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"""
View decorators
---------------
Decorators for view handlers.
All items in this module can be imported directly from :mod:`coaster.views`.
"""
from functools import wraps
from flask import (
Response,
abort,
current_app,
g,
jsonify,
make_response,
redirect,
render_template,
request,
url_for,
)
from werkzeug.datastructures import Headers
from werkzeug.exceptions import BadRequest
from werkzeug.wrappers import Response as WerkzeugResponse
from ..auth import add_auth_attribute, current_auth
from ..utils import is_collection
from .misc import jsonp
__all__ = [
'RequestTypeError',
'RequestValueError',
'requestargs',
'requestform',
'requestquery',
'load_model',
'load_models',
'render_with',
'cors',
'requires_permission',
]
class RequestTypeError(BadRequest, TypeError):
"""
Exception that combines TypeError with BadRequest. Used by :func:`requestargs`.
"""
class RequestValueError(BadRequest, ValueError):
"""
Exception that combines ValueError with BadRequest. Used by :func:`requestargs`.
"""
def requestargs(*args, **config):
"""
Decorator that loads parameters from request.values if not specified in the
function's keyword arguments. Usage::
@requestargs('param1', ('param2', int), 'param3[]', ...)
def function(param1, param2=0, param3=None):
...
requestargs takes a list of parameters to pass to the wrapped function, with
an optional filter (useful to convert incoming string request data into integers
and other common types). If a required parameter is missing and your function does
not specify a default value, Python will raise TypeError. requestargs recasts this
as :exc:`RequestTypeError`, which returns HTTP 400 Bad Request.
If the parameter name ends in ``[]``, requestargs will attempt to read a list from
the incoming data. Filters are applied to each member of the list, not to the whole
list.
If the filter raises a ValueError, this is recast as a :exc:`RequestValueError`,
which also returns HTTP 400 Bad Request.
Tests::
>>> from flask import Flask
>>> app = Flask(__name__)
>>>
>>> @requestargs('p1', ('p2', int), ('p3[]', int))
... def f(p1, p2=None, p3=None):
... return p1, p2, p3
...
>>> f(p1=1)
(1, None, None)
>>> f(p1=1, p2=2)
(1, 2, None)
>>> f(p1='a', p2='b')
('a', 'b', None)
>>> with app.test_request_context('/?p2=2'):
... f(p1='1')
...
('1', 2, None)
>>> with app.test_request_context('/?p3=1&p3=2'):
... f(p1='1', p2='2')
...
('1', '2', [1, 2])
>>> with app.test_request_context('/?p2=100&p3=1&p3=2'):
... f(p1='1', p2=200)
...
('1', 200, [1, 2])
"""
if config and list(config.keys()) != ['source']:
raise TypeError(f"Unrecognised parameters: {config.keys()!r}")
return inner
def requestform(*args):
"""
Like :func:`requestargs`, but loads from request.form (the form submission).
"""
return requestargs(*args, **{'source': 'form'})
def requestquery(*args):
"""
Like :func:`requestargs`, but loads from request.args (the query string).
"""
return requestargs(*args, **{'source': 'query'})
def load_model(
model,
attributes=None,
parameter=None,
kwargs=False,
permission=None,
addlperms=None,
urlcheck=(),
):
"""
Decorator to load a model given a query parameter.
Typical usage::
@app.route('/<profile>')
@load_model(Profile, {'name': 'profile'}, 'profileob')
def profile_view(profileob):
# 'profileob' is now a Profile model instance.
# The load_model decorator replaced this:
# profileob = Profile.query.filter_by(name=profile).first_or_404()
return f"Hello, {profileob.name}"
Using the same name for request and parameter makes code easier to understand::
@app.route('/<profile>')
@load_model(Profile, {'name': 'profile'}, 'profile')
def profile_view(profile):
return f"Hello, {profile.name}"
``load_model`` aborts with a 404 if no instance is found.
:param model: The SQLAlchemy model to query. Must contain a ``query`` object
(which is the default with Flask-SQLAlchemy)
:param attributes: A dict of attributes (from the URL request) that will be
used to query for the object. For each key:value pair, the key is the name of
the column on the model and the value is the name of the request parameter that
contains the data
:param parameter: The name of the parameter to the decorated function via which
the result is passed. Usually the same as the attribute. If the parameter name
is prefixed with 'g.', the parameter is also made available as g.<parameter>
:param kwargs: If True, the original request parameters are passed to the decorated
function as a ``kwargs`` parameter
:param permission: If present, ``load_model`` calls the
:meth:`~coaster.sqlalchemy.PermissionMixin.permissions` method of the
retrieved object with ``current_auth.actor`` as a parameter. If
``permission`` is not present in the result, ``load_model`` aborts with
a 403. The permission may be a string or a list of strings, in which
case access is allowed if any of the listed permissions are available
:param addlperms: Iterable or callable that returns an iterable containing
additional permissions available to the user, apart from those granted by the
models. In an app that uses Lastuser for authentication, passing
``lastuser.permissions`` will pass through permissions granted via Lastuser
:param list urlcheck: If an attribute in this list has been used to load an object,
but the value of the attribute in the loaded object does not match the request
argument, issue a redirect to the corrected URL. This is useful for attributes
like ``url_id_name`` and ``url_name_uuid_b58`` where the ``name`` component may
change
"""
return load_models(
(model, attributes, parameter),
kwargs=kwargs,
permission=permission,
addlperms=addlperms,
urlcheck=urlcheck,
)
def load_models(*chain, **kwargs):
"""
Decorator to load a chain of models from the given parameters. This works just like
:func:`load_model` and accepts the same parameters, with some small differences.
:param chain: The chain is a list of tuples of (``model``, ``attributes``,
``parameter``). Lists and tuples can be used interchangeably. All retrieved
instances are passed as parameters to the decorated function
:param permission: Same as in :func:`load_model`, except
:meth:`~coaster.sqlalchemy.PermissionMixin.permissions` is called on every
instance in the chain and the retrieved permissions are passed as the second
parameter to the next instance in the chain. This allows later instances to
revoke permissions granted by earlier instances. As an example, if a URL
represents a hierarchy such as ``/<page>/<comment>``, the ``page`` can assign
``edit`` and ``delete`` permissions, while the ``comment`` can revoke ``edit``
and retain ``delete`` if the current user owns the page but not the comment
In the following example, load_models loads a Folder with a name matching the name
in the URL, then loads a Page with a matching name and with the just-loaded Folder
as parent. If the Page provides a 'view' permission to the current user, the
decorated function is called::
@app.route('/<folder_name>/<page_name>')
@load_models(
(Folder, {'name': 'folder_name'}, 'folder'),
(Page, {'name': 'page_name', 'parent': 'folder'}, 'page'),
permission='view')
def show_page(folder, page):
return render_template('page.html', folder=folder, page=page)
"""
return inner
def dict_jsonify(param):
"""
Convert the parameter into a dictionary before calling jsonify, if it's not already
one
"""
if not isinstance(param, dict):
param = dict(param)
return jsonify(param)
def dict_jsonp(param):
"""
Convert the parameter into a dictionary before calling jsonp, if it's not already
one
"""
if not isinstance(param, dict):
param = dict(param)
return jsonp(param)
def render_with(template=None, json=False, jsonp=False): # skipcq: PYL-W0621
"""
Decorator to render the wrapped function with the given template (or dictionary
of mimetype keys to templates, where the template is a string name of a template
file or a callable that returns a Response). The function's return value must be
a dictionary and is passed to the template as parameters. Callable templates get
a single parameter with the function's return value. Usage::
@app.route('/myview')
@render_with('myview.html')
def myview():
return {'data': 'value'}
@app.route('/myview_with_json')
@render_with('myview.html', json=True)
def myview_no_json():
return {'data': 'value'}
@app.route('/otherview')
@render_with({
'text/html': 'otherview.html',
'text/xml': 'otherview.xml'})
def otherview():
return {'data': 'value'}
@app.route('/404view')
@render_with('myview.html')
def myview():
return {'error': '404 Not Found'}, 404
@app.route('/headerview')
@render_with('myview.html')
def myview():
return {'data': 'value'}, 200, {'X-Header': 'Header value'}
When a mimetype is specified and the template is not a callable, the response is
returned with the same mimetype. Callable templates must return Response objects
to ensure the correct mimetype is set.
If a dictionary of templates is provided and does not include a handler for ``*/*``,
render_with will attempt to use the handler for (in order) ``text/html``,
``text/plain`` and the various JSON types, falling back to rendering the value into
a unicode string.
If the method is called outside a request context, the wrapped method's original
return value is returned. This is meant to facilitate testing and should not be
used to call the method from within another view handler as the presence of a
request context will trigger template rendering.
Rendering may also be suspended by calling the view handler with ``_render=False``.
render_with provides JSON and JSONP handlers for the ``application/json``,
``text/json`` and ``text/x-json`` mimetypes if ``json`` or ``jsonp`` is True
(default is False).
:param template: Single template, or dictionary of MIME type to templates. If the
template is a callable, it is called with the output of the wrapped function
:param json: Helper to add a JSON handler (default is False)
:param jsonp: Helper to add a JSONP handler (if True, also provides JSON, default
is False)
"""
if jsonp:
templates = {
'application/json': dict_jsonp,
'application/javascript': dict_jsonp,
}
elif json:
templates = {'application/json': dict_jsonify}
else:
templates = {}
if isinstance(template, str):
templates['text/html'] = template
elif isinstance(template, dict):
templates.update(template)
elif template is None and (json or jsonp):
pass
else: # pragma: no cover
raise ValueError("Expected string or dict for template")
default_mimetype = '*/*'
if '*/*' not in templates:
templates['*/*'] = str
default_mimetype = 'text/plain'
for mimetype in ('text/html', 'text/plain', 'application/json'):
if mimetype in templates:
templates['*/*'] = templates[mimetype]
default_mimetype = (
mimetype # Remember which mimetype's handler is serving for */*
)
break
template_mimetypes = list(templates.keys())
template_mimetypes.remove(
'*/*'
) # */* messes up matching, so supply it only as last resort
return inner
def cors(
origins,
methods=('HEAD', 'OPTIONS', 'GET', 'POST', 'PUT', 'PATCH', 'DELETE'),
headers=(
'Accept',
'Accept-Language',
'Content-Language',
'Content-Type',
'X-Requested-With',
),
max_age=None,
):
"""
Adds CORS headers to the decorated view function.
:param origins: Allowed origins (see below)
:param methods: A list of allowed HTTP methods
:param headers: A list of allowed HTTP headers
:param max_age: Duration in seconds for which the CORS response may be cached
The :obj:`origins` parameter may be one of:
1. A callable that receives the origin as a parameter.
2. A list of origins.
3. ``*``, indicating that this resource is accessible by any origin.
Example use::
from flask import Flask, Response
from coaster.views import cors
app = Flask(__name__)
@app.route('/any')
@cors('*')
def any_origin():
return Response()
@app.route('/static', methods=['GET', 'POST'])
@cors(
['https://hasgeek.com'],
methods=['GET'],
headers=['Content-Type', 'X-Requested-With'],
max_age=3600)
def static_list():
return Response()
def check_origin(origin):
# check if origin should be allowed
return True
@app.route('/callable')
@cors(check_origin)
def callable_function():
return Response()
"""
return inner
def requires_permission(permission):
"""
View decorator that requires a certain permission to be present in
``current_auth.permissions`` before the view is allowed to proceed.
Aborts with ``403 Forbidden`` if the permission is not present.
The decorated view will have an ``is_available`` method that can be called
to perform the same test.
:param permission: Permission that is required. If a collection type is
provided, any one permission must be available
"""
return inner
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220,
220,
284,
1620,
262,
976,
1332,
13,
628,
220,
220,
220,
1058,
17143,
7170,
25,
2448,
3411,
326,
318,
2672,
13,
1002,
257,
4947,
2099,
318,
198,
220,
220,
220,
220,
220,
220,
220,
2810,
11,
597,
530,
7170,
1276,
307,
1695,
198,
220,
220,
220,
37227,
628,
220,
220,
220,
1441,
8434,
198
] | 2.701052 | 5,419 |
#!/usr/bin/env python3
# coding:utf-8
if __name__ == "__main__":
s = Solution()
print(s.Power(2, 0))
print(s.Power(0, 2))
print(s.Power(3.5, 2))
print(s.Power(3.5, -2))
|
[
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
18,
198,
2,
19617,
25,
40477,
12,
23,
628,
198,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
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1298,
198,
220,
220,
220,
264,
796,
28186,
3419,
198,
220,
220,
220,
3601,
7,
82,
13,
13434,
7,
17,
11,
657,
4008,
198,
220,
220,
220,
3601,
7,
82,
13,
13434,
7,
15,
11,
362,
4008,
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220,
220,
220,
3601,
7,
82,
13,
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7,
18,
13,
20,
11,
362,
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220,
220,
220,
3601,
7,
82,
13,
13434,
7,
18,
13,
20,
11,
532,
17,
4008,
198
] | 1.939394 | 99 |
# -*- coding : utf-8-*-
import abc
from enum import Enum
class StructTemplate(metaclass=abc.ABCMeta):
"""
构造物模板的基类
"""
@abc.abstractmethod
def _register_kwd(self):
"""
注册参数的抽象方法, 构造函数调用一次, 子类定义中需实现. 已注册的参数可以在构造函数中使用.
Returns:
"""
pass
@abc.abstractmethod
def TypeID(self) -> StructTypeEunm:
"""
注册结构类型
Returns:
"""
pass
|
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2,
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12,
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220,
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220,
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10545,
111,
101,
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119,
241,
162,
252,
226,
163,
109,
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252,
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220,
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220,
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25,
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220,
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220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1208,
198
] | 1.363354 | 322 |
from descarteslabs.client.exceptions import * # noqa
|
[
6738,
1715,
433,
274,
75,
8937,
13,
16366,
13,
1069,
11755,
1330,
1635,
220,
1303,
645,
20402,
198
] | 3 | 18 |
board = []
for loop in range(0, 5):
treta = ["O"] * 5
board.append(treta)
print(board)
|
[
3526,
796,
17635,
198,
198,
1640,
9052,
287,
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7,
15,
11,
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83,
1186,
64,
8,
198,
220,
220,
220,
3601,
7,
3526,
8,
198
] | 2.083333 | 48 |
from .version import __version__ as version
|
[
6738,
764,
9641,
1330,
11593,
9641,
834,
355,
2196
] | 4.777778 | 9 |
import time
import board
import keypad
import usb_hid
import neopixel
from adafruit_led_animation.animation.pulse import Pulse
from adafruit_led_animation.animation.solid import Solid
from adafruit_led_animation.animation.blink import Blink
from adafruit_led_animation.group import AnimationGroup
from adafruit_led_animation import color
from adafruit_led_animation.animation.chase import Chase
from adafruit_led_animation.animation.rainbow import Rainbow
from adafruit_led_animation.animation.rainbowsparkle import RainbowSparkle
from adafruit_led_animation.animation.colorcycle import ColorCycle
from adafruit_hid.keyboard import Keyboard
from adafruit_hid.keyboard_layout_us import KeyboardLayoutUS
# When all buttons are released, this code will type the mask of what
# had been pressed, surrounded by the prefix and suffix below.
MSG_PREFIX = ";#@lime"
MSG_SUFFIX = "#"
kbd = Keyboard(usb_hid.devices)
layout = KeyboardLayoutUS(kbd)
# This is the pin in the board that is connected to the NeoPixel Jewel - 7 RGB LED
pixel_pin = board.A0
num_pixels = 7
pixels = neopixel.NeoPixel(pixel_pin, num_pixels, brightness=0.8, auto_write=False)
internal_pixel = neopixel.NeoPixel(board.NEOPIXEL, 1, brightness=1, auto_write=False)
# The button pins we'll use. Each is directly connected to a Kailh Mechanical Key Switch
buttonpins = (board.A3, board.A2, board.A1, board.D10, board.D9, board.D8)
keys = keypad.Keys(buttonpins, value_when_pressed=False, pull=True)
animation_push_button = AnimationGroup(
Blink(pixels, speed=0.05, color=color.WHITE),
Blink(internal_pixel, speed=0.05, color=color.WHITE),
)
animation_fidget_push_button = AnimationGroup(
Blink(pixels, speed=0.05, color=color.PURPLE),
Solid(internal_pixel, color=color.PURPLE),
)
animation_long_push_button = AnimationGroup(
Blink(pixels, speed=0.05, color=color.RED),
Solid(internal_pixel, color=color.RED),
)
animation_off = AnimationGroup(
Solid(pixels, color=color.BLACK),
Solid(internal_pixel, color=color.BLACK),
)
animation_groups = [
AnimationGroup(
Pulse(pixels, speed=0.05, color=color.ORANGE, period=10),
Solid(internal_pixel, color=color.AMBER),
),
AnimationGroup(
Rainbow(pixels, speed=0.1, period=10),
Solid(internal_pixel, color=color.BLACK),
),
AnimationGroup(
RainbowSparkle(pixels, speed=0.1, num_sparkles=2),
RainbowSparkle(internal_pixel, speed=0.1, num_sparkles=0),
),
AnimationGroup(
Blink(pixels, speed=3, color=color.GOLD),
Solid(internal_pixel, color=color.GOLD),
),
AnimationGroup(
Chase(pixels, speed=0.1, size=3, spacing=6, color=color.GREEN),
Solid(internal_pixel, color=color.GREEN),
),
AnimationGroup(
ColorCycle(
pixels,
10,
colors=[
color.BLUE,
color.GREEN,
color.RED,
color.TEAL,
color.PURPLE,
color.AQUA,
],
),
Solid(internal_pixel, color=color.BLUE),
),
animation_off, # Expected to be the last one
]
# Initial animation to show that code is ready to go
start_ts = time.monotonic()
start_amin = ColorCycle(
pixels, 0.25, colors=[color.MAGENTA, color.ORANGE, color.TEAL, color.AQUA]
)
while time.monotonic() - start_ts < 1.5:
start_amin.animate()
ALL_BUTTONS_MASK = 2 ** len(buttonpins) - 1
# The state of the lemon keyboard
fidget_mode = False
curr_animation_group_index = -1
animations = animation_off
buttons_pressed_ts = None
buttons_pressed = 0
buttons_mask = 0
buttons_first_press = None
long_press = False
# Create an event we will reuse over and over.
event = keypad.Event()
print("Waiting for button presses")
while True:
animations.animate()
time.sleep(0.01)
# Detect long press
if (
(not long_press)
and buttons_pressed
and time.monotonic() - buttons_pressed_ts > 2.8
):
print("long press")
long_press = True
animations.reset()
animations = animation_long_push_button
if keys.events.get_into(event):
pressed_mask = 2 ** event.key_number
prev_buttons_pressed = buttons_pressed
prev_buttons_mask = buttons_mask
if event.pressed:
buttons_pressed |= pressed_mask
buttons_mask |= pressed_mask
else:
buttons_pressed &= ~pressed_mask
print(
"button",
event.key_number,
"pressed." if event.pressed else "released.",
"buttons_pressed_mask:",
buttons_pressed,
"buttons_mask_mask:",
buttons_mask,
"pressed_mask:",
pressed_mask,
)
if not prev_buttons_pressed and buttons_pressed:
print("first detected press")
# first button pressed
animations.reset()
animations = (
animation_fidget_push_button if fidget_mode else animation_push_button
)
buttons_pressed_ts = time.monotonic()
buttons_first_press = event.key_number
elif prev_buttons_pressed and not buttons_pressed:
print("last button release")
# last button released
if long_press:
if buttons_mask != 2 ** buttons_first_press:
# long press when multiple buttons were pressed: animation off
curr_animation_group_index = -1
else:
curr_animation_group_index = buttons_first_press % len(
animation_groups
)
else:
msg = f"{MSG_PREFIX}{buttons_mask}{MSG_SUFFIX}"
if buttons_mask == ALL_BUTTONS_MASK:
fidget_mode = not fidget_mode
print("fidget mode is now", "on" if fidget_mode else "off")
elif fidget_mode:
print("fidget mode message: ", msg)
else:
print("typing", msg)
layout.write(msg)
time.sleep(0.3)
keys.events.clear() # Empty the event queue.
animations.reset()
animations = animation_groups[curr_animation_group_index]
long_press = False
buttons_mask = 0
|
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5315,
20418,
2375,
198,
6738,
512,
1878,
4872,
62,
49675,
13,
2539,
3526,
1330,
31973,
198,
6738,
512,
1878,
4872,
62,
49675,
13,
2539,
3526,
62,
39786,
62,
385,
1330,
31973,
32517,
2937,
198,
198,
2,
1649,
477,
12163,
389,
2716,
11,
428,
2438,
481,
2099,
262,
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286,
644,
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550,
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21231,
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25113,
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31973,
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32517,
2937,
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8,
198,
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2,
770,
318,
262,
6757,
287,
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3096,
326,
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284,
262,
21227,
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532,
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32,
15,
198,
22510,
62,
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13,
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62,
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11,
997,
62,
79,
14810,
11,
22204,
28,
15,
13,
23,
11,
8295,
62,
13564,
28,
25101,
8,
198,
32538,
62,
32515,
796,
497,
404,
7168,
13,
8199,
78,
40809,
7,
3526,
13,
12161,
3185,
10426,
3698,
11,
352,
11,
22204,
28,
16,
11,
8295,
62,
13564,
28,
25101,
8,
198,
198,
2,
383,
4936,
20567,
356,
1183,
779,
13,
5501,
318,
3264,
5884,
284,
257,
509,
603,
71,
19663,
7383,
14645,
198,
16539,
49556,
796,
357,
3526,
13,
32,
18,
11,
3096,
13,
32,
17,
11,
3096,
13,
32,
16,
11,
3096,
13,
35,
940,
11,
3096,
13,
35,
24,
11,
3096,
13,
35,
23,
8,
198,
198,
13083,
796,
1994,
15636,
13,
40729,
7,
16539,
49556,
11,
1988,
62,
12518,
62,
45477,
28,
25101,
11,
2834,
28,
17821,
8,
198,
198,
11227,
341,
62,
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62,
16539,
796,
23535,
13247,
7,
198,
220,
220,
220,
41732,
7,
79,
14810,
11,
2866,
28,
15,
13,
2713,
11,
3124,
28,
8043,
13,
12418,
12709,
828,
198,
220,
220,
220,
41732,
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62,
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11,
2866,
28,
15,
13,
2713,
11,
3124,
28,
8043,
13,
12418,
12709,
828,
198,
8,
198,
198,
11227,
341,
62,
69,
17484,
62,
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62,
16539,
796,
23535,
13247,
7,
198,
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220,
220,
41732,
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28,
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15831,
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220,
10612,
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220,
11034,
62,
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1303,
1475,
7254,
284,
307,
262,
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530,
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60,
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2,
20768,
11034,
284,
905,
326,
2438,
318,
3492,
284,
467,
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9688,
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9688,
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5315,
20418,
2375,
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220,
17848,
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8043,
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3525,
32,
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10917,
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4514,
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3419,
532,
923,
62,
912,
1279,
352,
13,
20,
25,
198,
220,
220,
220,
923,
62,
5669,
13,
45685,
3419,
198,
198,
7036,
62,
47526,
11357,
50,
62,
31180,
42,
796,
362,
12429,
18896,
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49556,
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383,
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6045,
198,
6511,
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796,
10352,
198,
198,
2,
13610,
281,
1785,
356,
481,
32349,
625,
290,
625,
13,
198,
15596,
796,
1994,
15636,
13,
9237,
3419,
198,
198,
4798,
7203,
33484,
1780,
329,
4936,
31048,
4943,
198,
4514,
6407,
25,
198,
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220,
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22407,
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640,
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1303,
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611,
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1662,
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2073,
11034,
62,
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62,
16539,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
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220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
12163,
62,
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62,
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640,
13,
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313,
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220,
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1288,
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25,
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220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
7203,
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4936,
2650,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
938,
4936,
2716,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
890,
62,
8439,
25,
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220,
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220,
220,
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220,
220,
220,
220,
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611,
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62,
27932,
14512,
362,
12429,
12163,
62,
11085,
62,
8439,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
890,
1803,
618,
3294,
12163,
547,
12070,
25,
11034,
572,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1090,
81,
62,
11227,
341,
62,
8094,
62,
9630,
796,
532,
16,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1090,
81,
62,
11227,
341,
62,
8094,
62,
9630,
796,
12163,
62,
11085,
62,
8439,
4064,
18896,
7,
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220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
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220,
220,
220,
220,
220,
220,
220,
220,
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11034,
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24432,
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220,
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31456,
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1,
90,
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38,
62,
47,
31688,
10426,
18477,
4360,
27288,
62,
27932,
18477,
5653,
38,
62,
12564,
5777,
10426,
36786,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
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220,
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611,
12163,
62,
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6624,
11096,
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11357,
50,
62,
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42,
25,
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220,
220,
220,
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277,
17484,
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3601,
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1288,
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220,
220,
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220,
220,
220,
220,
220,
3601,
7203,
69,
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4235,
3275,
25,
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31456,
8,
198,
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220,
220,
220,
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220,
220,
220,
220,
220,
220,
220,
220,
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2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3601,
7203,
774,
13886,
1600,
31456,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
12461,
13,
13564,
7,
19662,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
640,
13,
42832,
7,
15,
13,
18,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8251,
13,
31534,
13,
20063,
3419,
220,
1303,
33523,
262,
1785,
16834,
13,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
22407,
13,
42503,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
22407,
796,
11034,
62,
24432,
58,
22019,
81,
62,
11227,
341,
62,
8094,
62,
9630,
60,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
890,
62,
8439,
796,
10352,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
12163,
62,
27932,
796,
657,
198
] | 2.255994 | 2,836 |
#!/usr/bin/python
# Copyright 2015 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
import contextlib
import os
import shutil
import tempfile
@contextlib.contextmanager
def TempDeploymentDir(paths, use_symlinks=True):
"""Sets up and tears down a directory for deploying an app."""
if use_symlinks:
link_func = os.symlink
else:
link_func = _Copy
try:
deployment_dir = tempfile.mkdtemp(prefix='deploy-')
_PopulateDeploymentDir(deployment_dir, paths, link_func)
yield deployment_dir
finally:
shutil.rmtree(deployment_dir)
def _PopulateDeploymentDir(deployment_dir, paths, link_func):
"""Fills the deployment directory using the link_func specified."""
for path in paths:
destination = os.path.join(deployment_dir, os.path.basename(path))
link_func(path, destination)
|
[
2,
48443,
14629,
14,
8800,
14,
29412,
198,
2,
15069,
1853,
383,
18255,
1505,
46665,
13,
1439,
2489,
10395,
13,
198,
2,
5765,
286,
428,
2723,
2438,
318,
21825,
416,
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347,
10305,
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628,
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31,
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37153,
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4299,
24189,
49322,
434,
35277,
7,
6978,
82,
11,
779,
62,
37047,
28751,
28,
17821,
2599,
198,
220,
37227,
50,
1039,
510,
290,
10953,
866,
257,
8619,
329,
29682,
281,
598,
526,
15931,
198,
220,
611,
779,
62,
37047,
28751,
25,
198,
220,
220,
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2792,
62,
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13,
1837,
4029,
676,
198,
220,
2073,
25,
198,
220,
220,
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2792,
62,
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4808,
29881,
628,
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1949,
25,
198,
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14833,
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67,
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1420,
12,
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220,
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4808,
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7,
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62,
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11,
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11,
2792,
62,
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8,
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220,
220,
220,
7800,
14833,
62,
15908,
198,
220,
3443,
25,
198,
220,
220,
220,
4423,
346,
13,
81,
16762,
631,
7,
2934,
1420,
434,
62,
15908,
8,
628,
198,
198,
4299,
4808,
16979,
5039,
49322,
434,
35277,
7,
2934,
1420,
434,
62,
15908,
11,
13532,
11,
2792,
62,
20786,
2599,
198,
220,
37227,
37,
2171,
262,
14833,
8619,
1262,
262,
2792,
62,
20786,
7368,
526,
15931,
198,
220,
329,
3108,
287,
13532,
25,
198,
220,
220,
220,
10965,
796,
28686,
13,
6978,
13,
22179,
7,
2934,
1420,
434,
62,
15908,
11,
28686,
13,
6978,
13,
12093,
12453,
7,
6978,
4008,
198,
220,
220,
220,
2792,
62,
20786,
7,
6978,
11,
10965,
8,
198
] | 3.003289 | 304 |
from functools import cache
if __name__ == '__main__':
print(numsSameConsecDiff(8, 1))
|
[
6738,
1257,
310,
10141,
1330,
12940,
628,
198,
198,
361,
11593,
3672,
834,
6624,
705,
834,
12417,
834,
10354,
198,
220,
220,
220,
3601,
7,
77,
5700,
30556,
3103,
2363,
28813,
7,
23,
11,
352,
4008,
198
] | 2.540541 | 37 |
import itertools
import json
from math import inf
import rtree as rtree
from pymunk import Vec2d
from k_road.builder.road_builder import RoadBuilder
from k_road.constants import Constants
from k_road.entity import entity_factory
from k_road.entity.entity_type import EntityType
# ------------------------------------------------#
### NOTE again whether we are mapping to right hand coords here or not.
# This ends up by negating all y coordinates
# The trick is to be consistent w.r.t. when this conversion happens.
# which so far we have not been succeeding. sorry
###
|
[
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340,
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13,
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62,
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20885,
6030,
628,
198,
2,
20368,
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2,
628,
198,
21017,
24550,
757,
1771,
356,
389,
16855,
284,
826,
1021,
763,
3669,
994,
393,
407,
13,
198,
2,
770,
5645,
510,
416,
2469,
803,
477,
331,
22715,
198,
2,
383,
6908,
318,
284,
307,
6414,
266,
13,
81,
13,
83,
13,
618,
428,
11315,
4325,
13,
198,
2,
543,
523,
1290,
356,
423,
407,
587,
34195,
13,
7926,
198,
21017,
198
] | 3.84 | 150 |
#!/usr/bin/python
import sys
import logging
logging.basicConfig(stream=sys.stderr)
sys.path.insert(0,"/var/www/vhosts/maildash.iccenter.org/")
from maildash import app as application
application.secret_key = 'development-key'
|
[
2,
48443,
14629,
14,
8800,
14,
29412,
198,
11748,
25064,
198,
11748,
18931,
198,
6404,
2667,
13,
35487,
16934,
7,
5532,
28,
17597,
13,
301,
1082,
81,
8,
198,
17597,
13,
6978,
13,
28463,
7,
15,
553,
14,
7785,
14,
2503,
14,
85,
4774,
82,
14,
2611,
688,
1077,
13,
291,
16159,
13,
2398,
14,
4943,
198,
198,
6738,
17266,
688,
1077,
1330,
598,
355,
3586,
198,
31438,
13,
21078,
62,
2539,
796,
705,
31267,
12,
2539,
6,
198
] | 2.873418 | 79 |
import os, glob
from fabric.api import env, sudo, run, cd, local, put, prefix, roles, execute, task, get
from fabric.api import settings as fab_settings
from fabric.context_managers import settings, hide
from fabric.contrib.files import sed
from subprocess import Popen, PIPE
import datetime
from utils import _build_env, _run_task, _cron_command, _request_input, _request_continue, _append_to_file, _load_template
from enumerations import GEONODE_TYPES, ISO_CATEGORIES
global targets
targets = ()
PATH_ACTIVATE = "/var/lib/geonode/bin/activate"
PATH_MANAGEPY_VN = "/var/lib/geonode"
PATH_MANAGEPY_GS = "/var/lib/geonode/rogue_geonode"
PATH_DNA_JSON = "/opt/chef-run/dna.json"
PATH_LS_VN = "/var/lib/geonode/local_settings.py"
PATH_LS_GS = "/var/lib/geonode/rogue_geonode/geoshape/local_settings.py"
PATH_GEOSERVER_DATA = "/var/lib/geoserver_data"
#############################################################
# The Public API
@task
def gn(*args):
"""
Load GeoNode settings from geonodes.py
Imports GeoNode settings from a geonodes.py file
in the same directory
"""
global targets
targets = args
@task
@task
## GeoSever
@task
@task
## Vanilla
@task
## GeoSHAPE
@task
def provision_geoshape(*args):
"""
Provision a GeoSHAPE instance
Runs `cybergis-scripts-rogue.sh prod provision`
"""
return _run_task(_provision_geoshape, args=args)
@task
def restart_geoshape(*args):
"""
Restart GeoSHAPE instance, including Django, GeoServer, and RabbitMQ
Calls ./stop_geonode and ./start_geonode,
restarts tomcat7, and resets RabbitMQ
"""
return _run_task(_restart_geoshape, args=args)
@task
@task
@task
def importlayers(t=None, local=None, drop=None, user=None, overwrite=None, category=None, keywords=None, private=None):
"""
Import local files into a GeoNode instance
Puts via SFTP local files into the remote's "drop" folder and then
runs importlayers on all of them.
Options:
t = GeoNode Type (Vanilla or GeoSHAPE)
local = local file path
drop = temporary drop folder
user = the user that will own the layer
overwrite = overwrite existing layers
category = ISO Category for layer
keywords = comma separated list of keywords
private = Is layer only visible to owner and admins?
"""
return _run_task(_importlayers, kwargs={'t':t, 'local':local, 'drop': drop, 'user': user, 'overwrite': overwrite, 'category': category, 'keywords': keywords, 'private': private})
@task
def add_gmail(t=None, u=None, p=None):
"""
Adds server GMail to instance
Adds GMail settings to vim /var/lib/geonode/rogue_geonode/geoshape/local_settings.py
"""
address = _request_input("User", u, True)+'@gmail.com'
host = 'smtp.gmail.com'
return _run_task(_add_email, args=None, kwargs={'t':t, 'a':address, 'p':p, 'h':host})
@task
@task
@task
def backup_geonode(t=None, remote=None, local=None):
"""
Backup GeoNode to disk
Backs up GeoNode to the destination "d" folder
on disk.
Options:
t = GeoNode Type (Vanilla or GeoSHAPE)
remote = remote folder to backup to (required)
local = local folder to backup to (optional)
"""
return _run_task(_backup_geonode, args=None, kwargs={'t':t, 'remote':remote, 'local':local})
#############################################################
# The Private API
|
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] | 2.838442 | 1,207 |
for _ in range(6):
sauter()
avancer()
avancer()
gauche()
for _ in range(2):
avancer()
for _ in range(9):
coup()
avancer()
avancer()
ouvrir()
|
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] | 2.147059 | 68 |
import cv2
import tensorflow as tf
import numpy as np
import glob
import os
import time
import argparse
import configparser
from auto_pose.ae import factory, utils
parser = argparse.ArgumentParser()
parser.add_argument("experiment_name")
parser.add_argument("-f", "--file_str", required=True, help='folder or filename to image(s)')
# parser.add_argument("-gt_bb", action='store_true', default=False)
arguments = parser.parse_args()
full_name = arguments.experiment_name.split('/')
experiment_name = full_name.pop()
experiment_group = full_name.pop() if len(full_name) > 0 else ''
print('experiment name: ', experiment_name)
print('experiment group: ', experiment_group)
file_str = arguments.file_str
if os.path.isdir(file_str):
files = sorted(glob.glob(os.path.join(str(file_str),'*.png'))+glob.glob(os.path.join(str(file_str),'*.jpg'))+glob.glob(os.path.join(str(file_str),'*.JPG')))
else:
files = [file_str]
workspace_path = os.environ.get('AE_WORKSPACE_PATH')
if workspace_path == None:
print('Please define a workspace path:\n')
print('export AE_WORKSPACE_PATH=/path/to/workspace\n')
exit(-1)
log_dir = utils.get_log_dir(workspace_path,experiment_name,experiment_group)
ckpt_dir = utils.get_checkpoint_dir(log_dir)
start_time = time.time()
encoder = factory.build_codebook_from_name(experiment_name, experiment_group, return_encoder=True)
end_time = time.time()
print("encoder loading: ", str(end_time - start_time))
with tf.Session() as sess:
start_time = time.time()
factory.restore_checkpoint(sess, tf.train.Saver(), ckpt_dir)
end_time = time.time()
print("restoring checkpoint: ", str(end_time - start_time))
# for i in range(1, 8):
for file in files:
im = cv2.imread(file)
im = cv2.resize(im, (256, 256))
im = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
im = np.expand_dims(im, axis=2)
start_time = time.time()
latent_vector = encoder.latent_vector(sess, im)
end_time = time.time()
print('latent vector: ', latent_vector)
print("inference time: ", int(1000 * (end_time - start_time)) / 1000., " fps: ",
int(1 / (end_time - start_time)))
|
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7,
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923,
62,
2435,
4008,
1220,
8576,
1539,
366,
220,
220,
220,
32977,
25,
33172,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
493,
7,
16,
1220,
357,
437,
62,
2435,
532,
923,
62,
2435,
22305,
198
] | 2.508591 | 873 |
# -*- coding: utf-8 -*-
"""
Collection of functions that perform different types of parsing
"""
__author__ = "Brian Connelly <[email protected]>"
__credits__ = "Brian Connelly"
import re
from seeds.SEEDSError import *
def parse_int_rangelist(s, sorted=False):
"""Parse a list of numeric ranges. These lists are a comma-separated list
of either single numbers or ranges, specified by number-number.
Parameters:
s
A string containing a comma-separated list of integers and ranges of
integers
sorted
Whether or not to sort the resulting list (default: False)
"""
range_pattern = "\s*(\-?\d+)\s*\-\s*(\-?\d+)\s*"
retval = []
if s:
tokens = s.split(",")
for t in tokens:
match = re.match(range_pattern, t)
if match:
start = int(match.group(1))
end = int(match.group(2))
for i in range(start, end+1):
retval.append(i)
else:
try:
x = int(t)
retval.append(x)
except ValueError:
raise IntRangelistFormatError(s)
if sorted:
retval.sort()
return retval
def parse_version_string(s):
"""Parse a version string and return a 3-element dict with keys 'operator',
'major', and 'minor'. Input strings are of the form:
<operator><major_version>.<minor_version>
Where <operator> is one of: <, <=, =, >=, or >. Although not recommended,
when the operator is omitted, = will be used.
"""
pattern = '^\s*(?P<operator>[<>=]+)?\s*(?P<major>\d+)\.(?P<minor>\d+)(\.(?P<patch>\d+))?\s*$'
match = re.match(pattern, s)
if match:
retval = {}
if match.group('operator') == None:
retval['operator'] = '='
else:
retval['operator'] = match.group('operator')
retval['major'] = int(match.group('major'))
retval['minor'] = int(match.group('minor'))
if match.group('patch'):
retval['patch'] = int(match.group('patch'))
else:
retval['patch'] = 0
retval['version'] = (int(match.group('major')), int(match.group('minor')), int(retval['patch']))
return retval
else:
raise VersionStringFormatError("'{s}' is not a valid version string".format(s=s))
|
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1005,
2100,
17816,
17147,
20520,
796,
657,
628,
220,
220,
220,
220,
220,
220,
220,
1005,
2100,
17816,
9641,
20520,
796,
357,
600,
7,
15699,
13,
8094,
10786,
22478,
11537,
828,
493,
7,
15699,
13,
8094,
10786,
1084,
273,
11537,
828,
493,
7,
1186,
2100,
17816,
17147,
20520,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
1005,
2100,
198,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
5298,
10628,
10100,
26227,
12331,
7203,
6,
90,
82,
92,
6,
318,
407,
257,
4938,
2196,
4731,
1911,
18982,
7,
82,
28,
82,
4008,
198
] | 2.188472 | 1,093 |
#!/usr/bin/env python3
import contextlib
import os
import random
import socket
import string
import subprocess
import time
import unittest
@contextlib.contextmanager
class SmokeTest(unittest.TestCase):
'''High level smoke tests for the library.
These should be run via ninja smoke from your meson build directory.
'''
if __name__ == '__main__':
unittest.main()
|
[
2,
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10354,
198,
220,
220,
220,
555,
715,
395,
13,
12417,
3419,
198
] | 3.180328 | 122 |
from __future__ import print_function
import argparse
import glob
import os
if __name__ == '__main__':
main()
|
[
6738,
11593,
37443,
834,
1330,
3601,
62,
8818,
198,
198,
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705,
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12417,
834,
10354,
198,
220,
220,
220,
1388,
3419,
198
] | 3.025641 | 39 |
import math
from functools import reduce, wraps
from typing import Callable, List, Union, Optional
from toolz import groupby
import pandas as pd
from funcy import lmapcat
try:
from tqdm.autonotebook import tqdm
except ImportError:
_has_tqdm = False
tqdm = None
else:
_has_tqdm = True
def rename_keys(dictionary: dict, mapping: dict):
"Rename keys in a dictionary"
return {mapping.get(k, k): v for k, v in dictionary.items()}
def concat_dicts(dicts, prefix: Union[str, int] = ""):
"Concatenate list of dictionaries"
def bump_key_index(key, existing_dict, start=1):
"Prefix with _1 until index not in existing dictionary"
if key not in existing_dict:
return key
new_key = f"{key}_{start}"
if new_key in existing_dict:
return bump_key_index(key, existing_dict, start + 1)
return new_key
return prefix_dict_keys(reduce(reduce_two_dicts, dicts, {}), prefix)
def defaultprop(fn):
"""Function decorator to have a default property (but not automatically set
it)
"""
attr_name = "_" + fn.__name__
@property
@wraps(fn)
return _defaultprop
def add_prefixes(values: List[str], prefixes: List[str]):
"""Add prefix to each value if not already present"""
if len(prefixes) == 0:
return values
return lmapcat(
lambda prefix: [
(value if value.startswith(prefix) else f"{prefix}{value}")
for value in values
],
prefixes,
)
class Hashabledict(dict):
"""Dictionary that is hashable (useful for creating set of unique dictionaries)"""
def get_values_at_codeable_paths(value: dict, keys: List[str]):
"""Extract values from FHIR records based on keys (useful for extracting codes)"""
return lmapcat(lambda key: get_value_at_codeable_path(value, key), keys)
def extract_codes(results: list, display: str, code_fields: List[str]):
"""Extract code values from a list of dictionaries based on the code keys.
Requires a display value to filter results preemptively (instead of
filtering afterwards)
"""
codes = set()
for row in results:
row_codes = get_values_at_codeable_paths(row, code_fields)
for code in row_codes:
if (
isinstance(code, dict)
# Poor man's way to filter only matching codes (since Elasticsearch
# returns records which will include other codes)
and display.lower() in code.get("display", "").lower()
):
codes.add(code)
return pd.DataFrame(list(codes))
def split_by(args: dict, left_keys: List[str]):
"""Split into two dictionaries (left is whitelist and right is remaining)"""
result = {
k: dict(v)
for k, v in groupby(
lambda pair: pair[0] in left_keys, args.items()
).items()
}
return (result.get(True, {}), result.get(False, {}))
|
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828,
1255,
13,
1136,
7,
25101,
11,
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4008,
198
] | 2.52292 | 1,178 |
#!/usr/bin/env python3
import asyncio
import discord
import logging
import json
import random
logger = logging.getLogger('spookbot')
logger.setLevel(logging.INFO)
handler = logging.FileHandler(filename='spookbot.log', mode='w', encoding='utf-8')
handler.setFormatter(logging.Formatter('%(asctime)s:%(levelname)s:%(name)s: %(message)s'))
logger.addHandler(handler)
with open("auth.json") as auth:
auth = json.load(auth)
client = discord.Client()
commands = {}
@client.event
# {{{ Commands
@command
@command
@command
@command
# }}}
print("https://discordapp.com/oauth2/authorize?&client_id=" + auth['clientId'] + "&scope=bot&permissions=0")
client.run(auth['token'])
|
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2,
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4798,
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5450,
1378,
15410,
585,
1324,
13,
785,
14,
12162,
1071,
17,
14,
9800,
1096,
30,
5,
16366,
62,
312,
2625,
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6284,
17816,
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20520,
1343,
366,
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525,
8481,
28,
15,
4943,
198,
16366,
13,
5143,
7,
18439,
17816,
30001,
6,
12962,
198
] | 2.699605 | 253 |
from threading import Timer
import mido
import time
from singleton import Singleton
from activelayer import ActiveLayer, ActiveLayerIdentifier
|
[
6738,
4704,
278,
1330,
5045,
263,
198,
11748,
3095,
78,
198,
11748,
640,
198,
198,
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6738,
4075,
29289,
1330,
14199,
49925,
11,
14199,
49925,
33234,
7483,
628,
198
] | 4.171429 | 35 |
# coding: utf-8
import time
import pickle
import socket
import random
import logging
import argparse
import configparser
import threading
from utils import contains_successor
from queue import Queue
##############################################NODE DISCOVERY##############################################
# Method:
# 1. First node starts sending NODE_DISCOVERY packages with the args containg a dictionary of KEY: ID ; VALUE: Type
# {type:NODE_DISCOVERY,args{ {ENTITY-IDdictionary}, int rounds }}
# 2. Package gets sent to the next node in ring
# 3. When it reaches a node, the node checks whether the dictionary is complete:
# NOT COMPLETE - Add our ENTITY-ID to the dictionary
# COMPLETE - #1. Increment rounds
# 2. Check if rounds is 1 or 2
# 2: [STOP PROCESS]
# 1: Register the dictionary as our own
# 4. Send package to next node
# Q - How to check if it's full?
# A - Check if the current node's ID is the same as the Token Generator's ID (since this is the one where the discovery
# starts)
# Q - How many go-rounds does this method take?
# A - 2. 1 to build the dictionary + 1 to register on each node
# Q - How to check if we're done?
# A - We use a regDone int that's used to check how many nodes have registered the dictionary
##############################################NODE DISCOVERY##############################################
|
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198
] | 3.092593 | 486 |
import os
import numpy as np
from protoclass.preprocessing import StandardTimeNormalization
path_root = '/data/prostate/pre-processing/lemaitre-2016-nov/norm-objects'
shift_patient = []
# We have to open each npy file
for root, dirs, files in os.walk(path_root):
# Create the string for the file to read
for f in files:
filename = os.path.join(root, f)
# Load the normalization object
dce_norm = StandardTimeNormalization.load_from_pickles(filename)
shift_patient.append(dce_norm.fit_params_['shift-int'])
# Stack the different array vetically
shift_patient = np.vstack(shift_patient)
shift_patient = np.max(shift_patient, axis=0)
|
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# Generated by Django 2.0.3 on 2018-03-30 22:28
import ckeditor.fields
from django.db import migrations, models
|
[
2,
2980,
515,
416,
37770,
362,
13,
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13,
18,
319,
2864,
12,
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42625,
14208,
13,
9945,
1330,
15720,
602,
11,
4981,
628
] | 2.923077 | 39 |
end
print max(-1,-2) # = -1
print max(1,2) # = 2
print max(3,4) # = 4
print max(1.0, 1.5) # = 1.500000
|
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198
] | 1.644737 | 76 |
'''Cross validation codes.'''
"""
kwargs: keyword arguments to runSimulation
order of positional arguments: obs_data, model, parameters
"""
from collections import namedtuple
import lmfit # Fitting lib
import matplotlib.pyplot as plt
import math
import numpy as np
import pandas as pd
import random
import tellurium as te
TIME = "time"
ME_LEASTSQ = "leastsq"
ME_DIFFERENTIAL_EVOLUTION = "differential_evolution"
ME_BOTH = "both"
PER05 = 0.05
PER95 = 0.95
TIME_INTERVAL = 10
# data - named_array result
# road_runner - road_runner instance created
SimulationResult = namedtuple("SimulationResult",
"data road_runner")
ResidualCalculation = namedtuple("ResidualCalculation",
"residuals road_runner")
Statistic = namedtuple("Statistic", "mean std ci_low ci_high")
############## CONSTANTS ######################
# Default simulation model
MODEL = """
A -> B; k1*A
B -> C; k2*B
A = 5;
B = 0;
C = 0;
k1 = 0.1
k2 = 0.2
"""
CONSTANTS = ['k1', 'k2']
NOISE_STD = 0.5
NUM_POINTS = 10
KWARGS_NUM_POINTS = "num_points"
PARAMETERS = lmfit.Parameters()
PARAMETERS.add('k1', value=1, min=0, max=10)
PARAMETERS.add('k2', value=1, min=0, max=10)
ROAD_RUNNER = None
SIM_TIME = 30
# Default parameters values
DF_CONFIDENCE_INTERVAL = (5, 95)
DF_BOOTSTRAP_COUNT = 5
DF_NUM_FOLDS = 3
DF_METHOD = "least_squares"
############## FUNCTIONS ######################
def cleanColumns(df_data, is_force_time=True):
"""
Cleans the column names in the dataframe,
removing "[", "]". Makes time index.
:param pd.DataFrame df_data: Simulation data output.
:param bool is_force_time: force time to factors of 10
"""
df = df_data.copy()
columns = []
for col in df_data.columns:
new_col = str(col)
new_col = new_col.replace("[", "")
new_col = new_col.replace("]", "")
columns.append(new_col)
df.columns = columns
if TIME in df.columns:
df = df.set_index(TIME)
if df.index.name == TIME:
if is_force_time:
df.index = [float(v*TIME_INTERVAL) for v in range(len(df))]
df.index.name = TIME
return df
def matrixToDF(matrix, columns=None, index=None):
"""
Converts an array to a dataframe. If the index is
time, then rounds to a tenth.
:param np.arrayy matrix:
pd.DataFrame : already converted
:param list index: index for dataframe
:return pd.DataFrame: Columns are variables w/o [, ].
index is time.
"""
if isinstance(matrix, pd.DataFrame):
df = cleanColumns(matrix)
else:
df = pd.DataFrame(matrix)
if columns is None:
try:
columns = matrix.colnames
except:
pass
if columns is not None:
df.columns = columns
return cleanColumns(df)
def matrixToDFWithoutTime(matrix, columns=None):
"""
Converts an array to a dataframe, deleting time as a column.
:param np.arrayy matrix:
pd.DataFrame : already converted
:return pd.DataFrame:
"""
if isinstance(matrix, pd.DataFrame):
df = matrix.copy()
else:
df = matrixToDF(matrix, columns=columns)
if TIME != df.index.name:
df = df[df.columns.tolist()[1:]]
return df
def reshapeData(matrix, indices=None):
"""
Re-structures matrix as an array for just the rows
in indices.
:param array matrix: matrix of data
:param list-int indices: indexes to include in reshape
"""
if indices is None:
nrows = np.shape(matrix)[0]
indices = range(nrows)
num_columns = np.shape(matrix)[1]
trimmed_matrix = matrix[indices, :]
return np.reshape(trimmed_matrix, num_columns*len(indices))
def arrayDifference(matrix1, matrix2, indices=None):
"""
Calculates matrix1 - matrix2 as a nX1 array for the rows
specified in indices.
"""
array1 = reshapeData(matrix1, indices=indices)
array2 = reshapeData(matrix2, indices=indices)
return (array1 - array2)
def makeArrayFromMatrix(df_mat, indices):
"""
Returns an constructured from specified rows
organized in sequence by columns.
:param pd.DataFrame df_mat:
:param list-int indices:
:return np.array:
"""
df = df_mat.loc[df_mat.index[indices], :]
array = df.T.values
return np.reshape(array, len(indices)*len(df.columns))
def makeDFWithCommonColumns(df1, df2):
"""
Returns dataframes that have columns in common.
"""
columns = set(df1.columns).intersection(df2.columns)
df1_sub = df1.copy()
df2_sub = df2.copy()
df1_sub = df1_sub[columns]
df2_sub = df2_sub[columns]
return df1_sub, df2_sub
def calcRsq(observations, estimates, indices=None):
"""
Computes RSQ for simulation results.
:param matrix observations: non-time values
: pd.DataFrame : no time column
:param matrix estimates: non-time values
: pd.DataFrame : no time column
:param list-int indices:
:return float:
"""
df_obs = matrixToDF(observations)
df_est = matrixToDF(estimates)
if indices is None:
indices = range(len(df_obs))
#
df_obs_sub, df_est_sub = makeDFWithCommonColumns(df_obs, df_est)
arr_obs = makeArrayFromMatrix(df_obs_sub, indices)
arr_est = makeArrayFromMatrix(df_est_sub, indices)
try:
arr_rsq = arr_obs - arr_est
except:
import pdb; pdb.set_trace()
arr_rsq = arr_rsq*arr_rsq
rsq = 1 - sum(arr_rsq) / np.var(arr_obs)
return rsq
def makeParameters(constants=CONSTANTS, values=1, mins=0, maxs=10):
"""
Constructs parameters for the constants provided.
:param list-str constants: names of parameters
:param list-float values: initial value of parameter
if not list, the value for list
:param list-float mins: minimum values
if not list, the value for list
:param list-float maxs: maximum values
if not list, the value for list
"""
#
values = makeList(values, len(constants))
mins = makeList(mins, len(constants))
maxs = makeList(maxs, len(constants))
parameters = lmfit.Parameters()
for idx, constant in enumerate(constants):
parameters.add(constant,
value=values[idx], min=mins[idx], max=maxs[idx])
return parameters
def makeAverageParameters(list_parameters):
"""
Averages the values of parameters in a list.
:param list-lmfit.Parameters list_parameters:
:return lmfit.Parameters: sets min, max to extremes of list
"""
result_parameters = lmfit.Parameters()
names = list_parameters[0].valuesdict().keys()
for name in names:
values = []
mins = []
maxs = []
for parameters in list_parameters:
values.append(parameters.valuesdict()[name])
mins.append(parameters.get(name).min)
maxs.append(parameters.get(name).max)
value = np.mean(values)
min_val = min(mins)
max_val = min(maxs)
result_parameters.add(name, value=value,
min=min_val, max=max_val)
return result_parameters
def runSimulation(sim_time=SIM_TIME,
num_points=NUM_POINTS, road_runner=ROAD_RUNNER, parameters=None,
**kwargs):
"""
Runs the simulation model rr for the parameters.
:param int sim_time: time to run the simulation
:param int num_points: number of timepoints simulated
:param ExtendedRoadRunner road_runner:
:param lmfit.Parameters parameters:
:param dict kwargs: parameters used in makeSimulation
:return SimulationResult:
"""
if road_runner is None:
road_runner = makeSimulation(parameters=parameters, **kwargs)
else:
road_runner.reset()
setSimulationParameters(road_runner, parameters)
data = road_runner.simulate (0, sim_time, num_points)
simulation_result = SimulationResult(
data=data,
road_runner=road_runner,
)
return simulation_result
def setSimulationParameters(road_runner, parameters=None):
"""
Sets parameter values in a road runner instance.
:param ExtendedRoadRunner road_runner:
:param lmfit.Parameters parameters:
"""
if parameters is not None:
parameter_dict = parameters.valuesdict()
# Set the simulation constants for all parameters
for constant in parameter_dict.keys():
stmt = "road_runner.%s = float(parameter_dict['%s'])" % (
constant, constant)
try:
exec(stmt)
except:
import pdb; pdb.set_trace()
def makeSimulation(parameters=None, model=MODEL):
"""
Creates an road runner instance for the simulation.
:param lmfit.Parameters parameters:
:param str model:
:return ExtendedRoadRunner:
"""
road_runner = te.loada(model)
setSimulationParameters(road_runner, parameters)
return road_runner
def plotTimeSeries(data, is_scatter=False, title="",
columns=None, is_plot=True):
"""
Constructs a time series plot of simulation data.
:param array data: first column is time
:param bool is_scatter: do a scatter plot
:param str title: plot title
"""
if not isinstance(data, pd.DataFrame):
df = pd.DataFrame(data)
else:
df = data
columns = df.columns.tolist()
xv = df[columns[0]]
if is_scatter:
plt.plot (xv, df[columns[1:]], marker='*', linestyle='None')
else:
plt.plot (xv, df[columns[1:]])
plt.title(title)
plt.xlabel("Time")
plt.ylabel("Concentration")
if columns is None:
columns = np.repeat("", np.shape(data)[1])
plt.legend(columns)
if is_plot:
plt.show()
def foldGenerator(num_points, num_folds):
"""
Creates generator for test and training data indices.
:param int num_points: number of data points
:param int num_folds: number of folds
:return iterable: Each iteration produces a tuple
First element: training indices
Second element: test indices
"""
indices = range(num_points)
for remainder in range(num_folds):
test_indices = []
for idx in indices:
if idx % num_folds == remainder:
test_indices.append(idx)
train_indices = np.array(
list(set(indices).difference(test_indices)))
test_indices = np.array(test_indices)
yield train_indices, test_indices
def makeObservations(sim_time=SIM_TIME, num_points=NUM_POINTS,
noise_std=NOISE_STD, **kwargs):
"""
Creates synthetic observations.
:param int sim_time: time to run the simulation
:param int num_points: number of timepoints simulated
:param float noise_std: Standard deviation for random noise
:param dict kwargs: keyword parameters used by runSimulation
:return pd.DataFrame: simulation results with randomness
"""
# Create true values
simulation_result = runSimulation(sim_time=sim_time,
num_points=num_points,
**kwargs)
data = simulation_result.data
num_cols = len(data.colnames)
# Add randomness
for i in range (num_points):
for j in range(1, num_cols):
data[i, j] = max(data[i, j] \
+ np.random.normal(0, noise_std, 1), 0)
return matrixToDF(data)
def calcSimulationResiduals(obs_data, parameters,
indices=None, **kwargs):
"""
Runs a simulation with the specified parameters and calculates residuals
for the train_indices.
:param array obs_data: matrix of data, first col is time.
pd.DataFrame : index is time
:param lmfit.Parameters parameters:
:param list-int indices: indices for which calculation is done
if None, then all.
:param dict kwargs: optional parameters passed to simulation
:return ResidualCalculation:
"""
df_obs = matrixToDFWithoutTime(obs_data)
if indices is None:
indices = range(len(df_obs))
if not KWARGS_NUM_POINTS in kwargs.keys():
kwargs[KWARGS_NUM_POINTS] = len(df_obs)
simulation_result = runSimulation(parameters=parameters,
**kwargs)
df_sim = matrixToDFWithoutTime(simulation_result.data)
# Compute differences
df_obs, df_sim = makeDFWithCommonColumns(df_obs, df_sim)
arr_obs = makeArrayFromMatrix(df_obs, indices)
arr_sim = makeArrayFromMatrix(df_sim, indices)
residuals = arr_obs - arr_sim
residual_calculation = ResidualCalculation(residuals=residuals,
road_runner=simulation_result.road_runner)
return residual_calculation
# TODO: Fix handling of obs_data columns. May not be
# a named array, as in bootstrap.
def fit(obs_data, indices=None, parameters=PARAMETERS,
method=ME_LEASTSQ, **kwargs):
"""
Does a fit of the model to the observations.
:param ndarray obs_data: matrix of observed values with time
as the first column
pd.DataFrame : time is index
:param list-int indices: indices on which fit is performed
:param lmfit.Parameters parameters: parameters fit
:param str method: optimization method; both means
differential_evolution followed by leastsq
:param dict kwargs: optional parameters passed to runSimulation
:return lmfit.Parameters:
"""
global road_runner
road_runner = ROAD_RUNNER
#
#
if method == ME_BOTH:
parameters = estimateParameters(ME_DIFFERENTIAL_EVOLUTION,
parameters)
return estimateParameters(ME_LEASTSQ, parameters)
else:
return estimateParameters(method, parameters)
def crossValidate(obs_data, method=DF_METHOD,
sim_time=SIM_TIME,
num_points=None, parameters=PARAMETERS,
num_folds=3, **kwargs):
"""
Performs cross validation on an antimony model.
:param ndarray obs_data: data to fit;
columns are species;
rows are time instances
first column is time
pd.DataFrame : time is index
:param int sim_time: length of simulation run
:param int num_points: number of time points produced.
:param lmfit.Parameters: parameters to be estimated
:param dict kwargs: optional arguments used in simulation
:return list-lmfit.Parameters, list-float: parameters and RSQ from folds
"""
df_obs = matrixToDF(obs_data)
if num_points is None:
num_points = len(df_obs)
# Iterate for for folds
fold_generator = foldGenerator(num_points, num_folds)
result_parameters = []
result_rsqs = []
road_runner = ROAD_RUNNER
for train_indices, test_indices in fold_generator:
# This function is defined inside the loop because it references a loop variable
new_parameters = parameters.copy()
fitted_parameters = fit(df_obs, method=method,
indices=train_indices, parameters=new_parameters,
sim_time=sim_time, num_points=num_points,
**kwargs)
result_parameters.append(fitted_parameters)
# Run the simulation using
# the parameters estimated using the training data.
simulation_result = runSimulation(road_runner=road_runner,
sim_time=sim_time, num_points=num_points,
parameters=fitted_parameters, **kwargs)
road_runner = simulation_result.road_runner
df_est = matrixToDF(simulation_result.data)
# Calculate RSQ
rsq = calcRsq(df_obs, df_est, test_indices)
result_rsqs.append(rsq)
return result_parameters, result_rsqs
def makeResidualDF(obs_data, model, parameters,
road_runner=ROAD_RUNNER,
**kwargs):
"""
Calculate residuals for each chemical species.
:param named_array/pd.DataFrame obs_data: matrix of observations; first column is time; number of rows is num_points
:param lmfit.Parameters parameters:
:param dict kwargs: optional arguments to runSimulation
:return pd.DataFrame: matrix of residuals; columns are chemical species
"""
df_obs = matrixToDF(obs_data)
if df_obs.index.name != TIME:
import pdb; pdb.set_trace()
raise ValueError("Invalid observational data")
residual_calculation = calcSimulationResiduals(df_obs, parameters,
model=model, road_runner=road_runner, **kwargs)
road_runnder = residual_calculation.road_runner
residuals = residual_calculation.residuals
# Reshape the residuals by species
num_species = len(df_obs.columns)
nrows = int(len(residuals) / num_species)
result = np.reshape(residuals, (nrows, num_species))
df_res = pd.DataFrame(result)
df_res.columns = df_obs.columns
return df_res
def makeSyntheticObservations(df_res, **kwargs):
"""
Constructs synthetic observations for the model.
:param pd.DataFrame df_res: matrix of residuals; columns are species; number of rows is num_points
:param dict kwargs: optional arguments to runSimulation
:return pd.DataFrame: index is time
"""
simulation_result = runSimulation(**kwargs)
df_data = matrixToDF(simulation_result.data)
df_data, df_res = makeDFWithCommonColumns(df_data, df_res)
df_res.columns = df_data.columns
nrows = len(df_data)
ncols = len(df_data.columns)
for col in df_data.columns:
for idx in df_data.index:
random_index = df_res.index[np.random.randint(0, nrows)]
df_data.loc[idx, col] = df_data.loc[idx, col] \
+ df_res.loc[random_index, col]
df_data = df_data.applymap(lambda v: max(v, 0))
return df_data
def doBootstrapWithResiduals(df_res,
method=DF_METHOD, count=DF_BOOTSTRAP_COUNT, **kwargs):
"""
Performs bootstrapping by repeatedly generating synthetic observations.
:param pd.DataFrame residuals_matrix:
:param int count: number of iterations in bootstrap
:param dict kwargs: optional arguments to runSimulation
"""
list_parameters = []
for _ in range(count):
df_data = makeSyntheticObservations(df_res, **kwargs)
parameters = fit(df_data, method=method, **kwargs)
list_parameters.append(parameters)
return list_parameters
def doBootstrap(df_data, model, parameters,
method=DF_METHOD, count=DF_BOOTSTRAP_COUNT,
confidence_limits=DF_CONFIDENCE_INTERVAL, **kwargs):
"""
Performs bootstrapping by repeatedly generating synthetic observations,
calculating the residuals as well.
:param pd.DataFrame df_data: index is time
:param str model:
:param lmfit.Parameters parameters:
:param int count: number of iterations in bootstrap
:param dict kwargs: optional arguments to runSimulation
:return dict: confidence limits
"""
df_res = makeResidualDF(df_data, model,
parameters, **kwargs)
list_parameters = doBootstrapWithResiduals(df_res,
method=method,
count=count, model=model, parameters=parameters, **kwargs)
return makeParameterStatistics(list_parameters,
confidence_limits=confidence_limits)
def calcStatistic(values, confidence_limits=[PER05, PER95]):
"""
Calculates Statistic
:param list-float values:
:return Statistic:
"""
quantiles = np.quantile(values, confidence_limits)
return Statistic(
mean =np.mean(values),
std = np.std(values),
ci_low = quantiles[0],
ci_high = quantiles[1],
)
def makeParameterStatistics(list_parameters,
confidence_limits=DF_CONFIDENCE_INTERVAL):
"""
Computes the mean and standard deviation of the parameters in a list of parameters.
:param list-lmfit.Parameters
:param (float, float) confidence_limits: if none, report mean and variance
:return dict: key is the parameter name; value is ParameterStatistic
"""
statistic_dict = {}
parameter_names = list(list_parameters[0].valuesdict().keys())
for name in parameter_names:
statistic_dict[name] = []
for parameters in list_parameters:
statistic_dict[name].append(parameters.valuesdict()[name])
# Calculate the statistics
for name in statistic_dict.keys():
statistic_dict[name] = calcStatistic(statistic_dict[name])
return statistic_dict
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] | 2.721607 | 7,044 |
from qcore.asserts import assert_eq
import random
from python_project_template.utils import random_string
|
[
6738,
10662,
7295,
13,
30493,
82,
1330,
6818,
62,
27363,
198,
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198,
6738,
21015,
62,
16302,
62,
28243,
13,
26791,
1330,
4738,
62,
8841,
628
] | 3.857143 | 28 |
import unittest
import torch
from pytorch_metric_learning.losses import NPairsLoss
from pytorch_metric_learning.utils import common_functions as c_f, loss_and_miner_utils as lmu
|
[
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] | 3.016949 | 59 |
import requests
import json
import datetime
import pandas as pd
import numpy as np
import platform
# 有時候的登入狀態會抓不到資料:
# 要抓的港口 'ID': 港口名稱
port_ID_map = {'87':'Los Angeles','2727':'longBeach','93':'Oakland','1253':'Shanhi','1006':'Yantian',
'290':'Singapore','172':'Hamburg','2036':'Rotterdam','199':'Felixstowe'}
#船隻種類
ship_type = ['CONTAINER SHIPS','DRY BREAKBULK','DRY BULK','LNG CARRIERS','LPG CARRIERS',
'PASSENGER SHIPS','RO/RO','WET BULK','SUPPORTING VESSELS','OTHER MARKETS']
url = 'https://www.marinetraffic.com/en/users/ajax_login'
headers = {
'User-Agent':'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.164 Safari/537.36'
,'Content-Type':'application/x-www-form-urlencoded; charset=UTF-8'
,'X-Requested-With':'XMLHttpRequest'
}
form_data = {'email': '[email protected]',
'password': 'lay9821529',
'remember': '1'}
# use session to login
s = requests.Session()
#login
s.post(url,headers = headers, data = form_data)
print(s)
# Define 合併函數的裝飾函數
@merge_data_func()
# 主爬蟲
# 要抓的港口 'ID': 港口名稱
port_ID_map = {'87':'Los Angeles','2727':'longBeach','93':'Oakland','1253':'Shanhi','1006':'Yantian',
'290':'Singapore','172':'Hamburg','2036':'Rotterdam','199':'Felixstowe'}
#船隻種類
ship_type = ['CONTAINER SHIPS','DRY BREAKBULK','DRY BULK','LNG CARRIERS','LPG CARRIERS',
'PASSENGER SHIPS','RO/RO','WET BULK','SUPPORTING VESSELS']
# 放所有的資料的地方
result = []
# 迴圈跑所有的港口
for port_ID,port_name in port_ID_map.items():
url = f'https://www.marinetraffic.com/en/ais/getHighcharts/'
myobj = {'PORT_ID':port_ID}
# 分別要去拿到達的時間 跟離開的時間
for job in ['TaA','TaP']:
# 如果現在要拿的是 到達的時間
if job == 'TaA':
myobj['configID'] = 'VesselType_TaA'
else:
myobj['configID'] = 'VesselType_TaP'
r = s.post(url,headers = headers, data = myobj)
# print(r.text)
response = json.loads(r.text)
for i in range(len(response)):
if job == 'TaA':
response[i]['categorization'] = 'Arrive'
else:
response[i]['categorization'] = 'Departure'
result = response + result
df = pd.DataFrame(result)
# 轉型把數字都轉成float
# print(df.columns)
df.loc[:,ship_type] = df.loc[:,ship_type].astype(float)
# 把port_ID maping 到看得懂的名字
df['Port_ID'] = df['Port_ID'].apply(lambda x: port_ID_map[x])
# print(df['Port_ID'].to_string())
# 重新安排欄位名稱
df = df[['Calendar_Week','Port_ID','categorization','ALL','CONTAINER SHIPS','DRY BREAKBULK'
,'DRY BULK','LNG CARRIERS','LPG CARRIERS','PASSENGER SHIPS','RO/RO','WET BULK'
,'SUPPORTING VESSELS']]
print(df)
# 檔案位置
if platform.system() == "Windows":
# Local 端
path = 'static/data/Shipping/congestion.csv'
else:
# AWS 端
path = "/home/cathaylife04/smartphone/iphone11/static/data/Shipping/congestion.csv"
# 執行合併檔案
congestion(df,data_name = path)
|
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] | 1.848523 | 1,591 |
#!/usr/bin/env python
import unittest
import sys
import os.path
remotedir = os.path.dirname(os.path.dirname(os.path.dirname((__file__))))
sys.path.insert(0, remotedir)
from robotremoteserver import RobotRemoteServer
if __name__ == '__main__':
unittest.main()
|
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import json
import logging
import xbmc
logger = logging.getLogger(__name__)
_JSONRPC_TEMPLATE = """{{"jsonrpc":"2.0","id":0,"method":"{method}","params":{params}}}"""
PLAYER_MUSIC = 0
PLAYER_VIDEO = 1
PLAYER_PICTURE = 2
LIST_FIELD_ART = "art"
LIST_FIELD_UNIQUEID = "uniqueid"
|
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#!/usr/bin/python
# (c) 2021, NetApp, Inc
# GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt)
from __future__ import absolute_import, division, print_function
__metaclass__ = type
DOCUMENTATION = '''
module: na_ontap_fpolicy_scope
short_description: NetApp ONTAP - Create, delete or modify an FPolicy policy scope configuration.
extends_documentation_fragment:
- netapp.ontap.netapp.na_ontap
version_added: '21.4.0'
author: NetApp Ansible Team (@carchi8py) <[email protected]>
description:
- Create, delete or modify an FPolicy policy scope.
options:
state:
description:
- Whether the FPolicy policy scope is present or not
choices: ['present', 'absent']
default: present
type: str
vserver:
description:
- the name of the vserver to create the scope on
required: true
type: str
name:
description:
- Name of the policy. The FPolicy policy must exist for the scope to be created.
required: true
type: str
check_extensions_on_directories:
description:
- Indicates whether directory names are also subjected to extensions check, similar to file names.
- By default, the value is true if policy is configured with Native engine, false otherwise.
type: bool
export_policies_to_exclude:
description:
- Export Policies to exclude for file access monitoring. By default no export policy is selected.
type: list
elements: str
export_policies_to_include:
description:
- Export policies to include for file access monitoring. By default no export policy is selected.
type: list
elements: str
file_extensions_to_exclude:
description:
- File extensions excluded for screening. By default no file extension is selected.
type: list
elements: str
file_extensions_to_include:
description:
- File extensions included for screening. By default no file extension is selected.
type: list
elements: str
is_monitoring_of_objects_with_no_extension_enabled:
description:
- Indicates whether monitoring of objects with no extension is required. By default, the value is false.
type: bool
shares_to_exclude:
description:
- Shares to exclude for file access monitoring. By default no share is selected.
type: list
elements: str
shares_to_include:
description:
- Shares to include for file access monitoring. By default no share is selected.
type: list
elements: str
volumes_to_exclude:
description:
- Volumes that are inactive for the file policy. The list can include items which are regular expressions, such as 'vol*' or 'user?'.
- Note that if a policy has both an exclude list and an include list, the include list is ignored by the filer when processing user requests.
- By default no volume is selected.
type: list
elements: str
volumes_to_include:
description:
- Volumes that are active for the file policy. The list can include items which are regular expressions, such as 'vol*' or 'user?'.
- By default no volume is selected.
type: list
elements: str
'''
EXAMPLES = """
- name: Create FPolicy scope
na_ontap_fpolicy_scope:
state: present
vserver: GBSMNAS80LD
name: policy1
export_policies_to_include: export1
shares_to_include: share1
username: "{{ username }}"
password: "{{ password }}"
hostname: "{{ hostname }}"
use_rest: "{{ use_rest }}"
- name: Modify FPolicy scope
na_ontap_fpolicy_scope:
state: present
vserver: GBSMNAS80LD
name: policy1
export_policies_to_include: export1,export2
shares_to_include: share1,share2
username: "{{ username }}"
password: "{{ password }}"
hostname: "{{ hostname }}"
use_rest: "{{ use_rest }}"
- name: Delete FPolicy scope
na_ontap_fpolicy_scope:
state: absent
vserver: GBSMNAS80LD
name: policy1
username: "{{ username }}"
password: "{{ password }}"
hostname: "{{ hostname }}"
use_rest: "{{ use_rest }}"
"""
RETURN = """
"""
import traceback
from ansible.module_utils.basic import AnsibleModule
from ansible.module_utils._text import to_native
import ansible_collections.netapp.ontap.plugins.module_utils.netapp as netapp_utils
from ansible_collections.netapp.ontap.plugins.module_utils.netapp_module import NetAppModule
from ansible_collections.netapp.ontap.plugins.module_utils.netapp import OntapRestAPI
import ansible_collections.netapp.ontap.plugins.module_utils.rest_response_helpers as rrh
def main():
"""
Execute action from playbook
"""
command = NetAppOntapFpolicyScope()
command.apply()
if __name__ == '__main__':
main()
|
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"""Console script for codebots.
You can get detaled information about each of the bots with the :code:`--help` option.
.. code-block:: bash
codebots --help
emailbot --help
telebot --help
slackbot --help
sshbot --help
deploybot --help
latexbot --help
drivebot --help
"""
import sys
import os
from pathlib import Path
import click
import codebots
from codebots.bots import SlackBot
from codebots.bots import TeleBot
from codebots.bots import EmailBot
from codebots.bots import sshBot
from codebots.bots.deploybot import DeployBot
from codebots.bots.latexbot import LatexBot
from codebots.bots.drivebot import DriveBot
from codebots.utilities.ssh import gen_keypair, add_pubkey_to_server
from codebots.utilities.tokens import add_token, get_telegram_chatid, set_token_dir, reset_token_dir
from codebots.utilities.deploy import configure_local, configure_server
# -------------------------------- MAIN ----------------------------------#
@click.group()
def main():
"""base bot to setup the common settings for all the other bots.
Run `codebots ono-o-one` for more info.
"""
pass
@main.command()
def one_o_one():
"""Basic explanation of command line usage."""
click.echo("\nHey there! this is codebots, a family of bots here to help you!\n\n"
"To use codebots directly from the command line, type the name of your bot followed by the action.\n"
"For example, this command sends a message through slack:\n\n"
" slackbot --channel=random \"Hello from your slacbot!\"\n")
@main.command()
def get_tokens_path():
"""Get the path to the tokens folder.\n
Return\n
------\n
str\n
path to the folder containing the tokens or passwords for the codebots.\n
"""
out = codebots.TOKENS
click.echo(out)
@main.command()
@click.argument('path')
def set_tokens_path(path):
"""Set the path to the tokens folder.\n
Parameters\n
----------\n
path : str\n
path to the folder containing the tokens or passwords for the codebots.\n
"""
out = set_token_dir(path)
click.echo(out)
@main.command()
def reset_tokens_path():
"""Reset the tokens path to the default (~/.tokens)."""
out = reset_token_dir()
click.echo(out)
# -------------------------------- SLACK ----------------------------------#
@click.group()
def slackbot():
"""bot to interact with slack"""
pass
@slackbot.command()
@click.argument('token')
def set_token(token):
"""create the token file with the credentials.\n
Parameters\n
----------\n
token : str\n
token of the telegram bot.\n
chatid : str\n
chatID of the chat with the bot.\n
"""
out = add_token("slack", bot_token=token)
click.echo(out)
@slackbot.command()
@click.option('--channel', default='general', help='the channel you want to send the message to')
@click.argument('message', default='Ciao Mamma!')
def send(message, channel):
"""Send a message using slack.\n
message : txt\n
the message you want to send to yo.ur slack channel, by default `Ciao Mamma!`
"""
bot = SlackBot()
bot.send_message(channel, message)
# ----------------------------- TELEGRAM ----------------------------------#
@click.group()
def telebot():
"""bot to interact with telegram"""
pass
@telebot.command()
@click.argument('message', default='Ciao Mamma!')
def send(message):
"""Send a message using slack.\n
message : txt\n
the message you want to send to yo.ur slack channel, by default `Ciao Mamma!`
"""
bot = TeleBot()
bot.send_message(message)
@telebot.command()
@click.argument('token')
def set_token(token):
"""create the token file with the credentials.\n
Parameters\n
----------\n
token : str\n
token of the telegram bot.\n
"""
try:
chatid = get_telegram_chatid(token)
except Exception:
raise ConnectionError("Something went wrong! Did you start a chat with your bot on telegram?")
out = add_token("telegram", bot_token=token, bot_chatID=str(chatid))
click.echo(out)
# -------------------------------- EMAIL ----------------------------------#
@click.group()
def emailbot():
"""bot to send emails from the command line"""
pass
@emailbot.command()
@click.argument('receiver', default='[email protected]')
@click.argument('subject', default='Ciao')
@click.argument('body', default='Ciao Mamma!')
# @click.option('--attach', type='path', help='path to any file you want to attach')
def send(receiver, subject, body):
"""Send an email to an email address.\n
Parameters\n
----------\n
receiver : str\n
email address of the receiver\n
subject : str\n
subject of the email\n
body : str\n
body text of the email\n
attachment : str, optional\n
path to the file to attach, by default None\
"""
# sender = Sender.form_file(".tokens/email")
receiver = "[email protected]"
subject = "message from bot"
body = "This message was sent by a bot"
# attach = "document.pdf"
bot = EmailBot()
bot.send_email(receiver, subject, body)
@emailbot.command()
@click.argument('username')
@click.argument('password')
def set_token(username, password):
"""create the token file with the credentials.\n
Parameters\n
----------\n
token : str\n
token of the telegram bot.\n
chatid : str\n
chatID of the chat with the bot.\n
"""
out = add_token("email", username=username, password=password)
click.echo(out)
# --------------------------------- SSH -----------------------------------#
@click.group()
def sshbot():
"""bot to remotely operate on a (linux) server"""
pass
@sshbot.command()
@click.argument('hostname')
@click.argument('username')
@click.option('--password', default='', help='password to access the host or to decrypt the private key')
@click.option('--pvtkey', default='', help='path to the private key')
def set_token(hostname, username, password, pvtkey):
"""create the token file with the credentials.\n
NOTE: to be useful either the password or the ssh private key must be passed.
Parameters\n
----------\n
hostname : str\n
ip address of the server.\n
username : str\n
username on the server.\n
"""
out = add_token(alias=f"{username}@{hostname}", hostname=hostname,
username=username, password=password, pvtkey=pvtkey)
click.echo(out)
@sshbot.command()
@click.option('--ssh_folder', default=None, help='path where the key pair will be saved, by default None (the `USER/.ssh` folder will be used)')
@click.option('--password', default=None, help='encrypt the private key with a password')
def genkeys(ssh_folder, password):
"""Create a set of public and private keys and save them in the given folder.
"""
out = gen_keypair(ssh_folder, password)
click.echo(out)
@sshbot.command()
@click.argument('hostname')
@click.argument('username')
@click.argument('password')
@click.option('--ssh_folder', default=None, help='path where the key pair will be saved')
def link_keys(hostname, username, password, ssh_folder):
"""Adds the public key to the server's list.\n
Parameters\n
----------\n
hostname : str\n
ip address of the server.\n
username : str\n
username on the server.\n
password : str\n
password on the server, by default empty.\n
"""
bot = sshBot(config_file=None, hostname=hostname, username=username, password=password, pvtkey="")
if not ssh_folder:
ssh_folder = os.path.join(str(Path.home()), '.ssh')
out = add_pubkey_to_server(bot, ssh_folder)
click.echo(out)
out = add_token(f"{username}@{hostname}", hostname=hostname, username=username,
password="", pvtkey=os.path.join(ssh_folder, 'id_rsa'))
click.echo(out)
# ------------------------------- DEPLOY ----------------------------------#
@click.group()
def deploybot():
"""bot to deploy projects to a server"""
pass
@deploybot.command()
@click.argument('project')
@click.argument('address')
@click.argument('local')
@click.argument('server')
@click.option('--branch', default='main', help='branch to push to.')
@click.option('--sshbot', default=None, help='instance of an `sshBot` with access to the server.')
def configure(project, address, local, server, branch, sshbot):
"""Configure a local repository to sync with a server.\n
Parameters\n
----------\n
project : str\n
name of the project for the setting file.\n
address : str\n
server address (username@host).\n
local : str\n
path to the local clone of the repository.\n
server : str\n
path to the server bare repository. If no repository is present\n
at the given location a bare new one is created.\n
"""
out = add_token(bot=project, server_address=address, local_repo_path=local, server_repo_path=server)
click.echo(out)
bot = DeployBot(project)
out = configure_local(bot.local_repo, bot.server_complete_path)
click.echo(out)
out = configure_server(bot.server_repo_path, branch, sshbot)
click.echo(out)
@deploybot.command()
@click.argument('project')
def configure_local(project):
"""Configure a local repository to sync with a server.\n
Parameters\n
----------\n
project : str\n
name of the project for the setting file.\n
"""
bot = DeployBot(project)
out = configure_local(bot.local_repo, bot.server_complete_path)
click.echo(out)
@deploybot.command()
@click.argument('project')
@click.option('--branch', default='main', help='branch to push to.')
@click.option('--sshbot', default=None, help='instance of an `sshBot` with access to the server.')
def configure_remote(project, branch, sshbot):
"""Configure a local repository to sync with a server.\n
Parameters\n
----------\n
project : str\n
name of the project for the setting file.\n
address : str\n
server address (username@host).\n
local : str\n
path to the local clone of the repository.\n
server : str\n
path to the server bare repository. If no repository is present\n
at the given location a bare new one is created.\n
"""
bot = DeployBot(project)
out = configure_server(bot.server_repo_path, branch, sshbot)
click.echo(out)
# ------------------------------- LATEX ----------------------------------#
@click.group()
def latexbot():
"""bot to help with latex documents"""
pass
@latexbot.command()
@click.option('--git', default=True, help='if True, install git')
@click.option('--pandoc', default=True, help='if True, install pandoc')
@click.option('--miktex', default=False, help='if True, install miktex')
def configure(git, pandoc, miktex):
"""Download dependencies and set everything up.\n
"""
bot = LatexBot()
out = bot.install_dependencies(git, pandoc, miktex)
click.echo(out)
@latexbot.command()
@click.option('--input', default=None, help='path to the folder containing the .tex files')
@click.option('--output', default=None, help='path to the folder where the .docx files will be saved')
def convert_tex_to_docx(input, output):
"""Convert the .tex files in a folder to .docx.\n
Parameters\n
----------\n
input : str\n
path to the folder containing the .tex files.\n
"""
bot = LatexBot()
if not input:
input = os.getcwd()
if not output: # TODO: change!
output = None
out = bot.convert_tex_to_docx(input, output)
click.echo(out)
@latexbot.command()
@click.argument('project')
@click.option('--output', default=None, help='path to the folder where the .docx files will be saved, by default None')
@click.option('--inspect', default=True, help='open the file after the conversion')
@click.option('--upload', default=False, help='if True upload the docx to your Google Drive')
def convert_overleaf_to_docx(project, output, inspect, upload):
"""Convert an overleaf project to a .docx file.\n
Parameters\n
----------\n
project : str\n
name of the project for the setting file.\n
"""
bot = LatexBot()
out = bot.convert_overleaf_to_docx(project, output, inspect, upload)
click.echo(out)
# ------------------------------ DRIVEBOT ----------------------------------#
@click.group()
def drivebot():
"""bot to help with Google Drive"""
pass
@drivebot.command()
@click.option('--type', default='web', help='choose how you want to authenticate')
@click.option('--save', default=True, help='save the credentials as .json file')
def authenticate(type, save):
"""Sign in your Google Drive.\n
"""
bot = DriveBot(type, save)
bot
click.echo('done!')
@drivebot.command()
@click.argument('path_to_file')
@click.argument('name')
def upload_local_file(path_to_file, name):
"""Upload a local file to your Google Drive.\n
"""
bot = DriveBot('web')
bot.upload_local_file(path_to_file, name)
click.echo('done!')
# -------------------------------- DEBUG ----------------------------------#
if __name__ == "__main__":
sys.exit(main())
|
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10214,
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13,
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62,
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7,
17620,
11,
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8,
198,
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2,
34400,
32501,
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2538,
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2390,
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2,
628,
198,
31,
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13,
8094,
3419,
198,
4299,
5735,
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198,
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284,
9427,
351,
573,
30536,
37811,
198,
220,
220,
220,
1208,
628,
198,
31,
46813,
13645,
13,
21812,
3419,
198,
31,
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13,
49140,
10786,
20500,
3256,
4277,
11639,
34,
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29926,
2611,
0,
11537,
198,
4299,
3758,
7,
20500,
2599,
198,
220,
220,
220,
37227,
25206,
257,
3275,
1262,
30740,
13,
59,
77,
198,
220,
220,
220,
3275,
1058,
256,
742,
59,
77,
198,
220,
220,
220,
220,
220,
220,
220,
262,
3275,
345,
765,
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284,
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13,
333,
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6518,
11,
416,
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34,
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29926,
2611,
0,
63,
198,
220,
220,
220,
37227,
628,
220,
220,
220,
10214,
796,
14318,
20630,
3419,
198,
220,
220,
220,
10214,
13,
21280,
62,
20500,
7,
20500,
8,
628,
198,
31,
46813,
13645,
13,
21812,
3419,
198,
31,
12976,
13,
49140,
10786,
30001,
11537,
198,
4299,
900,
62,
30001,
7,
30001,
2599,
198,
220,
220,
220,
37227,
17953,
262,
11241,
2393,
351,
262,
18031,
13,
59,
77,
628,
220,
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220,
40117,
59,
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198,
220,
220,
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24200,
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59,
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198,
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220,
220,
11241,
1058,
965,
59,
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198,
220,
220,
220,
220,
220,
220,
220,
11241,
286,
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13,
59,
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37227,
198,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
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220,
8537,
312,
796,
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62,
660,
30536,
62,
17006,
312,
7,
30001,
8,
198,
220,
220,
220,
2845,
35528,
25,
198,
220,
220,
220,
220,
220,
220,
220,
5298,
26923,
12331,
7203,
22210,
1816,
2642,
0,
7731,
345,
923,
257,
8537,
351,
534,
10214,
319,
573,
30536,
1701,
8,
198,
220,
220,
220,
503,
796,
751,
62,
30001,
7203,
660,
30536,
1600,
10214,
62,
30001,
28,
30001,
11,
10214,
62,
17006,
2389,
28,
2536,
7,
17006,
312,
4008,
198,
220,
220,
220,
3904,
13,
30328,
7,
448,
8,
198,
198,
2,
20368,
412,
5673,
4146,
20368,
438,
2,
628,
198,
31,
12976,
13,
8094,
3419,
198,
4299,
3053,
13645,
33529,
198,
220,
220,
220,
37227,
13645,
284,
3758,
7237,
422,
262,
3141,
1627,
37811,
198,
220,
220,
220,
1208,
628,
198,
31,
12888,
13645,
13,
21812,
3419,
198,
31,
12976,
13,
49140,
10786,
260,
39729,
3256,
4277,
11639,
76,
321,
2611,
31,
12888,
13,
785,
11537,
198,
31,
12976,
13,
49140,
10786,
32796,
3256,
4277,
11639,
34,
13481,
11537,
198,
31,
12976,
13,
49140,
10786,
2618,
3256,
4277,
11639,
34,
13481,
29926,
2611,
0,
11537,
198,
2,
2488,
12976,
13,
18076,
10786,
438,
47348,
3256,
220,
2099,
11639,
6978,
3256,
1037,
11639,
6978,
284,
597,
2393,
345,
765,
284,
10199,
11537,
198,
4299,
3758,
7,
260,
39729,
11,
2426,
11,
1767,
2599,
198,
220,
220,
220,
37227,
25206,
281,
3053,
284,
281,
3053,
2209,
13,
59,
77,
628,
220,
220,
220,
220,
220,
220,
220,
40117,
59,
77,
198,
220,
220,
220,
220,
220,
220,
220,
24200,
438,
59,
77,
198,
220,
220,
220,
220,
220,
220,
220,
9733,
1058,
965,
59,
77,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3053,
2209,
286,
262,
9733,
59,
77,
198,
220,
220,
220,
220,
220,
220,
220,
2426,
1058,
965,
59,
77,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2426,
286,
262,
3053,
59,
77,
198,
220,
220,
220,
220,
220,
220,
220,
1767,
1058,
965,
59,
77,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1767,
2420,
286,
262,
3053,
59,
77,
198,
220,
220,
220,
220,
220,
220,
220,
18231,
1058,
965,
11,
11902,
59,
77,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3108,
284,
262,
2393,
284,
10199,
11,
416,
4277,
6045,
59,
198,
220,
220,
220,
37227,
628,
220,
220,
220,
1303,
29788,
796,
311,
2194,
13,
687,
62,
7753,
7,
1911,
83,
482,
641,
14,
12888,
4943,
198,
220,
220,
220,
9733,
796,
366,
8310,
1817,
1073,
13,
81,
2271,
12003,
31,
14816,
13,
785,
1,
198,
220,
220,
220,
2426,
796,
366,
20500,
422,
10214,
1,
198,
220,
220,
220,
1767,
796,
366,
1212,
3275,
373,
1908,
416,
257,
10214,
1,
198,
220,
220,
220,
1303,
10199,
796,
366,
22897,
13,
12315,
1,
628,
220,
220,
220,
10214,
796,
9570,
20630,
3419,
198,
220,
220,
220,
10214,
13,
21280,
62,
12888,
7,
260,
39729,
11,
2426,
11,
1767,
8,
628,
198,
31,
12888,
13645,
13,
21812,
3419,
198,
31,
12976,
13,
49140,
10786,
29460,
11537,
198,
31,
12976,
13,
49140,
10786,
28712,
11537,
198,
4299,
900,
62,
30001,
7,
29460,
11,
9206,
2599,
198,
220,
220,
220,
37227,
17953,
262,
11241,
2393,
351,
262,
18031,
13,
59,
77,
628,
220,
220,
220,
40117,
59,
77,
198,
220,
220,
220,
24200,
438,
59,
77,
198,
220,
220,
220,
11241,
1058,
965,
59,
77,
198,
220,
220,
220,
220,
220,
220,
220,
11241,
286,
262,
573,
30536,
10214,
13,
59,
77,
198,
220,
220,
220,
8537,
312,
1058,
965,
59,
77,
198,
220,
220,
220,
220,
220,
220,
220,
8537,
2389,
286,
262,
8537,
351,
262,
10214,
13,
59,
77,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
503,
796,
751,
62,
30001,
7203,
12888,
1600,
20579,
28,
29460,
11,
9206,
28,
28712,
8,
198,
220,
220,
220,
3904,
13,
30328,
7,
448,
8,
628,
198,
2,
20368,
12,
33825,
20368,
6329,
2,
198,
31,
12976,
13,
8094,
3419,
198,
4299,
26678,
13645,
33529,
198,
220,
220,
220,
37227,
13645,
284,
19863,
8076,
319,
257,
357,
23289,
8,
4382,
37811,
198,
220,
220,
220,
1208,
628,
198,
31,
45824,
13645,
13,
21812,
3419,
198,
31,
12976,
13,
49140,
10786,
4774,
3672,
11537,
198,
31,
12976,
13,
49140,
10786,
29460,
11537,
198,
31,
12976,
13,
18076,
10786,
438,
28712,
3256,
4277,
11639,
3256,
1037,
11639,
28712,
284,
1895,
262,
2583,
393,
284,
42797,
262,
2839,
1994,
11537,
198,
31,
12976,
13,
18076,
10786,
438,
79,
36540,
2539,
3256,
4277,
11639,
3256,
1037,
11639,
6978,
284,
262,
2839,
1994,
11537,
198,
4299,
900,
62,
30001,
7,
4774,
3672,
11,
20579,
11,
9206,
11,
279,
36540,
2539,
2599,
198,
220,
220,
220,
37227,
17953,
262,
11241,
2393,
351,
262,
18031,
13,
59,
77,
198,
220,
220,
220,
24550,
25,
284,
307,
4465,
2035,
262,
9206,
393,
262,
26678,
2839,
1994,
1276,
307,
3804,
13,
628,
220,
220,
220,
40117,
59,
77,
198,
220,
220,
220,
24200,
438,
59,
77,
198,
220,
220,
220,
2583,
3672,
1058,
965,
59,
77,
198,
220,
220,
220,
220,
220,
220,
220,
20966,
2209,
286,
262,
4382,
13,
59,
77,
198,
220,
220,
220,
20579,
1058,
965,
59,
77,
198,
220,
220,
220,
220,
220,
220,
220,
20579,
319,
262,
4382,
13,
59,
77,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
503,
796,
751,
62,
30001,
7,
26011,
28,
69,
1,
90,
29460,
92,
31,
90,
4774,
3672,
92,
1600,
2583,
3672,
28,
4774,
3672,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
20579,
28,
29460,
11,
9206,
28,
28712,
11,
279,
36540,
2539,
28,
79,
36540,
2539,
8,
198,
220,
220,
220,
3904,
13,
30328,
7,
448,
8,
628,
198,
31,
45824,
13645,
13,
21812,
3419,
198,
31,
12976,
13,
18076,
10786,
438,
45824,
62,
43551,
3256,
4277,
28,
14202,
11,
1037,
11639,
6978,
810,
262,
1994,
5166,
481,
307,
7448,
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8,
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3904,
13,
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0,
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2,
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438,
2,
198,
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834,
12417,
834,
1298,
198,
220,
220,
220,
25064,
13,
37023,
7,
12417,
28955,
198
] | 2.829941 | 4,716 |
# Copyright (C) 2013 Sony Mobile Communications AB.
# All rights, including trade secret rights, reserved.
from ave.broker.session import RemoteSession
|
[
2,
15069,
357,
34,
8,
2211,
10184,
12173,
14620,
9564,
13,
198,
2,
1439,
2489,
11,
1390,
3292,
3200,
2489,
11,
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13,
198,
198,
6738,
257,
303,
13,
7957,
6122,
13,
29891,
1330,
21520,
36044,
198
] | 4.135135 | 37 |
# Add zip code
import pymongo
myclient = pymongo.MongoClient("mongodb://localhost:27017/")
mydb = myclient["mydatabase"]
mycol = mydb["restaurant"]
myquery = {"borough":{"$regex":"Bronx"}}
for x in mycol.find(myquery):
print(x)
|
[
2,
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2438,
201,
198,
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279,
4948,
25162,
201,
198,
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201,
198,
220,
220,
220,
3601,
7,
87,
8,
201,
198
] | 2.44 | 100 |
#!/usr/bin/env python3 -B
import paho.mqtt.publish as mqtt # pip install --upgrade paho-mqtt
import json
from collections import namedtuple
import time
import random
import base64
import os
Loc = namedtuple('Loc', 'imei lat lon alt vel cog plate tid')
positions = [
Loc("516081298750081", 59.373399, 17.946690, 101, 15, 280, "25-33-XQ", "xq"),
Loc("507957223448860", 32.851537, -80.012624, 90, 119, 110, "72-93-FQ", "fq"),
Loc("523674523738680", 41.474304, 15.397448, 14, 0, 110, "JL-19-74", "JL"),
Loc("867260028922633", 40.878464, -5.562181, 341, 56, 135, "A 0815 BL", "Gn"),
Loc("012549656802107", 48.856826, 2.292713, 43, 72, 205, "20-ER-20", "JJ"),
]
params = {
"hostname" : "localhost",
"port" : 1883,
"qos" : 1,
"retain" : True,
"client_id" : "pub-simu",
}
for p in positions:
topic = "owntracks/zbx/%s" % (p.imei)
# adjust random time: five minutes ago plus a bit
tst = int(time.time()) - 300 + random.randint(0, 120)
tst = int(time.time())
vel = p.vel
# vel = 10
vel = random.randint(40,80)
print(p.imei, vel)
data = {
"_type" : "location",
"tst" : tst,
"lat" : p.lat,
"lon" : p.lon,
"cog" : p.cog,
"alt" : p.alt,
"vel" : vel,
"tid" : p.tid,
"batt" : random.randint(82, 100),
"name" : p.plate, # OSM popup on last/
}
payload = json.dumps(data)
mqtt.single(topic, payload,
auth=None,
tls=None,
**params)
topic = "owntracks/zbx/%s/card" % (p.imei)
card = {
"_type" : "card",
"name" : p.plate,
}
for ext in [ "png", "jpg" ]:
image_file = "faces/{0}.{1}".format(p.imei, ext)
if os.path.exists(image_file):
img = base64.b64encode(open(image_file, "rb").read()).decode("utf-8")
card["face"] = img
break
mqtt.single(topic, json.dumps(card),
auth=None,
tls=None,
**params)
|
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737,
12501,
1098,
7203,
40477,
12,
23,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2657,
14692,
2550,
8973,
796,
33705,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2270,
628,
220,
220,
220,
285,
80,
926,
13,
29762,
7,
26652,
11,
33918,
13,
67,
8142,
7,
9517,
828,
198,
220,
220,
220,
220,
220,
220,
220,
6284,
28,
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11,
198,
220,
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256,
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14202,
11,
198,
220,
220,
220,
220,
220,
220,
220,
12429,
37266,
8,
628,
628
] | 1.846753 | 1,155 |
from db.repositories.statistics_repository import StatisticsRepository
from db.repositories.dna_repository import DNARepository
from model import Dna
from model.DTO.Dna import DNACreate
from service import statistics_service
from fastapi import HTTPException
|
[
6738,
20613,
13,
260,
1930,
270,
1749,
13,
14269,
3969,
62,
260,
1930,
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1330,
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6207,
13264,
198,
6738,
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13,
260,
1930,
270,
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13,
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2616,
62,
260,
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198,
6738,
3049,
15042,
1330,
14626,
16922,
198
] | 3.547945 | 73 |
# Copyright 2013-2020 Lawrence Livermore National Security, LLC and other
# Spack Project Developers. See the top-level COPYRIGHT file for details.
#
# SPDX-License-Identifier: (Apache-2.0 OR MIT)
from spack import *
class Julea(MesonPackage):
"""JULEA is a flexible storage framework that allows offering arbitrary
I/O interfaces to applications. To be able to rapidly prototype new
approaches, it offers object, key-value and database backends. Support
for popular storage technologies such as POSIX, LevelDB and MongoDB is
already included."""
homepage = "https://github.com/wr-hamburg/julea"
git = "https://github.com/wr-hamburg/julea.git"
tags = ['HPC', 'I/O', 'storage']
maintainers = ['michaelkuhn']
version('master', branch='master')
variant('hdf5', default=True, description='Enable HDF5 support')
variant('leveldb', default=True, description='Enable LevelDB support')
variant('lmdb', default=True, description='Enable LMDB support')
variant('mariadb', default=True, description='Enable MariaDB support')
variant('mongodb', default=True, description='Enable MongoDB support')
variant('sqlite', default=True, description='Enable SQLite support')
depends_on('pkgconfig', type='build')
depends_on('glib')
depends_on('libbson')
# depends_on('libfabric')
depends_on('[email protected]:', when='+leveldb')
depends_on('leveldb', when='+leveldb')
depends_on('lmdb', when='+lmdb')
depends_on('mariadb-c-client', when='+mariadb')
depends_on('mongo-c-driver', when='+mongodb')
depends_on('sqlite', when='+sqlite')
|
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] | 2.878307 | 567 |
import base64
# converte os bytes em imagem e salva no path especificado
# remove o cabeçalho do base64 enviado na requisição pelo JS
|
[
11748,
2779,
2414,
628,
220,
220,
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2,
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660,
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9881,
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] | 2.525424 | 59 |
#
# -------------------------------------------------------------------------
# Copyright (c) 2015-2017 AT&T Intellectual Property
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
# -------------------------------------------------------------------------
#
"""REST Helper"""
import json
from os import path
from oslo_config import cfg
from oslo_log import log
import requests
from requests.auth import HTTPBasicAuth
from six.moves.urllib import parse
from conductor.i18n import _LE, _LW # pylint: disable=W0212
LOG = log.getLogger(__name__)
CONF = cfg.CONF
class RESTException(IOError):
"""Basic exception for errors raised by REST"""
class CertificateFileNotFoundException(RESTException, ValueError):
"""Certificate file was not found"""
class MissingURLNetlocException(RESTException, ValueError):
"""URL is missing a host/port"""
class ProhibitedURLSchemeException(RESTException, ValueError):
"""URL is using a prohibited scheme"""
class REST(object):
"""Helper class for REST operations."""
server_url = None
timeout = None
# Why the funny looking connect/read timeouts? Here, read this:
# http://docs.python-requests.org/en/master/user/advanced/#timeouts
def __init__(self, server_url, retries=3, connect_timeout=3.05,
read_timeout=12.05, username=None, password=None,
cert_file=None, cert_key_file=None, ca_bundle_file=None,
log_debug=False):
"""Initializer."""
parsed = parse.urlparse(server_url, 'http')
if parsed.scheme not in ('http', 'https'):
raise ProhibitedURLSchemeException
if not parsed.netloc:
raise MissingURLNetlocException
for file_path in (cert_file, cert_key_file, ca_bundle_file):
if file_path and not path.exists(file_path):
raise CertificateFileNotFoundException
self.server_url = server_url.rstrip('/')
self.retries = int(retries)
self.timeout = (float(connect_timeout), float(read_timeout))
self.log_debug = log_debug
self.username = username
self.password = password
self.cert = cert_file
self.key = cert_key_file
self.verify = ca_bundle_file
# FIXME(jdandrea): Require a CA bundle; do not suppress warnings.
# This is here due to an A&AI's cert/server name mismatch.
# Permitting this defeats the purpose of using SSL/TLS.
if self.verify == "":
requests.packages.urllib3.disable_warnings()
self.verify = False
# Use connection pooling, kthx.
# http://docs.python-requests.org/en/master/user/advanced/
self.session = requests.Session()
def request(self, method='get', content_type='application/json',
path='', headers=None, data=None):
"""Performs HTTP request. Returns a requests.Response object."""
if method not in ('post', 'get', 'put', 'delete'):
method = 'get'
method_fn = getattr(self.session, method)
full_headers = {
'Accept': content_type,
'Content-Type': content_type,
}
if headers:
full_headers.update(headers)
full_url = '{}/{}'.format(self.server_url, path.lstrip('/'))
# Prepare the request args
try:
data_str = json.dumps(data) if data else None
except (TypeError, ValueError):
data_str = data
kwargs = {
'data': data_str,
'headers': full_headers,
'timeout': self.timeout,
'cert': (self.cert, self.key),
'verify': self.verify,
'stream': False,
}
if self.username or self.password:
LOG.debug("Using HTTPBasicAuth")
kwargs['auth'] = HTTPBasicAuth(self.username, self.password)
if self.cert and self.key:
LOG.debug("Using SSL/TLS Certificate/Key")
if self.log_debug:
LOG.debug("Request: {} {}".format(method.upper(), full_url))
if data:
LOG.debug("Request Body: {}".format(json.dumps(data)))
response = None
for attempt in range(self.retries):
if attempt > 0:
# No need to show 400 bad requests from Music - Ignorable when lock cannot be received at one particular point in time
if "MUSIC" not in full_url:
LOG.warn(_LW("Retry #{}/{}").format(
attempt + 1, self.retries))
try:
response = method_fn(full_url, **kwargs)
# We shouldn't have to do this since stream is set to False,
# but we're gonna anyway. See "Body Content Workflow" here:
# http://docs.python-requests.org/en/master/user/advanced/
response.close()
if not response.ok:
# No need to show 400 bad requests from Music - Ignorable when lock cannot be received at one particular point in time
if "MUSIC" not in full_url:
LOG.warn("Response Status: {} {}".format(
response.status_code, response.reason))
if self.log_debug and response.text:
try:
response_dict = json.loads(response.text)
LOG.debug("Response JSON: {}".format(
json.dumps(response_dict)))
except ValueError:
LOG.debug("Response Body: {}".format(response.text))
if response.ok:
break
except requests.exceptions.RequestException as err:
LOG.error("Exception: %s", err.message)
# Response.__bool__ returns false if status is not ok. Ruh roh!
# That means we must check the object type vs treating it as a bool.
# More info: https://github.com/kennethreitz/requests/issues/2002
if isinstance(response, requests.models.Response) and not response.ok:
# No need to show 400 bad requests from Music - Ignorable when lock cannot be received at one particular point in time
if "MUSIC" not in full_url:
LOG.error(_LE("Status {} {} after {} retries for URL: {}").format(
response.status_code, response.reason, self.retries, full_url))
return response
|
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7,
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2882,
13,
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62,
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4008,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
2882,
198
] | 2.374659 | 2,936 |
# Copyright 2016 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Utility functions related to tasks"""
import subprocess
|
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2,
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879,
5499,
3519,
284,
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37811,
198,
198,
11748,
850,
14681,
628
] | 3.987805 | 164 |
#!/usr/bin/env python
from suds.client import Client
import base64
# Suds does not support base64binary type, so we do the encoding manually.
file_data = base64.b64encode('file_data')
c=Client('http://localhost:9000/filemgr/?wsdl')
c.service.add('x', 'y', 'file_name', file_data)
print('file written.')
print()
print('incoming data:')
return_data = c.service.get('file_name')
print(repr(return_data))
|
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2,
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1050,
7,
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62,
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4008,
198
] | 2.8 | 145 |
from skimage.measure import marching_cubes
import pandas as pd
import numpy as np
from LoopStructural.utils import getLogger
logger = getLogger(__name__)
|
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1341,
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8
] | 3.208333 | 48 |
"""
1 comprehension
2 user defined function
# ASSIGNMENT:
1 WRITE list comprehension to create 15 random number
2 write list comprehensioon to create prime number till user defined number
3 write dictionary comprehension with 5 key value paiir
4 convert all assignmnent into user defined function
"""
### COMPREHENSION:
# 1 LIST COMPREHENSION:
# _odd = list()
# for i in range (1,10,2):
# _odd.append(i)
# print(_odd)
#
#
_odd=[i for i in range(1,10,2) ]
print(_odd)
# for i in range (1,10):
# if i%2==1:
# _odd.append(i)
# print(_odd)
# _odd=[i for i in range(1,10) if i%2==1]
# print(_odd)
# 2 DICTIONARY COMPREHENSION:
# sq={}
#
# numbers=[2,4,6,8,8,10,3,5]
# for num in numbers :
# sq[num]=num*num
# print(sq)
#
# _sq={ num:num*num for num in numbers}
# print(_sq)
#
# _sq={ num:num*num for num in numbers if num%2==1}
# print(_sq)
labels = ["name", "age", "contact no"]
user1 = ["pallavi", 24, 9975881339]
user2 = ["sonali", 20, 9881942199]
user3 = ["poonam", 15, 874596312]
# output as :[{"name: "pallavi,"age":24,"contact no" :9975881339},
# { "name":"sonali","age":20, "contact no": 9881942199},
# {"name":"poonam","age": 20,"contact no":874596312}
# ]
# labels1 = [{"name": user1[0] for i in user1}, {"age": user1[1] for i in user1}, {"contact no": user1[2] for i in user1}]
# print(labels1)
#
# label2=[ {"name":[0] for i in user1 }]
# output=[{label:user[index]for index,label in enumerate(labels)}
# for user in [user1,user2,user3]]
# print(output)
# output=[{labels[index]:user[index] for index in range (0,3)}
# for user in [user1,user2,user3]]
# print(output)
# op=list()
# for user in [user1,user2,user3]:
# _user=dict()
# for index in range(0,3):
# _user[labels[index]]=user[index]
# op.append(_user)
#
# print(op)
###2 USER DEFINED FUNCTION:
'''
## simple function
def<function name>():
"""
function doc string
"""
<statement1>
<statement2>
.
.
.
<statementn>
'''
# greeting()
def arg_greeting(name):
"""
this is greeting function with argument
:param name:
:return:
"""
print("hello {}".format(name))
print(F"hello {name}")
# arg_greeting(name="parth")
def arg_return_greeeting(name):
"""
this is greeting function with argument and return greeting message
:param name:
:return:
"""
message=F"hello {name}"
return message
# resp = arg_return_greeeting(name="pallavi")
# print(resp)
# name=input("enter your name : ")
# resp = arg_return_greeeting(name="pallavi")
# print(resp)
wild_card_arg_greetings(*["test1","test2"])
def wild_card_kwargs_function(**kwargs):
"""
:param kwargs:dictinary wild card argument
:return:
"""
for key, values in kwargs.items():
print(key, ":", values)
user1={"name":"pallavi","age":24,"contact no":9975881339}
wild_card_kwargs_function(**user1)
|
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15,
11,
18,
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2,
220,
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220,
220,
220,
220,
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329,
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685,
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16,
11,
7220,
17,
11,
7220,
18,
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198,
2,
3601,
7,
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8,
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2,
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28,
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2,
329,
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11,
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11,
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2,
220,
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220,
329,
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1,
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220,
220,
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2,
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62,
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62,
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631,
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7,
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2625,
79,
439,
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4943,
198,
2,
3601,
7,
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8,
198,
198,
2,
1438,
28,
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7203,
9255,
534,
1438,
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8,
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2,
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62,
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62,
70,
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7,
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8,
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62,
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62,
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62,
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8,
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62,
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86,
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13,
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220,
220,
220,
220,
220,
220,
220,
3601,
7,
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11,
366,
25,
1600,
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8,
198,
198,
7220,
16,
28,
4895,
3672,
2404,
79,
439,
15820,
2430,
496,
1298,
1731,
553,
32057,
645,
1298,
2079,
2425,
3459,
1485,
2670,
92,
198,
21992,
62,
9517,
62,
46265,
22046,
62,
8818,
7,
1174,
7220,
16,
8
] | 2.394586 | 1,219 |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import unittest
from punica.cli import main
from click.testing import CliRunner
if __name__ == '__main__':
unittest.main()
|
[
2,
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14629,
14,
8800,
14,
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18,
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2,
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12,
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834,
10354,
198,
220,
220,
220,
555,
715,
395,
13,
12417,
3419,
198
] | 2.5 | 72 |
import requests
import json
from github import GithubException
|
[
11748,
7007,
198,
11748,
33918,
198,
6738,
33084,
1330,
38994,
16922,
628
] | 5.333333 | 12 |
model = dm.DSCN(task=6723)
model.compile("adam", "sparse_categorical_crossentropy", metrics=['accuracy'])
print('start training...')
history = model.fit(train_model_input, data[target].values, batch_size=256, epochs=20, verbose=2, validation_data=(test_model_input, test_data[target].values))
model.save('./dscn.h5')
|
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21928,
7,
4458,
14,
67,
1416,
77,
13,
71,
20,
11537,
198
] | 2.717949 | 117 |
import pyodbc
server = 'localhost'
database = 'testDB'
username = 'SA'
password = 'giorgio$1'
cnxn = pyodbc.connect('DRIVER={ODBC Driver 17 for SQL Server};SERVER='+server+';DATABASE='+database+';UID='+username+';PWD='+ password)
cursor = cnxn.cursor()
print('Inserting a new row into table')
tsql = "INSERT INTO Employees (Name, Location) VALUES (?,?);"
with cursor.execute(tsql,'Jake','United States'):
print('Successfully Inserted!')
|
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276,
0,
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198
] | 2.828025 | 157 |
#! encoding: UTF-8
import os
import opts
import ipdb
import time
import random
import numpy as np
from six.moves import cPickle
import keras
from keras.datasets import mnist
import tensorflow as tf
if __name__ == '__main__':
opt = opts.parse_opt()
opt_dict = vars(opt)
for k, v in opt_dict.items():
print(k + ': \t' + str(v))
with open('permuted_mnist_110.pkl', 'rb') as f:
permuted_mnist = cPickle.load(f)
if os.path.isdir(opt.rcst_model_save_path) is False:
os.mkdir(opt.rcst_model_save_path)
x_train_permuted = permuted_mnist['x_train_permuted']
y_train = permuted_mnist['y_train']
x_test_permuted = permuted_mnist['x_test_permuted']
y_test = permuted_mnist['y_test']
# training
train(opt, x_train_permuted, y_train, x_test_permuted, y_test)
|
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11,
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62,
9288,
62,
16321,
7241,
11,
331,
62,
9288,
8,
628
] | 2.304469 | 358 |
# -*- coding:utf-8 -*-
#
# File : cmd_package.py
# This file is part of RT-Thread RTOS
# COPYRIGHT (C) 2006 - 2018, RT-Thread Development Team
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License along
# with this program; if not, write to the Free Software Foundation, Inc.,
# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
#
# Change Logs:
# Date Author Notes
# 2018-05-28 SummerGift Add copyright information
# 2018-12-28 Ernest Chen Add package information and enjoy package maker
# 2019-01-07 SummerGift The prompt supports utf-8 encoding
#
import os
import json
import kconfig
import pkgsdb
import shutil
import platform
import subprocess
import time
import logging
import archive
import sys
try:
import requests
except ImportError:
print("****************************************\n"
"* Import requests module error.\n"
"* Please install requests module first.\n"
"* pip install step:\n"
"* $ pip install requests\n"
"* command install step:\n"
"* $ sudo apt-get install python-requests\n"
"****************************************\n")
from package import Package, Bridge_SConscript, Kconfig_file, Package_json_file, Sconscript_file
from vars import Import, Export
from string import Template
from cmd_menuconfig import find_macro_in_config
"""package command"""
def execute_command(cmdstring, cwd=None, shell=True):
"""Execute the system command at the specified address."""
if shell:
cmdstring_list = cmdstring
sub = subprocess.Popen(cmdstring_list, cwd=cwd, stdin=subprocess.PIPE,
stdout=subprocess.PIPE, shell=shell, bufsize=4096)
stdout_str = ''
while sub.poll() is None:
stdout_str += sub.stdout.read()
time.sleep(0.1)
return stdout_str
def user_input(msg, default_value):
"""Gets the user's keyboard input."""
if default_value != '':
msg = '%s[%s]' % (msg, default_value)
print(msg)
value = raw_input()
if value == '':
value = default_value
return value
def get_mirror_giturl(submod_name):
"""Gets the submodule's url on mirror server.
Retrurn the download address of the submodule on the mirror server from the submod_name.
"""
mirror_url = 'https://gitee.com/RT-Thread-Mirror/submod_' + submod_name + '.git'
return mirror_url
def modify_submod_file_to_mirror(submod_path):
"""Modify the.gitmodules file based on the submodule to be updated"""
replace_list = []
try:
with open(submod_path, 'r') as f:
for line in f:
line = line.replace('\t', '').replace(' ', '').replace('\n', '').replace('\r', '')
if line.startswith('url'):
submod_git_url = line.split('=')[1]
submodule_name = submod_git_url.split('/')[-1].replace('.git', '')
replace_url = get_mirror_giturl(submodule_name)
# print(replace_url)
query_submodule_name = 'submod_' + submodule_name
# print(query_submodule_name)
get_package_url, get_ver_sha = get_url_from_mirror_server(
query_submodule_name, 'latest')
if get_package_url != None and determine_url_valid(get_package_url):
replace_list.append(
(submod_git_url, replace_url, submodule_name))
with open(submod_path, 'r+') as f:
submod_file_count = f.read()
write_content = submod_file_count
for item in replace_list:
write_content = write_content.replace(item[0], item[1])
with open(submod_path, 'w') as f:
f.write(str(write_content))
return replace_list
except Exception, e:
print('e.message:%s\t' % e.message)
def get_url_from_mirror_server(pkgs_name_in_json, pkgs_ver):
"""Get the download address from the mirror server based on the package name."""
payload_pkgs_name_in_json = pkgs_name_in_json.encode("utf-8")
payload = {
"userName": "RT-Thread",
"packages": [
{
"name": "NULL",
}
]
}
payload["packages"][0]['name'] = payload_pkgs_name_in_json
try:
r = requests.post(
"http://packages.rt-thread.org/packages/queries", data=json.dumps(payload))
# print(r.status_code)
if r.status_code == requests.codes.ok:
package_info = json.loads(r.text)
# print(package_info)
# Can't find package,change git package SHA if it's a git
# package
if len(package_info['packages']) == 0:
print("Package was NOT found on mirror server. Using a non-mirrored address to download.")
return None, None
else:
for item in package_info['packages'][0]['packages_info']['site']:
if item['version'] == pkgs_ver:
# Change download url
download_url = item['URL']
if download_url[-4:] == '.git':
# Change git package SHA
repo_sha = item['VER_SHA']
return download_url, repo_sha
return download_url, None
print("\nTips : \nThe system needs to be upgraded.")
print("Please use the <pkgs --upgrade> command to upgrade packages index.\n")
return None, None
except Exception, e:
# print('e.message:%s\t' % e.message)
print("\nThe mirror server could not be contacted. Please check your network connection.")
return None, None
def install_pkg(env_root, pkgs_root, bsp_root, pkg):
"""Install the required packages."""
# default true
ret = True
local_pkgs_path = os.path.join(env_root, 'local_pkgs')
bsp_pkgs_path = os.path.join(bsp_root, 'packages')
# get the .config file from env
env_kconfig_path = os.path.join(env_root, 'tools\scripts\cmds')
env_config_file = os.path.join(env_kconfig_path, '.config')
package = Package()
pkg_path = pkg['path']
if pkg_path[0] == '/' or pkg_path[0] == '\\':
pkg_path = pkg_path[1:]
pkg_path = os.path.join(pkgs_root, pkg_path, 'package.json')
package.parse(pkg_path)
url_from_json = package.get_url(pkg['ver'])
package_url = package.get_url(pkg['ver'])
pkgs_name_in_json = package.get_name()
if package_url[-4:] == '.git':
ver_sha = package.get_versha(pkg['ver'])
# print("==================================================>")
# print("packages name :"%pkgs_name_in_json.encode("utf-8"))
# print("ver :"%pkg['ver'])
# print("url :"%package_url.encode("utf-8"))
# print("url_from_json : "%url_from_json.encode("utf-8"))
# print("==================================================>")
get_package_url = None
get_ver_sha = None
upstream_change_flag = False
try:
if (not os.path.isfile(env_config_file)) or (os.path.isfile(env_config_file) and find_macro_in_config(env_config_file, 'SYS_PKGS_DOWNLOAD_ACCELERATE')):
get_package_url, get_ver_sha = get_url_from_mirror_server(pkgs_name_in_json, pkg['ver'])
# determine whether the package package url is valid
if get_package_url != None and determine_url_valid(get_package_url):
package_url = get_package_url
if get_ver_sha != None:
ver_sha = get_ver_sha
upstream_change_flag = True
except Exception, e:
# print('e.message:%s\t' % e.message)
print("Failed to connect to the mirror server, package will be downloaded from non-mirror server.\n")
if package_url[-4:] == '.git':
try:
repo_path = os.path.join(bsp_pkgs_path, pkgs_name_in_json)
repo_path = repo_path + '-' + pkg['ver']
repo_path_full = '"' + repo_path + '"'
cmd = 'git clone ' + package_url + ' ' + repo_path_full
execute_command(cmd, cwd=bsp_pkgs_path)
cmd = 'git checkout -q ' + ver_sha
execute_command(cmd, cwd=repo_path)
except Exception, e:
print("\nFailed to download software package with git. Please check the network connection.")
return False
if upstream_change_flag:
cmd = 'git remote set-url origin ' + url_from_json
execute_command(cmd, cwd=repo_path)
# If there is a .gitmodules file in the package, prepare to update submodule.
submod_path = os.path.join(repo_path, '.gitmodules')
if os.path.isfile(submod_path):
print("Start to update submodule")
# print("开始更新软件包子模块")
if (not os.path.isfile(env_config_file)) or (os.path.isfile(env_config_file) and find_macro_in_config(env_config_file, 'SYS_PKGS_DOWNLOAD_ACCELERATE')):
# print("开启了镜像加速，开始修改 .gitmodules 文件")
replace_list = modify_submod_file_to_mirror(submod_path) # Modify .gitmodules file
# print("开始执行更新动作")
cmd = 'git submodule update --init --recursive'
execute_command(cmd, cwd=repo_path)
if (not os.path.isfile(env_config_file)) or (os.path.isfile(env_config_file) and find_macro_in_config(env_config_file, 'SYS_PKGS_DOWNLOAD_ACCELERATE')):
if len(replace_list):
for item in replace_list:
submod_dir_path = os.path.join(repo_path, item[2])
if os.path.isdir(submod_dir_path):
cmd = 'git remote set-url origin ' + item[0]
execute_command(cmd, cwd=submod_dir_path)
if (not os.path.isfile(env_config_file)) or (os.path.isfile(env_config_file) and find_macro_in_config(env_config_file, 'SYS_PKGS_DOWNLOAD_ACCELERATE')):
if os.path.isfile(submod_path):
cmd = 'git checkout .gitmodules'
execute_command(cmd, cwd=repo_path)
else:
# Download a package of compressed package type.
if not package.download(pkg['ver'], local_pkgs_path.decode("gbk"), package_url):
return False
pkg_dir = package.get_filename(pkg['ver'])
pkg_dir = os.path.splitext(pkg_dir)[0]
pkg_fullpath = os.path.join(local_pkgs_path, package.get_filename(pkg['ver']))
if not archive.packtest(pkg_fullpath.encode("gbk")):
print("package : %s is invalid"%pkg_fullpath.encode("utf-8"))
return False
# unpack package
if not os.path.exists(pkg_dir.encode("gbk")):
try:
if not package.unpack(pkg_fullpath.encode("gbk"), bsp_pkgs_path, pkg, pkgs_name_in_json.encode("gbk")):
ret = False
except Exception, e:
os.remove(pkg_fullpath)
ret = False
print('e.message: %s\t' % e.message)
else:
print("The file does not exist.")
return ret
def package_list():
"""Print the packages list in env.
Read the.config file in the BSP directory,
and list the version number of the selected package.
"""
fn = '.config'
env_root = Import('env_root')
pkgs_root = Import('pkgs_root')
if not os.path.isfile(fn):
if platform.system() == "Windows":
os.system('chcp 65001 > nul')
print ("\n\033[1;31;40m当前路径下没有发现 .config 文件，请确保当前目录为 BSP 根目录。\033[0m")
print ("\033[1;31;40m如果确定当前目录为 BSP 根目录，请先使用 <menuconfig> 命令来生成 .config 文件。\033[0m\n")
print ('\033[1;31;40mNo system configuration file : .config.\033[0m')
print ('\033[1;31;40mYou should use < menuconfig > command to config bsp first.\033[0m')
if platform.system() == "Windows":
os.system('chcp 437 > nul')
return
pkgs = kconfig.parse(fn)
for pkg in pkgs:
package = Package()
pkg_path = pkg['path']
if pkg_path[0] == '/' or pkg_path[0] == '\\':
pkg_path = pkg_path[1:]
pkg_path = os.path.join(pkgs_root, pkg_path, 'package.json')
package.parse(pkg_path)
pkgs_name_in_json = package.get_name()
print ("package name : %s, ver : %s "%(pkgs_name_in_json.encode("utf-8"), pkg['ver'].encode("utf-8")))
if not pkgs:
print ("Packages list is empty.")
print ('You can use < menuconfig > command to select online packages.')
print ('Then use < pkgs --update > command to install them.')
return
def sub_list(aList, bList):
"""Return the items in aList but not in bList."""
tmp = []
for a in aList:
if a not in bList:
tmp.append(a)
return tmp
def and_list(aList, bList):
"""Return the items in aList and in bList."""
tmp = []
for a in aList:
if a in bList:
tmp.append(a)
return tmp
def update_submodule(repo_path):
"""Update the submodules in the repository."""
submod_path = os.path.join(repo_path, '.gitmodules')
if os.path.isfile(submod_path):
print("Please wait a few seconds in order to update the submodule.")
cmd = 'git submodule init -q'
execute_command(cmd, cwd=repo_path)
cmd = 'git submodule update'
execute_command(cmd, cwd=repo_path)
print("Submodule update successful")
def update_latest_packages(pkgs_fn, bsp_packages_path):
""" update the packages that are latest version.
If the selected package is the latest version,
check to see if it is the latest version after the update command,
if not, then update the latest version from the remote repository.
If the download has a conflict, you are currently using the prompt
message provided by git.
"""
env_root = Import('env_root')
pkgs_root = Import('pkgs_root')
env_kconfig_path = os.path.join(env_root, 'tools\scripts\cmds')
env_config_file = os.path.join(env_kconfig_path, '.config')
with open(pkgs_fn, 'r') as f:
read_back_pkgs_json = json.load(f)
for pkg in read_back_pkgs_json:
package = Package()
pkg_path = pkg['path']
if pkg_path[0] == '/' or pkg_path[0] == '\\':
pkg_path = pkg_path[1:]
pkg_path = os.path.join(pkgs_root, pkg_path, 'package.json')
package.parse(pkg_path)
pkgs_name_in_json = package.get_name()
# Find out the packages which version is 'latest'
if pkg['ver'] == "latest_version" or pkg['ver'] == "latest":
repo_path = os.path.join(bsp_packages_path, pkgs_name_in_json)
repo_path = get_pkg_folder_by_orign_path(repo_path, pkg['ver'])
try:
# If mirror acceleration is enabled, get the update address from
# the mirror server.
if (not os.path.isfile(env_config_file)) or (os.path.isfile(env_config_file) and find_macro_in_config(env_config_file, 'SYS_PKGS_DOWNLOAD_ACCELERATE')):
payload_pkgs_name_in_json = pkgs_name_in_json.encode("utf-8")
# Change repo's upstream address.
mirror_url = get_url_from_mirror_server(
payload_pkgs_name_in_json, pkg['ver'])
if mirror_url[0] != None:
cmd = 'git remote set-url origin ' + mirror_url[0]
git_cmd_exec(cmd, repo_path)
except Exception, e:
print("Failed to connect to the mirror server, using non-mirror server to update.")
# Update the package repository from upstream.
cmd = 'git pull'
git_cmd_exec(cmd, repo_path)
# If the package has submodules, update the submodules.
update_submodule(repo_path)
# recover origin url to the path which get from packages.json file
if package.get_url(pkg['ver']):
cmd = 'git remote set-url origin ' + \
package.get_url(pkg['ver'])
git_cmd_exec(cmd, repo_path)
else:
print("Can't find the package : %s's url in file : %s" %
(payload_pkgs_name_in_json.encode("utf-8"), pkg_path.encode("utf-8")))
print("==============================> %s update done \n" %
(pkgs_name_in_json.encode("utf-8")))
def pre_package_update():
""" Make preparations before updating the software package. """
bsp_root = Import('bsp_root')
env_root = Import('env_root')
if not os.path.exists('.config'):
if platform.system() == "Windows":
os.system('chcp 65001 > nul')
print ("\n\033[1;31;40m当前路径下没有发现 .config 文件，请确保当前目录为 BSP 根目录。\033[0m")
print ("\033[1;31;40m如果确定当前目录为 BSP 根目录，请先使用 <menuconfig> 命令来生成 .config 文件。\033[0m\n")
print ('No system configuration file : .config.')
print ('You should use < menuconfig > command to config bsp first.')
if platform.system() == "Windows":
os.system('chcp 437 > nul')
return False
bsp_packages_path = os.path.join(bsp_root, 'packages')
if not os.path.exists(bsp_packages_path):
os.mkdir("packages")
os.chdir(bsp_packages_path)
fp = open("pkgs.json", 'w')
fp.write("[]")
fp.close()
fp = open("pkgs_error.json", 'w')
fp.write("[]")
fp.close()
os.chdir(bsp_root)
# prepare target packages file
dbsqlite_pathname = os.path.join(bsp_packages_path, 'packages.dbsqlite')
Export('dbsqlite_pathname')
dbsqlite_pathname = dbsqlite_pathname.decode('gbk')
# Avoid creating tables more than one time
if not os.path.isfile(dbsqlite_pathname):
conn = pkgsdb.get_conn(dbsqlite_pathname)
sql = '''CREATE TABLE packagefile
(pathname TEXT ,package TEXT ,md5 TEXT );'''
pkgsdb.create_table(conn, sql)
fn = '.config'
pkgs = kconfig.parse(fn)
newpkgs = pkgs
if not os.path.exists(bsp_packages_path):
os.mkdir(bsp_packages_path)
pkgs_fn = os.path.join(bsp_packages_path, 'pkgs.json')
# regenerate file : packages/pkgs.json
if not os.path.exists(pkgs_fn):
os.chdir(bsp_packages_path)
fp = open("pkgs.json", 'w')
fp.write("[]")
fp.close()
os.chdir(bsp_root)
# Reading data back from pkgs.json
with open(pkgs_fn, 'r') as f:
oldpkgs = json.load(f)
# regenerate file : packages/pkgs_error.json
pkgs_error_list_fn = os.path.join(
bsp_packages_path, 'pkgs_error.json')
if not os.path.exists(pkgs_error_list_fn):
os.chdir(bsp_packages_path)
fp = open("pkgs_error.json", 'w')
fp.write("[]")
fp.close()
os.chdir(bsp_root)
# Reading data back from pkgs_error.json
with open(pkgs_error_list_fn, 'r') as f:
pkgs_error = json.load(f)
# create SConscript file
if not os.path.isfile(os.path.join(bsp_packages_path, 'SConscript')):
bridge_script = file(os.path.join(
bsp_packages_path, 'SConscript'), 'w')
bridge_script.write(Bridge_SConscript)
bridge_script.close()
return [oldpkgs, newpkgs, pkgs_error, pkgs_fn, pkgs_error_list_fn, bsp_packages_path, dbsqlite_pathname]
def handle_download_error_packages(pkgs_fn, bsp_packages_path):
""" handle download error packages.
Check to see if the packages stored in the Json file list actually exist,
and then download the packages if they don't exist.
"""
with open(pkgs_fn, 'r') as f:
read_back_pkgs_json = json.load(f)
error_packages_list = []
for pkg in read_back_pkgs_json:
removepath = get_package_remove_path(pkg, bsp_packages_path)
if os.path.exists(removepath):
continue
else:
error_packages_list.append(pkg)
# Handle the failed download packages
get_flag = error_packages_handle(
error_packages_list, read_back_pkgs_json, pkgs_fn)
return get_flag
def write_storage_file(pkgs_fn, newpkgs):
"""Writes the updated configuration to pkgs.json file.
Packages that are not downloaded correctly will be redownloaded at the
next update.
"""
pkgs_file = file(pkgs_fn, 'w')
pkgs_file.write(json.dumps(newpkgs, indent=1))
pkgs_file.close()
def package_update(isDeleteOld=False):
"""Update env's packages.
Compare the old and new software package list and update the package.
Remove unwanted packages and download the newly selected package.-
Check if the files in the deleted packages have been changed, and if so,
remind the user saved the modified file.
"""
sys_value = pre_package_update()
if not sys_value:
return
bsp_root = Import('bsp_root')
env_root = Import('env_root')
pkgs_root = Import('pkgs_root')
flag = True
# According to the env version, whether Chinese output is supported or not
if determine_support_chinese(env_root):
if platform.system() == "Windows":
os.system('chcp 65001 > nul')
oldpkgs = sys_value[0]
newpkgs = sys_value[1]
pkgs_delete_error_list = sys_value[2]
pkgs_fn = sys_value[3]
pkgs_error_list_fn = sys_value[4]
bsp_packages_path = sys_value[5]
dbsqlite_pathname = sys_value[6]
if len(pkgs_delete_error_list):
for error_package in pkgs_delete_error_list:
removepath_ver = get_package_remove_path(
error_package, bsp_packages_path)
if os.path.isdir(removepath_ver):
print("\nError: %s package delete failed, begin to remove it."%
error_package['name'].encode("utf-8"))
if rm_package(removepath_ver) == False:
print("Error: Delete package %s failed! Please delete the folder manually.\n"%error_package['name'].encode("utf-8"))
return
# 1.in old ,not in new : Software packages that need to be removed.
casedelete = sub_list(oldpkgs, newpkgs)
pkgs_delete_fail_list = []
for pkg in casedelete:
removepath_ver = get_package_remove_path(pkg, bsp_packages_path)
removepath_git = os.path.join(removepath_ver, '.git')
# Delete. Git directory.
if os.path.isdir(removepath_ver) and os.path.isdir(removepath_git):
gitdir = removepath_ver
print ("\nStart to remove %s \nplease wait..." % gitdir.encode("utf-8"))
if isDeleteOld:
if rm_package(gitdir) == False:
print("Floder delete fail: %s" % gitdir.encode("utf-8"))
print("Please delete this folder manually.")
else:
print (
"The folder is managed by git. Do you want to delete this folder?\n")
rc = raw_input(
'Press the Y Key to delete the folder or just press Enter to keep it : ')
if rc == 'y' or rc == 'Y':
try:
if rm_package(gitdir) == False:
pkgs_delete_fail_list.append(pkg)
print("Error: Please delete the folder manually.")
except Exception, e:
print('Error message:%s%s. error.message: %s\n\t' %
("Delete folder failed: ", gitdir.encode("utf-8"), e.message))
else:
if os.path.isdir(removepath_ver):
print("Start to remove %s \nplease wait..." % removepath_ver.encode("utf-8"))
try:
pkgsdb.deletepackdir(removepath_ver, dbsqlite_pathname)
except Exception, e:
pkgs_delete_fail_list.append(pkg)
print('Error message:\n%s %s. %s \n\t' % (
"Delete folder failed, please delete the folder manually", removepath_ver.encode("utf-8"), e.message))
if len(pkgs_delete_fail_list):
# write error messages
pkgs_file = file(pkgs_error_list_fn, 'w')
pkgs_file.write(json.dumps(pkgs_delete_fail_list, indent=1))
pkgs_file.close()
return
else:
# write error messages
pkgs_file = file(pkgs_error_list_fn, 'w')
pkgs_file.write(json.dumps(pkgs_delete_fail_list, indent=1))
pkgs_file.close()
# 2.in new not in old : Software packages to be installed.
# If the package download fails, record it, and then download again when
# the update command is executed.
casedownload = sub_list(newpkgs, oldpkgs)
# print 'in new not in old:', casedownload
pkgs_download_fail_list = []
for pkg in casedownload:
if install_pkg(env_root, pkgs_root, bsp_root, pkg):
print("==============================> %s %s is downloaded successfully. \n" % (
pkg['name'], pkg['ver']))
else:
# If the PKG download fails, record it in the
# pkgs_download_fail_list.
pkgs_download_fail_list.append(pkg)
print pkg, 'download failed.'
flag = False
# Get the currently updated configuration.
newpkgs = sub_list(newpkgs, pkgs_download_fail_list)
# Give hints based on the success of the download.
if len(pkgs_download_fail_list):
print("\nPackage download failed list:" )
for item in pkgs_download_fail_list:
print(item)
print("You need to reuse the <pkgs -update> command to download again.")
# update pkgs.json and SConscript
write_storage_file(pkgs_fn, newpkgs)
# handle download error packages.
get_flag = handle_download_error_packages(
pkgs_fn, bsp_packages_path)
if get_flag != None:
flag = get_flag
# Update the software packages, which the version is 'latest'
try:
update_latest_packages(pkgs_fn, bsp_packages_path)
except KeyboardInterrupt:
flag = False
if flag:
print ("Operation completed successfully.")
else:
print ("Operation failed.")
def package_wizard():
"""Packages creation wizard.
The user enters the package name, version number, category, and automatically generates the package index file.
"""
# Welcome
print ('\033[4;32;40mWelcome to using package wizard, please follow below steps.\033[0m\n')
#Simple introduction about the wizard
print ('note :')
print (' \033[5;35;40m[ ]\033[0m means default setting or optional information.')
print (' \033[5;35;40mEnter\033[0m means using default option or ending and proceeding to the next step.')
#first step
print ('\033[5;33;40m\n1.Please input a new package name :\033[0m')
name = raw_input()
while name == '' or name.isspace() == True :
print ('\033[1;31;40mError: you must input a package name. Try again.\033[0m')
name = raw_input()
default_description = 'Please add description of ' + name + ' in English.'
#description = user_input('menuconfig option name,default:\n',default_description)
description = default_description
description_zh = "请添加软件包 " + name +" 的中文描述。"
#second step
ver = user_input('\033[5;33;40m\n2.Please input this package version, default :\033[0m', '1.0.0')
ver_standard = ver.replace('.', '')
#keyword = user_input('keyword,default:\n', name)
keyword = name
#third step
packageclass = ('iot', 'language', 'misc', 'multimedia',
'peripherals', 'security', 'system', 'tools', 'peripherals/sensors')
print ('\033[5;33;40m\n3.Please choose a package category from 1 to 9 : \033[0m')
print ("\033[1;32;40m[1:iot]|[2:language]|[3:misc]|[4:multimedia]|[5:peripherals]|[6:security]|[7:system]|[8:tools]|[9:sensors]\033[0m")
classnu = raw_input()
while classnu == '' or classnu.isdigit()== False or int(classnu) < 1 or int(classnu) >9:
if classnu == '' :
print ('\033[1;31;40mError: You must choose a package category. Try again.\033[0m')
else :
print ('\033[1;31;40mError: You must input an integer number from 1 to 9. Try again.\033[0m')
classnu = raw_input()
pkgsclass = packageclass[int(classnu) - 1]
#fourth step
print ('\033[5;33;40m\n4.Please input author name of this package :\033[0m')
authorname = raw_input()
while authorname == '':
print ('\033[1;31;40mError: you must input author name of this package. Try again.\033[0m')
authorname = raw_input()
#fifth step
authoremail = raw_input('\033[5;33;40m\n5.Please input author email of this package :\n\033[0m')
while authoremail == '':
print ('\033[1;31;40mError: you must input author email of this package. Try again.\033[0m')
authoremail = raw_input()
#sixth step
print ('\033[5;33;40m\n6.Please choose a license of this package from 1 to 4, or input other license name :\033[0m')
print ("\033[1;32;40m[1:Apache-2.0]|[2:MIT]|[3:LGPL-2.1]|[4:GPL-2.0]\033[0m")
license_index = ('Apache-2.0', 'MIT', 'LGPL-2.1', 'GPL-2.0')
license_class = raw_input()
while license_class == '' :
print ('\033[1;31;40mError: you must choose or input a license of this package. Try again.\033[0m')
license_class = raw_input()
if license_class.isdigit()== True and int(license_class) >= 1 and int(license_class) <= 4:
license = license_index[int(license_class) - 1]
else :
license = license_class
#seventh step
print ('\033[5;33;40m\n7.Please input the repository of this package :\033[0m')
print ("\033[1;32;40mFor example, hello package's repository url is 'https://github.com/RT-Thread-packages/hello'.\033[0m")
repository = raw_input()
while repository == '':
print ('\033[1;31;40mError: you must input a repository of this package. Try again.\033[0m')
repository = raw_input()
pkg_path = name
if not os.path.exists(pkg_path):
os.mkdir(pkg_path)
else:
print ("\033[1;31;40mError: the package directory is exits!\033[0m")
s = Template(Kconfig_file)
uppername = str.upper(name)
kconfig = s.substitute(name=uppername, description=description, version=ver,
pkgs_class=pkgsclass, lowercase_name=name, version_standard=ver_standard)
f = file(os.path.join(pkg_path, 'Kconfig'), 'wb')
f.write(kconfig)
f.close()
s = Template(Package_json_file)
package = s.substitute(name=name, pkgsclass=pkgsclass,authorname=authorname,authoremail=authoremail, description=description, description_zh=description_zh,version=ver, keyword=keyword,license=license, repository=repository)
f = file(os.path.join(pkg_path, 'package.json'), 'wb')
f.write(package)
f.close()
print ('\nThe package index has been created \033[1;32;40msuccessfully\033[0m.')
print ('Please \033[5;34;40mupdate\033[0m other information of this package based on Kconfig and package.json in directory '+name+'.')
def upgrade_packages_index():
"""Update the package repository index."""
env_root = Import('env_root')
pkgs_root = Import('pkgs_root')
env_kconfig_path = os.path.join(env_root, 'tools\scripts\cmds')
env_config_file = os.path.join(env_kconfig_path, '.config')
if (not os.path.isfile(env_config_file)) or (os.path.isfile(env_config_file) and find_macro_in_config(env_config_file, 'SYS_PKGS_DOWNLOAD_ACCELERATE')):
get_package_url, get_ver_sha = get_url_from_mirror_server('packages', 'latest')
if get_package_url != None:
git_repo = get_package_url
else:
print("Failed to get url from mirror server. Using default url.")
git_repo = 'https://gitee.com/RT-Thread-Mirror/packages.git'
else:
git_repo = 'https://github.com/RT-Thread/packages.git'
packages_root = pkgs_root
pkgs_path = os.path.join(packages_root, 'packages')
if not os.path.isdir(pkgs_path):
cmd = 'git clone ' + git_repo + ' ' + pkgs_path
os.system(cmd)
print ("upgrade from :%s" % (git_repo.encode("utf-8")))
else:
print("Begin to upgrade env packages.")
cmd = r'git pull ' + git_repo
execute_command(cmd, cwd=pkgs_path)
print("==============================> Env packages upgrade done \n")
for filename in os.listdir(packages_root):
package_path = os.path.join(packages_root, filename)
if os.path.isdir(package_path):
if package_path == pkgs_path:
continue
if os.path.isdir(os.path.join(package_path, '.git')):
print("Begin to upgrade %s." % filename)
cmd = r'git pull'
execute_command(cmd, cwd=package_path)
print("==============================> Env %s update done \n" % filename)
def upgrade_env_script():
"""Update env function scripts."""
print("Begin to upgrade env scripts.")
env_root = Import('env_root')
env_kconfig_path = os.path.join(env_root, 'tools\scripts\cmds')
env_config_file = os.path.join(env_kconfig_path, '.config')
if (not os.path.isfile(env_config_file)) or (os.path.isfile(env_config_file) and find_macro_in_config(env_config_file, 'SYS_PKGS_DOWNLOAD_ACCELERATE')):
get_package_url, get_ver_sha = get_url_from_mirror_server('env', 'latest')
if get_package_url != None:
env_scripts_repo = get_package_url
else:
print("Failed to get url from mirror server. Using default url.")
env_scripts_repo = 'https://gitee.com/RT-Thread-Mirror/env.git'
else:
env_scripts_repo = 'https://github.com/RT-Thread/env.git'
env_scripts_root = os.path.join(env_root, 'tools', 'scripts')
cmd = r'git pull ' + env_scripts_repo
execute_command(cmd, cwd=env_scripts_root)
print("==============================> Env scripts upgrade done \n")
def package_upgrade():
"""Update the package repository directory and env function scripts."""
upgrade_packages_index()
upgrade_env_script()
def cmd(args):
"""Env's pkgs command execution options."""
if args.package_update_y:
package_update(True)
elif args.package_update:
package_update()
elif args.package_create:
package_wizard()
elif args.package_list:
package_list()
elif args.package_upgrade:
package_upgrade()
elif args.package_print_env:
package_print_env()
else:
os.system('pkgs -h')
def add_parser(sub):
"""The pkgs command parser for env."""
parser = sub.add_parser('package', help=__doc__, description=__doc__)
parser.add_argument('--force-update',
help='force update and clean packages, install or remove the packages by your settings in menuconfig',
action='store_true',
default=False,
dest='package_update_y')
parser.add_argument('--update',
help='update packages, install or remove the packages by your settings in menuconfig',
action='store_true',
default=False,
dest='package_update')
parser.add_argument('--list',
help='list target packages',
action='store_true',
default=False,
dest='package_list')
parser.add_argument('--wizard',
help='create a new package with wizard',
action='store_true',
default=False,
dest='package_create')
parser.add_argument('--upgrade',
help='upgrade local packages list and ENV scripts from git repo',
action='store_true',
default=False,
dest='package_upgrade')
parser.add_argument('--printenv',
help='print environmental variables to check',
action='store_true',
default=False,
dest='package_print_env')
# parser.add_argument('--upgrade', dest='reposource', required=False,
# help='add source & update packages repo ')
parser.set_defaults(func=cmd)
|
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28,
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201,
198
] | 2.110933 | 18,137 |
# Corrigido
# Bloco de importações
import random
# Bloco de entrada
print()
n = int(input('Informe um número maior que zero: '))
print()
# Bloco de cálculos
num = random.randint(0, n)
# Bloco de saída
print('Numéro de saída: {}.'.format(num))
print()
|
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2,
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2,
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25,
23884,
2637,
13,
18982,
7,
22510,
4008,
198,
4798,
3419,
198
] | 2.33945 | 109 |
# -*- encoding: utf-8 -*-
from django.conf.urls.defaults import *
from django.contrib import admin
from django.conf import settings
from tastypie.api import Api
from journalmanager import views, models
from api import resources
admin.autodiscover()
# RESTful API config
v1_api = Api(api_name='v1')
v1_api_resources = [
resources.JournalResource(),
resources.UserResource(),
resources.UseLicenseResource(),
resources.SponsorResource(),
resources.CollectionResource(),
resources.IssueResource(),
resources.SectionResource(),
resources.DataChangeEventResource(),
resources.PressReleaseResource(),
resources.AheadPressReleaseResource(),
resources.CheckinResource(),
resources.CheckinNoticeResource(),
resources.ArticleResource(),
resources.CheckinArticleResource(),
resources.TicketResource(),
resources.CommentResource()
]
for res in v1_api_resources:
v1_api.register(res)
urlpatterns = patterns('',
url(r'^$', views.index, name='index'),
# Article Tracking
url(r'^arttrack/', include('articletrack.urls')),
# Article Tools
url(r'^issue/(?P<issue_id>\d+)/articles/$', views.article_index, name='article.index'),
#url(r'^article/(?P<article_id>\d+)/edit/$', views.add_article, name='article.edit'),
# Journal Manager APP
url(r'^journal/', include('journalmanager.urls')),
url(r'^admin/doc/', include('django.contrib.admindocs.urls')),
url(r'^admin/', include(admin.site.urls)),
# Collection Tools
url(r'^collection/$', views.collection_index, {'model': models.Collection}, name='collection.index'),
url(r'^collection/new/$', views.add_collection, name='collection.add'),
url(r'^collection/(?P<collection_id>\d+)/edit/$', views.add_collection, name='collection.edit'),
url(r'accounts/', include('accounts.urls')),
(r'^i18n/', include('django.conf.urls.i18n')),
# Trash
url(r'^trash/$', views.trash_listing, name="trash.listing"),
url(r'^trash/bulk_action/(?P<model_name>\w+)/(?P<action_name>\w+)/(?P<value>\w+)/$',
views.generic_bulk_action, name='trash.bulk_action'),
#API version 1
(r'^api/', include(v1_api.urls)),
(r'^export/', include('export.urls')),
#AJAX
url(r'^ajx/ajx3/$', views.ajx_list_users, name="ajx.ajx_list_users"),
)
if settings.DEBUG:
urlpatterns += patterns('',
url(r'^static/(?P<path>.*)$', 'django.views.static.serve',
{'document_root': settings.MEDIA_ROOT}),
)
|
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] | 2.593361 | 964 |
"""
Neuroimaging cartesian reconstruction
=====================================
Credit: L Elgueddari
In this tutorial we will reconstruct an MRI image from the sparse kspace
measurments.
"""
# Package import
import pysap
from pysap.data import get_sample_data
from mri.numerics.linear import Wavelet2
from mri.numerics.fourier import NFFT
from mri.numerics.reconstruct import sparse_rec_fista
from mri.numerics.reconstruct import sparse_rec_condatvu
from mri.numerics.gradient import Gradient_pMRI
from mri.numerics.proximity import Threshold
from pysap.plugins.mri.parallel_mri.extract_sensitivity_maps import (
extract_k_space_center_and_locations, get_Smaps)
from pysap.plugins.mri.reconstruct.utils import normalize_frequency_locations
# Third party import
import numpy as np
# Loading input data
Il = get_sample_data("2d-pmri").data.astype("complex128")
SOS = np.squeeze(np.sqrt(np.sum(np.abs(Il)**2, axis=0)))
Smaps = np.asarray([Il[channel]/SOS for channel in range(Il.shape[0])])
kspace_loc = normalize_frequency_locations(
get_sample_data("mri-radial-samples").data)
image = pysap.Image(data=np.abs(SOS))
image.show()
#############################################################################
# Generate the kspace
# -------------------
#
# From the 2D brain slice and the acquistion mask, we generate the acquisition
# measurments, the observed kspace.
# We then reconstruct the zero order solution.
# Generate the subsampled kspace
fourier_op_gen = NFFT(samples=kspace_loc, shape=SOS.shape)
kspace_data = np.asarray([fourier_op_gen.op(Il[l]) for l in
range(Il.shape[0])])
# Generate the senitivity matrix from undersampled data
data_thresholded, samples_thresholded = extract_k_space_center_and_locations(
data_values=kspace_data,
samples_locations=kspace_loc,
thr=(0.5/128*5, 0.5/128*5),
img_shape=SOS.shape)
Smaps, SOS_Smaps = get_Smaps(
k_space=data_thresholded,
img_shape=SOS.shape,
samples=samples_thresholded,
mode='Gridding',
min_samples=np.min(kspace_loc),
max_samples=np.max(kspace_loc),
method='linear')
#############################################################################
# FISTA optimization
# ------------------
#
# We now want to refine the zero order solution using a FISTA optimization.
# Here no cost function is set, and the optimization will reach the
# maximum number of iterations. Fill free to play with this parameter.
# Start the FISTA reconstruction
max_iter = 50
linear_op = Wavelet2(wavelet_name="UndecimatedBiOrthogonalTransform",
nb_scale=4)
prox_op = Threshold(None)
fourier_op = NFFT(samples=kspace_loc, shape=SOS.shape)
gradient_op = Gradient_pMRI(data=kspace_data,
fourier_op=fourier_op,
linear_op=linear_op,
S=Smaps)
x_final, transform, cost, metrics = sparse_rec_fista(
gradient_op=gradient_op,
linear_op=linear_op,
prox_op=prox_op,
cost_op=None,
mu=1e-7,
lambda_init=1.0,
max_nb_of_iter=max_iter,
atol=1e-4,
verbose=1)
image_rec = pysap.Image(data=np.abs(x_final))
image_rec.show()
#############################################################################
# Condata-Vu optimization
# -----------------------
#
# We now want to refine the zero order solution using a Condata-Vu
# optimization.
# Here no cost function is set, and the optimization will reach the
# maximum number of iterations. Fill free to play with this parameter.
# Start the CONDAT-VU reconstruction
max_iter = 50
gradient_op_cd = Gradient_pMRI(data=kspace_data,
fourier_op=fourier_op,
S=Smaps)
x_final, transform, cost, metrics = sparse_rec_condatvu(
gradient_op=gradient_op_cd,
linear_op=linear_op,
prox_dual_op=prox_op,
cost_op=None,
std_est=None,
std_est_method="dual",
std_thr=2.,
mu=1e-7,
tau=None,
sigma=None,
relaxation_factor=1.0,
nb_of_reweights=0,
max_nb_of_iter=max_iter,
add_positivity=False,
atol=1e-4,
verbose=1)
image_rec = pysap.Image(data=np.abs(x_final))
image_rec.show()
|
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15655,
23286,
5574,
400,
519,
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41762,
1600,
198,
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220,
220,
220,
220,
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299,
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536,
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7,
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28,
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220,
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220,
220,
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311,
28,
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8,
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198,
87,
62,
20311,
11,
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37456,
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11,
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28,
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198,
220,
220,
220,
379,
349,
28,
16,
68,
12,
19,
11,
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220,
220,
220,
15942,
577,
28,
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8,
198,
9060,
62,
8344,
796,
279,
893,
499,
13,
5159,
7,
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28,
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13,
8937,
7,
87,
62,
20311,
4008,
198,
9060,
62,
8344,
13,
12860,
3419,
628,
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29113,
29113,
7804,
4242,
2,
198,
2,
9724,
1045,
12,
53,
84,
23989,
198,
2,
41436,
6329,
198,
2,
198,
2,
775,
783,
765,
284,
35139,
262,
6632,
1502,
4610,
1262,
257,
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1045,
12,
53,
84,
198,
2,
23989,
13,
198,
2,
3423,
645,
1575,
2163,
318,
900,
11,
290,
262,
23989,
481,
3151,
262,
198,
2,
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286,
34820,
13,
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284,
711,
351,
428,
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13,
198,
198,
2,
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62,
10210,
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62,
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11,
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220,
220,
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220,
220,
220,
220,
220,
220,
220,
220,
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220,
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46287,
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198,
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220,
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220,
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220,
220,
220,
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220,
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220,
220,
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220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
311,
28,
7556,
1686,
8,
198,
87,
62,
20311,
11,
6121,
11,
1575,
11,
20731,
796,
29877,
62,
8344,
62,
17561,
265,
40939,
7,
198,
220,
220,
220,
31312,
62,
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28,
49607,
62,
404,
62,
10210,
11,
198,
220,
220,
220,
14174,
62,
404,
28,
29127,
62,
404,
11,
198,
220,
220,
220,
14793,
62,
646,
282,
62,
404,
28,
1676,
87,
62,
404,
11,
198,
220,
220,
220,
1575,
62,
404,
28,
14202,
11,
198,
220,
220,
220,
14367,
62,
395,
28,
14202,
11,
198,
220,
220,
220,
14367,
62,
395,
62,
24396,
2625,
646,
282,
1600,
198,
220,
220,
220,
14367,
62,
400,
81,
28,
17,
1539,
198,
220,
220,
220,
38779,
28,
16,
68,
12,
22,
11,
198,
220,
220,
220,
256,
559,
28,
14202,
11,
198,
220,
220,
220,
264,
13495,
28,
14202,
11,
198,
220,
220,
220,
34205,
62,
31412,
28,
16,
13,
15,
11,
198,
220,
220,
220,
299,
65,
62,
1659,
62,
260,
43775,
28,
15,
11,
198,
220,
220,
220,
3509,
62,
46803,
62,
1659,
62,
2676,
28,
9806,
62,
2676,
11,
198,
220,
220,
220,
751,
62,
1930,
11365,
28,
25101,
11,
198,
220,
220,
220,
379,
349,
28,
16,
68,
12,
19,
11,
198,
220,
220,
220,
15942,
577,
28,
16,
8,
198,
9060,
62,
8344,
796,
279,
893,
499,
13,
5159,
7,
7890,
28,
37659,
13,
8937,
7,
87,
62,
20311,
4008,
198,
9060,
62,
8344,
13,
12860,
3419,
198
] | 2.539442 | 1,648 |
Version = "4.5.2"
if __name__ == "__main__":
print (Version)
|
[
14815,
796,
366,
19,
13,
20,
13,
17,
1,
198,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
220,
3601,
357,
14815,
8,
628
] | 2.233333 | 30 |
from django.contrib.auth.models import Group, Permission
from django.contrib.contenttypes.fields import GenericForeignKey
from django.contrib.contenttypes.models import ContentType
from django.core.exceptions import ValidationError
from django.db import models
from django.utils.translation import ugettext_lazy as _
from guardian.compat import user_model_label
from guardian.ctypes import get_content_type
from guardian.managers import GroupObjectPermissionManager, UserObjectPermissionManager
class BaseObjectPermission(models.Model):
"""
Abstract ObjectPermission class. Actual class should additionally define
a ``content_object`` field and either ``user`` or ``group`` field.
"""
permission = models.ForeignKey(Permission, on_delete=models.CASCADE)
class UserObjectPermissionBase(BaseObjectPermission):
"""
**Manager**: :manager:`UserObjectPermissionManager`
"""
user = models.ForeignKey(user_model_label, on_delete=models.CASCADE)
objects = UserObjectPermissionManager()
class GroupObjectPermissionBase(BaseObjectPermission):
"""
**Manager**: :manager:`GroupObjectPermissionManager`
"""
group = models.ForeignKey(Group, on_delete=models.CASCADE)
objects = GroupObjectPermissionManager()
setattr(Group, 'add_obj_perm',
lambda self, perm, obj: GroupObjectPermission.objects.assign_perm(perm, self, obj))
setattr(Group, 'del_obj_perm',
lambda self, perm, obj: GroupObjectPermission.objects.remove_perm(perm, self, obj))
|
[
6738,
42625,
14208,
13,
3642,
822,
13,
18439,
13,
27530,
1330,
4912,
11,
2448,
3411,
198,
6738,
42625,
14208,
13,
3642,
822,
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11299,
19199,
13,
25747,
1330,
42044,
33616,
9218,
198,
6738,
42625,
14208,
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822,
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1330,
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24765,
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198,
6738,
42625,
14208,
13,
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1330,
4981,
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6738,
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62,
75,
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355,
4808,
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6738,
21688,
13,
5589,
265,
1330,
2836,
62,
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62,
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13,
310,
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651,
62,
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62,
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6738,
21688,
13,
805,
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1330,
4912,
10267,
5990,
3411,
13511,
11,
11787,
10267,
5990,
3411,
13511,
628,
198,
4871,
7308,
10267,
5990,
3411,
7,
27530,
13,
17633,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
27741,
9515,
5990,
3411,
1398,
13,
33520,
1398,
815,
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8160,
198,
220,
220,
220,
257,
7559,
11299,
62,
15252,
15506,
2214,
290,
2035,
7559,
7220,
15506,
393,
7559,
8094,
15506,
2214,
13,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
7170,
796,
4981,
13,
33616,
9218,
7,
5990,
3411,
11,
319,
62,
33678,
28,
27530,
13,
34,
42643,
19266,
8,
628,
198,
198,
4871,
11787,
10267,
5990,
3411,
14881,
7,
14881,
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5990,
3411,
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198,
220,
220,
220,
37227,
198,
220,
220,
220,
12429,
13511,
1174,
25,
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25,
63,
12982,
10267,
5990,
3411,
13511,
63,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
2836,
796,
4981,
13,
33616,
9218,
7,
7220,
62,
19849,
62,
18242,
11,
319,
62,
33678,
28,
27530,
13,
34,
42643,
19266,
8,
628,
220,
220,
220,
5563,
796,
11787,
10267,
5990,
3411,
13511,
3419,
628,
198,
198,
4871,
4912,
10267,
5990,
3411,
14881,
7,
14881,
10267,
5990,
3411,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
12429,
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25,
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220,
220,
220,
37227,
198,
220,
220,
220,
1448,
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4981,
13,
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7,
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11,
319,
62,
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28,
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13,
34,
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19266,
8,
628,
220,
220,
220,
5563,
796,
4912,
10267,
5990,
3411,
13511,
3419,
628,
198,
198,
2617,
35226,
7,
13247,
11,
705,
2860,
62,
26801,
62,
16321,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
37456,
2116,
11,
9943,
11,
26181,
25,
4912,
10267,
5990,
3411,
13,
48205,
13,
562,
570,
62,
16321,
7,
16321,
11,
2116,
11,
26181,
4008,
198,
2617,
35226,
7,
13247,
11,
705,
12381,
62,
26801,
62,
16321,
3256,
198,
220,
220,
220,
220,
220,
220,
220,
37456,
2116,
11,
9943,
11,
26181,
25,
4912,
10267,
5990,
3411,
13,
48205,
13,
28956,
62,
16321,
7,
16321,
11,
2116,
11,
26181,
4008,
198
] | 3.265659 | 463 |
from transbank.error.invalid_amount_error import InvalidAmountError
|
[
6738,
1007,
17796,
13,
18224,
13,
259,
12102,
62,
17287,
62,
18224,
1330,
17665,
31264,
12331,
628
] | 4.058824 | 17 |
# -*- coding: utf-8 -*-
from usercrawler import UserCrawler
uid = u'小鱼游啊游0423'
crawler = UserCrawler()
userinfo = crawler.scratch(uid)
print userinfo
|
[
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
6738,
514,
2798,
39464,
1330,
11787,
34,
39464,
198,
27112,
796,
334,
6,
22887,
237,
165,
109,
120,
162,
116,
116,
161,
243,
232,
162,
116,
116,
3023,
1954,
6,
198,
66,
39464,
796,
11787,
34,
39464,
3419,
198,
7220,
10951,
796,
27784,
1754,
13,
1416,
36722,
7,
27112,
8,
198,
4798,
2836,
10951
] | 2.191176 | 68 |
import torch
from torch.nn import functional as F
from .utils import ConvNdTorch, PoolingNdTorch, NormNdTorch, DropoutNdTorch
from .basic_networks import BaseSegmentationTorchNetwork
|
[
11748,
28034,
198,
6738,
28034,
13,
20471,
1330,
10345,
355,
376,
198,
6738,
764,
26791,
1330,
34872,
45,
67,
15884,
354,
11,
19850,
278,
45,
67,
15884,
354,
11,
11220,
45,
67,
15884,
354,
11,
14258,
448,
45,
67,
15884,
354,
198,
6738,
764,
35487,
62,
3262,
5225,
1330,
7308,
41030,
14374,
15884,
354,
26245,
628,
628
] | 3.263158 | 57 |
from tensorflow.keras import layers
import time
import tensorflow as tf
def make_generator_model():
'''
Create GAN generator
:return: Generator
'''
model = tf.keras.Sequential()
model.add(layers.Dense(7*7*256, use_bias=False, input_shape=(100,)))
model.add(layers.BatchNormalization())
model.add(layers.LeakyReLU())
model.add(layers.Reshape((7, 7, 256)))
assert model.output_shape == (None, 7, 7, 256)
model.add(layers.Conv2DTranspose(128, (5, 5), strides=(1, 1), padding='same', use_bias=False))
assert model.output_shape == (None, 7, 7, 128)
model.add(layers.BatchNormalization())
model.add(layers.LeakyReLU())
model.add(layers.Conv2DTranspose(64, (5, 5), strides=(2, 2), padding='same', use_bias=False))
assert model.output_shape == (None, 14, 14, 64)
model.add(layers.BatchNormalization())
model.add(layers.LeakyReLU())
model.add(layers.Conv2DTranspose(1, (5, 5), strides=(2, 2), padding='same', use_bias=False, activation='tanh'))
assert model.output_shape == (None, 28, 28, 1)
return model
def make_discriminator_model():
"""
Create Discriminator for GAN
:return: Discriminator
"""
model = tf.keras.Sequential()
model.add(layers.Conv2D(64, (5, 5), strides=(2, 2), padding='same',
input_shape=[28, 28, 1]))
model.add(layers.LeakyReLU())
model.add(layers.Dropout(0.3))
model.add(layers.Conv2D(128, (5, 5), strides=(2, 2), padding='same'))
model.add(layers.LeakyReLU())
model.add(layers.Dropout(0.3))
model.add(layers.Flatten())
model.add(layers.Dense(1))
return model
def discriminator_loss(real_output, fake_output, cross_entropy):
"""
Calculate loss
:param real_output: real output
:param fake_output: fake output
:param cross_entropy: cross entropy
:return: loss
"""
real_loss = cross_entropy(tf.ones_like(real_output), real_output)
fake_loss = cross_entropy(tf.zeros_like(fake_output), fake_output)
total_loss = real_loss + fake_loss
return total_loss
@tf.function
|
[
6738,
11192,
273,
11125,
13,
6122,
292,
1330,
11685,
198,
11748,
640,
198,
198,
11748,
11192,
273,
11125,
355,
48700,
628,
198,
4299,
787,
62,
8612,
1352,
62,
19849,
33529,
198,
220,
220,
220,
705,
7061,
198,
220,
220,
220,
13610,
402,
1565,
17301,
198,
220,
220,
220,
1058,
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25,
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198,
220,
220,
220,
705,
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220,
220,
220,
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13,
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13,
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7,
75,
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13,
35,
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7,
22,
9,
22,
9,
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11,
779,
62,
65,
4448,
28,
25101,
11,
5128,
62,
43358,
16193,
3064,
11,
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198,
220,
220,
220,
2746,
13,
2860,
7,
75,
6962,
13,
33,
963,
26447,
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] | 2.386441 | 885 |
from typing import Optional, Union
from slack_sdk.web import SlackResponse
from slack_bolt.authorization import AuthorizeResult
from slack_bolt.request.request import BoltRequest
from slack_bolt.response import BoltResponse
#
# NOTE: this source file intentionally avoids having a reference to
# AsyncBoltRequest, AsyncSlackResponse, and whatever Async-prefixed.
#
# The reason why we do so is to enable developers use sync version of Bolt
# without installing aiohttp library (or any others we may use for async things)
#
|
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#!/usr/bin/env python
# -*- coding:utf-8 -*-
BROKER_BACKEND = "mongodb"
BROKER_HOST = "localhost"
BROKER_PORT = 7680
CELERY_RESULT_BACKEND = "mongodb"
CELERY_MONGODB_BACKEND_SETTINGS = {
"host": "localhost",
"port": 7680,
"database": "books",
"taskmeta_collection": "celerytasks",
}
CELERYD_CONCURRENCY = 5
# CELERYD_LOG_LEVEL = "INFO"
# CELERYD_LOG_FILE = "logs/celery.log"
CELERY_IMPORTS = ("celerytasks", )
|
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# -*- coding: utf-8 -*-
# Generated by the protocol buffer compiler. DO NOT EDIT!
# source: http.proto
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflection as _reflection
from google.protobuf import symbol_database as _symbol_database
# @@protoc_insertion_point(imports)
_sym_db = _symbol_database.Default()
DESCRIPTOR = _descriptor.FileDescriptor(
name="http.proto",
package="fetch.aea.Http",
syntax="proto3",
serialized_options=None,
serialized_pb=b'\n\nhttp.proto\x12\x0e\x66\x65tch.aea.Http"\xf1\x03\n\x0bHttpMessage\x12\x12\n\nmessage_id\x18\x01 \x01(\x05\x12"\n\x1a\x64ialogue_starter_reference\x18\x02 \x01(\t\x12$\n\x1c\x64ialogue_responder_reference\x18\x03 \x01(\t\x12\x0e\n\x06target\x18\x04 \x01(\x05\x12\x43\n\x07request\x18\x05 \x01(\x0b\x32\x30.fetch.aea.Http.HttpMessage.Request_PerformativeH\x00\x12\x45\n\x08response\x18\x06 \x01(\x0b\x32\x31.fetch.aea.Http.HttpMessage.Response_PerformativeH\x00\x1a\x64\n\x14Request_Performative\x12\x0e\n\x06method\x18\x01 \x01(\t\x12\x0b\n\x03url\x18\x02 \x01(\t\x12\x0f\n\x07version\x18\x03 \x01(\t\x12\x0f\n\x07headers\x18\x04 \x01(\t\x12\r\n\x05\x62odyy\x18\x05 \x01(\x0c\x1ar\n\x15Response_Performative\x12\x0f\n\x07version\x18\x01 \x01(\t\x12\x13\n\x0bstatus_code\x18\x02 \x01(\x05\x12\x13\n\x0bstatus_text\x18\x03 \x01(\t\x12\x0f\n\x07headers\x18\x04 \x01(\t\x12\r\n\x05\x62odyy\x18\x05 \x01(\x0c\x42\x0e\n\x0cperformativeb\x06proto3',
)
_HTTPMESSAGE_REQUEST_PERFORMATIVE = _descriptor.Descriptor(
name="Request_Performative",
full_name="fetch.aea.Http.HttpMessage.Request_Performative",
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name="method",
full_name="fetch.aea.Http.HttpMessage.Request_Performative.method",
index=0,
number=1,
type=9,
cpp_type=9,
label=1,
has_default_value=False,
default_value=b"".decode("utf-8"),
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=None,
file=DESCRIPTOR,
),
_descriptor.FieldDescriptor(
name="url",
full_name="fetch.aea.Http.HttpMessage.Request_Performative.url",
index=1,
number=2,
type=9,
cpp_type=9,
label=1,
has_default_value=False,
default_value=b"".decode("utf-8"),
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=None,
file=DESCRIPTOR,
),
_descriptor.FieldDescriptor(
name="version",
full_name="fetch.aea.Http.HttpMessage.Request_Performative.version",
index=2,
number=3,
type=9,
cpp_type=9,
label=1,
has_default_value=False,
default_value=b"".decode("utf-8"),
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=None,
file=DESCRIPTOR,
),
_descriptor.FieldDescriptor(
name="headers",
full_name="fetch.aea.Http.HttpMessage.Request_Performative.headers",
index=3,
number=4,
type=9,
cpp_type=9,
label=1,
has_default_value=False,
default_value=b"".decode("utf-8"),
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=None,
file=DESCRIPTOR,
),
_descriptor.FieldDescriptor(
name="bodyy",
full_name="fetch.aea.Http.HttpMessage.Request_Performative.bodyy",
index=4,
number=5,
type=12,
cpp_type=9,
label=1,
has_default_value=False,
default_value=b"",
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=None,
file=DESCRIPTOR,
),
],
extensions=[],
nested_types=[],
enum_types=[],
serialized_options=None,
is_extendable=False,
syntax="proto3",
extension_ranges=[],
oneofs=[],
serialized_start=296,
serialized_end=396,
)
_HTTPMESSAGE_RESPONSE_PERFORMATIVE = _descriptor.Descriptor(
name="Response_Performative",
full_name="fetch.aea.Http.HttpMessage.Response_Performative",
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name="version",
full_name="fetch.aea.Http.HttpMessage.Response_Performative.version",
index=0,
number=1,
type=9,
cpp_type=9,
label=1,
has_default_value=False,
default_value=b"".decode("utf-8"),
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=None,
file=DESCRIPTOR,
),
_descriptor.FieldDescriptor(
name="status_code",
full_name="fetch.aea.Http.HttpMessage.Response_Performative.status_code",
index=1,
number=2,
type=5,
cpp_type=1,
label=1,
has_default_value=False,
default_value=0,
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=None,
file=DESCRIPTOR,
),
_descriptor.FieldDescriptor(
name="status_text",
full_name="fetch.aea.Http.HttpMessage.Response_Performative.status_text",
index=2,
number=3,
type=9,
cpp_type=9,
label=1,
has_default_value=False,
default_value=b"".decode("utf-8"),
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=None,
file=DESCRIPTOR,
),
_descriptor.FieldDescriptor(
name="headers",
full_name="fetch.aea.Http.HttpMessage.Response_Performative.headers",
index=3,
number=4,
type=9,
cpp_type=9,
label=1,
has_default_value=False,
default_value=b"".decode("utf-8"),
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=None,
file=DESCRIPTOR,
),
_descriptor.FieldDescriptor(
name="bodyy",
full_name="fetch.aea.Http.HttpMessage.Response_Performative.bodyy",
index=4,
number=5,
type=12,
cpp_type=9,
label=1,
has_default_value=False,
default_value=b"",
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=None,
file=DESCRIPTOR,
),
],
extensions=[],
nested_types=[],
enum_types=[],
serialized_options=None,
is_extendable=False,
syntax="proto3",
extension_ranges=[],
oneofs=[],
serialized_start=398,
serialized_end=512,
)
_HTTPMESSAGE = _descriptor.Descriptor(
name="HttpMessage",
full_name="fetch.aea.Http.HttpMessage",
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name="message_id",
full_name="fetch.aea.Http.HttpMessage.message_id",
index=0,
number=1,
type=5,
cpp_type=1,
label=1,
has_default_value=False,
default_value=0,
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=None,
file=DESCRIPTOR,
),
_descriptor.FieldDescriptor(
name="dialogue_starter_reference",
full_name="fetch.aea.Http.HttpMessage.dialogue_starter_reference",
index=1,
number=2,
type=9,
cpp_type=9,
label=1,
has_default_value=False,
default_value=b"".decode("utf-8"),
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=None,
file=DESCRIPTOR,
),
_descriptor.FieldDescriptor(
name="dialogue_responder_reference",
full_name="fetch.aea.Http.HttpMessage.dialogue_responder_reference",
index=2,
number=3,
type=9,
cpp_type=9,
label=1,
has_default_value=False,
default_value=b"".decode("utf-8"),
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=None,
file=DESCRIPTOR,
),
_descriptor.FieldDescriptor(
name="target",
full_name="fetch.aea.Http.HttpMessage.target",
index=3,
number=4,
type=5,
cpp_type=1,
label=1,
has_default_value=False,
default_value=0,
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=None,
file=DESCRIPTOR,
),
_descriptor.FieldDescriptor(
name="request",
full_name="fetch.aea.Http.HttpMessage.request",
index=4,
number=5,
type=11,
cpp_type=10,
label=1,
has_default_value=False,
default_value=None,
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=None,
file=DESCRIPTOR,
),
_descriptor.FieldDescriptor(
name="response",
full_name="fetch.aea.Http.HttpMessage.response",
index=5,
number=6,
type=11,
cpp_type=10,
label=1,
has_default_value=False,
default_value=None,
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=None,
file=DESCRIPTOR,
),
],
extensions=[],
nested_types=[
_HTTPMESSAGE_REQUEST_PERFORMATIVE,
_HTTPMESSAGE_RESPONSE_PERFORMATIVE,
],
enum_types=[],
serialized_options=None,
is_extendable=False,
syntax="proto3",
extension_ranges=[],
oneofs=[
_descriptor.OneofDescriptor(
name="performative",
full_name="fetch.aea.Http.HttpMessage.performative",
index=0,
containing_type=None,
fields=[],
),
],
serialized_start=31,
serialized_end=528,
)
_HTTPMESSAGE_REQUEST_PERFORMATIVE.containing_type = _HTTPMESSAGE
_HTTPMESSAGE_RESPONSE_PERFORMATIVE.containing_type = _HTTPMESSAGE
_HTTPMESSAGE.fields_by_name["request"].message_type = _HTTPMESSAGE_REQUEST_PERFORMATIVE
_HTTPMESSAGE.fields_by_name[
"response"
].message_type = _HTTPMESSAGE_RESPONSE_PERFORMATIVE
_HTTPMESSAGE.oneofs_by_name["performative"].fields.append(
_HTTPMESSAGE.fields_by_name["request"]
)
_HTTPMESSAGE.fields_by_name["request"].containing_oneof = _HTTPMESSAGE.oneofs_by_name[
"performative"
]
_HTTPMESSAGE.oneofs_by_name["performative"].fields.append(
_HTTPMESSAGE.fields_by_name["response"]
)
_HTTPMESSAGE.fields_by_name["response"].containing_oneof = _HTTPMESSAGE.oneofs_by_name[
"performative"
]
DESCRIPTOR.message_types_by_name["HttpMessage"] = _HTTPMESSAGE
_sym_db.RegisterFileDescriptor(DESCRIPTOR)
HttpMessage = _reflection.GeneratedProtocolMessageType(
"HttpMessage",
(_message.Message,),
{
"Request_Performative": _reflection.GeneratedProtocolMessageType(
"Request_Performative",
(_message.Message,),
{
"DESCRIPTOR": _HTTPMESSAGE_REQUEST_PERFORMATIVE,
"__module__": "http_pb2"
# @@protoc_insertion_point(class_scope:fetch.aea.Http.HttpMessage.Request_Performative)
},
),
"Response_Performative": _reflection.GeneratedProtocolMessageType(
"Response_Performative",
(_message.Message,),
{
"DESCRIPTOR": _HTTPMESSAGE_RESPONSE_PERFORMATIVE,
"__module__": "http_pb2"
# @@protoc_insertion_point(class_scope:fetch.aea.Http.HttpMessage.Response_Performative)
},
),
"DESCRIPTOR": _HTTPMESSAGE,
"__module__": "http_pb2"
# @@protoc_insertion_point(class_scope:fetch.aea.Http.HttpMessage)
},
)
_sym_db.RegisterMessage(HttpMessage)
_sym_db.RegisterMessage(HttpMessage.Request_Performative)
_sym_db.RegisterMessage(HttpMessage.Response_Performative)
# @@protoc_insertion_point(module_scope)
|
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220,
220,
220,
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] | 1.83825 | 7,796 |
from function_file import best_fit, line_graph, normal_curve
if __name__ == "__main__":
# Create dataframe
df2 = pd.read_csv("../input/english-premier-league-data-for-10-seasons/epldat10seasons/epl-allseasons-matchstats.csv")
# Create dataframe to summarise cards given by season and create "TotalReds" column
season_cards = df2.groupby("Season")["HomeRedCards", "AwayRedCards"].sum()
season_cards["TotalReds"] = season_cards["HomeRedCards"] + season_cards["AwayRedCards"]
season_cards = season_cards.rename(columns={"HomeRedCards":"HomeReds", "AwayRedCards":"AwayReds"})
# Create line graphs for HomeReds, AwayReds and TotalReds, including linear regression lines
line_graph(season_cards["HomeReds"], "HomeReds", "Home Team Red Cards", style="seaborn-poster")
line_graph(season_cards["AwayReds"], "AwayReds", "Away Team Red Cards", style="seaborn-poster")
line_graph(season_cards["TotalReds"], "TotalReds", "Total Team Red Cards", style="seaborn-poster")
# Create variables to use to calculate z-values
data = season_cards["TotalReds"]
s1415 = np.max(data) # Taking the highest red card tally value, which is for season 2014/15
s1718 = np.min(data) # Taking the lowest red card tally value, which is for season 2017/18
mean = np.mean(data) # Taking the mean value for the 10 years of red card data
std = np.std(data) # Taking the standard deviation of this data
# Plot normal curves and show z-values
normal_curve(True, z1718, "Season 2017/18 Data")
normal_curve(True, z1415, "Season 2014/15 Data")
# Calculate p-values
p_value1415 = norm.sf(abs(z1415))
p_value1718 = norm.sf(abs(z1718))
|
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7,
89,
1558,
1507,
4008,
628,
220,
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220,
198
] | 2.577875 | 687 |
"""
Helpers for setup.py, e.g. requirements.txt parsing, version bumping, custom setup.py commands
Inside of :py:mod:`privex.helpers.setuppy.common` there's a variety of functions related to generating
requirements.txt files, parsing requirements.txt files which recursively import other requirements.txt files,
and handing automatic generation of ``extras_require`` from a folder containing requirements txt files.
Inside of :py:mod:`privex.helpers.setuppy.bump` - most notably is :py:func:`.bump_version` - a function which
detects a package's version, increments the appropriate part of the version number, and then updates the python
file containing the version number (e.g. an ``__init__.py``)
Inside of :py:mod:`privex.helpers.setuppy.commands` there are command classes which can be loaded into setup.py to
assist with building python packages, generating requirements.txt files from extras, as well as general management
such as a :class:`.BumpCommand` which allows you to bump your package version with a simple ``./setup.py bump --minor``
More detailed usage documentation is available within each individual module's documentation.
"""
try:
from privex.helpers.setuppy.common import *
except ImportError:
log.debug('%s failed to import "setuppy.common", not loading ...', __name__)
try:
from privex.helpers.setuppy.bump import *
except ImportError:
log.debug('%s failed to import "setuppy.bump", not loading ...', __name__)
try:
from privex.helpers.setuppy.commands import *
except ImportError:
log.debug('%s failed to import "setuppy.commands", not loading ...', __name__)
|
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] | 3.447761 | 469 |
__all__ = ('setup', 'Extension')
from celerid import patch_distutils # Cause distutils to be hot-patched.
from distutils.core import setup, Extension as std_Extension
from distutils.errors import DistutilsOptionError
|
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11,
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62,
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198,
6738,
1233,
26791,
13,
48277,
1330,
4307,
26791,
19722,
12331,
628
] | 3.606557 | 61 |
#
# Copyright (C) 2019 Databricks, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import inspect
from distutils.version import LooseVersion
import pandas as pd
from databricks import koalas
from databricks.koalas.config import set_option, reset_option
from databricks.koalas.exceptions import PandasNotImplementedError
from databricks.koalas.missing.groupby import _MissingPandasLikeDataFrameGroupBy, \
_MissingPandasLikeSeriesGroupBy
from databricks.koalas.testing.utils import ReusedSQLTestCase, TestUtils
|
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4487,
628
] | 3.52069 | 290 |
import multiprocessing
import os
import random
import shutil
import threading
import time
import traceback
import json
import re
import tempfile
from subprocess import run, PIPE
from urllib.parse import urlparse
from botocore.exceptions import ClientError
import boto3
import requests
from idseq_dag.engine.pipeline_step import PipelineStep
from idseq_dag.exceptions import InsufficientReadsError
import idseq_dag.util.command as command
import idseq_dag.util.command_patterns as command_patterns
import idseq_dag.util.count as count
import idseq_dag.util.log as log
import idseq_dag.util.m8 as m8
from idseq_dag.util.s3 import fetch_reference
from idseq_dag.util.trace_lock import TraceLock
from idseq_dag.util.lineage import DEFAULT_BLACKLIST_S3, DEFAULT_WHITELIST_S3
from idseq_dag.util.m8 import NT_MIN_ALIGNMENT_LEN
MAX_CHUNKS_IN_FLIGHT = 16
CHUNK_MAX_ATTEMPTS = 3
GSNAP_CHUNK_SIZE = 240000
RAPSEARCH_CHUNK_SIZE = 320000
def download_from_s3(session, src, dest):
"""
We are transitioning away from s3 downloads of files within steps.
This is only to be used for getting the state of batch jobs from the
s3 cache. These files are small and dynamically generated based on jobs
so this fetching is very different from downloading input files.
"""
try:
url = urlparse(src)
bucket, key = url.netloc, url.path
session.client("s3").download_file(bucket, key[1:], dest)
return True
except ClientError as e:
if e.response["Error"]["Code"] == "404":
return False
raise e
class PipelineStepRunAlignment(PipelineStep):
""" Runs gsnap/rapsearch2 remotely.
For GSNAP:
```
gsnapl
-A m8
--batch=0
--use-shared-memory=0
--gmap-mode=none
--npaths=100
--ordered
-t 48
--max-mismatches=40
-D {remote_index_dir}
-d nt_k16
{remote_input_files} > {multihit_remote_outfile}
```
GSNAP documentation is available [here](http://research-pub.gene.com/gmap/).
-t (threads): For example, r5d.24xlarge machines have 96 vCPUs. These are the machines used by the alignment batch compute environment.
Each batch job is allotted 48 vcpus. Use 48 threads and each instance will be able to concurrently process 2 chunks
For Rapsearch2:
```
rapsearch
-d {remote_index_dir}/nr_rapsearch
-e -6
-l 10
-a T
-b 0
-v 50
-z 24
-q {remote_input_files}
-o {multihit_remote_outfile}
```
Rapsearch2 documentation is available [here](http://omics.informatics.indiana.edu/mg/RAPSearch2/).
"""
@staticmethod
def run(self):
''' Run alignmment remotely '''
alignment_algorithm_inputs = PipelineStepRunAlignment._alignment_algorithm_inputs(self.input_files_local[0])
duplicate_cluster_sizes_path, = self.input_files_local[1]
output_m8, deduped_output_m8, output_hitsummary, output_counts_with_dcr_json = self.output_files_local()
assert output_counts_with_dcr_json.endswith("_with_dcr.json"), self.output_files_local()
if self.is_local_run:
self.run_locally(alignment_algorithm_inputs[self.alignment_algorithm], output_m8)
else:
self.run_remotely(alignment_algorithm_inputs[self.alignment_algorithm], output_m8)
# get database
lineage_db = fetch_reference(self.additional_files["lineage_db"], self.ref_dir_local)
accession2taxid_db = fetch_reference(self.additional_files["accession2taxid_db"], self.ref_dir_local, allow_s3mi=True)
deuterostome_db = None
if self.additional_files.get("deuterostome_db"):
deuterostome_db = fetch_reference(self.additional_files["deuterostome_db"],
self.ref_dir_local, allow_s3mi=True)
blacklist_s3_file = self.additional_files.get('taxon_blacklist', DEFAULT_BLACKLIST_S3)
taxon_blacklist = fetch_reference(blacklist_s3_file, self.ref_dir_local)
taxon_whitelist = None
if self.additional_attributes.get("use_taxon_whitelist"):
taxon_whitelist = fetch_reference(self.additional_files.get("taxon_whitelist", DEFAULT_WHITELIST_S3),
self.ref_dir_local)
min_alignment_length = NT_MIN_ALIGNMENT_LEN if self.alignment_algorithm == 'gsnap' else 0
m8.call_hits_m8(output_m8, lineage_db, accession2taxid_db,
deduped_output_m8, output_hitsummary, min_alignment_length,
deuterostome_db, taxon_whitelist, taxon_blacklist)
db_type = 'NT' if self.alignment_algorithm == 'gsnap' else 'NR'
m8.generate_taxon_count_json_from_m8(
deduped_output_m8, output_hitsummary, db_type,
lineage_db, deuterostome_db, taxon_whitelist, taxon_blacklist, duplicate_cluster_sizes_path,
output_counts_with_dcr_json)
def chunk_input(self, input_files, chunksize):
"""Chunk input files into pieces for performance and parallelism."""
part_lists = [] # Lists of partial files
known_nlines = None
part_suffix = ""
chunk_nlines = chunksize * 2
for input_file in input_files:
# Count number of lines in the file
cmd_output = command.execute_with_output(
command_patterns.SingleCommand(
cmd="wc",
args=[
"-l",
input_file
]
)
)
nlines = int(cmd_output.strip().split()[0])
# Number of lines should be the same in paired files
if known_nlines is not None:
msg = "Mismatched line counts in supposedly paired files: {}".format(
input_files)
assert nlines == known_nlines, msg
known_nlines = nlines
# Set number of pieces and names
numparts = (nlines + chunk_nlines - 1) // chunk_nlines
ndigits = len(str(numparts - 1))
part_suffix = "-chunksize-%d-numparts-%d-part-" % (chunksize, numparts)
out_prefix_base = os.path.basename(input_file) + part_suffix
out_prefix = os.path.join(self.chunks_result_dir_local, out_prefix_base)
# Split large file into smaller named pieces
command.execute(
command_patterns.SingleCommand(
cmd="split",
args=[
"-a",
ndigits,
"--numeric-suffixes",
"-l",
chunk_nlines,
input_file,
out_prefix
]
)
)
command.execute_with_retries(
command_patterns.SingleCommand(
cmd="aws",
args=[
"s3",
"sync",
"--only-show-errors",
os.path.join(self.chunks_result_dir_local, ""),
os.path.join(self.chunks_result_dir_s3, ""),
"--exclude",
"*",
"--include",
out_prefix_base + "*"
]
)
)
# Get the partial file names
partial_files = []
paths = command.glob(
glob_pattern=out_prefix + "*",
strip_folder_names=True
)
partial_files.extend(paths)
# Check that the partial files match our expected chunking pattern
pattern = "{:0%dd}" % ndigits
expected_partial_files = [(out_prefix_base + pattern.format(i))
for i in range(numparts)]
msg = "something went wrong with chunking: {} != {}".format(
partial_files, expected_partial_files)
assert expected_partial_files == partial_files, msg
part_lists.append(partial_files)
# Ex: [["input_R1.fasta-part-1", "input_R2.fasta-part-1"],
# ["input_R1.fasta-part-2", "input_R2.fasta-part-2"],
# ["input_R1.fasta-part-3", "input_R2.fasta-part-3"],...]
input_chunks = [list(part) for part in zip(*part_lists)]
return part_suffix, input_chunks
@staticmethod
@staticmethod
@staticmethod
def run_chunk(self, part_suffix, input_files, lazy_run):
"""
Dispatch a chunk to worker machines for distributed GSNAP or RAPSearch
group machines and handle their execution.
"""
chunk_id = int(input_files[0].split(part_suffix)[-1])
multihit_basename = f"multihit-{self.alignment_algorithm}-out{part_suffix}{chunk_id}.m8"
multihit_local_outfile = os.path.join(self.chunks_result_dir_local, multihit_basename)
multihit_s3_outfile = os.path.join(self.chunks_result_dir_s3, multihit_basename)
session = boto3.session.Session()
if lazy_run and download_from_s3(session, multihit_s3_outfile, multihit_local_outfile):
log.write(f"finished alignment for chunk {chunk_id} with {self.alignment_algorithm} by lazily fetching last result")
return multihit_local_outfile
deployment_environment = os.environ["DEPLOYMENT_ENVIRONMENT"]
priority_name = os.environ.get("PRIORITY_NAME", "normal")
index_dir_suffix = self.additional_attributes["index_dir_suffix"]
pattern = r's3://.+/samples/([0-9]+)/([0-9]+)/'
m = re.match(pattern, self.chunks_result_dir_s3)
if m:
project_id, sample_id = m.group(1), m.group(2)
else:
project_id, sample_id = '0', '0'
provisioning_model = 'SPOT'
# TODO: parameterize these https://jira.czi.team/browse/IDSEQ-2673
job_name = f"idseq-{deployment_environment}-{self.alignment_algorithm}-project-{project_id}-sample-{sample_id}-part-{chunk_id}"
job_queue = f"idseq-{deployment_environment}-{self.alignment_algorithm}-{provisioning_model}-{index_dir_suffix}-{priority_name}"
job_definition = f"idseq-{deployment_environment}-{self.alignment_algorithm}"
environment = [{
'name': f"INPUT_PATH_{i}",
'value': os.path.join(self.chunks_result_dir_s3, input_file),
} for i, input_file in enumerate(input_files)] + [{
'name': "OUTPUT_PATH",
'value': multihit_s3_outfile,
}]
input_paths = [f"local_input_{i}" for i, _ in enumerate(input_files)]
command = self._get_command("/references/reference", input_paths, "local_output")
try:
job_id = self._run_batch_job(
session=session,
job_name=job_name,
job_queue=job_queue,
job_definition=job_definition,
command=command,
environment=environment,
chunk_id=chunk_id,
retries=2
)
except BatchJobFailed:
provisioning_model = 'EC2'
# TODO: parameterize this https://jira.czi.team/browse/IDSEQ-2673
job_queue = f"idseq-{deployment_environment}-{self.alignment_algorithm}-{provisioning_model}-{index_dir_suffix}-{priority_name}"
job_id = self._run_batch_job(
session=session,
job_name=job_name,
job_queue=job_queue,
job_definition=job_definition,
command=command,
environment=environment,
chunk_id=chunk_id,
retries=1
)
for _ in range(12):
if download_from_s3(session, multihit_s3_outfile, multihit_local_outfile):
break
time.sleep(10)
else:
log.log_event("chunk_result_missing_in_s3", values={
'job_id': job_id,
'chunk_id': chunk_id,
'job_queue': job_queue,
'job_definition': job_definition,
'alignment_algorithm': self.alignment_algorithm,
})
raise Exception("Chunk result is missing from s3")
log.log_event("alignment_batch_chunk_result_downloaded", values={
'job_id': job_id,
'chunk_id': chunk_id,
'job_queue': job_queue,
'job_definition': job_definition,
'alignment_algorithm': self.alignment_algorithm,
})
self._validate_chunk_output(multihit_local_outfile)
return multihit_local_outfile
|
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3141,
13,
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62,
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62,
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7,
198,
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220,
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220,
220,
220,
220,
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220,
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3141,
62,
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82,
13,
28008,
21575,
7,
198,
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220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
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23991,
2625,
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198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
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26498,
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198,
220,
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220,
220,
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366,
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12,
12860,
12,
48277,
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198,
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220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
28686,
13,
6978,
13,
22179,
7,
944,
13,
354,
14125,
62,
20274,
62,
15908,
62,
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11,
366,
12340,
198,
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220,
220,
220,
220,
220,
220,
220,
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220,
220,
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220,
220,
220,
220,
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220,
220,
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28686,
13,
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62,
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62,
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503,
62,
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62,
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9,
1,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
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2361,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
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1267,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
3497,
262,
13027,
2393,
3891,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
13027,
62,
16624,
796,
17635,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
13532,
796,
3141,
13,
4743,
672,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
15095,
62,
33279,
28,
448,
62,
40290,
1343,
366,
9,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
10283,
62,
43551,
62,
14933,
28,
17821,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
13027,
62,
16624,
13,
2302,
437,
7,
6978,
82,
8,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
6822,
326,
262,
13027,
3696,
2872,
674,
2938,
16058,
278,
3912,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3912,
796,
45144,
25,
15,
4,
1860,
36786,
4064,
299,
12894,
896,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2938,
62,
47172,
62,
16624,
796,
47527,
448,
62,
40290,
62,
8692,
1343,
3912,
13,
18982,
7,
72,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
1312,
287,
2837,
7,
77,
931,
5889,
15437,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
31456,
796,
366,
18927,
1816,
2642,
351,
16058,
278,
25,
23884,
14512,
23884,
1911,
18982,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
13027,
62,
16624,
11,
2938,
62,
47172,
62,
16624,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
6818,
2938,
62,
47172,
62,
16624,
6624,
13027,
62,
16624,
11,
31456,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
636,
62,
20713,
13,
33295,
7,
47172,
62,
16624,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
1475,
25,
685,
14692,
15414,
62,
49,
16,
13,
7217,
64,
12,
3911,
12,
16,
1600,
366,
15414,
62,
49,
17,
13,
7217,
64,
12,
3911,
12,
16,
33116,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
14631,
15414,
62,
49,
16,
13,
7217,
64,
12,
3911,
12,
17,
1600,
366,
15414,
62,
49,
17,
13,
7217,
64,
12,
3911,
12,
17,
33116,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
14631,
15414,
62,
49,
16,
13,
7217,
64,
12,
3911,
12,
18,
1600,
366,
15414,
62,
49,
17,
13,
7217,
64,
12,
3911,
12,
18,
33116,
22345,
198,
220,
220,
220,
220,
220,
220,
220,
5128,
62,
354,
14125,
796,
685,
4868,
7,
3911,
8,
329,
636,
287,
19974,
46491,
3911,
62,
20713,
15437,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
636,
62,
37333,
844,
11,
5128,
62,
354,
14125,
628,
220,
220,
220,
2488,
12708,
24396,
628,
220,
220,
220,
2488,
12708,
24396,
628,
220,
220,
220,
2488,
12708,
24396,
628,
220,
220,
220,
825,
1057,
62,
354,
2954,
7,
944,
11,
636,
62,
37333,
844,
11,
5128,
62,
16624,
11,
16931,
62,
5143,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
35934,
257,
16058,
284,
8383,
8217,
329,
9387,
402,
15571,
2969,
393,
371,
2969,
18243,
198,
220,
220,
220,
220,
220,
220,
220,
1448,
8217,
290,
5412,
511,
9706,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
628,
220,
220,
220,
220,
220,
220,
220,
16058,
62,
312,
796,
493,
7,
15414,
62,
16624,
58,
15,
4083,
35312,
7,
3911,
62,
37333,
844,
38381,
12,
16,
12962,
198,
220,
220,
220,
220,
220,
220,
220,
1963,
4449,
270,
62,
12093,
12453,
796,
277,
1,
16680,
4449,
270,
12,
90,
944,
13,
282,
16747,
62,
282,
42289,
92,
12,
448,
90,
3911,
62,
37333,
844,
18477,
354,
2954,
62,
312,
27422,
76,
23,
1,
198,
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220,
220,
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1963,
4449,
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62,
12001,
62,
448,
7753,
796,
28686,
13,
6978,
13,
22179,
7,
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13,
354,
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62,
20274,
62,
15908,
62,
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11,
1963,
4449,
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62,
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8,
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1963,
4449,
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18,
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22179,
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62,
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62,
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18,
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1963,
4449,
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62,
12093,
12453,
8,
628,
220,
220,
220,
220,
220,
220,
220,
6246,
796,
275,
2069,
18,
13,
29891,
13,
36044,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
611,
16931,
62,
5143,
290,
4321,
62,
6738,
62,
82,
18,
7,
29891,
11,
1963,
4449,
270,
62,
82,
18,
62,
448,
7753,
11,
1963,
4449,
270,
62,
12001,
62,
448,
7753,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2604,
13,
13564,
7,
69,
1,
43952,
19114,
329,
16058,
1391,
354,
2954,
62,
312,
92,
351,
1391,
944,
13,
282,
16747,
62,
282,
42289,
92,
416,
37296,
813,
21207,
278,
938,
1255,
4943,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
1963,
4449,
270,
62,
12001,
62,
448,
7753,
628,
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] | 2.044452 | 6,209 |
import torch
import torch.nn as nn
import torch.jit as jit
from typing import Any
from typing import List
from typing import Tuple
from typing import Optional
from collections import namedtuple
state_type = Tuple[torch.Tensor, torch.Tensor]
return_type = Tuple[torch.Tensor, Tuple[torch.Tensor, torch.Tensor]]
LSTMState = namedtuple("LSTMState", ["hx", "cx"])
__all__ = [
"LSTM",
]
|
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] | 2.794326 | 141 |
import requests
from bs4 import BeautifulSoup
from _datetime import date
import progressbar
import time
import os
import pandas as pd
#check if a value is empty
#if it is we return 0.0
if __name__ == "__main__":
wrapper = WNBAWrapper()
wrapper.getBoxScore()
|
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50,
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198,
6738,
4808,
19608,
8079,
1330,
3128,
198,
11748,
4371,
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198,
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640,
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19798,
292,
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279,
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9122,
611,
257,
1988,
318,
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198,
220,
220,
220,
1303,
361,
340,
318,
356,
1441,
657,
13,
15,
198,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
220,
220,
220,
29908,
796,
370,
32470,
36918,
2848,
3419,
198,
220,
220,
220,
29908,
13,
1136,
14253,
26595,
3419
] | 2.98913 | 92 |
#!/usr/bin/env python
from subprocess import Popen, PIPE
import sys
import argparse
parser = argparse.ArgumentParser(description='Ping Scan Network')
# Main arguments
parser.add_argument("-network", dest="network", help="NetWork segment[For example 192.168.56]", required=True)
parser.add_argument("-machines", dest="machines", help="Machines number",type=int, required=True)
parsed_args = parser.parse_args()
for ip in range(1,parsed_args.machines+1):
ipAddress = parsed_args.network +'.' + str(ip)
print "Scanning %s " %(ipAddress)
if sys.platform.startswith('linux'):
# Linux
subprocess = Popen(['/bin/ping', '-c 1 ', ipAddress], stdin=PIPE, stdout=PIPE, stderr=PIPE)
elif sys.platform.startswith('win'):
# Windows
subprocess = Popen(['ping', ipAddress], stdin=PIPE, stdout=PIPE, stderr=PIPE)
stdout, stderr= subprocess.communicate(input=None)
print stdout
if "Lost = 0" in stdout or "bytes from " in stdout:
print "The Ip Address %s has responded with a ECHO_REPLY!" %(stdout.split()[1])
|
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2,
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] | 2.628205 | 390 |
from django.db import models
from django.utils import timezone
# Create your models here.
|
[
6738,
42625,
14208,
13,
9945,
1330,
4981,
198,
6738,
42625,
14208,
13,
26791,
1330,
640,
11340,
198,
198,
2,
13610,
534,
4981,
994,
13
] | 3.75 | 24 |
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.common.keys import Keys
from selenium.common.exceptions import ElementNotInteractableException, NoSuchElementException
import csv
import time
WPP_URL = "https://web.whatsapp.com/"
def le_arquivo(nome_arquivo):
'''
Função que lê o arquivo e retorna seu conteúdo na estrutura de dados adequada
Parâmetro:
nome_arquivo : str
Retorna: list | None
'''
if nome_arquivo == "contatos":
contatos = list()
with open(f"{nome_arquivo}.txt", "r") as f:
contatos = f.read().rstrip().splitlines()
return contatos
elif nome_arquivo == "mensagem":
mensagem = str()
with open(f"{nome_arquivo}.txt", "r") as f:
mensagem = f.read().rstrip().splitlines()
return mensagem
else:
return None
def iniciar_driver(path):
'''
Inicia o ChromeDriver, abre o navegador e retorna uma instância do
ChromeDriver.
Parâmetro:
path : str
'''
driver = webdriver.Chrome(path)
driver.get(WPP_URL)
return driver
def no_remember_me(driver):
'''
Aperta o botão de "rememberMe" para evitar o log-in a longo prazo
Parâmetro: WebDriver object
'''
botao = driver.find_element(By.NAME, "rememberMe")
botao.click()
def barra_de_pesquisa(contato, driver):
'''
Acha a caixa de texto para pesquisar o contato ou nome do grupo e o pesquisa
Parâmetros:
contato : str
driver : WebDriver object
'''
try:
campo_pesquisa = driver.find_element_by_xpath("//div[contains(@class, 'copyable-text selectable-text')]")
campo_pesquisa.click()
campo_pesquisa.send_keys(contato)
campo_pesquisa.send_keys(Keys.ENTER)
except NoSuchElementException:
driver.quit()
def envia_mensagem(mensagem, driver):
'''
Envia a mensagem ao contato
Parâmetros:
mensagem : list
driver : WebDriver object
'''
try:
campo_mensagem = driver.find_elements_by_xpath("//div[contains(@class, 'copyable-text selectable-text')]")
campo_mensagem[1].click()
for linha in mensagem:
campo_mensagem[1].send_keys(linha)
campo_mensagem[1].send_keys(Keys.SHIFT, Keys.ENTER)
campo_mensagem[1].send_keys(Keys.ENTER)
except NoSuchElementException:
return
def informacoes_do_grupo(driver, grupo):
'''
Devolve as informações sobre um certo grupo, como nome, descrição
e membros do grupo em um arquivo .csv
Parâmetros:
driver : Webdriver object
grupo : str
'''
# pesquisa o grupo
barra_de_pesquisa(grupo, driver)
barra_nome_do_grupo = driver.find_element_by_xpath("//div[contains(@class, '_2uaUb')]")
barra_nome_do_grupo.click()
# nome completo do grupo
header = ["Nome Grupo", "Descrição"]
nome_grupo = driver.find_element_by_xpath("//div[contains(@class, '_2_1wd')]").get_attribute("textContent")
escreve_arquivo_csv(nome_grupo, header)
try:
# clica botão de mostrar mais
botao_ver_mais = driver.find_element_by_xpath("//span[@class='_1oQqb' and @role='button']")
botao_ver_mais.click()
except ElementNotInteractableException:
pass
finally:
descricao = driver.find_element_by_xpath("//span[contains(@class, '_3-8er')]").get_attribute("textContent")
escreve_arquivo_csv(nome_grupo, [nome_grupo, descricao])
membros = driver.find_element_by_xpath("//span[@class='_7yrSq _3-8er selectable-text copyable-text']")
membros = membros.get_attribute("textContent")
membros = membros.split(", ")
for membro in membros:
escreve_arquivo_csv(nome_grupo, [membro])
|
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] | 2.187355 | 1,724 |
import cv2
import numpy as np
import os
import math
from utils import *
## ADD 'Frames' folder to file path before running code.
if __name__ == "__main__":
main()
|
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] | 3.017544 | 57 |
"""
671
easy
second minimum node in a binary tree
"""
# Definition for a binary tree node.
|
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] | 3.464286 | 28 |
from multiprocessing import Process
from core.himesis_utils import expand_graph
from copy import deepcopy
|
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#!/usr/bin/env python3
################################################################################
# This script will run the Arrythmia Web App from the command line. This
# script should be used for developing builds only.
################################################################################
import subprocess as sp
import os
import sys
def run_backend(current_dir, backend_source):
"""
run_backend runs the backend source code, will return to original directory
:param current_dir: current directory
:type current_dir: str
:param backend_source: directory location of the backend source code
:type backend_source: str
:return: the process instance of the backend
:rtype: Popen object
"""
os.chdir(backend_source)
process = sp.Popen(["python3", "manage.py", "runserver"], stdout=sp.PIPE)
os.chdir(current_dir)
return process
def run_frontend(current_dir, frontend_source):
"""
run_frontend runs the frontend source code, will return to original
directory
:param current_dir: current directory
:type current_dir: str
:param frontend_source: directory location of the frontend source code
:type frontend_source: str
:return: the process instance of the frontend
:rtype: Popen object
"""
os.chdir(frontend_source)
process = None
if not os.path.isdir("node_modules"):
process = sp.Popen(["npm", "install"])
process.wait()
process = sp.Popen(["npm", "start"], stdout=sp.PIPE)
os.chdir(current_dir)
return process
if __name__ == "__main__":
print("This script will start the Arrythmia web application.")
# Get directories
original_dir = os.getcwd()
frontend_start = str(original_dir) + "/frontend"
backend_start = str(original_dir) + "/backend"
# Keep track of all subprocesses (the backend and frontend)
subprocesses = []
try:
# Run the backend and frontend
subprocesses.append(run_backend(original_dir, backend_start))
subprocesses.append(run_frontend(original_dir, frontend_start))
exit_codes = [p.wait() for p in subprocesses]
except OSError:
# An error popped up for one of the processes, terminate everything
[p.terminate() for p in subprocesses]
print("OSError Error happened!")
sys.exit()
except KeyboardInterrupt:
# Python script is forcefully closed, terminate all processes
[p.terminate() for p in subprocesses]
print("KeyboardInterrupt Error happened!")
sys.exit()
except:
# An error popped up, terminate everything
[p.terminate() for p in subprocesses]
print("Error happened!")
sys.exit()
|
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] | 2.887712 | 944 |
# Regression analysis using scikit-learn functions
# Common imports
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import sklearn.linear_model as skl
from sklearn.model_selection import train_test_split
from sklearn.metrics import mean_squared_error, r2_score, mean_absolute_error
import os
# Where to save the figures and data files
PROJECT_ROOT_DIR = "Results"
FIGURE_ID = "Results/FigureFiles"
DATA_ID = "DataFiles/"
if not os.path.exists(PROJECT_ROOT_DIR):
os.mkdir(PROJECT_ROOT_DIR)
if not os.path.exists(FIGURE_ID):
os.makedirs(FIGURE_ID)
if not os.path.exists(DATA_ID):
os.makedirs(DATA_ID)
infile = open(data_path("MassEval2016.dat"),'r')
# Read the experimental data with Pandas
Masses = pd.read_fwf(infile, usecols=(2,3,4,6,11),
names=('N', 'Z', 'A', 'Element', 'Ebinding'),
widths=(1,3,5,5,5,1,3,4,1,13,11,11,9,1,2,11,9,1,3,1,12,11,1),
header=39,
index_col=False)
# Extrapolated values are indicated by '#' in place of the decimal place, so
# the Ebinding column won't be numeric. Coerce to float and drop these entries.
Masses['Ebinding'] = pd.to_numeric(Masses['Ebinding'], errors='coerce')
Masses = Masses.dropna()
# Convert from keV to MeV.
Masses['Ebinding'] /= 1000
# Group the DataFrame by nucleon number, A.
Masses = Masses.groupby('A')
# Find the rows of the grouped DataFrame with the maximum binding energy.
Masses = Masses.apply(lambda t: t[t.Ebinding==t.Ebinding.max()])
A = Masses['A']
Z = Masses['Z']
N = Masses['N']
Element = Masses['Element']
Energies = Masses['Ebinding']
# Now we set up the design matrix X
X = np.zeros((5,len(A)))
X[4,:] = A**(-1.0)
X[3,:] = A**(-1.0/3.0)
X[2,:] = A**(2.0/3.0)
X[1,:] = A
X[0,:] = 1
X_train = X.T
Y_train = Energies
n_hidden_neurons = 100
epochs = 100
from sklearn.neural_network import MLPRegressor
from sklearn.metrics import accuracy_score
# store models for later use
eta_vals = np.logspace(-5, 1, 7)
lmbd_vals = np.logspace(-5, 1, 7)
# store the models for later use
DNN_scikit = np.zeros((len(eta_vals), len(lmbd_vals)), dtype=object)
train_accuracy = np.zeros((len(eta_vals), len(lmbd_vals)))
import seaborn as sns
sns.set()
for i, eta in enumerate(eta_vals):
for j, lmbd in enumerate(lmbd_vals):
dnn = MLPRegressor(hidden_layer_sizes=(n_hidden_neurons), activation='logistic',
alpha=lmbd, learning_rate_init=eta, max_iter=epochs)
dnn.fit(X_train, Y_train)
DNN_scikit[i][j] = dnn
train_accuracy[i][j] = dnn.score(X_train, Y_train)
fig, ax = plt.subplots(figsize = (10, 10))
sns.heatmap(train_accuracy, annot=True, ax=ax, cmap="viridis")
ax.set_title("Training Accuracy")
ax.set_ylabel("$\eta$")
ax.set_xlabel("$\lambda$")
plt.show()
|
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] | 2.333894 | 1,189 |
# -*- coding: utf-8 -*-
# 句向量训练者称为出题者assitant，标签训练者称为student
import getData
from keras.models import Sequential
from keras.layers import LSTM, Dense, Dropout
from gensim.models import Word2Vec
import numpy as np
from keras import metrics
dim_num_feature = 120
# 用于限制长度
w2v_model = Word2Vec.load("./data/120features_20minwords_10context")
train_comments, train_labels = getData.getAllData(
"./data/webshell.json", "./data/normal.json")
count_list = []
commentVec_list = []
n = 30
j = 0
for comment in train_comments:
if(j % 100 == 0):
print("%d of %d total" % (j, len(train_comments)))
count_list.append(len(comment))
comment_vec = sen2Vec(magicFit(comment, n), w2v_model)
commentVec_list.append(comment_vec)
j += 1
commentVec_list = np.array(commentVec_list)
train_labels = np.array(train_labels)
indices = np.arange(commentVec_list.shape[0])
np.random.shuffle(indices)
data = commentVec_list[indices]
labels = train_labels[indices]
VALID_SAMPLE_SPLIT = 0.1
nb_vali_samples = int(VALID_SAMPLE_SPLIT * data.shape[0])
x_train = data[:-nb_vali_samples]
y_train = labels[:-nb_vali_samples]
print(x_train.shape[0], x_train.shape[1], x_train.shape[2])
y_train = getData.getOneHot(y_train)
x_val = data[-nb_vali_samples:]
y_val = labels[-nb_vali_samples:]
y_val = getData.getOneHot(y_val)
'''-----------Train Model-------------'''
assistant = Sequential()
assistant.add(LSTM(128, activation='tanh', input_shape=(
x_train.shape[1], x_train.shape[2])))
assistant.add(Dropout(0.2))
assistant.add(Dense(2, activation='softmax'))
assistant.compile(loss='categorical_crossentropy',
optimizer='adam',
metrics=['accuracy', "mae"])
assistant.summary()
assistant.fit(x_train, y_train, validation_data=(x_val, y_val),
epochs=12, batch_size=128)
#pickle_file = open('LSTM_webshell_20.model.pik','wb')
# pickle.dump(assistant,pickle_file)
# pickle_file.close()
|
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] | 2.125131 | 951 |
"""Provides methods for text cleanup."""
|
[
37811,
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1460,
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329,
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27425,
526,
15931,
198
] | 4.1 | 10 |
import logging
from contextlib import suppress
from datetime import datetime
from typing_extensions import Self
from ._util import _regex_it
from .api import _APIClient
from .base import ClubObject
from .config import get_from_cache, set_in_cache
from .constants import _TMIO
from .errors import TMIOException
from .player import Player
_log = logging.getLogger(__name__)
__all__ = (
"ClubMember",
"ClubActivity",
"Club",
)
class ClubMember(ClubObject):
"""
.. versionadded :: 0.5
Represents a member of a club.
Parameters
----------
name : str
The name of the player.
tag : str | None
The club tab of the player.
player_id : str
The ID of the player.
join_time : datetime
When the player joined the club.
role : str
The role of the player inside the club
vip : bool
Whether the player is a VIP.
"""
@classmethod
async def player(self) -> Player:
"""
.. versionadded :: 0.5
Gets the player who is this specific club member.
(IDK wtf to put here xD)
Returns
-------
:class:`Player`
The player who is the club member.
Raises
------
:class:`TMIOException`
If there is a problem with the TMIO API.
"""
return await Player.get_player(self.player_id)
class ClubActivity(ClubObject):
"""
.. versionadded :: 0.5
Represents an activity of the club.
Parameters
----------
name : str
The name of the activity.
type : str
What type of activity it is.
activity_id : int
The activity's ID.
target_activity_id : int
The activity's target ID.
position : int
The position of the activity within the club.
public : bool
Whether the activity is public or club-member only.
media : str
The media of the activity.
password : bool
Whether the activity is password-protected.
"""
@classmethod
class Club(ClubObject):
"""
Represents a Club in Trackmania 2020.
Parameters
----------
background : str
The club's background url.
created_at : datetime
The club's created date.
decal : str
The club decal URL
description : str
The club's description
featured : bool
Whether the club is featured or not.
club_id : int
The club's ID.
logo : str
The club's logo URL.
member_count : int
The club's member count.
name : str
The club's name.
popularity : int
The club popularity level
state : str
The club's state.
Is either Private or Public.
tag : str
The club tag
"""
@classmethod
@classmethod
async def get_club(cls: Self, club_id: int) -> Self | None:
"""
.. versionadded :: 0.5
Gets a club based on its club id.
Returns None if the `club_id` is 0
Parameters
----------
club_id : int
The club's id.
Returns
-------
:class:`Club` | None
Returns a `Club` class if a club exists with the given class id. Otherwise returns None.
Raises
------
:class:`TMIOException`
If the club doesn't exist or if an unexpected error occurs on TMIO's side.
"""
if club_id == 0:
return None
club_data = get_from_cache(f"club:{club_id}")
if club_data is not None:
return cls._from_dict(club_data)
api_client = _APIClient()
club_data = await api_client.get(_TMIO.build([_TMIO.TABS.CLUB, club_id]))
await api_client.close()
with suppress(KeyError, TypeError):
raise TMIOException(club_data["error"])
return cls._from_dict(club_data)
@classmethod
async def list_clubs(cls: Self, page: int = 0) -> list[Self]:
"""
.. versionadded :: 0.5
Lists all the popular clubs.
Parameters
----------
page : int, optional
The page bumber, by default 0
Returns
-------
:class:`list[Club]`
The list of clubs on that specific page.
"""
clubs = []
club_data = get_from_cache(f"clubs:{page}")
if club_data is not None:
for club in club_data.get("clubs", []):
clubs.append(cls._from_dict(club))
return clubs
api_client = _APIClient()
club_data = await api_client.get(
_TMIO.build([_TMIO.TABS.CLUBS, page]) + "?sort=popularity"
)
await api_client.close()
set_in_cache(f"clubs:{page}", club_data, ex=43200)
for club in club_data.get("clubs", []):
clubs.append(cls._from_dict(club))
return clubs
async def get_activities(self: Self, page: int = 0) -> list[ClubActivity]:
"""
.. versionadded :: 0.5
Gets the activities of the club.
Parameters
----------
page : int
The page number, by default 0
Returns
-------
:class:`list[ClubActivity]`
The list of activities of the club.
"""
club_activities = []
all_activities = get_from_cache(f"club_activities:{self.club_id}:{page}")
if all_activities is not None:
for activity in all_activities:
club_activities.append(ClubActivity._from_dict(activity))
return club_activities
api_client = _APIClient()
all_activities = await api_client.get(
_TMIO.build([_TMIO.TABS.CLUB, self.club_id, _TMIO.TABS.ACTIVITIES, page])
)
await api_client.close()
with suppress(KeyError, TypeError):
raise TMIOException(all_activities["error"])
for activity in all_activities.get("activities", []):
club_activities.append(ClubActivity._from_dict(activity))
return club_activities
async def get_members(self: Self, page: int = 0) -> list[ClubMember]:
"""
.. versionadded :: 0.5
Gets the members of the club.
Parameters
----------
page : int, optional
The page number, by default 0
Returns
-------
:class:`list[Player]`
The list of members of the club.
"""
player_list = []
club_members = get_from_cache(f"club_members:{self.club_id}:{page}")
if club_members is not None:
for member in club_members.get("members", []):
player_list.append(ClubMember._from_dict(member))
return player_list
api_client = _APIClient()
club_members = await api_client.get(
_TMIO.build([_TMIO.TABS.CLUB, self.club_id, _TMIO.TABS.MEMBERS, page])
)
await api_client.close()
for member in club_members.get("members", []):
player_list.append(ClubMember._from_dict(member))
return player_list
async def creator(self) -> Player:
"""
.. versionadded :: 0.5
Gets the creator of the club.
Returns
-------
:class:`Player`
The creator of the club.
"""
return await Player.get_player(self.creator_id)
|
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37227,
198,
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220,
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11485,
2196,
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657,
13,
20,
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220,
220,
220,
220,
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29620,
262,
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286,
262,
3430,
13,
628,
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220,
220,
220,
220,
220,
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16409,
198,
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220,
220,
220,
220,
220,
220,
35656,
198,
220,
220,
220,
220,
220,
220,
220,
1058,
4871,
25,
63,
14140,
63,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
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383,
13172,
286,
262,
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37227,
198,
220,
220,
220,
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220,
220,
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1441,
25507,
7853,
13,
1136,
62,
7829,
7,
944,
13,
45382,
62,
312,
8,
198
] | 2.252206 | 3,287 |
import os
import json
import torch
import numpy as np
from model import VAENAR, ScheduledOptim
|
[
11748,
28686,
198,
11748,
33918,
198,
198,
11748,
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11748,
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13753,
1677,
1503,
11,
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6309,
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320,
628,
628,
198
] | 3.258065 | 31 |
from twisted.application import internet, service
from twisted.internet import reactor
from txtrader.tcpserver import serverFactory
from txtrader.webserver import webServerFactory
from txtrader.rtx import RTX
if __name__ == '__main__':
main()
|
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6738,
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] | 3.36 | 75 |
from collections import namedtuple
from requests.structures import CaseInsensitiveDict
from boltons.typeutils import make_sentinel
class ReadOnlyContainer(object):
"""
Base class for read-only property containers.
"""
def __init__(self, **fields):
"""
Initialize the property container from the given field-value pairs.
:param fields: container field-value pairs as keyworded arguments.
"""
self._factory = namedtuple(
typename='read_only_container',
field_names=fields.keys()
)
self._container = self._factory(**fields)
|
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1267,
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2116,
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34924,
796,
2116,
13557,
69,
9548,
7,
1174,
25747,
8,
628,
198
] | 2.740088 | 227 |
import csv, datetime
with open('tooldesc.csv') as td:
rdr = csv.reader(td)
items = list(rdr)
items = [convertDate(item) for item in items]
with open('tooldesc2.csv', 'w', newline='') as td:
wrt = csv.writer(td)
for item in items:
wrt.writerow(item)
|
[
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220,
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1319,
83,
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322,
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] | 2.225806 | 124 |
"""
将mask rcnn转成shapefile的一些函数
"""
from osgeo import ogr, gdal, osr
import cv2
import numpy as np
def create_geom():
"""用于测试，生成一个wkt"""
multipolygon = ogr.Geometry(ogr.wkbMultiPolygon)
polygon = ogr.Geometry(ogr.wkbPolygon)
ring = ogr.Geometry(ogr.wkbLinearRing)
ring.AddPoint(1179091.1646903288, 712782.8838459781)
ring.AddPoint(1161053.0218226474, 667456.2684348812)
ring.AddPoint(1218405.0658121984, 721108.1805541387)
ring.AddPoint(1179091.1646903288, 712782.8838459781)
polygon.AddGeometry(ring)
multipolygon.AddGeometry(polygon)
polygon1 = ogr.Geometry(ogr.wkbPolygon)
ring1 = ogr.Geometry(ogr.wkbLinearRing)
ring1.AddPoint(1214704.933941905, 641092.8288590391)
ring1.AddPoint(1228580.428455506, 682719.3123998424)
ring1.AddPoint(1218405.0658121984, 721108.1805541387)
ring1.AddPoint(1214704.933941905, 641092.8288590391)
polygon1.AddGeometry(ring1)
multipolygon.AddGeometry(polygon1)
return multipolygon
def reference_of_tiff(input_tiff_path):
"""
获取给定tiff图像的地理坐标系和投影坐标系
:param input_tiff_path: tiff图像的路径
:return: 投影坐标系，地理坐标系
"""
tiff_data = gdal.Open(input_tiff_path)
prosrs = osr.SpatialReference()
prosrs.ImportFromWkt(tiff_data.GetProjection())
geosrs = prosrs.CloneGeogCS()
return prosrs, geosrs
def convert_geom_to_shp(input_geo, outputfile_name='untitled.shp', geo_type='multipolygon', spatialref=None):
"""
仅支持multipolygon类型转shapefile
:param spatialref: 空间参考坐标系，osr.SpatialReference()类型
:param outputfile_name: 输出文件的名字
:param input_geo: wkt格式的polygon
:return:
"""
if spatialref is None:
spatialref = osr.SpatialReference()
spatialref.ImportFromEPSG(4326)
gdal.SetConfigOption("GDAL_FILENAME_IS_UTF8", "YES")
gdal.SetConfigOption("SHAPE_ENCODING", "GBK")
driver = ogr.GetDriverByName("ESRI Shapefile")
if geo_type == 'multipolygon':
geometry_count = input_geo.GetGeometryCount()
output_shpfile = driver.CreateDataSource(outputfile_name)
dstlayer = output_shpfile.CreateLayer("layer", spatialref, geom_type=ogr.wkbMultiPolygon)
for i in range(geometry_count):
polygon = input_geo.GetGeometryRef(i)
feature = ogr.Feature(dstlayer.GetLayerDefn())
feature.SetGeometry(polygon)
dstlayer.CreateFeature(feature)
# feature.Destroy()
# output_shpfile.Destroy()
def convert_xy_from_img_to_geo(x, y, reference=None):
"""
将图上坐标转成地理坐标或者投影坐标
:param x: 计算机中的x,应该是列
:param y: 计算机中的y，应该是行
:param reference: GDAL的六参数，可以通过dataset.GetGeoTransform()获取，
这里的dataset = gdal.Open(file_name) file_name表示tif格式图片的路径，带坐标的tiff格式
:return:
"""
row = y
col = x
px = reference[0] + col * reference[1] + row * reference[2]
py = reference[3] + col * reference[4] + row * reference[5]
return px, py
"""if __name__ == '__main__':
poly = create_geom()
print(poly.ExportToWkt())
print(poly.GetGeometryCount())
print(poly.GetGeometryRef(1))
tiff_path = 'D:/codes/python/RS_Test/test.tif'
prosrs, geosrs = reference_of_tiff(tiff_path)
convert_geom_to_shp(poly, spatialref=geosrs)
"""
|
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] | 1.885781 | 1,716 |
from paypalrestsdk import WebhookEvent
import logging
logging.basicConfig(level=logging.INFO)
webhook_event = WebhookEvent.find("8PT597110X687430LKGECATA")
if webhook_event.resend(): # return True or False
print("webhook event[%s] resend successfully" % (webhook_event.id))
else:
print(webhook_event.error)
|
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] | 2.765217 | 115 |
#!/usr/bin/env python
# coding=utf-8
try:
import mock
except ImportError:
import unittest.mock as mock
from marvin_product_classifier_engine.data_handler import AcquisitorAndCleaner
import pandas as pd
@mock.patch('marvin_product_classifier_engine.data_handler.acquisitor_and_cleaner.pd.read_csv')
@mock.patch('marvin_product_classifier_engine.data_handler.acquisitor_and_cleaner.MarvinData.download_file')
|
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"""TcEx Service Common Module"""
# standard library
import base64
import json
import os
import subprocess
import sys
import time
import uuid
from multiprocessing import Process
from random import randint
from threading import Event, Lock, Thread
from typing import Any, Optional
from ..services import MqttMessageBroker
from .test_case_playbook_common import TestCasePlaybookCommon
class TestCaseServiceCommon(TestCasePlaybookCommon):
"""Service App TestCase Class"""
_mqtt_client = None
_message_broker = None
app_process = None
client_topic = f'client-topic-{randint(100, 999)}'
lock = Lock() # lock for subscription management
server_topic = f'server-topic-{randint(100, 999)}'
service_ready = Event()
service_run_method = 'subprocess' # run service as subprocess, multiprocess, or thread
shutdown = False
shutdown_complete = False
sleep_after_publish_config = 0.5
sleep_after_publish_webhook_event = 0.5
sleep_after_service_start = 5
sleep_before_delete_config = 2
sleep_before_shutdown = 0.5
subscriptions = {} # dictionary of events, posted to by MID by on_subscribe
trigger_requests = {}
trigger_responses = {}
def _app_callback(self, app):
"""Set app object from run.py callback"""
self.app = app
@property
def default_args(self):
"""Return App default args."""
args = super().default_args.copy()
args.update(
{
'tc_svc_broker_host': os.getenv('TC_SVC_BROKER_HOST', 'localhost'),
'tc_svc_broker_port': int(os.getenv('TC_SVC_BROKER_PORT', '1883')),
'tc_svc_broker_service': os.getenv('TC_SVC_BROKER_SERVICE', 'mqtt'),
'tc_svc_broker_conn_timeout': int(os.getenv('TC_SVC_BROKER_CONN_TIMEOUT', '15')),
'tc_svc_broker_token': os.getenv('TC_SVC_BROKER_TOKEN'),
'tc_svc_client_topic': self.client_topic,
'tc_svc_server_topic': self.server_topic,
'tc_svc_hb_timeout_seconds': int(os.getenv('TC_SVC_HB_TIMEOUT_SECONDS', '300')),
}
)
return args
@property
def message_broker(self):
"""Return an instance of MqttMessageBroker."""
if self._message_broker is None:
self._message_broker = MqttMessageBroker(
broker_host=self.default_args.get('tc_svc_broker_host'),
broker_port=self.default_args.get('tc_svc_broker_port'),
broker_timeout=self.default_args.get('tc_svc_broker_conn_timeout'),
logger=self.log,
)
self._message_broker.register_callbacks()
return self._message_broker
@property
def mqtt_client(self):
"""Return a mqtt client instance."""
return self.message_broker.client
def on_message(self, client, userdata, message): # pylint: disable=unused-argument
"""Handle message broker on_message shutdown command events."""
try:
m = json.loads(message.payload)
except ValueError:
raise RuntimeError(f'Could not parse API service response JSON. ({message})')
command = m.get('command').lower()
if command == 'ready':
self.service_ready.set()
trigger_id = str(m.get('triggerId'))
cmd_type = m.get('type', command).lower()
key = f'{trigger_id}-{cmd_type}'
if key in self.trigger_responses:
self.log.warning(f'Additional response arrived for trigger {key} -- discarded')
else:
self.trigger_responses[key] = m
if self.trigger_requests.get(key) is not None:
self.trigger_requests.pop(key).set()
# pylint: disable=unused-argument
def on_subscribe(self, client, userdata, mid, granted_qos):
"""Handle on subscribe callback after subscription completes"""
with self.lock:
event = self.subscriptions.pop(mid)
if event:
event.set()
def publish(self, message: str, topic: Optional[str] = None):
"""Publish message on server channel.
Args:
message: The message to send.
topic: The message broker topic. Defaults to None.
"""
self.message_broker.publish(message, topic)
def publish_create_config(self, message: dict) -> dict:
"""Send create config message.
Args:
trigger_id (str): The trigger id for the config message.
message (dict): The entire message with trigger_id and config.
Returns:
dict: CreateConfig Acknowledge response data.
"""
# merge the message config (e.g., optional, required)
message_config = message.pop('config')
config = message_config.get('optional', {})
config.update(message_config.get('required', {}))
message['config'] = config
# build config message
message['apiToken'] = self.tc_token
message['expireSeconds'] = int(time.time() + 86400)
message['command'] = 'CreateConfig'
message['config']['tc_playbook_out_variables'] = self.profile.tc_playbook_out_variables
message['triggerId'] = message.pop('trigger_id')
self.log.data('run', 'create config', f'{message["triggerId"]}')
self.message_broker.publish(json.dumps(message), self.server_topic)
# create thread wait event
event = Event()
key = f'{message["triggerId"]}-createconfig'
self.trigger_requests[key] = event
event.wait(10) # wait for 10 seconds
# time.sleep(self.sleep_after_publish_config)
result = self.trigger_responses.pop(key, {})
self.log.data(
'run',
'create config',
f'{message["triggerId"]} {result.get("status", "No Status")} '
f'{result.get("message", "No Message")}',
)
return dict(status=result.get('status', False), message=result.get('message'))
def publish_delete_config(self, message):
"""Send delete config message.
Args:
message (str): The message coming in on Broker channel
"""
time.sleep(self.sleep_before_delete_config)
# using triggerId here instead of trigger_id do to pop in publish_create_config
config_msg = {'command': 'DeleteConfig', 'triggerId': message.get('triggerId')}
self.log.data('run', 'delete config', f'{message["triggerId"]}')
self.message_broker.publish(json.dumps(config_msg), self.server_topic)
def publish_heartbeat(self):
"""Send heartbeat message to service."""
shutdown_msg = {'command': 'Heartbeat', 'metric': {}, 'memoryPercent': 0, 'cpuPercent': 0}
self.message_broker.publish(json.dumps(shutdown_msg), self.server_topic)
def publish_shutdown(self):
"""Publish shutdown message."""
config_msg = {'command': 'Shutdown'}
self.log.data('run', 'service', 'shutdown requested')
self.message_broker.publish(json.dumps(config_msg), self.server_topic)
def publish_webhook_event(
self,
trigger_id: int,
body: Optional[Any] = None,
headers: Optional[list] = None,
method: Optional[str] = 'GET',
query_params: Optional[list] = None,
request_key: Optional[str] = None,
):
"""Send create config message.
Args:
trigger_id: The trigger ID.
body: The HTTP request body.
headers: The HTTP request headers name/value pairs.
method: The HTTP request method.
query_params: The HTTP request query param name/value pairs.
request_key: The current request key.
"""
body = body or ''
request_key = request_key or str(uuid.uuid4())
if isinstance(body, dict):
body = json.dumps(body)
body = self.redis_client.hset(
request_key, 'request.body', base64.b64encode(body.encode('utf-8'))
)
event = {
'command': 'WebhookEvent',
'method': method,
'queryParams': query_params or [],
'headers': headers or [],
'body': 'request.body',
'requestKey': request_key,
'triggerId': trigger_id,
}
trigger_id = str(trigger_id)
self.log.data('run', 'webhook event', trigger_id)
ready = Event()
key = f'{trigger_id}-webhookevent'
self.trigger_requests[key] = ready
self.message_broker.publish(json.dumps(event), self.server_topic)
ready.wait(10) # wait for 10 seconds
status = 'Complete' if ready.isSet() else 'Timed Out'
self.trigger_responses.pop(key, {})
self.log.data('run', 'webhook event', f'{trigger_id} {status}')
def publish_marshall_webhook_event(
self,
trigger_id: int,
body: Optional[Any] = None,
headers: Optional[list] = None,
request_key: Optional[str] = None,
status_code: Optional[int] = 200,
):
"""Send create config message.
Args:
trigger_id: The trigger ID.
body: The HTTP response Body.
headers: The HTTP response headers name/value pairs.
request_key: The request key to reply with.
status_code: The HTTP response status code.
request_key: The current request key.
"""
body = body or ''
request_key = request_key or str(uuid.uuid4())
if isinstance(body, dict):
body = json.dumps(body)
body = self.redis_client.hset(
request_key, 'request.body', base64.b64encode(body.encode('utf-8'))
)
event = {
'command': 'WebhookMarshallEvent',
'headers': headers or [],
'body': 'request.body',
'requestKey': request_key,
'triggerId': trigger_id,
'statusCode': status_code,
}
trigger_id = str(trigger_id)
self.log.data('run', 'webhook marshal', trigger_id)
ready = Event()
key = f'{trigger_id}-webhookmarshallevent'
self.trigger_requests[key] = ready
self.message_broker.publish(json.dumps(event), self.server_topic)
ready.wait(10) # wait for 10 seconds
status = 'Complete' if ready.isSet() else 'Timed Out'
self.trigger_responses.pop(key, {})
self.log.data('run', 'webhook marshal', f'{trigger_id} {status}')
def run(self):
"""Implement in Child Class"""
raise NotImplementedError('Child class must implement this method.')
def run_service(self):
"""Run the micro-service."""
self.log.data('run', 'service method', self.service_run_method)
# backup sys.argv
sys_argv_orig = sys.argv
# clear sys.argv
sys.argv = sys.argv[:1]
# create required .app_params encrypted file. args are set in custom.py
self.args['tcex_testing_context'] = self.tcex_testing_context
self.create_config(self.args)
# run the service App in 1 of 3 ways
if self.service_run_method == 'subprocess':
# run the Service App as a subprocess
self.app_process = subprocess.Popen(['python', 'run.py'])
elif self.service_run_method == 'thread':
# run App in a thread
t = Thread(target=self.run, args=(), daemon=True)
t.start()
elif self.service_run_method == 'multiprocess':
p = Process(target=self.run, args=(), daemon=True)
p.start()
# restore sys.argv
sys.argv = sys_argv_orig
@classmethod
def setup_class(cls):
"""Run once before all test cases."""
super().setup_class()
cls.args = {}
cls.service_file = 'SERVICE_STARTED' # started file flag
# generate a context used in service.py to write context during fire event
cls.tcex_testing_context = str(uuid.uuid4())
def setup_method(self):
"""Run before each test method runs."""
super().setup_method()
self.stager.redis.from_dict(self.redis_staging_data)
self.redis_client = self.tcex.redis_client
for key in list(self.trigger_requests.keys()):
del self.trigger_requests[key]
for key in list(self.trigger_responses.keys()):
del self.trigger_responses[key]
self.service_ready.clear()
# register on_message shutdown monitor
self.message_broker.add_on_message_callback(
callback=self.on_message, topics=[self.client_topic]
)
# register on_subscribe notification
self.message_broker.add_on_subscribe_callback(callback=self.on_subscribe)
self.message_broker.client.loop_start()
self.subscribe(self.client_topic)
# only start service if it hasn't been started already base on file flag.
if not os.path.isfile(self.service_file):
open(self.service_file, 'w+').close() # create service started file flag
self.run_service()
# start shutdown monitor thread
t = Thread(target=self.shutdown_monitor, daemon=True)
t.start()
self.service_ready.wait(30)
if not self.service_ready.isSet():
self.log.data('run', 'service', 'failed to start')
else:
self.log.data('run', 'service', 'ready')
def shutdown_monitor(self):
"""Monitor for shutdown flag."""
while not self.shutdown:
time.sleep(0.5)
# shutdown the App
self.publish_shutdown()
# give Service App x seconds to shutdown before terminating
if self.service_run_method == 'subprocess':
for _ in range(1, 10):
time.sleep(0.5)
if self.app_process.poll() is not None:
break
else:
self.log.data('run', 'Terminating Process', f'PID: {self.app_process.pid}', 'debug')
self.app_process.terminate() # terminate subprocess
# remove started file flag
try:
os.remove(self.service_file)
except OSError:
pass
# set shutdown_complete
self.shutdown_complete = True
def stage_data(self, staged_data):
"""Stage the data in the profile."""
for key, value in list(staged_data.get('redis', {}).items()):
self.stager.redis.stage(key, value)
def subscribe(self, topic):
"""Subscribe to a topic and wait for the subscription to complete"""
event = Event()
with self.lock:
# don't try to subscribe outside of lock, since
# it could come back *before* we wait on it
_, mid = self.message_broker.client.subscribe(topic)
self.subscriptions[mid] = event
event.wait(10)
if mid in self.subscriptions: # failed to subscribe
self.log.error(f'Failed to subscribe to topic {topic}')
@classmethod
def teardown_class(cls):
"""Run once before all test cases."""
super().teardown_class()
# set shutdown flag for shutdown_monitor and wait until shutdown is done
cls.shutdown = True
for _ in range(1, 12):
if cls.shutdown_complete:
break
time.sleep(0.5)
def teardown_method(self):
"""Run after each test method runs."""
time.sleep(self.sleep_before_shutdown)
# run test_case_playbook_common teardown_method
super().teardown_method()
self.message_broker.client.loop_stop()
# clean up tcex testing context after populate_output has run
self.clear_context(self.tcex_testing_context)
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3546,
1154,
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10786,
16424,
1398,
1276,
3494,
428,
2446,
2637,
8,
628,
220,
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15271,
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944,
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24396,
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198,
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13,
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7,
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6,
12962,
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7,
16793,
28,
944,
13,
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11,
26498,
16193,
828,
33386,
28,
17821,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
256,
13,
9688,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
1288,
361,
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13,
15271,
62,
5143,
62,
24396,
6624,
705,
16680,
541,
305,
919,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
796,
10854,
7,
16793,
28,
944,
13,
5143,
11,
26498,
16193,
828,
33386,
28,
17821,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
279,
13,
9688,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
11169,
25064,
13,
853,
85,
198,
220,
220,
220,
220,
220,
220,
220,
25064,
13,
853,
85,
796,
25064,
62,
853,
85,
62,
11612,
628,
220,
220,
220,
2488,
4871,
24396,
198,
220,
220,
220,
825,
9058,
62,
4871,
7,
565,
82,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
10987,
1752,
878,
477,
1332,
2663,
526,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
2208,
22446,
40406,
62,
4871,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
537,
82,
13,
22046,
796,
23884,
198,
220,
220,
220,
220,
220,
220,
220,
537,
82,
13,
15271,
62,
7753,
796,
705,
35009,
27389,
62,
2257,
7227,
1961,
6,
220,
1303,
2067,
2393,
6056,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
7716,
257,
4732,
973,
287,
2139,
13,
9078,
284,
3551,
4732,
1141,
2046,
1785,
198,
220,
220,
220,
220,
220,
220,
220,
537,
82,
13,
83,
344,
87,
62,
33407,
62,
22866,
796,
965,
7,
12303,
312,
13,
12303,
312,
19,
28955,
628,
220,
220,
220,
825,
9058,
62,
24396,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
10987,
878,
1123,
1332,
2446,
4539,
526,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
2208,
22446,
40406,
62,
24396,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
301,
3536,
13,
445,
271,
13,
6738,
62,
11600,
7,
944,
13,
445,
271,
62,
301,
3039,
62,
7890,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
445,
271,
62,
16366,
796,
2116,
13,
83,
344,
87,
13,
445,
271,
62,
16366,
628,
220,
220,
220,
220,
220,
220,
220,
329,
1994,
287,
1351,
7,
944,
13,
46284,
62,
8897,
3558,
13,
13083,
3419,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1619,
2116,
13,
46284,
62,
8897,
3558,
58,
2539,
60,
628,
220,
220,
220,
220,
220,
220,
220,
329,
1994,
287,
1351,
7,
944,
13,
46284,
62,
16733,
274,
13,
13083,
3419,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1619,
2116,
13,
46284,
62,
16733,
274,
58,
2539,
60,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
15271,
62,
1493,
13,
20063,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
7881,
319,
62,
20500,
18325,
5671,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
20500,
62,
7957,
6122,
13,
2860,
62,
261,
62,
20500,
62,
47423,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
23838,
28,
944,
13,
261,
62,
20500,
11,
10233,
41888,
944,
13,
16366,
62,
26652,
60,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
7881,
319,
62,
7266,
12522,
14483,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
20500,
62,
7957,
6122,
13,
2860,
62,
261,
62,
7266,
12522,
62,
47423,
7,
47423,
28,
944,
13,
261,
62,
7266,
12522,
8,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
20500,
62,
7957,
6122,
13,
16366,
13,
26268,
62,
9688,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
7266,
12522,
7,
944,
13,
16366,
62,
26652,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
691,
923,
2139,
611,
340,
5818,
470,
587,
2067,
1541,
2779,
319,
2393,
6056,
13,
198,
220,
220,
220,
220,
220,
220,
220,
611,
407,
28686,
13,
6978,
13,
4468,
576,
7,
944,
13,
15271,
62,
7753,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1280,
7,
944,
13,
15271,
62,
7753,
11,
705,
86,
10,
27691,
19836,
3419,
220,
1303,
2251,
2139,
2067,
2393,
6056,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
5143,
62,
15271,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
923,
18325,
5671,
4704,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
256,
796,
14122,
7,
16793,
28,
944,
13,
49625,
2902,
62,
41143,
11,
33386,
28,
17821,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
256,
13,
9688,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
15271,
62,
1493,
13,
17077,
7,
1270,
8,
198,
220,
220,
220,
220,
220,
220,
220,
611,
407,
2116,
13,
15271,
62,
1493,
13,
271,
7248,
33529,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
6404,
13,
7890,
10786,
5143,
3256,
705,
15271,
3256,
705,
47904,
284,
923,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
6404,
13,
7890,
10786,
5143,
3256,
705,
15271,
3256,
705,
1493,
11537,
628,
220,
220,
220,
825,
18325,
62,
41143,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
35479,
329,
18325,
6056,
526,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
981,
407,
2116,
13,
49625,
2902,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
640,
13,
42832,
7,
15,
13,
20,
8,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
18325,
262,
2034,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
12984,
1836,
62,
49625,
2902,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
1577,
4809,
2034,
2124,
4201,
284,
18325,
878,
47985,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13,
15271,
62,
5143,
62,
24396,
6624,
705,
7266,
14681,
10354,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
329,
4808,
287,
2837,
7,
16,
11,
838,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
640,
13,
42832,
7,
15,
13,
20,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
611,
2116,
13,
1324,
62,
14681,
13,
30393,
3419,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2270,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
6404,
13,
7890,
10786,
5143,
3256,
705,
44798,
803,
10854,
3256,
277,
6,
47,
2389,
25,
1391,
944,
13,
1324,
62,
14681,
13,
35317,
92,
3256,
705,
24442,
11537,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
1324,
62,
14681,
13,
23705,
378,
3419,
220,
1303,
23654,
850,
14681,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
4781,
2067,
2393,
6056,
198,
220,
220,
220,
220,
220,
220,
220,
1949,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
28686,
13,
28956,
7,
944,
13,
15271,
62,
7753,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2845,
440,
5188,
81,
1472,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1208,
628,
220,
220,
220,
220,
220,
220,
220,
1303,
900,
18325,
62,
20751,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
49625,
2902,
62,
20751,
796,
6407,
628,
220,
220,
220,
825,
3800,
62,
7890,
7,
944,
11,
23393,
62,
7890,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
29391,
262,
1366,
287,
262,
7034,
526,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
329,
1994,
11,
1988,
287,
1351,
7,
301,
1886,
62,
7890,
13,
1136,
10786,
445,
271,
3256,
23884,
737,
23814,
3419,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
301,
3536,
13,
445,
271,
13,
14247,
7,
2539,
11,
1988,
8,
628,
220,
220,
220,
825,
12383,
7,
944,
11,
7243,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
27125,
284,
257,
7243,
290,
4043,
329,
262,
14569,
284,
1844,
37811,
198,
220,
220,
220,
220,
220,
220,
220,
1785,
796,
8558,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
351,
2116,
13,
5354,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
836,
470,
1949,
284,
12383,
2354,
286,
5793,
11,
1201,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
340,
714,
1282,
736,
1635,
19052,
9,
356,
4043,
319,
340,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
4808,
11,
3095,
796,
2116,
13,
20500,
62,
7957,
6122,
13,
16366,
13,
7266,
12522,
7,
26652,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
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] | 2.277994 | 6,939 |
'''aula de tkinter I'''
from tkinter import *
#dá nome ao quadro principal
quadro = Tk()
#dá um tamanho ao quadro
quadro.geometry("800x600")
#dá o titulo na janela do programa
quadro.title("primeiro programa pos retorno!")
#faz o quadro iniciar
# sem isso o programa não abre
quadro.mainloop()
|
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] | 2.41791 | 134 |
#This script Imports Game Data from ESPN, and Odds from the ODDS-API, and then imports them into a MySQL table, example in workbench here https://puu.sh/HOKCj/ce199eec8e.png
import mysql.connector
import requests
import json
import datetime
import time
#Connection to the MYSQL Server.
mydb = mysql.connector.connect(
host="",
user="",
password="",
database="basketbet_data"
)
mycursor = mydb.cursor()
#Games List.
allGames=[]
#Gets the game Data from ESPN API given the link.
#Gets the Odds from the ODDS-API.
#Block to keep the script running then sleep for time 300 with counter set at 72 for Games every 5min | Odds every 6hr.
counter=72
startTime = time.time()
while True:
#Today, Yesterday and Tomorrow.
today = datetime.date.today()
yesterday = today + datetime.timedelta(days=-1)
tomorrow = today + datetime.timedelta(days=1)
#Removing the - from the dates for the URLs, then making the URLs.
todayShort = str(today).replace('-', '')
yesterdayShort = str(yesterday).replace('-', '')
tomorrowShort = str(tomorrow).replace('-', '')
yesterdayUrl = "http://site.api.espn.com/apis/site/v2/sports/basketball/nba/scoreboard?dates=" + yesterdayShort + '-' + yesterdayShort
todayUrl = "http://site.api.espn.com/apis/site/v2/sports/basketball/nba/scoreboard?dates=" + todayShort + '-' + todayShort
tomorrowUrl = "http://site.api.espn.com/apis/site/v2/sports/basketball/nba/scoreboard?dates=" + tomorrowShort + '-' + tomorrowShort
newGetter(yesterdayUrl)
newGetter(todayUrl)
newGetter(tomorrowUrl)
#Inserting or updating the table in MYSQL with the games.
c=0
updateCount=0
newGameCount=0
while c < len(allGames):
query_string = 'SELECT * FROM basketbet_data.all_games WHERE Game_ID = %s'
gameID = (str(allGames[c][0]),)
mycursor.execute(query_string, gameID)
if mycursor.fetchone():
updateCount+=1
query_list = [allGames[c][1], allGames[c][2], allGames[c][4], allGames[c][5], allGames[c][3], allGames[c][6], allGames[c][7], allGames[c][8], allGames[c][9], allGames[c][0]]
query_string = 'UPDATE all_games SET Game_Name = %s, Home_Team = %s, Away_Team = %s, Away_Score = %s, Home_Score = %s, Game_Date = %s, Game_Time = %s, Game_Period = %s, Game_Status = %s WHERE (Game_ID = %s)'
mycursor.execute(query_string, query_list)
mydb.commit()
else:
newGameCount+=1
query_string = "INSERT INTO basketbet_data.all_games (Game_ID, Game_Name, Home_Team, Home_Odds, Home_Score, Away_Team, Away_Odds, Away_Score, Game_Date, Game_Time, Game_Period, Game_Status) VALUES (%s, %s, %s, 0, %s, %s, 0, %s, %s, %s, %s, %s)"
mycursor.execute(query_string, allGames[c])
mydb.commit()
c+=1
#Prints to console what games were updated and what new games were inserted.
print('----------------------------------------')
print(str(updateCount) + ' GAMES UPDATED, and ' + str(newGameCount) + ' NEW GAMES inserted.')
print('----------------------------------------')
allGames=[]
#Counter for the Odds script.
if counter==72:
oddsGetter()
counter=0
else:
counter+=1
print('\n')
time.sleep(300 - ((time.time() - startTime) % 300))
|
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] | 2.405726 | 1,432 |
from models import news
|
[
6738,
4981,
1330,
1705,
628,
628
] | 4.5 | 6 |
"""
Utilities for creating simulated data sets.
"""
from typing import Optional, Sequence
import numpy as np
import pandas as pd
from scipy.linalg import toeplitz
from ..api import AllTracker
__all__ = ["sim_data"]
__tracker = AllTracker(globals())
def sim_data(
n: int = 100,
intercept: float = -5,
two_way_coef: Optional[float] = None,
linear_vars: int = 10,
linear_var_coef: Optional[Sequence[float]] = None,
noise_vars: int = 0,
corr_vars: int = 0,
corr_type: str = "AR1",
corr_value: float = 0,
surg_err: float = 0.05,
bin_var_p: float = 0,
bin_coef: float = 0,
outcome: str = "classification",
regression_err: Optional[float] = None,
seed_val: int = 4763546,
) -> pd.DataFrame:
"""
Simulate data for classification or regression that includes an interaction between
two linear features, and some non-linear and linear features.
Noise variables, correlated variables that are not predictive and surrogate features
which are just derived from features that are predictive are also added.
This function is for the most part a direct translation of the ``twoClassSim``
function from the R package caret -- the option for an ordinal outcome and binary
outcome mis-labelling were omitted. Full credit for the approach used for simulating
binary classification data goes to the authors and contributors of caret
[`Kuhn, M. (2008). Caret package. Journal of Statistical Software, 28(5).
<https://rdrr.io/cran/caret/man/twoClassSim.html>`_]
Key modifications compared to the *R* implementation:
1. The ordinal outcome option has not been translated
2. Mis-labelling of the binary outcome has not been translated
3. The addition of a linear feature that is a copy of another used in the linear
predictor with a small amount of noise has been added to allow for the study
of variable surrogacy
4. Option for a binary predictor and surrogate has been added
5. Toggle option for regression versus classification has been added
6. Arguments for the coefficients of primary predictors of interest has been added
:param n: number of observations
:param intercept: value for the intercept which can be modified to generate class
imbalance
:param two_way_coef: list of three coefficients: two linear terms and an
interaction effect
:param linear_vars: number of linear features
:param linear_var_coef: an optional list of coefficients for linear features if
the default is not desired
:param noise_vars: number of unrelated independent noise features (do not
contribute to the linear predictor)
:param corr_vars: number of unrelated correlated noise features (do not contribute
to the linear predictor)
:param corr_type: type of correlation (exchangeable or auto-regressive) for
correlated noise features
:param corr_value: correlation for correlated noise features
:param surg_err: degree of noise added to first linear predictor
:param bin_var_p: prevalence for a binary feature to include in linear predictor
:param bin_coef: coefficient for the impact of binary feature on linear predictor
:param outcome: can be either classification for a binary outcome or regression
for a continuous outcome
:param regression_err: the error to be used in simulating a regression outcome
:param seed_val: set a seed for reproducibility
:return: data frame containing the simulated features and target for classification
"""
# set seed
np.random.seed(seed=seed_val)
# add two correlated normal features for use in creating an interaction term in the
# linear predictor
sigma = np.array([[2, 1.3], [1.3, 2]])
mu = [0, 0]
tmp_data = pd.DataFrame(
np.random.multivariate_normal(mu, sigma, size=n),
columns=["TwoFactor1", "TwoFactor2"],
)
# add independent linear features that contribute to the linear predictor
if linear_vars > 0:
lin_cols = ["Linear" + str(x) for x in range(1, linear_vars + 1)]
tmp_data = pd.concat(
[
tmp_data,
pd.DataFrame(np.random.normal(size=(n, linear_vars)), columns=lin_cols),
],
axis=1,
)
else:
lin_cols = None
# add non-linear features that contribute to the linear predictor
tmp_data["Nonlinear1"] = pd.Series(np.random.uniform(low=-1.0, high=1.0, size=n))
tmp_data = pd.concat(
[
tmp_data,
pd.DataFrame(
np.random.uniform(size=(n, 2)), columns=["Nonlinear2", "Nonlinear3"]
),
],
axis=1,
)
# add independent noise features that do not contribute to the linear predictor
if noise_vars > 0:
noise_cols = ["Noise" + str(x) for x in range(1, noise_vars + 1)]
tmp_data = pd.concat(
[
tmp_data,
pd.DataFrame(
np.random.normal(size=(n, noise_vars)), columns=noise_cols
),
],
axis=1,
)
# add correlated noise features that do not contribute to the linear predictor
if corr_vars > 0:
if corr_type == "exch":
vc = corr_value * np.ones((corr_vars, corr_vars))
np.fill_diagonal(vc, 1)
elif corr_type == "AR1":
vc_values = corr_value ** np.arange(corr_vars)
vc = toeplitz(vc_values)
else:
raise ValueError(
f'arg corr_type must be "exch" or "AR1", but got {repr(corr_type)}'
)
corr_cols = ["Corr" + str(x) for x in range(1, corr_vars + 1)]
tmp_data = pd.concat(
[
tmp_data,
pd.DataFrame(
np.random.multivariate_normal(np.zeros(corr_vars), vc, size=n),
columns=corr_cols,
),
],
axis=1,
)
# add a surrogate linear feature that does not contribute to the linear predictor
if linear_vars > 0:
tmp_data["Linear1_prime"] = tmp_data["Linear1"] + np.random.normal(
0, surg_err, size=n
)
# add a binary feature that contributes to the linear predictor
if bin_var_p > 0:
tmp_data["Binary1"] = np.where(np.random.uniform(size=n) <= bin_var_p, 0, 1)
# generate linear predictor
if two_way_coef is None:
two_way_coef = [4, 4, 2]
lp = (
intercept
- two_way_coef[0] * tmp_data.TwoFactor1
+ two_way_coef[1] * tmp_data.TwoFactor2
+ two_way_coef[2] * tmp_data.TwoFactor1 * tmp_data.TwoFactor2
+ tmp_data.Nonlinear1 ** 3
+ 2 * np.exp(-6 * (tmp_data.Nonlinear1 - 0.3) ** 2)
+ 2 * np.sin(np.pi * tmp_data.Nonlinear2 * tmp_data.Nonlinear3)
)
# add independent linear features to the linear predictor if required
if linear_vars > 0:
if linear_var_coef is None:
lin_coef = np.linspace(linear_vars, 1, num=linear_vars) / 4
neg_idx = list(range(1, linear_vars, 2))
lin_coef[neg_idx] *= -1
lp += tmp_data[lin_cols].dot(lin_coef)
elif linear_var_coef is not None:
if linear_vars != len(linear_var_coef):
raise ValueError(
"User defined linear feature coefficient list must be of length "
f"{linear_vars}"
)
lp += tmp_data[lin_cols].dot(linear_var_coef)
# add binary feature to the linear predictor if required
if bin_var_p > 0:
lp += bin_coef * tmp_data["Binary1"]
tmp_data["Binary1_prime"] = 1 - tmp_data["Binary1"]
# create classification outcome from linear predictor
if outcome == "classification":
# convert to a probability
prob = 1 / (1 + np.exp(-lp))
# generate target
tmp_data["target"] = np.where(prob <= np.random.uniform(size=n), 0, 1)
# create regression outcome
elif outcome == "regression":
# continuous outcome based on linear predictor
tmp_data["target"] = np.random.normal(lp, regression_err, size=n)
return tmp_data
__tracker.validate()
|
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] | 2.443789 | 3,389 |
# Copyright (c) 2021 - present / Neuralmagic, Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Base classes for describing models and layers in ML framework neural networks.
"""
import json
from abc import ABC, abstractmethod
from collections import OrderedDict
from copy import deepcopy
from enum import Enum
from typing import Any, Dict, List, Optional, Set, Union
import numpy
from pydantic import BaseModel, Field, root_validator
from sparseml.utils import clean_path, create_parent_dirs
__all__ = [
"LayerInfo",
"Result",
"ModelResult",
"PruningSensitivityResult",
"PruningSensitivityResultTypes",
"ModelInfo",
]
class LayerInfo(BaseModel):
"""
Class for storing properties about a layer in a model
"""
name: str = Field(
title="name",
description="unique name of the layer within its model",
)
op_type: str = Field(
title="op_type",
description="type of layer, i.e. 'conv', 'linear'",
)
params: Optional[int] = Field(
title="params",
default=None,
description=(
"number of non-bias parameters in the layer. must be included "
"for prunable layers"
),
)
bias_params: Optional[int] = Field(
title="bias_params",
default=None,
description="number of bias parameters in the layer",
)
prunable: bool = Field(
title="prunable",
default=False,
description="True if the layers non-bias parameters can be pruned",
)
flops: Optional[int] = Field(
title="flops",
default=None,
description="number of float operations within the layer",
)
execution_order: int = Field(
title="execution_order",
default=-1,
description="execution order of the layer within the model",
)
attributes: Optional[Dict[str, Any]] = Field(
title="attributes",
default=None,
description="dictionary of string attribute names to their values",
)
@root_validator(pre=True)
@classmethod
def linear_layer(
cls, name: str, in_channels: int, out_channels: int, bias: bool, **kwargs
) -> "LayerInfo":
"""
creates a LayerInfo object for a fully connected linear layer
:param name: unique name of the layer within its model
:param in_channels: number of input channels
:param out_channels: number of output channels
:param bias: True if the linear layer has a bias add included, False otherwise
:param kwargs: additional kwargs to be passed to the LayerInfo constructor
:return:
"""
attributes = {
"in_channels": in_channels,
"out_channels": out_channels,
}
attributes.update(kwargs.get("attributes", {}))
kwargs["attributes"] = attributes
return cls(
name=name,
op_type="linear",
params=in_channels * out_channels,
bias_params=out_channels if bias else None,
prunable=True,
**kwargs, # TODO: add FLOPS calculation
)
@classmethod
def conv_layer(
cls,
name: str,
in_channels: int,
out_channels: int,
kernel_shape: List[int],
bias: bool,
groups: int = 1,
stride: Union[int, List[int]] = 1,
padding: List[int] = None,
**kwargs,
) -> "LayerInfo":
"""
creates a LayerInfo object for a fully connected convolutional layer
:param name: unique name of the layer within its model
:param in_channels: number of input channels
:param out_channels: number of output channels
:param kernel_shape: kernel shape of this layer, given as a list
:param bias: True if the linear layer has a bias add included, False otherwise
:param groups: number of groups that input and output channels are divided into.
default is 1
:param stride: stride for this convolution, can be int or tuple of ints. default
is 1
:param padding: padding applied to each spatial axis. defualt is [0, 0, 0, 0]
:param kwargs: additional kwargs to be passed to the LayerInfo constructor
:return:
"""
attributes = {
"in_channels": in_channels,
"out_channels": out_channels,
"kernel_shape": kernel_shape,
"groups": groups,
"stride": stride,
"padding": padding if padding is not None else [0, 0, 0, 0],
}
attributes.update(kwargs.get("attributes", {}))
kwargs["attributes"] = attributes
return cls(
name=name,
op_type="conv",
params=in_channels * out_channels * numpy.prod(kernel_shape) // groups,
bias_params=out_channels if bias else None,
prunable=True,
**kwargs, # TODO: add FLOPS calculation
)
class Result(BaseModel):
"""
Base class for storing the results of an analysis
"""
value: Any = Field(
title="value",
default=None,
description="initial value of the result",
)
attributes: Optional[Dict[str, Any]] = Field(
title="attributes",
default=None,
description="dict of attributes of this result",
)
class ModelResult(Result):
"""
Class for storing the results of an analysis for an entire model
"""
analysis_type: str = Field(
title="analysis_type",
description="name of the type of analysis that was performed",
)
layer_results: Dict[str, Result] = Field(
title="layer_results",
default_factory=dict,
description=(
"dict of layer results to initialize for this analysis. should map "
"layer name to Result object"
),
)
class PruningSensitivityResultTypes(Enum):
"""
Types of pruning sensitivity results standardized by SparseML, used as
ModelResult.analysis_type
"""
LOSS = "pruning_sensitivity_loss"
PERF = "pruning_sensitivity_perf"
class PruningSensitivityResult(ModelResult):
"""
Helper class for creating and updating results of pruning sensitivity analyses
:param analysis_type: PruningSensitivityResultTypes Enum value
of type of analysis this is
:param kwargs: optional args to be passed into model result constructor
"""
def add_layer_sparsity_result(self, layer_name: str, sparsity: float, value: Any):
"""
Adds a result of the given value for a given sparsity to the given layer name
:param layer_name: layer param name to add result for
:param sparsity: sparsity of the layer at which the sensitivity was measured
:param value: sensitivity value
"""
sparsity = str(sparsity)
if layer_name not in self.layer_results:
self.layer_results[layer_name] = Result(value={})
self.layer_results[layer_name].value[sparsity] = value
def add_model_sparsity_result(self, sparsity: float, value: Any):
"""
Adds a model result of the given value for a given sparsity
:param sparsity: sparsity of model at which the sensitivity was measured
:param value: sensitivity value
"""
sparsity = str(sparsity)
if self.value is None:
self.value = {}
self.value[sparsity] = value
def get_available_layer_sparsities(self) -> List[float]:
"""
:return: list of sparsity values available for all model layers
"""
available_sparsities = None
for result in self.layer_results.values():
sparsities = set(result.value.keys())
if available_sparsities is None:
available_sparsities = sparsities
else:
available_sparsities = available_sparsities.intersection(sparsities)
return [float(sparsity) for sparsity in sorted(available_sparsities)]
def get_layer_sparsity_score(self, layer_name: str, sparsity: float) -> float:
"""
:param layer_name: name of layer to get sparsity score for
:param sparsity: sparsity to measure score at
:return: sparsity score at the given sparsity such that higher scores correlate
to a less prunable layer
"""
result = self.layer_results[layer_name].value
sparsity = str(sparsity)
if sparsity not in result:
raise ValueError(f"No result for sparsity {sparsity} in layer {layer_name}")
baseline_sparsity = str(0.0 if 0.0 in result else min(result))
return (
result[sparsity]
if self.analysis_type is PruningSensitivityResultTypes.PERF
else result[sparsity] - result[baseline_sparsity]
)
_ANALYSIS_TYPE_TO_CLASS = {
PruningSensitivityResultTypes.LOSS.value: PruningSensitivityResult,
PruningSensitivityResultTypes.PERF.value: PruningSensitivityResult,
}
class ModelInfo(ABC):
"""
Base class for extracting and serializing model metadata, layers info, and
analysis results
:param model: framework specific model object to extract info for
:param metadata: optional dict of string metadata attributes to value. Default
is empty dict
"""
@classmethod
def from_dict(cls, dictionary: Dict[str, Any]):
"""
:param dictionary: dict serialized by `dict(ModelInfo(...))`
:return: ModelInfo object created from the given dict
"""
dictionary = deepcopy(dictionary)
if "layer_info" not in dictionary:
raise ValueError(
"ModelInfo objects serialized as a dict must include a 'layer_info' key"
)
layer_info = {
name: LayerInfo.parse_obj(info)
for name, info in dictionary["layer_info"].items()
}
model_info = cls(layer_info, metadata=dictionary.get("metadata", {}))
results = dictionary.get("analysis_results", [])
for result in results:
model_result = _model_result_from_dict(result)
model_info.add_analysis_result(model_result)
return model_info
@staticmethod
def load(file_path) -> "ModelInfo":
"""
:param file_path: file path to JSON file to load ModelInfo object from
:return: the loaded ModelInfo object
"""
file_path = clean_path(file_path)
with open(file_path, "r") as file:
model_info_dict = json.load(file)
return ModelInfo.from_dict(model_info_dict)
@property
def layer_info(self) -> "OrderedDict[str, LayerInfo]":
"""
:return: dict of unique layer name to LayerInfo object of the given layer
"""
return self._layer_info
@property
def analysis_results(self) -> List[ModelResult]:
"""
:return: list of analysis results run on this model
"""
return self._analysis_results
@abstractmethod
def extract_layer_info(self, model: Any) -> "OrderedDict[str, LayerInfo]":
"""
Abstract method for extracting an ordered dictionary of layer name to
completed LayerInfo object for the layer
:param model: model to extract LayerInfo information of
:return: ordered dictionary of layer name to LayerInfo object for the layer
"""
raise NotImplementedError()
def get_results_by_type(self, analysis_type: str) -> List[ModelResult]:
"""
:param analysis_type: type of analysis in ModelResult.analysis_type to
filter by
:return: list of analysis results of this model that match the given type
"""
return [
result
for result in self._analysis_results
if result.analysis_type == analysis_type
]
def get_prunable_param_names(self) -> Set[str]:
"""
:return: set of parameter names of all prunable layers in this ModelInfo
"""
return {
layer_name
for layer_name, layer_info in self.layer_info.items()
if layer_info.prunable
}
def to_dict(self) -> Dict[str, Any]:
"""
:return: dict representation of this ModelResult
"""
layer_info = {name: dict(info) for name, info in self._layer_info.items()}
analysis_results = [dict(result) for result in self._analysis_results]
return {
"metadata": self.metadata,
"layer_info": layer_info,
"analysis_results": analysis_results,
}
def save(self, file_path: str):
"""
saves the dict representation of this ModelInfo object as a JSON file
to the given file path
:param file_path: file path to save to
"""
create_parent_dirs(file_path)
with open(file_path, "w") as file:
json.dump(self.to_dict(), file)
@staticmethod
|
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355,
257,
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2393,
198,
220,
220,
220,
220,
220,
220,
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284,
262,
1813,
2393,
3108,
198,
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220,
220,
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220,
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1058,
17143,
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62,
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3108,
284,
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37227,
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2251,
62,
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7,
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62,
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8,
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220,
220,
220,
220,
220,
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220,
351,
1280,
7,
7753,
62,
6978,
11,
366,
86,
4943,
355,
2393,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
33918,
13,
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7,
944,
13,
1462,
62,
11600,
22784,
2393,
8,
628,
220,
220,
220,
2488,
12708,
24396,
628
] | 2.515022 | 5,392 |
# -*- coding: utf-8 -*-
#
# Copyright (C) 2019 CESNET z.s.p.o..
#
# OARepo is free software; you can redistribute it and/or modify it
# under the terms of the MIT License; see LICENSE file for more details.
""" Models used by the ProxyIDP Remote application """
|
[
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
2,
198,
2,
15069,
357,
34,
8,
13130,
42700,
12884,
1976,
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82,
13,
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32329,
973,
416,
262,
38027,
2389,
47,
21520,
3586,
37227,
198
] | 3.05814 | 86 |
import argparse
from camp_real_engine.engine import RealizationEngine
|
[
11748,
1822,
29572,
198,
198,
6738,
1413,
62,
5305,
62,
18392,
13,
18392,
1330,
6416,
1634,
13798,
628,
198
] | 3.842105 | 19 |
from rest_framework.pagination import LimitOffsetPagination
from rest_framework.permissions import AllowAny
from rest_framework.viewsets import ReadOnlyModelViewSet
from ..models import Catalog
from ..serializers import CatalogListSerializer, CatalogSerializer
|
[
6738,
1334,
62,
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13,
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32634,
7509,
628
] | 4.311475 | 61 |
"""
File: weather_master.py
Name: Karen Wong
-----------------------
This program should implement a console program that asks weather data from user to compute the average, highest, lowest, cold days among the inputs.
Output format should match what is shown in the sample run in the Assignment 2 Handout.
"""
EXIT = -100
def main():
"""
This program is used to calculate the highest, lowest, average temperature
and the total cold day (temperature < 16 ) of the given sequences.
"""
print('stanCode "Weather Master 4.0"!')
temp = int(input('Next Temperature(or ' + str(EXIT) + ' to quit)? '))
if temp == EXIT:
print('No temperature were entered.')
else:
highest = temp
lowest = temp
average = temp
if temp < 16:
cold = 1
else:
cold = 0
total_num = 1
while True:
temp1 = int(input('Next Temperature(or ' + str(EXIT)+' to quit)? '))
if temp1 == EXIT:
break
else:
total_num += 1
if temp1 > highest:
highest = temp1
if temp1 < lowest:
lowest = temp1
if temp1 <= 16:
cold += 1
average = (temp1+average*(total_num-1))/total_num
temp = temp1
print('Highest temperature = ' + str(highest))
print('Lowest temperature = ' + str(lowest))
print('Average temperature = ' + str(average))
print(str(cold)+' cold days!')
if __name__ == "__main__":
main()
|
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3672,
834,
6624,
366,
834,
12417,
834,
1298,
198,
197,
12417,
3419,
198
] | 2.824895 | 474 |
"""Color cycler."""
from matplotlib import cycler as mpl_cycler
def cycler(**kwargs):
"""Wrap a matplotlib.cycler object into a parameter-dictionary compatible with plt.rcParams.
Please refer to
https://matplotlib.org/cycler/
and
https://matplotlib.org/stable/tutorials/intermediate/color_cycle.html
for information about how to use cyclers.
"""
return {"axes.prop_cycle": mpl_cycler(**kwargs)}
|
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14,
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62,
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13,
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198,
220,
220,
220,
329,
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546,
703,
284,
779,
11700,
364,
13,
198,
220,
220,
220,
37227,
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220,
220,
1441,
19779,
897,
274,
13,
22930,
62,
13696,
1298,
285,
489,
62,
15539,
263,
7,
1174,
46265,
22046,
38165,
198
] | 2.676829 | 164 |
# Copyright (c) 2020 Continental Automotive GmbH
"""Testing functions."""
|
[
2,
220,
15069,
357,
66,
8,
12131,
30462,
17406,
19138,
402,
2022,
39,
198,
198,
37811,
44154,
5499,
526,
15931,
198
] | 3.619048 | 21 |
import unittest
import pandas as pd
import pytest
import riptable as rt
# N.B. TL;DR We have to import the actual implementation module to override the module global
# variable "tm.N" and "tm.K".
# In pandas 1.0 they move the code from pandas/util/testing.py to pandas/_testing.py.
# The "import pandas.util.testing" still works but because it doesn't contain the actual code
# our attempt to override the "tm.N" and "tm.K" will not change the actual value for
# makeTimeDataFrame, which will produce data with different shape and make the test
# "test_accum_table" fail. Maybe we want to reconsider using the pandas internal testing utils.
try:
import pandas._testing as tm
except ImportError:
import pandas.util.testing as tm
from riptable import *
from numpy.testing import (
assert_array_equal,
assert_almost_equal,
assert_array_almost_equal,
)
from riptable.rt_numpy import arange
# To create AccumTable test data
from riptable.Utils.pandas_utils import dataset_from_pandas_df
from riptable.rt_datetime import DateTimeNano
tm.N = 3
tm.K = 5
class Accum2_Test(unittest.TestCase):
'''
TODO: add more tests for different types
'''
@pytest.mark.xfail(reason='20200416 This test was previously overridden by a later test in the file with the same name. Need to revisit and get back in a working state.')
if __name__ == "__main__":
tester = unittest.main()
|
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736,
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1181,
2637,
8,
201,
198,
201,
198,
201,
198,
201,
198,
361,
11593,
3672,
834,
6624,
366,
834,
12417,
834,
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201,
198,
220,
220,
220,
256,
7834,
796,
555,
715,
395,
13,
12417,
3419,
201,
198
] | 2.776735 | 533 |
"""Indent and Dedent classes."""
from sqlfluff.core.parser.match_wrapper import match_wrapper
from sqlfluff.core.parser.segments.raw import RawSegment
from sqlfluff.core.parser.context import ParseContext
from typing import Optional, List
class MetaSegment(RawSegment):
"""A segment which is empty but indicates where something should be."""
type = "meta"
_is_code = False
_template = "<unset>"
indent_val = 0
is_meta = True
@staticmethod
def _suffix():
"""Return any extra output required at the end when logging.
Meta classes have not much to say here so just stay blank.
"""
return ""
@classmethod
@match_wrapper()
def match(cls, segments, parse_context): # pragma: no cover
"""This will never be called. If it is then we're using it wrong."""
raise NotImplementedError(
"{} has no match method, it should only be used in a Sequence!".format(
cls.__name__
)
)
@classmethod
def simple(cls, parse_context: ParseContext) -> Optional[List[str]]:
"""Does this matcher support an uppercase hash matching route?
This should be true if the MATCH grammar is simple. Most more
complicated segments will be assumed to overwrite this method
if they wish to be considered simple.
"""
return None
class Indent(MetaSegment):
"""A segment which is empty but indicates where an indent should be.
This segment is always empty, i.e. its raw format is '', but it indicates
the position of a theoretical indent which will be used in linting
and reconstruction. Even if there is an *actual indent* that occurs
in the same place this intentionally *won't* capture it, they will just
be compared later.
"""
type = "indent"
indent_val = 1
class Dedent(Indent):
"""A segment which is empty but indicates where an dedent should be.
This segment is always empty, i.e. its raw format is '', but it indicates
the position of a theoretical dedent which will be used in linting
and reconstruction. Even if there is an *actual dedent* that occurs
in the same place this intentionally *won't* capture it, they will just
be compared later.
"""
type = "dedent"
indent_val = -1
class TemplateSegment(MetaSegment):
"""A segment which is empty but indicates something should be.
This segment is always empty, i.e. its raw format is '', but it indicates
the position of an element on a line which has been removed. This is used
to record the position of template blocks, so that their indents are not
removed during linting.
This is used to hold a reference point for code from the source file
which is removed in the templated version such as loop blocks or comments.
On initialisation we optionally accept the source string as a kwarg in
case rules want to lint this down the line.
"""
type = "placeholder"
def __init__(self, pos_marker=None, source_str="", block_type=""):
"""Initialise a placeholder with the source code embedded."""
if not source_str: # pragma: no cover
raise ValueError("Cannot instantiate TemplateSegment without a source_str.")
self.source_str = source_str
self.block_type = block_type
# Call the super of the pos_marker.
super().__init__(pos_marker=pos_marker)
def _suffix(self):
"""Also output what it's a placeholder for."""
return f"[Type: {self.block_type!r}, Raw: {self.source_str!r}]"
def to_tuple(self, code_only=False, show_raw=False, include_meta=False):
"""Return a tuple structure from this segment.
Unlike most segments, we return the _source_ content for placeholders
if viewing metas is allowed. This allows verification of the content
of those placeholders for inspection or debugging.
"""
if include_meta:
return (self.get_type(), self.source_str)
else: # pragma: no cover TODO?
return (self.get_type(), self.raw)
|
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319,
257,
1627,
543,
468,
587,
4615,
13,
770,
318,
973,
198,
220,
220,
220,
284,
1700,
262,
2292,
286,
11055,
7021,
11,
523,
326,
511,
773,
658,
389,
407,
198,
220,
220,
220,
4615,
1141,
300,
600,
278,
13,
628,
220,
220,
220,
770,
318,
973,
284,
1745,
257,
4941,
966,
329,
2438,
422,
262,
2723,
2393,
198,
220,
220,
220,
543,
318,
4615,
287,
262,
2169,
489,
515,
2196,
884,
355,
9052,
7021,
393,
3651,
13,
198,
220,
220,
220,
1550,
4238,
5612,
356,
42976,
2453,
262,
2723,
4731,
355,
257,
479,
86,
853,
287,
198,
220,
220,
220,
1339,
3173,
765,
284,
300,
600,
428,
866,
262,
1627,
13,
198,
220,
220,
220,
37227,
628,
220,
220,
220,
2099,
796,
366,
5372,
13829,
1,
628,
220,
220,
220,
825,
11593,
15003,
834,
7,
944,
11,
1426,
62,
4102,
263,
28,
14202,
11,
2723,
62,
2536,
2625,
1600,
2512,
62,
4906,
33151,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
24243,
786,
257,
46076,
351,
262,
2723,
2438,
14553,
526,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
611,
407,
2723,
62,
2536,
25,
220,
1303,
23864,
2611,
25,
645,
3002,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5298,
11052,
12331,
7203,
34,
34574,
9113,
9386,
37350,
41030,
434,
1231,
257,
2723,
62,
2536,
19570,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
10459,
62,
2536,
796,
2723,
62,
2536,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13,
9967,
62,
4906,
796,
2512,
62,
4906,
198,
220,
220,
220,
220,
220,
220,
220,
1303,
4889,
262,
2208,
286,
262,
1426,
62,
4102,
263,
13,
198,
220,
220,
220,
220,
220,
220,
220,
2208,
22446,
834,
15003,
834,
7,
1930,
62,
4102,
263,
28,
1930,
62,
4102,
263,
8,
628,
220,
220,
220,
825,
4808,
37333,
844,
7,
944,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
7583,
5072,
644,
340,
338,
257,
46076,
329,
526,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
277,
17912,
6030,
25,
1391,
944,
13,
9967,
62,
4906,
0,
81,
5512,
16089,
25,
1391,
944,
13,
10459,
62,
2536,
0,
81,
92,
30866,
628,
220,
220,
220,
825,
284,
62,
83,
29291,
7,
944,
11,
2438,
62,
8807,
28,
25101,
11,
905,
62,
1831,
28,
25101,
11,
2291,
62,
28961,
28,
25101,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
13615,
257,
46545,
4645,
422,
428,
10618,
13,
628,
220,
220,
220,
220,
220,
220,
220,
12101,
749,
17894,
11,
356,
1441,
262,
4808,
10459,
62,
2695,
329,
1295,
10476,
198,
220,
220,
220,
220,
220,
220,
220,
611,
11681,
1138,
292,
318,
3142,
13,
770,
3578,
19637,
286,
262,
2695,
198,
220,
220,
220,
220,
220,
220,
220,
286,
883,
1295,
10476,
329,
15210,
393,
28769,
13,
198,
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220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2291,
62,
28961,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
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944,
13,
1136,
62,
4906,
22784,
2116,
13,
10459,
62,
2536,
8,
198,
220,
220,
220,
220,
220,
220,
220,
2073,
25,
220,
1303,
23864,
2611,
25,
645,
3002,
16926,
46,
30,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
357,
944,
13,
1136,
62,
4906,
22784,
2116,
13,
1831,
8,
198
] | 2.924221 | 1,412 |
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