures""" return round(x, sig - int(floor(log10(abs(x)))) - 1)
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Round the number to the specified number of significant figures
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python
train
elliterate/capybara.py
capybara/selector/selector.py
https://github.com/elliterate/capybara.py/blob/0c6ae449cc37e4445ec3cd6af95674533beedc6c/capybara/selector/selector.py#L141-L157
def node_filter(self, name, **kwargs): """ Returns a decorator function for adding a node filter. Args: name (str): The name of the filter. **kwargs: Variable keyword arguments for the filter. Returns: Callable[[Callable[[Element, Any], bool]]]: A decorator function for adding a node filter. """ def decorator(func): self.filters[name] = NodeFilter(name, func, **kwargs) return decorator
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Returns a decorator function for adding a node filter. Args: name (str): The name of the filter. **kwargs: Variable keyword arguments for the filter. Returns: Callable[[Callable[[Element, Any], bool]]]: A decorator function for adding a node filter.
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python
test
Arubacloud/pyArubaCloud
ArubaCloud/PyArubaAPI.py
https://github.com/Arubacloud/pyArubaCloud/blob/ec4aecd8ca342b1e1a4f16b7cc87cb5e697cfcd4/ArubaCloud/PyArubaAPI.py#L309-L323
def get_package_id(self, name): """ Retrieve the smart package id given is English name @param (str) name: the Aruba Smart package size name, ie: "small", "medium", "large", "extra large". @return: The package id that depends on the Data center and the size choosen. """ json_scheme = self.gen_def_json_scheme('GetPreConfiguredPackages', dict(HypervisorType=4)) json_obj = self.call_method_post(method='GetPreConfiguredPackages ', json_scheme=json_scheme) for package in json_obj['Value']: packageId = package['PackageID'] for description in package['Descriptions']: languageID = description['LanguageID'] packageName = description['Text'] if languageID == 2 and packageName.lower() == name.lower(): return packageId
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Retrieve the smart package id given is English name @param (str) name: the Aruba Smart package size name, ie: "small", "medium", "large", "extra large". @return: The package id that depends on the Data center and the size choosen.
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python
train
DataBiosphere/toil
src/toil/common.py
https://github.com/DataBiosphere/toil/blob/a8252277ff814e7bee0971139c2344f88e44b644/src/toil/common.py#L1337-L1349
def getFileSystemSize(dirPath): """ Return the free space, and total size of the file system hosting `dirPath`. :param str dirPath: A valid path to a directory. :return: free space and total size of file system :rtype: tuple """ assert os.path.exists(dirPath) diskStats = os.statvfs(dirPath) freeSpace = diskStats.f_frsize * diskStats.f_bavail diskSize = diskStats.f_frsize * diskStats.f_blocks return freeSpace, diskSize
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Return the free space, and total size of the file system hosting `dirPath`. :param str dirPath: A valid path to a directory. :return: free space and total size of file system :rtype: tuple
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python
train
morse-talk/morse-talk
morse_talk/plot.py
https://github.com/morse-talk/morse-talk/blob/71e09ace0aa554d28cada5ee658e43758305b8fa/morse_talk/plot.py#L56-L71
def plot(message, duration=1, ax=None): """ Plot a message Returns: ax a Matplotlib Axe """ lst_bin = _encode_binary(message) x, y = _create_x_y(lst_bin, duration) ax = _create_ax(ax) ax.plot(x, y, linewidth=2.0) delta_y = 0.1 ax.set_ylim(-delta_y, 1 + delta_y) ax.set_yticks([0, 1]) delta_x = 0.5 * duration ax.set_xlim(-delta_x, len(lst_bin) * duration + delta_x) return ax
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Plot a message Returns: ax a Matplotlib Axe
[ "Plot", "a", "message" ]
python
train
MacHu-GWU/crawlib-project
crawlib/spider.py
https://github.com/MacHu-GWU/crawlib-project/blob/241516f2a7a0a32c692f7af35a1f44064e8ce1ab/crawlib/spider.py#L24-L114
def execute_one_to_many_job(parent_class=None, get_unfinished_kwargs=None, get_unfinished_limit=None, parser_func=None, parser_func_kwargs=None, build_url_func_kwargs=None, downloader_func=None, downloader_func_kwargs=None, post_process_response_func=None, post_process_response_func_kwargs=None, process_item_func_kwargs=None, logger=None, sleep_time=None): """ A standard one-to-many crawling workflow. :param parent_class: :param get_unfinished_kwargs: :param get_unfinished_limit: :param parser_func: html parser function. :param parser_func_kwargs: other keyword arguments for ``parser_func`` :param build_url_func_kwargs: other keyword arguments for ``parent_class().build_url(**build_url_func_kwargs)`` :param downloader_func: a function that taking ``url`` as first arg, make http request and return response/html. :param downloader_func_kwargs: other keyword arguments for ``downloader_func`` :param post_process_response_func: a callback function taking response/html as first argument. You can put any logic in it. For example, you can make it sleep if you detect that you got banned. :param post_process_response_func_kwargs: other keyword arguments for ``post_process_response_func`` :param process_item_func_kwargs: other keyword arguments for ``ParseResult().process_item(**process_item_func_kwargs)`` :param logger: :param sleep_time: default 0, wait time before making each request. """ # prepare arguments get_unfinished_kwargs = prepare_kwargs(get_unfinished_kwargs) parser_func_kwargs = prepare_kwargs(parser_func_kwargs) build_url_func_kwargs = prepare_kwargs(build_url_func_kwargs) downloader_func_kwargs = prepare_kwargs(downloader_func_kwargs) post_process_response_func_kwargs = prepare_kwargs( post_process_response_func_kwargs) process_item_func_kwargs = prepare_kwargs(process_item_func_kwargs) if post_process_response_func is None: def post_process_response_func(response, **kwargs): pass if not isinstance(logger, SpiderLogger): raise TypeError if sleep_time is None: sleep_time = 0 # do the real job query_set = parent_class.get_all_unfinished(**get_unfinished_kwargs) if get_unfinished_limit is not None: query_set = query_set.limit(get_unfinished_limit) todo = list(query_set) logger.log_todo_volumn(todo) for parent_instance in todo: url = parent_instance.build_url(**build_url_func_kwargs) logger.log_to_crawl_url(url) logger.log_sleeper(sleep_time) time.sleep(sleep_time) try: response_or_html = downloader_func(url, **downloader_func_kwargs) if isinstance(response_or_html, string_types): parser_func_kwargs["html"] = response_or_html else: parser_func_kwargs["response"] = response_or_html post_process_response_func( response_or_html, **post_process_response_func_kwargs) except Exception as e: logger.log_error(e) continue try: parse_result = parser_func( parent=parent_instance, **parser_func_kwargs ) parse_result.process_item(**process_item_func_kwargs) logger.log_status(parse_result) except Exception as e: logger.log_error(e) continue
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A standard one-to-many crawling workflow. :param parent_class: :param get_unfinished_kwargs: :param get_unfinished_limit: :param parser_func: html parser function. :param parser_func_kwargs: other keyword arguments for ``parser_func`` :param build_url_func_kwargs: other keyword arguments for ``parent_class().build_url(**build_url_func_kwargs)`` :param downloader_func: a function that taking ``url`` as first arg, make http request and return response/html. :param downloader_func_kwargs: other keyword arguments for ``downloader_func`` :param post_process_response_func: a callback function taking response/html as first argument. You can put any logic in it. For example, you can make it sleep if you detect that you got banned. :param post_process_response_func_kwargs: other keyword arguments for ``post_process_response_func`` :param process_item_func_kwargs: other keyword arguments for ``ParseResult().process_item(**process_item_func_kwargs)`` :param logger: :param sleep_time: default 0, wait time before making each request.
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python
train
heikomuller/sco-datastore
scodata/image.py
https://github.com/heikomuller/sco-datastore/blob/7180a6b51150667e47629da566aedaa742e39342/scodata/image.py#L711-L738
def to_dict(self, img_coll): """Create a Json-like dictionary for image group. Extends the basic object with an array of image identifiers. Parameters ---------- img_coll : ImageGroupHandle Returns ------- (JSON) Json-like object, i.e., dictionary. """ # Get the basic Json object from the super class json_obj = super(DefaultImageGroupManager, self).to_dict(img_coll) # Add list of images as Json array images = [] for img_group in img_coll.images: images.append({ 'identifier' : img_group.identifier, 'folder' : img_group.folder, 'name' : img_group.name }) json_obj['images'] = images # Transform dictionary of options into list of elements, one per typed # attribute in the options set. json_obj['options'] = attribute.attributes_to_dict(img_coll.options) return json_obj
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Create a Json-like dictionary for image group. Extends the basic object with an array of image identifiers. Parameters ---------- img_coll : ImageGroupHandle Returns ------- (JSON) Json-like object, i.e., dictionary.
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python
train
mrstephenneal/dirutility
dirutility/system.py
https://github.com/mrstephenneal/dirutility/blob/339378659e2d7e09c53acfc51c5df745bb0cd517/dirutility/system.py#L51-L62
def execute(self): """Execute a system command.""" if self._decode_output: # Capture and decode system output with Popen(self.command, shell=True, stdout=PIPE) as process: self._output = [i.decode("utf-8").strip() for i in process.stdout] self._success = True else: # Execute without capturing output os.system(self.command) self._success = True return self
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Execute a system command.
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python
train
klahnakoski/pyLibrary
jx_base/language.py
https://github.com/klahnakoski/pyLibrary/blob/fa2dcbc48fda8d26999baef400e9a98149e0b982/jx_base/language.py#L125-L134
def is_op(call, op): """ :param call: The specific operator instance (a method call) :param op: The the operator we are testing against :return: isinstance(call, op), but faster """ try: return call.id == op.id except Exception as e: return False
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:param call: The specific operator instance (a method call) :param op: The the operator we are testing against :return: isinstance(call, op), but faster
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python
train
radical-cybertools/radical.entk
src/radical/entk/execman/rp/task_processor.py
https://github.com/radical-cybertools/radical.entk/blob/945f6c93c9a62db90ad191b306418d5c1cdd9d24/src/radical/entk/execman/rp/task_processor.py#L10-L91
def resolve_placeholders(path, placeholder_dict): """ **Purpose**: Substitute placeholders in staging attributes of a Task with actual paths to the corresponding tasks. :arguments: :path: string describing the staging paths, possibly containing a placeholder :placeholder_dict: dictionary holding the values for placeholders """ try: if isinstance(path, unicode): path = str(path) if not isinstance(path, str): raise TypeError(expected_type=str, actual_type=type(path)) if '$' not in path: return path # Extract placeholder from path if len(path.split('>')) == 1: placeholder = path.split('/')[0] else: if path.split('>')[0].strip().startswith('$'): placeholder = path.split('>')[0].strip().split('/')[0] else: placeholder = path.split('>')[1].strip().split('/')[0] # SHARED if placeholder == "$SHARED": return path.replace(placeholder, 'pilot://') # Expected placeholder format: # $Pipeline_{pipeline.uid}_Stage_{stage.uid}_Task_{task.uid} broken_placeholder = placeholder.split('/')[0].split('_') if not len(broken_placeholder) == 6: raise ValueError( obj='placeholder', attribute='task', expected_value='$Pipeline_(pipeline_name)_Stage_(stage_name)_Task_(task_name) or $SHARED', actual_value=broken_placeholder) pipeline_name = broken_placeholder[1] stage_name = broken_placeholder[3] task_name = broken_placeholder[5] resolved_placeholder = None if pipeline_name in placeholder_dict.keys(): if stage_name in placeholder_dict[pipeline_name].keys(): if task_name in placeholder_dict[pipeline_name][stage_name].keys(): resolved_placeholder = path.replace(placeholder, placeholder_dict[ pipeline_name][stage_name][task_name]['path']) else: logger.warning('%s not assigned to any task in Stage %s Pipeline %s' % (task_name, stage_name, pipeline_name)) else: logger.warning('%s not assigned to any Stage in Pipeline %s' % ( stage_name, pipeline_name)) else: logger.warning('%s not assigned to any Pipeline' % (pipeline_name)) if not resolved_placeholder: logger.warning('No placeholder could be found for task name %s \ stage name %s and pipeline name %s. Please be sure to \ use object names and not uids in your references,i.e, \ $Pipeline_(pipeline_name)_Stage_(stage_name)_Task_(task_name)') raise ValueError( obj='placeholder', attribute='task', expected_value='$Pipeline_(pipeline_name)_Stage_(stage_name)_Task_(task_name) or $SHARED', actual_value=broken_placeholder) return resolved_placeholder except Exception, ex: logger.exception('Failed to resolve placeholder %s, error: %s' %(path, ex)) raise
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python
train
youversion/crony
crony/crony.py
https://github.com/youversion/crony/blob/c93d14b809a2e878f1b9d6d53d5a04947896583b/crony/crony.py#L232-L290
def main(): """Entry point for running crony. 1. If a --cronitor/-c is specified, a "run" ping is sent to cronitor. 2. The argument string passed to crony is ran. 3. Next steps depend on the exit code of the command ran. * If the exit status is 0 and a --cronitor/-c is specified, a "complete" ping is sent to cronitor. * If the exit status is greater than 0, a message is sent to Sentry with the output captured from the script's exit. * If the exit status is great than 0 and --cronitor/-c is specified, a "fail" ping is sent to cronitor. """ parser = argparse.ArgumentParser( description='Monitor your crons with cronitor.io & sentry.io', epilog='https://github.com/youversion/crony', prog='crony' ) parser.add_argument('-c', '--cronitor', action='store', help='Cronitor link identifier. This can be found in your Cronitor unique' ' ping URL right after https://cronitor.link/') parser.add_argument('-e', '--venv', action='store', help='Path to virtualenv to source before running script. May be passed' ' as an argument or loaded from an environment variable or config file.') parser.add_argument('-d', '--cd', action='store', help='If the script needs ran in a specific directory, than can be passed' ' or cd can be ran prior to running crony.') parser.add_argument('-l', '--log', action='store', help='Log file to direct stdout of script run to. Can be passed or ' 'defined in config file with "log_file"') parser.add_argument('-o', '--config', action='store', help='Path to a crony config file to use.') parser.add_argument('-p', '--path', action='store', help='Paths to append to the PATH environment variable before running. ' ' Can be passed as an argument or loaded from config file.') parser.add_argument('-s', '--dsn', action='store', help='Sentry DSN. May be passed or loaded from an environment variable ' 'or a config file.') parser.add_argument('-t', '--timeout', action='store', default=10, help='Timeout to use when' ' sending requests to Cronitor', type=int) parser.add_argument('-v', '--verbose', action='store_true', help='Increase level of verbosity' ' output by crony') parser.add_argument('--version', action='store_true', help='Output crony version # and exit') parser.add_argument('cmd', nargs=argparse.REMAINDER, help='Command to run and monitor') cc = CommandCenter(parser.parse_args()) sys.exit(cc.log(*cc.func()))
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[ "Entry", "point", "for", "running", "crony", "." ]
python
train
elifesciences/elife-tools
elifetools/parseJATS.py
https://github.com/elifesciences/elife-tools/blob/4b9e38cbe485c61a4ed7cbd8970c6b318334fd86/elifetools/parseJATS.py#L1699-L1713
def correspondence(soup): """ Find the corresp tags included in author-notes for primary correspondence """ correspondence = [] author_notes_nodes = raw_parser.author_notes(soup) if author_notes_nodes: corresp_nodes = raw_parser.corresp(author_notes_nodes) for tag in corresp_nodes: correspondence.append(tag.text) return correspondence
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Find the corresp tags included in author-notes for primary correspondence
[ "Find", "the", "corresp", "tags", "included", "in", "author", "-", "notes", "for", "primary", "correspondence" ]
python
train
awslabs/aws-shell
awsshell/shellcomplete.py
https://github.com/awslabs/aws-shell/blob/8950f03d9d720879890af6c11537b8f9789ce5a9/awsshell/shellcomplete.py#L53-L56
def change_profile(self, profile_name): """Change the profile used for server side completions.""" self._server_side_completer = self._create_server_side_completer( session=botocore.session.Session(profile=profile_name))
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Change the profile used for server side completions.
[ "Change", "the", "profile", "used", "for", "server", "side", "completions", "." ]
python
train
chapel-lang/sphinxcontrib-chapeldomain
sphinxcontrib/chapeldomain.py
https://github.com/chapel-lang/sphinxcontrib-chapeldomain/blob/00970fe1b3aed5deb1186bec19bf0912d2f92853/sphinxcontrib/chapeldomain.py#L975-L989
def _make_module_refnode(self, builder, fromdocname, name, contnode): """Helper function to generate new xref node based on current environment. """ # Get additional info for modules. docname, synopsis, platform, deprecated = self.data['modules'][name] title = name if synopsis: title += ': ' + synopsis if deprecated: title += _(' (deprecated)') if platform: title += ' (' + platform + ')' return make_refnode(builder, fromdocname, docname, 'module-' + name, contnode, title)
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Helper function to generate new xref node based on current environment.
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python
train
dtmilano/AndroidViewClient
src/com/dtmilano/android/viewclient.py
https://github.com/dtmilano/AndroidViewClient/blob/7e6e83fde63af99e5e4ab959712ecf94f9881aa2/src/com/dtmilano/android/viewclient.py#L1235-L1249
def openQuickSettings(self): ''' Opens the Quick Settings shade. ''' # the tablet has a different Notification/Quick Settings bar depending on x w23 = 2 * self.device.display['width'] / 3 s = (w23, 0) e = (w23, self.device.display['height']/2) self.device.drag(s, e, 500, 20, -1) self.vc.sleep(1) if self.vc.getSdkVersion() >= 20: self.device.drag(s, e, 500, 20, -1) self.vc.sleep(1) self.vc.dump(-1)
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Opens the Quick Settings shade.
[ "Opens", "the", "Quick", "Settings", "shade", "." ]
python
train
kashifrazzaqui/again
again/statemachine.py
https://github.com/kashifrazzaqui/again/blob/09cfbda7650d44447dbb0b27780835e9236741ea/again/statemachine.py#L122-L126
def can(self, event): """ returns a list of states that can result from processing this event """ return [t.new_state for t in self._transitions if t.event.equals(event)]
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returns a list of states that can result from processing this event
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python
train
koenedaele/skosprovider
skosprovider/skos.py
https://github.com/koenedaele/skosprovider/blob/7304a37953978ca8227febc2d3cc2b2be178f215/skosprovider/skos.py#L249-L262
def _sortkey(self, key='uri', language='any'): ''' Provide a single sortkey for this conceptscheme. :param string key: Either `uri`, `label` or `sortlabel`. :param string language: The preferred language to receive the label in if key is `label` or `sortlabel`. This should be a valid IANA language tag. :rtype: :class:`str` ''' if key == 'uri': return self.uri else: l = label(self.labels, language, key == 'sortlabel') return l.label.lower() if l else ''
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Provide a single sortkey for this conceptscheme. :param string key: Either `uri`, `label` or `sortlabel`. :param string language: The preferred language to receive the label in if key is `label` or `sortlabel`. This should be a valid IANA language tag. :rtype: :class:`str`
[ "Provide", "a", "single", "sortkey", "for", "this", "conceptscheme", "." ]
python
valid
jasonrbriggs/stomp.py
stomp/adapter/multicast.py
https://github.com/jasonrbriggs/stomp.py/blob/643843c5fbf25fd24339dd0e69a9411c3d8b94c7/stomp/adapter/multicast.py#L135-L142
def disconnect(self, receipt=None, headers=None, **keyword_headers): """ :param str receipt: :param dict headers: :param keyword_headers: """ Protocol12.disconnect(self, receipt, headers, **keyword_headers) self.transport.stop()
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:param str receipt: :param dict headers: :param keyword_headers:
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python
train
vingd/encrypted-pickle-python
encryptedpickle/encryptedpickle.py
https://github.com/vingd/encrypted-pickle-python/blob/7656233598e02e65971f69e11849a0f288b2b2a5/encryptedpickle/encryptedpickle.py#L636-L642
def _read_version(self, data): '''Read header version from data''' version = ord(data[0]) if version not in self.VERSIONS: raise Exception('Version not defined: %d' % version) return version
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Read header version from data
[ "Read", "header", "version", "from", "data" ]
python
valid
carta/ldap_tools
src/ldap_tools/key.py
https://github.com/carta/ldap_tools/blob/7c039304a5abaf836c7afc35cf068b4471306264/src/ldap_tools/key.py#L214-L222
def list(config): # pragma: no cover """List SSH public key(s) from LDAP.""" client = Client() client.prepare_connection() key_api = API(client) for key, values in key_api.get_keys_from_ldap().items(): print("{}: ".format(key)) for value in [v.decode() for v in values]: print("\t - {}".format(value))
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List SSH public key(s) from LDAP.
[ "List", "SSH", "public", "key", "(", "s", ")", "from", "LDAP", "." ]
python
train
Raynes/quarantine
quarantine/cdc.py
https://github.com/Raynes/quarantine/blob/742a318fcb7d34dbdf4fac388daff03a36872d8b/quarantine/cdc.py#L38-L41
def create_env(self): """Create a virtual environment.""" virtualenv(self.env, _err=sys.stderr) os.mkdir(self.env_bin)
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Create a virtual environment.
[ "Create", "a", "virtual", "environment", "." ]
python
train
zeromake/aiko
aiko/response.py
https://github.com/zeromake/aiko/blob/53b246fa88652466a9e38ac3d1a99a6198195b0f/aiko/response.py#L197-L202
def status(self, status: int) -> None: """ 设置响应状态 """ self._status = status self._message = STATUS_CODES[status]
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设置响应状态
[ "设置响应状态" ]
python
train
mardiros/pyshop
pyshop/models.py
https://github.com/mardiros/pyshop/blob/b42510b9c3fa16e0e5710457401ac38fea5bf7a0/pyshop/models.py#L866-L885
def by_filename(cls, session, release, filename): """ Get a release file for a given release and a given filename. :param session: SQLAlchemy session :type session: :class:`sqlalchemy.Session` :param release: release :type release: :class:`pyshop.models.Release` :param filename: filename of the release file :type filename: unicode :return: release file :rtype: :class:`pyshop.models.ReleaseFile` """ return cls.first(session, where=(ReleaseFile.release_id == release.id, ReleaseFile.filename == filename, ))
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Get a release file for a given release and a given filename. :param session: SQLAlchemy session :type session: :class:`sqlalchemy.Session` :param release: release :type release: :class:`pyshop.models.Release` :param filename: filename of the release file :type filename: unicode :return: release file :rtype: :class:`pyshop.models.ReleaseFile`
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python
train
django-haystack/pysolr
pysolr.py
https://github.com/django-haystack/pysolr/blob/ee28b39324fa21a99842d297e313c1759d8adbd2/pysolr.py#L995-L1016
def optimize(self, commit=True, waitFlush=None, waitSearcher=None, maxSegments=None, handler='update'): """ Tells Solr to streamline the number of segments used, essentially a defragmentation operation. Optionally accepts ``maxSegments``. Default is ``None``. Optionally accepts ``waitFlush``. Default is ``None``. Optionally accepts ``waitSearcher``. Default is ``None``. Usage:: solr.optimize() """ if maxSegments: msg = '<optimize maxSegments="%d" />' % maxSegments else: msg = '<optimize />' return self._update(msg, commit=commit, waitFlush=waitFlush, waitSearcher=waitSearcher, handler=handler)
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Tells Solr to streamline the number of segments used, essentially a defragmentation operation. Optionally accepts ``maxSegments``. Default is ``None``. Optionally accepts ``waitFlush``. Default is ``None``. Optionally accepts ``waitSearcher``. Default is ``None``. Usage:: solr.optimize()
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python
train
molmod/molmod
molmod/io/number_state.py
https://github.com/molmod/molmod/blob/a7b5b4364ed514ad4c465856c05b5eda1cb561e0/molmod/io/number_state.py#L260-L325
def load(self, filename, subset=None): """Load data into the registered fields Argument: | ``filename`` -- the filename to read from Optional argument: | ``subset`` -- a list of field names that are read from the file. If not given, all data is read from the file. """ with open(filename, "r") as f: name = None num_names = 0 while True: # read a header line line = f.readline() if len(line) == 0: break # process the header line words = line.split() name = words[0] attr = self._fields.get(name) if attr is None: raise FileFormatError("Wrong header: unknown field %s" % name) if not words[1].startswith("kind="): raise FileFormatError("Malformatted array header line. (kind)") kind = words[1][5:] expected_kind = attr.get_kind(attr.get()) if kind != expected_kind: raise FileFormatError("Wrong header: kind of field %s does not match. Got %s, expected %s" % (name, kind, expected_kind)) skip = ((subset is not None) and (name not in subset)) print(words) if (words[2].startswith("shape=(") and words[2].endswith(")")): if not isinstance(attr, ArrayAttr): raise FileFormatError("field '%s' is not an array." % name) shape = words[2][7:-1] if shape[-1] == ', ': shape = shape[:-1] try: shape = tuple(int(word) for word in shape.split(",")) except ValueError: raise FileFormatError("Malformatted array header. (shape)") expected_shape = attr.get().shape if shape != expected_shape: raise FileFormatError("Wrong header: shape of field %s does not match. Got %s, expected %s" % (name, shape, expected_shape)) attr.load(f, skip) elif words[2].startswith("value="): if not isinstance(attr, ScalarAttr): raise FileFormatError("field '%s' is not a single value." % name) if not skip: if kind == 'i': attr.set(int(words[2][6:])) else: attr.set(float(words[2][6:])) else: raise FileFormatError("Malformatted array header line. (shape/value)") num_names += 1 if num_names != len(self._fields) and subset is None: raise FileFormatError("Some fields are missing in the file.")
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Load data into the registered fields Argument: | ``filename`` -- the filename to read from Optional argument: | ``subset`` -- a list of field names that are read from the file. If not given, all data is read from the file.
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python
train
spyder-ide/spyder
spyder/plugins/projects/widgets/explorer.py
https://github.com/spyder-ide/spyder/blob/f76836ce1b924bcc4efd3f74f2960d26a4e528e0/spyder/plugins/projects/widgets/explorer.py#L154-L167
def delete(self, fnames=None): """Delete files""" if fnames is None: fnames = self.get_selected_filenames() multiple = len(fnames) > 1 yes_to_all = None for fname in fnames: if fname == self.proxymodel.path_list[0]: self.sig_delete_project.emit() else: yes_to_all = self.delete_file(fname, multiple, yes_to_all) if yes_to_all is not None and not yes_to_all: # Canceled break
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Delete files
[ "Delete", "files" ]
python
train
bokeh/bokeh
bokeh/embed/bundle.py
https://github.com/bokeh/bokeh/blob/dc8cf49e4e4302fd38537ad089ece81fbcca4737/bokeh/embed/bundle.py#L156-L167
def _use_gl(objs): ''' Whether a collection of Bokeh objects contains a plot requesting WebGL Args: objs (seq[Model or Document]) : Returns: bool ''' from ..models.plots import Plot return _any(objs, lambda obj: isinstance(obj, Plot) and obj.output_backend == "webgl")
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Whether a collection of Bokeh objects contains a plot requesting WebGL Args: objs (seq[Model or Document]) : Returns: bool
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python
train
YosaiProject/yosai
yosai/core/subject/subject.py
https://github.com/YosaiProject/yosai/blob/7f96aa6b837ceae9bf3d7387cd7e35f5ab032575/yosai/core/subject/subject.py#L348-L365
def has_role_collective(self, role_s, logical_operator=all): """ :param role_s: 1..N role identifier :type role_s: a Set of Strings :param logical_operator: indicates whether all or at least one permission check is true (any) :type: any OR all (from python standard library) :returns: a Boolean """ if self.authorized: return self.security_manager.has_role_collective(self.identifiers, role_s, logical_operator) else: msg = 'Cannot check permission when identifiers aren\'t set!' raise ValueError(msg)
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:param role_s: 1..N role identifier :type role_s: a Set of Strings :param logical_operator: indicates whether all or at least one permission check is true (any) :type: any OR all (from python standard library) :returns: a Boolean
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python
train
ttsteiger/cryptocompy
cryptocompy/price.py
https://github.com/ttsteiger/cryptocompy/blob/b0514079202587a5bfb3a4f2c871196315b9302e/cryptocompy/price.py#L7-L83
def get_current_price(fsyms, tsyms, e='all', try_conversion=True, full=False, format='raw'): """Get latest trading price or full trading information in display or raw format for the specified FROM/TO currency pairs. Args: fsyms: Single string or list of FROM symbols. tsyms: Single string or list of TO symbols. e: Default returns average price across all exchanges. Can be set to the name of a single exchange. try_conversion: If the crypto does not trade directly into the toSymbol requested, BTC will be used for conversion. If set to false, it will try to get values without using any conversion at all. full: Default of False returns only the latest price. True returns the following dictionary structure containing the full trading info: format: Default returns the 'RAW' format. Can be set to 'DISPLAY' format. Returns: Returns a dictionary containing the latest price pairs if full is set to false: {fsym1: {tsym1: ..., tsym2:..., ...}, fsym2: {...}, ...} or full trading info dictionaries for all the price pairs in the other case: {fsym1: {tsym1: {'CHANGE24HOUR': ..., 'CHANGEPCT24HOUR': ..., 'FLAGS': ..., 'FROMSYMBOL': ..., 'HIGH24HOUR': ..., 'LASTMARKET': ..., 'LASTTRADEID': ..., 'LASTUPDATE': ..., 'LASTVOLUME': ..., 'LASTVOLUMETO': ..., 'LOW24HOUR': ..., 'MARKET' ..., 'MKTCAP': ..., 'OPEN24HOUR': ..., 'PRICE': ..., 'SUPPLY': ..., 'TOSYMBOL': ..., 'TYPE': ..., 'VOLUME24HOUR': ..., 'VOLUME24HOURTO': ...}, tsym2: ..., ...}, fsym2: {...}, ...} """ # select API function based on 'full' parameter value if not full: func = 'pricemulti' else: func = 'pricemultifull' # convert single fsym and tsym input to single element lists if not isinstance(fsyms, list): fsyms = [fsyms] if not isinstance(tsyms, list): tsyms = [tsyms] # load data url = build_url(func, fsyms=fsyms, tsyms=tsyms, e=e, try_conversion=try_conversion) data = load_data(url) # select right format to return for full requests if full and format == 'raw': data = data['RAW'] elif full and format == 'display': data = data['DISPLAY'] return data
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Get latest trading price or full trading information in display or raw format for the specified FROM/TO currency pairs. Args: fsyms: Single string or list of FROM symbols. tsyms: Single string or list of TO symbols. e: Default returns average price across all exchanges. Can be set to the name of a single exchange. try_conversion: If the crypto does not trade directly into the toSymbol requested, BTC will be used for conversion. If set to false, it will try to get values without using any conversion at all. full: Default of False returns only the latest price. True returns the following dictionary structure containing the full trading info: format: Default returns the 'RAW' format. Can be set to 'DISPLAY' format. Returns: Returns a dictionary containing the latest price pairs if full is set to false: {fsym1: {tsym1: ..., tsym2:..., ...}, fsym2: {...}, ...} or full trading info dictionaries for all the price pairs in the other case: {fsym1: {tsym1: {'CHANGE24HOUR': ..., 'CHANGEPCT24HOUR': ..., 'FLAGS': ..., 'FROMSYMBOL': ..., 'HIGH24HOUR': ..., 'LASTMARKET': ..., 'LASTTRADEID': ..., 'LASTUPDATE': ..., 'LASTVOLUME': ..., 'LASTVOLUMETO': ..., 'LOW24HOUR': ..., 'MARKET' ..., 'MKTCAP': ..., 'OPEN24HOUR': ..., 'PRICE': ..., 'SUPPLY': ..., 'TOSYMBOL': ..., 'TYPE': ..., 'VOLUME24HOUR': ..., 'VOLUME24HOURTO': ...}, tsym2: ..., ...}, fsym2: {...}, ...}
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python
train
KelSolaar/Umbra
umbra/components/factory/script_editor/script_editor.py
https://github.com/KelSolaar/Umbra/blob/66f45f08d9d723787f1191989f8b0dda84b412ce/umbra/components/factory/script_editor/script_editor.py#L2939-L2951
def register_file(self, file): """ Registers given file in the **file_system_events_manager**. :param file: File. :type file: unicode :return: Method success. :rtype: bool """ not self.__engine.file_system_events_manager.is_path_registered(file) and \ self.__engine.file_system_events_manager.register_path(file) return True
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Registers given file in the **file_system_events_manager**. :param file: File. :type file: unicode :return: Method success. :rtype: bool
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python
train
arkottke/pysra
pysra/motion.py
https://github.com/arkottke/pysra/blob/c72fd389d6c15203c0c00728ac00f101bae6369d/pysra/motion.py#L188-L208
def _calc_sdof_tf(self, osc_freq, damping=0.05): """Compute the transfer function for a single-degree-of-freedom oscillator. The transfer function computes the pseudo-spectral acceleration. Parameters ---------- osc_freq : float natural frequency of the oscillator [Hz] damping : float, optional damping ratio of the oscillator in decimal. Default value is 0.05, or 5%. Returns ------- tf : :class:`numpy.ndarray` Complex-valued transfer function with length equal to `self.freq`. """ return (-osc_freq ** 2. / (np.square(self.freqs) - np.square(osc_freq) - 2.j * damping * osc_freq * self.freqs))
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Compute the transfer function for a single-degree-of-freedom oscillator. The transfer function computes the pseudo-spectral acceleration. Parameters ---------- osc_freq : float natural frequency of the oscillator [Hz] damping : float, optional damping ratio of the oscillator in decimal. Default value is 0.05, or 5%. Returns ------- tf : :class:`numpy.ndarray` Complex-valued transfer function with length equal to `self.freq`.
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python
train
bcbio/bcbio-nextgen
bcbio/structural/cnvkit.py
https://github.com/bcbio/bcbio-nextgen/blob/6a9348c0054ccd5baffd22f1bb7d0422f6978b20/bcbio/structural/cnvkit.py#L31-L39
def use_general_sv_bins(data): """Check if we should use a general binning approach for a sample. Checks if CNVkit is enabled and we haven't already run CNVkit. """ if any([c in dd.get_svcaller(data) for c in ["cnvkit", "titancna", "purecn", "gatk-cnv"]]): if not _get_original_coverage(data): return True return False
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Check if we should use a general binning approach for a sample. Checks if CNVkit is enabled and we haven't already run CNVkit.
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python
train
subdownloader/subdownloader
subdownloader/provider/SDService.py
https://github.com/subdownloader/subdownloader/blob/bbccedd11b18d925ad4c062b5eb65981e24d0433/subdownloader/provider/SDService.py#L248-L277
def _login(self, username="", password=""): """Login to the Server using username/password, empty parameters means an anonymously login Returns True if login sucessful, and False if not. """ self.log.debug("----------------") self.log.debug("Logging in (username: %s)..." % username) def run_query(): return self._xmlrpc_server.LogIn( username, password, self.language, self.user_agent) info = self._safe_exec(run_query, None) if info is None: self._token = None return False self.log.debug("Login ended in %s with status: %s" % (info['seconds'], info['status'])) if info['status'] == "200 OK": self.log.debug("Session ID: %s" % info['token']) self.log.debug("----------------") self._token = info['token'] return True else: # force token reset self.log.debug("----------------") self._token = None return False
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Login to the Server using username/password, empty parameters means an anonymously login Returns True if login sucessful, and False if not.
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python
train
geophysics-ubonn/reda
lib/reda/utils/geometric_factors.py
https://github.com/geophysics-ubonn/reda/blob/46a939729e40c7c4723315c03679c40761152e9e/lib/reda/utils/geometric_factors.py#L11-L26
def apply_K(df, k): """Apply the geometric factors to the dataset and compute (apparent) resistivities/conductivities """ if 'k' not in df.columns: df['k'] = k if 'rho_a' not in df.columns: df['rho_a'] = df['r'] * df['k'] if 'sigma_a' not in df.columns: df['sigma_a'] = 1.0 / df['rho_a'] if 'Zt' in df.columns: df['rho_a_complex'] = df['Zt'] * df['k'] return df
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Apply the geometric factors to the dataset and compute (apparent) resistivities/conductivities
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python
train
xolox/python-update-dotdee
update_dotdee/__init__.py
https://github.com/xolox/python-update-dotdee/blob/04d5836f0d217e32778745b533beeb8159d80c32/update_dotdee/__init__.py#L214-L226
def write_file(self, filename, contents): """ Write a text file and provide feedback to the user. :param filename: The pathname of the file to write (a string). :param contents: The new contents of the file (a string). """ logger.info("Writing file: %s", format_path(filename)) contents = contents.rstrip() + b"\n" self.context.write_file(filename, contents) logger.debug("Wrote %s to %s.", pluralize(len(contents.splitlines()), "line"), format_path(filename))
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Write a text file and provide feedback to the user. :param filename: The pathname of the file to write (a string). :param contents: The new contents of the file (a string).
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python
train
wal-e/wal-e
wal_e/blobstore/s3/calling_format.py
https://github.com/wal-e/wal-e/blob/027263860e72a403bc0e1497bb3e67523138e7a2/wal_e/blobstore/s3/calling_format.py#L43-L62
def _is_ipv4_like(s): """Find if a string superficially looks like an IPv4 address. AWS documentation plays it fast and loose with this; in other regions, it seems like even non-valid IPv4 addresses (in particular, ones that possess decimal numbers out of range for IPv4) are rejected. """ parts = s.split('.') if len(parts) != 4: return False for part in parts: try: int(part) except ValueError: return False return True
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Find if a string superficially looks like an IPv4 address. AWS documentation plays it fast and loose with this; in other regions, it seems like even non-valid IPv4 addresses (in particular, ones that possess decimal numbers out of range for IPv4) are rejected.
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python
train
pycontribs/pyrax
pyrax/clouddns.py
https://github.com/pycontribs/pyrax/blob/9ddfd5064b3a292d7337906f3b2d5dce95b50b99/pyrax/clouddns.py#L589-L606
def findall(self, **kwargs): """ Finds all items with attributes matching ``**kwargs``. Normally this isn't very efficient, since the default action is to load the entire list and then filter on the Python side, but the DNS API provides a more efficient search option when filtering on name. So if the filter is on name, use that; otherwise, use the default. """ if (len(kwargs) == 1) and ("name" in kwargs): # Filtering on name; use the more efficient method. nm = kwargs["name"].lower() uri = "/%s?name=%s" % (self.uri_base, nm) matches = self._list(uri, list_all=True) return [match for match in matches if match.name.lower() == nm] else: return super(CloudDNSManager, self).findall(**kwargs)
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Finds all items with attributes matching ``**kwargs``. Normally this isn't very efficient, since the default action is to load the entire list and then filter on the Python side, but the DNS API provides a more efficient search option when filtering on name. So if the filter is on name, use that; otherwise, use the default.
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python
train