PatrickHaller/the-stack-python-1M · Datasets at Hugging Face

fa1db442c9e53ef996398c6e62a52fb34b4bd8ef

2,350

py

Python

tests/data/events.py

stackriot-labs/gitsome

d7c57abc7cb66e9c910a844f15d4536866da3310

[ "Apache-2.0" ]

7,986

2015-11-07T11:59:21.000Z

2022-03-27T17:20:49.000Z

tests/data/events.py

themaximum88/gitsome

d7c57abc7cb66e9c910a844f15d4536866da3310

[ "Apache-2.0" ]

161

2016-05-09T09:53:48.000Z

2022-02-22T04:18:59.000Z

tests/data/events.py

themaximum88/gitsome

d7c57abc7cb66e9c910a844f15d4536866da3310

[ "Apache-2.0" ]

539

2016-04-05T05:39:58.000Z

2022-03-23T20:47:52.000Z

# -*- coding: utf-8 -*- # Copyright 2015 Donne Martin. 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. A copy of # the License is located at # # http://www.apache.org/licenses/LICENSE-2.0 # # or in the "license" file accompanying this file. This file 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. formatted_events = u'\x1b[35m 1. \x1b[0mdonnemartin \x1b[0m\x1b[32mcommented on commit \x1b[0m\x1b[36mAAA23e2\x1b[0m\x1b[32m at \x1b[0m\x1b[36muser1/repo1\x1b[0m\x1b[33m (just now)\x1b[0m\n \x1b[36m\x1b[0mfoo\x1b[0m\n\x1b[35m 2. \x1b[0mdonnemartin \x1b[0m\x1b[32mcreated\x1b[0m\x1b[32m branch\x1b[0m\x1b[36m master\x1b[0m\x1b[32m at \x1b[0m\x1b[36muser1/repo1\x1b[0m\x1b[33m (just now)\x1b[0m\n \x1b[36m\x1b[0m\x1b[0m\n\x1b[35m 3. \x1b[0mdonnemartin \x1b[0m\x1b[32mfollowed \x1b[0m\x1b[36muser1/repo1\x1b[0m\x1b[33m (just now)\x1b[0m\n\x1b[35m 4. \x1b[0mdonnemartin \x1b[0m\x1b[32mforked\x1b[0m\x1b[36m user1/repo1\x1b[0m\x1b[33m (just now)\x1b[0m\n\x1b[35m 5. \x1b[0mdonnemartin \x1b[0m\x1b[32mcommented on \x1b[0m\x1b[36muser1/repo1#1\x1b[0m\x1b[33m (just now)\x1b[0m\n \x1b[36m\x1b[0mfoo\x1b[0m\n \x1b[36m\x1b[0mfoo\x1b[0m\n\x1b[35m 6. \x1b[0mdonnemartin \x1b[0m\x1b[32mclosed issue \x1b[0m\x1b[36muser1/repo1#1\x1b[0m\x1b[33m (just now)\x1b[0m\n \x1b[36m\x1b[0mfoo\x1b[0m\n\x1b[35m 7. \x1b[0mdonnemartin \x1b[0m\x1b[32mclosed pull request \x1b[0m\x1b[36muser1/repo1#1\x1b[0m\x1b[33m (just now)\x1b[0m\n \x1b[36m\x1b[0mfoo\x1b[0m\n\x1b[35m 8. \x1b[0mdonnemartin \x1b[0m\x1b[32mpushed to\x1b[0m\x1b[36m master\x1b[0m\x1b[32m at \x1b[0m\x1b[36muser1/repo1\x1b[0m\x1b[33m (just now)\x1b[0m\n \x1b[36m5ee4d1b: \x1b[0m\x1b[0mFix GitHubCli class docstring\x1b[0m\n \x1b[36mfc2309b: \x1b[0m\x1b[0mUpdate gh configure docstring\x1b[0m\n \x1b[36mdde19b7: \x1b[0m\x1b[0mUpdate gh create-comment docstring\x1b[0m\n\x1b[35m 9. \x1b[0mdonnemartin \x1b[0m\x1b[32mreleased \x1b[0m\x1b[36m0.5.0 \x1b[0m\x1b[32mat \x1b[0m\x1b[36muser1/repo1\x1b[0m\x1b[33m (just now)\x1b[0m\n\x1b[0m'

138.235294

1,770

0.714043

93f551e5469b1f02fbf0ae7bd5d72a1f50913ecb

6,617

py

Python

landlab/components/stream_power/examples/plot_concavities_forAGU.py

awickert/landlab

496de56717a5877db96f354a1b1285bfabe8b56f

[ "MIT" ]

1

2015-08-17T19:29:50.000Z

landlab/components/stream_power/examples/plot_concavities_forAGU.py

awickert/landlab

496de56717a5877db96f354a1b1285bfabe8b56f

[ "MIT" ]

1

2018-04-07T08:24:56.000Z

2018-04-07T13:52:03.000Z

landlab/components/stream_power/examples/plot_concavities_forAGU.py

awickert/landlab

496de56717a5877db96f354a1b1285bfabe8b56f

[ "MIT" ]

2

2017-07-03T20:21:13.000Z

2018-09-06T23:58:19.000Z

from pylab import figure, plot, xlabel, ylabel, title, loglog, show, gca, xlim, ylim, legend import numpy as np yunnan_propx = np.loadtxt('yunnan_proplength.txt') yunnan_theta = np.loadtxt('yunnan_theta.txt') fagaras_propx = np.loadtxt('fagaras_proplength.txt') fagaras_theta = np.loadtxt('fagaras_theta.txt') ladakh_propx = np.loadtxt('ladakh_proplength.txt') ladakh_theta = np.loadtxt('ladakh_theta.txt') #this data is u=0.0001->0.0005, no threshold, explicit, small random K var from 1e-6 pureDL_nothresh_propx = np.loadtxt('pureDLnothresh_proplength.txt') pureDL_nothresh_theta = np.loadtxt('pureDLnothresh_theta.txt') seddepNMG_propx = np.loadtxt('seddepNMG_proplength.txt') seddepNMG_theta = np.loadtxt('seddepNMG_theta.txt') stormsDL_thresh_propx = np.loadtxt('stormsDLthresh1e-1_proplength.txt') stormsDL_thresh_theta = np.loadtxt('stormsDLthresh1e-1_theta.txt') stormsDL_nothresh_propx = np.loadtxt('stormsDLnothresh_proplength.txt') stormsDL_nothresh_theta = np.loadtxt('stormsDLnothresh_theta.txt') bevel1seddep_propx = np.loadtxt('seddepNMG0.0001bevel_proplength.txt') bevel1seddep_theta = np.loadtxt('seddepNMG0.0001bevel_theta.txt') bevel2seddep_propx = np.loadtxt('seddepNMG0.0006bevel_proplength.txt') #no perturbation... we're not crossing the hump bevel2seddep_theta = np.loadtxt('seddepNMG0.0006bevel_theta.txt') aparabolicNMG2x10_propx = np.loadtxt('aparabolicNMG20001x10_proplength.txt') aparabolicNMG2x10_theta = np.loadtxt('aparabolicNMG20001x10_theta.txt') aparabolicNMG2x5_propx = np.loadtxt('aparabolicNMG20001x5_proplength.txt') aparabolicNMG2x5_theta = np.loadtxt('aparabolicNMG20001x5_theta.txt') aparabolicNMG4x100_propx = np.loadtxt('aparabolicNMG4000001x100_proplength.txt') aparabolicNMG4x100_theta = np.loadtxt('aparabolicNMG4000001x100_theta.txt') aparabolicNMG4x10_propx = np.loadtxt('aparabolicNMG4000001x10_proplength.txt') aparabolicNMG4x10_theta = np.loadtxt('aparabolicNMG4000001x10_theta.txt') aparabolicNMG5x10_propx = np.loadtxt('aparabolicNMG500001x10_proplength.txt') aparabolicNMG5x10_theta = np.loadtxt('aparabolicNMG500001x10_theta.txt') figure('concavities_just_one_sde') plot(seddepNMG_propx, seddepNMG_theta, 'rx-', label='sediment flux dependent') gca().set_yscale('log') xlim([0,1]) y_scale = gca().get_ylim() plot(np.array([0.,1.]), 0.5*np.ones(2.), 'k--') figure('concavities_just_one_DL') plot(pureDL_nothresh_propx, pureDL_nothresh_theta, 'b.-', label='pure detachment limited') gca().set_yscale('log') xlim([0,1]) ylim(y_scale) plot(np.array([0.,1.]), 0.5*np.ones(2.), 'k--') legend(loc=2) figure('concavities_one_sde_one_DL') plot(pureDL_nothresh_propx, pureDL_nothresh_theta, 'b.-', label='pure detachment limited') plot(seddepNMG_propx, seddepNMG_theta, 'rx-', label='sediment flux dependent') gca().set_yscale('log') xlim([0,1]) plot(np.array([0.,1.]), 0.5*np.ones(2.), 'k--') legend(loc=2) figure('all_models') plot(np.array([0.,1.]), 0.5*np.ones(2.), 'k--') plot(pureDL_nothresh_propx, pureDL_nothresh_theta, 'b.-', label='pureDL') plot(stormsDL_nothresh_propx, stormsDL_nothresh_theta, 'b+-', label='pureDL_storms') plot(stormsDL_thresh_propx, stormsDL_thresh_theta, 'b*-', label='pureDL_storms_thresh') plot(seddepNMG_propx, seddepNMG_theta, 'rx-', label='U=0.0001,K=5*10^-5,5*dU') plot(aparabolicNMG2x10_propx[1:], aparabolicNMG2x10_theta[1:], 'r+-', label='10*U,2*K,10*dU') plot(aparabolicNMG2x5_propx, aparabolicNMG2x5_theta, 'rv-', label='10*U,2*K,5*dU') plot(aparabolicNMG4x100_propx, aparabolicNMG4x100_theta, 'r<-', label='0.1*U,100*dU') plot(aparabolicNMG4x10_propx, aparabolicNMG4x10_theta, 'r>-', label='0.1*U,10*dU') plot(aparabolicNMG5x10_propx, aparabolicNMG5x10_theta, 'r^-', label='0.2*K,10*dU') plot(bevel1seddep_propx, bevel1seddep_theta, 'rp-', label='bevel_lowangle') plot(bevel2seddep_propx[1:], bevel2seddep_theta[1:], 'rh-', label='bevel_highangle') #first val is a bad pick gca().set_yscale('log') y_scale_all = gca().get_ylim() xlim([0,1]) legend(loc=2) figure('all_DL') plot(np.array([0.,1.]), 0.5*np.ones(2.), 'k--') plot(pureDL_nothresh_propx, pureDL_nothresh_theta, 'b.-', label='pureDL') plot(stormsDL_nothresh_propx, stormsDL_nothresh_theta, 'b+-', label='pureDL_storms') plot(stormsDL_thresh_propx, stormsDL_thresh_theta, 'b*-', label='pureDL_storms_thresh') gca().set_yscale('log') xlim([0,1]) ylim(y_scale_all) legend(loc=2) figure('all_model_just_Ladakh') plot(np.array([0.,1.]), 0.5*np.ones(2.), 'k--') plot(pureDL_nothresh_propx, pureDL_nothresh_theta, ':', color='0.6', label='pure detachment limited') plot(stormsDL_nothresh_propx, stormsDL_nothresh_theta, ':', color='0.6') plot(stormsDL_thresh_propx, stormsDL_thresh_theta, ':', color='0.6') plot(seddepNMG_propx, seddepNMG_theta, '-', color='0.3', label='sed flux dependent') plot(aparabolicNMG2x10_propx[1:], aparabolicNMG2x10_theta[1:], '-', color='0.3') plot(aparabolicNMG2x5_propx, aparabolicNMG2x5_theta, '-', color='0.3') plot(aparabolicNMG4x100_propx, aparabolicNMG4x100_theta, '-', color='0.3') plot(aparabolicNMG4x10_propx, aparabolicNMG4x10_theta, '-', color='0.3') plot(aparabolicNMG5x10_propx, aparabolicNMG5x10_theta, '-', color='0.3') plot(bevel1seddep_propx, bevel1seddep_theta, '-', color='0.3') plot(bevel2seddep_propx[1:], bevel2seddep_theta[1:], '-', color='0.3') #first val is a bad pick plot(ladakh_propx, ladakh_theta, 'bo', label='Ladakh field data') gca().set_yscale('log') xlim([0,1]) ylim(y_scale_all) legend(loc=2) figure('all_model_all_data') plot(np.array([0.,1.]), 0.5*np.ones(2.), 'k--') plot(pureDL_nothresh_propx, pureDL_nothresh_theta, ':', color='0.6', label='pure detachment limited') plot(stormsDL_nothresh_propx, stormsDL_nothresh_theta, ':', color='0.6') plot(stormsDL_thresh_propx, stormsDL_thresh_theta, ':', color='0.6') plot(seddepNMG_propx, seddepNMG_theta, '-', color='0.3', label='sed flux dependent') plot(aparabolicNMG2x10_propx[1:], aparabolicNMG2x10_theta[1:], '-', color='0.3') plot(aparabolicNMG2x5_propx, aparabolicNMG2x5_theta, '-', color='0.3') plot(aparabolicNMG4x100_propx, aparabolicNMG4x100_theta, '-', color='0.3') plot(aparabolicNMG4x10_propx, aparabolicNMG4x10_theta, '-', color='0.3') plot(aparabolicNMG5x10_propx, aparabolicNMG5x10_theta, '-', color='0.3') plot(bevel1seddep_propx, bevel1seddep_theta, '-', color='0.3') plot(bevel2seddep_propx[1:], bevel2seddep_theta[1:], '-', color='0.3') #first val is a bad pick plot(yunnan_propx, yunnan_theta, 'sr', label='Red River field data') plot(ladakh_propx, ladakh_theta, 'bo', label='Ladakh field data') plot(fagaras_propx, fagaras_theta, 'vg', label='Fagaras field data') gca().set_yscale('log') xlim([0,1]) ylim(y_scale_all) legend(loc=2)

53.796748

118

0.767115

f883ede988d8c7ff74636ec5037471134c42eda6

6,946

py

Python

lib/yaml/reader.py

pflarr/pyyaml

239110c403da1068498591e0c3bbff12cfc121ae

[ "MIT" ]

2

2018-04-27T22:12:50.000Z

2020-11-27T23:32:06.000Z

lib/yaml/reader.py

pflarr/pyyaml

239110c403da1068498591e0c3bbff12cfc121ae

[ "MIT" ]

null

lib/yaml/reader.py

pflarr/pyyaml

239110c403da1068498591e0c3bbff12cfc121ae

[ "MIT" ]

2

2020-01-29T20:36:20.000Z

2021-03-08T02:05:35.000Z

# This module contains abstractions for the input stream. You don't have to # looks further, there are no pretty code. # # We define two classes here. # # Mark(source, line, column) # It's just a record and its only use is producing nice error messages. # Parser does not use it for any other purposes. # # Reader(source, data) # Reader determines the encoding of `data` and converts it to unicode. # Reader provides the following methods and attributes: # reader.peek(length=1) - return the next `length` characters # reader.forward(length=1) - move the current position to `length` characters. # reader.index - the number of the current character. # reader.line, stream.column - the line and the column of the current character. from __future__ import unicode_literals, division, print_function __all__ = ['Reader', 'ReaderError'] from .error import YAMLError, Mark import codecs, re, sys class ReaderError(YAMLError): def __init__(self, name, position, character, encoding, reason): self.name = name self.character = character self.position = position self.encoding = encoding self.reason = reason def __str__(self): if isinstance(self.character, bytes): return "'%s' codec can't decode byte #x%02x: %s\n" \ " in \"%s\", position %d" \ % (self.encoding, ord(self.character), self.reason, self.name, self.position) else: return "unacceptable character #x%04x: %s\n" \ " in \"%s\", position %d" \ % (self.character, self.reason, self.name, self.position) class Reader(object): # Reader: # - determines the data encoding and converts it to a unicode string, # - checks if characters are in allowed range, # - adds '\0' to the end. # Reader accepts # - a `bytes` object, # - a `str` object, # - a file-like object with its `read` method returning `str`, # - a file-like object with its `read` method returning `unicode`. # Yeah, it's ugly and slow. def __init__(self, stream): self.name = None self.stream = None self.stream_pointer = 0 self.eof = True self.buffer = '' self.pointer = 0 self.raw_buffer = None self.raw_decode = None self.encoding = None self.index = 0 self.line = 0 self.column = 0 if isinstance(stream, str): self.name = "<unicode string>" self.check_printable(stream) self.buffer = stream+'\0' elif isinstance(stream, bytes): self.name = "<byte string>" self.raw_buffer = stream self.determine_encoding() else: self.stream = stream self.name = getattr(stream, 'name', "<file>") self.eof = False self.raw_buffer = None self.determine_encoding() def peek(self, index=0): try: return self.buffer[self.pointer+index] except IndexError: self.update(index+1) return self.buffer[self.pointer+index] def prefix(self, length=1): if self.pointer+length >= len(self.buffer): self.update(length) return self.buffer[self.pointer:self.pointer+length] def forward(self, length=1): if self.pointer+length+1 >= len(self.buffer): self.update(length+1) while length: ch = self.buffer[self.pointer] self.pointer += 1 self.index += 1 if ch in '\n\x85\u2028\u2029' \ or (ch == '\r' and self.buffer[self.pointer] != '\n'): self.line += 1 self.column = 0 elif ch != '\uFEFF': self.column += 1 length -= 1 def get_mark(self): if self.stream is None: return Mark(self.name, self.index, self.line, self.column, self.buffer, self.pointer) else: return Mark(self.name, self.index, self.line, self.column, None, None) def determine_encoding(self): while not self.eof and (self.raw_buffer is None or len(self.raw_buffer) < 2): self.update_raw() if isinstance(self.raw_buffer, bytes): if self.raw_buffer.startswith(codecs.BOM_UTF16_LE): self.raw_decode = codecs.utf_16_le_decode self.encoding = 'utf-16-le' elif self.raw_buffer.startswith(codecs.BOM_UTF16_BE): self.raw_decode = codecs.utf_16_be_decode self.encoding = 'utf-16-be' else: self.raw_decode = codecs.utf_8_decode self.encoding = 'utf-8' self.update(1) NON_PRINTABLE = re.compile('[^\x09\x0A\x0D\x20-\x7E\x85\xA0-\uD7FF\uE000-\uFFFD\U00010000-\U0010ffff]') def check_printable(self, data): match = self.NON_PRINTABLE.search(data) if match: character = match.group() position = self.index+(len(self.buffer)-self.pointer)+match.start() raise ReaderError(self.name, position, ord(character), 'unicode', "special characters are not allowed") def update(self, length): if self.raw_buffer is None: return self.buffer = self.buffer[self.pointer:] self.pointer = 0 while len(self.buffer) < length: if not self.eof: self.update_raw() if self.raw_decode is not None: try: data, converted = self.raw_decode(self.raw_buffer, 'strict', self.eof) except UnicodeDecodeError as exc: character = self.raw_buffer[exc.start] if self.stream is not None: position = self.stream_pointer-len(self.raw_buffer)+exc.start else: position = exc.start raise ReaderError(self.name, position, character, exc.encoding, exc.reason) else: data = self.raw_buffer converted = len(data) self.check_printable(data) self.buffer += data self.raw_buffer = self.raw_buffer[converted:] if self.eof: self.buffer += '\0' self.raw_buffer = None break def update_raw(self, size=4096): data = self.stream.read(size) if self.raw_buffer is None: self.raw_buffer = data else: self.raw_buffer += data self.stream_pointer += len(data) if not data: self.eof = True #try: # import psyco # psyco.bind(Reader) #except ImportError: # pass

35.804124

107

0.560035

08bf20f42b00ff927888ab8a1ab64f9b0a98eaba

1,586

py

Python

python/testData/inspections/PyArgumentListInspection/badarglist.py

Sajadrahimi/intellij-community

ab9ff612dde3ee94ecae33cbc0ea639fa51550d4

[ "Apache-2.0" ]

null

python/testData/inspections/PyArgumentListInspection/badarglist.py

Sajadrahimi/intellij-community

ab9ff612dde3ee94ecae33cbc0ea639fa51550d4

[ "Apache-2.0" ]

null

python/testData/inspections/PyArgumentListInspection/badarglist.py

Sajadrahimi/intellij-community

ab9ff612dde3ee94ecae33cbc0ea639fa51550d4

[ "Apache-2.0" ]

1

2022-01-02T19:58:08.000Z

# bad argument list samples class A: def foo(self, x, y): pass # no self, but so what def bar(one, two): pass a = A() a.foo(1,2) a.bar(<warning descr="Parameter 'two' unfilled">)</warning>; def f1(): pass f1() f1<warning descr="Unexpected argument(s)">(<warning descr="Unexpected argument">1</warning>)</warning> f1<warning descr="Unexpected argument(s)">(<warning descr="Unexpected argument">a = 1</warning>)</warning> def f2(a): pass f2(<warning descr="Parameter 'a' unfilled">)</warning> # ok, fail f2(1) # ok, pass f2<warning descr="Unexpected argument(s)">(1, <warning descr="Unexpected argument">2</warning>)</warning> # ok, fail f2(a = 1) # ok, pass f2(<warning descr="Unexpected argument">b = 1</warning><warning descr="Parameter 'a' unfilled">)</warning> # ok, fail f2<warning descr="Unexpected argument(s)">(a = 1, <warning descr="Unexpected argument">b = 2</warning>)</warning> # ok, fail def f3(a, b): pass f3(1, 2) f3<warning descr="Unexpected argument(s)">(1, 2, <warning descr="Unexpected argument">3</warning>)</warning> f3(b=2, a=1) f3<warning descr="Unexpected argument(s)">(b=1, <error descr="Keyword argument repeated">b=2</error>, a=1)</warning> f3(1, b=2) f3(a=1, <error descr="Positional argument after keyword argument">2</error><warning descr="Parameter 'b' unfilled">)</warning> def f4(a, *b): pass f4(1) f4(1, 2) f4(1, 2, 3) f4(1, *(2, 3)) f4(*(1,2,3)) f4(a=1, <error descr="Positional argument after keyword argument">2</error>, <error descr="Positional argument after keyword argument">3</error>)

28.321429

145

0.664565

9d7bb559e11f6498887ac670402f66515d1c2a29

11,578

py

Python

code/python/StocksAPIforDigitalPortals/v2/fds/sdk/StocksAPIforDigitalPortals/model/inline_response2005_data_reported_key_figures_first_fiscal_year_ratios_enterprise_value_ebitda.py

factset/enterprise-sdk

3fd4d1360756c515c9737a0c9a992c7451d7de7e

[ "Apache-2.0" ]

6

2022-02-07T16:34:18.000Z

2022-03-30T08:04:57.000Z

code/python/StocksAPIforDigitalPortals/v2/fds/sdk/StocksAPIforDigitalPortals/model/inline_response2005_data_reported_key_figures_first_fiscal_year_ratios_enterprise_value_ebitda.py

factset/enterprise-sdk

3fd4d1360756c515c9737a0c9a992c7451d7de7e

[ "Apache-2.0" ]

2

2022-02-07T05:25:57.000Z

2022-03-07T14:18:04.000Z

code/python/StocksAPIforDigitalPortals/v2/fds/sdk/StocksAPIforDigitalPortals/model/inline_response2005_data_reported_key_figures_first_fiscal_year_ratios_enterprise_value_ebitda.py

factset/enterprise-sdk

3fd4d1360756c515c9737a0c9a992c7451d7de7e

[ "Apache-2.0" ]

null

""" Prime Developer Trial No description provided (generated by Openapi Generator https://github.com/openapitools/openapi-generator) # noqa: E501 The version of the OpenAPI document: v1 Generated by: https://openapi-generator.tech """ import re # noqa: F401 import sys # noqa: F401 from fds.sdk.StocksAPIforDigitalPortals.model_utils import ( # noqa: F401 ApiTypeError, ModelComposed, ModelNormal, ModelSimple, cached_property, change_keys_js_to_python, convert_js_args_to_python_args, date, datetime, file_type, none_type, validate_get_composed_info, OpenApiModel ) from fds.sdk.StocksAPIforDigitalPortals.exceptions import ApiAttributeError class InlineResponse2005DataReportedKeyFiguresFirstFiscalYearRatiosEnterpriseValueEbitda(ModelNormal): """NOTE: This class is auto generated by OpenAPI Generator. Ref: https://openapi-generator.tech Do not edit the class manually. Attributes: allowed_values (dict): The key is the tuple path to the attribute and the for var_name this is (var_name,). The value is a dict with a capitalized key describing the allowed value and an allowed value. These dicts store the allowed enum values. attribute_map (dict): The key is attribute name and the value is json key in definition. discriminator_value_class_map (dict): A dict to go from the discriminator variable value to the discriminator class name. validations (dict): The key is the tuple path to the attribute and the for var_name this is (var_name,). The value is a dict that stores validations for max_length, min_length, max_items, min_items, exclusive_maximum, inclusive_maximum, exclusive_minimum, inclusive_minimum, and regex. additional_properties_type (tuple): A tuple of classes accepted as additional properties values. """ allowed_values = { } validations = { } @cached_property def additional_properties_type(): """ This must be a method because a model may have properties that are of type self, this must run after the class is loaded """ return (bool, date, datetime, dict, float, int, list, str, none_type,) # noqa: E501 _nullable = False @cached_property def openapi_types(): """ This must be a method because a model may have properties that are of type self, this must run after the class is loaded Returns openapi_types (dict): The key is attribute name and the value is attribute type. """ return { 'minimum': (float,), # noqa: E501 'maximum': (float,), # noqa: E501 } @cached_property def discriminator(): return None attribute_map = { 'minimum': 'minimum', # noqa: E501 'maximum': 'maximum', # noqa: E501 } read_only_vars = { } _composed_schemas = {} @classmethod @convert_js_args_to_python_args def _from_openapi_data(cls, *args, **kwargs): # noqa: E501 """InlineResponse2005DataReportedKeyFiguresFirstFiscalYearRatiosEnterpriseValueEbitda - a model defined in OpenAPI Keyword Args: _check_type (bool): if True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True _path_to_item (tuple/list): This is a list of keys or values to drill down to the model in received_data when deserializing a response _spec_property_naming (bool): True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default) _configuration (Configuration): the instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done. _visited_composed_classes (tuple): This stores a tuple of classes that we have traveled through so that if we see that class again we will not use its discriminator again. When traveling through a discriminator, the composed schema that is is traveled through is added to this set. For example if Animal has a discriminator petType and we pass in "Dog", and the class Dog allOf includes Animal, we move through Animal once using the discriminator, and pick Dog. Then in Dog, we will make an instance of the Animal class but this time we won't travel through its discriminator because we passed in _visited_composed_classes = (Animal,) minimum (float): Minimum value.. [optional] # noqa: E501 maximum (float): Maximum value.. [optional] # noqa: E501 """ _check_type = kwargs.pop('_check_type', True) _spec_property_naming = kwargs.pop('_spec_property_naming', False) _path_to_item = kwargs.pop('_path_to_item', ()) _configuration = kwargs.pop('_configuration', None) _visited_composed_classes = kwargs.pop('_visited_composed_classes', ()) self = super(OpenApiModel, cls).__new__(cls) if args: raise ApiTypeError( "Invalid positional arguments=%s passed to %s. Remove those invalid positional arguments." % ( args, self.__class__.__name__, ), path_to_item=_path_to_item, valid_classes=(self.__class__,), ) self._data_store = {} self._check_type = _check_type self._spec_property_naming = _spec_property_naming self._path_to_item = _path_to_item self._configuration = _configuration self._visited_composed_classes = _visited_composed_classes + (self.__class__,) for var_name, var_value in kwargs.items(): if var_name not in self.attribute_map and \ self._configuration is not None and \ self._configuration.discard_unknown_keys and \ self.additional_properties_type is None: # discard variable. continue setattr(self, var_name, var_value) return self required_properties = set([ '_data_store', '_check_type', '_spec_property_naming', '_path_to_item', '_configuration', '_visited_composed_classes', ]) @convert_js_args_to_python_args def __init__(self, *args, **kwargs): # noqa: E501 """InlineResponse2005DataReportedKeyFiguresFirstFiscalYearRatiosEnterpriseValueEbitda - a model defined in OpenAPI Keyword Args: _check_type (bool): if True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True _path_to_item (tuple/list): This is a list of keys or values to drill down to the model in received_data when deserializing a response _spec_property_naming (bool): True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default) _configuration (Configuration): the instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done. _visited_composed_classes (tuple): This stores a tuple of classes that we have traveled through so that if we see that class again we will not use its discriminator again. When traveling through a discriminator, the composed schema that is is traveled through is added to this set. For example if Animal has a discriminator petType and we pass in "Dog", and the class Dog allOf includes Animal, we move through Animal once using the discriminator, and pick Dog. Then in Dog, we will make an instance of the Animal class but this time we won't travel through its discriminator because we passed in _visited_composed_classes = (Animal,) minimum (float): Minimum value.. [optional] # noqa: E501 maximum (float): Maximum value.. [optional] # noqa: E501 """ _check_type = kwargs.pop('_check_type', True) _spec_property_naming = kwargs.pop('_spec_property_naming', False) _path_to_item = kwargs.pop('_path_to_item', ()) _configuration = kwargs.pop('_configuration', None) _visited_composed_classes = kwargs.pop('_visited_composed_classes', ()) if args: raise ApiTypeError( "Invalid positional arguments=%s passed to %s. Remove those invalid positional arguments." % ( args, self.__class__.__name__, ), path_to_item=_path_to_item, valid_classes=(self.__class__,), ) self._data_store = {} self._check_type = _check_type self._spec_property_naming = _spec_property_naming self._path_to_item = _path_to_item self._configuration = _configuration self._visited_composed_classes = _visited_composed_classes + (self.__class__,) for var_name, var_value in kwargs.items(): if var_name not in self.attribute_map and \ self._configuration is not None and \ self._configuration.discard_unknown_keys and \ self.additional_properties_type is None: # discard variable. continue setattr(self, var_name, var_value) if var_name in self.read_only_vars: raise ApiAttributeError(f"`{var_name}` is a read-only attribute. Use `from_openapi_data` to instantiate " f"class with read only attributes.")

44.530769

124

0.578943

76bc248ecd134f17b32444962d08929ebb3edca2

1,107

py

Python

Machine Learning Algorithms/Section 2 - Regression/2. Multiple Linear Regression/multiple_linear_regression.py

Hrishi97/All-About-Machine-Learning

e141951bc629cbd8c3068cc9d284cb40478d2d75

[ "Unlicense" ]

389

2021-06-13T13:57:13.000Z

2022-03-30T07:49:47.000Z

multiple_linear_regression.py

rishikonapure/-100daysofmlcode

50ea710eb197287ae1e538c8528c88c4503d9f9a

[ "MIT" ]

23

2020-07-21T04:54:58.000Z

2022-03-08T23:30:06.000Z

multiple_linear_regression.py

rishikonapure/-100daysofmlcode

50ea710eb197287ae1e538c8528c88c4503d9f9a

[ "MIT" ]

109

2021-06-13T14:26:21.000Z

2022-03-29T11:55:27.000Z

# Multiple Linear Regression # Importing the libraries import numpy as np import matplotlib.pyplot as plt import pandas as pd # Importing the dataset dataset = pd.read_csv('50_Startups.csv') X = dataset.iloc[:, :-1].values y = dataset.iloc[:, -1].values print(X) # Encoding categorical data from sklearn.compose import ColumnTransformer from sklearn.preprocessing import OneHotEncoder ct = ColumnTransformer(transformers=[('encoder', OneHotEncoder(), [3])], remainder='passthrough') X = np.array(ct.fit_transform(X)) print(X) # Splitting the dataset into the Training set and Test set from sklearn.model_selection import train_test_split X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.2, random_state = 0) # Training the Multiple Linear Regression model on the Training set from sklearn.linear_model import LinearRegression regressor = LinearRegression() regressor.fit(X_train, y_train) # Predicting the Test set results y_pred = regressor.predict(X_test) np.set_printoptions(precision=2) print(np.concatenate((y_pred.reshape(len(y_pred),1), y_test.reshape(len(y_test),1)),1))

33.545455

97

0.785005

1141c9a9df8b6d197d8d175dc525309ee4a1e479

14,846

py

Python

analyze/analyzeMinutes.py

Aquaware/MarketAlertWithXM

6cfbc26f7b32880ff9a6911599b4a9614345e505

[ "MIT" ]

null

analyze/analyzeMinutes.py

Aquaware/MarketAlertWithXM

6cfbc26f7b32880ff9a6911599b4a9614345e505

[ "MIT" ]

null

analyze/analyzeMinutes.py

Aquaware/MarketAlertWithXM

6cfbc26f7b32880ff9a6911599b4a9614345e505

[ "MIT" ]

null

# -*- coding: utf-8 -*- import os import sys sys.path.append(os.path.join(os.path.dirname(__file__), '../common')) import pandas as pd import numpy as np from datetime import date, datetime, timedelta from Timeframe import Timeframe from CandlePlot import CandlePlot, BandPlot, makeFig import matplotlib.pyplot as plt import matplotlib.gridspec as gridspec import calendar from ta.trend import SMAIndicator import TradeSimulation TIME = 'time' OPEN = 'open' HIGH = 'high' LOW = 'low' CLOSE = 'close' DIF = 'close-open' SIGMA = 'sigma' DMA_SLOW = 'dma_slow' DMA_FAST = 'dma_fast' BID = 'bid' ASK = 'ask' MID = 'mid' SPREAD = 'spread' THRESHOLD = 'threshold' DELAY = 'delay' LOSSCUT = 'loscut' def weekday(year, month, day): d = date(year, month, day) day_index = d.weekday() return calendar.day_name[day_index][:3] def dirPath(root, stock, year): path = root + stock + '/' + str(year).zfill(4) + '/' return path def filename(stock, year, month, day): path = stock + '_Tick_' + str(year).zfill(4) + '-' + str(month).zfill(2) + '-' + str(day).zfill(2) + '.csv' return path def timeFilter(tohlc_dic, year, month, day, hourmins): time = tohlc_dic[TIME] try: t1 = datetime(year, month, day, hourmins[0][0], hourmins[0][1]) t2 = datetime(year, month, day, hourmins[1][0], hourmins[1][1]) if t1 > t2: t2 += timedelta(days=1) if t1 > time[-1] or t2 < time[0]: return (0, None) except: return (0, None) begin = None stop = None for (i, t) in enumerate(time): if begin is None: if t >= t1: begin = i else: if t >= t2: stop = i break if stop is None: stop = len(time) if begin is None or stop is None: return (0, None) dic = {} dic[TIME] = time[begin:stop] dic[OPEN] = tohlc_dic[OPEN][begin: stop] dic[HIGH] = tohlc_dic[HIGH][begin: stop] dic[LOW] = tohlc_dic[LOW][begin: stop] dic[CLOSE] = tohlc_dic[CLOSE][begin: stop] return (stop - begin, dic) def candle(prices): o = prices[0] c = prices[-1] h = np.max(prices) l = np.min(prices) return [o, h, l, c] def tohlc2ohlc(tohlc): time = [] ohlc = [] for value in tohlc: time.append(value[0]) ohlc.append(value[1:]) return (time, ohlc) def separate(tohlc, timeframe): time = None data = [] open = None high = None low = None close = None for t, o, h, l, c in tohlc: tt = timeframe.roundTime(t) if time is None: time = tt open = o high = h low = l close = c else: if tt > time: data.append([time, open, high, low, close]) time = tt open = o high = h low = l close = c else: if h > high: high = h if l < low: low = l close = c data.append([time, open, high, low, close]) time = [] open = [] high = [] low = [] close = [] dif = [] for t, o, h, l, c in data: if t is None or c is None or o is None: continue time.append(t) open.append(o) high.append(h) low.append(l) close.append(c) dif.append(c - o) dic = {} dic[TIME] = time dic[OPEN] = open dic[HIGH] = high dic[LOW] = low dic[CLOSE] = close dic[DIF] = dif return dic def SMA(array, window): ind = SMAIndicator(close=pd.Series(array), window=window) close = ind.sma_indicator() return close.values.tolist() def drawGraph(market, title, timeframe, tohlc, display_time_range, trades): fig = plt.figure(figsize=(14, 6)) gs = gridspec.GridSpec(6, 1) #縦,横 ax1 = plt.subplot(gs[0:5, 0]) ax2 = plt.subplot(gs[5:6, 0]) time = tohlc[TIME] open = tohlc[OPEN] high = tohlc[HIGH] low = tohlc[LOW] close = tohlc[CLOSE] ohlc = [] for o, h, l, c in zip(open, high, low, close): ohlc.append([o, h, l, c]) if display_time_range is None: t_range = (time[0], time[-1]) else: tt = time[0] t0 = datetime(tt.year, tt.month, tt.day, display_time_range[0][0], display_time_range[0][1]) t1 = datetime(tt.year, tt.month, tt.day, display_time_range[1][0], display_time_range[1][1]) if t1 < t0: t1 += timedelta(days=1) t_range = [t0, t1] graph1 = CandlePlot(fig, ax1, title) graph1.xlimit(t_range) graph1.drawCandle(time, ohlc, timerange=t_range) windows =[3, 5, 7, 10, 20] colors = ['salmon', 'red', 'gray', 'yellowgreen', 'green'] mas = {} for w, color in zip(windows, colors): ma = SMA(close, w) mas['MA' + str(w)] = ma if color is not None: graph1.drawLine(time, ma, color=color, label='MA' + str(w)) for trade in trades: [status, topen, open_price, tclose, close_price, profit1, tpeak, peak_price, profit2] = trade if status > 0: color = 'green' marker = '^' else: color = 'red' marker = 'v' graph1.drawMarker(topen, open_price, marker, color, markersize=10) graph1.drawMarker(tpeak, peak_price, 'x', color, markersize=10) flag = [] for o, c in zip(open, close): try: v = (c - o) / o * 100.0 except: v = 0 flag.append(v) graph2 = BandPlot(fig, ax2, 'Flag') graph2.xlimit(t_range) graph2.drawLine(time, flag, timerange=t_range) #ax1.legend() #ax2.legend() def priceRange(ohlc): p = [] for o, h, l, c in ohlc: p.append(c) return (max(p), min(p)) def drawByDay(market, tf, ticks, year, month): for day in range(1, 32): count, data = timeFilter(ticks, year, month, day, [[21, 30], [4, 30]]) #ticks = fromDb(market, year, month, day, [22, 23], None) if count > 100: (tohlc, spreads) = ticks2TOHLC(tf, data) time, ohlc = tohlc2ohlc(tohlc) price_range = priceRange(ohlc) title = market + ' (' + tf.symbol + ') ' + str(year) + '-' + str(month) + '-' + str(day) + ' (' + weekday(year, month, day)[:3]+ ') Price Range: ' + str(price_range[0] - price_range[1]) drawGraph(title, tf, time, ohlc) def showByDay(market, year, month, day, timeframe, display_time_range, tohlc_dic): title = market + ' ' + str(year) + '-' + str(month) + '-' + str(day) + ' (' + weekday(year, month, day)[:3] + ') ' count, dic = timeFilter(tohlc_dic, year, month, day, [[8, 0], [7, 0]]) if count > 100: drawGraph(market, title, timeframe, dic, display_time_range) def importClickSec(dir_path, market, year, month): ym = str(year) + str(month).zfill(2) dir_path = dir_path + '/' + market + '/' + market + '_' + ym + '/' + ym + '/' tohlc = [] for day in range(1, 32): file_name = market + '_' + ym + str(day).zfill(2) + '.csv' path = os.path.join(dir_path, file_name) try: df0 = pd.read_csv(path, encoding='sjis') df = df0[['日時', '始値(BID)', '高値(BID)', '安値(BID)', '終値(BID)']] values= df.values.tolist() except: continue for value in values: [tint, o, h, l, c] = value t = str(tint) time = datetime(int(t[0:4]), int(t[4:6]), int(t[6:8]), int(t[8:10]), int(t[10:12])) tohlc.append([time, float(value[1]), float(value[2]), float(value[3]), float(value[4])]) return tohlc def dayRange(year, month): if month == 12: tend = datetime(year + 1, 1, 1) else: tend = datetime(year, month + 1, 1) days = [] for day in range(1, 32): try: t = datetime(year, month, day) except: break if t < tend: days.append(day) else: break return days def show(market, timeframe, year, month): display_time_range = [[8, 0], [7, 0]] tohlc = importClickSec("../click_sec_data", market, year, month) tohlc_dic = separate(tohlc, timeframe) for day in dayRange(year, month): showByDay(market, year, month, day, timeframe, display_time_range, tohlc_dic) def filterUpper(array, threshold): out = [] for v in array: if v > threshold: out.append(v) return out def filterLower(array, threshold): out = [] for v in array: if v < threshold: out.append(v) return out def rangeHistogram(market, timeframe): for year in [2019, 2020, 2021]: ranges = [] for month in range(1, 13): tohlc = importClickSec("../click_sec_data", market, year, month) tohlc_dic = separate(tohlc, timeframe) for (o, c) in zip(tohlc_dic[OPEN], tohlc_dic[CLOSE]): ranges.append((c - o) / o * 100) higher = filterUpper(ranges, 0.3) lower = filterLower(ranges, -0.3) vmin = np.min(ranges) vmax = np.max(ranges) fig, axes= plt.subplots(1,2) axes[1].hist(higher, bins=10) #axes[1].set_title(market + "-" + timeframe.symbol + " " + str(year) + " Min: " + str(vmin) + " Max: " + str(vmax)) axes[0].hist(lower, bins=10) axes[0].set_title(market + "-" + timeframe.symbol + " " + str(year) + " Min: " + str(vmin)[:7] + " Max: " + str(vmax)[:7]) fig.show() def judge(rng, threshold): lower = np.min(threshold) upper = np.max(threshold) if rng > lower and rng < upper: return True else: return False def longBarLowerStrategy(market, timeframe, threshold, after_minutes): out = [] for year in [2019, 2020, 2021]: longBars = [] tend = None values = [] for month in range(1, 13): tohlc = importClickSec("../click_sec_data", market, year, month) tohlc_dic = separate(tohlc, timeframe) for (t, o, c) in zip(tohlc_dic[TIME], tohlc_dic[OPEN], tohlc_dic[CLOSE]): rng = (c - o) / o * 100 if tend is None: if judge(rng, threshold): tend = t + timedelta(minutes= after_minutes) values.append([t, o, c]) else: if t > tend: longBars.append(values) tend = None values = [] else: values.append([t, o, c]) print('*** Year ', year) for longBar in longBars: closes = [] begin = None for i, (t, o, c) in enumerate(longBar): if i == 0: begin = [t, c] print('Begin: t: ', t, 'Range: ', (c - o) / o * 100, 'Close:', c) else: closes.append(c) if i == len(longBar)-1: end = [t, c] print(' -> End: t: ', t, 'close: ', c, 'Profit:', c - begin[1]) if len(closes) > 0: minv = np.min(closes) maxv = np.max(closes) is_short = threshold[0] < 0 if is_short: profit = minv - begin[1] else: profit = maxv - begin[1] print (' -> Min: ', minv, maxv, 'profit: ', profit) out.append([year, begin[0], begin[1], end[0], end[1], end[1] - begin[1], minv, maxv, profit]) print ('') data = [] s = 0.0 for d in out: s += d[-1] dd = d dd.append(s) data.append(dd) df = pd.DataFrame(data=data, columns=['Year', 'tbegin', 'close', 'tend', 'close', 'profit', 'close-min', 'close-max', 'profit', 'profit-sum']) #df.to_excel(market + 'LongBarStrategy.xlsx', index=False) return s def test1(): market = "JP225" timeframe = Timeframe("M10") year = 2021 month = 10 show(market, timeframe, year, month) def analyze(): market = "SPOT_GOLD" #"CHNA50" #"US30" #WTI" #SPOT_GOLD" #"JP225" tf = "M5" timeframe = Timeframe(tf) #rangeHistogram(market, timeframe) r1 = [[0.3, 0.6], [0.4, 0.6], [0.5, 0.7], [-0.3, -0.6], [-0.4, -0.6], [-0.5, -0.7]] r2 = [[0.5, 1.0], [1.0, 2.0], [3.0, 5.0], [-0.5, -1.0], [-1.0, -2.0], [-3.0, -5.0]] out = [] for threshold in r1: for delay in [15, 30, 60, 90, 120]: profit = longBarLowerStrategy(market, timeframe, threshold, delay) out.append([market, tf, threshold, delay, profit]) df = pd.DataFrame(data= out, columns=['Market', 'Timeframe', 'threshold', 'delay', 'profit']) df.to_excel('./docs/' + market + '-LongBarStragegySummary.xlsx', index=False) def trade(): market = "SPOT_GOLD" #"JP225" #"CHNA50" #"US30" #WTI" #SPOT_GOLD" #"JP225" tf = "M15" timeframe = Timeframe(tf) data_time_range = [[8, 0], [7, 0]] params = [ {THRESHOLD: [0.25, 0.5], DELAY: 60, LOSSCUT: 0.5}, {THRESHOLD: [-0.25, -0.5], DELAY: 60, LOSSCUT: 0.5}] out = [] for year in [2019]: #, 2020, 2021]: for month in range(1, 13): tohlc = importClickSec("../click_sec_data", market, year, month) tohlc_dic = separate(tohlc, timeframe) for day in dayRange(year, month): date_str = str(year) + '-' + str(month) + '-' + str(day) count, dic = timeFilter(tohlc_dic, year, month, day, data_time_range) if count > 50: sim = TradeSimulation.Simulation(dic, timeframe, data_time_range) trades = [] for param in params: profit, trade = sim.runLongBar(param) if len(trade) > 0: out += trade trades += trade title = market + " " + date_str drawGraph(market, title, timeframe, dic, data_time_range, trades) #df = pd.DataFrame(data=out, columns=['Status', 'OpenTime', 'OpenPrice', 'CloseTime', 'ClosePrice', 'Profit1', 'MaxTime', 'MaxPrice', 'profit2']) #df.to_excel('./docs/' + market + '-tradeSummary.xlsx', index=False) if __name__ == '__main__': trade()

31.926882

201

0.505725

2fa2e1721327d71cd3cc1aefb5183d97a913170a

1,986

py

Python

backend/api/admin/resource/claritylist.py

blodstone/harness

048a15d5f971b5b87cf6e80db98c7f9dd7a2cdbc

[ "MIT" ]

null

backend/api/admin/resource/claritylist.py

blodstone/harness

048a15d5f971b5b87cf6e80db98c7f9dd7a2cdbc

[ "MIT" ]

null

backend/api/admin/resource/claritylist.py

blodstone/harness

048a15d5f971b5b87cf6e80db98c7f9dd7a2cdbc

[ "MIT" ]

null

import urllib.parse from flask import request from flask_restful import Resource, abort from backend.model.project import ClarityProject, ClarityProjectSchema from backend.model.project_status import ProjectStatus from backend.model import ma class ProgressObject(object): def __init__(self, total, current): self.total = total self.current = current class ProgressSchema(ma.Schema): class Meta: fields = ('total', 'current') class ClarityUIObject(object): def __init__(self, no, project, link, progress): self.no = no self.project = project self.link = link self.progress = progress class ClarityUISchema(ma.Schema): class Meta: # Fields to expose fields = ('no', 'project', 'link', 'progress') project = ma.Nested(ClarityProjectSchema) progress = ma.Nested(ProgressSchema) class ClarityListResource(Resource): def __get_project_progress(self, project): total = ProjectStatus.query.filter_by(clarity_proj_id=project.id).count() current = ProjectStatus.query.filter_by( clarity_proj_id=project.id, is_finished=True).count() return ProgressObject(total=total, current=current) def get(self): projects = ClarityProject.query.all() if len(projects) == 0: return abort(404, message=f"No clarity projects.") else: schema = ClarityUISchema(many=True) clarity_ui_objs = [] for no, project in enumerate(projects): progress = self.__get_project_progress(project) link = urllib.parse.urljoin( request.host_url, f"#/Clarity/{project.id}" ) clarity_ui_obj = ClarityUIObject( no=no+1, project=project, link=link, progress=progress) clarity_ui_objs.append(clarity_ui_obj) return schema.dump(clarity_ui_objs)

32.557377

81

0.638469

9a8a72241d1d1a945bb43b6e7167fa7a16148f29

17,540

py

Python

psat_server_web/atlas/atlas/dbviews.py

genghisken/psat-server-web

63c697f1d08dc2173328d3018aadf8efc1e8e14f

[ "MIT" ]

null

psat_server_web/atlas/atlas/dbviews.py

genghisken/psat-server-web

63c697f1d08dc2173328d3018aadf8efc1e8e14f

[ "MIT" ]

11

2021-03-11T17:28:29.000Z

2022-01-05T11:35:14.000Z

psat_server_web/atlas/atlas/dbviews.py

genghisken/psat-server-web

63c697f1d08dc2173328d3018aadf8efc1e8e14f

[ "MIT" ]

null

from django.db import models #from atlas.utils import * from math import log10 from atlas.models import TcsCrossMatchesExternal, TcsDetectionLists, TcsImages from gkutils.commonutils import ra_to_sex, dec_to_sex, getFlagDefs, getDateFractionMJD, FLAGS, transform, J2000toGalactic class CustomLCPoints(models.Model): """CustomLCPoints. """ id = models.IntegerField(primary_key=True, db_column='id') mag = models.FloatField(db_column='mag') magerr = models.FloatField(db_column='magerr') mjd = models.FloatField(db_column='mjd') exptime = models.FloatField(db_column='exptime') filter = models.CharField(max_length=90, db_column='filter') zp = models.FloatField(db_column='zp') expname = models.CharField(max_length=90, db_column='expname') ra = models.FloatField(db_column='ra') dec = models.FloatField(db_column='dec') atlas_metadata_id = models.IntegerField(db_column='atlas_metadata_id') class CustomLCBlanks(models.Model): """CustomLCBlanks. """ id = models.IntegerField(primary_key=True, db_column='id') mjd = models.FloatField(db_column='mjd') exptime = models.FloatField(db_column='exptime') filter = models.CharField(max_length=90, db_column='filter') zp = models.FloatField(db_column='zp') expname = models.CharField(max_length=90, db_column='expname') filename = models.CharField(max_length=765, db_column='filename') input = models.CharField(max_length=765, db_column='input') reference = models.CharField(max_length=765, db_column='reference') pointing = models.CharField(max_length=765, db_column='pointing') class CustomFollowupLCData(models.Model): """CustomFollowupLCData. """ id = models.IntegerField(primary_key=True, db_column='id') transient_object_id = models.IntegerField(db_column='transient_object_id') mjd = models.FloatField(db_column='mjd') mag = models.FloatField(db_column='mag') magerr = models.FloatField(db_column='magerr') filter = models.CharField(max_length=90, db_column='filter') telescope_name = models.CharField(max_length=90, db_column='telescope_name') telescope_description = models.CharField(max_length=180, db_column='telescope_description') instrument_name = models.CharField(max_length=90, db_column='instrument_name') instrument_description = models.CharField(max_length=180, db_column='instrument_description') class FollowupRaw(models.Model): """FollowupRaw. """ rank = models.IntegerField(db_column='rank') id = models.BigIntegerField(primary_key=True, db_column='id') atlas_designation = models.CharField(max_length=60, db_column='atlas_designation') other_designation = models.CharField(max_length=60, db_column='other_designation') ra = models.FloatField(db_column='ra') dec = models.FloatField(db_column='dec') object_classification = models.IntegerField(db_column='object_classification') followup_flag_date = models.DateField(db_column='followup_flag_date') observation_status = models.CharField(max_length=40, db_column='observation_status') current_trend = models.CharField(max_length=40, db_column='current_trend') earliest_mjd = models.FloatField(db_column='earliest_mjd') earliest_mag = models.FloatField(db_column='earliest_mag') earliest_filter = models.CharField(max_length=80, db_column='earliest_filter') latest_mjd = models.FloatField(db_column='latest_mjd') latest_mag = models.FloatField(db_column='latest_mag') latest_filter = models.CharField(max_length=80, db_column='latest_filter') catalogue = models.CharField(max_length=60, db_column='catalogue') catalogue_object_id = models.CharField(max_length=30, db_column='catalogue_object_id') separation = models.FloatField(db_column='separation') realbogus_factor = models.FloatField(db_column='realbogus_factor') rb_pix = models.FloatField(db_column='zooniverse_score') date_modified = models.FloatField(db_column='date_modified') external_crossmatches = models.CharField(max_length=1500, db_column='external_crossmatches') discovery_target = models.CharField(max_length=90, db_column='discovery_target') @property def ra_sex(self): """ra_sex. """ ra_in_sex = ra_to_sex (self.ra) return ra_in_sex @property def dec_sex(self): """dec_sex. """ dec_in_sex = dec_to_sex (self.dec) return dec_in_sex @property def decode_flag_bits(self): """decode_flag_bits. """ object_definition = getFlagDefs(self.object_classification, FLAGS, delimiter = ' ') return object_definition @property def externalXMs(self): """This is a Hack to get all the external crossmatches per row. Note that it only gets executed 100 times (for each page) so it is not disastrous for database performance. """ xms = TcsCrossMatchesExternal.objects.filter(transient_object_id__id=self.id).order_by('external_designation') #names = xms.values_list("external_designation", flat=True) #nameColumn = ", ".join(names) return xms class WebViewAbstractFollowup(models.Model): """WebViewAbstractFollowup. """ rank = models.IntegerField(db_column='rank') id = models.BigIntegerField(primary_key=True, db_column='id') atlas_designation = models.CharField(max_length=60, db_column='atlas_designation') other_designation = models.CharField(max_length=60, db_column='other_designation') ra = models.FloatField(db_column='ra') dec = models.FloatField(db_column='dec') ra_avg = models.FloatField(db_column='ra_avg') dec_avg = models.FloatField(db_column='dec_avg') object_classification = models.IntegerField(db_column='object_classification') sherlockClassification = models.CharField(max_length=120, db_column='sherlockClassification') followup_flag_date = models.DateField(db_column='followup_flag_date') observation_status = models.CharField(max_length=40, db_column='observation_status') current_trend = models.CharField(max_length=40, db_column='current_trend') earliest_mjd = models.FloatField(db_column='earliest_mjd') earliest_mag = models.FloatField(db_column='earliest_mag') earliest_filter = models.CharField(max_length=80, db_column='earliest_filter') latest_mjd = models.FloatField(db_column='latest_mjd') latest_mag = models.FloatField(db_column='latest_mag') latest_filter = models.CharField(max_length=80, db_column='latest_filter') catalogue = models.CharField(max_length=60, db_column='catalogue') catalogue_object_id = models.CharField(max_length=30, db_column='catalogue_object_id') separation = models.FloatField(db_column='separation') realbogus_factor = models.FloatField(db_column='realbogus_factor') rb_pix = models.FloatField(db_column='zooniverse_score') date_modified = models.FloatField(db_column='date_modified') external_crossmatches = models.CharField(max_length=1500, db_column='external_crossmatches') discovery_target = models.CharField(max_length=90, db_column='discovery_target') rms = models.FloatField(db_column='rms') detection_list_id = models.ForeignKey(TcsDetectionLists, null=True, to_field='id', db_column='detection_list_id', on_delete=models.CASCADE) images_id = models.ForeignKey(TcsImages, to_field='id', db_column='images_id', on_delete=models.CASCADE) class Meta: """Meta. """ abstract = True @property def ra_sex(self): """ra_sex. """ if self.ra_avg: ra_in_sex = ra_to_sex (self.ra_avg) else: ra_in_sex = ra_to_sex (self.ra) return ra_in_sex @property def dec_sex(self): """dec_sex. """ if self.dec_avg: dec_in_sex = dec_to_sex (self.dec_avg) else: dec_in_sex = dec_to_sex (self.dec) return dec_in_sex @property def decode_flag_bits(self): """decode_flag_bits. """ object_definition = getFlagDefs(self.object_classification, FLAGS, delimiter = ' ') return object_definition @property def externalXMs(self): """This is a Hack to get all the external crossmatches per row. Note that it only gets executed 100 times (for each page) so it is not disastrous for database performance. """ xms = TcsCrossMatchesExternal.objects.filter(transient_object_id__id=self.id).order_by('external_designation') #names = xms.values_list("external_designation", flat=True) #nameColumn = ", ".join(names) #sys.stderr.write('\nOBJECT (%s) = %s\n' % (self.ID, nameColumn)) return xms @property def galactic(self): """galactic. """ if self.ra_avg and self.dec_avg: g = transform([self.ra_avg, self.dec_avg], J2000toGalactic) else: g = transform([self.ra, self.dec], J2000toGalactic) return g class WebViewFollowupTransients(WebViewAbstractFollowup): """WebViewFollowupTransients. """ class Meta(WebViewAbstractFollowup.Meta): """Meta. """ db_table = 'atlas_v_followupall' class WebViewFollowupTransients0(WebViewAbstractFollowup): """WebViewFollowupTransients0. """ class Meta(WebViewAbstractFollowup.Meta): """Meta. """ db_table = 'atlas_v_followup0' class WebViewFollowupTransients1(WebViewAbstractFollowup): """WebViewFollowupTransients1. """ class Meta(WebViewAbstractFollowup.Meta): """Meta. """ db_table = 'atlas_v_followup1' class WebViewFollowupTransients2(WebViewAbstractFollowup): """WebViewFollowupTransients2. """ class Meta(WebViewAbstractFollowup.Meta): """Meta. """ db_table = 'atlas_v_followup2' class WebViewFollowupTransients3(WebViewAbstractFollowup): """WebViewFollowupTransients3. """ class Meta(WebViewAbstractFollowup.Meta): """Meta. """ db_table = 'atlas_v_followup3' class WebViewFollowupTransients4(WebViewAbstractFollowup): """WebViewFollowupTransients4. """ class Meta(WebViewAbstractFollowup.Meta): """Meta. """ db_table = 'atlas_v_followup4' class WebViewFollowupTransients5(WebViewAbstractFollowup): """WebViewFollowupTransients5. """ class Meta(WebViewAbstractFollowup.Meta): """Meta. """ db_table = 'atlas_v_followup5' class WebViewFollowupTransients6(WebViewAbstractFollowup): """WebViewFollowupTransients6. """ class Meta(WebViewAbstractFollowup.Meta): """Meta. """ db_table = 'atlas_v_followup6' class WebViewFollowupTransients7(WebViewAbstractFollowup): """WebViewFollowupTransients7. """ class Meta(WebViewAbstractFollowup.Meta): """Meta. """ db_table = 'atlas_v_followup7' class WebViewFollowupTransients8(WebViewAbstractFollowup): """WebViewFollowupTransients8. """ class Meta(WebViewAbstractFollowup.Meta): """Meta. """ db_table = 'atlas_v_followup8' class WebViewFollowupTransientsGeneric(WebViewAbstractFollowup): """WebViewFollowupTransientsGeneric. """ class Meta(WebViewAbstractFollowup.Meta): """Meta. """ db_table = 'atlas_v_followup' class WebViewFollowupTransientsGenericGW(WebViewAbstractFollowup): """WebViewFollowupTransientsGenericGW. """ class Meta(WebViewAbstractFollowup.Meta): """Meta. """ db_table = 'atlas_v_followup_gw' # 2011-04-14 KWS New model for User Defined Lists. # 2013-10-23 KWS Added confidence_factor. # 2014-02-20 KWS Added external_crossmatches and discovery_target. class WebViewAbstractUserDefined(models.Model): """WebViewAbstractUserDefined. """ rank = models.IntegerField(db_column='rank') id = models.BigIntegerField(db_column='id', primary_key=True) atlas_designation = models.CharField(max_length=60, db_column='atlas_designation') other_designation = models.CharField(max_length=60, db_column='other_designation') local_comments = models.CharField(max_length=768, db_column='local_comments') ra = models.FloatField(db_column='ra') dec = models.FloatField(db_column='dec') ra_avg = models.FloatField(db_column='ra_avg') dec_avg = models.FloatField(db_column='dec_avg') object_classification = models.IntegerField(db_column='object_classification') sherlockClassification = models.CharField(max_length=120, db_column='sherlockClassification') followup_flag_date = models.DateField(db_column='followup_flag_date') observation_status = models.CharField(max_length=40, db_column='observation_status') current_trend = models.CharField(max_length=40, db_column='current_trend') earliest_mjd = models.FloatField(db_column='earliest_mjd') earliest_mag = models.FloatField(db_column='earliest_mag') earliest_filter = models.CharField(max_length=80, db_column='earliest_filter') latest_mjd = models.FloatField(db_column='latest_mjd') latest_mag = models.FloatField(db_column='latest_mag') latest_filter = models.CharField(max_length=80, db_column='latest_filter') catalogue = models.CharField(max_length=60, db_column='catalogue') catalogue_object_id = models.CharField(max_length=30, db_column='catalogue_object_id') separation = models.FloatField(db_column='separation') # Extra columns for the user defined object list table object_group_id = models.IntegerField(db_column='object_group_id') detection_list_id = models.ForeignKey(TcsDetectionLists, null=True, to_field='id', db_column='detection_list_id', on_delete=models.CASCADE) realbogus_factor = models.FloatField(db_column='realbogus_factor') rb_pix = models.FloatField(db_column='zooniverse_score') date_modified = models.DateTimeField(db_column='date_modified') external_crossmatches = models.CharField(max_length=1500, db_column='external_crossmatches') discovery_target = models.CharField(max_length=90, db_column='discovery_target') rms = models.FloatField(db_column='rms') class Meta: """Meta. """ abstract = True @property def ra_sex(self): """ra_sex. """ ra_in_sex = ra_to_sex (self.ra) return ra_in_sex @property def dec_sex(self): """dec_sex. """ dec_in_sex = dec_to_sex (self.dec) return dec_in_sex # 2013-12-20 KWS Added option to grab space-delimited RA and DEC (e.g. for producing catalogues) @property def ra_sex_spaces(self): """ra_sex_spaces. """ ra_in_sex = ra_to_sex (self.ra, delimiter=' ') return ra_in_sex @property def dec_sex_spaces(self): """dec_sex_spaces. """ dec_in_sex = dec_to_sex (self.dec, delimiter=' ') return dec_in_sex @property def decode_flag_bits(self): """decode_flag_bits. """ object_definition = getFlagDefs(self.object_classification, FLAGS, delimiter = ' ') return object_definition @property def externalXMs(self): """This is a Hack to get all the external crossmatches per row. Note that it only gets executed 100 times (for each page) so it is not disastrous for database performance. """ xms = TcsCrossMatchesExternal.objects.filter(transient_object_id__id=self.id).order_by('external_designation') #names = xms.values_list("external_designation", flat=True) #nameColumn = ", ".join(names) #sys.stderr.write('\nOBJECT (%s) = %s\n' % (self.ID, nameColumn)) return xms # 2015-03-13 KWS New methods to retrieve the earliest and latest dates # in date format. @property def getEarliestDate(self): """getEarliestDate. """ dateFraction = getDateFractionMJD(self.earliest_mjd) return dateFraction @property def getLatestDate(self): """getLatestDate. """ dateFraction = getDateFractionMJD(self.latest_mjd) return dateFraction class WebViewUserDefined(WebViewAbstractUserDefined): """WebViewUserDefined. """ class Meta(WebViewAbstractUserDefined.Meta): """Meta. """ db_table = 'atlas_v_followup_userdefined' # 2018-08-01 KWS Added custom view for getting ATLAS recurrences for PESSTO. # This is much faster than the ORM query and doesn't take up # all the memory! class AtlasVRecurrencesddcPessto(models.Model): """AtlasVRecurrencesddcPessto. """ rank = models.IntegerField(db_column='rank') id = models.BigIntegerField(db_column='id', primary_key=True) name = models.CharField(max_length=90, db_column='name') tns_name = models.CharField(max_length=90, db_column='tns_name') ra = models.FloatField(db_column='ra') dec = models.FloatField(db_column='dec') expname = models.CharField(max_length=90, db_column='expname') mag = models.FloatField(db_column='mag') dm = models.FloatField(db_column='dm') filter = models.CharField(max_length=90, db_column='filter') mjd = models.FloatField(db_column='mjd') class Meta: """Meta. """ managed = False db_table = 'atlas_v_recurrencesddc_pessto'

35.869121

143

0.701767

f0c8b35da052c54719297dabd73fad3e8d3007b7

1,902

py

Python

tests/materials_test.py

hammy4815/EMpy

64f2c356fbfb783277f69c2a69e020272b91df5d

[ "MIT" ]

null

tests/materials_test.py

hammy4815/EMpy

64f2c356fbfb783277f69c2a69e020272b91df5d

[ "MIT" ]

null

tests/materials_test.py

hammy4815/EMpy

64f2c356fbfb783277f69c2a69e020272b91df5d

[ "MIT" ]

null

# pylint: disable=no-self-use from unittest import TestCase from numpy import array from numpy.testing import assert_almost_equal, assert_raises import EMpy_gpu.materials as mat class RefractiveIndexTest(TestCase): def test_all_nones(self): with assert_raises(ValueError): mat.RefractiveIndex() def test_const(self): test_rix = 1.50 a = mat.RefractiveIndex(n0_const=test_rix) self.assertEqual(a.get_rix(1.0)[0], array([test_rix])) def test_poly(self): test_poly = [1, 1] # n(wl) = 1 * wl + 1 test_rix = 2.0 # n(1) = 1 * 1 + 1 = 2 a = mat.RefractiveIndex(n0_poly=test_poly) assert_almost_equal(a.get_rix(1.0)[0], array([test_rix])) def test_smcoeffs(self): test_poly = [1] * 6 ''' 6-coeffs: n(wls) = 1. + B1 * wls ** 2 / (wls ** 2 - C1) + B2 * wls ** 2 / (wls ** 2 - C2) + B3 * wls ** 2 / (wls ** 2 - C3) ''' test_rix = 1.0536712127723509e-08 a = mat.RefractiveIndex(n0_smcoeffs=test_poly) assert_almost_equal(a.get_rix(0.5)[0], array([test_rix])) def test_func(self): test_rix = 1.50 def test_func_const(x): # returns a const return 0.0 * x + test_rix a = mat.RefractiveIndex(n0_func=test_func_const) assert_almost_equal(a.get_rix([1.0, 1.5]), array([1.5, 1.5])) def test_func_var(x): # returns a const return 1.0 * x + test_rix b = mat.RefractiveIndex(n0_func=test_func_var) assert_almost_equal(b.get_rix([1.0, 1.5]), array([2.5, 3.0])) def test_known(self): test_rix = 1.50 test_wl = 1.0 n0_known = { test_wl: test_rix } a = mat.RefractiveIndex(n0_known=n0_known) self.assertEqual(a.get_rix(test_wl)[0], array([test_rix]))

29.71875

69

0.572555

cbe82cebba1975db85cc22bf6e450519f57c004b

3,914

py

Python

message_families/audit_proof/aca_py_audit_proof/manager.py

ianco/aca-py-audit-plugin

2280e79bca0cc785865b08b8e8cbcb5829d57e8e

[ "Apache-2.0" ]

null

message_families/audit_proof/aca_py_audit_proof/manager.py

ianco/aca-py-audit-plugin

2280e79bca0cc785865b08b8e8cbcb5829d57e8e

[ "Apache-2.0" ]

null

message_families/audit_proof/aca_py_audit_proof/manager.py

ianco/aca-py-audit-plugin

2280e79bca0cc785865b08b8e8cbcb5829d57e8e

[ "Apache-2.0" ]

null

"""Classes to support proof audit.""" import logging from aries_cloudagent.core.error import BaseError from aries_cloudagent.revocation.models.revocation_registry import RevocationRegistry from aries_cloudagent.core.error import BaseError from aries_cloudagent.core.profile import Profile from aries_cloudagent.ledger.base import BaseLedger from aries_cloudagent.indy.verifier import IndyVerifier class AuditProofManagerError(BaseError): """Audit Proof error.""" class AuditProofManager: """Class for providing proof audits.""" def __init__(self, profile: Profile): """ Initialize an AuditProofManager. Args: profile: The profile for this proof audit """ self._profile = profile self._logger = logging.getLogger(__name__) @property def profile(self) -> Profile: """ Accessor for the current injection profile. Returns: The injection profile for this connection """ return self._profile async def verify_presentation( self, presentation_request: dict, presentation: dict ): """ Verify a presentation. Args: presentation_request: indy presentation request presentation: indy presentation to verify Returns: verification status """ indy_proof_request = presentation_request indy_proof = presentation schema_ids = [] credential_definition_ids = [] schemas = {} credential_definitions = {} rev_reg_defs = {} rev_reg_entries = {} identifiers = indy_proof["identifiers"] ledger = self._profile.inject(BaseLedger) async with ledger: for identifier in identifiers: schema_ids.append(identifier["schema_id"]) credential_definition_ids.append(identifier["cred_def_id"]) # Build schemas for anoncreds if identifier["schema_id"] not in schemas: schemas[identifier["schema_id"]] = await ledger.get_schema( identifier["schema_id"] ) if identifier["cred_def_id"] not in credential_definitions: credential_definitions[ identifier["cred_def_id"] ] = await ledger.get_credential_definition( identifier["cred_def_id"] ) if identifier.get("rev_reg_id"): if identifier["rev_reg_id"] not in rev_reg_defs: rev_reg_defs[ identifier["rev_reg_id"] ] = await ledger.get_revoc_reg_def(identifier["rev_reg_id"]) if identifier.get("timestamp"): rev_reg_entries.setdefault(identifier["rev_reg_id"], {}) if ( identifier["timestamp"] not in rev_reg_entries[identifier["rev_reg_id"]] ): ( found_rev_reg_entry, _found_timestamp, ) = await ledger.get_revoc_reg_entry( identifier["rev_reg_id"], identifier["timestamp"] ) rev_reg_entries[identifier["rev_reg_id"]][ identifier["timestamp"] ] = found_rev_reg_entry verifier = self._profile.inject(IndyVerifier) verified = await verifier.verify_presentation( indy_proof_request, indy_proof, schemas, credential_definitions, rev_reg_defs, rev_reg_entries, ) return verified

32.616667

85

0.553654

9ec37c0a2d5ef0fddf647b6b8005092800c7fc4a

1,279

py

Python

cifar10_test.py

z-a-f/PyTorch_CIFAR10

3233d8f86c546de438d0d117ff6698c85a0ca841

[ "MIT" ]

1

2020-07-12T23:18:09.000Z

cifar10_test.py

z-a-f/PyTorch_CIFAR10

3233d8f86c546de438d0d117ff6698c85a0ca841

[ "MIT" ]

null

cifar10_test.py

z-a-f/PyTorch_CIFAR10

3233d8f86c546de438d0d117ff6698c85a0ca841

[ "MIT" ]

null

import os, shutil import torch from argparse import ArgumentParser from pytorch_lightning import Trainer from cifar10_module import CIFAR10_Module def main(hparams): # If only train on 1 GPU. Must set_device otherwise PyTorch always store model on GPU 0 first if type(hparams.gpus) == str: if len(hparams.gpus) == 2: # GPU number and comma e.g. '0,' or '1,' torch.cuda.set_device(int(hparams.gpus[0])) save_to_path = os.path.join(kThisPath, 'test_temp') os.makedirs(save_to_path, exist_ok=True) model = CIFAR10_Module(hparams, pretrained=True) trainer = Trainer(gpus=hparams.gpus, default_save_path=save_to_path) trainer.test(model) shutil.rmtree(save_to_path) if __name__ == '__main__': parser = ArgumentParser() parser.add_argument('--classifier', type=str, default='resnet18') parser.add_argument('--data_dir', type=str, default='/data/huy/cifar10/') parser.add_argument('--gpus', default='0,') parser.add_argument('--max_epochs', type=int, default=100) parser.add_argument('--batch_size', type=int, default=256) parser.add_argument('--learning_rate', type=float, default=1e-2) parser.add_argument('--weight_decay', type=float, default=1e-2) args = parser.parse_args() main(args)

39.96875

97

0.713057

43d64d215f00c56a0967f1ff60395d9b841a365f

3,920

py

Python

pyiArduinoI2Cexpander/examples/FindDevices.py

tremaru/pyiArduinoI2Cexpander

01154070bb1696346897113930379b52680b5669

[ "MIT" ]

null

pyiArduinoI2Cexpander/examples/FindDevices.py

tremaru/pyiArduinoI2Cexpander

01154070bb1696346897113930379b52680b5669

[ "MIT" ]

1

2021-09-16T14:05:26.000Z

pyiArduinoI2Cexpander/examples/FindDevices.py

tremaru/pyiArduinoI2Cexpander

01154070bb1696346897113930379b52680b5669

[ "MIT" ]

1

2021-03-15T08:47:38.000Z

# Данный пример ищет модули на шине и выводит информацию о них. # import smbus # Подключаем модуль шины smbus(i2c) choices = { # Создаём список устройств 0x01: "кнопкой", # Если значение 1, значит это кнопка. 0x02: "светодиодом", # Если значение 2, значит это RGB светодиод. 0x03: "потенциометром", # Если значение 3, значит это потенциометр. 0x04: "звукоизлучателем", # Если значение 4, значит это звукоизлучатель. 0x05: "датчиком DHT", # Если значение 5, значит это датчик владности и температуры. 0x06: "датчиком света", # Если значение 6, значит это датчик света. 0x07: "расширителем выводов", # Если значение 7, значит это датчик света. 0x08: "LED матрицей", # Если значение 8, значит это светодиодная матрица. 0x09: "Энкодером", # Если значение 9, значит это энкодер. 0x0A: "реле на 2 канала", # Если значение A, значит это электромеханическое реле на 2 канала. 0x0B: "реле на 4 канала", # Если значение B, значит это твердотельное реле на 4 канала. 0x0C: "силовым ключём 4 N", # Если значение C, значит это силовой ключ на 4 N-канала. 0x0D: "силовым ключём 4 P", # Если значение D, значит это силовой ключ на 4 P-канала. 0x0E: "силовым ключём 4 N", # Если значение E, значит это силовой ключ на 4 N-канала, с измерением тока. 0x0F: "силовым ключём 4 P" # Если значение F, значит это силовой ключ на 4 P-канала, с измерением тока. } # try: # bus = smbus.SMBus(1) # Пробуем открыть файл шины i2c except FileNotFoundError: # Если файл не найден print("Шина i2c не включена. Запустите" # "`raspi-config` и включите шину.") # Выводим сообщение в stdout except: # Если любая другая ошибка print("неизвестная ошибка") # Выводим сообщение в stdout else: # Если ошибок не найдено for i in range(7, 127): # Проходим по всем доступным адресам на шине I2C ... try: # Пробуем вывести адрес bus.write_quick(i) # устройства на шину except OSError: # Если устройства с текущим адресом не на шине continue # Возвращаемся в начало цикла for со следующим адресом except: # Если любая другая ошибка print("неизвестная ошибка") # Выводим сообщение в stdout else: # Если устройство найдено print("Устройство с адресом" "%#.2X" % i, end='') # Выводим адрес в stdout k = bus.read_i2c_block_data(i, 0x04) # Читаем регистры, начиная с 4 if k[2]>>1 == i and (k[3]==0xc3 or k[3]==0x3c): # Если значение второго элемента массива k совпадает с адресом устройства, а в третьем элементе хранится идентификатор 0xC3 (модуль Metro), или 3С (модуль Flash), то ... print(" является ", end='') # Выводим текст в stdout model = choices.get(k[0], "неизвестным модулем") # Cравниваем модель модуля со списком, если ничего не совпало - записываем в model строку по умолчанию print("%s с версией прошивки %d." % (model, k[1])) # Выводим модель и версию в stdout else: # Выводим текст, если устройство не опознано print(" не опознано") # или на шине два устроойства с одним адресом

80

213

0.539286

880310388e6c829f07bf86dfcb9346436ea5303f

602

py

Python

Sketchbots/sw/labqueue/lask/server/xmp.py

rlugojr/ChromeWebLab

60f964b3f283c15704b7a04b7bb50cb15791e2e4

[ "Apache-2.0" ]

306

2015-01-09T14:03:44.000Z

2017-09-16T13:03:35.000Z

Sketchbots/sw/labqueue/lask/server/xmp.py

rlugojr/ChromeWebLab

60f964b3f283c15704b7a04b7bb50cb15791e2e4

[ "Apache-2.0" ]

90

2019-03-26T05:36:00.000Z

2021-07-28T05:30:16.000Z

Sketchbots/sw/labqueue/lask/server/xmp.py

rlugojr/ChromeWebLab

60f964b3f283c15704b7a04b7bb50cb15791e2e4

[ "Apache-2.0" ]

119

2015-01-26T15:04:33.000Z

2017-09-13T09:30:53.000Z

# Copyright 2013 Google 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.

43

77

0.727575

9c0e21d216903c0dc6ad9111c1cc62f2b7ef12f6

198

py

Python

ems_wheniwork/views/api/exceptions.py

uw-asa/django-ems-wheniwork

6a19f4a860fda369c68b8cb48518d61904d98683

[ "Apache-2.0" ]

null

ems_wheniwork/views/api/exceptions.py

uw-asa/django-ems-wheniwork

6a19f4a860fda369c68b8cb48518d61904d98683

[ "Apache-2.0" ]

null

ems_wheniwork/views/api/exceptions.py

uw-asa/django-ems-wheniwork

6a19f4a860fda369c68b8cb48518d61904d98683

[ "Apache-2.0" ]

null

""" Custom exceptions used by EMS Scheduler. """ class MissingParamException(Exception): pass class InvalidParamException(Exception): pass class NotFoundException(Exception): pass

12.375

40

0.742424

9529d7ae50c90c42cc3229363fd381e4e4993d31

6,428

py

Python

cfg_exporter/helper.py

dong50252409/cfg_exporter

8e6fdfef00dbb228eb34ffdf4c1c23a74f1d7e18

[ "MIT" ]

3

2021-12-10T10:26:15.000Z

2022-02-11T08:34:31.000Z

cfg_exporter/helper.py

dong50252409/cfg_exporter

8e6fdfef00dbb228eb34ffdf4c1c23a74f1d7e18

[ "MIT" ]

null

cfg_exporter/helper.py

dong50252409/cfg_exporter

8e6fdfef00dbb228eb34ffdf4c1c23a74f1d7e18

[ "MIT" ]

1

2022-02-11T09:16:00.000Z

import os from argparse import RawTextHelpFormatter, ArgumentTypeError, ArgumentParser from cfg_exporter.const import ExportType, ExtensionType, TEMPLATE_EXTENSION def valid_source(source): if os.path.exists(source): return source else: raise ArgumentTypeError(_('the source path does not exists `{source}`').format(source=source)) def valid_export(export): if export in ExportType.__members__: return ExportType[export] else: raise ArgumentTypeError(_('the export file type does not exits {export}').format(export=export)) def valid_table(row_num): try: row_num = int(row_num) assert row_num > 0 return row_num except (ValueError, AssertionError): raise ArgumentTypeError(_('{row_num} is not a valid line number').format(row_num=row_num)) def valid_lang_template(lang_template): if os.path.exists(lang_template): return lang_template else: raise ArgumentTypeError(_('the lang template path does not exists `{lang_template}`') .format(source=lang_template)) parser = ArgumentParser(description=_('Configuration table export toolset'), formatter_class=RawTextHelpFormatter) base_group = parser.add_argument_group(title=_('Base options')) base_group.add_argument('--clear_dir', default=False, action='store_true', help=_('clear the output directory.')) base_group.add_argument('--exclude_files', default=[], nargs="*", help=_('specify a list of file names not to load.')) base_group.add_argument('-e', '--export_type', type=valid_export, metavar=f'[{",".join(ExportType.__members__.keys())}]', help=_('specify the configuration table export type.')) base_group.add_argument('--file_prefix', default='', help=_('specify the prefix of the output filename.')) base_group.add_argument('--force', default=False, action='store_true', help=_('force all configuration tables to be generated.')) base_group.add_argument('-o', '--output', type=str, default="", help=_('specify the configuration table output path.')) base_group.add_argument('-r', '--recursive', default=False, action='store_true', help=_('recursively search the source path.')) base_group.add_argument('--verification', default=False, action='store_true', help=_('verify only the correctness of the configuration table.')) base_group.add_argument('-s', '--source', type=valid_source, required=True, help=_( 'specify the configuration table source path.\nsupported file types [{extensions}]').format( extensions=",".join(ExtensionType.__members__.keys()))) base_group.add_argument('--template_path', help=_('specify the extension template path.\n' 'the template name consists of the table name, export type, ' 'and {template_extension} extension\n' 'e.g:\n' '`item.erl.{template_extension}` `item.hrl.{template_extension}` ' '`item.lua.{template_extension}`\n' 'loads the template based on the specified export type\n' 'e.g:\n' '`--export_type erl` templates ending with `.erl.{template_extension}` ' 'and `.hrl.{template_extension}` will be loaded\n' '`--export_type lua` templates ending with `.lua.{template_extension}` will be loaded' ).format(template_extension=TEMPLATE_EXTENSION)) base_group.add_argument('--verbose', default=False, action='store_true', help=_('show the details.')) table_group = parser.add_argument_group(title=_('Table options')) table_group.add_argument('--data_row', type=valid_table, required=True, help=_('specify the start line number of the configuration table body data.')) table_group.add_argument('--desc_row', type=valid_table, help=_('specify the line number of the configuration table column description.')) table_group.add_argument('--field_row', type=valid_table, required=True, help=_('specify the line number of the configuration table field name.')) table_group.add_argument('--rule_row', type=valid_table, help=_('specify the line number of the configuration table check rule.')) table_group.add_argument('--type_row', type=valid_table, required=True, help=_('specify the line number of the configuration table data type.')) lang_group = parser.add_argument_group(title=_('Multi languages options')) lang_group.add_argument('--lang_template', type=valid_lang_template, help=_('specify the language template path.')) lang_group.add_argument('--export_lang_template', help=_('output language template.')) csv_group = parser.add_argument_group(title=_('CSV options')) csv_group.add_argument('--csv_encoding', default='utf-8-sig', metavar='ENCODING', help=_('specify the default encoding format for CSV files.\nDEFAULT UTF-8')) erl_group = parser.add_argument_group(title=_('Erlang options')) erl_group.add_argument('--erl_dir', default='', help=_('specify output directory for where to generate the .erl.')) erl_group.add_argument('--hrl_dir', default='', help=_('specify output directory for where to generate the .hrl.')) lua_group = parser.add_argument_group(title=_('LUA options')) lua_group.add_argument('--lua_optimize', default=False, action='store_true', help=_('remove default value fields ( store them into metatable ) ' 'and reuse all table values to save memory')) py_group = parser.add_argument_group(title=_('PYTHON options')) py_group.add_argument('--py_optimize', default=False, action='store_true', help=_('remove default value fields and reuse all table values to save memory')) args = parser.parse_args() __all__ = ('args',)

45.588652

120

0.632078

12ca0ab0e9e224776635b85b9cccd063e505e9d0

10,281

py

Python

image_widget.py

zhangkaisong/YoloAll

7bb8c0ce11b6c033f0e6fd15621fdb5d5a2f1787

[ "Apache-2.0" ]

1

2021-12-05T07:52:50.000Z

image_widget.py

zhangkaisong/YoloAll

7bb8c0ce11b6c033f0e6fd15621fdb5d5a2f1787

[ "Apache-2.0" ]

null

image_widget.py

zhangkaisong/YoloAll

7bb8c0ce11b6c033f0e6fd15621fdb5d5a2f1787

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- import sys import os if hasattr(sys, 'frozen'): os.environ['PATH'] = sys._MEIPASS + ";" + os.environ['PATH'] from PyQt5.QtWidgets import * from PyQt5 import QtCore, QtGui, uic from PyQt5.QtCore import * from PyQt5.QtGui import * import copy import xml.etree.cElementTree as et import os import cv2 import math from PIL import Image # ui配置文件 cUi, cBase = uic.loadUiType("image_widget.ui") # 主界面 class ImageWidget(QWidget, cUi): def __init__(self): #, main_widget=None): # 设置UI QMainWindow.__init__(self) cUi.__init__(self) self.setupUi(self) self.comboBoxCamera.addItem('0') self.comboBoxCamera.addItem('1') self.comboBoxCamera.addItem('2') self.timer = QTimer() self.video_cap = None self.camera_cap = None self.qpixmap = None self.qpixmap_bg = None self.cAlg = None self.infer = None self.class_map = None self.alg_time = None self.color_list = [QColor(255,0,0), QColor(0,255,0), QColor(0,0,255), QColor(0,255,255), QColor(255,0,255), QColor(8,46,84), QColor(199,97,20), QColor(255,227,132), QColor(255,255,0), QColor(128,138,135)] self.change_background('normal') @pyqtSlot() def on_btnPhoto_clicked(self): print('on_btnPhoto_clicked') img_path = QFileDialog.getOpenFileName(self, "选取图片", "./", "Images (*.jpg);;Images (*.png)") img_path = img_path[0] if img_path != '': self.slot_photo_frame(img_path) @pyqtSlot() def on_btnVideo_clicked(self): print('on_btnVideo_clicked') video_path = QFileDialog.getOpenFileName(self, "选取视频", "./", "Videos (*.mp4);;Images (*.3gp)") video_path = video_path[0] if video_path != '': self.video_cap = cv2.VideoCapture(video_path) self.timer.start() self.timer.setInterval(int(1000 / float(30.0))) self.timer.timeout.connect(self.slot_video_frame) @pyqtSlot() def on_btnCamera_clicked(self): print('on_btnCamera_clicked') if self.camera_cap is None: self.camera_cap = cv2.VideoCapture(int(0)) self.timer.start() self.timer.setInterval(int(1000 / float(30.0))) self.timer.timeout.connect(self.slot_camera_frame) else: self.camera_cap.release() self.camera_cap = None self.timer.stop() @pyqtSlot() def on_btnStop_clicked(self): self.stop_all() def slot_photo_frame(self, photo_path): img = cv2.imread(photo_path) self.cAlg.add_img(img) def slot_camera_frame(self): if self.camera_cap is not None: # get a frame ret, img = self.camera_cap.read() if ret is False: self.stop_all() return self.cAlg.add_img(img) def slot_video_frame(self): if self.video_cap is not None: ret, img = self.video_cap.read() if ret is False: self.stop_all() return self.cAlg.add_img(img) def slot_alg_result(self, img, result, time_spend): if result['type'] == 'info': print(result['result']) return elif result['type'] == 'img': img = result['result'] self.infer = None else: self.infer = result height, width, bytesPerComponent = img.shape bytesPerLine = bytesPerComponent * width cv2.cvtColor(img, cv2.COLOR_BGR2RGB, img) image = QImage(img.data, width, height, bytesPerLine, QImage.Format_RGB888) self.qpixmap = QPixmap.fromImage(image) self.alg_time = time_spend self.update() def stop_all(self): self.timer.stop() self.qpixmap = None if self.camera_cap is not None: self.camera_cap.release() self.camera_cap = None if self.video_cap is not None: self.video_cap.release() self.video_cap = None def set_alg_handle(self, handle): self.cAlg = handle def change_background(self, bg_name): self.qpixmap_bg = None bg_path = './icons/bg_' + bg_name + '.png' self.qpixmap_bg = QPixmap(bg_path) self.update() def draw_image(self, painter): pen = QPen() font = QFont("Microsoft YaHei") if self.qpixmap is not None: painter.drawPixmap(QtCore.QRect(0, 0, self.width(), self.height()), self.qpixmap) pen.setColor(self.getColor(0)) painter.setPen(pen) pointsize = font.pointSize() font.setPixelSize(pointsize*180/72) painter.setFont(font) painter.drawText(10, 30, 'time=%.4f seconds fps=%.4f' % (self.alg_time, 1 / self.alg_time)) else: if self.qpixmap_bg is not None: painter.drawPixmap(QtCore.QRect(0, 0, self.width(), self.height()), self.qpixmap_bg) pen.setColor(QColor(0, 0, 0)) pen.setWidth(4) painter.setPen(pen) painter.drawRect(0, 0, self.width(), self.height()) def draw_infer(self, painter): if self.infer is None: return # class if self.infer['type'] == 'classify': self.draw_infer_class(painter) # det elif self.infer['type'] == 'detection': self.draw_infer_det(painter) # kp elif self.infer['type'] == 'keypoint': self.draw_infer_kp(painter) else: print('unknown info type') assert(False) def draw_infer_class(self, painter): font = QFont("宋体") pointsize = font.pointSize() font.setPixelSize(pointsize*90/72) painter.setFont(font) pen = QPen() pen.setWidth(1) pen.setColor(QColor(0, 255, 0)) painter.setPen(pen) top1 = self.infer['result'][0] name = self.infer['result'][1] score = self.infer['result'][2] painter.drawText(10, 50, 'top1=%s(%.4f)' % (name, score)) def draw_infer_det(self, painter): pass def draw_infer_kp(self, painter): x_scale = self.width() / self.qpixmap.width() y_scale = self.height() / self.qpixmap.height() for kps in self.infer['result']: kps[:,0] = kps[:,0] * y_scale kps[:,1] = kps[:,1] * x_scale nose = kps[0] left_shoulder = kps[5] right_shoulder = kps[6] center_shoulder = (left_shoulder + right_shoulder) / 2 right_shoulder = kps[6] left_elbow = kps[7] right_elbow = kps[8] left_wrist = kps[9] right_wrist = kps[10] left_hip = kps[11] right_hip = kps[12] center_hip = (left_hip + right_hip) / 2 left_knee = kps[13] right_knee = kps[14] left_ankle = kps[15] right_ankle = kps[16] pen = QPen() pen.setColor(self.getColor(0)) pen.setWidth(3) painter.setPen(pen) painter.drawLine(nose[1], nose[0], center_shoulder[1], center_shoulder[0]) pen.setColor(self.getColor(1)) pen.setWidth(3) painter.setPen(pen) painter.drawLine(center_shoulder[1], center_shoulder[0], center_hip[1], center_hip[0]) pen.setColor(self.getColor(2)) pen.setWidth(3) painter.setPen(pen) painter.drawLine(left_shoulder[1], left_shoulder[0], right_shoulder[1], right_shoulder[0]) pen.setColor(self.getColor(3)) pen.setWidth(3) painter.setPen(pen) painter.drawLine(left_shoulder[1], left_shoulder[0], left_elbow[1], left_elbow[0]) pen.setColor(self.getColor(4)) pen.setWidth(3) painter.setPen(pen) painter.drawLine(left_elbow[1], left_elbow[0], left_wrist[1], left_wrist[0]) pen.setColor(self.getColor(5)) pen.setWidth(3) painter.setPen(pen) painter.drawLine(right_shoulder[1], right_shoulder[0], right_elbow[1], right_elbow[0]) pen.setColor(self.getColor(6)) pen.setWidth(3) painter.setPen(pen) painter.drawLine(right_elbow[1], right_elbow[0], right_wrist[1], right_wrist[0]) pen.setColor(self.getColor(7)) pen.setWidth(3) painter.setPen(pen) painter.drawLine(left_hip[1], left_hip[0], right_hip[1], right_hip[0]) pen.setColor(self.getColor(8)) pen.setWidth(3) painter.setPen(pen) painter.drawLine(left_hip[1], left_hip[0], left_knee[1], left_knee[0]) pen.setColor(self.getColor(9)) pen.setWidth(3) painter.setPen(pen) painter.drawLine(left_knee[1], left_knee[0], left_ankle[1], left_ankle[0]) pen.setColor(self.getColor(10)) pen.setWidth(3) painter.setPen(pen) painter.drawLine(right_hip[1], right_hip[0], right_knee[1], right_knee[0]) pen.setColor(self.getColor(11)) pen.setWidth(3) painter.setPen(pen) painter.drawLine(right_knee[1], right_knee[0], right_ankle[1], right_ankle[0]) def paintEvent(self, event): painter = QtGui.QPainter(self) self.draw_image(painter) self.draw_infer(painter) def getColor(self, index): return self.color_list[index % len(self.color_list)] if __name__ == "__main__": cApp = QApplication(sys.argv) cImageWidget = ImageWidget() cImageWidget.show() sys.exit(cApp.exec_())

35.329897

104

0.548779

06ba49e42e54f7ee4c7e52a132b320670ecd9e9f

10,348

py

Python

rubikenv/rubikgym.py

Forbu/rubikenv

2dcf156b4dd03541c176c430675d8ddd5653825f

[ "Apache-2.0" ]

null

rubikenv/rubikgym.py

Forbu/rubikenv

2dcf156b4dd03541c176c430675d8ddd5653825f

[ "Apache-2.0" ]

null

rubikenv/rubikgym.py

Forbu/rubikenv

2dcf156b4dd03541c176c430675d8ddd5653825f

[ "Apache-2.0" ]

null

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Fri Dec 21 15:51:06 2018 @author: adrien """ import numpy as np import pandas as pd import gym from gym import spaces class rubik_cube: """ This is a rubik's cube class simulator Attributes : - state : a 9x6 array of value between 1 and 6 """ number_of_face = 6 number_of_element_in_sideface = 3 def __init__(self, init_state=None): """ Initialisation of the rubik """ # init state initialisation if init_state is not None: init_state = init_state.astype(int) self.state = init_state self.init_state = np.copy(init_state) else: # perfect cube init_state = np.zeros((self.number_of_element_in_sideface, self.number_of_element_in_sideface,self.number_of_face)) for i in range(self.number_of_face): init_state[:,:,i] = i init_state = init_state.astype(int) self.state = init_state self.init_state = np.copy(init_state) # other ? def setInit(self): # perfect cube init_state = np.zeros((self.number_of_element_in_sideface, self.number_of_element_in_sideface,self.number_of_face)) for i in range(self.number_of_face): init_state[:, :, i] = i init_state = init_state.astype(int) self.state = init_state self.init_state = np.copy(init_state) def move(self,index_move): """ For the convention there is exactly 12 possible moves the move are indexed between 0 and 11 the index is in [X Y Z] with X : 0 1 2 3 Y : 4 5 6 7 Z : 8 9 10 11 The first two number here are the move corresponding the a certain position on the face. The two other number at the end are the inverse of those move (the two first) X Y and Z corresponding to the rotation angle """ value_side = index_move % 2 # entre 0 et 1 the position of the rotation on the face value_side_rotation = index_move // 4 # entre 0 et 2 the rotation index of the array value_side_inverse = (index_move % 4)//2 # entre 0 et 1 if inverse or not #print("value_side= ", str(value_side)) #print("value_side_rotation= ", str(value_side_rotation)) #print("value_side_inverse= ", str(value_side_inverse)) if value_side == 1: value_side = 2 # correction to simplify the calculation if value_side_rotation == 0: # inversion value if value_side_inverse == 0: self.state[:,value_side,[5,1,4,3]] = self.state[:,value_side,[1,4,3,5]] if value_side == 0: self.state[:,:,0] = np.rot90(self.state[:,:,0],k=3) else: self.state[:,:,2] = np.rot90(self.state[:,:,2]) else: self.state[:,value_side,[5,1,4,3]] = self.state[:,value_side,[3,5,1,4]] if value_side == 0: self.state[:,:,0] = np.rot90(self.state[:,:,0]) else: self.state[:,:,2] = np.rot90(self.state[:,:,2], k=3) elif value_side_rotation == 1: # inversion value if value_side_inverse == 0: self.state[:,value_side,[5,0,4,2]] = self.state[:,value_side,[0,4,2,5]] if value_side == 0: self.state[:,:,1] = np.rot90(self.state[:,:,1],k=3) else: self.state[:,:,3] = np.rot90(self.state[:,:,3]) else: self.state[:,value_side,[5,0,4,2]] = self.state[:,value_side,[2,5,0,4]] if value_side == 0: self.state[:,:,1] = np.rot90(self.state[:,:,1]) else: self.state[:,:,3] = np.rot90(self.state[:,:,3], k=3) # TODO again elif value_side_rotation == 2: tmp_state = np.copy(self.state) # inversion value if value_side_inverse == 0: # TODO more complex self.state[:,value_side,0] = tmp_state[value_side,:,1][::-1] self.state[2-value_side,:,3] = tmp_state[:,value_side,0] self.state[:,2-value_side,2] = tmp_state[2-value_side,:,3][::-1] self.state[value_side,:,1] = tmp_state[:,2-value_side,2] if value_side == 0: self.state[:,:,4] = np.rot90(self.state[:,:,4],k=3) else: self.state[:,:,5] = np.rot90(self.state[:,:,5]) else: self.state[value_side,:,1] = tmp_state[:,value_side,0][::-1] self.state[:,value_side,0] = tmp_state[2-value_side,:,3] self.state[2-value_side,:,3] = tmp_state[:,2-value_side,2][::-1] self.state[:,2-value_side,2] = tmp_state[value_side,:,1] if value_side == 0: self.state[:,:,4] = np.rot90(self.state[:,:,4]) else: self.state[:,:,5] = np.rot90(self.state[:,:,5], k=3) def move_cube(self, index_move,state): """ For the convention there is exactly 12 possible moves the move are indexed between 0 and 11 the index is in [X Y Z] with X : 0 1 2 3 Y : 4 5 6 7 Z : 8 9 10 11 The first two number here are the move corresponding the a certain position on the face. The two other number at the end are the inverse of those move (the two first) X Y and Z corresponding to the rotation angle """ value_side = index_move % 2 # entre 0 et 1 the position of the rotation on the face value_side_rotation = index_move // 4 # entre 0 et 2 the rotation index of the array value_side_inverse = (index_move % 4)//2 # entre 0 et 1 if inverse or not #print("value_side= ", str(value_side)) #print("value_side_rotation= ", str(value_side_rotation)) #print("value_side_inverse= ", str(value_side_inverse)) if value_side == 1: value_side = 2 # correction to simplify the calculation if value_side_rotation == 0: # inversion value if value_side_inverse == 0: state[:,value_side,[5,1,4,3]] = state[:,value_side,[1,4,3,5]] if value_side == 0: state[:,:,0] = np.rot90(state[:,:,0],k=3) else: state[:,:,2] = np.rot90(state[:,:,2]) else: state[:,value_side,[5,1,4,3]] = state[:,value_side,[3,5,1,4]] if value_side == 0: state[:,:,0] = np.rot90(state[:,:,0]) else: state[:,:,2] = np.rot90(state[:,:,2], k=3) elif value_side_rotation == 1: # inversion value if value_side_inverse == 0: state[:,value_side,[5,0,4,2]] = state[:,value_side,[0,4,2,5]] if value_side == 0: state[:,:,1] = np.rot90(state[:,:,1],k=3) else: state[:,:,3] = np.rot90(state[:,:,3]) else: state[:,value_side,[5,0,4,2]] = state[:,value_side,[2,5,0,4]] if value_side == 0: state[:,:,1] = np.rot90(state[:,:,1]) else: state[:,:,3] = np.rot90(state[:,:,3], k=3) # TODO again elif value_side_rotation == 2: tmp_state = np.copy(state) # inversion value if value_side_inverse == 0: # TODO more complex state[:,value_side,0] = tmp_state[value_side,:,1][::-1] state[2-value_side,:,3] = tmp_state[:,value_side,0] state[:,2-value_side,2] = tmp_state[2-value_side,:,3][::-1] state[value_side,:,1] = tmp_state[:,2-value_side,2] if value_side == 0: state[:,:,4] = np.rot90(state[:,:,4],k=3) else: state[:,:,5] = np.rot90(state[:,:,5]) else: state[value_side,:,1] = tmp_state[:,value_side,0][::-1] state[:,value_side,0] = tmp_state[2-value_side,:,3] state[2-value_side,:,3] = tmp_state[:,2-value_side,2][::-1] state[:,2-value_side,2] = tmp_state[value_side,:,1] if value_side == 0: state[:,:,4] = np.rot90(state[:,:,4]) else: state[:,:,5] = np.rot90(state[:,:,5], k=3) return state class rubikgym(gym.Env, rubik_cube): reward_range = (-1, 1) spec = None # Set these in ALL subclasses action_space = spaces.Discrete(12) # flatten discret space observation_space = spaces.MultiDiscrete([6 for _ in range(3*3*6)]) def __init__(self): gym.Env.__init__(self) rubik_cube.__init__(self) def step(self, action): self.move(action) return self.state, 0, 0, 0 def reset(self): self.setInit(), 0 def render(self, mode='human'): print(self.state) def set_init(self, state): self.init_state = state self.state = state

35.560137

92

0.469463

71ccaeec04285c9d8689dbfa9fe0eb1fe7d9922c

4,762

py

Python

once_upon_a_repository/utilities.py

allegroai/trains-blogs

19a1bc971f9eb5f31a0d08dd553ea0d1f5437e9d

[ "Apache-2.0" ]

12

2020-02-06T10:02:36.000Z

2022-01-15T19:38:16.000Z

once_upon_a_repository/utilities.py

allegroai/trains-blogs

19a1bc971f9eb5f31a0d08dd553ea0d1f5437e9d

[ "Apache-2.0" ]

1

2021-09-08T01:54:46.000Z

once_upon_a_repository/utilities.py

allegroai/trains-blogs

19a1bc971f9eb5f31a0d08dd553ea0d1f5437e9d

[ "Apache-2.0" ]

3

2020-02-10T00:19:44.000Z

2020-05-31T13:51:06.000Z

import json import attr import cv2 import numpy as np import torch import torchvision from torchvision.models.detection.faster_rcnn import FastRCNNPredictor from torchvision.models.detection.mask_rcnn import MaskRCNNPredictor from torchvision.transforms import functional as F from torchvision_references import utils def safe_collate(batch): batch = list(filter(lambda x: x is not None, batch)) return utils.collate_fn(batch) def draw_boxes(im, boxes, labels, color=(150, 0, 0)): for box, draw_label in zip(boxes, labels): draw_box = box.astype('int') im = cv2.rectangle(im, tuple(draw_box[:2]), tuple(draw_box[2:]), color, 2) im = cv2.putText(im, str(draw_label), (draw_box[0], max(0, draw_box[1]-5)), cv2.FONT_HERSHEY_COMPLEX, 0.8, color, 2) return im def draw_debug_images(images, targets, predictions=None, score_thr=0.3): debug_images = [] for image, target in zip(images, targets): img = draw_boxes(np.array(F.to_pil_image(image.cpu())), [box.cpu().numpy() for box in target['boxes']], [label.item() for label in target['labels']]) if predictions: img = draw_boxes(img, [box.cpu().numpy() for box, score in zip(predictions[target['image_id'].item()]['boxes'], predictions[target['image_id'].item()]['scores']) if score >= score_thr], [label.item() for label, score in zip(predictions[target['image_id'].item()]['labels'], predictions[target['image_id'].item()]['scores']) if score >= score_thr], color=(0, 150, 0)) debug_images.append(img) return debug_images def draw_mask(target): masks = [channel*label for channel, label in zip(target['masks'].cpu().numpy(), target['labels'].cpu().numpy())] masks_sum = sum(masks) masks_out = masks_sum + 25*(masks_sum > 0) return (masks_out*int(255/masks_out.max())).astype('uint8') def get_model_instance_segmentation(num_classes, hidden_layer): # load an instance segmentation model pre-trained on COCO model = torchvision.models.detection.maskrcnn_resnet50_fpn(pretrained=True) # get number of input features for the classifier in_features = model.roi_heads.box_predictor.cls_score.in_features # replace the pre-trained head with a new one model.roi_heads.box_predictor = FastRCNNPredictor(in_features, num_classes) # now get the number of input features for the mask classifier in_features_mask = model.roi_heads.mask_predictor.conv5_mask.in_channels # and replace the mask predictor with a new one model.roi_heads.mask_predictor = MaskRCNNPredictor(in_features_mask, hidden_layer, num_classes) return model def get_iou_types(model): model_without_ddp = model if isinstance(model, torch.nn.parallel.DistributedDataParallel): model_without_ddp = model.module iou_types = ["bbox"] if isinstance(model_without_ddp, torchvision.models.detection.MaskRCNN): iou_types.append("segm") if isinstance(model_without_ddp, torchvision.models.detection.KeypointRCNN): iou_types.append("keypoints") return iou_types @attr.s(auto_attribs=True) class CocoLikeAnnotations(): def __attrs_post_init__(self): self.coco_like_json: dict = {'images': [], 'annotations': []} self._ann_id: int = 0 def update_images(self, file_name, height, width, id): self.coco_like_json['images'].append({'file_name': file_name, 'height': height, 'width': width, 'id': id}) def update_annotations(self, box, label_id, image_id, is_crowd=0): segmentation, bbox, area = self.extract_coco_info(box) self.coco_like_json['annotations'].append({'segmentation': segmentation, 'bbox': bbox, 'area': area, 'category_id': int(label_id), 'id': self._ann_id, 'iscrowd': is_crowd, 'image_id': image_id}) self._ann_id += 1 @staticmethod def extract_coco_info(box): segmentation = list(map(int, [box[0], box[1], box[0], box[3], box[2], box[3], box[2], box[1]])) bbox = list(map(int, np.append(box[:2], (box[2:] - box[:2])))) area = int(bbox[2] * bbox[3]) return segmentation, bbox, area def dump_to_json(self, path_to_json='/tmp/inference_results/inference_results.json'): with open(path_to_json, "w") as write_file: json.dump(self.coco_like_json, write_file)

42.517857

116

0.634817

dfd7c5f562d84ddb6236ae21284c21d516b30548

7,751

py

Python

configs/trainval/daotad_eccv2022/7.b.ii.py

klauscc/vedatad

c59f5ddc8fb227ef08baccbb513948bb1bb23857

[ "Apache-2.0" ]

null

configs/trainval/daotad_eccv2022/7.b.ii.py

klauscc/vedatad

c59f5ddc8fb227ef08baccbb513948bb1bb23857

[ "Apache-2.0" ]

null

configs/trainval/daotad_eccv2022/7.b.ii.py

klauscc/vedatad

c59f5ddc8fb227ef08baccbb513948bb1bb23857

[ "Apache-2.0" ]

null

# 1. data dataset_type = "Thumos14Dataset" data_root = "data/thumos14/" img_norm_cfg = dict( mean=[122.7709, 116.7460, 104.0937], std=[68.5005, 66.6322, 70.3232], to_rgb=True ) num_frames = 480 chunk_size = 1 img_shape = (224, 224) overlap_ratio = 0.25 keep_ratio = 0.2 feat_downsample = 1 expid = "7.b.ii" data = dict( samples_per_gpu=2, workers_per_gpu=6, train=dict( typename=dataset_type, ann_file=data_root + "annotations/val.json", video_prefix=data_root + "frames_15fps_256x256/val", pipeline=[ dict(typename="LoadMetaInfo"), dict(typename="LoadAnnotations"), dict(typename="Time2Frame"), dict(typename="TemporalRandomCrop", num_frames=num_frames, iof_th=0.75), dict(typename="LoadFrames", to_float32=True), dict(typename="SpatialRandomCrop", crop_size=img_shape), dict( typename="PhotoMetricDistortion", brightness_delta=32, contrast_range=(0.5, 1.5), saturation_range=(0.5, 1.5), hue_delta=18, p=0.5, ), dict(typename="Rotate", limit=(-45, 45), border_mode="reflect101", p=0.5), dict(typename="SpatialRandomFlip", flip_ratio=0.5), dict(typename="Normalize", **img_norm_cfg), dict(typename="Pad", size=(num_frames, *img_shape)), dict(typename="DefaultFormatBundle"), dict( typename="Collect", keys=["imgs", "gt_segments", "gt_labels", "gt_segments_ignore"], ), ], ), val=dict( typename=dataset_type, ann_file=data_root + "annotations/test.json", video_prefix=data_root + "frames_15fps_256x256/test", pipeline=[ dict(typename="LoadMetaInfo"), dict(typename="Time2Frame"), dict( typename="OverlapCropAug", num_frames=num_frames, overlap_ratio=overlap_ratio, transforms=[ dict(typename="TemporalCrop"), dict(typename="LoadFrames", to_float32=True), dict(typename="SpatialCenterCrop", crop_size=img_shape), dict(typename="Normalize", **img_norm_cfg), dict(typename="Pad", size=(num_frames, *img_shape)), dict(typename="DefaultFormatBundle"), dict(typename="Collect", keys=["imgs"]), ], ), ], ), ) # 2. model num_classes = 20 strides = [8, 16, 32, 64, 128] use_sigmoid = True scales_per_octave = 5 octave_base_scale = 2 num_anchors = scales_per_octave model = dict( typename="MemSingleStageDetector", chunk_size=chunk_size, backbone=dict( typename="ChunkActionClip", chunk_size=chunk_size, forward_mode="batch", pretrained_model="data/pretrained_models/action-clip/vit-b-16-32f.pt", ), neck=[ dict( typename="SRMResizeFeature", srm_cfg=dict( kernel_size=2, ), ), dict( typename="SRMSwin", srm_cfg=dict( in_channels=512, out_channels=512, with_transformer=False, ), ), dict( typename="Transformer1DRelPos", encoder_layer_cfg=dict( dim=512, num_heads=16, max_seq_len=num_frames // strides[0], drop_path=0.1, ), num_layers=3, ), dict( typename="SelfAttnTDM", in_channels=512, out_channels=512, strides=2, num_heads=8, kernel_sizes=(7, 7, 5, 5), stage_layers=(1, 1, 1, 1), out_indices=(0, 1, 2, 3, 4), out_order="bct", ), dict( typename="FPN", in_channels=[512, 512, 512, 512, 512], out_channels=256, num_outs=5, start_level=0, conv_cfg=dict(typename="Conv1d"), norm_cfg=dict(typename="SyncBN"), ), ], head=dict( typename="RetinaHead", num_classes=num_classes, num_anchors=num_anchors, in_channels=256, stacked_convs=4, feat_channels=256, use_sigmoid=use_sigmoid, conv_cfg=dict(typename="Conv1d"), norm_cfg=dict(typename="SyncBN"), ), ) # 3. engines meshgrid = dict( typename="SegmentAnchorMeshGrid", strides=strides, base_anchor=dict( typename="SegmentBaseAnchor", base_sizes=strides, octave_base_scale=octave_base_scale, scales_per_octave=scales_per_octave, ), ) segment_coder = dict( typename="DeltaSegmentCoder", target_means=[0.0, 0.0], target_stds=[1.0, 1.0] ) train_engine = dict( typename="MemBankTrainEngine", membank=dict( chunk_size=chunk_size, keep_ratio=keep_ratio, feat_downsample=feat_downsample, mode="random", mem_bank_meta_file=f"data/tmp/eccv2022/thumos14/memory_mechanism/{expid}/actionclip_vitb16_15fps_256x256_crop224x224/meta_val.json", mem_bank_dir=f"data/tmp/eccv2022/thumos14/memory_mechanism/{expid}/actionclip_vitb16_15fps_256x256_crop224x224/val", ), model=model, criterion=dict( typename="SegmentAnchorCriterion", num_classes=num_classes, meshgrid=meshgrid, segment_coder=segment_coder, reg_decoded_segment=True, loss_cls=dict( typename="FocalLoss", use_sigmoid=use_sigmoid, gamma=2.0, alpha=0.25, loss_weight=1.0, ), loss_segment=dict(typename="DIoULoss", loss_weight=1.0), train_cfg=dict( assigner=dict( typename="MaxIoUAssigner", pos_iou_thr=0.6, neg_iou_thr=0.4, min_pos_iou=0, ignore_iof_thr=-1, ignore_wrt_candidates=True, iou_calculator=dict(typename="SegmentOverlaps"), ), allowed_border=-1, pos_weight=-1, debug=False, ), ), optimizer=dict( typename="SGD", lr=0.01, momentum=0.9, weight_decay=0.0001, paramwise_cfg=dict(custom_keys=dict(backbone={"lr_mult": 0.4})), ), ) # 3.2 val engine val_engine = dict( typename="ValEngine", model=model, meshgrid=meshgrid, converter=dict( typename="SegmentAnchorConverter", num_classes=num_classes, segment_coder=segment_coder, nms_pre=1000, use_sigmoid=use_sigmoid, ), num_classes=num_classes, test_cfg=dict( score_thr=0.005, nms=dict(typename="nmw", iou_thr=0.5), max_per_video=1200 ), use_sigmoid=use_sigmoid, ) # 4. hooks hooks = [ dict(typename="OptimizerHook"), dict( typename="CosineRestartLrSchedulerHook", periods=[100] * 12, restart_weights=[1] * 12, warmup="linear", warmup_iters=500, warmup_ratio=1e-1, min_lr_ratio=1e-2, ), dict(typename="EvalHook", eval_cfg=dict(mode="anet")), dict(typename="SnapshotHook", interval=100), dict(typename="LoggerHook", interval=10), ] # 5. work modes modes = ["train"] max_epochs = 1000 # 6. checkpoint # optimizer = dict(filepath='epoch_900_optim.pth') # meta = dict(filepath='epoch_900_meta.pth') # 7. misc seed = 10 dist_params = dict(backend="nccl") log_level = "INFO" find_unused_parameters = False # gpu_mem_fraction = 0.2

29.249057

140

0.56883

fdd52d1a1220d7207f5871e3fcdca365b1fa0e6c

7,964

py

Python

livvkit/components/numerics_tests/ismip.py

jhkennedy/LIVVkit

680120cd437e408673e62e535fc0a246c7fc17db

[ "BSD-3-Clause" ]

null

livvkit/components/numerics_tests/ismip.py

jhkennedy/LIVVkit

680120cd437e408673e62e535fc0a246c7fc17db

[ "BSD-3-Clause" ]

null

livvkit/components/numerics_tests/ismip.py

jhkennedy/LIVVkit

680120cd437e408673e62e535fc0a246c7fc17db

[ "BSD-3-Clause" ]

null

# coding=utf-8 # Copyright (c) 2015-2017, UT-BATTELLE, LLC # All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # # 1. Redistributions of source code must retain the above copyright notice, this # list of conditions and the following disclaimer. # # 2. Redistributions in binary form must reproduce the above copyright notice, # this list of conditions and the following disclaimer in the documentation # and/or other materials provided with the distribution. # # 3. Neither the name of the copyright holder nor the names of its contributors # may be used to endorse or promote products derived from this software without # specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND # ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED # WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE # FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL # DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR # SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER # CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. """ Utilities to provide numerical verification for the ISMIP test cases """ from __future__ import absolute_import, division, print_function, unicode_literals import six import os import numpy as np import matplotlib.pyplot as plt import livvkit from livvkit.util.LIVVDict import LIVVDict from livvkit.util import elements from livvkit.util import functions case_color = {'bench': '#d7191c', 'test': '#fc8d59'} line_style = {'bench': 'o-', 'test': '-'} setup = None def set_up(): global setup setup = functions.read_json(os.path.join(os.path.dirname(__file__), 'ismip.json')) for exp, size in [('ismip-hom-a', '005'), ('ismip-hom-c', '005'), ('ismip-hom-f', '000')]: recreate_file = os.path.join(livvkit.__path__[0], setup[exp]["data_dir"], setup[exp]['pattern'][0].replace('???', size)) setup[exp]['interp_points'] = \ np.genfromtxt(recreate_file, delimiter=',', missing_values='nan', usecols=(0,), unpack=True) if exp == 'ismip-hom-f': setup[exp]['interp_points'] = setup[exp]['interp_points']*100 - 50 def get_case_length(case): return str(int(case.split('-')[-1][1:])).zfill(3) def run(config, analysis_data): case = config['name'] if case in ['ismip-hom-a', 'ismip-hom-c', 'ismip-hom-f']: coord = 'x_hat' else: coord = 'y_hat' lengths = list(set( [get_case_length(d) for d in six.iterkeys(analysis_data)] )) plot_list = [] for p, pattern in enumerate(sorted(setup[case]['pattern'])): fig_label = pattern.split('_')[1] description = '' for l in sorted(lengths): plt.figure(figsize=(10, 8), dpi=150) plt.xlabel(setup[case]['xlabel'][p]) plt.ylabel(setup[case]['ylabel'][p]) if case in ['ismip-hom-a', 'ismip-hom-c']: plt.title(str(int(l))+' km') title = fig_label[0:-1]+'. '+fig_label[-1]+': '+str(int(l))+' km' else: plt.title('No-Slip Bed') title = fig_label[0:-2]+'. '+fig_label[-2:]+': No-Slip Bed' plot_file = os.path.join(config["plot_dir"], config['name']+'_'+fig_label+'_'+l+'.png') recreate_file = os.path.join( livvkit.__path__[0], setup[case]["data_dir"], pattern ).replace('???', l) axis, fs_amin, fs_amax, fs_mean, fs_std, ho_amin, ho_amax, ho_mean, ho_std = \ np.genfromtxt(recreate_file, delimiter=',', missing_values='nan', unpack=True) if case in ['ismip-hom-f']: axis = axis*100.0 - 50.0 plt.fill_between(axis, ho_amin, ho_amax, facecolor='green', alpha=0.5) plt.fill_between(axis, fs_amin, fs_amax, facecolor='blue', alpha=0.5) plt.plot(axis, fs_mean, 'b-', linewidth=2, label='Full stokes') plt.plot(axis, ho_mean, 'g-', linewidth=2, label='Higher order') analysis = {} for a in six.iterkeys(analysis_data): if int(l) == int(a.split('-')[-1][1:]): analysis[a] = analysis_data[a] for a in six.iterkeys(analysis): for model in sorted(six.iterkeys(analysis[a])): plt.plot(analysis[a][model][coord], analysis[a][model][config['plot_vars'][p]], line_style[model], color=case_color[model], linewidth=2, label=a+'-'+model) plt.legend(loc='best') if livvkit.publish: plt.savefig(os.path.splitext(plot_file)[0]+'.eps', dpi=600) plt.savefig(plot_file) plt.close() plot_list.append(elements.image(title, description, os.path.basename(plot_file))) return elements.gallery("Numerics Plots", plot_list) def summarize_result(data, config): case = config['name'] summary = LIVVDict() lengths = list(set([get_case_length(d) for d in six.iterkeys(data)])) for p, pattern in enumerate(sorted(setup[case]['pattern'])): for l in sorted(lengths): recreate_file = os.path.join( livvkit.__path__[0], setup[case]["data_dir"], pattern ).replace('???', l) axis, fs_amin, fs_amax, fs_mean, fs_std, ho_amin, ho_amax, ho_mean, ho_std = \ np.genfromtxt(recreate_file, delimiter=',', missing_values='nan', unpack=True) analysis = {} for a in six.iterkeys(data): if int(l) == int(a.split('-')[-1][1:]): analysis[a] = data[a] for a in six.iterkeys(analysis): for model in sorted(six.iterkeys(analysis[a])): if setup[case]['ylabel'][p].split(" ")[0].lower() == 'surface': percent_errors = np.divide(analysis[a][model][config['plot_vars'][p]] - ho_mean, ho_mean+1000) coefficient = np.divide(ho_std, ho_mean+1000) else: percent_errors = np.divide(analysis[a][model][config['plot_vars'][p]] - ho_mean, ho_mean) coefficient = np.divide(ho_std, ho_mean) label = a+' '+setup[case]['ylabel'][p].split(" ")[0] if model.lower() == 'bench': summary[label]['Bench mean % error'] = \ '{:3.2%}'.format(np.nanmean(percent_errors)) else: summary[label]['Test mean % error'] = \ '{:3.2%}'.format(np.nanmean(percent_errors)) summary[label]['Coefficient of variation'] = \ '{:3.2%}'.format(np.nanmean(coefficient)) return summary def print_summary(case, summary): """ Show some statistics from the run """ for subcase in six.iterkeys(summary): message = case + " " + subcase print(" " + message) print(" " + "-"*len(message)) for key, val in summary[subcase].items(): print(" "*4 + key.ljust(25) + ":" + val.rjust(7)) print("")

40.632653

99

0.573707

ff82373210dc1842acf9ffc54515bb4033c6bbaf

14,270

py

Python

ml_service/pipelines/img_class_build_parallel_batchscore_pipeline.py

MFG-Azure-MLOps-Hub/MLOpsImgClass

4a1bbeb292590d12d2f46da4f0b993b86730e4eb

[ "MIT" ]

1

2020-12-08T03:10:35.000Z

ml_service/pipelines/img_class_build_parallel_batchscore_pipeline.py

MFG-Azure-MLOps-Hub/MLOpsImgClass

4a1bbeb292590d12d2f46da4f0b993b86730e4eb

[ "MIT" ]

null

ml_service/pipelines/img_class_build_parallel_batchscore_pipeline.py

MFG-Azure-MLOps-Hub/MLOpsImgClass

4a1bbeb292590d12d2f46da4f0b993b86730e4eb

[ "MIT" ]

1

2020-12-08T03:10:37.000Z

""" Copyright (C) Microsoft Corporation. All rights reserved. Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual, royalty-free right to use, copy, and modify the software code provided by us ("Software Code"). You may not sublicense the Software Code or any use of it (except to your affiliates and to vendors to perform work on your behalf) through distribution, network access, service agreement, lease, rental, or otherwise. This license does not purport to express any claim of ownership over data you may have shared with Microsoft in the creation of the Software Code. Unless applicable law gives you more rights, Microsoft reserves all other rights not expressly granted herein, whether by implication, estoppel or otherwise. THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. """ import os from azureml.pipeline.steps import ParallelRunConfig, ParallelRunStep from ml_service.util.manage_environment import get_environment from ml_service.pipelines.load_sample_data import create_sample_data_csv from ml_service.util.env_variables import Env from ml_service.util.attach_compute import get_compute from azureml.core import ( Workspace, Dataset, Datastore, RunConfiguration, ) from azureml.pipeline.core import Pipeline, PipelineData, PipelineParameter from azureml.core.compute import ComputeTarget from azureml.data.datapath import DataPath from azureml.pipeline.steps import PythonScriptStep from typing import Tuple def get_or_create_datastore( datastorename: str, ws: Workspace, env: Env, input: bool = True ) -> Datastore: """ Obtains a datastore with matching name. Creates it if none exists. :param datastorename: Name of the datastore :param ws: Current AML Workspace :param env: Environment variables :param input: Datastore points to the input container if this is True(default) or the output storage container otherwise :returns: Datastore :raises: ValueError """ if datastorename is None: raise ValueError("Datastore name is required.") containername = ( env.scoring_datastore_input_container if input else env.scoring_datastore_output_container ) if datastorename in ws.datastores: datastore = ws.datastores[datastorename] # the datastore is not registered but we have all details to register it elif ( env.scoring_datastore_access_key is not None and containername is not None # NOQA: E501 ): # NOQA:E501 datastore = Datastore.register_azure_blob_container( workspace=ws, datastore_name=datastorename, account_name=env.scoring_datastore_storage_name, account_key=env.scoring_datastore_access_key, container_name=containername, ) else: raise ValueError( "No existing datastore named {} nor was enough information supplied to create one.".format( # NOQA: E501 datastorename ) ) return datastore def get_input_dataset(ws: Workspace, ds: Datastore, env: Env) -> Dataset: """ Gets an input dataset wrapped around an input data file. The input data file is assumed to exist in the supplied datastore. :param ws: AML Workspace :param ds: Datastore containing the data file :param env: Environment variables :returns: Input Dataset """ scoringinputds = Dataset.Tabular.from_delimited_files( path=DataPath(ds, env.scoring_datastore_input_filename) ) scoringinputds = scoringinputds.register( ws, name=env.scoring_dataset_name, tags={"purpose": "scoring input", "format": "csv"}, create_new_version=True, ).as_named_input(env.scoring_dataset_name) return scoringinputds def get_fallback_input_dataset(ws: Workspace, env: Env) -> Dataset: """ Called when an input datastore does not exist or no input data file exists at that location. Create a sample dataset using the img_class dataset from scikit-learn. Useful when debugging this code in the absence of the input data location Azure blob. :param ws: AML Workspace :param env: Environment Variables :returns: Fallback input dataset :raises: FileNotFoundError """ # This call creates an example CSV from sklearn sample data. If you # have already bootstrapped your project, you can comment this line # out and use your own CSV. create_sample_data_csv( file_name=env.scoring_datastore_input_filename, for_scoring=True ) if not os.path.exists(env.scoring_datastore_input_filename): error_message = ( "Could not find CSV dataset for scoring at {}. " + "No alternate data store location was provided either.".format( env.scoring_datastore_input_filename ) # NOQA: E501 ) raise FileNotFoundError(error_message) # upload the input data to the workspace default datastore default_datastore = ws.get_default_datastore() scoreinputdataref = default_datastore.upload_files( [env.scoring_datastore_input_filename], target_path="scoringinput", overwrite=False, ) scoringinputds = ( Dataset.Tabular.from_delimited_files(scoreinputdataref) .register(ws, env.scoring_dataset_name, create_new_version=True) .as_named_input(env.scoring_dataset_name) ) return scoringinputds def get_output_location( ws: Workspace, env: Env, outputdatastore: Datastore = None ) -> PipelineData: """ Returns a Datastore wrapped as a PipelineData instance suitable for passing into a pipeline step. Represents the location where the scoring output should be written. Uses the default workspace blob store if no output datastore is supplied. :param ws: AML Workspace :param env: Environment Variables :param outputdatastore: AML Datastore, optional, default is None :returns: PipelineData wrapping the output datastore """ if outputdatastore is None: output_loc = PipelineData( name="defaultoutput", datastore=ws.get_default_datastore() ) else: output_loc = PipelineData( name=outputdatastore.name, datastore=outputdatastore ) # NOQA: E501 return output_loc def get_inputds_outputloc( ws: Workspace, env: Env ) -> Tuple[Dataset, PipelineData]: # NOQA: E501 """ Prepare the input and output for the scoring step. Input is a tabular dataset wrapped around the scoring data. Output is PipelineData representing a location to write the scores down. :param ws: AML Workspace :param env: Environment Variables :returns: Input dataset and output location """ if env.scoring_datastore_storage_name is None: # fall back to default scoringinputds = get_fallback_input_dataset(ws, env) output_loc = get_output_location(ws, env) else: inputdatastore = get_or_create_datastore( "{}_in".format(env.scoring_datastore_storage_name), ws, env ) outputdatastore = get_or_create_datastore( "{}_out".format(env.scoring_datastore_storage_name), ws, env, input=False, # NOQA: E501 ) scoringinputds = get_input_dataset(ws, inputdatastore, env) output_loc = get_output_location(ws, env, outputdatastore) return (scoringinputds, output_loc) def get_run_configs( ws: Workspace, computetarget: ComputeTarget, env: Env ) -> Tuple[ParallelRunConfig, RunConfiguration]: """ Creates the necessary run configurations required by the pipeline to enable parallelized scoring. :param ws: AML Workspace :param computetarget: AML Compute target :param env: Environment Variables :returns: Tuple[Scoring Run configuration, Score copy run configuration] """ # get a conda environment for scoring environment = get_environment( ws, env.aml_env_name_scoring, conda_dependencies_file=env.aml_env_score_conda_dep_file, enable_docker=True, use_gpu=env.use_gpu_for_scoring, create_new=env.rebuild_env_scoring, ) score_run_config = ParallelRunConfig( entry_script=env.batchscore_script_path, source_directory=env.sources_directory_train, error_threshold=10, output_action="append_row", compute_target=computetarget, node_count=env.max_nodes_scoring, environment=environment, run_invocation_timeout=300, ) copy_run_config = RunConfiguration() copy_run_config.environment = get_environment( ws, env.aml_env_name_score_copy, conda_dependencies_file=env.aml_env_scorecopy_conda_dep_file, enable_docker=True, use_gpu=env.use_gpu_for_scoring, create_new=env.rebuild_env_scoring, ) return (score_run_config, copy_run_config) def get_scoring_pipeline( scoring_dataset: Dataset, output_loc: PipelineData, score_run_config: ParallelRunConfig, copy_run_config: RunConfiguration, computetarget: ComputeTarget, ws: Workspace, env: Env, ) -> Pipeline: """ Creates the scoring pipeline. :param scoring_dataset: Data to score :param output_loc: Location to save the scoring results :param score_run_config: Parallel Run configuration to support parallelized scoring :param copy_run_config: Script Run configuration to support score copying :param computetarget: AML Compute target :param ws: AML Workspace :param env: Environment Variables :returns: Scoring pipeline instance """ # To help filter the model make the model name, model version and a # tag/value pair bindable parameters so that they can be passed to # the pipeline when invoked either over REST or via the AML SDK. model_name_param = PipelineParameter( "model_name", default_value=" " ) # NOQA: E501 model_version_param = PipelineParameter( "model_version", default_value=" " ) # NOQA: E501 model_tag_name_param = PipelineParameter( "model_tag_name", default_value=" " ) # NOQA: E501 model_tag_value_param = PipelineParameter( "model_tag_value", default_value=" " ) # NOQA: E501 scoring_step = ParallelRunStep( name="scoringstep", inputs=[scoring_dataset], output=output_loc, arguments=[ "--model_name", model_name_param, "--model_version", model_version_param, "--model_tag_name", model_tag_name_param, "--model_tag_value", model_tag_value_param, ], parallel_run_config=score_run_config, allow_reuse=False, ) copying_step = PythonScriptStep( name="scorecopystep", script_name=env.batchscore_copy_script_path, source_directory=env.sources_directory_train, arguments=[ "--output_path", output_loc, "--scoring_output_filename", env.scoring_datastore_output_filename if env.scoring_datastore_output_filename is not None else "", "--scoring_datastore", env.scoring_datastore_storage_name if env.scoring_datastore_storage_name is not None else "", "--score_container", env.scoring_datastore_output_container if env.scoring_datastore_output_container is not None else "", "--scoring_datastore_key", env.scoring_datastore_access_key if env.scoring_datastore_access_key is not None else "", ], inputs=[output_loc], allow_reuse=False, compute_target=computetarget, runconfig=copy_run_config, ) return Pipeline(workspace=ws, steps=[scoring_step, copying_step]) def build_batchscore_pipeline(): """ Main method that builds and publishes a scoring pipeline. """ try: env = Env() # Get Azure machine learning workspace aml_workspace = Workspace.get( name=env.workspace_name, subscription_id=env.subscription_id, resource_group=env.resource_group, ) # Get Azure machine learning cluster aml_compute_score = get_compute( aml_workspace, env.compute_name_scoring, env.vm_size_scoring, for_batch_scoring=True, ) input_dataset, output_location = get_inputds_outputloc( aml_workspace, env ) # NOQA: E501 scoring_runconfig, score_copy_runconfig = get_run_configs( aml_workspace, aml_compute_score, env ) scoring_pipeline = get_scoring_pipeline( input_dataset, output_location, scoring_runconfig, score_copy_runconfig, aml_compute_score, aml_workspace, env, ) published_pipeline = scoring_pipeline.publish( name=env.scoring_pipeline_name, description="Diabetes Batch Scoring Pipeline", ) pipeline_id_string = "##vso[task.setvariable variable=pipeline_id;isOutput=true]{}".format( # NOQA: E501 published_pipeline.id ) print(pipeline_id_string) except Exception as e: print(e) exit(1) if __name__ == "__main__": build_batchscore_pipeline()

33.263403

117

0.688788

1a2af3e295ac20af3f8bd5d081d8eed841351846

7,520

py

Python

src/.history/HiwinRA605_socket_ros_20190604110804.py

SamKaiYang/2019_Hiwin_Shaking

d599f8c87dc4da89eae266990d12eb3a8b0f3e16

[ "MIT" ]

null

src/.history/HiwinRA605_socket_ros_20190604110804.py

SamKaiYang/2019_Hiwin_Shaking

d599f8c87dc4da89eae266990d12eb3a8b0f3e16

[ "MIT" ]

null

src/.history/HiwinRA605_socket_ros_20190604110804.py

SamKaiYang/2019_Hiwin_Shaking

d599f8c87dc4da89eae266990d12eb3a8b0f3e16

[ "MIT" ]

null

#!/usr/bin/env python3 # license removed for brevity #接收策略端命令用Socket傳輸至控制端電腦 import socket ##多執行序 import threading import time ## import sys import os import numpy as np import rospy import matplotlib as plot from std_msgs.msg import String from ROS_Socket.srv import * from ROS_Socket.msg import * import HiwinRA605_socket_TCPcmd as TCP import HiwinRA605_socket_Taskcmd as Taskcmd import talker as talk import enum data = '0' #設定傳輸資料初始直 Arm_feedback = 1 #假設手臂忙碌 state_feedback = 0 NAME = 'socket_server' client_response = 0 #回傳次數初始值 ##------------class pos------- class pos(): def __init__(self, x, y, z, pitch, roll, yaw): self.x = x self.y = y self.z = z self.pitch = pitch self.roll = roll self.yaw = yaw ##------------class socket_cmd--------- class socket_cmd(): def __init__(self, grip, setvel, ra, delay, setboth, action): self.grip = grip self.setvel = setvel self.ra = ra self.delay = delay self.setboth = setboth self.action = action ##-----------switch define------------## class switch(object): def __init__(self, value): self.value = value self.fall = False def __iter__(self): """Return the match method once, then stop""" yield self.match raise StopIteration def match(self, *args): """Indicate whether or not to enter a case suite""" if self.fall or not args: return True elif self.value in args: # changed for v1.5, see below self.fall = True return True else: return False ##-----------client feedback arm state---------- def socket_client_arm_state(Arm_state): global state_feedback rospy.wait_for_service('arm_state') try: Arm_state_client = rospy.ServiceProxy('arm_state', arm_state) state_feedback = Arm_state_client(Arm_state) #pos_feedback_times = pos_feedback.response return state_feedback except rospy.ServiceException as e: print ("Service call failed: %s"%e) ##-----------client feedback arm state end---------- ##------------server ------- ##--------touch strategy--------### def point_data(req): global client_response pos.x = '%s'%req.x pos.y = '%s'%req.y pos.z = '%s'%req.z pos.pitch = '%s'%req.pitch pos.roll = '%s'%req.roll pos.yaw = '%s'%req.yaw client_response = client_response + 1 return(client_response) ##----------Arm Mode-------------### def Arm_Mode(req): socket_cmd.action = int('%s'%req.action) socket_cmd.grip = int('%s'%req.grip) socket_cmd.ra = int('%s'%req.ra) socket_cmd.setvel = int('%s'%req.vel) socket_cmd.setboth = int('%s'%req.both) return(1) ##--------touch strategy end--------### def socket_server(): rospy.init_node(NAME) a = rospy.Service('arm_mode',arm_mode, Arm_Mode) ##server arm mode data s = rospy.Service('arm_pos',arm_data, point_data) ##server arm point data print ("Ready to connect") rospy.spin() ## spin one ##------------server end------- ##----------socket 封包傳輸--------------## ##-----------socket client-------- def socket_client(): global Arm_feedback,data try: s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) s.connect(('192.168.0.1', 8080))#iclab 5 #s.connect(('192.168.1.102', 8080))#iclab computerx except socket.error as msg: print(msg) sys.exit(1) print('Connection has been successful') print(s.recv(1024)) start_input=int(input('開始傳輸請按1,離開請按3 : ')) #start_input = 1 if start_input==1: while 1: ##---------------socket 傳輸手臂命令----------------- for case in switch(socket_cmd.action): if case(Taskcmd.Action_Type.PtoP): for case in switch(socket_cmd.setboth): if case(Taskcmd.Ctrl_Mode.CTRL_POS): data = TCP.SetPtoP(socket_cmd.grip,Taskcmd.RA.ABS,Taskcmd.Ctrl_Mode.CTRL_POS,pos.x,pos.y,pos.z,pos.pitch,pos.roll,pos.yaw,socket_cmd.setvel) break if case(Taskcmd.Ctrl_Mode.CTRL_EULER): data = TCP.SetPtoP(socket_cmd.grip,Taskcmd.RA.ABS,Taskcmd.Ctrl_Mode.CTRL_EULER,pos.x,pos.y,pos.z,pos.pitch,pos.roll,pos.yaw,socket_cmd.setvel) break if case(Taskcmd.Ctrl_Mode.CTRL_BOTH): data = TCP.SetPtoP(socket_cmd.grip,Taskcmd.RA.ABS,Taskcmd.Ctrl_Mode.CTRL_BOTH,pos.x,pos.y,pos.z,pos.pitch,pos.roll,pos.yaw,socket_cmd.setvel) break break if case(Taskcmd.Action_Type.Line): for case in switch(socket_cmd.setboth): if case(Taskcmd.Ctrl_Mode.CTRL_POS): data = TCP.SetLine(socket_cmd.grip,Taskcmd.RA.ABS,Taskcmd.Ctrl_Mode.CTRL_POS,pos.x,pos.y,pos.z,pos.pitch,pos.roll,pos.yaw,socket_cmd.setvel) break if case(Taskcmd.Ctrl_Mode.CTRL_EULER): data = TCP.SetLine(socket_cmd.grip,Taskcmd.RA.ABS,Taskcmd.Ctrl_Mode.CTRL_EULER,pos.x,pos.y,pos.z,pos.pitch,pos.roll,pos.yaw,socket_cmd.setvel ) break if case(Taskcmd.Ctrl_Mode.CTRL_BOTH): data = TCP.SetLine(socket_cmd.grip,Taskcmd.RA.ABS,Taskcmd.Ctrl_Mode.CTRL_BOTH,pos.x,pos.y,pos.z,pos.pitch,pos.roll,pos.yaw,socket_cmd.setvel ) break break if case(Taskcmd.Action_Type.SetVel): data = TCP.SetVel(socket_cmd.grip, socket_cmd.setvel) break if case(Taskcmd.Action_Type.Delay): data = TCP.SetDelay(socket_cmd.grip,0) break if case(Taskcmd.Action_Type.Mode): data = TCP.SetMode(socket_cmd.grip,0) break socket_cmd.action= 5 s.send(data.encode('utf-8'))#socket傳送for python to translate str feedback_str = s.recv(1024) #手臂端傳送手臂狀態 ###test 0403 if str(feedback_str[2]) == '70':# F feedback = 0 socket_client_arm_state(feedback) print("isbusy false") if str(feedback_str[2]) == '84':# T feedback = 1 socket_client_arm_state(feedback) print("isbusy true") if str(feedback_str[2]) == '54':# 6 feedback = 6 socket_client_arm_state(feedback) print("shutdown") #Arm_feedback = TCP.Is_busy(feedback) ###test 0403 ##---------------socket 傳輸手臂命令 end----------------- if Arm_feedback == Taskcmd.Arm_feedback_Type.shutdown: rospy.on_shutdown(myhook) break if start_input == 3: pass s.close() ##-----------socket client end-------- ##-------------socket 封包傳輸 end--------------## ## 多執行緒 def thread_test(): socket_client() ## 多執行序 end def myhook(): print ("shutdown time!") if __name__ == '__main__': socket_cmd.action = 5 t = threading.Thread(target=thread_test) t.start() socket_server() t.join() # Ctrl+K Ctrl+C 添加行注释 Add line comment # Ctrl+K Ctrl+U 删除行注释 Remove line comment #Ctrl+] / [ 缩进/缩进行 Indent/outdent line

36.862745

171

0.562234

e93e4b2d340bfe7b131b6091d0ecd8f0008f2f8b

10,106

py

Python

src/5_Upload-to-aws.py

biomage-ltd/data-ingest

cbac0d5aae262afa6afdd2ee74b8ef7c58e745f6

[ "MIT" ]

2

2020-10-23T17:41:10.000Z

2021-02-10T20:50:49.000Z

src/5_Upload-to-aws.py

biomage-ltd/data-ingest

cbac0d5aae262afa6afdd2ee74b8ef7c58e745f6

[ "MIT" ]

10

2021-01-07T11:34:57.000Z

2021-06-22T15:46:46.000Z

src/5_Upload-to-aws.py

biomage-ltd/data-ingest

cbac0d5aae262afa6afdd2ee74b8ef7c58e745f6

[ "MIT" ]

1

2020-11-10T23:17:30.000Z

#!/usr/bin/python3 ################################################ ## 5_upload-to-aws.py ## - Getting ready samples-table and experiments-table ## - Upload tables to DynamoDB ## - Upload experiment.rds to S3 ################################################ import hashlib import os import pandas from scipy.io import mmread import matplotlib.pyplot as plt import boto3 import json from decimal import Decimal from datetime import datetime import uuid COLOR_POOL = [] CLUSTER_ENVS = [os.getenv("CLUSTER_ENV", "staging")] if CLUSTER_ENVS[0] == "all": CLUSTER_ENVS = ['staging', 'production'] WARN_TXT_COL = "\033[93m" RESET_TXT_COL = "\033[0m" ERR_TXT_COL = "\033[91m" for CLUSTER_ENV in CLUSTER_ENVS: print(f"{WARN_TXT_COL}Deploying to {CLUSTER_ENV}{RESET_TXT_COL}") for CLUSTER_ENV in CLUSTER_ENVS: if not (CLUSTER_ENV in ["staging", "production"]): print(f"{ERR_TXT_COL}{CLUSTER_ENV} does not exists{RESET_TXT_COL}") exit(1) with open("/data-ingest/src/color_pool.json") as f: COLOR_POOL = json.load(f) def calculate_checksum(filenames): hash = hashlib.md5() for fn in filenames: if os.path.isfile(fn): hash.update(open(fn, "rb").read()) return hash.hexdigest() # This function crate the table information for samples. As input it requires the experiment id and the config. def create_samples_table(config, experiment_id): # In samples_table we are going to add the core of the information samples_table = {} # Getting flag_filtered information df_prefilered = pandas.read_csv( "/output/df_flag_filtered.txt", sep="\t", na_values=["None"], ) # Firstly, we identify the samples name. To do that we fetch the names of the folders (we suppose that the name # of the folders corresponds with the samples name) or direclty get them from the config if len(config["samples"]) > 1: samples = config["samples"] else: samples = [ name for name in os.listdir("/input") if os.path.isdir(os.path.join("/input", name)) ] samples_table["ids"] = ["sample-" + sample for sample in samples] # For the current datasets it could happen that they are not in the gz format, so we leave the alternative tsv format. mime_options = { "tsv": "application/tsv", "gz": "application/gzip", "mtx": "application/mtx", } for sample in samples: # flag filtered preFiltered = ( df_prefilered.loc[ df_prefilered.samples == sample, "flag_filtered" ].tolist()[0] == "Filtered" ) # Identify datetime createdDate = datetime.now() lastModified = datetime.now() fileNames = {} # Look for the file that are not hidden (the hidden files start with .hidden.tsv) sample_files = [ sample + "/" + f for f in os.listdir("/input/" + sample) if not f.startswith(".") ] # Iterate over each file to create the slot for sample_file in sample_files: fileNames[sample_file] = { "objectKey": "", "name": sample_file, "size": os.stat("/input/" + sample_file).st_size, "mime": mime_options[sample_file.split(".")[-1]], "success": True, "error": False, } # Add the whole information to each sample samples_table["sample-" + sample] = { "name": sample, "uuid": str(uuid.uuid4()), "species": config["organism"], "type": config["input"]["type"], "createdDate": createdDate.isoformat(), "lastModified": lastModified.isoformat(), "complete": True, "error": False, "fileNames": sample_files, "files": fileNames, "preFiltered": preFiltered, } return {"experimentId": experiment_id, "samples": samples_table} # cell_sets fn for seurat samples name def samples_sets(): # construct new cell set group samples_annotations = pandas.read_csv( "/output/samples-cells.csv", sep="\t", names=["Cells_ID", "Value"], na_values=["None"], ) cell_set = { "key": "sample", "name": "Samples", "rootNode": True, "children": [], "type": "metadataCategorical", } for sample in samples_annotations["Value"].unique(): view = samples_annotations[samples_annotations.Value == sample]["Cells_ID"] cell_set["children"].append( { "key": f"sample-{sample}", "name": f"{sample}", "color": COLOR_POOL.pop(0), "cellIds": [int(d) for d in view.tolist()], } ) return cell_set # cell_sets fn for seurat metadata information def meta_sets(): meta_annotations = pandas.read_csv( "/output/metadata-cells.csv", sep="\t", header=0, ) cell_set_list = list() # The first column is the cells_id, the rest is the metadata information for i in range(1, len(meta_annotations.columns)): # keep as key and name the name of the column key = meta_annotations.columns[i] name = meta_annotations.columns[i] cell_set = { "key": key, "name": name, "rootNode": True, "children": [], "type": "metadataCategorical", } for value in meta_annotations.iloc[:, i].unique(): view = meta_annotations[meta_annotations.iloc[:, i] == value]["cells_id"] cell_set["children"].append( { "key": key + f"-{value}", "name": f"{value}", "color": COLOR_POOL.pop(0), "cellIds": [int(d) for d in view.tolist()], } ) cell_set_list.append(cell_set) return cell_set_list def main(): experiment_id = calculate_checksum( [ "/output/r-out-raw.mtx", "/output/r-out-normalized.mtx", "/output/r-out-cells.tsv", ] ) # save experiment_id for record-keeping with open("/output/experiment_id.txt", "w") as text_file: text_file.write(experiment_id) config = None with open("/input/meta.json", "r") as f: config = json.load(f) # read config related with QC pipeline config_dataProcessing = None with open("/output/config_dataProcessing.json", "r") as f: config_dataProcessing = json.load(f) # Design cell_set scratchpad for DynamoDB scratchpad = { "key": "scratchpad", "name": "Scratchpad", "rootNode": True, "children": [], "type": "cellSets", } samples_data = create_samples_table(config, experiment_id) samples_set = samples_sets() if "metadata" in config.keys(): # Design cell_set meta_data for DynamoDB meta_set = meta_sets() cellSets = [samples_set, scratchpad] + meta_set else: # Design cell_set meta_data for DynamoDB cellSets = [scratchpad, samples_set] print("Experiment name is", config["name"]) FILE_NAMES = [ f"biomage-source-{CLUSTER_ENV}/{experiment_id}/r.rds" for CLUSTER_ENV in CLUSTER_ENVS] experiment_data = { "apiVersion": "2.0.0-data-ingest-seurat-rds-automated", "experimentId": experiment_id, "experimentName": config["name"], "meta": { "organism": config["organism"], "type": config["input"]["type"], }, "processingConfig": config_dataProcessing, } cellSetsObject = {"cellSets": cellSets} cell_sets_data = json.dumps(cellSetsObject) # Conver to float all decimals experiment_data = json.loads(json.dumps(experiment_data), parse_float=Decimal) if CLUSTER_ENV == "production": rbac_write = "a07c6615-d982-413b-9fdc-48bd85182e83" else: rbac_write = "70c213d4-e7b6-4920-aefb-706ce8606ee2" experiment_data["rbac_can_write"] = set([rbac_write]) samples_data = json.loads(json.dumps(samples_data), parse_float=Decimal) access_key = os.getenv("AWS_ACCESS_KEY_ID") secret_access_key = os.getenv("AWS_SECRET_ACCESS_KEY") for CLUSTER_ENV, FILE_NAME in zip(CLUSTER_ENVS, FILE_NAMES): r_object_bucket, r_object_key = FILE_NAME.split("/", 1) dynamo = boto3.resource( "dynamodb", aws_access_key_id=access_key, aws_secret_access_key=secret_access_key, region_name="eu-west-1", ).Table(f"experiments-{CLUSTER_ENV}") dynamo.put_item(Item=experiment_data) dynamo = boto3.resource( "dynamodb", aws_access_key_id=access_key, aws_secret_access_key=secret_access_key, region_name="eu-west-1", ).Table(f"samples-{CLUSTER_ENV}") dynamo.put_item(Item=samples_data) s3 = boto3.client( "s3", aws_access_key_id=access_key, aws_secret_access_key=secret_access_key, region_name="eu-west-1", ) s3.put_object( Body=cell_sets_data, Bucket=f"cell-sets-{CLUSTER_ENV}", Key=experiment_id ) s3 = boto3.client( "s3", aws_access_key_id=access_key, aws_secret_access_key=secret_access_key, region_name="eu-west-1", ) with open("/output/experiment.rds", "rb") as f: s3.put_object(Body=f, Bucket=r_object_bucket, Key=r_object_key) if CLUSTER_ENV == "production": print("successful. experiment is now accessible at:") print(f"https://scp.biomage.net/experiments/{experiment_id}/data-exploration") elif CLUSTER_ENV == "staging": print(f"successful. Experiment ID: {experiment_id} uploaded to staging.") main() print("Step 5 completed.")

30.439759

122

0.586483

f693863e5efd6d3824327951bced428042da4edc

1,046

py

Python

tests/bind_tests/boolean_tests/sweep_event_tests/strategies.py

skrat/martinez

86db48324cb50ecb52be8ab2e4278a6d5cdd562b

[ "MIT" ]

7

2020-05-07T08:13:44.000Z

2021-12-17T07:33:51.000Z

tests/bind_tests/boolean_tests/sweep_event_tests/strategies.py

skrat/martinez

86db48324cb50ecb52be8ab2e4278a6d5cdd562b

[ "MIT" ]

17

2019-11-29T23:17:26.000Z

2020-12-20T15:47:17.000Z

tests/bind_tests/boolean_tests/sweep_event_tests/strategies.py

skrat/martinez

86db48324cb50ecb52be8ab2e4278a6d5cdd562b

[ "MIT" ]

1

2020-12-17T22:44:21.000Z

from hypothesis import strategies from tests.bind_tests.factories import (to_acyclic_bound_sweep_events, to_bound_sweep_events, to_nested_bound_sweep_events, to_plain_bound_sweep_events) from tests.bind_tests.hints import BoundPoint from tests.bind_tests.utils import (bound_edges_types, bound_polygons_types) from tests.strategies import (booleans, floats, unsigned_integers) booleans = booleans unsigned_integers = unsigned_integers points = strategies.builds(BoundPoint, floats, floats) polygons_types = bound_polygons_types edges_types = bound_edges_types leaf_sweep_events = to_plain_bound_sweep_events(strategies.none()) acyclic_sweep_events = to_acyclic_bound_sweep_events() sweep_events = to_bound_sweep_events() nested_sweep_events = to_nested_bound_sweep_events() maybe_sweep_events = strategies.none() | sweep_events

43.583333

70

0.68738

d2222ceb694665f3958bcd9c395bbc4372b26251

606

py

Python

example_project/blog/factories.py

allran/djangorestframework-appapi

5e843b70910ccd55d787096ee08eb85315c80000

[ "BSD-2-Clause" ]

4

2019-10-15T06:47:29.000Z

2019-11-11T13:16:15.000Z

example_project/blog/factories.py

allran/djangorestframework-appapi

5e843b70910ccd55d787096ee08eb85315c80000

[ "BSD-2-Clause" ]

null

example_project/blog/factories.py

allran/djangorestframework-appapi

5e843b70910ccd55d787096ee08eb85315c80000

[ "BSD-2-Clause" ]

null

# -*- encoding: utf-8 -*- import factory from faker import Factory as FakerFactory from .models import ( Author, Blog, ) faker = FakerFactory.create() faker.seed(883843) class BlogFactory(factory.django.DjangoModelFactory): class Meta: model = Blog title = factory.LazyAttribute(lambda x: faker.name()) content = factory.LazyAttribute(lambda x: faker.name()) class AuthorFactory(factory.django.DjangoModelFactory): class Meta: model = Author name = factory.LazyAttribute(lambda x: faker.name()) email = factory.LazyAttribute(lambda x: faker.email())

21.642857

59

0.70132

8a27adb3e8e25e0949f740704a115c233df5e798

290

py

Python

src/camera-test.py

parhamzm/OpenCV-FaceDetection_Filtering

61cb497adeebac3d0c5062885078b4ba239ed963

[ "MIT" ]

null

src/camera-test.py

parhamzm/OpenCV-FaceDetection_Filtering

61cb497adeebac3d0c5062885078b4ba239ed963

[ "MIT" ]

null

src/camera-test.py

parhamzm/OpenCV-FaceDetection_Filtering

61cb497adeebac3d0c5062885078b4ba239ed963

[ "MIT" ]

null

import numpy as np import cv2 cap = cv2.VideoCapture(0) while True: ret, frame = cap.read() grayscale = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) cv2.imshow('frame', frame) cv2.imshow('frame2', grayscale) if cv2.waitKey(20) & 0xFF == ord('q'): break

22.307692

56

0.617241

af72e2f5e1e65273b8dd9fc984cfe188e06a8f1a

1,690

py

Python

indico/modules/events/sessions/models/types.py

uxmaster/indico

ecd19f17ef6fdc9f5584f59c87ec647319ce5d31

[ "MIT" ]

null

indico/modules/events/sessions/models/types.py

uxmaster/indico

ecd19f17ef6fdc9f5584f59c87ec647319ce5d31

[ "MIT" ]

null

indico/modules/events/sessions/models/types.py

uxmaster/indico

ecd19f17ef6fdc9f5584f59c87ec647319ce5d31

[ "MIT" ]

null

# This file is part of Indico. # Copyright (C) 2002 - 2019 CERN # # Indico is free software; you can redistribute it and/or # modify it under the terms of the MIT License; see the # LICENSE file for more details. from __future__ import unicode_literals from sqlalchemy.ext.declarative import declared_attr from indico.core.db import db from indico.util.locators import locator_property from indico.util.string import format_repr, return_ascii class SessionType(db.Model): __tablename__ = 'session_types' @declared_attr def __table_args__(cls): return (db.Index('ix_uq_session_types_event_id_name_lower', cls.event_id, db.func.lower(cls.name), unique=True), {'schema': 'events'}) id = db.Column( db.Integer, primary_key=True ) event_id = db.Column( db.Integer, db.ForeignKey('events.events.id'), index=True, nullable=False ) name = db.Column( db.String, nullable=False ) code = db.Column( db.String, nullable=False, default='' ) is_poster = db.Column( db.Boolean, nullable=False, default=False ) event = db.relationship( 'Event', lazy=True, backref=db.backref( 'session_types', cascade='all, delete-orphan', lazy=True ) ) # relationship backrefs: # - sessions (Session.type) @return_ascii def __repr__(self): return format_repr(self, 'id', _text=self.name) @locator_property def locator(self): return dict(self.event.locator, session_type_id=self.id)

23.802817

106

0.616568

c4f8370c65c932a5e676049d43b43fc639fa4ef9

3,782

py

Python

PyCapture2-2.13.31/examples/python3/SaveImageToAVIEx.py

sjtu-automatic-maritime-system/PengZhenghao

c063294d44ea9be972114b2c144dab3d9a2de863

[ "MIT" ]

1

2019-04-16T09:07:26.000Z

PyCapture2-2.13.31/examples/python3/SaveImageToAVIEx.py

sjtu-automatic-maritime-system/PengZhenghao

c063294d44ea9be972114b2c144dab3d9a2de863

[ "MIT" ]

null

PyCapture2-2.13.31/examples/python3/SaveImageToAVIEx.py

sjtu-automatic-maritime-system/PengZhenghao

c063294d44ea9be972114b2c144dab3d9a2de863

[ "MIT" ]

null

# ============================================================================= # Copyright (c) 2001-2018 FLIR Systems, Inc. All Rights Reserved. # # This software is the confidential and proprietary information of FLIR # Integrated Imaging Solutions, Inc. ("Confidential Information"). You # shall not disclose such Confidential Information and shall use it only in # accordance with the terms of the license agreement you entered into # with FLIR Integrated Imaging Solutions, Inc. (FLIR). # # FLIR MAKES NO REPRESENTATIONS OR WARRANTIES ABOUT THE SUITABILITY OF THE # SOFTWARE, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR # PURPOSE, OR NON-INFRINGEMENT. FLIR SHALL NOT BE LIABLE FOR ANY DAMAGES # SUFFERED BY LICENSEE AS A RESULT OF USING, MODIFYING OR DISTRIBUTING # THIS SOFTWARE OR ITS DERIVATIVES. # ============================================================================= import PyCapture2 def print_build_info(): lib_ver = PyCapture2.getLibraryVersion() print('PyCapture2 library version: %d %d %d %d' % (lib_ver[0], lib_ver[1], lib_ver[2], lib_ver[3])) print() def print_camera_info(cam): cam_info = cam.getCameraInfo() print('\n*** CAMERA INFORMATION ***\n') print('Serial number - %d', cam_info.serialNumber) print('Camera model - %s', cam_info.modelName) print('Camera vendor - %s', cam_info.vendorName) print('Sensor - %s', cam_info.sensorInfo) print('Resolution - %s', cam_info.sensorResolution) print('Firmware version - %s', cam_info.firmwareVersion) print('Firmware build time - %s', cam_info.firmwareBuildTime) print() def save_video_helper(cam, file_format, filename, framerate): num_images = 100 video = PyCapture2.FlyCapture2Video() for i in range(num_images): try: image = cam.retrieveBuffer() except PyCapture2.Fc2error as fc2Err: print('Error retrieving buffer : %s' % fc2Err) continue print('Grabbed image {}'.format(i)) if (i == 0): if file_format == 'AVI': video.AVIOpen(filename, framerate) elif file_format == 'MJPG': video.MJPGOpen(filename, framerate, 75) elif file_format == 'H264': video.H264Open(filename, framerate, image.getCols(), image.getRows(), 1000000) else: print('Specified format is not available.') return video.append(image) print('Appended image %d...' % i) print('Appended {} images to {} file: {}...'.format(num_images, file_format, filename)) video.close() # # Example Main # # Print PyCapture2 Library Information print_build_info() # Ensure sufficient cameras are found bus = PyCapture2.BusManager() num_cams = bus.getNumOfCameras() print('Number of cameras detected: %d' % num_cams) if not num_cams: print('Insufficient number of cameras. Exiting...') exit() # Select camera on 0th index cam = PyCapture2.Camera() cam.connect(bus.getCameraFromIndex(0)) # Print camera details print_camera_info(cam) print('Starting capture...') cam.startCapture() print('Detecting frame rate from Camera') fRateProp = cam.getProperty(PyCapture2.PROPERTY_TYPE.FRAME_RATE) framerate = fRateProp.absValue print('Using frame rate of {}'.format(framerate)) for file_format in ('AVI','H264','MJPG'): filename = 'SaveImageToAviEx_{}.avi'.format(file_format) save_video_helper(cam, file_format, filename.encode('utf-8'), framerate) print('Stopping capture...') cam.stopCapture() cam.disconnect() input('Done! Press Enter to exit...\n')

35.345794

104

0.641988

ac818486ddb8df5fc9b2b1c4d429452d1fecff71

4,614

py

Python

ark-tweet-nlp-0.3.2/postagger.py

enlighter/twitter-disasters-info-retrieval

0a362fa68c1604152709dc25922c5611b0d1a484

[ "MIT" ]

null

ark-tweet-nlp-0.3.2/postagger.py

enlighter/twitter-disasters-info-retrieval

0a362fa68c1604152709dc25922c5611b0d1a484

[ "MIT" ]

null

ark-tweet-nlp-0.3.2/postagger.py

enlighter/twitter-disasters-info-retrieval

0a362fa68c1604152709dc25922c5611b0d1a484

[ "MIT" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- """Simple Python wrapper for runTagger.sh script for CMU's Tweet Tokeniser and Part of Speech tagger: http://www.ark.cs.cmu.edu/TweetNLP/ Usage: results=runtagger_parse(['example tweet 1', 'example tweet 2']) results will contain a list of lists (one per tweet) of triples, each triple represents (term, type, confidence) """ import subprocess import shlex # The only relavent source I've found is here: # http://m1ked.com/post/12304626776/pos-tagger-for-twitter-successfully-implemented-in # which is a very simple implementation, my implementation is a bit more # useful (but not much). # NOTE this command is directly lifted from runTagger.sh RUN_TAGGER_CMD = "java -XX:ParallelGCThreads=2 -Xmx500m -jar ark-tweet-nlp-0.3.2.jar" def _split_results(rows): """Parse the tab-delimited returned lines, modified from: https://github.com/brendano/ark-tweet-nlp/blob/master/scripts/show.py""" for line in rows: line = line.strip() # remove '\n' if len(line) > 0: if line.count('\t') == 2: parts = line.split('\t') tokens = parts[0] tags = parts[1] confidence = float(parts[2]) yield tokens, tags, confidence def _call_runtagger(tweets, run_tagger_cmd=RUN_TAGGER_CMD): """Call runTagger.sh using a named input file""" # remove carriage returns as they are tweet separators for the stdin # interface tweets_cleaned = [tw.replace('\n', ' ') for tw in tweets] message = "\n".join(tweets_cleaned) # force UTF-8 encoding (from internal unicode type) to avoid .communicate encoding error as per: # http://stackoverflow.com/questions/3040101/python-encoding-for-pipe-communicate message = message.encode('utf-8') # build a list of args args = shlex.split(run_tagger_cmd) args.append('--output-format') args.append('conll') po = subprocess.Popen(args, stdin=subprocess.PIPE, stdout=subprocess.PIPE, stderr=subprocess.PIPE) # old call - made a direct call to runTagger.sh (not Windows friendly) #po = subprocess.Popen([run_tagger_cmd, '--output-format', 'conll'], stdin=subprocess.PIPE, stdout=subprocess.PIPE, stderr=subprocess.PIPE) result = po.communicate(message) # expect a tuple of 2 items like: # ('hello\t!\t0.9858\nthere\tR\t0.4168\n\n', # 'Listening on stdin for input. (-h for help)\nDetected text input format\nTokenized and tagged 1 tweets (2 tokens) in 7.5 seconds: 0.1 tweets/sec, 0.3 tokens/sec\n') pos_result = result[0].strip('\n\n') # get first line, remove final double carriage return pos_result = pos_result.split('\n\n') # split messages by double carriage returns pos_results = [pr.split('\n') for pr in pos_result] # split parts of message by each carriage return return pos_results def runtagger_parse(tweets, run_tagger_cmd=RUN_TAGGER_CMD): """Call runTagger.sh on a list of tweets, parse the result, return lists of tuples of (term, type, confidence)""" pos_raw_results = _call_runtagger(tweets, run_tagger_cmd) pos_result = [] for pos_raw_result in pos_raw_results: pos_result.append([x for x in _split_results(pos_raw_result)]) return pos_result def check_script_is_present(run_tagger_cmd=RUN_TAGGER_CMD): """Simple test to make sure we can see the script""" success = False try: args = shlex.split(run_tagger_cmd) args.append("--help") po = subprocess.Popen(args, stdout=subprocess.PIPE) # old call - made a direct call to runTagger.sh (not Windows friendly) #po = subprocess.Popen([run_tagger_cmd, '--help'], stdout=subprocess.PIPE) while not po.poll(): lines = [l for l in po.stdout] # we expected the first line of --help to look like the following: assert "RunTagger [options]" in lines[0] success = True except OSError as err: print "Caught an OSError, have you specified the correct path to runTagger.sh? We are using \"%s\". Exception: %r" % (run_tagger_cmd, repr(err)) return success if __name__ == "__main__": print "Checking that we can see \"%s\", this will crash if we can't" % (RUN_TAGGER_CMD) success = check_script_is_present() if success: print "Success." print "Now pass in two messages, get a list of tuples back:" tweets = ['I predict I won\'t win a single game I bet on. Got Cliff Lee today, so if he loses its on me RT @e_one: Texas (cont) http:\//tl.gd\/6meogh', 'and a second message'] print runtagger_parse(tweets)

47.081633

183

0.683572

771d228a71da476ad35e7b87c9c46d55499dcd42

8,851

py

Python

great_expectations/exceptions.py

ap3xx/great_expectations

67251ff3fcb60b1a52a6ece1bec98fb8e96f6a96

[ "Apache-2.0" ]

null

great_expectations/exceptions.py

ap3xx/great_expectations

67251ff3fcb60b1a52a6ece1bec98fb8e96f6a96

[ "Apache-2.0" ]

47

2020-07-15T06:32:50.000Z

2022-03-29T12:03:23.000Z

great_expectations/exceptions.py

ap3xx/great_expectations

67251ff3fcb60b1a52a6ece1bec98fb8e96f6a96

[ "Apache-2.0" ]

null

import importlib import json from marshmallow import ValidationError class GreatExpectationsError(Exception): def __init__(self, message): self.message = message super().__init__(message) class GreatExpectationsValidationError(ValidationError, GreatExpectationsError): def __init__(self, message, validation_error): self.message = message self.messages = validation_error.messages class SuiteEditNotebookCustomTemplateModuleNotFoundError(ModuleNotFoundError): def __init__(self, custom_module): message = f"The custom module '{custom_module}' could not be found" super().__init__(message) class DataContextError(GreatExpectationsError): pass class CheckpointError(DataContextError): pass class CheckpointNotFoundError(CheckpointError): pass class StoreBackendError(DataContextError): pass class UnavailableMetricError(GreatExpectationsError): pass class ParserError(GreatExpectationsError): pass class InvalidConfigurationYamlError(DataContextError): pass class InvalidTopLevelConfigKeyError(GreatExpectationsError): pass class MissingTopLevelConfigKeyError(GreatExpectationsValidationError): pass class InvalidDataContextConfigError(GreatExpectationsValidationError): pass class InvalidBatchKwargsError(GreatExpectationsError): pass class InvalidBatchIdError(GreatExpectationsError): pass class InvalidDataContextKeyError(DataContextError): pass class UnsupportedConfigVersionError(DataContextError): pass class EvaluationParameterError(GreatExpectationsError): pass class ProfilerError(GreatExpectationsError): pass class InvalidConfigError(DataContextError): def __init__(self, message): self.message = message super().__init__(self.message) class MissingConfigVariableError(InvalidConfigError): def __init__(self, message, missing_config_variable=None): if not missing_config_variable: missing_config_variable = [] self.message = message self.missing_config_variable = missing_config_variable super().__init__(self.message) class AmbiguousDataAssetNameError(DataContextError): def __init__(self, message, candidates=None): self.message = message self.candidates = candidates super().__init__(self.message) class StoreConfigurationError(DataContextError): pass class InvalidExpectationKwargsError(GreatExpectationsError): pass class InvalidExpectationConfigurationError(GreatExpectationsError): pass class InvalidValidationResultError(GreatExpectationsError): pass class GreatExpectationsTypeError(TypeError): pass class StoreError(DataContextError): pass class InvalidKeyError(StoreError): pass class InvalidCacheValueError(GreatExpectationsError): def __init__(self, result_dict): template = """\ Invalid result values were found when trying to instantiate an ExpectationValidationResult. - Invalid result values are likely caused by inconsistent cache values. - Great Expectations enables caching by default. - Please ensure that caching behavior is consistent between the underlying Dataset (e.g. Spark) and Great Expectations. Result: {} """ self.message = template.format(json.dumps(result_dict, indent=2)) super().__init__(self.message) class ConfigNotFoundError(DataContextError): """The great_expectations dir could not be found.""" def __init__(self): self.message = """Error: No great_expectations directory was found here! - Please check that you are in the correct directory or have specified the correct directory. - If you have never run Great Expectations in this project, please run `great_expectations init` to get started. """ super().__init__(self.message) class PluginModuleNotFoundError(GreatExpectationsError): """A module import failed.""" def __init__(self, module_name): template = """\ No module named `{}` could be found in your plugins directory. - Please verify your plugins directory is configured correctly. - Please verify you have a module named `{}` in your plugins directory. """ self.message = template.format(module_name, module_name) colored_template = "<red>" + template + "</red>" module_snippet = "</red><yellow>" + module_name + "</yellow><red>" self.cli_colored_message = colored_template.format( module_snippet, module_snippet ) super().__init__(self.message) class PluginClassNotFoundError(DataContextError, AttributeError): """A module import failed.""" def __init__(self, module_name, class_name): class_name_changes = { "FixedLengthTupleFilesystemStoreBackend": "TupleFilesystemStoreBackend", "FixedLengthTupleS3StoreBackend": "TupleS3StoreBackend", "FixedLengthTupleGCSStoreBackend": "TupleGCSStoreBackend", "InMemoryEvaluationParameterStore": "EvaluationParameterStore", "DatabricksTableGenerator": "DatabricksTableBatchKwargsGenerator", "GlobReaderGenerator": "GlobReaderBatchKwargsGenerator", "SubdirReaderGenerator": "SubdirReaderBatchKwargsGenerator", "QueryGenerator": "QueryBatchKwargsGenerator", "TableGenerator": "TableBatchKwargsGenerator", "S3Generator": "S3GlobReaderBatchKwargsGenerator", "ExtractAndStoreEvaluationParamsAction": "StoreEvaluationParametersAction", "StoreAction": "StoreValidationResultAction", } if class_name_changes.get(class_name): template = """The module: `{}` does not contain the class: `{}`. The class name `{}` has changed to `{}`.""" self.message = template.format( module_name, class_name, class_name, class_name_changes.get(class_name) ) else: template = """The module: `{}` does not contain the class: `{}`. - Please verify that the class named `{}` exists.""" self.message = template.format(module_name, class_name, class_name) colored_template = "<red>" + template + "</red>" module_snippet = "</red><yellow>" + module_name + "</yellow><red>" class_snippet = "</red><yellow>" + class_name + "</yellow><red>" if class_name_changes.get(class_name): new_class_snippet = ( "</red><yellow>" + class_name_changes.get(class_name) + "</yellow><red>" ) self.cli_colored_message = colored_template.format( module_snippet, class_snippet, class_snippet, new_class_snippet ) else: self.cli_colored_message = colored_template.format( module_snippet, class_snippet, class_snippet, ) super().__init__(self.message) class ClassInstantiationError(GreatExpectationsError): def __init__(self, module_name, package_name, class_name): module_spec = importlib.util.find_spec(module_name, package=package_name) if not module_spec: if not package_name: package_name = "" self.message = f"""No module named "{package_name + module_name}" could be found in the repository. \ Please make sure that the file, corresponding to this package and module, exists and that dynamic loading of code \ modules, templates, and assets is supported in your execution environment. This error is unrecoverable. """ else: self.message = f"""The module "{module_name}" exists; however, the system is unable to create an instance \ of the class "{class_name}", searched for inside this module. Please make sure that the class named "{class_name}" is \ properly defined inside its intended module and declared correctly by the calling entity. This error is unrecoverable. """ super().__init__(self.message) class ExpectationSuiteNotFoundError(GreatExpectationsError): def __init__(self, data_asset_name): self.data_asset_name = data_asset_name self.message = ( "No expectation suite found for data_asset_name %s" % data_asset_name ) super().__init__(self.message) class BatchKwargsError(DataContextError): def __init__(self, message, batch_kwargs=None): self.message = message self.batch_kwargs = batch_kwargs super().__init__(self.message) class DatasourceInitializationError(GreatExpectationsError): def __init__(self, datasource_name, message): self.message = "Cannot initialize datasource %s, error: %s" % ( datasource_name, message, ) super().__init__(self.message) class InvalidConfigValueTypeError(DataContextError): pass

32.30292

120

0.707604

71945fb988133992fb441fa7ac8bb7f8654a6e1b

1,792

py

Python

python/pascal_triangle.py

shub0/leetcode

8221d10f201d001abcb15b27c9cf4b8cd5060f1f

[ "BSD-3-Clause" ]

null

python/pascal_triangle.py

shub0/leetcode

8221d10f201d001abcb15b27c9cf4b8cd5060f1f

[ "BSD-3-Clause" ]

null

python/pascal_triangle.py

shub0/leetcode

8221d10f201d001abcb15b27c9cf4b8cd5060f1f

[ "BSD-3-Clause" ]

null

#! /usr/bin/python ''' Given numRows, generate the first numRows of Pascal's triangle. For example, given numRows = 5, Return [ [1], [1,1], [1,2,1], [1,3,3,1], [1,4,6,4,1] ] ''' import math class Solution: # @param numRows, an integer # @return a list of lists of integers def generate(self, numRows): if numRows == 0: return [] if numRows == 1: return [[1]] pascal_triangle = list() curr_row = [1] pascal_triangle.append(curr_row) for row_index in range(1, numRows): curr_row = [0] * (row_index + 1) curr_row[0] = 1 curr_row[-1] = 1 for column_index in range(1, row_index): curr_row[column_index] = pascal_triangle[row_index - 1][column_index - 1] + pascal_triangle[row_index - 1][column_index] pascal_triangle.append(curr_row) return pascal_triangle # @param n, an integer # @param k, an integer # @return an integer def getCombinational(self, n, k): return math.factorial(n) / math.factorial(n - k) / math.factorial(k) # @param rowIndex, an integer # @return a list of integers def getRow(self, rowIndex): if rowIndex == 0: return [1] prev_row = [1] for curr_row_index in range(1, rowIndex + 1): curr_row = [0] * (curr_row_index + 1) curr_row[0] = 1 curr_row[-1] = 1 for column_index in range(1, curr_row_index): curr_row[column_index] = prev_row[column_index - 1] + prev_row[column_index] prev_row = curr_row return prev_row if __name__ == '__main__': solution = Solution() print solution.generate(7) print solution.getRow(3)

28.444444

136

0.573103

2432cea86c791ca43e4b7bb4d8923916aa0be20d

122

py

Python

Python/School/Project/q2.py

abdalrhmanyasser/Abdalrhman_Rep

e0fc3caa2cc04e92f591ccd7934586986d194000

[ "CC0-1.0" ]

null

Python/School/Project/q2.py

abdalrhmanyasser/Abdalrhman_Rep

e0fc3caa2cc04e92f591ccd7934586986d194000

[ "CC0-1.0" ]

null

Python/School/Project/q2.py

abdalrhmanyasser/Abdalrhman_Rep

e0fc3caa2cc04e92f591ccd7934586986d194000

[ "CC0-1.0" ]

null

new_text = [] for i in input("enter your text : ").split(): new_text.append(i.capitalize()) print(" ".join(new_text))

24.4

45

0.647541

2229d633063975601d8b69179326163a31b1091d

7,976

py

Python

PathPlanning/AStar/a_star.py

robberwick/PythonRobotics

e8ffc01cc7975e02e226b547583d955dda8d0150

[ "MIT" ]

2

2020-03-07T11:04:57.000Z

2020-04-10T03:34:47.000Z

PathPlanning/AStar/a_star.py

JeffLIrion/PythonRobotics

487a7e4141dc4e2a0ae887e7fec98251900362b7

[ "MIT" ]

null

PathPlanning/AStar/a_star.py

JeffLIrion/PythonRobotics

487a7e4141dc4e2a0ae887e7fec98251900362b7

[ "MIT" ]

1

2022-03-07T10:30:07.000Z

""" A* grid planning author: Atsushi Sakai(@Atsushi_twi) Nikos Kanargias (nkana@tee.gr) See Wikipedia article (https://en.wikipedia.org/wiki/A*_search_algorithm) """ import math import matplotlib.pyplot as plt show_animation = True class AStarPlanner: def __init__(self, ox, oy, reso, rr): """ Initialize grid map for a star planning ox: x position list of Obstacles [m] oy: y position list of Obstacles [m] reso: grid resolution [m] rr: robot radius[m] """ self.reso = reso self.rr = rr self.calc_obstacle_map(ox, oy) self.motion = self.get_motion_model() class Node: def __init__(self, x, y, cost, pind): self.x = x # index of grid self.y = y # index of grid self.cost = cost self.pind = pind def __str__(self): return str(self.x) + "," + str(self.y) + "," + str(self.cost) + "," + str(self.pind) def planning(self, sx, sy, gx, gy): """ A star path search input: sx: start x position [m] sy: start y position [m] gx: goal x position [m] gy: goal y position [m] output: rx: x position list of the final path ry: y position list of the final path """ nstart = self.Node(self.calc_xyindex(sx, self.minx), self.calc_xyindex(sy, self.miny), 0.0, -1) ngoal = self.Node(self.calc_xyindex(gx, self.minx), self.calc_xyindex(gy, self.miny), 0.0, -1) open_set, closed_set = dict(), dict() open_set[self.calc_grid_index(nstart)] = nstart while 1: if len(open_set) == 0: print("Open set is empty..") break c_id = min( open_set, key=lambda o: open_set[o].cost + self.calc_heuristic(ngoal, open_set[o])) current = open_set[c_id] # show graph if show_animation: # pragma: no cover plt.plot(self.calc_grid_position(current.x, self.minx), self.calc_grid_position(current.y, self.miny), "xc") # for stopping simulation with the esc key. plt.gcf().canvas.mpl_connect('key_release_event', lambda event: [exit(0) if event.key == 'escape' else None]) if len(closed_set.keys()) % 10 == 0: plt.pause(0.001) if current.x == ngoal.x and current.y == ngoal.y: print("Find goal") ngoal.pind = current.pind ngoal.cost = current.cost break # Remove the item from the open set del open_set[c_id] # Add it to the closed set closed_set[c_id] = current # expand_grid search grid based on motion model for i, _ in enumerate(self.motion): node = self.Node(current.x + self.motion[i][0], current.y + self.motion[i][1], current.cost + self.motion[i][2], c_id) n_id = self.calc_grid_index(node) # If the node is not safe, do nothing if not self.verify_node(node): continue if n_id in closed_set: continue if n_id not in open_set: open_set[n_id] = node # discovered a new node else: if open_set[n_id].cost > node.cost: # This path is the best until now. record it open_set[n_id] = node rx, ry = self.calc_final_path(ngoal, closed_set) return rx, ry def calc_final_path(self, ngoal, closedset): # generate final course rx, ry = [self.calc_grid_position(ngoal.x, self.minx)], [ self.calc_grid_position(ngoal.y, self.miny)] pind = ngoal.pind while pind != -1: n = closedset[pind] rx.append(self.calc_grid_position(n.x, self.minx)) ry.append(self.calc_grid_position(n.y, self.miny)) pind = n.pind return rx, ry @staticmethod def calc_heuristic(n1, n2): w = 1.0 # weight of heuristic d = w * math.hypot(n1.x - n2.x, n1.y - n2.y) return d def calc_grid_position(self, index, minp): """ calc grid position :param index: :param minp: :return: """ pos = index * self.reso + minp return pos def calc_xyindex(self, position, min_pos): return round((position - min_pos) / self.reso) def calc_grid_index(self, node): return (node.y - self.miny) * self.xwidth + (node.x - self.minx) def verify_node(self, node): px = self.calc_grid_position(node.x, self.minx) py = self.calc_grid_position(node.y, self.miny) if px < self.minx: return False elif py < self.miny: return False elif px >= self.maxx: return False elif py >= self.maxy: return False # collision check if self.obmap[node.x][node.y]: return False return True def calc_obstacle_map(self, ox, oy): self.minx = round(min(ox)) self.miny = round(min(oy)) self.maxx = round(max(ox)) self.maxy = round(max(oy)) print("minx:", self.minx) print("miny:", self.miny) print("maxx:", self.maxx) print("maxy:", self.maxy) self.xwidth = round((self.maxx - self.minx) / self.reso) self.ywidth = round((self.maxy - self.miny) / self.reso) print("xwidth:", self.xwidth) print("ywidth:", self.ywidth) # obstacle map generation self.obmap = [[False for i in range(self.ywidth)] for i in range(self.xwidth)] for ix in range(self.xwidth): x = self.calc_grid_position(ix, self.minx) for iy in range(self.ywidth): y = self.calc_grid_position(iy, self.miny) for iox, ioy in zip(ox, oy): d = math.hypot(iox - x, ioy - y) if d <= self.rr: self.obmap[ix][iy] = True break @staticmethod def get_motion_model(): # dx, dy, cost motion = [[1, 0, 1], [0, 1, 1], [-1, 0, 1], [0, -1, 1], [-1, -1, math.sqrt(2)], [-1, 1, math.sqrt(2)], [1, -1, math.sqrt(2)], [1, 1, math.sqrt(2)]] return motion def main(): print(__file__ + " start!!") # start and goal position sx = 10.0 # [m] sy = 10.0 # [m] gx = 50.0 # [m] gy = 50.0 # [m] grid_size = 2.0 # [m] robot_radius = 1.0 # [m] # set obstable positions ox, oy = [], [] for i in range(-10, 60): ox.append(i) oy.append(-10.0) for i in range(-10, 60): ox.append(60.0) oy.append(i) for i in range(-10, 61): ox.append(i) oy.append(60.0) for i in range(-10, 61): ox.append(-10.0) oy.append(i) for i in range(-10, 40): ox.append(20.0) oy.append(i) for i in range(0, 40): ox.append(40.0) oy.append(60.0 - i) if show_animation: # pragma: no cover plt.plot(ox, oy, ".k") plt.plot(sx, sy, "og") plt.plot(gx, gy, "xb") plt.grid(True) plt.axis("equal") a_star = AStarPlanner(ox, oy, grid_size, robot_radius) rx, ry = a_star.planning(sx, sy, gx, gy) if show_animation: # pragma: no cover plt.plot(rx, ry, "-r") plt.show() if __name__ == '__main__': main()

29.109489

99

0.503009

7d040410ad52288978ee523cffe1c8bda5eea87a

1,840

py

Python

retinopathy/models/heads/gwap.py

RamsteinWR/Diabetic-Retinopathy-Blindness-Detection

24390aeefd197600255a961189872dd4dfc77092

[ "MIT" ]

68

2019-09-08T20:04:23.000Z

2021-05-05T10:05:14.000Z

retinopathy/models/heads/gwap.py

RamsteinWR/Diabetic-Retinopathy-Blindness-Detection

24390aeefd197600255a961189872dd4dfc77092

[ "MIT" ]

1

2019-09-24T06:40:33.000Z

2019-10-04T09:13:35.000Z

retinopathy/models/heads/gwap.py

RamsteinWR/Diabetic-Retinopathy-Blindness-Detection

24390aeefd197600255a961189872dd4dfc77092

[ "MIT" ]

25

2019-09-09T04:42:51.000Z

2022-03-28T15:01:30.000Z

from pytorch_toolbelt.modules.pooling import GWAP from torch import nn class GlobalWeightedAvgPoolHead(nn.Module): """ 1) Squeeze last feature map in num_classes 2) Compute global average """ def __init__(self, feature_maps, num_classes: int, dropout=0.): super().__init__() self.features_size = feature_maps[-1] self.gwap = GWAP(self.features_size) self.dropout = nn.Dropout(dropout) self.logits = nn.Linear(self.features_size, num_classes) # Regression to grade using SSD-like module self.regression = nn.Sequential( nn.Linear(self.features_size, 16), nn.ELU(inplace=True), nn.Linear(16, 16), nn.ELU(inplace=True), nn.Linear(16, 16), nn.ELU(inplace=True), nn.Linear(16, 1), nn.ELU(inplace=True), ) self.ordinal = nn.Sequential( nn.Linear(self.features_size, 16), nn.ELU(inplace=True), nn.Linear(16, 16), nn.ELU(inplace=True), nn.Linear(16, 16), nn.ELU(inplace=True), nn.Linear(16, num_classes - 1), ) def forward(self, feature_maps): # Take last feature map features = feature_maps[-1] features = self.gwap(features) features = features.view(features.size(0), features.size(1)) features = self.dropout(features) logits = self.logits(features) regression = self.regression(features) if regression.size(1) == 1: regression = regression.squeeze(1) ordinal = self.ordinal(features).sigmoid().sum(dim=1) return { 'features': features, 'logits': logits, 'regression': regression, 'ordinal': ordinal }

29.677419

68

0.571739

092905028cc957eb5b398e024528b38074f0b84c

1,088

py

Python

02-files-lab2/read_write_file.py

iproduct/course-robotics-npmg

0feb2ded46007ba87b8128f1f2e039036ef274bd

[ "Apache-2.0" ]

null

02-files-lab2/read_write_file.py

iproduct/course-robotics-npmg

0feb2ded46007ba87b8128f1f2e039036ef274bd

[ "Apache-2.0" ]

null

02-files-lab2/read_write_file.py

iproduct/course-robotics-npmg

0feb2ded46007ba87b8128f1f2e039036ef274bd

[ "Apache-2.0" ]

1

2021-03-17T09:08:02.000Z

"""File read write demo script""" def find_count(substring, string): """finds the number of occurences of substring in string""" counter = 0 index = string.find(substring) while index >= 0: counter += 1 index = string.find(substring, index + 1) return counter if __name__ == "__main__": """main script""" with open("read_write_file.py", "rt") as f: # read file with automatic closing with open("comments.txt", "wt") as out: for line in f: # read one line start_of_comment = line.find("#") str_start = line[:start_of_comment] quote_count = find_count("'", str_start) double_quote_count = find_count('"', str_start) find_count('"', str_start) % 2 == 0 if start_of_comment > 0 and quote_count % 2 == 0 and double_quote_count % 2 == 0: comment = line[start_of_comment:] # get comment only string print(comment, end="") # print comment out.write(comment) # write to file

41.846154

97

0.571691

be61eced7489304f1a225d0dbe7102f6434c5a6b

2,975

py

Python

sdk/recoveryservices/azure-mgmt-recoveryservicesbackup/azure/mgmt/recoveryservicesbackup/models/azure_vm_workload_sap_hana_system_workload_item.py

SanjayHukumRana/azure-sdk-for-python

0669a0f07aaead29852f9d59cce8bc2d6085a7a2

[ "MIT" ]

null

sdk/recoveryservices/azure-mgmt-recoveryservicesbackup/azure/mgmt/recoveryservicesbackup/models/azure_vm_workload_sap_hana_system_workload_item.py

SanjayHukumRana/azure-sdk-for-python

0669a0f07aaead29852f9d59cce8bc2d6085a7a2

[ "MIT" ]

null

sdk/recoveryservices/azure-mgmt-recoveryservicesbackup/azure/mgmt/recoveryservicesbackup/models/azure_vm_workload_sap_hana_system_workload_item.py

SanjayHukumRana/azure-sdk-for-python

0669a0f07aaead29852f9d59cce8bc2d6085a7a2

[ "MIT" ]

null

# coding=utf-8 # -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for # license information. # # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is # regenerated. # -------------------------------------------------------------------------- from .azure_vm_workload_item import AzureVmWorkloadItem class AzureVmWorkloadSAPHanaSystemWorkloadItem(AzureVmWorkloadItem): """Azure VM workload-specific workload item representing SAP HANA System. All required parameters must be populated in order to send to Azure. :param backup_management_type: Type of backup management to backup an item. :type backup_management_type: str :param workload_type: Type of workload for the backup management :type workload_type: str :param friendly_name: Friendly name of the backup item. :type friendly_name: str :param protection_state: State of the back up item. Possible values include: 'Invalid', 'NotProtected', 'Protecting', 'Protected', 'ProtectionFailed' :type protection_state: str or ~azure.mgmt.recoveryservicesbackup.models.ProtectionStatus :param workload_item_type: Required. Constant filled by server. :type workload_item_type: str :param parent_name: Name for instance or AG :type parent_name: str :param server_name: Host/Cluster Name for instance or AG :type server_name: str :param is_auto_protectable: Indicates if workload item is auto-protectable :type is_auto_protectable: bool :param subinquireditemcount: For instance or AG, indicates number of DB's present :type subinquireditemcount: int :param sub_workload_item_count: For instance or AG, indicates number of DB's to be protected :type sub_workload_item_count: int """ _validation = { 'workload_item_type': {'required': True}, } _attribute_map = { 'backup_management_type': {'key': 'backupManagementType', 'type': 'str'}, 'workload_type': {'key': 'workloadType', 'type': 'str'}, 'friendly_name': {'key': 'friendlyName', 'type': 'str'}, 'protection_state': {'key': 'protectionState', 'type': 'str'}, 'workload_item_type': {'key': 'workloadItemType', 'type': 'str'}, 'parent_name': {'key': 'parentName', 'type': 'str'}, 'server_name': {'key': 'serverName', 'type': 'str'}, 'is_auto_protectable': {'key': 'isAutoProtectable', 'type': 'bool'}, 'subinquireditemcount': {'key': 'subinquireditemcount', 'type': 'int'}, 'sub_workload_item_count': {'key': 'subWorkloadItemCount', 'type': 'int'}, } def __init__(self, **kwargs): super(AzureVmWorkloadSAPHanaSystemWorkloadItem, self).__init__(**kwargs) self.workload_item_type = 'SAPHanaSystem'

43.75

82

0.665882

3affa5d4bec0cc1e46177bddedea7a476ca9552b

9,970

py

Python

game/sprites.py

coder489/Freestyle

d681bc839dd4b085f31e9b471edc5211388ddf83

[ "MIT" ]

null

game/sprites.py

coder489/Freestyle

d681bc839dd4b085f31e9b471edc5211388ddf83

[ "MIT" ]

null

game/sprites.py

coder489/Freestyle

d681bc839dd4b085f31e9b471edc5211388ddf83

[ "MIT" ]

null

import pygame as pg from settings import * from os import path vec = pg.math.Vector2 class Player(pg.sprite.Sprite): """ Creates the Player class to provide a template for players in the game. """ def __init__(self, game, img): """ Initializes (sets up) the player class. Parameters: self (self): keyword we can access the attributes and methods of the class in python game: used to reference items in the game class img (.png file): png file that has an image for the player Source: YouTube Videos KidsCanCode provided information needed for initial setup of code, though code was majorly altered to tailor to project Source Link: https://www.youtube.com/watch?v=uWvb3QzA48c """ self.game = game pg.sprite.Sprite.__init__(self) self.image = pg.Surface((32,32)) self.image = pg.image.load(path.join(img_dir, img)).convert_alpha() self.rect = self.image.get_rect() self.rect.center = (WIDTH / 2, HEIGHT / 2) self.pos = vec(WIDTH/2, HEIGHT/2) self.vel = vec(0,0) self.acc = vec(0,0) self.health = PLAYER_HEALTH self.radius = 15 def jump(self): """ Defines rules for the player action of jumping. Parameters: self (self): keyword we can access the attributes and methods of the class in python Source: YouTube Videos KidsCanCode provided information needed for initial setup of code, though code was majorly altered to tailor to project Source Link: https://www.youtube.com/watch?v=uWvb3QzA48c """ self.rect.y += 1 hits = pg.sprite.spritecollide(self,self.game.platforms, False) self.rect.y -= 1 if hits: self.vel.y = -PLAYER_JUMP def update(self): """ Method to control sprite's behavior (player movement). Parameters: self (self): keyword we can access the attributes and methods of the class in python Source: YouTube Videos KidsCanCode provided information needed for initial setup of code, though code was majorly altered to tailor to project Source Link: https://www.youtube.com/watch?v=uWvb3QzA48c """ self.acc = vec(0,PLAYER_GRAV) keys = pg.key.get_pressed() if keys[pg.K_LEFT]: self.acc.x = -PLAYER_ACC if keys[pg.K_RIGHT]: self.acc.x = PLAYER_ACC # apply friction self.acc.x += self.vel.x * PLAYER_FRICTION # equations of motion self.vel += self.acc self.pos += self.vel + 0.5 * self.acc # Nothing passed the sides self.rect.midbottom = self.pos if self.pos.x > WIDTH: self.pos.x = WIDTH if self.pos.x < 0: self.pos.x = 0 class Platform(pg.sprite.Sprite): """ Creates the Platform class to provide a template for platforms in the game. """ def __init__(self, x, y, w, h): """ Initializes (sets up) the platform class. Parameters: self (self): keyword we can access the attributes and methods of the class in python x (int): x coordinate of the platform on the screen (changing the coordinate moves the pltform horizontally) y (int): y coordinate of the platform on the screen (changing the coordinate moves the pltform vertically) w (int): length of the platform (changing the coordinate makes the platform longer) h (int): height of the platform (changing the coordinate makes the platform taller) Source: YouTube Videos KidsCanCode provided information needed for initial setup of code, though code was majorly altered to tailor to project Source Link: https://www.youtube.com/watch?v=uWvb3QzA48c """ pg.sprite.Sprite.__init__(self) self.image = pg.Surface((w,h)) self.image.fill(BLACK) self.rect = self.image.get_rect() self.rect.x = x self.rect.y = y class Enemy(pg.sprite.Sprite): """ Creates the Enemy class to provide a template for enemies in the game. """ def __init__(self,x,y, img): """ Initializes (sets up) the enemy class. Parameters: self (self): keyword we can access the attributes and methods of the class in python x (int): x coordinate of the platform on the screen (changing the coordinate moves the platform horizontally) y (int): y coordinate of the platform on the screen (changing the coordinate moves the platform vertically) img (.png file): png file that has an image for the enemy """ pg.sprite.Sprite.__init__(self) self.image = pg.image.load(path.join(img_dir, img)).convert_alpha() self.rect = self.image.get_rect() self.rect.x = x self.rect.y = y self.health = ENEMY_HEALTH def update(self): """ Method to control sprite's behavior (enemy health). Parameters: self (self): keyword we can access the attributes and methods of the class in python """ if self.health <= 0: self.kill() death_sound = pg.mixer.Sound('game\sounds\explode.ogg') pg.mixer.Sound.play(death_sound) def draw_health(self): """ Used to draw the enemy health bars. Parameters: self (self): keyword we can access the attributes and methods of the class in python """ if self.health > 60: col = GREEN elif self.health > 30: col = YELLOW else: col = RED width = int(self.rect.width * self.health/ENEMY_HEALTH) width2 = int(self.rect.width) self.health_bar = pg.Rect(0, 0, width, 7) self.total = pg.Rect(0,0, width2, 7) if self.health < ENEMY_HEALTH: pg.draw.rect(self.image, BLACK, self.total) pg.draw.rect(self.image, col, self.health_bar) class Arrow(pg.sprite.Sprite): """ Creates the Arrow class to provide a template for arrows (player weapons) in the game. """ def __init__(self, x, y, img): """ Initializes (sets up) the arrow class. Parameters: self (self): keyword we can access the attributes and methods of the class in python x (int): x coordinate of the arrow on the screen y (int): y coordinate of the arrow on the screen img (.png file): png file that has an image for the enemy Source: YouTube Videos KidsCanCode provided information needed for initial setup of code, though code was majorly altered to tailor to project Source Link: https://www.youtube.com/watch?v=uWvb3QzA48c """ pg.sprite.Sprite.__init__(self) self.image = pg.image.load(path.join(img_dir, img)).convert_alpha() self.image.set_colorkey(BLACK) self.rect = self.image.get_rect() self.rect.centery = y self.rect.centerx = x self.pos = vec(x, y) self.vel = vec(ARROW_SPEED,-3) self.acc = vec(0,0) def update(self): """ Method to control sprite's behavior (arrow movement and impact). Parameters: self (self): keyword we can access the attributes and methods of the class in python Source: YouTube Videos KidsCanCode provided information needed for initial setup of code, though code was majorly altered to tailor to project Source Link: https://www.youtube.com/watch?v=uWvb3QzA48c """ # equations of motion self.acc = vec(0, PLAYER_GRAV) self.acc.x += self.vel.x self.vel.y += self.acc.y self.pos += self.vel + 0.5 * self.acc self.rect.x = self.pos.x self.rect.y = self.pos.y - 32 if self.rect.x > WIDTH + 100: self.kill() if self.rect.y > HEIGHT + 100: self.kill() class Fireball(pg.sprite.Sprite): """ Creates the Fireball class to provide a template for fireballs (enemy weapons) in the game. """ def __init__(self, x, y, img): """ Initializes (sets up) the fireball class. Parameters: self (self): keyword we can access the attributes and methods of the class in python x (int): x coordinate of the fireball on the screen y (int): y coordinate of the fireball on the screen img (.png file): png file that has an image for the enemy """ pg.sprite.Sprite.__init__(self) self.image = pg.image.load(path.join(img_dir, img)).convert_alpha() self.image.set_colorkey(BLACK) self.rect = self.image.get_rect() self.rect.centery = y self.rect.centerx = x self.pos = vec(x, y) self.vel = vec(-FIREBALL_SPEED,0) self.acc = vec(0,0) def update(self): """ Method to control sprite's behavior (fireball movement and impact). Parameters: self (self): keyword we can access the attributes and methods of the class in python """ # equations of motion self.acc = vec(0, 0.006) self.acc.x += self.vel.x self.vel.y += self.acc.y self.pos += self.vel + 0.5 * self.acc self.rect.x = self.pos.x self.rect.y = self.pos.y - 64

31.550633

150

0.577332

6c2220b72b2e87c7fb5f4421687f68764fe2beaa

4,580

py

Python

modules/tests/org/change_user_roles.py

nursix/STL

682d8455c8e1c761f48542dad96da08767301923

[ "MIT" ]

1

2017-11-16T14:50:19.000Z

modules/tests/org/change_user_roles.py

vpccalderara/sahana

6eb3f9798879dfa51bbe5d2b84829b1402671499

[ "MIT" ]

null

modules/tests/org/change_user_roles.py

vpccalderara/sahana

6eb3f9798879dfa51bbe5d2b84829b1402671499

[ "MIT" ]

null

""" Sahana Eden Automated Test - ORG010 Change User Roles @copyright: 2011-2017 (c) Sahana Software Foundation @license: MIT Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ from selenium.webdriver.support.ui import Select from gluon import current from tests.web2unittest import SeleniumUnitTest class ChangeUserRole(SeleniumUnitTest): """ Desc: Change User Roles Case: ORG010 TO DO: Check if works and upgrade to new test system framework. """ def org010(): """ 1. Log in as admin 2. Give test user org admin rights over Timor-Leste 3. Give user margarida.martins@redcross.tl some access on Timor-Leste 4. Log in as test user 5. Revoke all access for margarida.martins@redcross.tl on Timor-Leste """ as_admin() logout() as_orgadmin() logout() def as_admin(): """ Run the tests as an administrator """ config = current.test_config browser = config.browser driver = browser login(account='admin') make_user_orgadmin() open_organisation_roles() select_user() # Set some new access levels driver.find_element_by_id('role_volvol_reader').click() driver.find_element_by_id('role_projectproject_data_entry').click() driver.find_element_by_id('role_projectproject_data_entry').submit() # @todo: check the values of the matrix def as_orgadmin(): """ Run the tests as an org admin """ config = current.test_config browser = config.browser driver = browser login() open_organisation_roles(action="Details") select_user() # Reset those access levels back to None driver.find_element_by_id('role_volNone').click() driver.find_element_by_id('role_projectNone').click() driver.find_element_by_id('role_projectNone').submit() # @todo: check the values of the matrix def make_user_orgadmin(): config = current.test_config browser = config.browser driver = browser browser.get("%s/admin/user" % config.url) # Open the roles page for text@example.com user account dt_filter("test@example.com") dt_action(action="Roles") # Give org admin rights to Test User on Timor-Leste Red Cross Society Select(driver.find_element_by_name("group_id")).select_by_visible_text("Organisation Admin") Select(driver.find_element_by_name("pe_id")).select_by_visible_text("Timor-Leste Red Cross Society (Organization)") driver.find_element_by_id("submit_add_button").click() def open_organisation_roles(action="Open"): config = current.test_config browser = config.browser driver = browser # Go to the organisation list browser.get("%s/org/organisation" % config.url) # Open the Timor-Leste organisation dt_filter("Timor-Leste") dt_action(action=action) # Go to the organisations' User Roles tab driver.find_element_by_link_text("User Roles").click() def select_user(): config = current.test_config browser = config.browser driver = browser # Select a user from the drop-down list Select(driver.find_element_by_name("user")).select_by_visible_text("test@example.com") driver.find_element_by_xpath("//input[@type='submit']").click()

33.925926

123

0.671397

bbd5c01695ae5b038f6fa40a26b2f8255461d01d

10,370

py

Python

sympy/functions/special/spherical_harmonics.py

ovolve/sympy

0a15782f20505673466b940454b33b8014a25c13

[ "BSD-3-Clause" ]

4

2018-07-04T17:20:12.000Z

2019-07-14T18:07:25.000Z

sympy/functions/special/spherical_harmonics.py

ovolve/sympy

0a15782f20505673466b940454b33b8014a25c13

[ "BSD-3-Clause" ]

7

2017-05-01T14:15:32.000Z

2017-09-06T20:44:24.000Z

sympy/functions/special/spherical_harmonics.py

ovolve/sympy

0a15782f20505673466b940454b33b8014a25c13

[ "BSD-3-Clause" ]

1

2020-09-09T15:20:27.000Z

from __future__ import print_function, division from sympy import pi, I from sympy.core.singleton import S from sympy.core import Dummy, sympify from sympy.core.function import Function, ArgumentIndexError from sympy.functions import assoc_legendre from sympy.functions.elementary.trigonometric import sin, cos, cot from sympy.functions.combinatorial.factorials import factorial from sympy.functions.elementary.complexes import Abs from sympy.functions.elementary.exponential import exp from sympy.functions.elementary.miscellaneous import sqrt _x = Dummy("x") class Ynm(Function): r""" Spherical harmonics defined as .. math:: Y_n^m(\theta, \varphi) := \sqrt{\frac{(2n+1)(n-m)!}{4\pi(n+m)!}} \exp(i m \varphi) \mathrm{P}_n^m\left(\cos(\theta)\right) Ynm() gives the spherical harmonic function of order `n` and `m` in `\theta` and `\varphi`, `Y_n^m(\theta, \varphi)`. The four parameters are as follows: `n \geq 0` an integer and `m` an integer such that `-n \leq m \leq n` holds. The two angles are real-valued with `\theta \in [0, \pi]` and `\varphi \in [0, 2\pi]`. Examples ======== >>> from sympy import Ynm, Symbol >>> from sympy.abc import n,m >>> theta = Symbol("theta") >>> phi = Symbol("phi") >>> Ynm(n, m, theta, phi) Ynm(n, m, theta, phi) Several symmetries are known, for the order >>> from sympy import Ynm, Symbol >>> from sympy.abc import n,m >>> theta = Symbol("theta") >>> phi = Symbol("phi") >>> Ynm(n, -m, theta, phi) (-1)**m*exp(-2*I*m*phi)*Ynm(n, m, theta, phi) as well as for the angles >>> from sympy import Ynm, Symbol, simplify >>> from sympy.abc import n,m >>> theta = Symbol("theta") >>> phi = Symbol("phi") >>> Ynm(n, m, -theta, phi) Ynm(n, m, theta, phi) >>> Ynm(n, m, theta, -phi) exp(-2*I*m*phi)*Ynm(n, m, theta, phi) For specific integers n and m we can evalute the harmonics to more useful expressions >>> simplify(Ynm(0, 0, theta, phi).expand(func=True)) 1/(2*sqrt(pi)) >>> simplify(Ynm(1, -1, theta, phi).expand(func=True)) sqrt(6)*exp(-I*phi)*sin(theta)/(4*sqrt(pi)) >>> simplify(Ynm(1, 0, theta, phi).expand(func=True)) sqrt(3)*cos(theta)/(2*sqrt(pi)) >>> simplify(Ynm(1, 1, theta, phi).expand(func=True)) -sqrt(6)*exp(I*phi)*sin(theta)/(4*sqrt(pi)) >>> simplify(Ynm(2, -2, theta, phi).expand(func=True)) sqrt(30)*exp(-2*I*phi)*sin(theta)**2/(8*sqrt(pi)) >>> simplify(Ynm(2, -1, theta, phi).expand(func=True)) sqrt(30)*exp(-I*phi)*sin(2*theta)/(8*sqrt(pi)) >>> simplify(Ynm(2, 0, theta, phi).expand(func=True)) sqrt(5)*(3*cos(theta)**2 - 1)/(4*sqrt(pi)) >>> simplify(Ynm(2, 1, theta, phi).expand(func=True)) -sqrt(30)*exp(I*phi)*sin(2*theta)/(8*sqrt(pi)) >>> simplify(Ynm(2, 2, theta, phi).expand(func=True)) sqrt(30)*exp(2*I*phi)*sin(theta)**2/(8*sqrt(pi)) We can differentiate the functions with respect to both angles >>> from sympy import Ynm, Symbol, diff >>> from sympy.abc import n,m >>> theta = Symbol("theta") >>> phi = Symbol("phi") >>> diff(Ynm(n, m, theta, phi), theta) m*cot(theta)*Ynm(n, m, theta, phi) + sqrt((-m + n)*(m + n + 1))*exp(-I*phi)*Ynm(n, m + 1, theta, phi) >>> diff(Ynm(n, m, theta, phi), phi) I*m*Ynm(n, m, theta, phi) Further we can compute the complex conjugation >>> from sympy import Ynm, Symbol, conjugate >>> from sympy.abc import n,m >>> theta = Symbol("theta") >>> phi = Symbol("phi") >>> conjugate(Ynm(n, m, theta, phi)) (-1)**(2*m)*exp(-2*I*m*phi)*Ynm(n, m, theta, phi) To get back the well known expressions in spherical coordinates we use full expansion >>> from sympy import Ynm, Symbol, expand_func >>> from sympy.abc import n,m >>> theta = Symbol("theta") >>> phi = Symbol("phi") >>> expand_func(Ynm(n, m, theta, phi)) sqrt((2*n + 1)*factorial(-m + n)/factorial(m + n))*exp(I*m*phi)*assoc_legendre(n, m, cos(theta))/(2*sqrt(pi)) See Also ======== Ynm_c, Znm References ========== .. [1] http://en.wikipedia.org/wiki/Spherical_harmonics .. [2] http://mathworld.wolfram.com/SphericalHarmonic.html .. [3] http://functions.wolfram.com/Polynomials/SphericalHarmonicY/ .. [4] http://dlmf.nist.gov/14.30 """ @classmethod def eval(cls, n, m, theta, phi): n, m, theta, phi = [sympify(x) for x in (n, m, theta, phi)] # Handle negative index m and arguments theta, phi if m.could_extract_minus_sign(): m = -m return S.NegativeOne**m * exp(-2*I*m*phi) * Ynm(n, m, theta, phi) if theta.could_extract_minus_sign(): theta = -theta return Ynm(n, m, theta, phi) if phi.could_extract_minus_sign(): phi = -phi return exp(-2*I*m*phi) * Ynm(n, m, theta, phi) # TODO Add more simplififcation here def _eval_expand_func(self, **hints): n, m, theta, phi = self.args rv = (sqrt((2*n + 1)/(4*pi) * factorial(n - m)/factorial(n + m)) * exp(I*m*phi) * assoc_legendre(n, m, cos(theta))) # We can do this because of the range of theta return rv.subs(sqrt(-cos(theta)**2 + 1), sin(theta)) def fdiff(self, argindex=4): if argindex == 1: # Diff wrt n raise ArgumentIndexError(self, argindex) elif argindex == 2: # Diff wrt m raise ArgumentIndexError(self, argindex) elif argindex == 3: # Diff wrt theta n, m, theta, phi = self.args return (m * cot(theta) * Ynm(n, m, theta, phi) + sqrt((n - m)*(n + m + 1)) * exp(-I*phi) * Ynm(n, m + 1, theta, phi)) elif argindex == 4: # Diff wrt phi n, m, theta, phi = self.args return I * m * Ynm(n, m, theta, phi) else: raise ArgumentIndexError(self, argindex) def _eval_rewrite_as_polynomial(self, n, m, theta, phi): # TODO: Make sure n \in N # TODO: Assert |m| <= n ortherwise we should return 0 return self.expand(func=True) def _eval_rewrite_as_sin(self, n, m, theta, phi): return self.rewrite(cos) def _eval_rewrite_as_cos(self, n, m, theta, phi): # This method can be expensive due to extensive use of simplification! from sympy.simplify import simplify, trigsimp # TODO: Make sure n \in N # TODO: Assert |m| <= n ortherwise we should return 0 term = simplify(self.expand(func=True)) # We can do this because of the range of theta term = term.xreplace({Abs(sin(theta)):sin(theta)}) return simplify(trigsimp(term)) def _eval_conjugate(self): # TODO: Make sure theta \in R and phi \in R n, m, theta, phi = self.args return S.NegativeOne**m * self.func(n, -m, theta, phi) def as_real_imag(self, deep=True, **hints): # TODO: Handle deep and hints n, m, theta, phi = self.args re = (sqrt((2*n + 1)/(4*pi) * factorial(n - m)/factorial(n + m)) * cos(m*phi) * assoc_legendre(n, m, cos(theta))) im = (sqrt((2*n + 1)/(4*pi) * factorial(n - m)/factorial(n + m)) * sin(m*phi) * assoc_legendre(n, m, cos(theta))) return (re, im) def _eval_evalf(self, prec): # Note: works without this function by just calling # mpmath for Legendre polynomials. But using # the dedicated function directly is cleaner. from mpmath import mp, workprec from sympy import Expr n = self.args[0]._to_mpmath(prec) m = self.args[1]._to_mpmath(prec) theta = self.args[2]._to_mpmath(prec) phi = self.args[3]._to_mpmath(prec) with workprec(prec): res = mp.spherharm(n, m, theta, phi) return Expr._from_mpmath(res, prec) def _sage_(self): import sage.all as sage return sage.spherical_harmonic(self.args[0]._sage_(), self.args[1]._sage_(), self.args[2]._sage_(), self.args[3]._sage_()) def Ynm_c(n, m, theta, phi): r"""Conjugate spherical harmonics defined as .. math:: \overline{Y_n^m(\theta, \varphi)} := (-1)^m Y_n^{-m}(\theta, \varphi) See Also ======== Ynm, Znm References ========== .. [1] http://en.wikipedia.org/wiki/Spherical_harmonics .. [2] http://mathworld.wolfram.com/SphericalHarmonic.html .. [3] http://functions.wolfram.com/Polynomials/SphericalHarmonicY/ """ from sympy import conjugate return conjugate(Ynm(n, m, theta, phi)) class Znm(Function): r""" Real spherical harmonics defined as .. math:: Z_n^m(\theta, \varphi) := \begin{cases} \frac{Y_n^m(\theta, \varphi) + \overline{Y_n^m(\theta, \varphi)}}{\sqrt{2}} &\quad m > 0 \\ Y_n^m(\theta, \varphi) &\quad m = 0 \\ \frac{Y_n^m(\theta, \varphi) - \overline{Y_n^m(\theta, \varphi)}}{i \sqrt{2}} &\quad m < 0 \\ \end{cases} which gives in simplified form .. math:: Z_n^m(\theta, \varphi) = \begin{cases} \frac{Y_n^m(\theta, \varphi) + (-1)^m Y_n^{-m}(\theta, \varphi)}{\sqrt{2}} &\quad m > 0 \\ Y_n^m(\theta, \varphi) &\quad m = 0 \\ \frac{Y_n^m(\theta, \varphi) - (-1)^m Y_n^{-m}(\theta, \varphi)}{i \sqrt{2}} &\quad m < 0 \\ \end{cases} See Also ======== Ynm, Ynm_c References ========== .. [1] http://en.wikipedia.org/wiki/Spherical_harmonics .. [2] http://mathworld.wolfram.com/SphericalHarmonic.html .. [3] http://functions.wolfram.com/Polynomials/SphericalHarmonicY/ """ @classmethod def eval(cls, n, m, theta, phi): n, m, th, ph = [sympify(x) for x in (n, m, theta, phi)] if m.is_positive: zz = (Ynm(n, m, th, ph) + Ynm_c(n, m, th, ph)) / sqrt(2) return zz elif m.is_zero: return Ynm(n, m, th, ph) elif m.is_negative: zz = (Ynm(n, m, th, ph) - Ynm_c(n, m, th, ph)) / (sqrt(2)*I) return zz

33.237179

113

0.563934

5679f6a65c616ae6169ecfe361080267cb71eb97

1,544

gyp

Python

ui/events/platform/x11/x11_events_platform.gyp

Wzzzx/chromium-crosswalk

768dde8efa71169f1c1113ca6ef322f1e8c9e7de

[ "BSD-3-Clause-No-Nuclear-License-2014", "BSD-3-Clause" ]

2

2019-01-28T08:09:58.000Z

2021-11-15T15:32:10.000Z

ui/events/platform/x11/x11_events_platform.gyp

maidiHaitai/haitaibrowser

a232a56bcfb177913a14210e7733e0ea83a6b18d

[ "BSD-3-Clause" ]

null

ui/events/platform/x11/x11_events_platform.gyp

maidiHaitai/haitaibrowser

a232a56bcfb177913a14210e7733e0ea83a6b18d

[ "BSD-3-Clause" ]

6

2020-09-23T08:56:12.000Z

2021-11-18T03:40:49.000Z

# Copyright 2014 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. { 'variables': { 'chromium_code': 1, }, 'targets': [{ # GN version: //ui/events/platform/x11 'target_name': 'x11_events_platform', 'type': '<(component)', 'defines': [ 'EVENTS_IMPLEMENTATION', ], 'dependencies': [ '../../../../base/base.gyp:base', '../../../../build/linux/system.gyp:x11', '../../../gfx/gfx.gyp:gfx', '../../../gfx/x/gfx_x11.gyp:gfx_x11', '../../devices/events_devices.gyp:events_devices', '../../devices/x11/events_devices_x11.gyp:events_devices_x11', '../../events.gyp:events', '../../events.gyp:events_base', '../../x/events_x.gyp:events_x', '../events_platform.gyp:events_platform', ], 'sources': [ 'x11_event_source.cc', 'x11_event_source.h', 'x11_hotplug_event_handler.cc', 'x11_hotplug_event_handler.h', ], 'conditions': [ ['use_glib==1', { 'dependencies': [ '../../../../build/linux/system.gyp:glib', ], 'sources': [ 'x11_event_source_glib.cc', 'x11_event_source_glib.h', ], }, { # use_glib == 0 'sources': [ 'x11_event_source_libevent.cc', 'x11_event_source_libevent.h', ], 'dependencies': [ '../../keycodes/events_keycodes.gyp:keycodes_x11', ], }], ], }], }

27.571429

72

0.538212

03487e44a28d3a0c86bea22fff1834f5072df4e0

1,820

py

Python

internal/notes/builtin-SAVE/packages/xinit/package.py

HPCToolkit/hpctest

5ff4455582bf39e75530a31badcf6142081b386b

[ "BSD-3-Clause" ]

1

2019-01-17T20:07:19.000Z

internal/notes/builtin-SAVE/packages/xinit/package.py

HPCToolkit/hpctest

5ff4455582bf39e75530a31badcf6142081b386b

[ "BSD-3-Clause" ]

null

internal/notes/builtin-SAVE/packages/xinit/package.py

HPCToolkit/hpctest

5ff4455582bf39e75530a31badcf6142081b386b

[ "BSD-3-Clause" ]

2

2019-08-06T18:13:57.000Z

2021-11-05T18:19:49.000Z

############################################################################## # Copyright (c) 2013-2017, Lawrence Livermore National Security, LLC. # Produced at the Lawrence Livermore National Laboratory. # # This file is part of Spack. # Created by Todd Gamblin, tgamblin@llnl.gov, All rights reserved. # LLNL-CODE-647188 # # For details, see https://github.com/spack/spack # Please also see the NOTICE and LICENSE files for our notice and the LGPL. # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU Lesser General Public License (as # published by the Free Software Foundation) version 2.1, February 1999. # # 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 terms and # conditions of the GNU Lesser General Public License for more details. # # You should have received a copy of the GNU Lesser General Public # License along with this program; if not, write to the Free Software # Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA ############################################################################## from spack import * class Xinit(AutotoolsPackage): """The xinit program is used to start the X Window System server and a first client program on systems that are not using a display manager such as xdm.""" homepage = "http://cgit.freedesktop.org/xorg/app/xinit" url = "https://www.x.org/archive/individual/app/xinit-1.3.4.tar.gz" version('1.3.4', '91c5697345016ec7841f5e5fccbe7a4c') depends_on('libx11') depends_on('xproto@7.0.17:', type='build') depends_on('pkg-config@0.9.0:', type='build') depends_on('util-macros', type='build')

42.325581

78

0.674725

1d5702806c84daf7efc2d8c470d6a56aa7c91b9e

439

py

Python

terrathings/connection/deployment_status.py

elangenhan/terrathings

d54c9dce28762602475f5a77a6b07165efd2d5b0

[ "MIT" ]

null

terrathings/connection/deployment_status.py

elangenhan/terrathings

d54c9dce28762602475f5a77a6b07165efd2d5b0

[ "MIT" ]

null

terrathings/connection/deployment_status.py

elangenhan/terrathings

d54c9dce28762602475f5a77a6b07165efd2d5b0

[ "MIT" ]

null

class Deployment: def __init__(self, id: str, sha256: str) -> None: self.id = id self.sha256 = sha256 class Runtime: def __init__(self, id: str, sha256: str) -> None: self.id = id self.sha256 = sha256 class Status: def __init__( self, runtime: Runtime, deployment: Deployment | None, ) -> None: self.runtime = runtime self.deployment = deployment

20.904762

53

0.571754

51c7fcc1545daf287ecd45a8baeb94709cb59837

485

py

Python

src/unicon/plugins/asa/ASAv/service_implementation.py

tahigash/unicon.plugins

1b43a5a61244ea9312387fd855442ace37c65db9

[ "Apache-2.0" ]

null

src/unicon/plugins/asa/ASAv/service_implementation.py

tahigash/unicon.plugins

1b43a5a61244ea9312387fd855442ace37c65db9

[ "Apache-2.0" ]

null

src/unicon/plugins/asa/ASAv/service_implementation.py

tahigash/unicon.plugins

1b43a5a61244ea9312387fd855442ace37c65db9

[ "Apache-2.0" ]

null

from unicon.plugins.generic.service_implementation import Reload from unicon.eal.dialogs import Dialog, Statement from unicon.plugins.asa.ASAv.service_statements import asa_reload_stmt_list class ASAReload(Reload): def __init__(self, connection, context, **kwargs): super().__init__(connection, context, **kwargs) self.start_state = 'enable' self.end_state = 'enable' self.service_name = 'reload' self.dialog = Dialog(asa_reload_stmt_list)

40.416667

75

0.740206

d25afc1a1b0b1bbb5107951ac4f4021c58f8de6c

420

py

Python

packages/python/plotly/plotly/validators/table/cells/fill/_colorsrc.py

mastermind88/plotly.py

efa70710df1af22958e1be080e105130042f1839

[ "MIT" ]

null

packages/python/plotly/plotly/validators/table/cells/fill/_colorsrc.py

mastermind88/plotly.py

efa70710df1af22958e1be080e105130042f1839

[ "MIT" ]

null

packages/python/plotly/plotly/validators/table/cells/fill/_colorsrc.py

mastermind88/plotly.py

efa70710df1af22958e1be080e105130042f1839

[ "MIT" ]

null

import _plotly_utils.basevalidators class ColorsrcValidator(_plotly_utils.basevalidators.SrcValidator): def __init__( self, plotly_name="colorsrc", parent_name="table.cells.fill", **kwargs ): super(ColorsrcValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "none"), **kwargs, )

30

78

0.652381

b2c33a10ede2d4331c9365e19ff4fc966dcb5722

632

py

Python

setup.py

Chitanda-Satou/avocadopy

b6287416b5bfd6c283e848c9acdece1a8eade126

[ "MIT" ]

null

setup.py

Chitanda-Satou/avocadopy

b6287416b5bfd6c283e848c9acdece1a8eade126

[ "MIT" ]

null

setup.py

Chitanda-Satou/avocadopy

b6287416b5bfd6c283e848c9acdece1a8eade126

[ "MIT" ]

null

import setuptools with open("README.md", "r") as fh: long_description = fh.read() setuptools.setup( name="avocadopy", version="0.0.2", author='B Niu', author_email='shinji006@126.com', description='Tools for medical statistics.', long_description=long_description, long_description_content_type="text/markdown", url='https://github.com/b-niu/avocadopy', packages=setuptools.find_packages(), classifiers=[ "Programming Language :: Python :: 3", "License :: OSI Approved :: MIT License", "Operating System :: OS Independent", ], python_requires='>=3.6', )

27.478261

50

0.655063

ba7ffa54998c0e9d9575d3ee2f7b6876bad29405

1,731

py

Python

sequniq/records.py

standage/sequniq

f77430402e52efeed62a6b41f9529d1a2ac4245b

[ "0BSD" ]

2

2017-03-24T09:46:50.000Z

2017-03-29T16:52:33.000Z

sequniq/records.py

standage/sequniq

f77430402e52efeed62a6b41f9529d1a2ac4245b

[ "0BSD" ]

3

2015-06-30T18:01:50.000Z

2015-06-30T18:02:22.000Z

sequniq/records.py

standage/sequniq

f77430402e52efeed62a6b41f9529d1a2ac4245b

[ "0BSD" ]

null

# ----------------------------------------------------------------------------- # Copyright (C) Daniel Standage, 2015. It is licensed under the ISC license, # see LICENSE.txt. Contact: daniel.standage@gmail.com # ----------------------------------------------------------------------------- """ Utilities for working with complete sequence records from a database of Fast[aq] sequences. SHA1 hash of each sequence is stored in memory, instead of the sequence itself. Therefore, these utilities are very space efficient when working with thousands of long(ish) sequences such as scaffolds and contigs. The memory savings will not be quite as drastic when working with millions of short sequences, such as from an RNA-seq experiment. """ import sequniq import hashlib def uniqseqs(seqdata, trimdefline=False, checkrevcom=False, fastq=True, paired=True): """ Given a file of Fast[aq] sequences `seqdata`, retrieve unique sequences. Generator function yields complete Fast[aq] records. """ seqs = {} parsefunc = sequniq.parse.get_parser(fastq=fastq, paired=paired) for record in parsefunc(seqdata): sequniq.parse.check_record(record, fastq=fastq, paired=paired) seq = record[1] if paired: if fastq: seq += record[4] else: seq += record[3] seqsha = hashlib.sha1(seq).hexdigest() if seqsha not in seqs: if checkrevcom: rseqsha = hashlib.sha1(sequniq.revcomp(seq)).hexdigest() if rseqsha not in seqs: seqs[seqsha] = 1 yield record else: seqs[seqsha] = 1 yield record

36.829787

79

0.581745

262074695f7a0f3b74b5c985eaab8eee3ad89550

2,748

py

Python

vp_suite/model_blocks/conv_lstm_hzzone.py

angelvillar96/vp-suite

3e7c7d852862bad09a771d754fc56a71abf0a25f

[ "MIT" ]

null

vp_suite/model_blocks/conv_lstm_hzzone.py

angelvillar96/vp-suite

3e7c7d852862bad09a771d754fc56a71abf0a25f

[ "MIT" ]

null

vp_suite/model_blocks/conv_lstm_hzzone.py

angelvillar96/vp-suite

3e7c7d852862bad09a771d754fc56a71abf0a25f

[ "MIT" ]

null

from torch import nn import torch from vp_suite.base.base_model_block import ModelBlock class ConvLSTM(ModelBlock): NAME = "ConvLSTM (Shi et al.)" PAPER_REFERENCE = "https://arxiv.org/abs/1506.04214" CODE_REFERENCE = "https://github.com/Hzzone/Precipitation-Nowcasting" MATCHES_REFERENCE = "Yes" def __init__(self, device, in_c, enc_c, state_h, state_w, kernel_size, stride=1, padding=1): super().__init__() self.device = device self._conv = nn.Conv2d(in_channels=in_c + enc_c, out_channels=enc_c * 4, kernel_size=kernel_size, stride=stride, padding=padding) self.state_h = state_h self.state_w = state_w # if using requires_grad flag, torch.save will not save parameters in deed although it may be updated every epoch. # However, if you use declare an optimizer like Adam(model.parameters()), # parameters will not be updated forever. self.Wci = nn.Parameter(torch.zeros(1, enc_c, self.state_h, self.state_w)).to(self.device) self.Wcf = nn.Parameter(torch.zeros(1, enc_c, self.state_h, self.state_w)).to(self.device) self.Wco = nn.Parameter(torch.zeros(1, enc_c, self.state_h, self.state_w)).to(self.device) self.in_c = in_c self.enc_c = enc_c # inputs and states should not be all none # inputs: [b, t, c, h, w] def forward(self, inputs, states, seq_len): if states is None: b = inputs.shape[0] c = torch.zeros((b, self.enc_c, self.state_h, self.state_w), dtype=torch.float, device=self.device) h = torch.zeros((b, self.enc_c, self.state_h, self.state_w), dtype=torch.float, device=self.device) else: h, c = states b = h.shape[0] T = seq_len outputs = [] for t in range(T): # initial inputs if inputs is None: x = torch.zeros((b, self.in_c, self.state_h, self.state_w), dtype=torch.float, device=self.device) else: x = inputs[:, t] # mustn't be None. Should be zero on first decoder step cat_x = torch.cat([x, h], dim=1) conv_x = self._conv(cat_x) i, f, tmp_c, o = torch.chunk(conv_x, 4, dim=1) i = torch.sigmoid(i+self.Wci*c) f = torch.sigmoid(f+self.Wcf*c) c = f*c + i*torch.tanh(tmp_c) o = torch.sigmoid(o+self.Wco*c) h = o*torch.tanh(c) outputs.append(h) return torch.stack(outputs, dim=1), (h, c)

40.411765

122

0.561863

ec4a45263b13b7d7ddc5e6f6a6c9d7aa3ffb460f

78,553

py

Python

constants/commands.py

Pure-Peace/gulag

d46c3c54ae8d224b62141c5e237b8ea988033864

[ "MIT" ]

1

2021-09-22T03:15:01.000Z

constants/commands.py

Pure-Peace/gulag

d46c3c54ae8d224b62141c5e237b8ea988033864

[ "MIT" ]

null

constants/commands.py

Pure-Peace/gulag

d46c3c54ae8d224b62141c5e237b8ea988033864

[ "MIT" ]

1

2022-02-07T02:32:00.000Z

# -*- coding: utf-8 -*- import asyncio import copy import importlib import os import pprint import random import secrets import signal import struct import time import uuid from collections import Counter from dataclasses import dataclass from datetime import datetime from importlib.metadata import version as pkg_version from time import perf_counter_ns as clock_ns from typing import Callable from typing import NamedTuple from typing import Optional from typing import Sequence from typing import TYPE_CHECKING from typing import Union from pathlib import Path import aiomysql import cmyui.utils import psutil from peace_performance_python import Beatmap as PeaceBeatmap, Calculator import packets import utils.misc from constants import regexes, mixed_calculator from constants.gamemodes import GameMode from constants.mods import Mods from constants.mods import SPEED_CHANGING_MODS from constants.privileges import Privileges from objects import glob from objects.beatmap import Beatmap from objects.beatmap import ensure_local_osu_file from objects.beatmap import RankedStatus from objects.clan import Clan from objects.clan import ClanPrivileges from objects.match import Match from objects.match import MapPool from objects.match import MatchTeams from objects.match import MatchTeamTypes from objects.match import MatchWinConditions from objects.match import SlotStatus from objects.player import Player from objects.score import SubmissionStatus from utils.misc import seconds_readable if TYPE_CHECKING: from objects.channel import Channel BEATMAPS_PATH = Path.cwd() / '.data/osu' Messageable = Union['Channel', Player] CommandResponse = dict[str, str] @dataclass class Context: player: Player trigger: str args: Sequence[str] recipient: Optional[Messageable] = None match: Optional[Match] = None class Command(NamedTuple): triggers: list[str] callback: Callable[[Context], str] priv: Privileges hidden: bool doc: str class CommandSet: __slots__ = ('trigger', 'doc', 'commands') def __init__(self, trigger: str, doc: str) -> None: self.trigger = trigger self.doc = doc self.commands: list[Command] = [] def add(self, priv: Privileges, aliases: list[str] = [], hidden: bool = False) -> Callable: def wrapper(f: Callable): self.commands.append(Command( # NOTE: this method assumes that functions without any # triggers will be named like '{self.trigger}_{trigger}'. triggers = ( [f.__name__.removeprefix(f'{self.trigger}_').strip()] + aliases ), callback = f, priv = priv, hidden = hidden, doc = f.__doc__ )) return f return wrapper # TODO: refactor help commands into some base ver # since they're all the same anyways lol. # not sure if this should be in glob or not, # trying to think of some use cases lol.. regular_commands = [] command_sets = [ mp_commands := CommandSet('mp', 'Multiplayer commands.'), pool_commands := CommandSet('pool', 'Mappool commands.'), clan_commands := CommandSet('clan', 'Clan commands.') ] glob.commands = { 'regular': regular_commands, 'sets': command_sets } def command(priv: Privileges, aliases: list[str] = [], hidden: bool = False) -> Callable: def wrapper(f: Callable): regular_commands.append(Command( callback = f, priv = priv, hidden = hidden, triggers = [f.__name__.strip('_')] + aliases, doc = f.__doc__ )) return f return wrapper """ User commands # The commands below are not considered dangerous, # and are granted to any unbanned players. """ @command(Privileges.Normal, aliases=['', 'h'], hidden=True) async def _help(ctx: Context) -> str: """Show all documented commands the player can access.""" prefix = glob.config.command_prefix l = ['Individual commands', '-----------'] for cmd in regular_commands: if not cmd.doc or ctx.player.priv & cmd.priv != cmd.priv: # no doc, or insufficient permissions. continue l.append(f'{prefix}{cmd.triggers[0]}: {cmd.doc}') l.append('') # newline l.extend(['Command sets', '-----------']) for cmd_set in command_sets: l.append(f'{prefix}{cmd_set.trigger}: {cmd_set.doc}') return '\n'.join(l) @command(Privileges.Normal) async def roll(ctx: Context) -> str: """Roll an n-sided die where n is the number you write (100 default).""" if ctx.args and ctx.args[0].isdecimal(): max_roll = min(int(ctx.args[0]), 0x7fff) else: max_roll = 100 if max_roll == 0: return "Roll what?" points = random.randrange(0, max_roll) return f'{ctx.player.name} rolls {points} points!' @command(Privileges.Normal, hidden=True) async def block(ctx: Context) -> str: """Block another user from communicating with you.""" target = await glob.players.get_ensure(name=' '.join(ctx.args)) if not target: return 'User not found.' if ( target is glob.bot or target is ctx.player ): return 'What?' if target.id in ctx.player.blocks: return f'{target.name} already blocked!' if target.id in ctx.player.friends: ctx.player.friends.remove(target.id) await ctx.player.add_block(target) return f'Added {target.name} to blocked users.' @command(Privileges.Normal, hidden=True) async def unblock(ctx: Context) -> str: """Unblock another user from communicating with you.""" target = await glob.players.get_ensure(name=' '.join(ctx.args)) if not target: return 'User not found.' if ( target is glob.bot or target is ctx.player ): return 'What?' if target.id not in ctx.player.blocks: return f'{target.name} not blocked!' await ctx.player.remove_block(target) return f'Removed {target.name} from blocked users.' @command(Privileges.Normal) async def reconnect(ctx: Context) -> str: """Disconnect and reconnect to the server.""" ctx.player.logout() @command(Privileges.Normal) async def changename(ctx: Context) -> str: """Change your username.""" name = ' '.join(ctx.args).strip() if not regexes.username.match(name): return 'Must be 2-15 characters in length.' if '_' in name and ' ' in name: return 'May contain "_" and " ", but not both.' if name in glob.config.disallowed_names: return 'Disallowed username; pick another.' if await glob.db.fetch('SELECT 1 FROM users WHERE name = %s', [name]): return 'Username already taken by another player.' # all checks passed, update their name safe_name = name.lower().replace(' ', '_') await glob.db.execute( 'UPDATE users ' 'SET name = %s, safe_name = %s ' 'WHERE id = %s', [name, safe_name, ctx.player.id] ) ctx.player.enqueue( packets.notification(f'Your username has been changed to {name}!') ) ctx.player.logout() @command(Privileges.Normal, aliases=['bloodcat', 'beatconnect', 'chimu', 'q']) async def maplink(ctx: Context) -> str: """Return a download link to the user's current map (situation dependant).""" bmap = None # priority: multiplayer -> spectator -> last np match = ctx.player.match spectating = ctx.player.spectating if match and match.map_id: bmap = await Beatmap.from_md5(match.map_md5) elif spectating and spectating.status.map_id: bmap = await Beatmap.from_md5(spectating.status.map_md5) elif time.time() < ctx.player.last_np['timeout']: bmap = ctx.player.last_np['bmap'] else: return 'No map found!' # gatari.pw & nerina.pw are pretty much the only # reliable mirrors i know of? perhaps beatconnect return f'[https://osu.gatari.pw/d/{bmap.set_id} {bmap.full}]' @command(Privileges.Normal, aliases=['last', 'r']) async def recent(ctx: Context) -> str: """Show information about your most recent score.""" if ctx.args: if not (target := glob.players.get(name=' '.join(ctx.args))): return 'Player not found.' else: target = ctx.player if not (s := target.recent_score): return 'No scores found :o (only saves per play session)' l = [f'[{s.mode!r}] {s.bmap.embed}', f'{s.acc:.2f}%'] if s.mods: l.insert(1, f'+{s.mods!r}') l = [' '.join(l)] if s.passed: rank = s.rank if s.status == SubmissionStatus.BEST else 'NA' l.append(f'PASS {{{s.pp:.2f}pp #{rank}}}') else: # XXX: prior to v3.2.0, gulag didn't parse total_length from # the osu!api, and thus this can do some zerodivision moments. # this can probably be removed in the future, or better yet # replaced with a better system to fix the maps. if s.bmap.total_length != 0: completion = s.time_elapsed / (s.bmap.total_length * 1000) l.append(f'FAIL {{{completion * 100:.2f}% complete}})') else: l.append('FAIL') return ' | '.join(l) # TODO: !top (get top #1 score) # TODO: !compare (compare to previous !last/!top post's map) @command(Privileges.Normal, aliases=['w'], hidden=True) async def _with(ctx: Context) -> str: """Specify custom accuracy & mod combinations with `/np`.""" if ctx.recipient is not glob.bot: return 'This command can only be used in DM with bot.' if time.time() >= ctx.player.last_np['timeout']: return 'Please /np a map first!' bmap: Beatmap = ctx.player.last_np['bmap'] osu_file_path = BEATMAPS_PATH / f'{bmap.id}.osu' if not await ensure_local_osu_file(osu_file_path, bmap.id, bmap.md5): return ('Mapfile could not be found; ' 'this incident has been reported.') mode_vn = ctx.player.last_np['mode_vn'] if mode_vn in (0, 1): # osu, taiko if not ctx.args or len(ctx.args) > 4: return 'Invalid syntax: !with <acc/nmiss/combo/mods ...>' # !with 95% 1m 429x hddt acc = mods = combo = nmiss = None # parse acc, misses, combo and mods from arguments. # tried to balance complexity vs correctness here for arg in map(str.lower, ctx.args): # mandatory suffix, combo & nmiss if ( combo is None and arg.endswith('x') and arg[:-1].isdecimal() ): combo = int(arg[:-1]) if combo > bmap.max_combo: return 'Invalid combo.' elif ( nmiss is None and arg.endswith('m') and arg[:-1].isdecimal() ): nmiss = int(arg[:-1]) # TODO: store nobjects? if nmiss > bmap.max_combo: return 'Invalid misscount.' else: # optional prefix/suffix, mods & accuracy arg_stripped = arg.removeprefix('+').removesuffix('%') if ( mods is None and arg_stripped.isalpha() and len(arg_stripped) % 2 == 0 ): mods = Mods.from_modstr(arg_stripped) mods = mods.filter_invalid_combos(mode_vn) elif ( acc is None and arg_stripped.replace('.', '', 1).isdecimal() ): acc = float(arg_stripped) if not 0 <= acc <= 100: return 'Invalid accuracy.' else: return f'Unknown argument: {arg}' msg = [] combo = bmap.max_combo c = Calculator() if mods is not None: c.set_mods(int(mods)) msg.append(f'{mods!r}') if nmiss is not None: c.set_miss(nmiss) msg.append(f'{nmiss}m') if combo is not None: c.set_combo(combo) msg.append(f'{combo}x') if acc is not None: c.set_acc(acc) msg.append(f'{acc:.2f}%') result = mixed_calculator.simple_calculate(mode_vn, nmiss, combo, acc, mods, osu_file_path, 0) pp, sr = result[0], result[1] return f"{' '.join(msg)}: {pp:.2f}pp ({sr:.2f}*)" else: # mania if not ctx.args or len(ctx.args) > 2: return 'Invalid syntax: !with <score/mods ...>' score = 1000 mods = Mods.NOMOD for param in (p.strip('+k') for p in ctx.args): if param.isdecimal(): # acc if not 0 <= (score := int(param)) <= 1000: return 'Invalid score.' if score <= 500: return '<=500k score is always 0pp.' elif len(param) % 2 == 0: mods = Mods.from_modstr(param) mods = mods.filter_invalid_combos(mode_vn) else: return 'Invalid syntax: !with <score/mods ...>' result = mixed_calculator.simple_calculate(mode_vn, 0, 0, 0, mods, osu_file_path, score) return f'{score}k {mods!r}: {result[0]:.2f}pp ({result[1]:.2f}*)' @command(Privileges.Normal, aliases=['req']) async def request(ctx: Context) -> str: """Request a beatmap for nomination.""" if ctx.args: return 'Invalid syntax: !request' if time.time() >= ctx.player.last_np['timeout']: return 'Please /np a map first!' bmap = ctx.player.last_np['bmap'] if bmap.status != RankedStatus.Pending: return 'Only pending maps may be requested for status change.' await glob.db.execute( 'INSERT INTO map_requests ' '(map_id, player_id, datetime, active) ' 'VALUES (%s, %s, NOW(), 1)', [bmap.id, ctx.player.id] ) return 'Request submitted.' @command(Privileges.Normal) async def get_apikey(ctx: Context) -> str: """Generate a new api key & assign it to the player.""" if ctx.recipient is not glob.bot: return f'Command only available in DMs with {glob.bot.name}.' # remove old token if ctx.player.api_key: glob.api_keys.pop(ctx.player.api_key) # generate new token ctx.player.api_key = str(uuid.uuid4()) await glob.db.execute( 'UPDATE users ' 'SET api_key = %s ' 'WHERE id = %s', [ctx.player.api_key, ctx.player.id] ) glob.api_keys[ctx.player.api_key] = ctx.player.id ctx.player.enqueue(packets.notification('/savelog & click popup for an easy copy.')) return f'Your API key is now: {ctx.player.api_key}' """ Nominator commands # The commands below allow users to # manage the server's state of beatmaps. """ @command(Privileges.Nominator, aliases=['reqs'], hidden=True) async def requests(ctx: Context) -> str: """Check the nomination request queue.""" if ctx.args: return 'Invalid syntax: !requests' res = await glob.db.fetchall( 'SELECT map_id, player_id, datetime ' 'FROM map_requests WHERE active = 1', _dict=False # return rows as tuples ) if not res: return 'The queue is clean! (0 map request(s))' l = [f'Total requests: {len(res)}'] for (map_id, player_id, dt) in res: # find player & map for each row, and add to output. if not (p := await glob.players.get_ensure(id=player_id)): l.append(f'Failed to find requesting player ({player_id})?') continue if not (bmap := await Beatmap.from_bid(map_id)): l.append(f'Failed to find requested map ({map_id})?') continue l.append(f'[{p.embed} @ {dt:%b %d %I:%M%p}] {bmap.embed}.') return '\n'.join(l) _status_str_to_int_map = { 'unrank': 0, 'rank': 2, 'love': 5 } def status_to_id(s: str) -> int: return _status_str_to_int_map[s] @command(Privileges.Nominator) async def _map(ctx: Context) -> str: """Changes the ranked status of the most recently /np'ed map.""" if ( len(ctx.args) != 2 or ctx.args[0] not in ('rank', 'unrank', 'love') or ctx.args[1] not in ('set', 'map') ): return 'Invalid syntax: !map <rank/unrank/love> <map/set>' if time.time() >= ctx.player.last_np['timeout']: return 'Please /np a map first!' bmap = ctx.player.last_np['bmap'] new_status = RankedStatus(status_to_id(ctx.args[0])) if bmap.status == new_status: return f'{bmap.embed} is already {new_status!s}!' # update sql & cache based on scope # XXX: not sure if getting md5s from sql # for updating cache would be faster? # surely this will not scale as well.. async with glob.db.pool.acquire() as conn: async with conn.cursor() as db_cursor: if ctx.args[1] == 'set': # update whole set await db_cursor.execute( 'UPDATE maps SET status = %s, ' 'frozen = 1 WHERE set_id = %s', [new_status, bmap.set_id] ) # select all map ids for clearing map requests. await db_cursor.execute( 'SELECT id FROM maps ' 'WHERE set_id = %s', [bmap.set_id] ) map_ids = [row[0] async for row in db_cursor] for bmap in glob.cache['beatmapset'][bmap.set_id].maps: bmap.status = new_status else: # update only map await db_cursor.execute( 'UPDATE maps SET status = %s, ' 'frozen = 1 WHERE id = %s', [new_status, bmap.id] ) map_ids = [bmap.id] if bmap.md5 in glob.cache['beatmap']: glob.cache['beatmap'][bmap.md5].status = new_status # deactivate rank requests for all ids for map_id in map_ids: await db_cursor.execute( 'UPDATE map_requests ' 'SET active = 0 ' 'WHERE map_id = %s', [map_id] ) return f'{bmap.embed} updated to {new_status!s}.' """ Mod commands # The commands below are somewhat dangerous, # and are generally for managing players. """ @command(Privileges.Mod, hidden=True) async def notes(ctx: Context) -> str: """Retrieve the logs of a specified player by name.""" if len(ctx.args) != 2 or not ctx.args[1].isdecimal(): return 'Invalid syntax: !notes <name> <days_back>' if not (t := await glob.players.get_ensure(name=ctx.args[0])): return f'"{ctx.args[0]}" not found.' days = int(ctx.args[1]) if days > 365: return 'Please contact a developer to fetch >365 day old information.' elif days <= 0: return 'Invalid syntax: !notes <name> <days_back>' res = await glob.db.fetchall( 'SELECT `msg`, `time` ' 'FROM `logs` WHERE `to` = %s ' 'AND UNIX_TIMESTAMP(`time`) >= UNIX_TIMESTAMP(NOW()) - %s ' 'ORDER BY `time` ASC', [t.id, days * 86400] ) if not res: return f'No notes found on {t} in the past {days} days.' return '\n'.join(['[{time}] {msg}'.format(**row) for row in res]) @command(Privileges.Mod, hidden=True) async def addnote(ctx: Context) -> str: """Add a note to a specified player by name.""" if len(ctx.args) < 2: return 'Invalid syntax: !addnote <name> <note ...>' if not (t := await glob.players.get_ensure(name=ctx.args[0])): return f'"{ctx.args[0]}" not found.' log_msg = f'{ctx.player} added note: {" ".join(ctx.args[1:])}' await glob.db.execute( 'INSERT INTO logs ' '(`from`, `to`, `msg`, `time`) ' 'VALUES (%s, %s, %s, NOW())', [ctx.player.id, t.id, log_msg] ) return f'Added note to {t}.' # some shorthands that can be used as # reasons in many moderative commands. SHORTHAND_REASONS = { 'aa': 'having their appeal accepted', 'cc': 'using a modified osu! client', '3p': 'using 3rd party programs', 'rx': 'using 3rd party programs (relax)', 'tw': 'using 3rd party programs (timewarp)', 'au': 'using 3rd party programs (auto play)' } DURATION_MULTIPLIERS = { 's': 1, 'm': 60, 'h': 3600, 'd': 86400, 'w': 604800 } @command(Privileges.Mod, hidden=True) async def silence(ctx: Context) -> str: """Silence a specified player with a specified duration & reason.""" if len(ctx.args) < 3: return 'Invalid syntax: !silence <name> <duration> <reason>' if not (t := await glob.players.get_ensure(name=ctx.args[0])): return f'"{ctx.args[0]}" not found.' if ( t.priv & Privileges.Staff and not ctx.player.priv & Privileges.Dangerous ): return 'Only developers can manage staff members.' if not (r_match := regexes.scaled_duration.match(ctx.args[1])): return 'Invalid syntax: !silence <name> <duration> <reason>' multiplier = DURATION_MULTIPLIERS[r_match['scale']] duration = int(r_match['duration']) * multiplier reason = ' '.join(ctx.args[2:]) if reason in SHORTHAND_REASONS: reason = SHORTHAND_REASONS[reason] await t.silence(ctx.player, duration, reason) return f'{t} was silenced.' @command(Privileges.Mod, hidden=True) async def unsilence(ctx: Context) -> str: """Unsilence a specified player.""" if len(ctx.args) != 1: return 'Invalid syntax: !unsilence <name>' if not (t := await glob.players.get_ensure(name=ctx.args[0])): return f'"{ctx.args[0]}" not found.' if not t.silenced: return f'{t} is not silenced.' if ( t.priv & Privileges.Staff and not ctx.player.priv & Privileges.Dangerous ): return 'Only developers can manage staff members.' await t.unsilence(ctx.player) return f'{t} was unsilenced.' """ Admin commands # The commands below are relatively dangerous, # and are generally for managing players. """ @command(Privileges.Admin, aliases=['u'], hidden=True) async def user(ctx: Context) -> str: """Return general information about a given user.""" if not ctx.args: # no username specified, use ctx.player p = ctx.player else: # username given, fetch the player p = await glob.players.get_ensure(name=' '.join(ctx.args)) if not p: return 'Player not found.' priv_readable = '|'.join(reversed([ priv.name for priv in Privileges if p.priv & priv and bin(priv).count('1') == 1 ])) current_time = time.time() login_delta = current_time - p.login_time last_recv_delta = current_time - p.last_recv_time if current_time < p.last_np['timeout']: last_np = p.last_np['bmap'].embed else: last_np = None return '\n'.join(( f'[{"Bot" if p.bot_client else "Player"}] {p.full_name} ({p.id})', f'Privileges: {priv_readable}', f'Channels: {[p._name for p in p.channels]}', f'Logged in: {login_delta:.2f} sec ago', f'Last server interaction: {last_recv_delta:.2f} sec ago', f'osu! build: {p.osu_ver} | Tourney: {p.tourney_client}', f'Silenced: {p.silenced} | Spectating: {p.spectating}', f'Last /np: {last_np}', f'Recent score: {p.recent_score}', f'Match: {p.match}', f'Spectators: {p.spectators}' )) @command(Privileges.Admin, hidden=True) async def restrict(ctx: Context) -> str: """Restrict a specified player's account, with a reason.""" if len(ctx.args) < 2: return 'Invalid syntax: !restrict <name> <reason>' # find any user matching (including offline). if not (t := await glob.players.get_ensure(name=ctx.args[0])): return f'"{ctx.args[0]}" not found.' if ( t.priv & Privileges.Staff and not ctx.player.priv & Privileges.Dangerous ): return 'Only developers can manage staff members.' if t.restricted: return f'{t} is already restricted!' reason = ' '.join(ctx.args[1:]) if reason in SHORTHAND_REASONS: reason = SHORTHAND_REASONS[reason] await t.restrict(admin=ctx.player, reason=reason) return f'{t} was restricted.' @command(Privileges.Admin, hidden=True) async def unrestrict(ctx: Context) -> str: """Unrestrict a specified player's account, with a reason.""" if len(ctx.args) < 2: return 'Invalid syntax: !unrestrict <name> <reason>' # find any user matching (including offline). if not (t := await glob.players.get_ensure(name=ctx.args[0])): return f'"{ctx.args[0]}" not found.' if ( t.priv & Privileges.Staff and not ctx.player.priv & Privileges.Dangerous ): return 'Only developers can manage staff members.' if not t.restricted: return f'{t} is not restricted!' reason = ' '.join(ctx.args[1:]) if reason in SHORTHAND_REASONS: reason = SHORTHAND_REASONS[reason] await t.unrestrict(ctx.player, reason) return f'{t} was unrestricted.' @command(Privileges.Admin, hidden=True) async def alert(ctx: Context) -> str: """Send a notification to all players.""" if len(ctx.args) < 1: return 'Invalid syntax: !alert <msg>' notif_txt = ' '.join(ctx.args) glob.players.enqueue(packets.notification(notif_txt)) return 'Alert sent.' @command(Privileges.Admin, aliases=['alertu'], hidden=True) async def alertuser(ctx: Context) -> str: """Send a notification to a specified player by name.""" if len(ctx.args) < 2: return 'Invalid syntax: !alertu <name> <msg>' if not (t := glob.players.get(name=ctx.args[0])): return 'Could not find a user by that name.' notif_txt = ' '.join(ctx.args[1:]) t.enqueue(packets.notification(notif_txt)) return 'Alert sent.' # NOTE: this is pretty useless since it doesn't switch anything other # than the c[e4-6].ppy.sh domains; it exists on bancho as a tournament # server switch mechanism, perhaps we could leverage this in the future. @command(Privileges.Admin, hidden=True) async def switchserv(ctx: Context) -> str: """Switch your client's internal endpoints to a specified IP address.""" if len(ctx.args) != 1: return 'Invalid syntax: !switch <endpoint>' new_bancho_ip = ctx.args[0] ctx.player.enqueue(packets.switchTournamentServer(new_bancho_ip)) return 'Have a nice journey..' @command(Privileges.Admin, aliases=['restart']) async def shutdown(ctx: Context) -> str: """Gracefully shutdown the server.""" if ctx.trigger == 'restart': _signal = signal.SIGUSR1 else: _signal = signal.SIGTERM if ctx.args: # shutdown after a delay if not (r_match := regexes.scaled_duration.match(ctx.args[0])): return f'Invalid syntax: !{ctx.trigger} <delay> <msg ...>' multiplier = DURATION_MULTIPLIERS[r_match['scale']] delay = int(r_match['duration']) * multiplier if delay < 15: return 'Minimum delay is 15 seconds.' if len(ctx.args) > 1: # alert all online players of the reboot. alert_msg = (f'The server will {ctx.trigger} in {ctx.args[0]}.\n\n' f'Reason: {" ".join(ctx.args[1:])}') glob.players.enqueue(packets.notification(alert_msg)) glob.loop.call_later(delay, os.kill, os.getpid(), _signal) return f'Enqueued {ctx.trigger}.' else: # shutdown immediately os.kill(os.getpid(), _signal) return ':D' """ Developer commands # The commands below are either dangerous or # simply not useful for any other roles. """ _fake_users = [] @command(Privileges.Dangerous, aliases=['fu']) async def fakeusers(ctx: Context) -> str: """Add fake users to the online player list (for testing).""" # NOTE: this is mostly just for speedtesting things # regarding presences/stats. it's implementation is # indeed quite cursed, but rather efficient. if ( len(ctx.args) != 2 or ctx.args[0] not in ('add', 'rm') or not ctx.args[1].isdecimal() ): return 'Invalid syntax: !fakeusers <add/rm> <amount>' action = ctx.args[0] amount = int(ctx.args[1]) if not 0 < amount <= 100_000: return 'Amount must be in range 0-100k.' # we start at half way through # the i32 space for fake user ids. FAKE_ID_START = 0x7fffffff >> 1 # data to send to clients (all new user info) # we'll send all the packets together at end (more efficient) data = bytearray() if action == 'add': const_uinfo = { # non important stuff 'utc_offset': 0, 'osu_ver': 'dn', 'pm_private': False, 'clan': None, 'clan_priv': None, 'priv': Privileges.Normal | Privileges.Verified, 'silence_end': 0, 'login_time': 0x7fffffff # never auto-dc } _stats = packets.userStats(ctx.player) if _fake_users: current_fakes = max([x.id for x in _fake_users]) - (FAKE_ID_START - 1) else: current_fakes = 0 start_id = FAKE_ID_START + current_fakes end_id = start_id + amount vn_std = GameMode.vn_std base_player = Player(id=0, name='', **const_uinfo) base_player.stats[vn_std] = copy.copy(ctx.player.stats[vn_std]) new_fakes = [] # static part of the presence packet, # no need to redo this every iteration. static_presence = struct.pack( '<BBBffi', 19, # -5 (EST) + 24 38, # country (canada) 0b11111, # all in-game privs 0.0, 0.0, # lat, lon 1 # rank #1 ) for i in range(start_id, end_id): # create new fake player from base name = f'fake #{i - (FAKE_ID_START - 1)}' fake = copy.copy(base_player) fake.id = i fake.name = name # append userpresence packet data += struct.pack( '<HxIi', 83, # packetid 21 + len(name), # packet len i # userid ) data += f'\x0b{chr(len(name))}{name}'.encode() data += static_presence data += _stats new_fakes.append(fake) # extend all added fakes to the real list _fake_users.extend(new_fakes) glob.players.extend(new_fakes) del new_fakes msg = 'Added.' else: # remove len_fake_users = len(_fake_users) if amount > len_fake_users: return f'Too many! only {len_fake_users} remaining.' to_remove = _fake_users[len_fake_users - amount:] logout_packet_header = b'\x0c\x00\x00\x05\x00\x00\x00' for fake in to_remove: if not fake.online: # already auto-dced _fake_users.remove(fake) continue data += logout_packet_header data += fake.id.to_bytes(4, 'little') # 4 bytes pid data += b'\x00' # 1 byte 0 glob.players.remove(fake) _fake_users.remove(fake) msg = 'Removed.' data = bytes(data) # bytearray -> bytes # only enqueue data to real users. for o in [x for x in glob.players if x.id < FAKE_ID_START]: o.enqueue(data) return msg @command(Privileges.Dangerous) async def stealth(ctx: Context) -> str: """Toggle the developer's stealth, allowing them to be hidden.""" # NOTE: this command is a large work in progress and currently # half works; eventually it will be moved to the Admin level. ctx.player.stealth = not ctx.player.stealth return f'Stealth {"enabled" if ctx.player.stealth else "disabled"}.' @command(Privileges.Dangerous) async def recalc(ctx: Context) -> str: """Recalculate pp for a given map, or all maps.""" # NOTE: at the moment this command isn't very optimal and re-parses # the beatmap file each iteration; this will be heavily improved. if len(ctx.args) != 1 or ctx.args[0] not in ('map', 'all'): return 'Invalid syntax: !recalc <map/all>' if ctx.args[0] == 'map': # by specific map, use their last /np if time.time() >= ctx.player.last_np['timeout']: return 'Please /np a map first!' bmap: Beatmap = ctx.player.last_np['bmap'] osu_file_path = BEATMAPS_PATH / f'{bmap.id}.osu' if not await ensure_local_osu_file(osu_file_path, bmap.id, bmap.md5): return ('Mapfile could not be found; ' 'this incident has been reported.') async with glob.db.pool.acquire() as conn: async with conn.cursor(aiomysql.DictCursor) as select_cursor, conn.cursor(aiomysql.cursors.Cursor) as update_cursor : for table in ('scores_vn', 'scores_rx', 'scores_ap'): await select_cursor.execute( 'SELECT id, acc, mods, max_combo, nmiss, mode, score ' f'FROM {table} ' 'WHERE map_md5 = %s', [bmap.md5] ) async for row in select_cursor: result = mixed_calculator.simple_calculate(row['mode'], row['nmiss'], row['max_combo'], row['acc'], row['mods'], osu_file_path, row['score']) await update_cursor.execute( f'UPDATE {table} ' 'SET pp = %s ' 'WHERE id = %s', [result[0], row['id']] ) return 'Map recalculated.' else: # recalc all plays on the server, on all maps staff_chan = glob.channels['#staff'] # log any errs here async def recalc_all() -> None: staff_chan.send_bot(f'{ctx.player} started a full recalculation.') st = time.time() async with glob.db.pool.acquire() as conn: async with conn.cursor(aiomysql.Cursor) as bmap_select_cursor, conn.cursor(aiomysql.DictCursor) as score_select_cursor, conn.cursor(aiomysql.Cursor) as update_cursor: await bmap_select_cursor.execute( 'SELECT id, md5 ' 'FROM maps ' 'WHERE plays > 0' ) map_count = bmap_select_cursor.rowcount staff_chan.send_bot(f'Recalculating {map_count} maps.') async for bmap_row in bmap_select_cursor: bmap_id, bmap_md5 = bmap_row osu_file_path = BEATMAPS_PATH / f'{bmap_id}.osu' ''' for a better performance if not await ensure_local_osu_file(osu_file_path, bmap_id, bmap_md5): staff_chan.send_bot("[Recalc] Couldn't find " f"{bmap_id} / {bmap_md5}") continue ''' for table in ('scores_vn', 'scores_rx', 'scores_ap'): await score_select_cursor.execute( 'SELECT id, acc, mods, max_combo, nmiss, mode, score ' f'FROM {table} ' 'WHERE map_md5 = %s AND status = 2', [bmap_md5] ) async for row in score_select_cursor: result = mixed_calculator.simple_calculate(row['mode'], row['nmiss'], row['max_combo'], row['acc'], row['mods'], osu_file_path, row['score']) await update_cursor.execute( f'UPDATE {table} ' 'SET pp = %s ' 'WHERE id = %s', [result[0], row['id']] ) # leave at least 1/100th of # a second for handling conns. await asyncio.sleep(0.01) elapsed = utils.misc.seconds_readable(int(time.time() - st)) staff_chan.send_bot(f'Recalculation complete. | Elapsed: {elapsed}') glob.loop.create_task(recalc_all()) return 'Starting a full recalculation.' @command(Privileges.Dangerous, hidden=True) async def debug(ctx: Context) -> str: """Toggle the console's debug setting.""" glob.app.debug = not glob.app.debug return f"Toggled {'on' if glob.app.debug else 'off'}." # NOTE: these commands will likely be removed # with the addition of a good frontend. str_priv_dict = { 'normal': Privileges.Normal, 'verified': Privileges.Verified, 'whitelisted': Privileges.Whitelisted, 'supporter': Privileges.Supporter, 'premium': Privileges.Premium, 'alumni': Privileges.Alumni, 'tournament': Privileges.Tournament, 'nominator': Privileges.Nominator, 'mod': Privileges.Mod, 'admin': Privileges.Admin, 'dangerous': Privileges.Dangerous } @command(Privileges.Dangerous, hidden=True) async def addpriv(ctx: Context) -> str: """Set privileges for a specified player (by name).""" if len(ctx.args) < 2: return 'Invalid syntax: !addpriv <name> <role1 role2 role3 ...>' bits = Privileges(0) for m in [m.lower() for m in ctx.args[1:]]: if m not in str_priv_dict: return f'Not found: {m}.' bits |= str_priv_dict[m] if not (t := await glob.players.get_ensure(name=ctx.args[0])): return 'Could not find user.' await t.add_privs(bits) return f"Updated {t}'s privileges." @command(Privileges.Dangerous, hidden=True) async def rmpriv(ctx: Context) -> str: """Set privileges for a specified player (by name).""" if len(ctx.args) < 2: return 'Invalid syntax: !rmpriv <name> <role1 role2 role3 ...>' bits = Privileges(0) for m in [m.lower() for m in ctx.args[1:]]: if m not in str_priv_dict: return f'Not found: {m}.' bits |= str_priv_dict[m] if not (t := await glob.players.get_ensure(name=ctx.args[0])): return 'Could not find user.' await t.remove_privs(bits) return f"Updated {t}'s privileges." @command(Privileges.Dangerous) async def wipemap(ctx: Context) -> str: if ctx.args: return 'Invalid syntax: !wipemap' if time.time() >= ctx.player.last_np['timeout']: return 'Please /np a map first!' map_md5 = ctx.player.last_np['bmap'].md5 # delete scores from all tables async with glob.db.pool.acquire() as conn: async with conn.cursor() as db_cursor: for t in ('vn', 'rx', 'ap'): await db_cursor.execute( f'DELETE FROM scores_{t} ' 'WHERE map_md5 = %s', [map_md5] ) return 'Scores wiped.' @command(Privileges.Dangerous, hidden=True) async def menu(ctx: Context) -> str: """Temporary command to illustrate the menu option idea.""" ctx.player.send_current_menu() @command(Privileges.Dangerous, aliases=['re']) async def reload(ctx: Context) -> str: """Reload a python module.""" if len(ctx.args) != 1: return 'Invalid syntax: !reload <module>' parent, *children = ctx.args[0].split('.') try: mod = __import__(parent) except ModuleNotFoundError: return 'Module not found.' try: for child in children: mod = getattr(mod, child) except AttributeError: return f'Failed at {child}.' try: mod = importlib.reload(mod) except TypeError as exc: return f'{exc.args[0]}.' return f'Reloaded {mod.__name__}' @command(Privileges.Normal) async def server(ctx: Context) -> str: """Retrieve performance data about the server.""" build_str = f'gulag v{glob.version!r} ({glob.config.domain})' # get info about this process proc = psutil.Process(os.getpid()) uptime = int(time.time() - proc.create_time()) # get info about our cpu with open('/proc/cpuinfo') as f: header = 'model name\t: ' trailer = '\n' model_names = Counter( line[len(header):-len(trailer)] for line in f.readlines() if line.startswith('model name') ) # list of all cpus installed with thread count cpus_info = ' | '.join([f'{v}x {k}' for k, v in model_names.most_common()]) # get system-wide ram usage sys_ram = psutil.virtual_memory() # output ram usage as `{gulag_used}MB / {sys_used}MB / {sys_total}MB` gulag_ram = proc.memory_info()[0] ram_values = (gulag_ram, sys_ram.used, sys_ram.total) ram_info = ' / '.join([f'{v // 1024 ** 2}MB' for v in ram_values]) # divide up pkg versions, 3 displayed per line, e.g. # aiohttp v3.6.3 | aiomysql v0.0.21 | bcrypt v3.2.0 # cmyui v1.7.3 | datadog v0.40.1 | geoip2 v4.1.0 # mysql-connector-python v8.0.23 | orjson v3.5.1 # psutil v5.8.0 | py3rijndael v0.3.3 | uvloop v0.15.2 reqs = (Path.cwd() / 'ext/requirements.txt').read_text().splitlines() pkg_sections = [reqs[i:i+3] for i in range(0, len(reqs), 3)] mirror_url = glob.config.mirror using_osuapi = glob.config.osu_api_key != '' advanced_mode = glob.config.advanced auto_logging = glob.config.automatically_report_problems return '\n'.join([ f'{build_str} | uptime: {seconds_readable(uptime)}', f'cpu(s): {cpus_info}', f'ram: {ram_info}', f'mirror: {mirror_url} | osu!api connection: {using_osuapi}', f'advanced mode: {advanced_mode} | auto logging: {auto_logging}', '', 'requirements', '\n'.join([' | '.join([ f'{pkg} v{pkg_version(pkg)}' for pkg in section ]) for section in pkg_sections]) ]) """ Advanced commands (only allowed with `advanced = True` in config) """ # NOTE: some of these commands are potentially dangerous, and only # really intended for advanced users looking for access to lower level # utilities. Some may give direct access to utilties that could perform # harmful tasks to the underlying machine, so use at your own risk. if glob.config.advanced: from sys import modules as installed_mods __py_namespace = globals() | { mod: __import__(mod) for mod in ( 'asyncio', 'dis', 'os', 'sys', 'struct', 'discord', 'cmyui', 'datetime', 'time', 'inspect', 'math', 'importlib' ) if mod in installed_mods } @command(Privileges.Dangerous) async def py(ctx: Context) -> str: """Allow for (async) access to the python interpreter.""" # This can be very good for getting used to gulag's API; just look # around the codebase and find things to play with in your server. # Ex: !py return (await glob.players.get(name='cmyui')).status.action if not ctx.args: return 'owo' # turn our input args into a coroutine definition string. definition = '\n '.join([ 'async def __py(ctx):', ' '.join(ctx.args) ]) try: # def __py(ctx) exec(definition, __py_namespace) # add to namespace ret = await __py_namespace['__py'](ctx) # await it's return except Exception as exc: # return exception in osu! chat ret = f'{exc.__class__}: {exc}' if '__py' in __py_namespace: del __py_namespace['__py'] if ret is None: return 'Success' # TODO: perhaps size checks? if not isinstance(ret, str): ret = pprint.pformat(ret, compact=True) return ret """ Multiplayer commands # The commands below for multiplayer match management. # Most commands are open to player usage. """ @mp_commands.add(Privileges.Normal, aliases=['h']) async def mp_help(ctx: Context) -> str: """Show all documented multiplayer commands the player can access.""" prefix = glob.config.command_prefix cmds = [] for cmd in mp_commands.commands: if not cmd.doc or ctx.player.priv & cmd.priv != cmd.priv: # no doc, or insufficient permissions. continue cmds.append(f'{prefix}mp {cmd.triggers[0]}: {cmd.doc}') return '\n'.join(cmds) @mp_commands.add(Privileges.Normal, aliases=['st']) async def mp_start(ctx: Context) -> str: """Start the current multiplayer match, with any players ready.""" if len(ctx.args) > 1: return 'Invalid syntax: !mp start <force/seconds>' # this command can be used in a few different ways; # !mp start: start the match now (make sure all players are ready) # !mp start force: start the match now (don't check for ready) # !mp start N: start the match in N seconds (don't check for ready) # !mp start cancel: cancel the current match start timer if not ctx.args: # !mp start if ctx.match.starting['start'] is not None: time_remaining = int(ctx.match.starting['time'] - time.time()) return f'Match starting in {time_remaining} seconds.' if any([s.status == SlotStatus.not_ready for s in ctx.match.slots]): return 'Not all players are ready (`!mp start force` to override).' else: if ctx.args[0].isdecimal(): # !mp start N if ctx.match.starting['start'] is not None: time_remaining = int(ctx.match.starting['time'] - time.time()) return f'Match starting in {time_remaining} seconds.' # !mp start <seconds> duration = int(ctx.args[0]) if not 0 < duration <= 300: return 'Timer range is 1-300 seconds.' def _start() -> None: """Remove any pending timers & start the match.""" # remove start & alert timers ctx.match.starting['start'] = None ctx.match.starting['alerts'] = None ctx.match.starting['time'] = None # make sure player didn't leave the # match since queueing this start lol.. if ctx.player not in ctx.match: ctx.match.chat.send_bot('Player left match? (cancelled)') return ctx.match.start() ctx.match.chat.send_bot('Starting match.') def _alert_start(t: int) -> None: """Alert the match of the impending start.""" ctx.match.chat.send_bot(f'Match starting in {t} seconds.') # add timers to our match object, # so we can cancel them if needed. ctx.match.starting['start'] = glob.loop.call_later(duration, _start) ctx.match.starting['alerts'] = [ glob.loop.call_later(duration - t, lambda t=t: _alert_start(t)) for t in (60, 30, 10, 5, 4, 3, 2, 1) if t < duration ] ctx.match.starting['time'] = time.time() + duration return f'Match will start in {duration} seconds.' elif ctx.args[0] in ('cancel', 'c'): # !mp start cancel if ctx.match.starting['start'] is None: return 'Match timer not active!' ctx.match.starting['start'].cancel() for alert in ctx.match.starting['alerts']: alert.cancel() ctx.match.starting['start'] = None ctx.match.starting['alerts'] = None ctx.match.starting['time'] = None return 'Match timer cancelled.' elif ctx.args[0] not in ('force', 'f'): return 'Invalid syntax: !mp start <force/seconds>' # !mp start force simply passes through ctx.match.start() return 'Good luck!' @mp_commands.add(Privileges.Normal, aliases=['a']) async def mp_abort(ctx: Context) -> str: """Abort the current in-progress multiplayer match.""" if not ctx.match.in_progress: return 'Abort what?' ctx.match.unready_players(expected=SlotStatus.playing) ctx.match.in_progress = False ctx.match.enqueue(packets.matchAbort()) ctx.match.enqueue_state() return 'Match aborted.' @mp_commands.add(Privileges.Normal) async def mp_map(ctx: Context) -> str: """Set the current match's current map by id.""" if len(ctx.args) != 1 or not ctx.args[0].isdecimal(): return 'Invalid syntax: !mp map <beatmapid>' map_id = int(ctx.args[0]) if map_id == ctx.match.map_id: return 'Map already selected.' if not (bmap := await Beatmap.from_bid(map_id)): return 'Beatmap not found.' ctx.match.map_id = bmap.id ctx.match.map_md5 = bmap.md5 ctx.match.map_name = bmap.full ctx.match.mode = bmap.mode ctx.match.enqueue_state() return f'Selected: {bmap.embed}.' @mp_commands.add(Privileges.Normal) async def mp_mods(ctx: Context) -> str: """Set the current match's mods, from string form.""" if len(ctx.args) != 1 or len(ctx.args[0]) % 2 != 0: return 'Invalid syntax: !mp mods <mods>' mods = Mods.from_modstr(ctx.args[0]) mods = mods.filter_invalid_combos(ctx.match.mode.as_vanilla) if ctx.match.freemods: if ctx.player is ctx.match.host: # allow host to set speed-changing mods. ctx.match.mods = mods & SPEED_CHANGING_MODS # set slot mods ctx.match.get_slot(ctx.player).mods = mods & ~SPEED_CHANGING_MODS else: # not freemods, set match mods. ctx.match.mods = mods ctx.match.enqueue_state() return 'Match mods updated.' @mp_commands.add(Privileges.Normal, aliases=['fm', 'fmods']) async def mp_freemods(ctx: Context) -> str: """Toggle freemods status for the match.""" if len(ctx.args) != 1 or ctx.args[0] not in ('on', 'off'): return 'Invalid syntax: !mp freemods <on/off>' if ctx.args[0] == 'on': # central mods -> all players mods. ctx.match.freemods = True for s in ctx.match.slots: if s.status & SlotStatus.has_player: # the slot takes any non-speed # changing mods from the match. s.mods = ctx.match.mods & ~SPEED_CHANGING_MODS ctx.match.mods &= SPEED_CHANGING_MODS else: # host mods -> central mods. ctx.match.freemods = False host = ctx.match.get_host_slot() # should always exist # the match keeps any speed-changing mods, # and also takes any mods the host has enabled. ctx.match.mods &= SPEED_CHANGING_MODS ctx.match.mods |= host.mods for s in ctx.match.slots: if s.status & SlotStatus.has_player: s.mods = Mods.NOMOD ctx.match.enqueue_state() return 'Match freemod status updated.' @mp_commands.add(Privileges.Normal) async def mp_host(ctx: Context) -> str: """Set the current match's current host by id.""" if len(ctx.args) != 1: return 'Invalid syntax: !mp host <name>' if not (t := glob.players.get(name=ctx.args[0])): return 'Could not find a user by that name.' if t is ctx.match.host: return "They're already host, silly!" if t not in ctx.match: return 'Found no such player in the match.' ctx.match.host = t ctx.match.host.enqueue(packets.matchTransferHost()) ctx.match.enqueue_state(lobby=False) return 'Match host updated.' @mp_commands.add(Privileges.Normal) async def mp_randpw(ctx: Context) -> str: """Randomize the current match's password.""" ctx.match.passwd = secrets.token_hex(8) return 'Match password randomized.' @mp_commands.add(Privileges.Normal, aliases=['inv']) async def mp_invite(ctx: Context) -> str: """Invite a player to the current match by name.""" if len(ctx.args) != 1: return 'Invalid syntax: !mp invite <name>' if not (t := glob.players.get(name=ctx.args[0])): return 'Could not find a user by that name.' if t is glob.bot: return "I'm too busy!" if t is ctx.player: return "You can't invite yourself!" t.enqueue(packets.matchInvite(ctx.player, t.name)) return f'Invited {t} to the match.' @mp_commands.add(Privileges.Normal) async def mp_addref(ctx: Context) -> str: """Add a referee to the current match by name.""" if len(ctx.args) != 1: return 'Invalid syntax: !mp addref <name>' if not (t := glob.players.get(name=ctx.args[0])): return 'Could not find a user by that name.' if t not in ctx.match: return 'User must be in the current match!' if t in ctx.match.refs: return f'{t} is already a match referee!' ctx.match._refs.add(t) return f'{t.name} added to match referees.' @mp_commands.add(Privileges.Normal) async def mp_rmref(ctx: Context) -> str: """Remove a referee from the current match by name.""" if len(ctx.args) != 1: return 'Invalid syntax: !mp addref <name>' if not (t := glob.players.get(name=ctx.args[0])): return 'Could not find a user by that name.' if t not in ctx.match.refs: return f'{t} is not a match referee!' if t is ctx.match.host: return 'The host is always a referee!' ctx.match._refs.remove(t) return f'{t.name} removed from match referees.' @mp_commands.add(Privileges.Normal) async def mp_listref(ctx: Context) -> str: """List all referees from the current match.""" return ', '.join(map(str, ctx.match.refs)) + '.' @mp_commands.add(Privileges.Normal) async def mp_lock(ctx: Context) -> str: """Lock all unused slots in the current match.""" for slot in ctx.match.slots: if slot.status == SlotStatus.open: slot.status = SlotStatus.locked ctx.match.enqueue_state() return 'All unused slots locked.' @mp_commands.add(Privileges.Normal) async def mp_unlock(ctx: Context) -> str: """Unlock locked slots in the current match.""" for slot in ctx.match.slots: if slot.status == SlotStatus.locked: slot.status = SlotStatus.open ctx.match.enqueue_state() return 'All locked slots unlocked.' @mp_commands.add(Privileges.Normal) async def mp_teams(ctx: Context) -> str: """Change the team type for the current match.""" if len(ctx.args) != 1: return 'Invalid syntax: !mp teams <type>' team_type = ctx.args[0] if team_type in ('ffa', 'freeforall', 'head-to-head'): ctx.match.team_type = MatchTeamTypes.head_to_head elif team_type in ('tag', 'coop', 'co-op', 'tag-coop'): ctx.match.team_type = MatchTeamTypes.tag_coop elif team_type in ('teams', 'team-vs', 'teams-vs'): ctx.match.team_type = MatchTeamTypes.team_vs elif team_type in ('tag-teams', 'tag-team-vs', 'tag-teams-vs'): ctx.match.team_type = MatchTeamTypes.tag_team_vs else: return 'Unknown team type. (ffa, tag, teams, tag-teams)' # find the new appropriate default team. # defaults are (ffa: neutral, teams: red). if ctx.match.team_type in ( MatchTeamTypes.head_to_head, MatchTeamTypes.tag_coop ): new_t = MatchTeams.neutral else: new_t = MatchTeams.red # change each active slots team to # fit the correspoding team type. for s in ctx.match.slots: if s.status & SlotStatus.has_player: s.team = new_t if ctx.match.is_scrimming: # reset score if scrimming. ctx.match.reset_scrim() ctx.match.enqueue_state() return 'Match team type updated.' @mp_commands.add(Privileges.Normal, aliases=['cond']) async def mp_condition(ctx: Context) -> str: """Change the win condition for the match.""" if len(ctx.args) != 1: return 'Invalid syntax: !mp condition <type>' cond = ctx.args[0] if cond == 'pp': # special case - pp can't actually be used as an ingame # win condition, but gulag allows it to be passed into # this command during a scrims to use pp as a win cond. if not ctx.match.is_scrimming: return 'PP is only useful as a win condition during scrims.' if ctx.match.use_pp_scoring: return 'PP scoring already enabled.' ctx.match.use_pp_scoring = True else: if ctx.match.use_pp_scoring: ctx.match.use_pp_scoring = False if cond == 'score': ctx.match.win_condition = MatchWinConditions.score elif cond in ('accuracy', 'acc'): ctx.match.win_condition = MatchWinConditions.accuracy elif cond == 'combo': ctx.match.win_condition = MatchWinConditions.combo elif cond in ('scorev2', 'v2'): ctx.match.win_condition = MatchWinConditions.scorev2 else: return 'Invalid win condition. (score, acc, combo, scorev2, *pp)' ctx.match.enqueue_state(lobby=False) return 'Match win condition updated.' @mp_commands.add(Privileges.Normal, aliases=['autoref']) async def mp_scrim(ctx: Context) -> str: """Start a scrim in the current match.""" if ( len(ctx.args) != 1 or not (r_match := regexes.best_of.fullmatch(ctx.args[0])) ): return 'Invalid syntax: !mp scrim <bo#>' if not 0 <= (best_of := int(r_match[1])) < 16: return 'Best of must be in range 0-15.' winning_pts = (best_of // 2) + 1 if winning_pts != 0: # setting to real num if ctx.match.is_scrimming: return 'Already scrimming!' if best_of % 2 == 0: return 'Best of must be an odd number!' ctx.match.is_scrimming = True msg = (f'A scrimmage has been started by {ctx.player.name}; ' f'first to {winning_pts} points wins. Best of luck!') else: # setting to 0 if not ctx.match.is_scrimming: return 'Not currently scrimming!' ctx.match.is_scrimming = False ctx.match.reset_scrim() msg = 'Scrimming cancelled.' ctx.match.winning_pts = winning_pts return msg @mp_commands.add(Privileges.Normal, aliases=['end']) async def mp_endscrim(ctx: Context) -> str: """End the current matches ongoing scrim.""" if not ctx.match.is_scrimming: return 'Not currently scrimming!' ctx.match.is_scrimming = False ctx.match.reset_scrim() return 'Scrimmage ended.' # TODO: final score (get_score method?) @mp_commands.add(Privileges.Normal, aliases=['rm']) async def mp_rematch(ctx: Context) -> str: """Restart a scrim, or roll back previous match point.""" if ctx.args: return 'Invalid syntax: !mp rematch' if ctx.player is not ctx.match.host: return 'Only available to the host.' if not ctx.match.is_scrimming: if ctx.match.winning_pts == 0: msg = 'No scrim to rematch; to start one, use !mp scrim.' else: # re-start scrimming with old points ctx.match.is_scrimming = True msg = ( f'A rematch has been started by {ctx.player.name}; ' f'first to {ctx.match.winning_pts} points wins. Best of luck!' ) else: # reset the last match point awarded if not ctx.match.winners: return "No match points have yet been awarded!" if (recent_winner := ctx.match.winners[-1]) is None: return 'The last point was a tie!' ctx.match.match_points[recent_winner] -= 1 # TODO: team name ctx.match.winners.pop() msg = f'A point has been deducted from {recent_winner}.' return msg @mp_commands.add(Privileges.Admin, aliases=['f'], hidden=True) async def mp_force(ctx: Context) -> str: """Force a player into the current match by name.""" # NOTE: this overrides any limits such as silences or passwd. if len(ctx.args) != 1: return 'Invalid syntax: !mp force <name>' if not (t := glob.players.get(name=ctx.args[0])): return 'Could not find a user by that name.' t.join_match(ctx.match, ctx.match.passwd) return 'Welcome.' # mappool-related mp commands @mp_commands.add(Privileges.Normal, aliases=['lp']) async def mp_loadpool(ctx: Context) -> str: """Load a mappool into the current match.""" if len(ctx.args) != 1: return 'Invalid syntax: !mp loadpool <name>' if ctx.player is not ctx.match.host: return 'Only available to the host.' name = ctx.args[0] if not (pool := glob.pools.get(name)): return 'Could not find a pool by that name!' if ctx.match.pool is pool: return f'{pool!r} already selected!' ctx.match.pool = pool return f'{pool!r} selected.' @mp_commands.add(Privileges.Normal, aliases=['ulp']) async def mp_unloadpool(ctx: Context) -> str: """Unload the current matches mappool.""" if ctx.args: return 'Invalid syntax: !mp unloadpool' if ctx.player is not ctx.match.host: return 'Only available to the host.' if not ctx.match.pool: return 'No mappool currently selected!' ctx.match.pool = None return 'Mappool unloaded.' @mp_commands.add(Privileges.Normal) async def mp_ban(ctx: Context) -> str: """Ban a pick in the currently loaded mappool.""" if len(ctx.args) != 1: return 'Invalid syntax: !mp ban <pick>' if not ctx.match.pool: return 'No pool currently selected!' mods_slot = ctx.args[0] # separate mods & slot if not (r_match := regexes.mappool_pick.fullmatch(mods_slot)): return 'Invalid pick syntax; correct example: HD2' # not calling mods.filter_invalid_combos here intentionally. mods = Mods.from_modstr(r_match[1]) slot = int(r_match[2]) if (mods, slot) not in ctx.match.pool.maps: return f'Found no {mods_slot} pick in the pool.' if (mods, slot) in ctx.match.bans: return 'That pick is already banned!' ctx.match.bans.add((mods, slot)) return f'{mods_slot} banned.' @mp_commands.add(Privileges.Normal) async def mp_unban(ctx: Context) -> str: """Unban a pick in the currently loaded mappool.""" if len(ctx.args) != 1: return 'Invalid syntax: !mp unban <pick>' if not ctx.match.pool: return 'No pool currently selected!' mods_slot = ctx.args[0] # separate mods & slot if not (r_match := regexes.mappool_pick.fullmatch(mods_slot)): return 'Invalid pick syntax; correct example: HD2' # not calling mods.filter_invalid_combos here intentionally. mods = Mods.from_modstr(r_match[1]) slot = int(r_match[2]) if (mods, slot) not in ctx.match.pool.maps: return f'Found no {mods_slot} pick in the pool.' if (mods, slot) not in ctx.match.bans: return 'That pick is not currently banned!' ctx.match.bans.remove((mods, slot)) return f'{mods_slot} unbanned.' @mp_commands.add(Privileges.Normal) async def mp_pick(ctx: Context) -> str: """Pick a map from the currently loaded mappool.""" if len(ctx.args) != 1: return 'Invalid syntax: !mp pick <pick>' if not ctx.match.pool: return 'No pool currently loaded!' mods_slot = ctx.args[0] # separate mods & slot if not (r_match := regexes.mappool_pick.fullmatch(mods_slot)): return 'Invalid pick syntax; correct example: HD2' # not calling mods.filter_invalid_combos here intentionally. mods = Mods.from_modstr(r_match[1]) slot = int(r_match[2]) if (mods, slot) not in ctx.match.pool.maps: return f'Found no {mods_slot} pick in the pool.' if (mods, slot) in ctx.match.bans: return f'{mods_slot} has been banned from being picked.' # update match beatmap to the picked map. bmap = ctx.match.pool.maps[(mods, slot)] ctx.match.map_md5 = bmap.md5 ctx.match.map_id = bmap.id ctx.match.map_name = bmap.full # TODO: some kind of abstraction allowing # for something like !mp pick fm. if ctx.match.freemods: # if freemods are enabled, disable them. ctx.match.freemods = False for s in ctx.match.slots: if s.status & SlotStatus.has_player: s.mods = Mods.NOMOD # update match mods to the picked map. ctx.match.mods = mods ctx.match.enqueue_state() return f'Picked {bmap.embed}. ({mods_slot})' """ Mappool management commands # The commands below are for event managers # and tournament hosts/referees to help automate # tedious processes of running tournaments. """ @pool_commands.add(Privileges.Tournament, aliases=['h'], hidden=True) async def pool_help(ctx: Context) -> str: """Show all documented mappool commands the player can access.""" prefix = glob.config.command_prefix cmds = [] for cmd in pool_commands.commands: if not cmd.doc or ctx.player.priv & cmd.priv != cmd.priv: # no doc, or insufficient permissions. continue cmds.append(f'{prefix}pool {cmd.triggers[0]}: {cmd.doc}') return '\n'.join(cmds) @pool_commands.add(Privileges.Tournament, aliases=['c'], hidden=True) async def pool_create(ctx: Context) -> str: """Add a new mappool to the database.""" if len(ctx.args) != 1: return 'Invalid syntax: !pool create <name>' name = ctx.args[0] if glob.pools.get(name): return 'Pool already exists by that name!' # insert pool into db await glob.db.execute( 'INSERT INTO tourney_pools ' '(name, created_at, created_by) ' 'VALUES (%s, NOW(), %s)', [name, ctx.player.id] ) # add to cache (get from sql for id & time) res = await glob.db.fetch('SELECT * FROM tourney_pools ' 'WHERE name = %s', [name]) res['created_by'] = await glob.players.get_ensure(id=res['created_by']) glob.pools.append(MapPool(**res)) return f'{name} created.' @pool_commands.add(Privileges.Tournament, aliases=['del', 'd'], hidden=True) async def pool_delete(ctx: Context) -> str: """Remove a mappool from the database.""" if len(ctx.args) != 1: return 'Invalid syntax: !pool delete <name>' name = ctx.args[0] if not (pool := glob.pools.get(name)): return 'Could not find a pool by that name!' # delete from db await glob.db.execute( 'DELETE FROM tourney_pools ' 'WHERE name = %s', [name] ) # remove from cache glob.pools.remove(pool) return f'{name} deleted.' @pool_commands.add(Privileges.Tournament, aliases=['a'], hidden=True) async def pool_add(ctx: Context) -> str: """Add a new map to a mappool in the database.""" if len(ctx.args) != 2: return 'Invalid syntax: !pool add <name> <pick>' if time.time() >= ctx.player.last_np['timeout']: return 'Please /np a map first!' name, mods_slot = ctx.args mods_slot = mods_slot.upper() # ocd bmap = ctx.player.last_np['bmap'] # separate mods & slot if not (r_match := regexes.mappool_pick.fullmatch(mods_slot)): return 'Invalid pick syntax; correct example: HD2' if len(r_match[1]) % 2 != 0: return 'Invalid mods.' # not calling mods.filter_invalid_combos here intentionally. mods = Mods.from_modstr(r_match[1]) slot = int(r_match[2]) if not (pool := glob.pools.get(name)): return 'Could not find a pool by that name!' if (mods, slot) in pool.maps: return f'{mods_slot} is already {pool.maps[(mods, slot)].embed}!' if bmap in pool.maps.values(): return 'Map is already in the pool!' # insert into db await glob.db.execute( 'INSERT INTO tourney_pool_maps ' '(map_id, pool_id, mods, slot) ' 'VALUES (%s, %s, %s, %s)', [bmap.id, pool.id, mods, slot] ) # add to cache pool.maps[(mods, slot)] = bmap return f'{bmap.embed} added to {name}.' @pool_commands.add(Privileges.Tournament, aliases=['rm', 'r'], hidden=True) async def pool_remove(ctx: Context) -> str: """Remove a map from a mappool in the database.""" if len(ctx.args) != 2: return 'Invalid syntax: !pool remove <name> <pick>' name, mods_slot = ctx.args mods_slot = mods_slot.upper() # ocd # separate mods & slot if not (r_match := regexes.mappool_pick.fullmatch(mods_slot)): return 'Invalid pick syntax; correct example: HD2' # not calling mods.filter_invalid_combos here intentionally. mods = Mods.from_modstr(r_match[1]) slot = int(r_match[2]) if not (pool := glob.pools.get(name)): return 'Could not find a pool by that name!' if (mods, slot) not in pool.maps: return f'Found no {mods_slot} pick in the pool.' # delete from db await glob.db.execute( 'DELETE FROM tourney_pool_maps ' 'WHERE mods = %s AND slot = %s', [mods, slot] ) # remove from cache del pool.maps[(mods, slot)] return f'{mods_slot} removed from {name}.' @pool_commands.add(Privileges.Tournament, aliases=['l'], hidden=True) async def pool_list(ctx: Context) -> str: """List all existing mappools information.""" if not (pools := glob.pools): return 'There are currently no pools!' l = [f'Mappools ({len(pools)})'] for pool in pools: l.append( f'[{pool.created_at:%Y-%m-%d}] {pool.id}. ' f'{pool.name}, by {pool.created_by}.' ) return '\n'.join(l) @pool_commands.add(Privileges.Tournament, aliases=['i'], hidden=True) async def pool_info(ctx: Context) -> str: """Get all information for a specific mappool.""" if len(ctx.args) != 1: return 'Invalid syntax: !pool info <name>' name = ctx.args[0] if not (pool := glob.pools.get(name)): return 'Could not find a pool by that name!' _time = pool.created_at.strftime('%H:%M:%S%p') _date = pool.created_at.strftime('%Y-%m-%d') datetime_fmt = f'Created at {_time} on {_date}' l = [f'{pool.id}. {pool.name}, by {pool.created_by} | {datetime_fmt}.'] for (mods, slot), bmap in pool.maps.items(): l.append(f'{mods!r}{slot}: {bmap.embed}') return '\n'.join(l) """ Clan managment commands # The commands below are for managing gulag # clans, for users, clan staff, and server staff. """ @clan_commands.add(Privileges.Normal, aliases=['h']) async def clan_help(ctx: Context) -> str: """Show all documented clan commands the player can access.""" prefix = glob.config.command_prefix cmds = [] for cmd in clan_commands.commands: if not cmd.doc or ctx.player.priv & cmd.priv != cmd.priv: # no doc, or insufficient permissions. continue cmds.append(f'{prefix}clan {cmd.triggers[0]}: {cmd.doc}') return '\n'.join(cmds) @clan_commands.add(Privileges.Normal, aliases=['c']) async def clan_create(ctx: Context) -> str: """Create a clan with a given tag & name.""" if len(ctx.args) < 2: return 'Invalid syntax: !clan create <tag> <name>' if not 1 <= len(tag := ctx.args[0].upper()) <= 6: return 'Clan tag may be 1-6 characters long.' if not 2 <= len(name := ' '.join(ctx.args[1:])) <= 16: return 'Clan name may be 2-16 characters long.' if ctx.player.clan: return f"You're already a member of {ctx.player.clan}!" if glob.clans.get(name=name): return 'That name has already been claimed by another clan.' if glob.clans.get(tag=tag): return 'That tag has already been claimed by another clan.' created_at = datetime.now() # add clan to sql (generates id) clan_id = await glob.db.execute( 'INSERT INTO clans ' '(name, tag, created_at, owner) ' 'VALUES (%s, %s, %s, %s)', [name, tag, created_at, ctx.player.id] ) # add clan to cache clan = Clan(id=clan_id, name=name, tag=tag, created_at=created_at, owner=ctx.player.id) glob.clans.append(clan) # set owner's clan & clan priv (cache & sql) ctx.player.clan = clan ctx.player.clan_priv = ClanPrivileges.Owner clan.owner = ctx.player.id clan.members.add(ctx.player.id) if 'full_name' in ctx.player.__dict__: del ctx.player.full_name # wipe cached_property await glob.db.execute( 'UPDATE users ' 'SET clan_id = %s, ' 'clan_priv = 3 ' # ClanPrivileges.Owner 'WHERE id = %s', [clan_id, ctx.player.id] ) # announce clan creation if announce_chan := glob.channels['#announce']: msg = f'\x01ACTION founded {clan!r}.' announce_chan.send(msg, sender=ctx.player, to_self=True) return f'{clan!r} created.' @clan_commands.add(Privileges.Normal, aliases=['delete', 'd']) async def clan_disband(ctx: Context) -> str: """Disband a clan (admins may disband others clans).""" if ctx.args: # disband a specified clan by tag if ctx.player not in glob.players.staff: return 'Only staff members may disband the clans of others.' if not (clan := glob.clans.get(tag=' '.join(ctx.args).upper())): return 'Could not find a clan by that tag.' else: # disband the player's clan if not (clan := ctx.player.clan): return "You're not a member of a clan!" # delete clan from sql await glob.db.execute( 'DELETE FROM clans ' 'WHERE id = %s', [clan.id] ) # remove all members from the clan, # reset their clan privs (cache & sql). # NOTE: only online players need be to be uncached. for member_id in clan.members: if member := glob.players.get(id=member_id): member.clan = None member.clan_priv = None if 'full_name' in member.__dict__: del member.full_name # wipe cached_property await glob.db.execute( 'UPDATE users ' 'SET clan_id = 0, ' 'clan_priv = 0 ' 'WHERE clan_id = %s', [clan.id] ) # remove clan from cache glob.clans.remove(clan) # announce clan disbanding if announce_chan := glob.channels['#announce']: msg = f'\x01ACTION disbanded {clan!r}.' announce_chan.send(msg, sender=ctx.player, to_self=True) return f'{clan!r} disbanded.' @clan_commands.add(Privileges.Normal, aliases=['i']) async def clan_info(ctx: Context) -> str: """Lookup information of a clan by tag.""" if not ctx.args: return 'Invalid syntax: !clan info <tag>' if not (clan := glob.clans.get(tag=' '.join(ctx.args).upper())): return 'Could not find a clan by that tag.' msg = [f"{clan!r} | Founded {clan.created_at:%b %d, %Y}."] # get members privs from sql res = await glob.db.fetchall( 'SELECT name, clan_priv ' 'FROM users ' 'WHERE clan_id = %s ' 'ORDER BY clan_priv DESC', [clan.id], _dict=False ) for member_name, clan_priv in res: priv_str = ('Member', 'Officer', 'Owner')[clan_priv - 1] msg.append(f'[{priv_str}] {member_name}') return '\n'.join(msg) # TODO: !clan inv, !clan join, !clan leave @clan_commands.add(Privileges.Normal, aliases=['l']) async def clan_list(ctx: Context) -> str: """List all existing clans information.""" if ctx.args: if len(ctx.args) != 1 or not ctx.args[0].isdecimal(): return 'Invalid syntax: !clan list (page)' else: offset = 25 * int(ctx.args[0]) else: offset = 0 if offset >= (total_clans := len(glob.clans)): return 'No clans found.' msg = [f'gulag clans listing ({total_clans} total).'] for idx, clan in enumerate(glob.clans, offset): msg.append(f'{idx + 1}. {clan!r}') return '\n'.join(msg) async def process_commands(p: Player, t: Messageable, msg: str) -> Optional[CommandResponse]: # response is either a CommandResponse if we hit a command, # or simply False if we don't have any command hits. start_time = clock_ns() prefix_len = len(glob.config.command_prefix) trigger, *args = msg[prefix_len:].strip().split(' ') # case-insensitive triggers trigger = trigger.lower() for cmd_set in command_sets: # check if any command sets match. if trigger == cmd_set.trigger: # matching set found; if not args: args = ['help'] if trigger == 'mp': # multi set is a bit of a special case, # as we do some additional checks. if not (m := p.match): # player not in a match return if t is not m.chat: # message not in match channel return if args[0] != 'help' and (p not in m.refs and not p.priv & Privileges.Tournament): # doesn't have privs to use !mp commands (allow help). return t = m # send match for mp commands instead of chan trigger, *args = args # get subcommand # case-insensitive triggers trigger = trigger.lower() commands = cmd_set.commands break else: # no set commands matched, check normal commands. commands = regular_commands for cmd in commands: if ( trigger in cmd.triggers and p.priv & cmd.priv == cmd.priv ): # found matching trigger with sufficient privs ctx = Context(player=p, trigger=trigger, args=args) if isinstance(t, Match): ctx.match = t else: ctx.recipient = t # command found & we have privileges, run it. if res := await cmd.callback(ctx): elapsed = cmyui.utils.magnitude_fmt_time(clock_ns() - start_time) return { 'resp': f'{res} | Elapsed: {elapsed}', 'hidden': cmd.hidden } return {'hidden': False}

32.730417

182

0.597495

fa4a994e9123f80a551a9ea97895f95e25326e4d

12,805

py

Python

tests/test_create.py

fschleich/mhl

5ae1f083c05f44a4e9751dc233f7d393b01e2210

[ "MIT" ]

null

tests/test_create.py

fschleich/mhl

5ae1f083c05f44a4e9751dc233f7d393b01e2210

[ "MIT" ]

null

tests/test_create.py

fschleich/mhl

5ae1f083c05f44a4e9751dc233f7d393b01e2210

[ "MIT" ]

null

""" __author__ = "Alexander Sahm" __copyright__ = "Copyright 2020, Pomfort GmbH" __license__ = "MIT" __maintainer__ = "Patrick Renner, Alexander Sahm" __email__ = "opensource@pomfort.com" """ import os from freezegun import freeze_time from click.testing import CliRunner from ascmhl.history import MHLHistory import ascmhl.commands scenario_output_path = "examples/scenarios/Output" fake_ref_path = "/ref" @freeze_time("2020-01-16 09:15:00") def test_create_succeed(fs): fs.create_file("/root/Stuff.txt", contents="stuff\n") fs.create_file("/root/A/A1.txt", contents="A1\n") runner = CliRunner() result = runner.invoke(ascmhl.commands.create, ["/root", "-h", "xxh64", "-v"]) assert not result.exception assert os.path.exists("/root/ascmhl/0001_root_2020-01-16_091500.mhl") # with open('/root/ascmhl/0001_root_2020-01-16_091500.mhl', 'r') as fin: # print(fin.read()) assert os.path.exists("/root/ascmhl/ascmhl_chain.xml") @freeze_time("2020-01-16 09:15:00") def test_create_directory_hashes(fs): fs.create_file("/root/Stuff.txt", contents="stuff\n") fs.create_file("/root/A/A1.txt", contents="A1\n") result = CliRunner().invoke(ascmhl.commands.create, ["/root", "-h", "xxh64", "-v"]) assert result.exit_code == 0 # a directory hash for the folder A was created hash_list = MHLHistory.load_from_path("/root").hash_lists[0] assert hash_list.find_media_hash_for_path("A").is_directory assert hash_list.find_media_hash_for_path("A").hash_entries[0].hash_string == "95e230e90be29dd6" # and the directory hash of the root folder is set in the header assert hash_list.process_info.root_media_hash.hash_entries[0].hash_string == "36e824bc313f3b77" # test that the directory-hash command creates the same directory hashes # FIXME: command doesn't exist any more, replace with tests of verify directory hashes command? # result = CliRunner().invoke(ascmhl.commands.directory_hash, ["/root", "-v"]) # assert result.exit_code == 0 # assert "directory hash for: /root/A xxh64: ee2c3b94b6eecb8d" in result.output # assert "root hash: xxh64: 15ef0ade91fff267" in result.output # add some more files and folders fs.create_file("/root/B/B1.txt", contents="B1\n") fs.create_file("/root/A/A2.txt", contents="A2\n") fs.create_file("/root/A/AA/AA1.txt", contents="AA1\n") os.mkdir("/root/emptyFolderA") os.mkdir("/root/emptyFolderB") os.mkdir("/root/emptyFolderC") os.mkdir("/root/emptyFolderC/emptyFolderCA") os.mkdir("/root/emptyFolderC/emptyFolderCB") runner = CliRunner() result = runner.invoke(ascmhl.commands.create, ["/root", "-v", "-h", "xxh64"]) assert result.exit_code == 0 hash_list = MHLHistory.load_from_path("/root").hash_lists[-1] # due to the additional content the directory hash of folder A and the root folder changed assert hash_list.find_media_hash_for_path("A").hash_entries[0].hash_string == "a8d0ad812ab102bd" assert hash_list.process_info.root_media_hash.hash_entries[0].hash_string == "d6b881fed0b325bd" # empty folder all have the same directory hash assert hash_list.find_media_hash_for_path("emptyFolderA").hash_entries[0].hash_string == "ef46db3751d8e999" assert hash_list.find_media_hash_for_path("emptyFolderB").hash_entries[0].hash_string == "ef46db3751d8e999" # but since we also contain the file names in the dir hashes an empty folder that contains other empty folders # has a different directory structure hash assert ( hash_list.find_media_hash_for_path("emptyFolderC").hash_entries[0].structure_hash_string == "a5e6b8f95dfe2762" ) # the content hash stays the same assert hash_list.find_media_hash_for_path("emptyFolderC").hash_entries[0].hash_string == "ef46db3751d8e999" # test that the directory-hash command creates the same directory hashes # FIXME: command doesn't exist any more, replace with tests of verify directory hashes command? # result = CliRunner().invoke(ascmhl.commands.directory_hash, ["/root"]) # assert result.exit_code == 0 # assert " calculated root hash: xxh64: 5f4af3b3fd736415" in result.output # altering the content of one file with open("/root/A/A2.txt", "a") as file: file.write("!!") runner = CliRunner() result = runner.invoke(ascmhl.commands.create, ["/root", "-v", "-h", "xxh64"]) assert "ERROR: hash mismatch for A/A2.txt" in result.output hash_list = MHLHistory.load_from_path("/root").hash_lists[-1] # an altered file leads to a different root directory hash assert hash_list.process_info.root_media_hash.hash_entries[0].hash_string == "cae6659fc7b34c2f" # structure hash stays the same assert hash_list.process_info.root_media_hash.hash_entries[0].structure_hash_string == "2c99e94e8fa7d90c" # test that the directory-hash command creates the same root hash # FIXME: command doesn't exist any more, replace with tests of verify directory hashes command? # result = CliRunner().invoke(ascmhl.commands.directory_hash, ["/root"]) # assert result.exit_code == 0 # assert "root hash: xxh64: adf18c910489663c" in result.output assert hash_list.find_media_hash_for_path("B").hash_entries[0].hash_string == "51fb8fb099e92821" assert hash_list.find_media_hash_for_path("B").hash_entries[0].structure_hash_string == "945ecf443295ffbd" assert hash_list.process_info.root_media_hash.hash_entries[0].hash_string == "cae6659fc7b34c2f" assert hash_list.process_info.root_media_hash.hash_entries[0].structure_hash_string == "2c99e94e8fa7d90c" # rename one file os.rename("/root/B/B1.txt", "/root/B/B2.txt") runner = CliRunner() result = runner.invoke(ascmhl.commands.create, ["/root", "-v", "-h", "xxh64"]) assert "ERROR: hash mismatch for A/A2.txt" in result.output # in addition to the failing verification we also have a missing file B1/B1.txt assert "missing file(s):\n B/B1.txt" in result.output hash_list = MHLHistory.load_from_path("/root").hash_lists[-1] # the file name is part of the structure directory hash of the containing directory so it's hash changes assert hash_list.find_media_hash_for_path("B").hash_entries[0].structure_hash_string == "fa4e99472911e118" # .. and the content hash stays the same assert hash_list.find_media_hash_for_path("B").hash_entries[0].hash_string == "51fb8fb099e92821" # a renamed file also leads to a different root structure directory hash assert hash_list.process_info.root_media_hash.hash_entries[0].structure_hash_string == "b758c9b165fb6c2a" # and an unchanged content hash assert hash_list.process_info.root_media_hash.hash_entries[0].hash_string == "cae6659fc7b34c2f" # test that the directory-hash command creates the same root hash # FIXME: command doesn't exist any more, replace with tests of verify directory hashes command? # result = CliRunner().invoke(ascmhl.commands.directory_hash, ["/root"]) # assert result.exit_code == 0 # assert "root hash: xxh64: 01441cdf1803e2b8" in result.output @freeze_time("2020-01-16 09:15:00") def test_create_no_directory_hashes(fs): fs.create_file("/root/Stuff.txt", contents="stuff\n") fs.create_file("/root/A/A1.txt", contents="A1\n") os.mkdir("/root/emptyFolder") runner = CliRunner() result = runner.invoke(ascmhl.commands.create, ["/root", "-v", "-n"]) assert result.exit_code == 0 # a directory entry without hash was created for the folder A hash_list = MHLHistory.load_from_path("/root").hash_lists[0] assert hash_list.find_media_hash_for_path("A").is_directory assert len(hash_list.find_media_hash_for_path("A").hash_entries) == 0 # and no directory hash of the root folder is set in the header assert len(hash_list.process_info.root_media_hash.hash_entries) == 0 # the empty folder is still referenced even if not creating directory hashes assert hash_list.find_media_hash_for_path("emptyFolder").is_directory # removing an empty folder will cause creating a new generation to fail os.removedirs("/root/emptyFolder") runner = CliRunner() result = runner.invoke(ascmhl.commands.create, ["/root", "-v", "-n"]) assert result.exit_code == 15 assert "1 missing file(s):\n emptyFolder" in result.output def test_create_fail_altered_file(fs, simple_mhl_history): # alter a file with open("/root/Stuff.txt", "a") as file: file.write("!!") result = CliRunner().invoke(ascmhl.commands.create, ["/root"]) assert result.exit_code == 12 assert "Stuff.txt" in result.output # since the file is still altered every other seal will fail as well since we compare to the original hash result = CliRunner().invoke(ascmhl.commands.create, ["/root"]) assert result.exit_code == 12 assert "Stuff.txt" in result.output # when we now choose a new hash format we still fail but will add the new hash in the new format result = CliRunner().invoke(ascmhl.commands.create, ["/root", "-h", "md5"]) assert result.exit_code == 12 assert "Stuff.txt" in result.output root_history = MHLHistory.load_from_path("/root") stuff_txt_latest_media_hash = root_history.hash_lists[-1].find_media_hash_for_path("Stuff.txt") # the media hash for the Stuff.txt in the latest generation contains the failed xxh64 hash of the altered file assert stuff_txt_latest_media_hash.hash_entries[0].hash_format == "xxh64" assert stuff_txt_latest_media_hash.hash_entries[0].hash_string == "2346e97eb08788cc" assert stuff_txt_latest_media_hash.hash_entries[0].action == "failed" # and it contains NO new md5 hash value of the altered file assert len(stuff_txt_latest_media_hash.hash_entries) == 1 # since we didn't add a new md5 hash for the failing file before creating a new generation will still fail for the altered file result = CliRunner().invoke(ascmhl.commands.create, ["/root", "-h", "md5"]) assert result.exit_code == 12 assert "Stuff.txt" in result.output def test_create_fail_missing_file(fs, nested_mhl_histories): """ test that creating a new generation fails if there is a file missing on the file system that is referenced by one of the histories """ root_history = MHLHistory.load_from_path("/root") paths = root_history.set_of_file_paths() assert paths == {"/root/B/B1.txt", "/root/B/BB/BB1.txt", "/root/Stuff.txt", "/root/A/AA/AA1.txt"} os.remove("/root/A/AA/AA1.txt") runner = CliRunner() result = runner.invoke(ascmhl.commands.create, ["/root"]) assert result.exit_code == 15 assert "1 missing file(s):\n A/AA/AA1.txt" in result.output # the actual seal has been written to disk anyways we expect the history to contain # the new not yet referenced files (/root/B/BA/BA1.txt and /root/A/AB/AB1.txt) as well now root_history = MHLHistory.load_from_path("/root") paths = root_history.set_of_file_paths() # since we scan all generations for file paths we now get old files, missing files and new files here # as well as all entries for the directories assert paths == { "/root/B/B1.txt", "/root/B/BA/BA1.txt", "/root/B", "/root/A/AA", "/root/A/AB/AB1.txt", "/root/B/BA", "/root/A/AA/AA1.txt", "/root/A/AB", "/root/Stuff.txt", "/root/B/BB", "/root/A", "/root/B/BB/BB1.txt", } # since the file /root/A/AA/AA1.txt is still missing all further seal attempts will still fail runner = CliRunner() result = runner.invoke(ascmhl.commands.create, ["/root"]) assert result.exit_code == 15 assert "1 missing file(s):\n A/AA/AA1.txt" in result.output def test_create_nested_new_format(fs, nested_mhl_histories): """ test that ensures that hasehs in a new format are also verified in child histories used to verify fix of bug: https://github.com/ascmitc/mhl/issues/48 """ runner = CliRunner() result = runner.invoke(ascmhl.commands.create, ["/root", "-h", "md5"]) assert result.exit_code == 0 # load one of the the nested histories and check the first media hash of the last generation nested_history = MHLHistory.load_from_path("/root/A/AA") media_hash = nested_history.hash_lists[-1].media_hashes[0] # assure that the first hash entry is the verification of the original hash assert media_hash.hash_entries[0].action == "verified" assert media_hash.hash_entries[0].hash_format == "xxh64" # assure that the second hash entry is the new md5 hash assert media_hash.hash_entries[1].action == "verified" # formerly 'new' assert media_hash.hash_entries[1].hash_format == "md5"

47.425926

134

0.713081

b4906b3427dc03099d4bd0d3667aa733e3e4e636

6,818

py

Python

reinforcement_learning/rl_traveling_salesman_vehicle_routing_coach/src/TSP_env.py

jpmarques19/tensorflwo-test

0ff8b06e0415075c7269820d080284a42595bb2e

[ "Apache-2.0" ]

5

2019-01-19T23:53:35.000Z

2022-01-29T14:04:31.000Z

reinforcement_learning/rl_traveling_salesman_vehicle_routing_coach/src/TSP_env.py

jpmarques19/tensorflwo-test

0ff8b06e0415075c7269820d080284a42595bb2e

[ "Apache-2.0" ]

6

2020-01-28T23:08:49.000Z

2022-02-10T00:27:19.000Z

reinforcement_learning/rl_traveling_salesman_vehicle_routing_coach/src/TSP_env.py

jpmarques19/tensorflwo-test

0ff8b06e0415075c7269820d080284a42595bb2e

[ "Apache-2.0" ]

8

2020-12-14T15:49:24.000Z

2022-03-23T18:38:36.000Z

import gym import numpy as np from gym import spaces from TSP_view_2D import TSPView2D class TSPEasyEnv(gym.Env): def render(self, mode="human", close=False): if self.tsp_view is None: self.tsp_view = TSPView2D(self.n_orders, self.map_quad, grid_size=25) return self.tsp_view.update(self.agt_at_restaurant, self.restaurant_x, self.restaurant_y, self.o_delivery, self.o_x, self.o_y, self.agt_x, self.agt_y, mode) def __init__(self, n_orders=4, map_quad=(2, 2), max_time=50, randomized_orders=False): self.tsp_view = None self.map_quad = map_quad self.o_y = [] self.o_x = [] self.randomized_orders = randomized_orders self.n_orders = n_orders self.restaurant_x = 0 self.restaurant_y = 0 self.agt_x = None self.agt_y = None self.o_delivery = [] self.o_time = [] self.agt_at_restaurant = None self.agt_time = None self.max_time = max_time self.map_min_x = - map_quad[0] self.map_max_x = + map_quad[0] self.map_min_y = - map_quad[1] self.map_max_y = + map_quad[1] # agent x, agt_x_min = [self.map_min_x] agt_x_max = [self.map_max_x] # agent y, agt_y_min = [self.map_min_y] agt_y_max = [self.map_max_y] # n_orders for x positions of orders, o_x_min = [self.map_min_x for i in range(n_orders)] o_x_max = [self.map_max_x for i in range(n_orders)] # n_orders for y positions of orders, o_y_min = [self.map_min_y for i in range(n_orders)] o_y_max = [self.map_max_y for i in range(n_orders)] # whether delivered or not, 0 not delivered, 1 delivered o_delivery_min = [0] * n_orders o_delivery_max = [1] * n_orders # whether agent is at restaurant or not agt_at_restaurant_max = 1 agt_at_restaurant_min = 0 # Time since orders have been placed o_time_min = [0] * n_orders o_time_max = [max_time] * n_orders # Time since start agt_time_min = 0 agt_time_max = max_time self.observation_space = spaces.Box( low=np.array( agt_x_min + agt_y_min + o_x_min + o_y_min + [0] + [0] + o_delivery_min + [ agt_at_restaurant_min] + o_time_min + [ agt_time_min] + [0]), high=np.array( agt_x_max + agt_y_max + o_x_max + o_y_max + [0] + [0] + o_delivery_max + [ agt_at_restaurant_max] + o_time_max + [ agt_time_max] + [self.max_time]), dtype=np.int16 ) # Action space, UP, DOWN, LEFT, RIGHT self.action_space = spaces.Discrete(4) def reset(self): self.restaurant_x = 0 self.restaurant_y = 0 self.agt_x = self.restaurant_x self.agt_y = self.restaurant_y if self.randomized_orders: # Enforce uniqueness of orders, to prevent multiple orders being placed on the same points # And ensure actual orders in the episode are always == n_orders as expected orders=[] while len(orders) != self.n_orders: orders += [self.__receive_order()] orders = list(set(orders)) else: orders = [(-2, -2), (1,1), (2,0), (0, -2)] self.o_x = [x for x, y in orders] self.o_y = [y for x, y in orders] self.o_delivery = [0] * self.n_orders self.o_time = [0] * self.n_orders self.agt_at_restaurant = 1 self.agt_time = 0 return self.__compute_state() def step(self, action): done = False reward_before_action = self.__compute_reward() self.__play_action(action) reward = self.__compute_reward() - reward_before_action # If agent completed the route and returned back to start, give additional reward if (np.sum(self.o_delivery) == self.n_orders) and self.agt_at_restaurant: done = True reward += self.max_time * 0.1 # If there is timeout, no additional reward if self.agt_time >= self.max_time: done = True info = {} return self.__compute_state(), reward, done, info def __play_action(self, action): if action == 0: # UP self.agt_y = min(self.map_max_y, self.agt_y + 1) elif action == 1: # DOWN self.agt_y = max(self.map_min_y, self.agt_y - 1) elif action == 2: # LEFT self.agt_x = max(self.map_min_x, self.agt_x - 1) elif action == 3: # RIGHT self.agt_x = min(self.map_max_x, self.agt_x + 1) else: raise Exception("action: {action} is invalid") # Check for deliveries for ix in range(self.n_orders): if self.o_delivery[ix] == 0: if (self.o_x[ix] == self.agt_x) and (self.o_y[ix] == self.agt_y): self.o_delivery[ix] = 1 # Update the time for the waiting orders for ix in range(self.n_orders): if self.o_delivery[ix] == 0: self.o_time[ix] += 1 # Update time since agent left restaurant self.agt_time += 1 # Check if agent is at restaurant self.agt_at_restaurant = int((self.agt_x == self.restaurant_x) and (self.agt_y == self.restaurant_y)) def __compute_state(self): return [self.agt_x] + [self.agt_y] + self.o_x + self.o_y + [self.restaurant_x] + [ self.restaurant_y] + self.o_delivery + [ self.agt_at_restaurant] + self.o_time + [ self.agt_time] + [(self.max_time - self.agt_time)] def __receive_order(self): # Generate a single order, not at the center (where the restaurant is) self.order_x = \ np.random.choice([i for i in range(self.map_min_x, self.map_max_x + 1) if i != self.restaurant_x], 1)[0] self.order_y = \ np.random.choice([i for i in range(self.map_min_y, self.map_max_y + 1) if i != self.restaurant_y], 1)[0] return self.order_x, self.order_y def __compute_reward(self): return np.sum(np.asarray(self.o_delivery) * self.max_time / (np.asarray(self.o_time) + 0.0001)) \ - self.agt_time class TSPMediumEnv(TSPEasyEnv): def __init__(self, n_orders=4, map_quad=(2, 2), max_time=50, randomized_orders=True): super().__init__(n_orders, map_quad, max_time, randomized_orders) class TSPHardEnv(TSPEasyEnv): def __init__(self, n_orders=10, map_quad=(10, 10), max_time=5000, randomized_orders=True): super().__init__(n_orders, map_quad, max_time, randomized_orders)

35.510417

116

0.588589

25a6bff3eb2f21d4cc8d8685672e3e4d3ec6bda2

451

py

Python

nautilus/graphql/query.py

LeptoSpira/nautilus-chambers

5aafd9eb599ed35d3e90c3ef7b84a25d28e60922

[ "MIT" ]

1

2020-05-12T03:01:58.000Z

nautilus/graphql/query.py

LeptoFlare/nautilus-chambers

5aafd9eb599ed35d3e90c3ef7b84a25d28e60922

[ "MIT" ]

13

2020-05-05T01:06:01.000Z

2020-07-19T07:17:31.000Z

nautilus/graphql/query.py

LeptoFlare/nautilus-chambers

5aafd9eb599ed35d3e90c3ef7b84a25d28e60922

[ "MIT" ]

1

2019-08-16T02:35:17.000Z

"""Contains query resolvers.""" from ariadne import QueryType from nautilus import utils query_type = QueryType() @query_type.field("readProfile") def resolve_read_profile(*_, discord): """query readProfile""" utils.logger.debug(f"readProfile | discord={discord}") if not (error := utils.errors.check_for([utils.errors.missing], discord)): return utils.dbh.find_profile(discord) return {"status": False, "errors": [error]}

28.1875

78

0.711752

70a5578ba6fed6590e22243adcf2db40376f8e99

110

py

Python

1065-pares-entre-cinco-numeros.py

ErickSimoes/URI-Online-Judge

7e6f141db2647b1d0d69951b064bd95b0ce4ba1a

[ "MIT" ]

null

1065-pares-entre-cinco-numeros.py

ErickSimoes/URI-Online-Judge

7e6f141db2647b1d0d69951b064bd95b0ce4ba1a

[ "MIT" ]

null

1065-pares-entre-cinco-numeros.py

ErickSimoes/URI-Online-Judge

7e6f141db2647b1d0d69951b064bd95b0ce4ba1a

[ "MIT" ]

1

2019-10-29T16:51:29.000Z

par = 0 for _ in range(5): num = int(input()) if num % 2 == 0: par += 1 print(par, 'valores pares')

12.222222

27

0.527273

755448555b6e9730432590407eb688e632243c9c

1,204

py

Python

perfkitbenchmarker/linux_packages/iperf3.py

Nowasky/PerfKitBenchmarker

cfa88e269eb373780910896ed4bdc8db09469753

[ "Apache-2.0" ]

3

2018-04-28T13:06:14.000Z

2020-06-09T02:39:44.000Z

perfkitbenchmarker/linux_packages/iperf3.py

Nowasky/PerfKitBenchmarker

cfa88e269eb373780910896ed4bdc8db09469753

[ "Apache-2.0" ]

1

2021-09-09T07:43:25.000Z

2021-09-09T10:47:56.000Z

perfkitbenchmarker/linux_packages/iperf3.py

Nowasky/PerfKitBenchmarker

cfa88e269eb373780910896ed4bdc8db09469753

[ "Apache-2.0" ]

6

2019-06-11T18:59:57.000Z

2021-03-02T19:14:42.000Z

# Copyright 2021 PerfKitBenchmarker Authors. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Module containing iperf3 installation functions.""" def _Install(vm): """Install Cloud Harmory iperf benchmark on VM.""" # Follows instructions from https://software.es.net/iperf/obtaining.html. vm.Install('wget') vm.Install('build_tools') vm.InstallPackages('lib32z1') vm.RemoteCommand( 'wget https://downloads.es.net/pub/iperf/iperf-3.9.tar.gz --no-check-certificate' ) vm.RemoteCommand('tar -xf iperf-3.9.tar.gz') vm.RemoteCommand('cd iperf-3.9 && ./configure') vm.RemoteCommand('cd iperf-3.9 && make') vm.RemoteCommand('cd iperf-3.9 && sudo make install')

38.83871

87

0.737542

7bfed55a579da789231c48e03ad08b1ac860b67c

25,763

py

Python

keras/layers/wrappers.py

chasebrignac/keras

2ad932ba4ea501af7c3163573fce994ef878d8ef

[ "MIT" ]

1

2020-03-03T08:56:34.000Z

keras/layers/wrappers.py

chasebrignac/keras

2ad932ba4ea501af7c3163573fce994ef878d8ef

[ "MIT" ]

10

2018-09-27T23:03:18.000Z

2018-12-05T23:32:33.000Z

keras/layers/wrappers.py

chasebrignac/keras

2ad932ba4ea501af7c3163573fce994ef878d8ef

[ "MIT" ]

null

# -*- coding: utf-8 -*- """Layers that augment the functionality of a base layer. """ from __future__ import absolute_import from __future__ import division from __future__ import print_function import copy from ..engine.base_layer import Layer from ..engine.base_layer import InputSpec from ..utils.generic_utils import has_arg from ..utils.generic_utils import object_list_uid from .. import backend as K from . import recurrent class Wrapper(Layer): """Abstract wrapper base class. Wrappers take another layer and augment it in various ways. Do not use this class as a layer, it is only an abstract base class. Two usable wrappers are the `TimeDistributed` and `Bidirectional` wrappers. # Arguments layer: The layer to be wrapped. """ def __init__(self, layer, **kwargs): self.layer = layer # Tracks mapping of Wrapper inputs to inner layer inputs. Useful when # the inner layer has update ops that depend on its inputs (as opposed # to the inputs to the Wrapper layer). self._input_map = {} super(Wrapper, self).__init__(**kwargs) def build(self, input_shape=None): self.built = True @property def activity_regularizer(self): if hasattr(self.layer, 'activity_regularizer'): return self.layer.activity_regularizer else: return None @property def trainable(self): return self.layer.trainable @trainable.setter def trainable(self, value): self.layer.trainable = value @property def trainable_weights(self): return self.layer.trainable_weights @property def non_trainable_weights(self): return self.layer.non_trainable_weights @property def updates(self): if hasattr(self.layer, 'updates'): return self.layer.updates return [] def get_updates_for(self, inputs=None): # If the wrapper modifies the inputs, use the modified inputs to # get the updates from the inner layer. inner_inputs = inputs if inputs is not None: uid = object_list_uid(inputs) if uid in self._input_map: inner_inputs = self._input_map[uid] updates = self.layer.get_updates_for(inner_inputs) updates += super(Wrapper, self).get_updates_for(inputs) return updates @property def losses(self): if hasattr(self.layer, 'losses'): return self.layer.losses return [] def get_losses_for(self, inputs=None): if inputs is None: losses = self.layer.get_losses_for(None) return losses + super(Wrapper, self).get_losses_for(None) return super(Wrapper, self).get_losses_for(inputs) def get_weights(self): return self.layer.get_weights() def set_weights(self, weights): self.layer.set_weights(weights) def get_config(self): config = {'layer': {'class_name': self.layer.__class__.__name__, 'config': self.layer.get_config()}} base_config = super(Wrapper, self).get_config() return dict(list(base_config.items()) + list(config.items())) @classmethod def from_config(cls, config, custom_objects=None): from . import deserialize as deserialize_layer layer = deserialize_layer(config.pop('layer'), custom_objects=custom_objects) return cls(layer, **config) class TimeDistributed(Wrapper): """This wrapper applies a layer to every temporal slice of an input. The input should be at least 3D, and the dimension of index one will be considered to be the temporal dimension. Consider a batch of 32 samples, where each sample is a sequence of 10 vectors of 16 dimensions. The batch input shape of the layer is then `(32, 10, 16)`, and the `input_shape`, not including the samples dimension, is `(10, 16)`. You can then use `TimeDistributed` to apply a `Dense` layer to each of the 10 timesteps, independently: ```python # as the first layer in a model model = Sequential() model.add(TimeDistributed(Dense(8), input_shape=(10, 16))) # now model.output_shape == (None, 10, 8) ``` The output will then have shape `(32, 10, 8)`. In subsequent layers, there is no need for the `input_shape`: ```python model.add(TimeDistributed(Dense(32))) # now model.output_shape == (None, 10, 32) ``` The output will then have shape `(32, 10, 32)`. `TimeDistributed` can be used with arbitrary layers, not just `Dense`, for instance with a `Conv2D` layer: ```python model = Sequential() model.add(TimeDistributed(Conv2D(64, (3, 3)), input_shape=(10, 299, 299, 3))) ``` # Arguments layer: a layer instance. """ def __init__(self, layer, **kwargs): super(TimeDistributed, self).__init__(layer, **kwargs) self.supports_masking = True def _get_shape_tuple(self, init_tuple, tensor, start_idx, int_shape=None): """Finds non-specific dimensions in the static shapes and replaces them by the corresponding dynamic shapes of the tensor. # Arguments init_tuple: a tuple, the first part of the output shape tensor: the tensor from which to get the (static and dynamic) shapes as the last part of the output shape start_idx: int, which indicate the first dimension to take from the static shape of the tensor int_shape: an alternative static shape to take as the last part of the output shape # Returns The new int_shape with the first part from init_tuple and the last part from either `int_shape` (if provided) or K.int_shape(tensor), where every `None` is replaced by the corresponding dimension from K.shape(tensor) """ # replace all None in int_shape by K.shape if int_shape is None: int_shape = K.int_shape(tensor)[start_idx:] if not any(not s for s in int_shape): return init_tuple + int_shape tensor_shape = K.shape(tensor) int_shape = list(int_shape) for i, s in enumerate(int_shape): if not s: int_shape[i] = tensor_shape[start_idx + i] return init_tuple + tuple(int_shape) def build(self, input_shape): assert len(input_shape) >= 3 self.input_spec = InputSpec(shape=input_shape) child_input_shape = (input_shape[0],) + input_shape[2:] if not self.layer.built: self.layer.build(child_input_shape) self.layer.built = True super(TimeDistributed, self).build() def compute_output_shape(self, input_shape): child_input_shape = (input_shape[0],) + input_shape[2:] child_output_shape = self.layer.compute_output_shape(child_input_shape) timesteps = input_shape[1] return (child_output_shape[0], timesteps) + child_output_shape[1:] def call(self, inputs, training=None, mask=None): kwargs = {} if has_arg(self.layer.call, 'training'): kwargs['training'] = training uses_learning_phase = False input_shape = K.int_shape(inputs) if input_shape[0]: # batch size matters, use rnn-based implementation def step(x, _): global uses_learning_phase output = self.layer.call(x, **kwargs) if hasattr(output, '_uses_learning_phase'): uses_learning_phase = (output._uses_learning_phase or uses_learning_phase) return output, [] _, outputs, _ = K.rnn(step, inputs, initial_states=[], input_length=input_shape[1], unroll=False) y = outputs else: # No batch size specified, therefore the layer will be able # to process batches of any size. # We can go with reshape-based implementation for performance. input_length = input_shape[1] if not input_length: input_length = K.shape(inputs)[1] inner_input_shape = self._get_shape_tuple((-1,), inputs, 2) # Shape: (num_samples * timesteps, ...). And track the # transformation in self._input_map. input_uid = object_list_uid(inputs) inputs = K.reshape(inputs, inner_input_shape) self._input_map[input_uid] = inputs # (num_samples * timesteps, ...) if has_arg(self.layer.call, 'mask') and mask is not None: inner_mask_shape = self._get_shape_tuple((-1,), mask, 2) kwargs['mask'] = K.reshape(mask, inner_mask_shape) y = self.layer.call(inputs, **kwargs) if hasattr(y, '_uses_learning_phase'): uses_learning_phase = y._uses_learning_phase # Shape: (num_samples, timesteps, ...) output_shape = self.compute_output_shape(input_shape) output_shape = self._get_shape_tuple( (-1, input_length), y, 1, output_shape[2:]) y = K.reshape(y, output_shape) # Apply activity regularizer if any: if (hasattr(self.layer, 'activity_regularizer') and self.layer.activity_regularizer is not None): regularization_loss = self.layer.activity_regularizer(y) self.add_loss(regularization_loss, inputs) if uses_learning_phase: y._uses_learning_phase = True return y def compute_mask(self, inputs, mask=None): """Computes an output mask tensor for Embedding layer based on the inputs, mask, and the inner layer. If batch size is specified: Simply return the input `mask`. (An rnn-based implementation with more than one rnn inputs is required but not supported in Keras yet.) Otherwise we call `compute_mask` of the inner layer at each time step. If the output mask at each time step is not `None`: (E.g., inner layer is Masking or RNN) Concatenate all of them and return the concatenation. If the output mask at each time step is `None` and the input mask is not `None`: (E.g., inner layer is Dense) Reduce the input_mask to 2 dimensions and return it. Otherwise (both the output mask and the input mask are `None`): (E.g., `mask` is not used at all) Return `None`. # Arguments inputs: Tensor mask: Tensor # Returns None or a tensor """ # cases need to call the layer.compute_mask when input_mask is None: # Masking layer and Embedding layer with mask_zero input_shape = K.int_shape(inputs) if input_shape[0]: # batch size matters, we currently do not handle mask explicitly return mask inner_mask = mask if inner_mask is not None: inner_mask_shape = self._get_shape_tuple((-1,), mask, 2) inner_mask = K.reshape(inner_mask, inner_mask_shape) input_uid = object_list_uid(inputs) inner_inputs = self._input_map[input_uid] output_mask = self.layer.compute_mask(inner_inputs, inner_mask) if output_mask is None: if mask is None: return None # input_mask is not None, and output_mask is None: # we should return a not-None mask output_mask = mask for _ in range(2, len(K.int_shape(mask))): output_mask = K.any(output_mask, axis=-1) else: # output_mask is not None. We need to reshape it input_length = input_shape[1] if not input_length: input_length = K.shape(inputs)[1] output_mask_int_shape = K.int_shape(output_mask) if output_mask_int_shape is None: # if the output_mask does not have a static shape, # its shape must be the same as mask's if mask is not None: output_mask_int_shape = K.int_shape(mask) else: output_mask_int_shape = K.compute_output_shape(input_shape)[:-1] output_mask_shape = self._get_shape_tuple( (-1, input_length), output_mask, 1, output_mask_int_shape[1:]) output_mask = K.reshape(output_mask, output_mask_shape) return output_mask class Bidirectional(Wrapper): """Bidirectional wrapper for RNNs. # Arguments layer: `Recurrent` instance. merge_mode: Mode by which outputs of the forward and backward RNNs will be combined. One of {'sum', 'mul', 'concat', 'ave', None}. If None, the outputs will not be combined, they will be returned as a list. # Raises ValueError: In case of invalid `merge_mode` argument. # Examples ```python model = Sequential() model.add(Bidirectional(LSTM(10, return_sequences=True), input_shape=(5, 10))) model.add(Bidirectional(LSTM(10))) model.add(Dense(5)) model.add(Activation('softmax')) model.compile(loss='categorical_crossentropy', optimizer='rmsprop') ``` """ def __init__(self, layer, merge_mode='concat', weights=None, **kwargs): if merge_mode not in ['sum', 'mul', 'ave', 'concat', None]: raise ValueError('Invalid merge mode. ' 'Merge mode should be one of ' '{"sum", "mul", "ave", "concat", None}') self.forward_layer = copy.copy(layer) config = layer.get_config() config['go_backwards'] = not config['go_backwards'] self.backward_layer = layer.__class__.from_config(config) self.forward_layer.name = 'forward_' + self.forward_layer.name self.backward_layer.name = 'backward_' + self.backward_layer.name self.merge_mode = merge_mode if weights: nw = len(weights) self.forward_layer.initial_weights = weights[:nw // 2] self.backward_layer.initial_weights = weights[nw // 2:] self.stateful = layer.stateful self.return_sequences = layer.return_sequences self.return_state = layer.return_state self.supports_masking = True self._trainable = True super(Bidirectional, self).__init__(layer, **kwargs) self.input_spec = layer.input_spec self._num_constants = None @property def trainable(self): return self._trainable @trainable.setter def trainable(self, value): self._trainable = value self.forward_layer.trainable = value self.backward_layer.trainable = value def get_weights(self): return self.forward_layer.get_weights() + self.backward_layer.get_weights() def set_weights(self, weights): nw = len(weights) self.forward_layer.set_weights(weights[:nw // 2]) self.backward_layer.set_weights(weights[nw // 2:]) def compute_output_shape(self, input_shape): output_shape = self.forward_layer.compute_output_shape(input_shape) if self.return_state: state_shape = output_shape[1:] output_shape = output_shape[0] if self.merge_mode == 'concat': output_shape = list(output_shape) output_shape[-1] *= 2 output_shape = tuple(output_shape) elif self.merge_mode is None: output_shape = [output_shape, copy.copy(output_shape)] if self.return_state: if self.merge_mode is None: return output_shape + state_shape + copy.copy(state_shape) return [output_shape] + state_shape + copy.copy(state_shape) return output_shape def __call__(self, inputs, initial_state=None, constants=None, **kwargs): inputs, initial_state, constants = recurrent._standardize_args( inputs, initial_state, constants, self._num_constants) if initial_state is None and constants is None: return super(Bidirectional, self).__call__(inputs, **kwargs) # Applies the same workaround as in `RNN.__call__` additional_inputs = [] additional_specs = [] if initial_state is not None: # Check if `initial_state` can be splitted into half num_states = len(initial_state) if num_states % 2 > 0: raise ValueError( 'When passing `initial_state` to a Bidirectional RNN, ' 'the state should be a list containing the states of ' 'the underlying RNNs. ' 'Found: ' + str(initial_state)) kwargs['initial_state'] = initial_state additional_inputs += initial_state state_specs = [InputSpec(shape=K.int_shape(state)) for state in initial_state] self.forward_layer.state_spec = state_specs[:num_states // 2] self.backward_layer.state_spec = state_specs[num_states // 2:] additional_specs += state_specs if constants is not None: kwargs['constants'] = constants additional_inputs += constants constants_spec = [InputSpec(shape=K.int_shape(constant)) for constant in constants] self.forward_layer.constants_spec = constants_spec self.backward_layer.constants_spec = constants_spec additional_specs += constants_spec self._num_constants = len(constants) self.forward_layer._num_constants = self._num_constants self.backward_layer._num_constants = self._num_constants is_keras_tensor = K.is_keras_tensor(additional_inputs[0]) for tensor in additional_inputs: if K.is_keras_tensor(tensor) != is_keras_tensor: raise ValueError('The initial state of a Bidirectional' ' layer cannot be specified with a mix of' ' Keras tensors and non-Keras tensors' ' (a "Keras tensor" is a tensor that was' ' returned by a Keras layer, or by `Input`)') if is_keras_tensor: # Compute the full input spec, including state full_input = [inputs] + additional_inputs full_input_spec = self.input_spec + additional_specs # Perform the call with temporarily replaced input_spec original_input_spec = self.input_spec self.input_spec = full_input_spec output = super(Bidirectional, self).__call__(full_input, **kwargs) self.input_spec = original_input_spec return output else: return super(Bidirectional, self).__call__(inputs, **kwargs) def call(self, inputs, mask=None, training=None, initial_state=None, constants=None): kwargs = {} if has_arg(self.layer.call, 'training'): kwargs['training'] = training if has_arg(self.layer.call, 'mask'): kwargs['mask'] = mask if has_arg(self.layer.call, 'constants'): kwargs['constants'] = constants if initial_state is not None and has_arg(self.layer.call, 'initial_state'): forward_inputs = [inputs[0]] backward_inputs = [inputs[0]] pivot = len(initial_state) // 2 + 1 # add forward initial state forward_state = inputs[1:pivot] forward_inputs += forward_state if self._num_constants is None: # add backward initial state backward_state = inputs[pivot:] backward_inputs += backward_state else: # add backward initial state backward_state = inputs[pivot:-self._num_constants] backward_inputs += backward_state # add constants for forward and backward layers forward_inputs += inputs[-self._num_constants:] backward_inputs += inputs[-self._num_constants:] y = self.forward_layer.call(forward_inputs, initial_state=forward_state, **kwargs) y_rev = self.backward_layer.call(backward_inputs, initial_state=backward_state, **kwargs) else: y = self.forward_layer.call(inputs, **kwargs) y_rev = self.backward_layer.call(inputs, **kwargs) if self.return_state: states = y[1:] + y_rev[1:] y = y[0] y_rev = y_rev[0] if self.return_sequences: y_rev = K.reverse(y_rev, 1) if self.merge_mode == 'concat': output = K.concatenate([y, y_rev]) elif self.merge_mode == 'sum': output = y + y_rev elif self.merge_mode == 'ave': output = (y + y_rev) / 2 elif self.merge_mode == 'mul': output = y * y_rev elif self.merge_mode is None: output = [y, y_rev] else: raise ValueError('Unrecognized value for argument merge_mode: %s' % (self.merge_mode)) # Properly set learning phase if (getattr(y, '_uses_learning_phase', False) or getattr(y_rev, '_uses_learning_phase', False)): if self.merge_mode is None: for out in output: out._uses_learning_phase = True else: output._uses_learning_phase = True if self.return_state: if self.merge_mode is None: return output + states return [output] + states return output def reset_states(self): self.forward_layer.reset_states() self.backward_layer.reset_states() def build(self, input_shape): with K.name_scope(self.forward_layer.name): self.forward_layer.build(input_shape) with K.name_scope(self.backward_layer.name): self.backward_layer.build(input_shape) self.built = True def compute_mask(self, inputs, mask): if isinstance(mask, list): mask = mask[0] if self.return_sequences: if not self.merge_mode: output_mask = [mask, mask] else: output_mask = mask else: output_mask = [None, None] if not self.merge_mode else None if self.return_state: states = self.forward_layer.states state_mask = [None for _ in states] if isinstance(output_mask, list): return output_mask + state_mask * 2 return [output_mask] + state_mask * 2 return output_mask @property def trainable_weights(self): if hasattr(self.forward_layer, 'trainable_weights'): return (self.forward_layer.trainable_weights + self.backward_layer.trainable_weights) return [] @property def non_trainable_weights(self): if hasattr(self.forward_layer, 'non_trainable_weights'): return (self.forward_layer.non_trainable_weights + self.backward_layer.non_trainable_weights) return [] @property def updates(self): if hasattr(self.forward_layer, 'updates'): return self.forward_layer.updates + self.backward_layer.updates return [] def get_updates_for(self, inputs=None): forward_updates = self.forward_layer.get_updates_for(inputs) backward_updates = self.backward_layer.get_updates_for(inputs) return (super(Wrapper, self).get_updates_for(inputs) + forward_updates + backward_updates) @property def losses(self): if hasattr(self.forward_layer, 'losses'): return self.forward_layer.losses + self.backward_layer.losses return [] def get_losses_for(self, inputs=None): forward_losses = self.forward_layer.get_losses_for(inputs) backward_losses = self.backward_layer.get_losses_for(inputs) return (super(Wrapper, self).get_losses_for(inputs) + forward_losses + backward_losses) @property def constraints(self): constraints = {} if hasattr(self.forward_layer, 'constraints'): constraints.update(self.forward_layer.constraints) constraints.update(self.backward_layer.constraints) return constraints def get_config(self): config = {'merge_mode': self.merge_mode} if self._num_constants is not None: config['num_constants'] = self._num_constants base_config = super(Bidirectional, self).get_config() return dict(list(base_config.items()) + list(config.items())) @classmethod def from_config(cls, config, custom_objects=None): from . import deserialize as deserialize_layer rnn_layer = deserialize_layer(config.pop('layer'), custom_objects=custom_objects) num_constants = config.pop('num_constants', None) layer = cls(rnn_layer, **config) layer._num_constants = num_constants return layer

39.392966

98

0.608237

7d2eb81d14d6f696ce047ce29601b12652e9b220

286

py

Python

test/lex_doc1.py

pyarnold/ply

98bb0e095d72c8aed9de01c15b65fa096c745ce3

[ "Unlicense" ]

1

2020-12-18T01:07:42.000Z

test/lex_doc1.py

pyarnold/ply

98bb0e095d72c8aed9de01c15b65fa096c745ce3

[ "Unlicense" ]

null

test/lex_doc1.py

pyarnold/ply

98bb0e095d72c8aed9de01c15b65fa096c745ce3

[ "Unlicense" ]

null

# lex_doc1.py # # Missing documentation string import sys if ".." not in sys.path: sys.path.insert(0, "..") import ply.lex as lex tokens = [ "PLUS", "MINUS", "NUMBER", ] t_PLUS = r'\+' t_MINUS = r'-' def t_NUMBER(t): pass def t_error(t): pass lex.lex()

9.862069

30

0.56993

844419c97ccd0ed050ed5004ca38582cf0766427

2,779

py

Python

samples/basic/executor/models/ietf/ietf-netconf-monitoring/nc-execute-ietf-netconf-monitoring-20-ydk.py

deom119/ydk-py-samples

1ad6cc2b798f358ff835df93d12924df308b85fc

[ "Apache-2.0" ]

104

2016-03-15T17:04:01.000Z

2021-12-31T06:09:35.000Z

samples/basic/executor/models/ietf/ietf-netconf-monitoring/nc-execute-ietf-netconf-monitoring-20-ydk.py

https-maxus-github-com/ydk-py-samples

1ad6cc2b798f358ff835df93d12924df308b85fc

[ "Apache-2.0" ]

15

2016-03-15T23:09:47.000Z

2020-08-13T12:13:18.000Z

samples/basic/executor/models/ietf/ietf-netconf-monitoring/nc-execute-ietf-netconf-monitoring-20-ydk.py

https-maxus-github-com/ydk-py-samples

1ad6cc2b798f358ff835df93d12924df308b85fc

[ "Apache-2.0" ]

87

2016-04-15T16:59:23.000Z

2021-09-18T18:05:47.000Z

#!/usr/bin/env python # # Copyright 2016 Cisco Systems, 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. # """ Execute RPC for model ietf-netconf-monitoring. usage: nc-execute-ietf-netconf-monitoring-20-ydk.py [-h] [-v] device positional arguments: device NETCONF device (ssh://user:password@host:port) optional arguments: -h, --help show this help message and exit -v, --verbose print debugging messages """ from argparse import ArgumentParser from urlparse import urlparse from ydk.services import ExecutorService from ydk.providers import NetconfServiceProvider from ydk.models.ietf import ietf_netconf_monitoring \ as ietf_netconf_monitoring import logging def prepare_get_schema(get_schema): """Add RPC input data to get_schema object.""" get_schema.input.identifier = "openconfig-bgp" if __name__ == "__main__": """Execute main program.""" parser = ArgumentParser() parser.add_argument("-v", "--verbose", help="print debugging messages", action="store_true") parser.add_argument("device", help="NETCONF device (ssh://user:password@host:port)") args = parser.parse_args() device = urlparse(args.device) # log debug messages if verbose argument specified if args.verbose: logger = logging.getLogger("ydk") logger.setLevel(logging.INFO) handler = logging.StreamHandler() formatter = logging.Formatter(("%(asctime)s - %(name)s - " "%(levelname)s - %(message)s")) handler.setFormatter(formatter) logger.addHandler(handler) # create NETCONF provider provider = NetconfServiceProvider(address=device.hostname, port=device.port, username=device.username, password=device.password, protocol=device.scheme) # create executor service executor = ExecutorService() get_schema = ietf_netconf_monitoring.GetSchema() # create object prepare_get_schema(get_schema) # add RPC input # execute RPC on NETCONF device print(executor.execute_rpc(provider, get_schema)) exit() # End of script

33.481928

78

0.666067

d061354971c3542ad5859e145a366e0886c3430a

21,752

py

Python

dabl/plot/utils.py

j1c/dabl

c70fef7ca276a9d2378d84183b1df2d56008b187

[ "BSD-3-Clause" ]

null

dabl/plot/utils.py

j1c/dabl

c70fef7ca276a9d2378d84183b1df2d56008b187

[ "BSD-3-Clause" ]

null

dabl/plot/utils.py

j1c/dabl

c70fef7ca276a9d2378d84183b1df2d56008b187

[ "BSD-3-Clause" ]

null

from warnings import warn from functools import reduce import itertools import numpy as np import pandas as pd import matplotlib.pyplot as plt from matplotlib.patches import Rectangle from seaborn.utils import despine # from sklearn.dummy import DummyClassifier # from sklearn.metrics import recall_score from sklearn.tree import DecisionTreeClassifier from sklearn.metrics import roc_curve from sklearn.model_selection import cross_val_score, StratifiedShuffleSplit from ..preprocessing import detect_types def find_pretty_grid(n_plots, max_cols=5): """Determine a good grid shape for subplots. Tries to find a way to arange n_plots many subplots on a grid in a way that fills as many grid-cells as possible, while keeping the number of rows low and the number of columns below max_cols. Parameters ---------- n_plots : int Number of plots to arrange. max_cols : int, default=5 Maximum number of columns. Returns ------- n_rows : int Number of rows in grid. n_cols : int Number of columns in grid. Examples -------- >>> find_pretty_grid(16, 5) (4, 4) >>> find_pretty_grid(11, 5) (3, 4) >>> find_pretty_grid(10, 5) (2, 5) """ # we could probably do something with prime numbers here # but looks like that becomes a combinatorial problem again? if n_plots % max_cols == 0: # perfect fit! # if max_cols is 6 do we prefer 6x1 over 3x2? return int(n_plots / max_cols), max_cols # min number of rows needed min_rows = int(np.ceil(n_plots / max_cols)) best_empty = max_cols best_cols = max_cols for cols in range(max_cols, min_rows - 1, -1): # we only allow getting narrower if we have more cols than rows remainder = (n_plots % cols) empty = cols - remainder if remainder != 0 else 0 if empty == 0: return int(n_plots / cols), cols if empty < best_empty: best_empty = empty best_cols = cols return int(np.ceil(n_plots / best_cols)), best_cols def plot_coefficients(coefficients, feature_names, n_top_features=10, classname=None, ax=None): """Visualize coefficients of a linear model. Parameters ---------- coefficients : nd-array, shape (n_features,) Model coefficients. feature_names : list or nd-array of strings, shape (n_features,) Feature names for labeling the coefficients. n_top_features : int, default=10 How many features to show. The function will show the largest (most positive) and smallest (most negative) n_top_features coefficients, for a total of 2 * n_top_features coefficients. """ coefficients = coefficients.squeeze() feature_names = np.asarray(feature_names) if coefficients.ndim > 1: # this is not a row or column vector raise ValueError("coefficients must be 1d array or column vector, got" " shape {}".format(coefficients.shape)) coefficients = coefficients.ravel() if len(coefficients) != len(feature_names): raise ValueError("Number of coefficients {} doesn't match number of" "feature names {}.".format(len(coefficients), len(feature_names))) # get coefficients with large absolute values coef = coefficients.ravel() mask = coef != 0 coef = coef[mask] feature_names = feature_names[mask] # FIXME this could be easier with pandas by sorting by a column interesting_coefficients = np.argsort(np.abs(coef))[-n_top_features:] new_inds = np.argsort(coef[interesting_coefficients]) interesting_coefficients = interesting_coefficients[new_inds] # plot them if ax is None: plt.figure(figsize=(len(interesting_coefficients), 5)) ax = plt.gca() colors = ['red' if c < 0 else 'blue' for c in coef[interesting_coefficients]] ax.bar(np.arange(len(interesting_coefficients)), coef[interesting_coefficients], color=colors) feature_names = np.array(feature_names) ax.set_xticks(np.arange(0, len(interesting_coefficients))) ax.set_xticklabels(feature_names[interesting_coefficients], rotation=60, ha="right") ax.set_ylabel("Coefficient magnitude") ax.set_xlabel("Feature") ax.set_title(classname) return feature_names[interesting_coefficients] def heatmap(values, xlabel, ylabel, xticklabels, yticklabels, cmap=None, vmin=None, vmax=None, ax=None, fmt="%0.2f", origin='lower'): if ax is None: ax = plt.gca() img = ax.pcolor(values, cmap=cmap, vmin=vmin, vmax=vmax) img.update_scalarmappable() ax.set_xlabel(xlabel) ax.set_ylabel(ylabel) ax.set_xticks(np.arange(len(xticklabels)) + .5) ax.set_yticks(np.arange(len(yticklabels)) + .5) ax.set_xticklabels(xticklabels) ax.set_yticklabels(yticklabels) ax.set_aspect(1) if origin == 'upper': ylim = ax.get_ylim() ax.set_ylim(ylim[::-1]) for p, color, value in zip(img.get_paths(), img.get_facecolors(), img.get_array()): x, y = p.vertices[:-2, :].mean(0) if np.mean(color[:3]) > 0.5: c = 'k' else: c = 'w' ax.text(x, y, fmt % value, color=c, ha="center", va="center") return img def _shortname(some_string, maxlen=20): """Shorten a string given a maximum length. Longer strings will be shortened and the rest replaced by ... Parameters ---------- some_string : string Input string to shorten maxlen : int, default=20 Returns ------- return_string : string Output string of size ``min(len(some_string), maxlen)``. """ some_string = str(some_string) if len(some_string) > maxlen: return some_string[:maxlen - 3] + "..." else: return some_string def mosaic_plot(data, rows, cols, vary_lightness=False, ax=None): """Create a mosaic plot from a dataframe. Right now only horizontal mosaic plots are supported, i.e. rows are prioritized over columns. Parameters ---------- data : pandas data frame Data to tabulate. rows : column specifier Column in data to tabulate across rows. cols : column specifier Column in data to use to subpartition rows. vary_lightness : bool, default=False Whether to vary lightness across categories. ax : matplotlib axes or None Axes to plot into. """ cont = pd.crosstab(data[cols], data[rows]) sort = np.argsort((cont / cont.sum()).iloc[0]) cont = cont.iloc[:, sort] if ax is None: ax = plt.gca() pos_y = 0 positions_y = [] n_cols = cont.shape[1] for i, col in enumerate(cont.columns): height = cont[col].sum() positions_y.append(pos_y + height / 2) pos_x = 0 for j, row in enumerate(cont[col]): width = row / height color = plt.cm.tab10(j) if vary_lightness: color = _lighten_color(color, (i + 1) / (n_cols + 1)) rect = Rectangle((pos_x, pos_y), width, height, edgecolor='k', facecolor=color) pos_x += width ax.add_patch(rect) pos_y += height ax.set_ylim(0, pos_y) ax.set_yticks(positions_y) ax.set_yticklabels(cont.columns) def _lighten_color(color, amount=0.5): """ Lightens the given color by multiplying (1-luminosity) by the given amount. Input can be matplotlib color string, hex string, or RGB tuple. https://stackoverflow.com/questions/37765197/darken-or-lighten-a-color-in-matplotlib Examples: >> lighten_color('g', 0.3) >> lighten_color('#F034A3', 0.6) >> lighten_color((.3,.55,.1), 0.5) """ import matplotlib.colors as mc import colorsys c = color amount += 0.5 c = colorsys.rgb_to_hls(*mc.to_rgb(c)) return colorsys.hls_to_rgb(c[0], 1 - amount * (1 - c[1]), c[2]) def _get_n_top(features, name): if features.shape[1] > 20: print("Showing only top 10 of {} {} features".format( features.shape[1], name)) # too many features, show just top 10 show_top = 10 else: show_top = features.shape[1] return show_top def _prune_categories(series, max_categories=10): series = series.astype('category') small_categories = series.value_counts()[max_categories:].index res = series.cat.remove_categories(small_categories) res = res.cat.add_categories(['dabl_other']).fillna("dabl_other") return res def _prune_category_make_X(X, col, target_col, max_categories=20): col_values = X[col] if col_values.nunique() > max_categories: # keep only top 10 categories if there are more than 20 col_values = _prune_categories(col_values, max_categories=min(10, max_categories)) X_new = X[[target_col]].copy() X_new[col] = col_values else: X_new = X.copy() X_new[col] = X_new[col].astype('category') return X_new def _fill_missing_categorical(X): # fill in missing values in categorical variables with new category # ensure we use strings for object columns and number for integers X = X.copy() max_value = X.max(numeric_only=True).max() for col in X.columns: if X[col].dtype == 'object': X[col].fillna("dabl_missing", inplace=True) else: X[col].fillna(max_value + 1, inplace=True) return X def _make_subplots(n_plots, max_cols=5, row_height=3): """Create a harmonious subplot grid. """ n_rows, n_cols = find_pretty_grid(n_plots, max_cols=max_cols) fig, axes = plt.subplots(n_rows, n_cols, figsize=(4 * n_cols, row_height * n_rows), constrained_layout=True) # we don't want ravel to fail, this is awkward! axes = np.atleast_2d(axes) return fig, axes def _check_X_target_col(X, target_col, types=None, type_hints=None, task=None): if types is None: types = detect_types(X, type_hints=type_hints) if (not isinstance(target_col, str) and hasattr(target_col, '__len__') and len(target_col) > 1): raise ValueError("target_col should be a column in X, " "got {}".format(target_col)) if target_col not in X.columns: raise ValueError("{} is not a valid column of X".format(target_col)) if X[target_col].nunique() < 2: raise ValueError("Less than two classes present, {}, need at least two" " for classification.".format(X.loc[0, target_col])) # FIXME we get target types here with detect_types, # but in the estimator with type_of_target if task == "classification" and not types.loc[target_col, 'categorical']: raise ValueError("Type for target column {} detected as {}," " need categorical for classification.".format( target_col, types.T.idxmax()[target_col])) if task == "regression" and (not types.loc[target_col, 'continuous']): raise ValueError("Type for target column {} detected as {}," " need continuous for regression.".format( target_col, types.T.idxmax()[target_col])) return types def _short_tick_names(ax): ax.set_yticklabels([_shortname(t.get_text(), maxlen=10) for t in ax.get_yticklabels()]) ax.set_xlabel(_shortname(ax.get_xlabel(), maxlen=20)) ax.set_ylabel(_shortname(ax.get_ylabel(), maxlen=20)) def _find_scatter_plots_classification(X, target, how_many=3, random_state=None): # input is continuous # look at all pairs of features, find most promising ones # dummy = DummyClassifier(strategy='prior').fit(X, target) # baseline_score = recall_score(target, dummy.predict(X), average='macro') scores = [] # converting to int here might save some time _, target = np.unique(target, return_inverse=True) # limit to 2000 training points for speed? train_size = min(2000, int(.9 * X.shape[0])) cv = StratifiedShuffleSplit(n_splits=3, train_size=train_size, random_state=random_state) for i, j in itertools.combinations(np.arange(X.shape[1]), 2): this_X = X[:, [i, j]] # assume this tree is simple enough so not be able to overfit in 2d # so we don't bother with train/test split tree = DecisionTreeClassifier(max_leaf_nodes=8) scores.append((i, j, np.mean(cross_val_score( tree, this_X, target, cv=cv, scoring='recall_macro')))) scores = pd.DataFrame(scores, columns=['feature0', 'feature1', 'score']) top = scores.sort_values(by='score').iloc[-how_many:][::-1] return top def discrete_scatter(x, y, c, unique_c=None, legend='first', clip_outliers=True, alpha='auto', s='auto', ax=None, **kwargs): """Scatter plot for categories. Creates a scatter plot for x and y grouped by c. Parameters ---------- x : array-like x coordinates to scatter y : array-like y coordinates to scatter c : array-like Grouping of samples (similar to hue in seaborn) legend : bool, or "first", default="first" Whether to create a legend. "first" mean only the first one in a given gridspec. scatter_alpha : float, default='auto' Alpha values for scatter plots. 'auto' is dirty hacks. scatter_size : float, default='auto'. Marker size for scatter plots. 'auto' is dirty hacks. ax : matplotlib axes, default=None Axes to plot into kwargs : Passed through to plt.scatter """ alpha = _get_scatter_alpha(alpha, x) s = _get_scatter_size(s, x) if ax is None: ax = plt.gca() if legend == "first": legend = (ax.get_geometry()[2] == 1) if unique_c is None: unique_c = np.unique(c) for i in unique_c: mask = c == i ax.scatter(x[mask], y[mask], label=i, s=s, alpha=alpha, **kwargs) if clip_outliers: x_low, x_high = _inlier_range(x) y_low, y_high = _inlier_range(y) xlims = ax.get_xlim() ylims = ax.get_ylim() ax.set_xlim(max(x_low, xlims[0]), min(x_high, xlims[1])) ax.set_ylim(max(y_low, ylims[0]), min(y_high, ylims[1])) if legend: props = {} if len(unique_c) > 15: props['size'] = 6 legend = ax.legend(prop=props) for handle in legend.legendHandles: handle.set_alpha(1) handle.set_sizes((100,)) def class_hists(data, column, target, bins="auto", ax=None, legend=False, scale_separately=True): """Grouped univariate histograms. Parameters ---------- data : pandas DataFrame Input data to plot column : column specifier Column in the data to compute histograms over (must be continuous). target : column specifier Target column in data, must be categorical. bins : string, int or array-like Number of bins, 'auto' or bin edges. Passed to np.histogram_bin_edges. We always show at least 5 bins for now. ax : matplotlib axes Axes to plot into legend : boolean, default=False Whether to create a legend. scale_separately : boolean, default=True Whether to scale each class separately. Examples -------- >>> from dabl.datasets import load_adult >>> data = load_adult() >>> class_hists(data, "age", "gender", legend=True) """ col_data = data[column].dropna() if ax is None: ax = plt.gca() if col_data.nunique() > 10: ordinal = False # histograms bin_edges = np.histogram_bin_edges(col_data, bins=bins) if len(bin_edges) > 30: bin_edges = np.histogram_bin_edges(col_data, bins=30) counts = {} for name, group in data.groupby(target)[column]: this_counts, _ = np.histogram(group, bins=bin_edges) counts[name] = this_counts counts = pd.DataFrame(counts) else: ordinal = True # ordinal data, count distinct values counts = data.groupby(target)[column].value_counts().unstack(target) if scale_separately: # normalize by maximum counts = counts / counts.max() bottom = counts.max().max() * 1.1 for i, name in enumerate(counts.columns): if ordinal: ax.bar(range(counts.shape[0]), counts[name], width=.9, bottom=bottom * i, tick_label=counts.index, linewidth=2, edgecolor='k') xmin, xmax = 0 - .5, counts.shape[0] - .5 else: ax.bar(bin_edges[:-1], counts[name], bottom=bottom * i, label=name, align='edge', width=(bin_edges[1] - bin_edges[0]) * .9) xmin, xmax = bin_edges[0], bin_edges[-1] ax.hlines(bottom * i, xmin=xmin, xmax=xmax, linewidth=1) if legend: ax.legend() ax.set_yticks(()) ax.set_xlabel(column) return ax def pairplot(data, target_col, columns=None, scatter_alpha='auto', scatter_size='auto'): """Pairplot (scattermatrix) Because there's already too many implementations of this. This is meant for classification only. This is very bare-bones right now :-/ Parameters ---------- data : pandas dataframe Input data target_col : column specifier Target column in data. columns : column specifiers, default=None. Columns in data to include. None means all. scatter_alpha : float, default='auto' Alpha values for scatter plots. 'auto' is dirty hacks. scatter_size : float, default='auto'. Marker size for scatter plots. 'auto' is dirty hacks. """ if columns is None: columns = data.columns.drop(target_col) n_features = len(columns) fig, axes = plt.subplots(n_features, n_features, figsize=(n_features * 3, n_features * 3)) axes = np.atleast_2d(axes) for ax, (i, j) in zip(axes.ravel(), itertools.product(range(n_features), repeat=2)): legend = i == 0 and j == n_features - 1 if i == j: class_hists(data, columns[i], target_col, ax=ax.twinx()) else: discrete_scatter(data[columns[j]], data[columns[i]], c=data[target_col], legend=legend, ax=ax, alpha=scatter_alpha, s=scatter_size) if j == 0: ax.set_ylabel(columns[i]) else: ax.set_ylabel("") ax.set_yticklabels(()) if i == n_features - 1: ax.set_xlabel(columns[j]) else: ax.set_xlabel("") ax.set_xticklabels(()) despine(fig) if n_features > 1: axes[0, 0].set_yticks(axes[0, 1].get_yticks()) axes[0, 0].set_ylim(axes[0, 1].get_ylim()) return axes def _inlier_range(series): low = np.nanquantile(series, 0.01) high = np.nanquantile(series, 0.99) assert low <= high # the two is a complete hack inner_range = (high - low) / 2 return low - inner_range, high + inner_range def _find_inliers(series): low, high = _inlier_range(series) mask = series.between(low, high) mask = mask | series.isna() dropped = len(mask) - mask.sum() if dropped > 0: warn("Dropped {} outliers in column {}.".format( int(dropped), series.name), UserWarning) return mask def _clean_outliers(data): def _find_outliers_series(series): series = series.dropna() low = series.quantile(0.01) high = series.quantile(0.99) # the two is a complete hack inner_range = (high - low) / 2 return series.between(low - inner_range, high + inner_range) mask = data.apply(_find_outliers_series) mask = mask.apply(lambda x: reduce(np.logical_and, x), axis=1).fillna(True) dropped = len(mask) - mask.sum() if dropped > 0: warn("Dropped {} outliers.".format(int(dropped)), UserWarning) return mask return None def _get_scatter_alpha(scatter_alpha, x): if scatter_alpha != "auto": return scatter_alpha if x.shape[0] < 100: return .9 elif x.shape[0] < 1000: return .5 elif x.shape[0] < 10000: return .2 else: return .1 def _get_scatter_size(scatter_size, x): if scatter_size != "auto": return scatter_size if x.shape[0] < 100: return 30 elif x.shape[0] < 1000: return 30 elif x.shape[0] < 2000: return 10 elif x.shape[0] < 10000: return 2 else: return 1 def plot_multiclass_roc_curve(estimator, X_val, y_val): if len(estimator.classes_) < 3: raise ValueError("Only for multi-class") try: y_score = estimator.predict_proba(X_val) except AttributeError: y_score = estimator.decision_function(X_val) fig, axes = _make_subplots(len(estimator.classes_)) for i, (ax, c) in enumerate(zip(axes.ravel(), estimator.classes_)): fpr, tpr, _ = roc_curve(y_val == c, y_score[:, i]) ax.plot(fpr, tpr) ax.set_xlabel("False Positive Rate") ax.set_ylabel("True Positive Rate (recall)") ax.set_title("ROC curve for class {}".format(c))

34.363349

88

0.614426

c903650b451dbd241027420860a19244192fd8e9

1,233

py

Python

com.nast.email/src/main/resources/com/ur/urcap/mail/impl/daemon/MailDaemon.py

nagmik/URCap-EMail

fcf3fb269c06b4a8b66989bbf7a5b0c7b203d519

[ "Apache-2.0" ]

3

2020-01-05T14:59:49.000Z

2020-12-14T21:06:10.000Z

com.nast.email/src/main/resources/com/ur/urcap/mail/impl/daemon/MailDaemon.py

nagmik/URCap-EMail

fcf3fb269c06b4a8b66989bbf7a5b0c7b203d519

[ "Apache-2.0" ]

null

com.nast.email/src/main/resources/com/ur/urcap/mail/impl/daemon/MailDaemon.py

nagmik/URCap-EMail

fcf3fb269c06b4a8b66989bbf7a5b0c7b203d519

[ "Apache-2.0" ]

1

2020-01-20T21:20:18.000Z

#!/usr/bin/env python import xmlrpclib from SimpleXMLRPCServer import SimpleXMLRPCServer import string import smtplib from email.MIMEMultipart import MIMEMultipart from email.MIMEText import MIMEText # ***************************** # send email # ***************************** def sendMail( smtpHost, smtpPort, username, password, mailRecipient, mailFrom, subject, message ): msg = MIMEMultipart() msg['From'] = mailFrom msg['To'] = mailRecipient msg['Subject'] = subject body = message msg.attach(MIMEText(body, 'plain')) ## Connect to host try: server = smtplib.SMTP(smtpHost, smtpPort) except smtplib.socket.gaierror: return 400 ## Login try: server.login(username, password) except smtplib.SMTPAuthenticationError: server.quit() return 401 ## Send message try: text = msg.as_string() server.sendmail(mailFrom, mailRecipient, text) except smtplib.SMTPException: return 402 finally: server.quit() return 200 # ***************************** server = SimpleXMLRPCServer(("", 33015), allow_none=True) server.register_function(sendMail, "sendMail") server.serve_forever()

24.66

98

0.623682

5cb01068cee0b6d808f74931f393bf2882f44796

1,779

py

Python

step1_run_time_series_converter.py

M2LabOrg/WRF_little_r

8f46e733387db4c62f39426a03b6a03b3b406b0e

[ "Apache-2.0" ]

1

2021-09-14T06:41:02.000Z

step1_run_time_series_converter.py

M2LabOrg/WRF_little_r

8f46e733387db4c62f39426a03b6a03b3b406b0e

[ "Apache-2.0" ]

null

step1_run_time_series_converter.py

M2LabOrg/WRF_little_r

8f46e733387db4c62f39426a03b6a03b3b406b0e

[ "Apache-2.0" ]

null

#!/usr/bin/env python """ This script creates little_r formatted files to be used in WRF. They are part of the input files needed for observation nudging. The script makes use of the function time_series_to_little_r, which is a FORTRAN wrapper found in time_series_converter.py and record.py Wrapper sources: https://github.com/tommz9/python-little_r https://github.com/valcap/csv2little_r Note that: - You need to install the Python packages needed to run this script: $ pip install -r requirements.txt - After running this script, you need to convert it to the format needed by WRF - You do that by running: $ perl RT_fdda_reformat_obsnud.pl OUTPUT/obs:2021-04-14_02 $ perl RT_fdda_reformat_obsnud.pl OUTPUT/obs:2021-04-14_03 $ (and so on) - This will produce files with extension .obsnud, which you will concatenate (see example below) - You will also need to change the file name to OBS_DOMAIN101 for domain 1, and OBS_DOMAIN201 for domain 2, and so on, as described in the WRF Users' manual $ cat *.obsnud >> OBS_DOMAIN101 Adapted here by: Michel Mesquita, Ph.D. (July 2021) """ import pandas as pd from pandas.tseries.offsets import DateOffset from time_series_converter import time_series_to_little_r df = pd.read_csv('inputToyData.csv', sep=";") df.set_index(pd.to_datetime(df['datetime']), drop = False, inplace = True) df.index = df.index.tz_localize('GMT').tz_convert('Europe/Oslo') time_series_to_little_r( df.index, df['temperature'], 'Bergen', # location 60.3971, # latitude 5.3244, # longitude 40, # altitude 'temperature', # variable 'OUTPUT_STEP1/obs', # start of filename or path + start of filename convert_to_kelvin=True)

31.210526

82

0.717257

d0657c8c7475f2b5d7ccd2206cb4843366bd0d82

260

py

Python

arc/arc006/arc006a.py

c-yan/atcoder

940e49d576e6a2d734288fadaf368e486480a948

[ "MIT" ]

1

2019-08-21T00:49:34.000Z

arc/arc006/arc006a.py

c-yan/atcoder

940e49d576e6a2d734288fadaf368e486480a948

[ "MIT" ]

null

arc/arc006/arc006a.py

c-yan/atcoder

940e49d576e6a2d734288fadaf368e486480a948

[ "MIT" ]

null

E = set(input().split()) B = input() L = set(input().split()) t = E & L if len(t) == 6: print(1) elif len(t) == 5: if B in L: print(2) else: print(3) elif len(t) == 4: print(4) elif len(t) == 3: print(5) else: print(0)

13.684211

24

0.465385

e6362bc8dca85d6c909c76274c9275f3ace0d201

6,141

py

Python

buddy/migrations/0001_initial.py

gc-13/studybuddy

4488475eea7844adecb955d79d17687c4e0accda

[ "HPND", "MIT" ]

null

buddy/migrations/0001_initial.py

gc-13/studybuddy

4488475eea7844adecb955d79d17687c4e0accda

[ "HPND", "MIT" ]

null

buddy/migrations/0001_initial.py

gc-13/studybuddy

4488475eea7844adecb955d79d17687c4e0accda

[ "HPND", "MIT" ]

null

# Generated by Django 3.1 on 2020-11-13 16:55 from django.conf import settings import django.contrib.auth.models import django.contrib.auth.validators from django.db import migrations, models import django.db.models.deletion import django.utils.timezone class Migration(migrations.Migration): initial = True dependencies = [ ('auth', '0012_alter_user_first_name_max_length'), ] operations = [ migrations.CreateModel( name='User', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('password', models.CharField(max_length=128, verbose_name='password')), ('last_login', models.DateTimeField(blank=True, null=True, verbose_name='last login')), ('is_superuser', models.BooleanField(default=False, help_text='Designates that this user has all permissions without explicitly assigning them.', verbose_name='superuser status')), ('username', models.CharField(error_messages={'unique': 'A user with that username already exists.'}, help_text='Required. 150 characters or fewer. Letters, digits and @/./+/-/_ only.', max_length=150, unique=True, validators=[django.contrib.auth.validators.UnicodeUsernameValidator()], verbose_name='username')), ('first_name', models.CharField(blank=True, max_length=150, verbose_name='first name')), ('last_name', models.CharField(blank=True, max_length=150, verbose_name='last name')), ('email', models.EmailField(blank=True, max_length=254, verbose_name='email address')), ('is_staff', models.BooleanField(default=False, help_text='Designates whether the user can log into this admin site.', verbose_name='staff status')), ('is_active', models.BooleanField(default=True, help_text='Designates whether this user should be treated as active. Unselect this instead of deleting accounts.', verbose_name='active')), ('date_joined', models.DateTimeField(default=django.utils.timezone.now, verbose_name='date joined')), ('major', models.CharField(blank=True, max_length=60)), ('description', models.CharField(blank=True, max_length=140)), ('year', models.CharField(blank=True, max_length=10)), ('first', models.CharField(blank=True, max_length=100)), ('second', models.CharField(blank=True, max_length=100)), ('third', models.CharField(blank=True, max_length=100)), ('image', models.ImageField(blank=True, upload_to='profile_image')), ], options={ 'verbose_name': 'user', 'verbose_name_plural': 'users', 'abstract': False, }, managers=[ ('objects', django.contrib.auth.models.UserManager()), ], ), migrations.CreateModel( name='Course', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('subject', models.CharField(max_length=4)), ('catalog_number', models.CharField(max_length=4)), ('class_title', models.CharField(max_length=100)), ('instructor', models.CharField(max_length=40)), ], ), migrations.CreateModel( name='StudyRequest', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('title', models.CharField(max_length=100)), ('description', models.CharField(max_length=500)), ('assignment', models.CharField(blank=True, max_length=140)), ('current_size', models.PositiveIntegerField(default=1)), ('sizeOfGroup', models.PositiveIntegerField()), ('accepted', models.BooleanField(default=False)), ('hidden', models.BooleanField(default=False)), ('course', models.ForeignKey(default=20485, on_delete=django.db.models.deletion.CASCADE, to='buddy.course')), ('users', models.ManyToManyField(to=settings.AUTH_USER_MODEL)), ], ), migrations.CreateModel( name='StudyGroup', fields=[ ('groupID', models.AutoField(primary_key=True, serialize=False)), ('name', models.CharField(max_length=100)), ('groupme_id', models.PositiveIntegerField(blank=True, default=0)), ('groupme_shareurl', models.URLField(blank=True, default='')), ('current_size', models.PositiveIntegerField(default=2)), ('sizeOfGroup', models.PositiveIntegerField(default=2)), ('hidden', models.BooleanField(default=False)), ('course', models.ForeignKey(default=20485, on_delete=django.db.models.deletion.CASCADE, to='buddy.course')), ('studyrequest', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='buddy.studyrequest')), ('users', models.ManyToManyField(to=settings.AUTH_USER_MODEL)), ], ), migrations.AddField( model_name='user', name='courses', field=models.ManyToManyField(to='buddy.Course'), ), migrations.AddField( model_name='user', name='groups', field=models.ManyToManyField(blank=True, help_text='The groups this user belongs to. A user will get all permissions granted to each of their groups.', related_name='user_set', related_query_name='user', to='auth.Group', verbose_name='groups'), ), migrations.AddField( model_name='user', name='user_permissions', field=models.ManyToManyField(blank=True, help_text='Specific permissions for this user.', related_name='user_set', related_query_name='user', to='auth.Permission', verbose_name='user permissions'), ), ]

57.392523

329

0.617978

6208deefd49012e284c73519bc7ffe6ffbad0104

652

py

Python

contrib/python/pypodman/pypodman/lib/__init__.py

stevekuznetsov/libpod

af791f340cfc3f8134e1fe0e3b0a6d3597706277

[ "Apache-2.0" ]

null

contrib/python/pypodman/pypodman/lib/__init__.py

stevekuznetsov/libpod

af791f340cfc3f8134e1fe0e3b0a6d3597706277

[ "Apache-2.0" ]

null

contrib/python/pypodman/pypodman/lib/__init__.py

stevekuznetsov/libpod

af791f340cfc3f8134e1fe0e3b0a6d3597706277

[ "Apache-2.0" ]

null

"""Remote podman client support library.""" from pypodman.lib.action_base import AbstractActionBase from pypodman.lib.parser_actions import (BooleanAction, BooleanValidate, PathAction, PositiveIntAction, UnitAction) from pypodman.lib.podman_parser import PodmanArgumentParser from pypodman.lib.report import Report, ReportColumn # Silence pylint overlording... assert BooleanAction assert BooleanValidate assert PathAction assert PositiveIntAction assert UnitAction __all__ = [ 'AbstractActionBase', 'PodmanArgumentParser', 'Report', 'ReportColumn', ]

29.636364

72

0.710123

e999071b638aee46a8642b223ab112f55905a720

3,818

py

Python

linear_projection.py

evrimozmermer/self_supervised_learning_linear_projection

2cad8362c1d3be37e4ce5e94abf7f5e5db227cb9

[ "Apache-2.0" ]

1

2021-11-26T14:27:09.000Z

linear_projection.py

evrimozmermer/self_supervised_learning_linear_projection

2cad8362c1d3be37e4ce5e94abf7f5e5db227cb9

[ "Apache-2.0" ]

null

linear_projection.py

evrimozmermer/self_supervised_learning_linear_projection

2cad8362c1d3be37e4ce5e94abf7f5e5db227cb9

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- """ Created on Sat Oct 16 20:16:44 2021 @author: tekin.evrim.ozmermer """ import torchvision import torch from torch import nn from classifiers.MLP_ExactSolution import Model as mlpes class LinearProjection(nn.Module): def __init__(self, cfg): super().__init__() self.cfg = cfg if cfg.model == "resnet18": self.model = torchvision.models.resnet18(zero_init_residual=True)#pretrained=True)# elif cfg.model == "resnet34": self.model = torchvision.models.resnet34(zero_init_residual=True)#pretrained=True)# elif cfg.model == "resnet50": self.model = torchvision.models.resnet50(zero_init_residual=True)#pretrained=True)# elif cfg.model == "resnet101": self.model = torchvision.models.resnet101(zero_init_residual=True)#pretrained=True)# else: print("Model architecture is given wrong, default is being used\n DEFAULT: RESNET50") self.model = torchvision.models.resnet50(pretrained=True) self.model.gap = nn.AdaptiveAvgPool2d(1) self.model.gmp = nn.AdaptiveMaxPool2d(1) self.model.embedding = nn.Sequential(nn.Linear(self.model.fc.in_features, cfg.embedding_size, bias = False)) self.linear_projection = mlpes(cfg) def forward_conv_layers(self, x): x = self.model.conv1(x) x = self.model.bn1(x) x = self.model.relu(x) x = self.model.maxpool(x) x = self.model.layer1(x) x = self.model.layer2(x) x = self.model.layer3(x) x = self.model.layer4(x) return x def forward_pooling(self, x): avg_x = self.model.gap(x) max_x = self.model.gmp(x) return avg_x+max_x def flatten(self, x): return x.view(x.size(0), -1) def l2_norm(self, x): input_size = x.size() buffer = torch.pow(x, 2) normp = torch.sum(buffer, 1).add_(1e-12) norm = torch.sqrt(normp).detach() _output = torch.div(x, norm.view(-1, 1).expand_as(x)) output = _output.view(input_size) return output def criterion_negative(self, sims, alpha, mrg): shape = sims.shape[0] neg_exp_sum = torch.exp(alpha * (sims + mrg)) neg_term = torch.log(1 + neg_exp_sum).sum()/shape return neg_term def criterion_positive(self, sims, alpha, mrg): shape = sims.shape[0] pos_exp_sum = torch.exp(-alpha * (sims - mrg)) pos_term = torch.log(1 + pos_exp_sum).sum()/shape return pos_term def forward(self, x): if type(x) == tuple: x0 = self.forward_conv_layers(x[0]) x0 = self.forward_pooling(x0) x0 = self.flatten(x0) z0 = self.model.embedding(x0) x1 = self.forward_conv_layers(x[1]) x1 = self.forward_pooling(x1) x1 = self.flatten(x1) z1 = self.model.embedding(x1) # calculate loss self.linear_projection.create_collection(backbone = None, dl_coll = None, input_batch = z0) self.linear_projection.solve_exact() loss = self.linear_projection.calculate_loss(z1) return loss else: x = self.forward_conv_layers(x) x = self.forward_pooling(x) x = self.flatten(x) z = self.model.embedding(x) return z def off_diagonal(x): # return a flattened view of the off-diagonal elements of a square matrix n, m = x.shape assert n == m return x.flatten()[:-1].view(n - 1, n + 1)[:, 1:].flatten()

35.351852

97

0.57098

3b39bbfe59b4a940b81dac1981613e6c028361e3

2,876

py

Python

alipay/aop/api/domain/KoubeiRetailWmsDeliverypackageQueryModel.py

articuly/alipay-sdk-python-all

0259cd28eca0f219b97dac7f41c2458441d5e7a6

[ "Apache-2.0" ]

null

alipay/aop/api/domain/KoubeiRetailWmsDeliverypackageQueryModel.py

articuly/alipay-sdk-python-all

0259cd28eca0f219b97dac7f41c2458441d5e7a6

[ "Apache-2.0" ]

null

alipay/aop/api/domain/KoubeiRetailWmsDeliverypackageQueryModel.py

articuly/alipay-sdk-python-all

0259cd28eca0f219b97dac7f41c2458441d5e7a6

[ "Apache-2.0" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- import simplejson as json from alipay.aop.api.constant.ParamConstants import * from alipay.aop.api.domain.OperateContext import OperateContext class KoubeiRetailWmsDeliverypackageQueryModel(object): def __init__(self): self._express_code = None self._notice_order_id = None self._operate_context = None self._work_order_id = None @property def express_code(self): return self._express_code @express_code.setter def express_code(self, value): self._express_code = value @property def notice_order_id(self): return self._notice_order_id @notice_order_id.setter def notice_order_id(self, value): self._notice_order_id = value @property def operate_context(self): return self._operate_context @operate_context.setter def operate_context(self, value): if isinstance(value, OperateContext): self._operate_context = value else: self._operate_context = OperateContext.from_alipay_dict(value) @property def work_order_id(self): return self._work_order_id @work_order_id.setter def work_order_id(self, value): self._work_order_id = value def to_alipay_dict(self): params = dict() if self.express_code: if hasattr(self.express_code, 'to_alipay_dict'): params['express_code'] = self.express_code.to_alipay_dict() else: params['express_code'] = self.express_code if self.notice_order_id: if hasattr(self.notice_order_id, 'to_alipay_dict'): params['notice_order_id'] = self.notice_order_id.to_alipay_dict() else: params['notice_order_id'] = self.notice_order_id if self.operate_context: if hasattr(self.operate_context, 'to_alipay_dict'): params['operate_context'] = self.operate_context.to_alipay_dict() else: params['operate_context'] = self.operate_context if self.work_order_id: if hasattr(self.work_order_id, 'to_alipay_dict'): params['work_order_id'] = self.work_order_id.to_alipay_dict() else: params['work_order_id'] = self.work_order_id return params @staticmethod def from_alipay_dict(d): if not d: return None o = KoubeiRetailWmsDeliverypackageQueryModel() if 'express_code' in d: o.express_code = d['express_code'] if 'notice_order_id' in d: o.notice_order_id = d['notice_order_id'] if 'operate_context' in d: o.operate_context = d['operate_context'] if 'work_order_id' in d: o.work_order_id = d['work_order_id'] return o

31.955556

81

0.636648

b844f8a46b62ebdf685fb854ec92baa2163e6f77

6,358

py

Python

padmal/DataLogs/POC_Setup/2022-02-21:03-21-19/plot.py

CloudyPadmal/Phantom-Contiki

c1f0e53cb1aaaa946c36f2d1dc72499875c35f5b

[ "BSD-3-Clause" ]

1

2022-03-07T18:50:41.000Z

padmal/DataLogs/POC_Setup/2022-02-21:03-21-19/plot.py

CloudyPadmal/Phantom-Contiki

c1f0e53cb1aaaa946c36f2d1dc72499875c35f5b

[ "BSD-3-Clause" ]

null

padmal/DataLogs/POC_Setup/2022-02-21:03-21-19/plot.py

CloudyPadmal/Phantom-Contiki

c1f0e53cb1aaaa946c36f2d1dc72499875c35f5b

[ "BSD-3-Clause" ]

null

import matplotlib.pyplot as plt import numpy as np plt.rcParams["figure.figsize"] = (20, 8) POWER_L = 0 RATE_P = 50 PACKETS = 2500 MIN_RSSI = -100 MAX_RSSI = -10 BINS = [i * (PACKETS / 10) for i in range(11)] SCATTER = 5 L_WIDTH = 0.5 props = dict(boxstyle='round', facecolor='#cccccc', alpha=0.5) TX_NODE = '5a7a.b713.0074.1200' def extract_packet_data(filename): """ This method will take a file of packet readings as input and go through each line. If any line has the IP address defined above, it will fill in the points array with the corresponding RSSI value and another array with sequence number There will be four arrays returned at last, two with RSSI readings and two with seq. [INFO: EavesDr ] Received 0 from 0f2a.7d13.0074.1200 [RSSI: -60 | LQI: 107] """ file_node_lines = filename.readlines() node_points = [] node_seq = [] for line in file_node_lines: if TX_NODE in line: try: line_as_list = line.split(' ') rssi = int(line_as_list[-4]) seq = int(line_as_list[-8]) node_points.append(rssi) node_seq.append(seq) except: continue print("Parsing", filename.name) return node_points, node_seq ####################################################################################################################### # Files # ####################################################################################################################### Ev1 = open('Eaves-1.txt', 'r') Ev2 = open('Eaves-2.txt', 'r') Ev3 = open('Eaves-3.txt', 'r') Ev4 = open('Eaves-4.txt', 'r') Ph2 = open('Receive.txt', 'r') ####################################################################################################################### # Plots # ####################################################################################################################### f, ((ev1, ev2, ev3, ev4, pha), (fr1, fr2, fr3, fr4, fr5)) = plt.subplots(2, 5) ttl = 'RSSI Measurements {Packets: ' + str(PACKETS) + '; Power: ' + str(POWER_L) + ' dBm; Rate: ' + str(RATE_P) + \ ' ms; Bin: ' + str(int(PACKETS / 10)) + ' packets}' f.suptitle(ttl, fontweight='bold') (P1_E1, S_P1_E1) = extract_packet_data(Ev1) prr1 = 'PRR:' + str(round((len(P1_E1) / PACKETS), 3) * 100)[:4] + '%' ev1.scatter(S_P1_E1, P1_E1, s=SCATTER, label='from node 1') ev1.plot([np.mean(P1_E1) for _ in range(PACKETS)], label='node 1 mean', linewidth=L_WIDTH) ev1.set_xlim(0, PACKETS) ev1.set_ylim(MIN_RSSI, MAX_RSSI) ev1.set_title('Eaves 01') ev1.set_xlabel('Sequence number') ev1.set_ylabel('RSSI (dBm)') ev1.text(0.3, 0.95, prr1, transform=ev1.transAxes, fontsize=8, verticalalignment='center', bbox=props) print("EV 1 Ready") (P1_E2, S_P1_E2) = extract_packet_data(Ev2) prr2 = 'PRR:' + str(round((len(P1_E2) / PACKETS), 3) * 100)[:4] + '%' ev2.scatter(S_P1_E2, P1_E2, s=SCATTER, label='from node 1') ev2.plot([np.mean(P1_E2) for _ in range(PACKETS)], label='node 1 mean', linewidth=L_WIDTH) ev2.set_xlim(0, PACKETS) ev2.set_ylim(MIN_RSSI, MAX_RSSI) ev2.set_title('Eaves 02') ev2.set_xlabel('Sequence number') ev2.text(0.4, 0.95, prr2, transform=ev2.transAxes, fontsize=8, verticalalignment='center', bbox=props) print("EV 2 Ready") (P1_E3, S_P1_E3) = extract_packet_data(Ev3) prr3 = 'PRR:' + str(round((len(P1_E3) / PACKETS), 3) * 100)[:4] + '%' ev3.scatter(S_P1_E3, P1_E3, s=SCATTER, label='from node 1') ev3.plot([np.mean(P1_E3) for _ in range(PACKETS)], label='node 1 mean', linewidth=L_WIDTH) ev3.set_xlim(0, PACKETS) ev3.set_ylim(MIN_RSSI, MAX_RSSI) ev3.set_title('Eaves 03') ev3.set_xlabel('Sequence number') ev3.text(0.4, 0.95, prr3, transform=ev3.transAxes, fontsize=8, verticalalignment='center', bbox=props) print("EV 3 Ready") (P1_E4, S_P1_E4) = extract_packet_data(Ev4) prr4 = 'PRR:' + str(round((len(P1_E4) / PACKETS), 3) * 100)[:4] + '%' ev4.scatter(S_P1_E4, P1_E4, s=SCATTER, label='from node 1') ev4.plot([np.mean(P1_E4) for _ in range(PACKETS)], label='node 1 mean', linewidth=L_WIDTH) ev4.set_xlim(0, PACKETS) ev4.set_ylim(MIN_RSSI, MAX_RSSI) ev4.set_title('Eaves 04') ev4.set_xlabel('Sequence number') ev4.text(0.4, 0.95, prr4, transform=ev4.transAxes, fontsize=8, verticalalignment='center', bbox=props) print("EV 4 Ready") (P1_P2, S_P1_P2) = extract_packet_data(Ph2) prr5 = 'PRR:' + str(round((len(P1_P2) / PACKETS), 3) * 100)[:4] + '%' pha.scatter(S_P1_P2, P1_P2, s=SCATTER, label='from node 1') pha.plot([np.mean(P1_P2) for _ in range(PACKETS)], label='node 1 mean', linewidth=L_WIDTH) pha.set_xlim(0, PACKETS) pha.set_ylim(MIN_RSSI, MAX_RSSI) pha.set_title('In-body') pha.set_xlabel('Sequence number') pha.text(0.4, 0.95, prr5, transform=pha.transAxes, fontsize=8, verticalalignment='center', bbox=props) print("RX Ready") ####################################################################################################################### # Fast RSSI Sampling # ####################################################################################################################### fr1.hist(S_P1_E1, BINS, label='count', alpha=0.7, rwidth=0.9) fr1.set_xlabel('Sequence Range') fr1.set_ylabel('Count') fr2.hist(S_P1_E2, BINS, label='count', alpha=0.7, rwidth=0.9) fr2.set_xlabel('Reading instance') fr3.hist(S_P1_E3, BINS, label='count', alpha=0.7, rwidth=0.9) fr3.set_xlabel('Reading instance') fr4.hist(S_P1_E4, BINS, label='count', alpha=0.7, rwidth=0.9) fr4.set_xlabel('Reading instance') fr5.hist(S_P1_P2, BINS, label='count', alpha=0.7, rwidth=0.9) fr5.set_xlabel('Reading instance') ev1.grid(True, axis='y', alpha=0.35) ev2.grid(True, axis='y', alpha=0.35) ev3.grid(True, axis='y', alpha=0.35) ev4.grid(True, axis='y', alpha=0.35) pha.grid(True, axis='y', alpha=0.35) fr1.grid(True, axis='y', alpha=0.35) fr2.grid(True, axis='y', alpha=0.35) fr3.grid(True, axis='y', alpha=0.35) fr4.grid(True, axis='y', alpha=0.35) fr5.grid(True, axis='y', alpha=0.35) plt.savefig('results.png', dpi=300) plt.show()

40.496815

119

0.56134

ae76db1762cd23ecd5394f05cf6db126f6dbc993

4,411

py

Python

posts/migrations/0004_auto_20211108_0210.py

GrimJ0/yatube

7c6919bdfd25130d853d0d3ffdb9a63f32660c73

[ "BSD-3-Clause" ]

1

2021-11-09T21:29:16.000Z

posts/migrations/0004_auto_20211108_0210.py

GrimJ0/yatube

7c6919bdfd25130d853d0d3ffdb9a63f32660c73

[ "BSD-3-Clause" ]

null

posts/migrations/0004_auto_20211108_0210.py

GrimJ0/yatube

7c6919bdfd25130d853d0d3ffdb9a63f32660c73

[ "BSD-3-Clause" ]

null

# Generated by Django 2.2.9 on 2021-11-07 23:10 from django.conf import settings from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('posts', '0003_auto_20211107_2325'), ] operations = [ migrations.AlterModelOptions( name='comment', options={'ordering': ('-created',), 'verbose_name': 'Комментарий', 'verbose_name_plural': 'Комментарии'}, ), migrations.AlterModelOptions( name='follow', options={'verbose_name': 'Подписчик', 'verbose_name_plural': 'Подписчики'}, ), migrations.AlterModelOptions( name='group', options={'verbose_name': 'Группа', 'verbose_name_plural': 'Группы'}, ), migrations.AlterModelOptions( name='post', options={'ordering': ('-pub_date',), 'verbose_name': 'Пост', 'verbose_name_plural': 'Посты'}, ), migrations.AlterField( model_name='comment', name='author', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='comments', to=settings.AUTH_USER_MODEL, verbose_name='Автор'), ), migrations.AlterField( model_name='comment', name='created', field=models.DateTimeField(auto_now_add=True, verbose_name='Дата публикации'), ), migrations.AlterField( model_name='comment', name='post', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='comments', to='posts.Post', verbose_name='Пост'), ), migrations.AlterField( model_name='comment', name='text', field=models.TextField(help_text='Введите ваш комментарий', verbose_name='Комментария'), ), migrations.AlterField( model_name='follow', name='author', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='following', to=settings.AUTH_USER_MODEL, verbose_name='Автор'), ), migrations.AlterField( model_name='follow', name='user', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='follower', to=settings.AUTH_USER_MODEL, verbose_name='Подписчик'), ), migrations.AlterField( model_name='group', name='description', field=models.TextField(help_text='Опишите группу', verbose_name='Описание'), ), migrations.AlterField( model_name='group', name='slug', field=models.SlugField(help_text='Задайте уникальный адрес сообщества', unique=True, verbose_name='Адрес'), ), migrations.AlterField( model_name='group', name='title', field=models.CharField(max_length=100, verbose_name='Название сообщества'), ), migrations.AlterField( model_name='post', name='author', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='posts', to=settings.AUTH_USER_MODEL, verbose_name='Автор'), ), migrations.AlterField( model_name='post', name='group', field=models.ForeignKey(blank=True, help_text='Выберите группу', null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='posts', to='posts.Group', verbose_name='Сообщество'), ), migrations.AlterField( model_name='post', name='image', field=models.ImageField(blank=True, help_text='Добавьте изображение к посту', null=True, upload_to='posts/', verbose_name='Изображение'), ), migrations.AlterField( model_name='post', name='pub_date', field=models.DateTimeField(auto_now_add=True, verbose_name='Дата публикации'), ), migrations.AlterField( model_name='post', name='text', field=models.TextField(help_text='Введите текст вашего поста', verbose_name='Текст поста'), ), migrations.AlterField( model_name='post', name='title', field=models.CharField(max_length=100, unique=True, verbose_name='Заголовок'), ), ]

41.224299

201

0.607345

3d3ac9456e88a1e83999d907de2204c66088cd8a

1,080

py

Python

exercise_2020_05/test_data_wrapper.py

yorkshire-geek/advent_of_code_2020

6868f89849ab7347689136b010020f8cd90f2d93

[ "Apache-2.0" ]

null

exercise_2020_05/test_data_wrapper.py

yorkshire-geek/advent_of_code_2020

6868f89849ab7347689136b010020f8cd90f2d93

[ "Apache-2.0" ]

null

exercise_2020_05/test_data_wrapper.py

yorkshire-geek/advent_of_code_2020

6868f89849ab7347689136b010020f8cd90f2d93

[ "Apache-2.0" ]

null

import unittest from .exercise_5 import DataWrapper class MyTestCase(unittest.TestCase): data_wrapper = DataWrapper("FBFBBFFRLR") def test_row_data(self): self.assertEqual("FBFBBFF", self.data_wrapper.get_row_str()) def test_seat_data(self): self.assertEqual("RLR", self.data_wrapper.get_column_str()) def test_row_binary(self): self.assertEqual("0101100", self.data_wrapper.get_row_binary()) def test_column_binary(self): self.assertEqual("0101100", self.data_wrapper.get_row_binary()) def test_row(self): self.assertEqual(44, self.data_wrapper.get_row()) def test_column(self): self.assertEqual(5, self.data_wrapper.get_column()) def test_id(self): self.assertEqual(357, self.data_wrapper.get_id()) def test_one_two_three(self): self.assertEqual(567, DataWrapper("BFFFBBFRRR").get_id()) self.assertEqual(119, DataWrapper("FFFBBBFRRR").get_id()) self.assertEqual(820, DataWrapper("BBFFBBFRLL").get_id()) if __name__ == '__main__': unittest.main()

29.189189

71

0.700926

23dfa9774dd013e4933c2bc360661be0a8433e5d

1,527

py

Python

openstack/tests/functional/network/v2/test_quota.py

NeCTAR-RC/openstacksdk

60a24f6c4717a1f9a0e545c9a07e68afaedc5a27

[ "Apache-2.0" ]

99

2018-03-28T15:41:45.000Z

2022-01-23T17:22:13.000Z

openstack/tests/functional/network/v2/test_quota.py

NeCTAR-RC/openstacksdk

60a24f6c4717a1f9a0e545c9a07e68afaedc5a27

[ "Apache-2.0" ]

5

2018-05-25T16:54:23.000Z

2021-11-21T02:27:16.000Z

openstack/tests/functional/network/v2/test_quota.py

NeCTAR-RC/openstacksdk

60a24f6c4717a1f9a0e545c9a07e68afaedc5a27

[ "Apache-2.0" ]

104

2018-04-06T14:33:54.000Z

2022-03-01T01:58:09.000Z

# 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. from openstack.tests.functional import base class TestQuota(base.BaseFunctionalTest): def test_list(self): for qot in self.conn.network.quotas(): self.assertIsNotNone(qot.project_id) self.assertIsNotNone(qot.networks) def test_list_details(self): expected_keys = ['limit', 'used', 'reserved'] project_id = self.conn.session.get_project_id() quota_details = self.conn.network.get_quota(project_id, details=True) for details in quota_details._body.attributes.values(): for expected_key in expected_keys: self.assertTrue(expected_key in details.keys()) def test_set(self): attrs = {'networks': 123456789} for project_quota in self.conn.network.quotas(): self.conn.network.update_quota(project_quota, **attrs) new_quota = self.conn.network.get_quota(project_quota.project_id) self.assertEqual(123456789, new_quota.networks)

41.27027

77

0.707924

147b9a4a68b6d401d59161005d7af4109ea5f30d

6,204

py

Python

vendor-local/lib/python/celery/worker/bootsteps.py

Mozilla-GitHub-Standards/6f0d85288b5b0ef8beecb60345173dc14c98e40f48e1307a444ab1e08231e695

bf6a382913901ad193d907f022086931df0de8c4

[ "BSD-3-Clause" ]

1

2015-07-13T03:29:04.000Z

vendor-local/lib/python/celery/worker/bootsteps.py

Mozilla-GitHub-Standards/6f0d85288b5b0ef8beecb60345173dc14c98e40f48e1307a444ab1e08231e695

bf6a382913901ad193d907f022086931df0de8c4

[ "BSD-3-Clause" ]

2

2015-03-03T23:02:19.000Z

2019-03-30T04:45:51.000Z

vendor-local/lib/python/celery/worker/bootsteps.py

Mozilla-GitHub-Standards/6f0d85288b5b0ef8beecb60345173dc14c98e40f48e1307a444ab1e08231e695

bf6a382913901ad193d907f022086931df0de8c4

[ "BSD-3-Clause" ]

2

2016-04-15T11:43:05.000Z

2016-04-15T11:43:15.000Z

# -*- coding: utf-8 -*- """ celery.worker.bootsteps ~~~~~~~~~~~~~~~~~~~~~~~ The boot-step components. """ from __future__ import absolute_import from collections import defaultdict from importlib import import_module from celery.datastructures import DependencyGraph from celery.utils.imports import instantiate from celery.utils.log import get_logger logger = get_logger(__name__) class Namespace(object): """A namespace containing components. Every component must belong to a namespace. When component classes are created they are added to the mapping of unclaimed components. The components will be claimed when the namespace they belong to is created. :keyword name: Set the name of this namespace. :keyword app: Set the Celery app for this namespace. """ name = None _unclaimed = defaultdict(dict) _started_count = 0 def __init__(self, name=None, app=None): self.app = app self.name = name or self.name self.services = [] def modules(self): """Subclasses can override this to return a list of modules to import before components are claimed.""" return [] def load_modules(self): """Will load the component modules this namespace depends on.""" for m in self.modules(): self.import_module(m) def apply(self, parent, **kwargs): """Apply the components in this namespace to an object. This will apply the ``__init__`` and ``include`` methods of each components with the object as argument. For ``StartStopComponents`` the services created will also be added the the objects ``components`` attribute. """ self._debug('Loading modules.') self.load_modules() self._debug('Claiming components.') self.components = self._claim() self._debug('Building boot step graph.') self.boot_steps = [self.bind_component(name, parent, **kwargs) for name in self._finalize_boot_steps()] self._debug( 'New boot order: {%s}', ', '.join(c.name for c in self.boot_steps), ) for component in self.boot_steps: component.include(parent) return self def bind_component(self, name, parent, **kwargs): """Bind component to parent object and this namespace.""" comp = self[name](parent, **kwargs) comp.namespace = self return comp def import_module(self, module): return import_module(module) def __getitem__(self, name): return self.components[name] def _find_last(self): for C in self.components.itervalues(): if C.last: return C def _finalize_boot_steps(self): G = self.graph = DependencyGraph( (C.name, C.requires) for C in self.components.itervalues()) last = self._find_last() if last: for obj in G: if obj != last.name: G.add_edge(last.name, obj) return G.topsort() def _claim(self): return self._unclaimed[self.name] def _debug(self, msg, *args): return logger.debug('[%s] ' + msg, *(self.name.capitalize(), ) + args) class ComponentType(type): """Metaclass for components.""" def __new__(cls, name, bases, attrs): abstract = attrs.pop('abstract', False) if not abstract: try: cname = attrs['name'] except KeyError: raise NotImplementedError('Components must be named') namespace = attrs.get('namespace', None) if not namespace: attrs['namespace'], _, attrs['name'] = cname.partition('.') cls = super(ComponentType, cls).__new__(cls, name, bases, attrs) if not abstract: Namespace._unclaimed[cls.namespace][cls.name] = cls return cls class Component(object): """A component. The :meth:`__init__` method is called when the component is bound to a parent object, and can as such be used to initialize attributes in the parent object at parent instantiation-time. """ __metaclass__ = ComponentType #: The name of the component, or the namespace #: and the name of the component separated by dot. name = None #: List of component names this component depends on. #: Note that the dependencies must be in the same namespace. requires = () #: can be used to specify the namespace, #: if the name does not include it. namespace = None #: if set the component will not be registered, #: but can be used as a component base class. abstract = True #: Optional obj created by the :meth:`create` method. #: This is used by StartStopComponents to keep the #: original service object. obj = None #: This flag is reserved for the workers Consumer, #: since it is required to always be started last. #: There can only be one object marked with lsat #: in every namespace. last = False #: This provides the default for :meth:`include_if`. enabled = True def __init__(self, parent, **kwargs): pass def create(self, parent): """Create the component.""" pass def include_if(self, parent): """An optional predicate that decided whether this component should be created.""" return self.enabled def instantiate(self, qualname, *args, **kwargs): return instantiate(qualname, *args, **kwargs) def include(self, parent): if self.include_if(parent): self.obj = self.create(parent) return True class StartStopComponent(Component): abstract = True terminable = False def start(self): return self.obj.start() def stop(self): return self.obj.stop() def terminate(self): if self.terminable: return self.obj.terminate() return self.obj.stop() def include(self, parent): if super(StartStopComponent, self).include(parent): parent.components.append(self.obj)

29.264151

79

0.620729

9a477ec2dfb5268c91fe53bc2f477afa12b61727

1,543

py

Python

src/helper/paths_generator.py

amillert/pic2story

efa0c7c966392b4efb88ae370d8eb78cd2ab062b

[ "MIT" ]

3

2020-09-27T21:25:01.000Z

2021-02-14T14:12:04.000Z

src/helper/paths_generator.py

amillert/pic2story

efa0c7c966392b4efb88ae370d8eb78cd2ab062b

[ "MIT" ]

15

2020-09-26T10:52:56.000Z

2020-11-15T08:19:12.000Z

src/helper/paths_generator.py

amillert/pic2story

efa0c7c966392b4efb88ae370d8eb78cd2ab062b

[ "MIT" ]

null

""" Module providing some helper functions """ import os # TODO: file needs general refactor def extract(path): """ Function for extracting path or paths if directory :param path: str :return: str / list[str] # TODO: fix """ if os.path.isdir(path): res = [] contents = os.listdir(path) for cont in contents: res.append(extract(os.path.join(path, cont))) return res return path def generate_abs_for_dir(dir_path, abs_paths): """ Function for generating absolute paths in the directory :param dir_path: str :param abs_paths: list[str] :return: """ for path in os.listdir(dir_path): if "-" not in path: joined = os.path.join(dir_path, path) if os.path.isdir(joined): abs_paths.extend(extract(joined)) else: abs_paths.append(extract(joined)) return abs_paths def generate_absolute_paths(paths): """ Function for generating paths :param paths: list[str] :return: list[list[str]] ? """ abs_paths = [] for path in paths: abs_path = os.path.abspath(path) if os.path.isdir(abs_path): abs_paths = generate_abs_for_dir(abs_path, abs_paths) else: abs_paths.append(abs_path) return abs_paths def parent_path(path): """ Function for easier access to the parent directory :param path: str :return: str """ return os.path.abspath(os.path.join(path, os.pardir))

22.691176

65

0.605314

51c817e9b4cb7e38af78f4d52835eda6f1b496cf

12,028

py

Python

mars/dataframe/base/astype.py

humaohai/mars

11373f64c3039d424f9276e610ae5ad108ea0eb1

[ "Apache-2.0" ]

1

2020-06-25T13:51:16.000Z

mars/dataframe/base/astype.py

humaohai/mars

11373f64c3039d424f9276e610ae5ad108ea0eb1

[ "Apache-2.0" ]

null

mars/dataframe/base/astype.py

humaohai/mars

11373f64c3039d424f9276e610ae5ad108ea0eb1

[ "Apache-2.0" ]

null

# Copyright 1999-2020 Alibaba Group Holding Ltd. # # 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 numpy as np import pandas as pd from pandas.api.types import CategoricalDtype from ... import opcodes as OperandDef from ...serialize import AnyField, StringField, ListField from ...utils import recursive_tile from ...tensor.base import sort from ..utils import build_empty_df, build_empty_series from ..core import SERIES_TYPE from ..operands import DataFrameOperand, DataFrameOperandMixin, ObjectType class DataFrameAstype(DataFrameOperand, DataFrameOperandMixin): _op_type_ = OperandDef.ASTYPE _dtype_values = AnyField('dtype_values') _errors = StringField('errors') _category_cols = ListField('category_cols') def __init__(self, dtype_values=None, copy=None, errors=None, category_cols=None, object_type=None, **kw): super().__init__(_dtype_values=dtype_values, _errors=errors, _category_cols=category_cols, _object_type=object_type, **kw) @property def dtype_values(self): return self._dtype_values @property def errors(self): return self._errors @property def category_cols(self): return self._category_cols @classmethod def _tile_one_chunk(cls, op): c = op.inputs[0].chunks[0] chunk_op = op.copy().reset_key() chunk_params = op.outputs[0].params.copy() chunk_params['index'] = c.index out_chunks = [chunk_op.new_chunk([c], **chunk_params)] new_op = op.copy() return new_op.new_tileables(op.inputs, nsplits=op.inputs[0].nsplits, chunks=out_chunks, **op.outputs[0].params.copy()) @classmethod def _tile_series(cls, op): in_series = op.inputs[0] out = op.outputs[0] unique_chunk = None if op.dtype_values == 'category' and isinstance(op.dtype_values, str): unique_chunk = recursive_tile(sort(in_series.unique())).chunks[0] chunks = [] for c in in_series.chunks: chunk_op = op.copy().reset_key() params = c.params.copy() params['dtype'] = out.dtype if unique_chunk is not None: chunk_op._category_cols = [in_series.name] new_chunk = chunk_op.new_chunk([c, unique_chunk], **params) else: new_chunk = chunk_op.new_chunk([c], **params) chunks.append(new_chunk) new_op = op.copy() return new_op.new_seriess(op.inputs, nsplits=in_series.nsplits, chunks=chunks, **out.params.copy()) @classmethod def _tile_dataframe(cls, op): in_df = op.inputs[0] out = op.outputs[0] cum_nsplits = np.cumsum((0,) + in_df.nsplits[1]) out_chunks = [] if op.dtype_values == 'category': # all columns need unique values for c in in_df.chunks: chunk_op = op.copy().reset_key() params = c.params.copy() dtypes = out.dtypes[cum_nsplits[c.index[1]]: cum_nsplits[c.index[1] + 1]] params['dtypes'] = dtypes chunk_op._category_cols = list(c.columns_value.to_pandas()) unique_chunks = [] for col in c.columns_value.to_pandas(): unique_chunks.append(recursive_tile(sort(in_df[col].unique())).chunks[0]) new_chunk = chunk_op.new_chunk([c] + unique_chunks, **params) out_chunks.append(new_chunk) elif isinstance(op.dtype_values, dict) and 'category' in op.dtype_values.values(): # some columns' types are category category_cols = [c for c, v in op.dtype_values.items() if isinstance(v, str) and v == 'category'] unique_chunks = dict((col, recursive_tile(sort(in_df[col].unique())).chunks[0]) for col in category_cols) for c in in_df.chunks: chunk_op = op.copy().reset_key() params = c.params.copy() dtypes = out.dtypes[cum_nsplits[c.index[1]]: cum_nsplits[c.index[1] + 1]] params['dtypes'] = dtypes chunk_category_cols = [] chunk_unique_chunks = [] for col in c.columns_value.to_pandas(): if col in category_cols: chunk_category_cols.append(col) chunk_unique_chunks.append(unique_chunks[col]) chunk_op._category_cols = chunk_category_cols new_chunk = chunk_op.new_chunk([c] + chunk_unique_chunks, **params) out_chunks.append(new_chunk) else: for c in in_df.chunks: chunk_op = op.copy().reset_key() params = c.params.copy() dtypes = out.dtypes[cum_nsplits[c.index[1]]: cum_nsplits[c.index[1] + 1]] params['dtypes'] = dtypes new_chunk = chunk_op.new_chunk([c], **params) out_chunks.append(new_chunk) new_op = op.copy() return new_op.new_dataframes(op.inputs, nsplits=in_df.nsplits, chunks=out_chunks, **out.params.copy()) @classmethod def tile(cls, op): if len(op.inputs[0].chunks) == 1: return cls._tile_one_chunk(op) elif isinstance(op.inputs[0], SERIES_TYPE): return cls._tile_series(op) else: return cls._tile_dataframe(op) @classmethod def execute(cls, ctx, op): in_data = ctx[op.inputs[0].key] if not isinstance(op.dtype_values, dict): if op.category_cols is not None: uniques = [ctx[c.key] for c in op.inputs[1:]] dtype = dict((col, CategoricalDtype(unique_values)) for col, unique_values in zip(op.category_cols, uniques)) ctx[op.outputs[0].key] = in_data.astype(dtype, errors=op.errors) else: ctx[op.outputs[0].key] = in_data.astype(op.dtype_values, errors=op.errors) else: selected_dtype = dict((k, v) for k, v in op.dtype_values.items() if k in in_data.columns) if op.category_cols is not None: uniques = [ctx[c.key] for c in op.inputs[1:]] for col, unique_values in zip(op.category_cols, uniques): selected_dtype[col] = CategoricalDtype(unique_values) ctx[op.outputs[0].key] = in_data.astype(selected_dtype, errors=op.errors) def __call__(self, df): if isinstance(df, SERIES_TYPE): self._object_type = ObjectType.series empty_series = build_empty_series(df.dtype) new_series = empty_series.astype(self.dtype_values, errors=self.errors) if new_series.dtype != df.dtype: dtype = CategoricalDtype() if isinstance( new_series.dtype, CategoricalDtype) else new_series.dtype else: # pragma: no cover dtype = df.dtype return self.new_series([df], shape=df.shape, dtype=dtype, name=df.name, index_value=df.index_value) else: self._object_type = ObjectType.dataframe empty_df = build_empty_df(df.dtypes) new_df = empty_df.astype(self.dtype_values, errors=self.errors) dtypes = [] for dt, new_dt in zip(df.dtypes, new_df.dtypes): if new_dt != dt and isinstance(new_dt, CategoricalDtype): dtypes.append(CategoricalDtype()) else: dtypes.append(new_dt) dtypes = pd.Series(dtypes, index=new_df.dtypes.index) return self.new_dataframe([df], shape=df.shape, dtypes=dtypes, index_value=df.index_value, columns_value=df.columns_value) def astype(df, dtype, copy=True, errors='raise'): """ Cast a pandas object to a specified dtype ``dtype``. Parameters ---------- dtype : data type, or dict of column name -> data type Use a numpy.dtype or Python type to cast entire pandas object to the same type. Alternatively, use {col: dtype, ...}, where col is a column label and dtype is a numpy.dtype or Python type to cast one or more of the DataFrame's columns to column-specific types. copy : bool, default True Return a copy when ``copy=True`` (be very careful setting ``copy=False`` as changes to values then may propagate to other pandas objects). errors : {'raise', 'ignore'}, default 'raise' Control raising of exceptions on invalid data for provided dtype. - ``raise`` : allow exceptions to be raised - ``ignore`` : suppress exceptions. On error return original object. Returns ------- casted : same type as caller See Also -------- to_datetime : Convert argument to datetime. to_timedelta : Convert argument to timedelta. to_numeric : Convert argument to a numeric type. numpy.ndarray.astype : Cast a numpy array to a specified type. Examples -------- Create a DataFrame: >>> import mars.dataframe as md >>> df = md.DataFrame(pd.DataFrame({'col1': [1, 2], 'col2': [3, 4]})) >>> df.dtypes col1 int64 col2 int64 dtype: object Cast all columns to int32: >>> df.astype('int32').dtypes col1 int32 col2 int32 dtype: object Cast col1 to int32 using a dictionary: >>> df.astype({'col1': 'int32'}).dtypes col1 int32 col2 int64 dtype: object Create a series: >>> ser = md.Series(pd.Series([1, 2], dtype='int32')) >>> ser.execute() 0 1 1 2 dtype: int32 >>> ser.astype('int64').execute() 0 1 1 2 dtype: int64 Convert to categorical type: >>> ser.astype('category').execute() 0 1 1 2 dtype: category Categories (2, int64): [1, 2] Convert to ordered categorical type with custom ordering: >>> cat_dtype = pd.api.types.CategoricalDtype( ... categories=[2, 1], ordered=True) >>> ser.astype(cat_dtype).execute() 0 1 1 2 dtype: category Categories (2, int64): [2 < 1] Note that using ``copy=False`` and changing data on a new pandas object may propagate changes: >>> s1 = md.Series(pd.Series([1, 2])) >>> s2 = s1.astype('int64', copy=False) >>> s1.execute() # note that s1[0] has changed too 0 1 1 2 dtype: int64 """ if isinstance(dtype, dict): keys = list(dtype.keys()) if isinstance(df, SERIES_TYPE): if len(keys) != 1 or keys[0] != df.name: raise KeyError('Only the Series name can be used for the key in Series dtype mappings.') else: dtype = list(dtype.values())[0] else: for k in keys: columns = df.columns_value.to_pandas() if k not in columns: raise KeyError('Only a column name can be used for the key in a dtype mappings argument.') op = DataFrameAstype(dtype_values=dtype, errors=errors) r = op(df) if not copy: df.data = r.data return df else: return r

37.943218

110

0.587629

125499d1b492f52653e97ff9af0a87245a597744

26,887

py

Python

sdk/network/azure-mgmt-network/azure/mgmt/network/v2016_09_01/operations/_virtual_networks_operations.py

beltr0n/azure-sdk-for-python

2f7fb8bee881b0fc0386a0ad5385755ceedd0453

[ "MIT" ]

2

2021-03-24T06:26:11.000Z

2021-04-18T15:55:59.000Z

sdk/network/azure-mgmt-network/azure/mgmt/network/v2016_09_01/operations/_virtual_networks_operations.py

beltr0n/azure-sdk-for-python

2f7fb8bee881b0fc0386a0ad5385755ceedd0453

[ "MIT" ]

4

2019-04-17T17:57:49.000Z

2020-04-24T21:11:22.000Z

sdk/network/azure-mgmt-network/azure/mgmt/network/v2016_09_01/operations/_virtual_networks_operations.py

beltr0n/azure-sdk-for-python

2f7fb8bee881b0fc0386a0ad5385755ceedd0453

[ "MIT" ]

2

2021-05-23T16:46:31.000Z

2021-05-26T23:51:09.000Z

# coding=utf-8 # -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is regenerated. # -------------------------------------------------------------------------- from typing import TYPE_CHECKING import warnings from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error from azure.core.paging import ItemPaged from azure.core.pipeline import PipelineResponse from azure.core.pipeline.transport import HttpRequest, HttpResponse from azure.core.polling import LROPoller, NoPolling, PollingMethod from azure.mgmt.core.exceptions import ARMErrorFormat from azure.mgmt.core.polling.arm_polling import ARMPolling from .. import models as _models if TYPE_CHECKING: # pylint: disable=unused-import,ungrouped-imports from typing import Any, Callable, Dict, Generic, Iterable, Optional, TypeVar, Union T = TypeVar('T') ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]] class VirtualNetworksOperations(object): """VirtualNetworksOperations operations. You should not instantiate this class directly. Instead, you should create a Client instance that instantiates it for you and attaches it as an attribute. :ivar models: Alias to model classes used in this operation group. :type models: ~azure.mgmt.network.v2016_09_01.models :param client: Client for service requests. :param config: Configuration of service client. :param serializer: An object model serializer. :param deserializer: An object model deserializer. """ models = _models def __init__(self, client, config, serializer, deserializer): self._client = client self._serialize = serializer self._deserialize = deserializer self._config = config def _delete_initial( self, resource_group_name, # type: str virtual_network_name, # type: str **kwargs # type: Any ): # type: (...) -> None cls = kwargs.pop('cls', None) # type: ClsType[None] error_map = { 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError } error_map.update(kwargs.pop('error_map', {})) api_version = "2016-09-01" # Construct URL url = self._delete_initial.metadata['url'] # type: ignore path_format_arguments = { 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), 'virtualNetworkName': self._serialize.url("virtual_network_name", virtual_network_name, 'str'), 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} # type: Dict[str, Any] query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') # Construct headers header_parameters = {} # type: Dict[str, Any] request = self._client.delete(url, query_parameters, header_parameters) pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response if response.status_code not in [200, 202, 204]: map_error(status_code=response.status_code, response=response, error_map=error_map) raise HttpResponseError(response=response, error_format=ARMErrorFormat) if cls: return cls(pipeline_response, None, {}) _delete_initial.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.Network/virtualNetworks/{virtualNetworkName}'} # type: ignore def begin_delete( self, resource_group_name, # type: str virtual_network_name, # type: str **kwargs # type: Any ): # type: (...) -> LROPoller[None] """Deletes the specified virtual network. :param resource_group_name: The name of the resource group. :type resource_group_name: str :param virtual_network_name: The name of the virtual network. :type virtual_network_name: str :keyword callable cls: A custom type or function that will be passed the direct response :keyword str continuation_token: A continuation token to restart a poller from a saved state. :keyword polling: True for ARMPolling, False for no polling, or a polling object for personal polling strategy :paramtype polling: bool or ~azure.core.polling.PollingMethod :keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present. :return: An instance of LROPoller that returns either None or the result of cls(response) :rtype: ~azure.core.polling.LROPoller[None] :raises ~azure.core.exceptions.HttpResponseError: """ polling = kwargs.pop('polling', True) # type: Union[bool, PollingMethod] cls = kwargs.pop('cls', None) # type: ClsType[None] lro_delay = kwargs.pop( 'polling_interval', self._config.polling_interval ) cont_token = kwargs.pop('continuation_token', None) # type: Optional[str] if cont_token is None: raw_result = self._delete_initial( resource_group_name=resource_group_name, virtual_network_name=virtual_network_name, cls=lambda x,y,z: x, **kwargs ) kwargs.pop('error_map', None) kwargs.pop('content_type', None) def get_long_running_output(pipeline_response): if cls: return cls(pipeline_response, None, {}) path_format_arguments = { 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), 'virtualNetworkName': self._serialize.url("virtual_network_name", virtual_network_name, 'str'), 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), } if polling is True: polling_method = ARMPolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) elif polling is False: polling_method = NoPolling() else: polling_method = polling if cont_token: return LROPoller.from_continuation_token( polling_method=polling_method, continuation_token=cont_token, client=self._client, deserialization_callback=get_long_running_output ) else: return LROPoller(self._client, raw_result, get_long_running_output, polling_method) begin_delete.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.Network/virtualNetworks/{virtualNetworkName}'} # type: ignore def get( self, resource_group_name, # type: str virtual_network_name, # type: str expand=None, # type: Optional[str] **kwargs # type: Any ): # type: (...) -> "_models.VirtualNetwork" """Gets the specified virtual network by resource group. :param resource_group_name: The name of the resource group. :type resource_group_name: str :param virtual_network_name: The name of the virtual network. :type virtual_network_name: str :param expand: Expands referenced resources. :type expand: str :keyword callable cls: A custom type or function that will be passed the direct response :return: VirtualNetwork, or the result of cls(response) :rtype: ~azure.mgmt.network.v2016_09_01.models.VirtualNetwork :raises: ~azure.core.exceptions.HttpResponseError """ cls = kwargs.pop('cls', None) # type: ClsType["_models.VirtualNetwork"] error_map = { 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError } error_map.update(kwargs.pop('error_map', {})) api_version = "2016-09-01" accept = "application/json, text/json" # Construct URL url = self.get.metadata['url'] # type: ignore path_format_arguments = { 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), 'virtualNetworkName': self._serialize.url("virtual_network_name", virtual_network_name, 'str'), 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} # type: Dict[str, Any] query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') if expand is not None: query_parameters['$expand'] = self._serialize.query("expand", expand, 'str') # Construct headers header_parameters = {} # type: Dict[str, Any] header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') request = self._client.get(url, query_parameters, header_parameters) pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) raise HttpResponseError(response=response, error_format=ARMErrorFormat) deserialized = self._deserialize('VirtualNetwork', pipeline_response) if cls: return cls(pipeline_response, deserialized, {}) return deserialized get.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.Network/virtualNetworks/{virtualNetworkName}'} # type: ignore def _create_or_update_initial( self, resource_group_name, # type: str virtual_network_name, # type: str parameters, # type: "_models.VirtualNetwork" **kwargs # type: Any ): # type: (...) -> "_models.VirtualNetwork" cls = kwargs.pop('cls', None) # type: ClsType["_models.VirtualNetwork"] error_map = { 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError } error_map.update(kwargs.pop('error_map', {})) api_version = "2016-09-01" content_type = kwargs.pop("content_type", "application/json") accept = "application/json, text/json" # Construct URL url = self._create_or_update_initial.metadata['url'] # type: ignore path_format_arguments = { 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), 'virtualNetworkName': self._serialize.url("virtual_network_name", virtual_network_name, 'str'), 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} # type: Dict[str, Any] query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') # Construct headers header_parameters = {} # type: Dict[str, Any] header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str') header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') body_content_kwargs = {} # type: Dict[str, Any] body_content = self._serialize.body(parameters, 'VirtualNetwork') body_content_kwargs['content'] = body_content request = self._client.put(url, query_parameters, header_parameters, **body_content_kwargs) pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response if response.status_code not in [200, 201]: map_error(status_code=response.status_code, response=response, error_map=error_map) raise HttpResponseError(response=response, error_format=ARMErrorFormat) if response.status_code == 200: deserialized = self._deserialize('VirtualNetwork', pipeline_response) if response.status_code == 201: deserialized = self._deserialize('VirtualNetwork', pipeline_response) if cls: return cls(pipeline_response, deserialized, {}) return deserialized _create_or_update_initial.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.Network/virtualNetworks/{virtualNetworkName}'} # type: ignore def begin_create_or_update( self, resource_group_name, # type: str virtual_network_name, # type: str parameters, # type: "_models.VirtualNetwork" **kwargs # type: Any ): # type: (...) -> LROPoller["_models.VirtualNetwork"] """Creates or updates a virtual network in the specified resource group. :param resource_group_name: The name of the resource group. :type resource_group_name: str :param virtual_network_name: The name of the virtual network. :type virtual_network_name: str :param parameters: Parameters supplied to the create or update virtual network operation. :type parameters: ~azure.mgmt.network.v2016_09_01.models.VirtualNetwork :keyword callable cls: A custom type or function that will be passed the direct response :keyword str continuation_token: A continuation token to restart a poller from a saved state. :keyword polling: True for ARMPolling, False for no polling, or a polling object for personal polling strategy :paramtype polling: bool or ~azure.core.polling.PollingMethod :keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present. :return: An instance of LROPoller that returns either VirtualNetwork or the result of cls(response) :rtype: ~azure.core.polling.LROPoller[~azure.mgmt.network.v2016_09_01.models.VirtualNetwork] :raises ~azure.core.exceptions.HttpResponseError: """ polling = kwargs.pop('polling', True) # type: Union[bool, PollingMethod] cls = kwargs.pop('cls', None) # type: ClsType["_models.VirtualNetwork"] lro_delay = kwargs.pop( 'polling_interval', self._config.polling_interval ) cont_token = kwargs.pop('continuation_token', None) # type: Optional[str] if cont_token is None: raw_result = self._create_or_update_initial( resource_group_name=resource_group_name, virtual_network_name=virtual_network_name, parameters=parameters, cls=lambda x,y,z: x, **kwargs ) kwargs.pop('error_map', None) kwargs.pop('content_type', None) def get_long_running_output(pipeline_response): deserialized = self._deserialize('VirtualNetwork', pipeline_response) if cls: return cls(pipeline_response, deserialized, {}) return deserialized path_format_arguments = { 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), 'virtualNetworkName': self._serialize.url("virtual_network_name", virtual_network_name, 'str'), 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), } if polling is True: polling_method = ARMPolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) elif polling is False: polling_method = NoPolling() else: polling_method = polling if cont_token: return LROPoller.from_continuation_token( polling_method=polling_method, continuation_token=cont_token, client=self._client, deserialization_callback=get_long_running_output ) else: return LROPoller(self._client, raw_result, get_long_running_output, polling_method) begin_create_or_update.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.Network/virtualNetworks/{virtualNetworkName}'} # type: ignore def list_all( self, **kwargs # type: Any ): # type: (...) -> Iterable["_models.VirtualNetworkListResult"] """Gets all virtual networks in a subscription. :keyword callable cls: A custom type or function that will be passed the direct response :return: An iterator like instance of either VirtualNetworkListResult or the result of cls(response) :rtype: ~azure.core.paging.ItemPaged[~azure.mgmt.network.v2016_09_01.models.VirtualNetworkListResult] :raises: ~azure.core.exceptions.HttpResponseError """ cls = kwargs.pop('cls', None) # type: ClsType["_models.VirtualNetworkListResult"] error_map = { 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError } error_map.update(kwargs.pop('error_map', {})) api_version = "2016-09-01" accept = "application/json, text/json" def prepare_request(next_link=None): # Construct headers header_parameters = {} # type: Dict[str, Any] header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') if not next_link: # Construct URL url = self.list_all.metadata['url'] # type: ignore path_format_arguments = { 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} # type: Dict[str, Any] query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') request = self._client.get(url, query_parameters, header_parameters) else: url = next_link query_parameters = {} # type: Dict[str, Any] request = self._client.get(url, query_parameters, header_parameters) return request def extract_data(pipeline_response): deserialized = self._deserialize('VirtualNetworkListResult', pipeline_response) list_of_elem = deserialized.value if cls: list_of_elem = cls(list_of_elem) return deserialized.next_link or None, iter(list_of_elem) def get_next(next_link=None): request = prepare_request(next_link) pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) raise HttpResponseError(response=response, error_format=ARMErrorFormat) return pipeline_response return ItemPaged( get_next, extract_data ) list_all.metadata = {'url': '/subscriptions/{subscriptionId}/providers/Microsoft.Network/virtualNetworks'} # type: ignore def list( self, resource_group_name, # type: str **kwargs # type: Any ): # type: (...) -> Iterable["_models.VirtualNetworkListResult"] """Gets all virtual networks in a resource group. :param resource_group_name: The name of the resource group. :type resource_group_name: str :keyword callable cls: A custom type or function that will be passed the direct response :return: An iterator like instance of either VirtualNetworkListResult or the result of cls(response) :rtype: ~azure.core.paging.ItemPaged[~azure.mgmt.network.v2016_09_01.models.VirtualNetworkListResult] :raises: ~azure.core.exceptions.HttpResponseError """ cls = kwargs.pop('cls', None) # type: ClsType["_models.VirtualNetworkListResult"] error_map = { 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError } error_map.update(kwargs.pop('error_map', {})) api_version = "2016-09-01" accept = "application/json, text/json" def prepare_request(next_link=None): # Construct headers header_parameters = {} # type: Dict[str, Any] header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') if not next_link: # Construct URL url = self.list.metadata['url'] # type: ignore path_format_arguments = { 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} # type: Dict[str, Any] query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') request = self._client.get(url, query_parameters, header_parameters) else: url = next_link query_parameters = {} # type: Dict[str, Any] request = self._client.get(url, query_parameters, header_parameters) return request def extract_data(pipeline_response): deserialized = self._deserialize('VirtualNetworkListResult', pipeline_response) list_of_elem = deserialized.value if cls: list_of_elem = cls(list_of_elem) return deserialized.next_link or None, iter(list_of_elem) def get_next(next_link=None): request = prepare_request(next_link) pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) raise HttpResponseError(response=response, error_format=ARMErrorFormat) return pipeline_response return ItemPaged( get_next, extract_data ) list.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.Network/virtualNetworks'} # type: ignore def check_ip_address_availability( self, resource_group_name, # type: str virtual_network_name, # type: str ip_address=None, # type: Optional[str] **kwargs # type: Any ): # type: (...) -> "_models.IPAddressAvailabilityResult" """Checks whether a private IP address is available for use. :param resource_group_name: The name of the resource group. :type resource_group_name: str :param virtual_network_name: The name of the virtual network. :type virtual_network_name: str :param ip_address: The private IP address to be verified. :type ip_address: str :keyword callable cls: A custom type or function that will be passed the direct response :return: IPAddressAvailabilityResult, or the result of cls(response) :rtype: ~azure.mgmt.network.v2016_09_01.models.IPAddressAvailabilityResult :raises: ~azure.core.exceptions.HttpResponseError """ cls = kwargs.pop('cls', None) # type: ClsType["_models.IPAddressAvailabilityResult"] error_map = { 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError } error_map.update(kwargs.pop('error_map', {})) api_version = "2016-09-01" accept = "application/json, text/json" # Construct URL url = self.check_ip_address_availability.metadata['url'] # type: ignore path_format_arguments = { 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), 'virtualNetworkName': self._serialize.url("virtual_network_name", virtual_network_name, 'str'), 'subscriptionId': self._serialize.url("self._config.subscription_id", self._config.subscription_id, 'str'), } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} # type: Dict[str, Any] if ip_address is not None: query_parameters['ipAddress'] = self._serialize.query("ip_address", ip_address, 'str') query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') # Construct headers header_parameters = {} # type: Dict[str, Any] header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') request = self._client.get(url, query_parameters, header_parameters) pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) raise HttpResponseError(response=response, error_format=ARMErrorFormat) deserialized = self._deserialize('IPAddressAvailabilityResult', pipeline_response) if cls: return cls(pipeline_response, deserialized, {}) return deserialized check_ip_address_availability.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.Network/virtualNetworks/{virtualNetworkName}/CheckIPAddressAvailability'} # type: ignore

48.620253

230

0.662774

4f58841e546993f965038dec2306af4284050f45

901

py

Python

examples/centerize.py

penguinflys/imgviz

3deadced1fcce8ca51716c705d07a058b1839514

[ "MIT" ]

171

2018-12-28T23:40:01.000Z

2022-03-29T14:55:27.000Z

examples/centerize.py

penguinflys/imgviz

3deadced1fcce8ca51716c705d07a058b1839514

[ "MIT" ]

16

2018-12-29T16:21:15.000Z

2022-03-09T15:36:06.000Z

examples/centerize.py

penguinflys/imgviz

3deadced1fcce8ca51716c705d07a058b1839514

[ "MIT" ]

23

2018-12-29T13:11:18.000Z

2022-02-06T15:18:42.000Z

#!/usr/bin/env python import matplotlib.pyplot as plt import imgviz def centerize(): data = imgviz.data.arc2017() rgb = data["rgb"] H, W = rgb.shape[:2] centerized1 = imgviz.centerize(rgb, shape=(H, H)) rgb_T = rgb.transpose(1, 0, 2) centerized2 = imgviz.centerize(rgb_T, shape=(H, H)) # ------------------------------------------------------------------------- plt.figure(dpi=200) plt.subplot(131) plt.title("original") plt.axis("off") plt.imshow(rgb) plt.subplot(132) plt.title("centerized1:\n{}".format(centerized1.shape)) plt.imshow(centerized1) plt.axis("off") plt.subplot(133) plt.title("centerized2:\n{}".format(centerized2.shape)) plt.imshow(centerized2) plt.axis("off") return imgviz.io.pyplot_to_numpy() if __name__ == "__main__": from base import run_example run_example(centerize)

20.022222

79

0.588235

0bc6164cf6aa4cdcc0bdd2265556a07b34572ac5

9,195

py

Python

userbot/__init__.py

Rizkipratama183/OpenUserBot

896c19686dd8ced2ec2e0faaad4d5dd41a53d707

[ "Naumen", "Condor-1.1", "MS-PL" ]

1

2020-05-18T00:17:28.000Z

userbot/__init__.py

Rizkipratama183/OpenUserBot

896c19686dd8ced2ec2e0faaad4d5dd41a53d707

[ "Naumen", "Condor-1.1", "MS-PL" ]

2

2020-05-19T13:01:21.000Z

2020-05-19T20:46:27.000Z

userbot/__init__.py

Rizkipratama183/OpenUserBot

896c19686dd8ced2ec2e0faaad4d5dd41a53d707

[ "Naumen", "Condor-1.1", "MS-PL" ]

null

# Copyright (C) 2019 The Raphielscape Company LLC. # # Licensed under the Raphielscape Public License, Version 1.c (the "License"); # you may not use this file except in compliance with the License. # # thanks to penn5 for bug fixing """ Userbot initialization. """ import os from sys import version_info from logging import basicConfig, getLogger, INFO, DEBUG from distutils.util import strtobool as sb from pymongo import MongoClient from redis import StrictRedis from pylast import LastFMNetwork, md5 from pySmartDL import SmartDL from dotenv import load_dotenv from requests import get from telethon import TelegramClient from telethon.sessions import StringSession load_dotenv("config.env") # Bot Logs setup: CONSOLE_LOGGER_VERBOSE = sb(os.environ.get("CONSOLE_LOGGER_VERBOSE", "False")) if CONSOLE_LOGGER_VERBOSE: basicConfig( format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", level=DEBUG, ) else: basicConfig(format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", level=INFO) LOGS = getLogger(__name__) if version_info[0] < 3 or version_info[1] < 8: LOGS.info("You MUST have a python version of at least 3.8." "Multiple features depend on this. Bot quitting.") quit(1) # Check if the config was edited by using the already used variable. # Basically, its the 'virginity check' for the config file ;) CONFIG_CHECK = os.environ.get( "", None) if CONFIG_CHECK: LOGS.info( "Please remove the line mentioned in the first hashtag from the config.env file" ) quit(1) #Quotes API Token QUOTES_API_TOKEN =os.environ.get("QOUTES_API_TOKEN", "21958215-520f-4460-9b05-5751920f67a5") # Telegram App KEY and HASH API_KEY = os.environ.get("API_KEY", "1287613") API_HASH = os.environ.get("API_HASH", "b31151a1dd663e9538b79a5afdf5da07") # Photo Chat - Get this value from http://antiddos.systems API_TOKEN = os.environ.get("API_TOKEN", "21958215-520f-4460-9b05-5751920f67a5") API_URL = os.environ.get("API_URL", "http://antiddos.systems") # Userbot Session String STRING_SESSION = os.environ.get("STRING_SESSION", "1BVtsOHgBu24AAhATiCBpTWK9hgPK11Mu4Hbdrdd66SPrp3R50yebePiUc0f246sMrUJg-q8fP_I7sGFGC85ShJgU0ojhjb6-0WSFMP84hpF6iSSMZx5axU9DvOMjtyz6CT4JyOAbfZ-nLRxJOg57EVXZazhvt7L59CZZU4hqLThQvNK0XnrAhcEZUgdtsg7Iph99-UAhdy5p98Cm4f8P94e6GNXCbKJ9wefEodrXzza76PwRu3fbB0hm_1fk-P85YKXFXOhNPiPvGFKQsq9a7tauOu5YulXHnxRi2k9vqinsXQCcs0vomLRxma3aZk6cHyBcxinV0odMtVRgjbjGVtf7ZkHdXDk=") # Logging channel/group ID configuration. BOTLOG_CHATID = int(os.environ.get("BOTLOG_CHATID", "-492505987")) # Userbot logging feature switch. BOTLOG = sb(os.environ.get("BOTLOG", "True")) LOGSPAMMER = sb(os.environ.get("LOGSPAMMER", "False")) # Bleep Blop, this is a bot ;) PM_AUTO_BAN = sb(os.environ.get("PM_AUTO_BAN", "False")) # Heroku Credentials for updater. HEROKU_MEMEZ = sb(os.environ.get("HEROKU_MEMEZ", "False")) HEROKU_APP_NAME = os.environ.get("HEROKU_APP_NAME", None) HEROKU_API_KEY = os.environ.get("HEROKU_API_KEY", "7ca04981-b77a-407f-a580-627af0282177") # Github Credentials for updater and Gitupload. GIT_REPO_NAME = os.environ.get("GIT_REPO_NAME", "OpenUserBot") GITHUB_ACCESS_TOKEN = os.environ.get("GITHUB_ACCESS_TOKEN", "ee3478dffc9ea26e91db89799962ef6ed4de1eeb") # Custom (forked) repo URL for updater. UPSTREAM_REPO_URL = os.environ.get("UPSTREAM_REPO_URL", "https://github.com/Rizkipratama183/OpenUserBot.git") UPSTREAM_REPO_BRANCH = os.environ.get("UPSTREAM_REPO_BRANCH", "https://github.com/mkaraniya/OpenUserBot.git") # Console verbose logging CONSOLE_LOGGER_VERBOSE = sb(os.environ.get("CONSOLE_LOGGER_VERBOSE", "False")) # SQL Database URI DB_URI = os.environ.get("DATABASE_URL", None) # For MONGO based DataBase MONGO_URI = os.environ.get("MONGO_URI", None) # OCR API key OCR_SPACE_API_KEY = os.environ.get("OCR_SPACE_API_KEY", "69a15874ea88957") # remove.bg API key REM_BG_API_KEY = os.environ.get("REM_BG_API_KEY", None) # Chrome Driver and Headless Google Chrome Binaries CHROME_DRIVER = os.environ.get("CHROME_DRIVER", None) GOOGLE_CHROME_BIN = os.environ.get("GOOGLE_CHROME_BIN", None) # OpenWeatherMap API Key OPEN_WEATHER_MAP_APPID = os.environ.get("OPEN_WEATHER_MAP_APPID", "9857d9956ac29abdd218b58359655143") WEATHER_DEFCITY = os.environ.get("WEATHER_DEFCITY", "Indonesia/Jakarta") # Lydia API LYDIA_API_KEY = os.environ.get("LYDIA_API_KEY", None) # set blacklist_chats where you do not want userbot's features UB_BLACK_LIST_CHAT = os.environ.get("UB_BLACK_LIST_CHAT", "") # Telegraph TELEGRAPH_SHORT_NAME = os.environ.get("TELEGRAPH_SHORT_NAME", "♤■Clown_Cyber■♧") # Anti Spambot Config ANTI_SPAMBOT = sb(os.environ.get("ANTI_SPAMBOT", "True")) ANTI_SPAMBOT_SHOUT = sb(os.environ.get("ANTI_SPAMBOT_SHOUT", "True")) # Youtube API key YOUTUBE_API_KEY = os.environ.get("YOUTUBE_API_KEY", None) # Default .alive name ALIVE_NAME = os.environ.get("ALIVE_NAME", "Clown Cyber") # Time & Date - Country and Time Zone COUNTRY = str(os.environ.get("COUNTRY", "Indonesia")) TZ_NUMBER = int(os.environ.get("TZ_NUMBER", 1)) TERM_ALIAS = os.environ.get("TERM_ALIAS", "OUB") # Clean Welcome CLEAN_WELCOME = sb(os.environ.get("CLEAN_WELCOME", "True")) # Last.fm Module BIO_PREFIX = os.environ.get("BIO_PREFIX", None) DEFAULT_BIO = os.environ.get("DEFAULT_BIO", None) LASTFM_API = os.environ.get("LASTFM_API", None) LASTFM_SECRET = os.environ.get("LASTFM_SECRET", None) LASTFM_USERNAME = os.environ.get("LASTFM_USERNAME", None) LASTFM_PASSWORD_PLAIN = os.environ.get("LASTFM_PASSWORD", None) LASTFM_PASS = md5(LASTFM_PASSWORD_PLAIN) if LASTFM_API and LASTFM_SECRET and LASTFM_USERNAME and LASTFM_PASS: lastfm = LastFMNetwork(api_key=LASTFM_API, api_secret=LASTFM_SECRET, username=LASTFM_USERNAME, password_hash=LASTFM_PASS) else: lastfm = None # Google Drive Module G_DRIVE_CLIENT_ID = os.environ.get("G_DRIVE_CLIENT_ID", None) G_DRIVE_CLIENT_SECRET = os.environ.get("G_DRIVE_CLIENT_SECRET", None) G_DRIVE_AUTH_TOKEN_DATA = os.environ.get("G_DRIVE_AUTH_TOKEN_DATA", None) GDRIVE_FOLDER_ID = os.environ.get("GDRIVE_FOLDER_ID", None) TEMP_DOWNLOAD_DIRECTORY = os.environ.get("TMP_DOWNLOAD_DIRECTORY", "./downloads") # Genius lyrics get this value from https://genius.com/developers both has same values GENIUS_API_TOKEN = os.environ.get("GENIUS", True) # Genius lyrics get this value from https://genius.com/developers both has same values GENIUS = os.environ.get("GENIUS_API_TOKEN", "LV3R5X9024-uD3UGzw_7Z090QUx43EPa_dEUpUj26F5oEw7598stRAD6GvSO2z2U") # Init Mongo MONGOCLIENT = MongoClient(MONGO_URI, 27017, serverSelectionTimeoutMS=1) MONGO = MONGOCLIENT.userbot def is_mongo_alive(): try: MONGOCLIENT.server_info() except BaseException: return False return True # Init Redis # Redis will be hosted inside the docker container that hosts the bot # We need redis for just caching, so we just leave it to non-persistent REDIS = StrictRedis(host='localhost', port=6379, db=0) def is_redis_alive(): try: REDIS.ping() return True except BaseException: return False # Setting Up CloudMail.ru and MEGA.nz extractor binaries, # and giving them correct perms to work properly. if not os.path.exists('bin'): os.mkdir('bin') binaries = { "https://raw.githubusercontent.com/adekmaulana/megadown/master/megadown": "bin/megadown", "https://raw.githubusercontent.com/yshalsager/cmrudl.py/master/cmrudl.py": "bin/cmrudl" } for binary, path in binaries.items(): downloader = SmartDL(binary, path, progress_bar=False) downloader.start() os.chmod(path, 0o755) # 'bot' variable if STRING_SESSION: # pylint: disable=invalid-name bot = TelegramClient(StringSession(STRING_SESSION), API_KEY, API_HASH) else: # pylint: disable=invalid-name bot = TelegramClient("userbot", API_KEY, API_HASH) async def check_botlog_chatid(): if not BOTLOG_CHATID and LOGSPAMMER: LOGS.info( "You must set up the BOTLOG_CHATID variable in the config.env or environment variables, for the private error log storage to work." ) quit(1) elif not BOTLOG_CHATID and BOTLOG: LOGS.info( "You must set up the BOTLOG_CHATID variable in the config.env or environment variables, for the userbot logging feature to work." ) quit(1) elif not BOTLOG or not LOGSPAMMER: return entity = await bot.get_entity(BOTLOG_CHATID) if entity.default_banned_rights.send_messages: LOGS.info( "Your account doesn't have rights to send messages to BOTLOG_CHATID " "group. Check if you typed the Chat ID correctly.") quit(1) with bot: try: bot.loop.run_until_complete(check_botlog_chatid()) except: LOGS.info( "BOTLOG_CHATID environment variable isn't a " "valid entity. Check your environment variables/config.env file.") quit(1) # Global Variables COUNT_MSG = 0 USERS = {} COUNT_PM = {} LASTMSG = {} ENABLE_KILLME = True CMD_HELP = {} ISAFK = False AFKREASON = None

34.567669

406

0.736378

0a7922b9cf2a8d5632f3e4f6933a9a68f500bdb0

3,907

py

Python

dataset/datasets.py

ruiming46zrm/CurricularFace

d853f3d28659f0929469029ec80e29e91e7b24c1

[ "MIT" ]

433

2020-04-02T04:24:50.000Z

2022-03-21T12:57:53.000Z

dataset/datasets.py

clscy/CurricularFace

d853f3d28659f0929469029ec80e29e91e7b24c1

[ "MIT" ]

35

2020-04-09T02:13:52.000Z

2022-03-07T07:48:10.000Z

dataset/datasets.py

clscy/CurricularFace

d853f3d28659f0929469029ec80e29e91e7b24c1

[ "MIT" ]

72

2020-04-02T21:57:37.000Z

2022-01-10T02:50:33.000Z

import numpy as np import torch from PIL import Image from torch.utils.data import Dataset import os from collections import defaultdict class ImageDataset(Dataset): def __init__(self, root_dir, transform): super(ImageDataset, self).__init__() self.transform = transform self.root_dir = root_dir classes, class_to_idx = self._find_classes(self.root_dir) samples, label_to_indexes = self._make_dataset(self.root_dir, class_to_idx) print('samples num', len(samples)) self.samples = samples self.class_to_idx = class_to_idx self.label_to_indexes = label_to_indexes self.classes = sorted(self.label_to_indexes.keys()) print('class num', len(self.classes)) def _find_classes(self, dir): classes = [d.name for d in os.scandir(dir) if d.is_dir()] classes.sort() class_to_idx = {classes[i]: i for i in range(len(classes))} return classes, class_to_idx def _make_dataset(self, root_dir, class_to_idx): root_dir = os.path.expanduser(root_dir) images = [] label2index = defaultdict(list) image_index = 0 for target in sorted(class_to_idx.keys()): d = os.path.join(root_dir, target) if not os.path.isdir(d): continue for root, _, fnames in sorted(os.walk(d)): for fname in sorted(fnames): path = os.path.join(root, fname) item = (path, class_to_idx[target]) images.append(item) label2index[class_to_idx[target]].append(image_index) image_index += 1 return images, label2index def __getitem__(self, index): path, target = self.samples[index] sample = Image.open(path) if self.transform is not None: sample = self.transform(sample) return sample, target def __len__(self): return len(self.samples) def read_samples_from_record(root_dir, record_dir, Train): samples = [] classes = set() names = [] label2index = defaultdict(list) with open(record_dir, "r") as f: for index, line in enumerate(f): line = line.split() if Train and len(line) < 2: print('Error, Label is missing') exit() elif len(line) == 1: image_dir = line[0] label = 0 else: image_dir, label = line[0], line[1] label = int(label) names.append(image_dir) image_dir = os.path.join(root_dir, image_dir) samples.append((image_dir, label)) classes.add(label) label2index[label].append(index) return samples, classes, names, label2index class FaceDataset(Dataset): def __init__(self, root_dir, record_dir, transform, Train=True): super(FaceDataset, self).__init__() self.transform = transform self.root_dir = root_dir self.train = Train self.imgs, self.classes, self.names, self.label_to_indexes = read_samples_from_record(root_dir, record_dir, Train=Train) print("Number of Sampels:{} Number of Classes: {}".format(len(self.imgs), len(self.classes))) def __getitem__(self, index): path, target = self.imgs[index] sample = Image.open(path) sample = sample.convert("RGB") if self.transform is not None: sample = self.transform(sample) if self.train: return sample, target else: return sample, target, self.names[index] def __len__(self): return len(self.imgs) def get_sample_num_of_each_class(self): sample_num = [] for label in self.classes: sample_num.append(len(self.label_to_indexes[label])) return sample_num

35.198198

128

0.602252

4343906b42accb20dabd6fbbcacdfe128c509e37

4,472

py

Python

naolution/utils/cnn.py

kostelansky17/NAOlution

60101858c233e4f0e83d38c4f8733c71187a1639

[ "MIT" ]

null

naolution/utils/cnn.py

kostelansky17/NAOlution

60101858c233e4f0e83d38c4f8733c71187a1639

[ "MIT" ]

null

naolution/utils/cnn.py

kostelansky17/NAOlution

60101858c233e4f0e83d38c4f8733c71187a1639

[ "MIT" ]

null

import numpy as np from keras import backend as K from keras import layers from keras.models import Sequential from keras.preprocessing import image as keras_image from keras.activations import relu, tanh from keras.initializers import random_normal from keras.layers.core import Dense, Flatten, Dropout from keras.layers.convolutional import Conv2D, MaxPooling2D from sklearn.utils import shuffle """ Creates Convolutional Neural Network with randomly initialized weights @return model: keras.model.Sequential """ def create_cnn(): #Input shape - image 128x128 pixels in grayscale input_shape = (128,128,1) model = Sequential() model.add(MaxPooling2D((2, 2), input_shape = input_shape)) model.add(Conv2D(4, (4, 4), kernel_initializer= 'random_normal', bias_initializer='random_normal')) model.add(Conv2D(4, (4, 4), kernel_initializer= 'random_normal', bias_initializer='random_normal')) model.add(MaxPooling2D((2, 2))) model.add(Conv2D(8, (4, 4), kernel_initializer= 'random_normal', bias_initializer='random_normal')) model.add(Conv2D(8, (4, 4), kernel_initializer= 'random_normal', bias_initializer='random_normal')) model.add(MaxPooling2D((2, 2))) model.add(Flatten()) model.add(Dropout(0.25)) model.add(Dense(16, activation = relu, kernel_initializer= 'random_normal', bias_initializer='random_normal')) model.add(Dense(16, activation = relu, kernel_initializer= 'random_normal', bias_initializer='random_normal')) model.add(Dense(3, activation = tanh, kernel_initializer= 'random_normal', bias_initializer='random_normal')) return model """ Creates list of CNNs generated by create_cnn(). @param size: int (number of CNNs) @return cnn_list: list (list of CNNs) """ def create_list_cnn(number): cnn_list = [] for i in range(number): cnn_list.append(create_cnn()) return cnn_list """ Loads and preprocess image to input shape for CNN created by cnn.py @param img_path: String (path to image) @return img: image in desired shape """ def preprocess_img_from_path(img_path): loaded_img = keras_image.load_img(img_path, color_mode = 'grayscale', target_size=(128, 128)) array_img = keras_image.img_to_array(loaded_img) img = np.expand_dims(array_img, axis=0) return img """ Creates dummmy Convolutional Neural Network with randomly initialized weights @return model: keras.model.Sequential """ def create_dummy_model(): input_shape = (128,128,1) model = Sequential() model.add(MaxPooling2D((2, 2), input_shape = input_shape)) model.add(Conv2D(1, (2, 2), kernel_initializer= 'random_normal', bias_initializer='random_normal')) model.add(Flatten()) model.add(Dense(2, activation = relu, kernel_initializer= 'random_normal', bias_initializer='random_normal')) return model """ Crossing two Keras sequential models @param model_A: First model @param model_B: Second model @return img: image in desired shape """ def mix_two_models(model_A, model_B): model_C = create_cnn() for layer_A, layer_B, layer_C in zip(model_A.layers, model_B.layers, model_C.layers): new_layer = list() for array_A, array_B in zip(layer_A.get_weights(), layer_B.get_weights()): choice = np.random.randint(2, size = array_A.size).reshape(array_A.shape).astype(bool) array_C = np.where(choice, array_A, array_B) new_layer.append(array_C) layer_C.set_weights(new_layer) return model_C """ Functionality testing created while developent """ if __name__ == "__main__": individual_A = create_cnn() individual_B = create_cnn() individual_C = create_cnn() for layer_A, layer_B, layer_C in zip(individual_A.layers, individual_B.layers, individual_C.layers): print("LAYER:") print(layer_A.get_weights()) print(type(layer_A.get_weights())) ml = list() for array_A, array_B in zip(layer_A.get_weights(), layer_B.get_weights()): print("ARR_A") print(array_A) print(array_A.shape) print("ARR_B") print(array_B) print(array_B.shape) choice = np.random.randint(2, size = array_A.size).reshape(array_A.shape).astype(bool) res = np.where(choice, array_A, array_B) print("SSSS") print(res) print(res.shape) ml.append(res) layer_C.set_weights(ml)

32.642336

114

0.695886

7a567e3282ff44c354f9f0236598d852bef6000b

373

py

Python

lec2.py

Caleb0929/IA241

2fed3e8d0f12bb8180a3e53beed036949cd9eaa0

[ "MIT" ]

null

lec2.py

Caleb0929/IA241

2fed3e8d0f12bb8180a3e53beed036949cd9eaa0

[ "MIT" ]

null

lec2.py

Caleb0929/IA241

2fed3e8d0f12bb8180a3e53beed036949cd9eaa0

[ "MIT" ]

null

""" this is a regional comment """ #print(" hello world ") # this is a single line comment #print( type("123.") ) #print("It's our second python class") #print("Hello" + " World") my_str = 'hello world' print(my_str) my_str = 'second str' print(my_str) my_int = 2 my_float = 2.0 print(my_int + 3) print(my_int * 3) print(my_int ** 3) print(my_int + my_float)

12.032258

55

0.646113

3734437b152ba33d8b52edec0724174e259d179d

3,584

py

Python

imperative/python/megengine/tools/accuracy_shake_var_tree.py

Olalaye/MegEngine

695d24f24517536e6544b07936d189dbc031bbce

[ "Apache-2.0" ]

5,168

2020-03-19T06:10:04.000Z

2022-03-31T11:11:54.000Z

imperative/python/megengine/tools/accuracy_shake_var_tree.py

Olalaye/MegEngine

695d24f24517536e6544b07936d189dbc031bbce

[ "Apache-2.0" ]

286

2020-03-25T01:36:23.000Z

2022-03-31T10:26:33.000Z

imperative/python/megengine/tools/accuracy_shake_var_tree.py

Olalaye/MegEngine

695d24f24517536e6544b07936d189dbc031bbce

[ "Apache-2.0" ]

515

2020-03-19T06:10:05.000Z

2022-03-30T09:15:59.000Z

#!/usr/bin/env python3 # -*-coding=utf-8-*- # This tool is used to analyze the file generated by compare_binary_iodump.py. # parse() can build a dependency tree with those varnodes # where accuracy shake occurs and show the root varnodes. # get_varNode()/get_dependence_list()/get_reference_list()/show_src_info() # are some functions which are used to query dependencies between varnodes. import argparse import os class varNode: var_node_dict = {} var_node_root_dict = {} def __init__(self, id, dependence_list, src_info): self.src_info = src_info if not id in varNode.var_node_dict.keys(): self.id = id self.dependence_list = [] self.reference_list = [] else: self = varNode.var_node_dict[id] if dependence_list: self.vitrual = False self.is_root = True else: self.vitrual = True self.is_root = False for i in dependence_list: if not i in varNode.var_node_dict.keys(): varNode.var_node_dict[i] = varNode(i, [], "") dv = varNode.var_node_dict[i] self.dependence_list.append(dv) if not dv.vitrual: self.is_root = False dv.reference_list.append(self) for i in self.reference_list: i.is_root = False varNode.var_node_root_dict.pop[i.id] if self.is_root: varNode.var_node_root_dict[id] = self varNode.var_node_dict[id] = self @staticmethod def get_varNode(id): return varNode.var_node_dict[id] def get_dependence_list(self): return self.dependence_list def get_reference_list(self): return self.reference_list def show_src_info(self): print(self.src_info) def get_dependence(string, src_info): start1 = "id:" end1 = "," e = 0 count = string.count(start1) dependence_list = [] for x in range(0, count): s = string.find(start1, e) e = string.find(end1, s) sub_str = string[s:e] if x == 0: var = sub_str else: dependence_list.append(sub_str) varNode(var, dependence_list, src_info) def parse(filename): with open(filename) as f: varNode.var_node_dict.clear() varNode.var_node_root_dict.clear() line = f.readline() s = ["", "", ""] idx = 1 while line: if line.find("not equal: ") != -1: s[2] = line src_info = s[0] + "\n" + s[1] + "\n" + s[2] get_dependence(s[0], src_info) else: if line.find("var={id:") != -1: idx = idx ^ 1 s[idx] = "" s[idx] = s[idx] + line.strip() line = f.readline() return varNode.var_node_root_dict def main(): parser = argparse.ArgumentParser( description=( "Analyze the outputs of compare_binary_iodump.py" "Should save the outputs of compare_binary_iodump.py" "as a file" ), formatter_class=argparse.ArgumentDefaultsHelpFormatter, ) parser.add_argument( "filename", help="file which save the outputs of compare_binary_iodump.py" ) args = parser.parse_args() parse(args.filename) print("varnode root:") for key, value in varNode.var_node_root_dict.items(): print(key) print("detail info:") value.show_src_info() if __name__ == "__main__": main()

27.358779

82

0.577288

672808a32edbecea6f4841e38b145440d7c0ecd4

1,197

py

Python

dlhub_sdk/utils/schemas.py

DLHub-Argonne/dlhub_sdk

9449f120490cba40fa43d4ccb06a0d1d7e78f1fd

[ "Apache-2.0" ]

24

2018-11-01T12:48:21.000Z

2021-12-30T21:19:16.000Z

dlhub_sdk/utils/schemas.py

DLHub-Argonne/dlhub_sdk

9449f120490cba40fa43d4ccb06a0d1d7e78f1fd

[ "Apache-2.0" ]

79

2018-11-27T16:41:29.000Z

2022-03-25T17:32:09.000Z

dlhub_sdk/utils/schemas.py

DLHub-Argonne/dlhub_toolbox

d8e06ba4247ebd3a955782099a4a9fa68890bea4

[ "Apache-2.0" ]

4

2019-02-27T16:23:19.000Z

2020-09-19T01:25:30.000Z

"""Utilities for validating against DLHub schemas""" from typing import Union from jsonschema import Draft7Validator, RefResolver import requests from dlhub_sdk.models import BaseMetadataModel _schema_repo = "https://raw.githubusercontent.com/DLHub-Argonne/dlhub_schemas/master/schemas/" def validate_against_dlhub_schema(document: Union[dict, BaseMetadataModel], schema_name: str): """Validate a metadata document against one of the DLHub schemas Note: Requires an internet connection Args: document: Document instance to be validated schema_name (string): Name of schema (e.g., "dataset" for validating datasets). For full list, see: https://github.com/DLHub-Argonne/dlhub_schemas Raises: (jsonschema.SchemaError) If the schema fails to validate """ # Convert to dictionary, if needed if isinstance(document, BaseMetadataModel): document = document.to_dict() # Make the schema validator schema = requests.get("{}/{}.json".format(_schema_repo, schema_name)).json() validator = Draft7Validator(schema, resolver=RefResolver(_schema_repo, schema)) # Test the document validator.validate(document)

34.2

94

0.736842

85724628b3792ced75fd57e833bd34daef742c58

475

py

Python

full-stack-angular-ngrx/backend/src/core/services/pg_data_session.py

t4d-classes/angular_02212022

152dfa4b14ee84c1c34cef0b852349b250103e3b

[ "MIT" ]

null

full-stack-angular-ngrx/backend/src/core/services/pg_data_session.py

t4d-classes/angular_02212022

152dfa4b14ee84c1c34cef0b852349b250103e3b

[ "MIT" ]

null

full-stack-angular-ngrx/backend/src/core/services/pg_data_session.py

t4d-classes/angular_02212022

152dfa4b14ee84c1c34cef0b852349b250103e3b

[ "MIT" ]

null

from sqlalchemy import create_engine from sqlalchemy.orm import sessionmaker from src.core.interfaces.data_session import DataSessionInterface class PgDataSession(DataSessionInterface): def __init__(self, url: str, name: str, user: str, password: str): engine = create_engine( f'postgresql://{user}:{password}@{url}/{name}') self.Session = sessionmaker(bind=engine) def get_session(self): return self.Session

27.941176

65

0.690526

0dd8978b9c29cc5df77b21474df7b16fd0eca5de

1,686

py

Python

eng/utils.py

Dalloriam/popeui

f3477cd546e885bc53e755b3eb1452ce43ef5697

[ "MIT" ]

30

2016-08-25T14:47:49.000Z

2017-12-20T23:01:03.000Z

eng/utils.py

dalloriam/engel

f3477cd546e885bc53e755b3eb1452ce43ef5697

[ "MIT" ]

25

2016-07-18T01:57:07.000Z

2016-08-24T18:33:54.000Z

eng/utils.py

dalloriam/engel

f3477cd546e885bc53e755b3eb1452ce43ef5697

[ "MIT" ]

5

2016-08-26T12:54:42.000Z

2017-09-17T00:08:26.000Z

import os from jinja2 import Template from eng.logging import error, success def create_folder(folder_path): if os.path.isdir(folder_path): error("Directory {dirName} already exists.".format(dirName=os.path.abspath(folder_path))) os.mkdir(folder_path) success(os.path.abspath(folder_path) + "/") def write_file(file_path, content): if os.path.isdir(file_path): error("File {filePath} already exists.").format(filePath=os.path.abspath(file_path)) with open(file_path, "a") as outfile: outfile.write(content) success(os.path.abspath(file_path)) def read_template(template): template_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), "templates") filename = template + ".template" template_file = os.path.join(template_dir, filename) if not os.path.isfile(template_file): error("Unknown template file ({tmpl}).".format(tmpl=filename)) data = None with open(template_file, "rU") as infile: data = infile.read() return Template(data) def render_app(app_name): template = read_template("app") ccName = app_name.replace('_', ' ').title().replace(' ', '') return template.render(appCamelCase=ccName) def render_view(view_name): template = read_template("view") view_title = view_name.replace('_', ' ').title().replace(' ', '') view_camel = view_title + 'View' return template.render(viewCamelCase=view_camel, viewTitle=view_title) def render_service(service_name): template = read_template("service") svc_camel = service_name.replace('_', ' ').title().replace(' ', '') + 'Service' return template.render(serviceCamelCase=svc_camel)

30.654545

97

0.69395

cc71595b8bbf92207b50b99a748848dac230bf4e

500

py

Python

plotly/validators/histogram/marker/colorbar/_tick0.py

faezs/plotly.py

6009b5b9c746e5d2a2849ad255a4eb234b551ed7

[ "MIT" ]

2

2020-03-24T11:41:14.000Z

2021-01-14T07:59:43.000Z

plotly/validators/histogram/marker/colorbar/_tick0.py

faezs/plotly.py

6009b5b9c746e5d2a2849ad255a4eb234b551ed7

[ "MIT" ]

null

plotly/validators/histogram/marker/colorbar/_tick0.py

faezs/plotly.py

6009b5b9c746e5d2a2849ad255a4eb234b551ed7

[ "MIT" ]

4

2019-06-03T14:49:12.000Z

2022-01-06T01:05:12.000Z

import _plotly_utils.basevalidators class Tick0Validator(_plotly_utils.basevalidators.AnyValidator): def __init__( self, plotly_name='tick0', parent_name='histogram.marker.colorbar', **kwargs ): super(Tick0Validator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type='colorbars', implied_edits={'tickmode': 'linear'}, role='style', **kwargs )

25

64

0.594

dc6d551743c6ad44bc972f07050291cf490441bb

374

py

Python

Catkin_PKG_Car/build/race_robot/catkin_generated/pkg.installspace.context.pc.py

jessecha/OPCAS

2b51543b4ad1ee37dba2e45a0c7d0b872309d418

[ "MIT" ]

1

2021-02-28T05:58:50.000Z

Catkin_PKG_Car/build/race_robot/catkin_generated/pkg.installspace.context.pc.py

jessecha/OPCAS

2b51543b4ad1ee37dba2e45a0c7d0b872309d418

[ "MIT" ]

null

Catkin_PKG_Car/build/race_robot/catkin_generated/pkg.installspace.context.pc.py

jessecha/OPCAS

2b51543b4ad1ee37dba2e45a0c7d0b872309d418

[ "MIT" ]

null

# generated from catkin/cmake/template/pkg.context.pc.in CATKIN_PACKAGE_PREFIX = "" PROJECT_PKG_CONFIG_INCLUDE_DIRS = "".split(';') if "" != "" else [] PROJECT_CATKIN_DEPENDS = "".replace(';', ' ') PKG_CONFIG_LIBRARIES_WITH_PREFIX = "".split(';') if "" != "" else [] PROJECT_NAME = "race_robot" PROJECT_SPACE_DIR = "/home/nvidia/catkin_ws/install" PROJECT_VERSION = "0.0.0"

41.555556

68

0.705882

3fd63e1d10600a20b76c274d31c46bbb2f7fff83

631

py

Python

src/global_get_latent.py

P2Oileen/oh-my-face

b73cb8ea713205bbf2bc1408145fa668c715359b

[ "MIT" ]

45

2021-12-20T07:49:17.000Z

2022-03-18T17:08:30.000Z

src/global_get_latent.py

P2Oileen/oh-my-face

b73cb8ea713205bbf2bc1408145fa668c715359b

[ "MIT" ]

null

src/global_get_latent.py

P2Oileen/oh-my-face

b73cb8ea713205bbf2bc1408145fa668c715359b

[ "MIT" ]

null

from cog_predict import get_latent_code import cv2 import argparse import torch parser = argparse.ArgumentParser(description='Process Options.') parser.add_argument('--input_dir', default='input.jpg', type=str) parser.add_argument('--data_type', default='face', type=str) #[face, cat] parser.add_argument('--weight_dir', default='./weights', type=str) args = parser.parse_args() img = cv2.imread(args.input_dir) latent,img = get_latent_code(img, args.data_type, args.weight_dir) latent = latent.unsqueeze(0) print(latent.shape) print("print aligned image:",cv2.imwrite("input_aligned.jpg",img)) torch.save(latent,"tmp_latent.pt")

37.117647

73

0.773376

613a67a11ccf95894141c3d36685b8bd82d00fd0

58

py

Python

flavio/physics/edms/__init__.py

jasonaebischerGIT/flavio

b8d833c8380c619112ed75175cb7db52b788b1cd

[ "MIT" ]

null

flavio/physics/edms/__init__.py

jasonaebischerGIT/flavio

b8d833c8380c619112ed75175cb7db52b788b1cd

[ "MIT" ]

null

flavio/physics/edms/__init__.py

jasonaebischerGIT/flavio

b8d833c8380c619112ed75175cb7db52b788b1cd

[ "MIT" ]

null

r"""Electric dipole moments.""" from . import neutronedm

14.5

31

0.724138

21ab7aff8e27cf2dfd4fd785c56d30b37a749332

516

py

Python

configurator/missile/classes/PersistenceStrategy.py

ClockworkOrigins/m2etis

3b9c0f98c172f48889e75fe0b80a61a0e47670f5

[ "Apache-2.0" ]

2

2016-01-24T22:08:27.000Z

2017-01-01T13:06:44.000Z

configurator/missile/classes/PersistenceStrategy.py

ClockworkOrigins/m2etis

3b9c0f98c172f48889e75fe0b80a61a0e47670f5

[ "Apache-2.0" ]

null

configurator/missile/classes/PersistenceStrategy.py

ClockworkOrigins/m2etis

3b9c0f98c172f48889e75fe0b80a61a0e47670f5

[ "Apache-2.0" ]

null

import copy import logging from strategy import Strategy logging.basicConfig(level=logging.INFO) LOG = logging.getLogger(__name__) class PersistenceStrategy(Strategy): def __init__(self, strategy): self.__dict__ = copy.deepcopy(strategy.__dict__) def compatible(self, event): if event is None: return True if event.dimensions["persistency"]["enabled"] == self.classification["description"]["enabled"]: return True else: return False

23.454545

103

0.670543

9d67d91f6844786c8bf5b84f3c6a90ee733b9574

210

py

Python

chartpy/__init__.py

Joukahainen/chartpy

410f9e4553cb07be7d11823cad404f10da079ada

[ "Apache-2.0" ]

519

2016-08-17T10:38:58.000Z

2022-03-30T19:30:15.000Z

chartpy/__init__.py

distagon/chartpy

39282158cdb6bbddba1ea1d5faa9ff182c3ceb39

[ "Apache-2.0" ]

5

2016-08-21T22:16:17.000Z

2019-12-06T06:17:13.000Z

chartpy/__init__.py

distagon/chartpy

39282158cdb6bbddba1ea1d5faa9ff182c3ceb39

[ "Apache-2.0" ]

108

2016-08-21T12:01:10.000Z

2022-03-25T06:38:58.000Z

__author__ = 'saeedamen' from chartpy.chart import Chart from chartpy.style import Style from chartpy.canvas import Canvas from chartpy.chartconstants import ChartConstants from chartpy.twitter import Twitter

26.25

49

0.847619

09cc0ee75bb333141c9a82af2ffabac227365dda

11,780

py

Python

app/DataCollection/models.py

RohitKochhar/FTU-Django-Dashboard

4015969058184ed9f11c48915ed1515b4524f46a

[ "Apache-2.0" ]

null

app/DataCollection/models.py

RohitKochhar/FTU-Django-Dashboard

4015969058184ed9f11c48915ed1515b4524f46a

[ "Apache-2.0" ]

null

app/DataCollection/models.py

RohitKochhar/FTU-Django-Dashboard

4015969058184ed9f11c48915ed1515b4524f46a

[ "Apache-2.0" ]

null

################################################################################ # File Name: models.py # # File Author: Rohit Singh # # File Description: # This file defines models used # in our database # # File History: # 2020-11-05: Result model added by Rohit # 2020-11-02: Created by Rohit # ################################################################################ # Imports --------------------------------------------------------------------- # Django imports from django.db import models from django.conf import settings # Python imports import numpy as np import os import json import paho.mqtt.client as mqtt # Class Definitions------------------------------------------------------------- class TestConfiguration(models.Model): # Constants i_MinimumTemperature = 0 i_MaximumTemperature = 125 i_MinimumVoltage = -50 i_MaximumVoltage = 50 i_MinimumField = 0 i_MaximumField = 50 i_MinimumTestTime = 0 i_MaximumTestTime = 1000 # Variables i_TestId = models.IntegerField(default=0) s_TestDesc = models.CharField(max_length=200, default="Default Test") i_DesiredTemp = models.IntegerField(default=0) i_DesiredVoltage = models.IntegerField(default=0) i_DesiredField = models.IntegerField(default=0) i_DesiredTestTime = models.IntegerField(default=0) i_DesiredSerialRate = models.IntegerField(default=9600) ############################################################################ # Function Name: save # Function Description: Checks inputs before saving # Inputs: (self) | Output: either ValueError or a saved object # Function History: # 2020-11-08: Created by Rohit ############################################################################ def save(self, *args, **kwargs): # Check i_TestId uniqueness try: b_TestIdIsUnique = False tc = TestConfiguration.objects.get(i_TestId = self.i_TestId) except Exception as e: if type(e) == self.DoesNotExist: # No object was found with this unique b_TestIdIsUnique = True if b_TestIdIsUnique == False: raise ValueError(f"Test ID: {self.i_TestId} is already in use") if self.i_TestId < 0: raise ValueError("Test ID must be a positive integer") if self.i_DesiredTemp < self.i_MinimumTemperature or self.i_DesiredTemp > self.i_MaximumTemperature: raise ValueError(f"Temperature must be between {self.i_MinimumTemperature} and {self.i_MaximumTemperature}") if self.i_DesiredVoltage < self.i_MinimumVoltage or self.i_DesiredVoltage > self.i_MaximumVoltage: raise ValueError(f"Voltage must be between {self.i_MinimumVoltage} and {self.i_MaximumVoltage}") if self.i_DesiredField < self.i_MinimumField or self.i_DesiredField > self.i_MaximumField: raise ValueError(f"Magnetic Field must be betten {self.i_MinimumField} and {self.i_MaximumField}") if self.i_DesiredTestTime < self.i_MinimumTestTime or self.i_DesiredTestTime > self.i_MaximumTestTime: raise ValueError(f"Test time must be between {self.i_MinimumTestTime} and {self.i_MaximumTestTime}") # TODO: Fix this thang if self.i_DesiredSerialRate != 9600: raise ValueError("Serial Rate must be 9600") super().save(*args, **kwargs) ############################################################################ # Function Name: GetJSONInstructions # Function Description: Returns the JSON object to be sent to board # Inputs: (self) | Output: JSON instructions to be sent # Function History: # 2020-11-05: Created by Rohit ############################################################################ def GetJSONInstructions(self): test_values = { 'temperature': self.i_DesiredTemp, 'v_stress': self.i_DesiredVoltage, 'test_time': self.i_DesiredTestTime, 'magnetic_field': self.i_DesiredField, 'Test_start': 1, 'Test_stop': 0, 'serial_rate': self.i_DesiredSerialRate, } measurement_params = { 'temperature': {"unit": "C"}, 'v_stress': {'unit': 'mV'}, 'test_time': {'unit': 'seconds'}, 'magnetic_field': {'unit': "mT"}, 'serial_rate': {'unit':'milliseconds'} } instructions = { 'id': self.i_TestId, 'description': self.s_TestDesc, 'test_values': test_values, 'measurement_params': measurement_params, } js_instructions = json.dumps(instructions) return js_instructions ############################################################################ # Function Name: SendJsonInstructions # Function Description: Sends the MQTT packet to broker # Inputs: (self) | Output: Sent object # Function History: # 2020-11-12: Created by Rohit ############################################################################ def SendJsonInstructions(self): # Use Built-in method to retreive JSON instructions s_Inst = self.GetJSONInstructions() # Create MQTT client client = mqtt.Client() # Connect to the wireless broker client.connect("35.173.190.207", 1883, 60) # Publish the message to topic s_Topic = "test" client.publish(s_Topic, payload=s_Inst, qos=0, retain = False) # Save some memory by deleting the client del client return ############################################################################ # Function Name: ___str___ # Function Description: Returns the objects identity string # Inputs: (self) | Output: "ID: 0, Description: Vibe Check" # Function History: # 2020-11-02: Created by Rohit ############################################################################ def __str__(self): return f"ID: {self.i_TestId}, Description: {self.s_TestDesc}" class Experiment(models.Model): i_ExperimentId = models.IntegerField(default=0) s_ExperimentName = models.CharField(max_length=200, default="Default Experiment") i_IterationNo = models.IntegerField(default=0) d_Date = models.DateTimeField('Trial Date') m_TestConfiguration = models.ForeignKey(TestConfiguration, on_delete=models.CASCADE) s_ResultsFile = models.CharField(max_length=100, default="SampleTest.csv") s_EmailAddress = models.CharField(max_length=100, default='IvanovFTU2020@gmail.com') ############################################################################ # Function Name: save # Function Description: Checks inputs before saving # Inputs: (self) | Output: either ValueError or a saved object # Function History: # 2020-11-09: Created by Rohit ############################################################################ def save(self, *args, **kwargs): # Check i_ExperimentId uniqueness try: b_ExperimentIdIsUnique = False exp = Experiment.objects.get(i_ExperimentId = self.i_ExperimentId) except Exception as e: if type(e) == self.DoesNotExist: # No object was found with this unique b_ExperimentIdIsUnique = True if b_ExperimentIdIsUnique == False: raise ValueError(f"Experiment ID: {self.i_ExperimentId} is already in use") if self.i_ExperimentId < 0: raise ValueError(f"Experiment ID: {self.i_ExperimentId} is invalid. (ID must be a positive integer)") super().save(*args, **kwargs) ############################################################################ # Function Name: ___str___ # Function Description: Returns the objects identity string # Inputs: (self) | Output: "ID: 0, (04/19/1999) Name: Vibe Check" # Function History: # 2020-11-02: Created by Rohit ############################################################################ def __str__(self): return f"ID: {self.i_ExperimentId}, ({str(self.d_Date.month)}/{str(self.d_Date.day)}/{str(self.d_Date.year)}) Name: {self.s_ExperimentName}" class Result(models.Model): # Pre-defined variables i_ColumnIdx = 0 # User defined variables s_FileName = models.CharField(max_length=200, default="SampleTest.csv") ############################################################################ # Function Name: save # Function Description: Checks inputs before saving # Inputs: (self) | Output: either ValueError or a saved object # Function History: # 2020-11-08: Created by Rohit ############################################################################ def save(self, *args, **kwargs): # Reset the column index whenever we save i_ColumnIdx = 0 # TODO: Add a uniqueness check here to ensure you can't create a duplicate # model (blocked until SampleTest simulations are resolved) super().save(*args, **kwargs) ############################################################################ # Function Name: LoadResultsFilepath # Function Description: Returns the associated csv file's path # Inputs: (self) | Output: './DataCollection/TestResults/SampleTest.csv' # Function History: # 2020-11-05: Created by Rohit ############################################################################ def LoadResultsFilepath(self): s_FilePath = os.path.join(settings.MEDIA_ROOT, './DataCollection/TestResults/' + self.s_FileName) if os.path.exists(s_FilePath): return s_FilePath else: return -1 ############################################################################ # Function Name: LoadResultsAsMatrix # Function Description: Returns a matrix of the experiments findings # Inputs: (self) | Output: M_data # Function History: # 2020-11-05: Created by Rohit ############################################################################ def LoadResultsAsMatrix(self): s_csvFilePath = self.LoadResultsFilepath() M_data = np.genfromtxt(s_csvFilePath, delimiter=',', dtype=None, encoding='utf8') return M_data ############################################################################ # Function Name: GetColumnByIndex # Function Description: Returns the nth column of the matrix # The nth column is assigned by m_Result.i_ColumnIdx # Inputs: (self) | all rows of the ith column # Function History: # 2020-11-05: Created by Rohit ############################################################################ def GetColumnByIndex(self): M_data = self.LoadResultsAsMatrix() return M_data[:,self.i_ColumnIdx] ############################################################################ # Function Name: ___str___ # Function Description: Returns the objects identity string # Inputs: (self) | Output: "SampleTest.csv" # Function History: # 2020-11-05: Created by Rohit ############################################################################ def __str__(self): return f"{self.s_FileName}"

45.836576

148

0.521902

f14097d8b129653ff56adc6c32ccac5f0fccc066

92,214

py

Python

test/unit/common/test_db.py

CiscoSystems/swift

d5067017f0509129d8d3e41aeff5d7c2a634643e

[ "Apache-2.0" ]

null

test/unit/common/test_db.py

CiscoSystems/swift

d5067017f0509129d8d3e41aeff5d7c2a634643e

[ "Apache-2.0" ]

null

test/unit/common/test_db.py

CiscoSystems/swift

d5067017f0509129d8d3e41aeff5d7c2a634643e

[ "Apache-2.0" ]

null

# Copyright (c) 2010-2012 OpenStack, LLC. # # 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. """ Tests for swift.common.db """ from __future__ import with_statement import hashlib import os import unittest from shutil import rmtree, copy from StringIO import StringIO from time import sleep, time from uuid import uuid4 import simplejson import sqlite3 import swift.common.db from swift.common.db import AccountBroker, chexor, ContainerBroker, \ DatabaseBroker, DatabaseConnectionError, dict_factory, get_db_connection from swift.common.utils import normalize_timestamp from swift.common.exceptions import LockTimeout class TestDatabaseConnectionError(unittest.TestCase): def test_str(self): err = \ DatabaseConnectionError(':memory:', 'No valid database connection') self.assert_(':memory:' in str(err)) self.assert_('No valid database connection' in str(err)) err = DatabaseConnectionError(':memory:', 'No valid database connection', timeout=1357) self.assert_(':memory:' in str(err)) self.assert_('No valid database connection' in str(err)) self.assert_('1357' in str(err)) class TestDictFactory(unittest.TestCase): def test_normal_case(self): conn = sqlite3.connect(':memory:') conn.execute('CREATE TABLE test (one TEXT, two INTEGER)') conn.execute('INSERT INTO test (one, two) VALUES ("abc", 123)') conn.execute('INSERT INTO test (one, two) VALUES ("def", 456)') conn.commit() curs = conn.execute('SELECT one, two FROM test') self.assertEquals(dict_factory(curs, curs.next()), {'one': 'abc', 'two': 123}) self.assertEquals(dict_factory(curs, curs.next()), {'one': 'def', 'two': 456}) class TestChexor(unittest.TestCase): def test_normal_case(self): self.assertEquals(chexor('d41d8cd98f00b204e9800998ecf8427e', 'new name', normalize_timestamp(1)), '4f2ea31ac14d4273fe32ba08062b21de') def test_invalid_old_hash(self): self.assertRaises(TypeError, chexor, 'oldhash', 'name', normalize_timestamp(1)) def test_no_name(self): self.assertRaises(Exception, chexor, 'd41d8cd98f00b204e9800998ecf8427e', None, normalize_timestamp(1)) class TestGetDBConnection(unittest.TestCase): def test_normal_case(self): conn = get_db_connection(':memory:') self.assert_(hasattr(conn, 'execute')) def test_invalid_path(self): self.assertRaises(DatabaseConnectionError, get_db_connection, 'invalid database path / name') class TestDatabaseBroker(unittest.TestCase): def setUp(self): self.testdir = os.path.join(os.path.dirname(__file__), 'db') rmtree(self.testdir, ignore_errors=1) os.mkdir(self.testdir) def test_DB_PREALLOCATION_setting(self): u = uuid4().hex b = DatabaseBroker(u) self.assertRaises(OSError, b._preallocate) swift.common.db.DB_PREALLOCATION = False b._preallocate() def tearDown(self): rmtree(self.testdir, ignore_errors=1) def test_memory_db_init(self): broker = DatabaseBroker(':memory:') self.assertEqual(broker.db_file, ':memory:') self.assertRaises(AttributeError, broker.initialize, normalize_timestamp('0')) def test_disk_db_init(self): db_file = os.path.join(self.testdir, '1.db') broker = DatabaseBroker(db_file) self.assertEqual(broker.db_file, db_file) self.assert_(broker.conn is None) def test_initialize(self): self.assertRaises(AttributeError, DatabaseBroker(':memory:').initialize, normalize_timestamp('1')) stub_dict = {} def stub(*args, **kwargs): for key in stub_dict.keys(): del stub_dict[key] stub_dict['args'] = args for key, value in kwargs.items(): stub_dict[key] = value broker = DatabaseBroker(':memory:') broker._initialize = stub broker.initialize(normalize_timestamp('1')) self.assert_(hasattr(stub_dict['args'][0], 'execute')) self.assertEquals(stub_dict['args'][1], '0000000001.00000') with broker.get() as conn: conn.execute('SELECT * FROM outgoing_sync') conn.execute('SELECT * FROM incoming_sync') broker = DatabaseBroker(os.path.join(self.testdir, '1.db')) broker._initialize = stub broker.initialize(normalize_timestamp('1')) self.assert_(hasattr(stub_dict['args'][0], 'execute')) self.assertEquals(stub_dict['args'][1], '0000000001.00000') with broker.get() as conn: conn.execute('SELECT * FROM outgoing_sync') conn.execute('SELECT * FROM incoming_sync') def test_delete_db(self): def init_stub(conn, put_timestamp): conn.execute('CREATE TABLE test (one TEXT)') conn.execute('CREATE TABLE test_stat (id TEXT)') conn.execute('INSERT INTO test_stat (id) VALUES (?)', (str(uuid4),)) conn.execute('INSERT INTO test (one) VALUES ("1")') conn.commit() stub_called = [False] def delete_stub(*a, **kw): stub_called[0] = True broker = DatabaseBroker(':memory:') broker.db_type = 'test' broker._initialize = init_stub # Initializes a good broker for us broker.initialize(normalize_timestamp('1')) self.assert_(broker.conn is not None) broker._delete_db = delete_stub stub_called[0] = False broker.delete_db('2') self.assert_(stub_called[0]) broker = DatabaseBroker(os.path.join(self.testdir, '1.db')) broker.db_type = 'test' broker._initialize = init_stub broker.initialize(normalize_timestamp('1')) broker._delete_db = delete_stub stub_called[0] = False broker.delete_db('2') self.assert_(stub_called[0]) # ensure that metadata was cleared m2 = broker.metadata self.assert_(not any(v[0] for v in m2.itervalues())) self.assert_(all(v[1] == normalize_timestamp('2') for v in m2.itervalues())) def test_get(self): broker = DatabaseBroker(':memory:') got_exc = False try: with broker.get() as conn: conn.execute('SELECT 1') except Exception: got_exc = True broker = DatabaseBroker(os.path.join(self.testdir, '1.db')) got_exc = False try: with broker.get() as conn: conn.execute('SELECT 1') except Exception: got_exc = True self.assert_(got_exc) def stub(*args, **kwargs): pass broker._initialize = stub broker.initialize(normalize_timestamp('1')) with broker.get() as conn: conn.execute('CREATE TABLE test (one TEXT)') try: with broker.get() as conn: conn.execute('INSERT INTO test (one) VALUES ("1")') raise Exception('test') conn.commit() except Exception: pass broker = DatabaseBroker(os.path.join(self.testdir, '1.db')) with broker.get() as conn: self.assertEquals( [r[0] for r in conn.execute('SELECT * FROM test')], []) with broker.get() as conn: conn.execute('INSERT INTO test (one) VALUES ("1")') conn.commit() broker = DatabaseBroker(os.path.join(self.testdir, '1.db')) with broker.get() as conn: self.assertEquals( [r[0] for r in conn.execute('SELECT * FROM test')], ['1']) orig_renamer = swift.common.db.renamer try: swift.common.db.renamer = lambda a, b: b qpath = os.path.dirname(os.path.dirname(os.path.dirname( os.path.dirname(self.testdir)))) if qpath: qpath += '/quarantined/tests/db' else: qpath = 'quarantined/tests/db' # Test malformed database copy(os.path.join(os.path.dirname(__file__), 'malformed_example.db'), os.path.join(self.testdir, '1.db')) broker = DatabaseBroker(os.path.join(self.testdir, '1.db')) broker.db_type = 'test' exc = None try: with broker.get() as conn: conn.execute('SELECT * FROM test') except Exception, err: exc = err self.assertEquals(str(exc), 'Quarantined %s to %s due to malformed database' % (self.testdir, qpath)) # Test corrupted database copy(os.path.join(os.path.dirname(__file__), 'corrupted_example.db'), os.path.join(self.testdir, '1.db')) broker = DatabaseBroker(os.path.join(self.testdir, '1.db')) broker.db_type = 'test' exc = None try: with broker.get() as conn: conn.execute('SELECT * FROM test') except Exception, err: exc = err self.assertEquals(str(exc), 'Quarantined %s to %s due to corrupted database' % (self.testdir, qpath)) finally: swift.common.db.renamer = orig_renamer def test_lock(self): broker = DatabaseBroker(os.path.join(self.testdir, '1.db'), timeout=.1) got_exc = False try: with broker.lock(): pass except Exception: got_exc = True self.assert_(got_exc) def stub(*args, **kwargs): pass broker._initialize = stub broker.initialize(normalize_timestamp('1')) with broker.lock(): pass with broker.lock(): pass broker2 = DatabaseBroker(os.path.join(self.testdir, '1.db'), timeout=.1) broker2._initialize = stub with broker.lock(): got_exc = False try: with broker2.lock(): pass except LockTimeout: got_exc = True self.assert_(got_exc) try: with broker.lock(): raise Exception('test') except Exception: pass with broker.lock(): pass def test_newid(self): broker = DatabaseBroker(':memory:') broker.db_type = 'test' broker.db_contains_type = 'test' uuid1 = str(uuid4()) def _initialize(conn, timestamp): conn.execute('CREATE TABLE test (one TEXT)') conn.execute('CREATE TABLE test_stat (id TEXT)') conn.execute('INSERT INTO test_stat (id) VALUES (?)', (uuid1,)) conn.commit() broker._initialize = _initialize broker.initialize(normalize_timestamp('1')) uuid2 = str(uuid4()) broker.newid(uuid2) with broker.get() as conn: uuids = [r[0] for r in conn.execute('SELECT * FROM test_stat')] self.assertEquals(len(uuids), 1) self.assertNotEquals(uuids[0], uuid1) uuid1 = uuids[0] points = [(r[0], r[1]) for r in conn.execute('SELECT sync_point, ' 'remote_id FROM incoming_sync WHERE remote_id = ?', (uuid2,))] self.assertEquals(len(points), 1) self.assertEquals(points[0][0], -1) self.assertEquals(points[0][1], uuid2) conn.execute('INSERT INTO test (one) VALUES ("1")') conn.commit() uuid3 = str(uuid4()) broker.newid(uuid3) with broker.get() as conn: uuids = [r[0] for r in conn.execute('SELECT * FROM test_stat')] self.assertEquals(len(uuids), 1) self.assertNotEquals(uuids[0], uuid1) uuid1 = uuids[0] points = [(r[0], r[1]) for r in conn.execute('SELECT sync_point, ' 'remote_id FROM incoming_sync WHERE remote_id = ?', (uuid3,))] self.assertEquals(len(points), 1) self.assertEquals(points[0][1], uuid3) broker.newid(uuid2) with broker.get() as conn: uuids = [r[0] for r in conn.execute('SELECT * FROM test_stat')] self.assertEquals(len(uuids), 1) self.assertNotEquals(uuids[0], uuid1) points = [(r[0], r[1]) for r in conn.execute('SELECT sync_point, ' 'remote_id FROM incoming_sync WHERE remote_id = ?', (uuid2,))] self.assertEquals(len(points), 1) self.assertEquals(points[0][1], uuid2) def test_get_items_since(self): broker = DatabaseBroker(':memory:') broker.db_type = 'test' broker.db_contains_type = 'test' def _initialize(conn, timestamp): conn.execute('CREATE TABLE test (one TEXT)') conn.execute('INSERT INTO test (one) VALUES ("1")') conn.execute('INSERT INTO test (one) VALUES ("2")') conn.execute('INSERT INTO test (one) VALUES ("3")') conn.commit() broker._initialize = _initialize broker.initialize(normalize_timestamp('1')) self.assertEquals(broker.get_items_since(-1, 10), [{'one': '1'}, {'one': '2'}, {'one': '3'}]) self.assertEquals(broker.get_items_since(-1, 2), [{'one': '1'}, {'one': '2'}]) self.assertEquals(broker.get_items_since(1, 2), [{'one': '2'}, {'one': '3'}]) self.assertEquals(broker.get_items_since(3, 2), []) self.assertEquals(broker.get_items_since(999, 2), []) def test_get_sync(self): broker = DatabaseBroker(':memory:') broker.db_type = 'test' broker.db_contains_type = 'test' uuid1 = str(uuid4()) def _initialize(conn, timestamp): conn.execute('CREATE TABLE test (one TEXT)') conn.execute('CREATE TABLE test_stat (id TEXT)') conn.execute('INSERT INTO test_stat (id) VALUES (?)', (uuid1,)) conn.execute('INSERT INTO test (one) VALUES ("1")') conn.commit() pass broker._initialize = _initialize broker.initialize(normalize_timestamp('1')) uuid2 = str(uuid4()) self.assertEquals(broker.get_sync(uuid2), -1) broker.newid(uuid2) self.assertEquals(broker.get_sync(uuid2), 1) uuid3 = str(uuid4()) self.assertEquals(broker.get_sync(uuid3), -1) with broker.get() as conn: conn.execute('INSERT INTO test (one) VALUES ("2")') conn.commit() broker.newid(uuid3) self.assertEquals(broker.get_sync(uuid2), 1) self.assertEquals(broker.get_sync(uuid3), 2) self.assertEquals(broker.get_sync(uuid2, incoming=False), -1) self.assertEquals(broker.get_sync(uuid3, incoming=False), -1) broker.merge_syncs([{'sync_point': 1, 'remote_id': uuid2}], incoming=False) self.assertEquals(broker.get_sync(uuid2), 1) self.assertEquals(broker.get_sync(uuid3), 2) self.assertEquals(broker.get_sync(uuid2, incoming=False), 1) self.assertEquals(broker.get_sync(uuid3, incoming=False), -1) broker.merge_syncs([{'sync_point': 2, 'remote_id': uuid3}], incoming=False) self.assertEquals(broker.get_sync(uuid2, incoming=False), 1) self.assertEquals(broker.get_sync(uuid3, incoming=False), 2) def test_merge_syncs(self): broker = DatabaseBroker(':memory:') def stub(*args, **kwargs): pass broker._initialize = stub broker.initialize(normalize_timestamp('1')) uuid2 = str(uuid4()) broker.merge_syncs([{'sync_point': 1, 'remote_id': uuid2}]) self.assertEquals(broker.get_sync(uuid2), 1) uuid3 = str(uuid4()) broker.merge_syncs([{'sync_point': 2, 'remote_id': uuid3}]) self.assertEquals(broker.get_sync(uuid2), 1) self.assertEquals(broker.get_sync(uuid3), 2) self.assertEquals(broker.get_sync(uuid2, incoming=False), -1) self.assertEquals(broker.get_sync(uuid3, incoming=False), -1) broker.merge_syncs([{'sync_point': 3, 'remote_id': uuid2}, {'sync_point': 4, 'remote_id': uuid3}], incoming=False) self.assertEquals(broker.get_sync(uuid2, incoming=False), 3) self.assertEquals(broker.get_sync(uuid3, incoming=False), 4) self.assertEquals(broker.get_sync(uuid2), 1) self.assertEquals(broker.get_sync(uuid3), 2) broker.merge_syncs([{'sync_point': 5, 'remote_id': uuid2}]) self.assertEquals(broker.get_sync(uuid2), 5) def test_get_replication_info(self): self.get_replication_info_tester(metadata=False) def test_get_replication_info_with_metadata(self): self.get_replication_info_tester(metadata=True) def get_replication_info_tester(self, metadata=False): broker = DatabaseBroker(':memory:', account='a') broker.db_type = 'test' broker.db_contains_type = 'test' broker_creation = normalize_timestamp(1) broker_uuid = str(uuid4()) broker_metadata = metadata and simplejson.dumps( {'Test': ('Value', normalize_timestamp(1))}) or '' def _initialize(conn, put_timestamp): if put_timestamp is None: put_timestamp = normalize_timestamp(0) conn.executescript(''' CREATE TABLE test ( ROWID INTEGER PRIMARY KEY AUTOINCREMENT, name TEXT UNIQUE, created_at TEXT ); CREATE TRIGGER test_insert AFTER INSERT ON test BEGIN UPDATE test_stat SET test_count = test_count + 1, hash = chexor(hash, new.name, new.created_at); END; CREATE TRIGGER test_update BEFORE UPDATE ON test BEGIN SELECT RAISE(FAIL, 'UPDATE not allowed; DELETE and INSERT'); END; CREATE TRIGGER test_delete AFTER DELETE ON test BEGIN UPDATE test_stat SET test_count = test_count - 1, hash = chexor(hash, old.name, old.created_at); END; CREATE TABLE test_stat ( account TEXT, created_at TEXT, put_timestamp TEXT DEFAULT '0', delete_timestamp TEXT DEFAULT '0', test_count INTEGER, hash TEXT default '00000000000000000000000000000000', id TEXT %s ); INSERT INTO test_stat (test_count) VALUES (0); ''' % (metadata and ", metadata TEXT DEFAULT ''" or "")) conn.execute(''' UPDATE test_stat SET account = ?, created_at = ?, id = ?, put_timestamp = ? ''', (broker.account, broker_creation, broker_uuid, put_timestamp)) if metadata: conn.execute('UPDATE test_stat SET metadata = ?', (broker_metadata,)) conn.commit() broker._initialize = _initialize put_timestamp = normalize_timestamp(2) broker.initialize(put_timestamp) info = broker.get_replication_info() self.assertEquals(info, {'count': 0, 'hash': '00000000000000000000000000000000', 'created_at': broker_creation, 'put_timestamp': put_timestamp, 'delete_timestamp': '0', 'max_row': -1, 'id': broker_uuid, 'metadata': broker_metadata}) insert_timestamp = normalize_timestamp(3) with broker.get() as conn: conn.execute(''' INSERT INTO test (name, created_at) VALUES ('test', ?) ''', (insert_timestamp,)) conn.commit() info = broker.get_replication_info() self.assertEquals(info, {'count': 1, 'hash': 'bdc4c93f574b0d8c2911a27ce9dd38ba', 'created_at': broker_creation, 'put_timestamp': put_timestamp, 'delete_timestamp': '0', 'max_row': 1, 'id': broker_uuid, 'metadata': broker_metadata}) with broker.get() as conn: conn.execute('DELETE FROM test') conn.commit() info = broker.get_replication_info() self.assertEquals(info, {'count': 0, 'hash': '00000000000000000000000000000000', 'created_at': broker_creation, 'put_timestamp': put_timestamp, 'delete_timestamp': '0', 'max_row': 1, 'id': broker_uuid, 'metadata': broker_metadata}) return broker def test_metadata(self): # Initializes a good broker for us broker = self.get_replication_info_tester(metadata=True) # Add our first item first_timestamp = normalize_timestamp(1) first_value = '1' broker.update_metadata({'First': [first_value, first_timestamp]}) self.assert_('First' in broker.metadata) self.assertEquals(broker.metadata['First'], [first_value, first_timestamp]) # Add our second item second_timestamp = normalize_timestamp(2) second_value = '2' broker.update_metadata({'Second': [second_value, second_timestamp]}) self.assert_('First' in broker.metadata) self.assertEquals(broker.metadata['First'], [first_value, first_timestamp]) self.assert_('Second' in broker.metadata) self.assertEquals(broker.metadata['Second'], [second_value, second_timestamp]) # Update our first item first_timestamp = normalize_timestamp(3) first_value = '1b' broker.update_metadata({'First': [first_value, first_timestamp]}) self.assert_('First' in broker.metadata) self.assertEquals(broker.metadata['First'], [first_value, first_timestamp]) self.assert_('Second' in broker.metadata) self.assertEquals(broker.metadata['Second'], [second_value, second_timestamp]) # Delete our second item (by setting to empty string) second_timestamp = normalize_timestamp(4) second_value = '' broker.update_metadata({'Second': [second_value, second_timestamp]}) self.assert_('First' in broker.metadata) self.assertEquals(broker.metadata['First'], [first_value, first_timestamp]) self.assert_('Second' in broker.metadata) self.assertEquals(broker.metadata['Second'], [second_value, second_timestamp]) # Reclaim at point before second item was deleted broker.reclaim(normalize_timestamp(3)) self.assert_('First' in broker.metadata) self.assertEquals(broker.metadata['First'], [first_value, first_timestamp]) self.assert_('Second' in broker.metadata) self.assertEquals(broker.metadata['Second'], [second_value, second_timestamp]) # Reclaim at point second item was deleted broker.reclaim(normalize_timestamp(4)) self.assert_('First' in broker.metadata) self.assertEquals(broker.metadata['First'], [first_value, first_timestamp]) self.assert_('Second' in broker.metadata) self.assertEquals(broker.metadata['Second'], [second_value, second_timestamp]) # Reclaim after point second item was deleted broker.reclaim(normalize_timestamp(5)) self.assert_('First' in broker.metadata) self.assertEquals(broker.metadata['First'], [first_value, first_timestamp]) self.assert_('Second' not in broker.metadata) class TestContainerBroker(unittest.TestCase): """ Tests for swift.common.db.ContainerBroker """ def test_creation(self): """ Test swift.common.db.ContainerBroker.__init__ """ broker = ContainerBroker(':memory:', account='a', container='c') self.assertEqual(broker.db_file, ':memory:') broker.initialize(normalize_timestamp('1')) with broker.get() as conn: curs = conn.cursor() curs.execute('SELECT 1') self.assertEqual(curs.fetchall()[0][0], 1) def test_exception(self): """ Test swift.common.db.ContainerBroker throwing a conn away after unhandled exception """ first_conn = None broker = ContainerBroker(':memory:', account='a', container='c') broker.initialize(normalize_timestamp('1')) with broker.get() as conn: first_conn = conn try: with broker.get() as conn: self.assertEquals(first_conn, conn) raise Exception('OMG') except Exception: pass self.assert_(broker.conn is None) def test_empty(self): """ Test swift.common.db.ContainerBroker.empty """ broker = ContainerBroker(':memory:', account='a', container='c') broker.initialize(normalize_timestamp('1')) self.assert_(broker.empty()) broker.put_object('o', normalize_timestamp(time()), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') self.assert_(not broker.empty()) sleep(.00001) broker.delete_object('o', normalize_timestamp(time())) self.assert_(broker.empty()) def test_reclaim(self): broker = ContainerBroker(':memory:', account='test_account', container='test_container') broker.initialize(normalize_timestamp('1')) broker.put_object('o', normalize_timestamp(time()), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') with broker.get() as conn: self.assertEquals(conn.execute( "SELECT count(*) FROM object " "WHERE deleted = 0").fetchone()[0], 1) self.assertEquals(conn.execute( "SELECT count(*) FROM object " "WHERE deleted = 1").fetchone()[0], 0) broker.reclaim(normalize_timestamp(time() - 999), time()) with broker.get() as conn: self.assertEquals(conn.execute( "SELECT count(*) FROM object " "WHERE deleted = 0").fetchone()[0], 1) self.assertEquals(conn.execute( "SELECT count(*) FROM object " "WHERE deleted = 1").fetchone()[0], 0) sleep(.00001) broker.delete_object('o', normalize_timestamp(time())) with broker.get() as conn: self.assertEquals(conn.execute( "SELECT count(*) FROM object " "WHERE deleted = 0").fetchone()[0], 0) self.assertEquals(conn.execute( "SELECT count(*) FROM object " "WHERE deleted = 1").fetchone()[0], 1) broker.reclaim(normalize_timestamp(time() - 999), time()) with broker.get() as conn: self.assertEquals(conn.execute( "SELECT count(*) FROM object " "WHERE deleted = 0").fetchone()[0], 0) self.assertEquals(conn.execute( "SELECT count(*) FROM object " "WHERE deleted = 1").fetchone()[0], 1) sleep(.00001) broker.reclaim(normalize_timestamp(time()), time()) with broker.get() as conn: self.assertEquals(conn.execute( "SELECT count(*) FROM object " "WHERE deleted = 0").fetchone()[0], 0) self.assertEquals(conn.execute( "SELECT count(*) FROM object " "WHERE deleted = 1").fetchone()[0], 0) # Test the return values of reclaim() broker.put_object('w', normalize_timestamp(time()), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') broker.put_object('x', normalize_timestamp(time()), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') broker.put_object('y', normalize_timestamp(time()), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') broker.put_object('z', normalize_timestamp(time()), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') # Test before deletion res = broker.reclaim(normalize_timestamp(time()), time()) broker.delete_db(normalize_timestamp(time())) def test_delete_object(self): """ Test swift.common.db.ContainerBroker.delete_object """ broker = ContainerBroker(':memory:', account='a', container='c') broker.initialize(normalize_timestamp('1')) broker.put_object('o', normalize_timestamp(time()), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') with broker.get() as conn: self.assertEquals(conn.execute( "SELECT count(*) FROM object " "WHERE deleted = 0").fetchone()[0], 1) self.assertEquals(conn.execute( "SELECT count(*) FROM object " "WHERE deleted = 1").fetchone()[0], 0) sleep(.00001) broker.delete_object('o', normalize_timestamp(time())) with broker.get() as conn: self.assertEquals(conn.execute( "SELECT count(*) FROM object " "WHERE deleted = 0").fetchone()[0], 0) self.assertEquals(conn.execute( "SELECT count(*) FROM object " "WHERE deleted = 1").fetchone()[0], 1) def test_put_object(self): """ Test swift.common.db.ContainerBroker.put_object """ broker = ContainerBroker(':memory:', account='a', container='c') broker.initialize(normalize_timestamp('1')) # Create initial object timestamp = normalize_timestamp(time()) broker.put_object('"{<object \'&\' name>}"', timestamp, 123, 'application/x-test', '5af83e3196bf99f440f31f2e1a6c9afe') with broker.get() as conn: self.assertEquals(conn.execute( "SELECT name FROM object").fetchone()[0], '"{<object \'&\' name>}"') self.assertEquals(conn.execute( "SELECT created_at FROM object").fetchone()[0], timestamp) self.assertEquals(conn.execute( "SELECT size FROM object").fetchone()[0], 123) self.assertEquals(conn.execute( "SELECT content_type FROM object").fetchone()[0], 'application/x-test') self.assertEquals(conn.execute( "SELECT etag FROM object").fetchone()[0], '5af83e3196bf99f440f31f2e1a6c9afe') self.assertEquals(conn.execute( "SELECT deleted FROM object").fetchone()[0], 0) # Reput same event broker.put_object('"{<object \'&\' name>}"', timestamp, 123, 'application/x-test', '5af83e3196bf99f440f31f2e1a6c9afe') with broker.get() as conn: self.assertEquals(conn.execute( "SELECT name FROM object").fetchone()[0], '"{<object \'&\' name>}"') self.assertEquals(conn.execute( "SELECT created_at FROM object").fetchone()[0], timestamp) self.assertEquals(conn.execute( "SELECT size FROM object").fetchone()[0], 123) self.assertEquals(conn.execute( "SELECT content_type FROM object").fetchone()[0], 'application/x-test') self.assertEquals(conn.execute( "SELECT etag FROM object").fetchone()[0], '5af83e3196bf99f440f31f2e1a6c9afe') self.assertEquals(conn.execute( "SELECT deleted FROM object").fetchone()[0], 0) # Put new event sleep(.00001) timestamp = normalize_timestamp(time()) broker.put_object('"{<object \'&\' name>}"', timestamp, 124, 'application/x-test', 'aa0749bacbc79ec65fe206943d8fe449') with broker.get() as conn: self.assertEquals(conn.execute( "SELECT name FROM object").fetchone()[0], '"{<object \'&\' name>}"') self.assertEquals(conn.execute( "SELECT created_at FROM object").fetchone()[0], timestamp) self.assertEquals(conn.execute( "SELECT size FROM object").fetchone()[0], 124) self.assertEquals(conn.execute( "SELECT content_type FROM object").fetchone()[0], 'application/x-test') self.assertEquals(conn.execute( "SELECT etag FROM object").fetchone()[0], 'aa0749bacbc79ec65fe206943d8fe449') self.assertEquals(conn.execute( "SELECT deleted FROM object").fetchone()[0], 0) # Put old event otimestamp = normalize_timestamp(float(timestamp) - 1) broker.put_object('"{<object \'&\' name>}"', otimestamp, 124, 'application/x-test', 'aa0749bacbc79ec65fe206943d8fe449') with broker.get() as conn: self.assertEquals(conn.execute( "SELECT name FROM object").fetchone()[0], '"{<object \'&\' name>}"') self.assertEquals(conn.execute( "SELECT created_at FROM object").fetchone()[0], timestamp) self.assertEquals(conn.execute( "SELECT size FROM object").fetchone()[0], 124) self.assertEquals(conn.execute( "SELECT content_type FROM object").fetchone()[0], 'application/x-test') self.assertEquals(conn.execute( "SELECT etag FROM object").fetchone()[0], 'aa0749bacbc79ec65fe206943d8fe449') self.assertEquals(conn.execute( "SELECT deleted FROM object").fetchone()[0], 0) # Put old delete event dtimestamp = normalize_timestamp(float(timestamp) - 1) broker.put_object('"{<object \'&\' name>}"', dtimestamp, 0, '', '', deleted=1) with broker.get() as conn: self.assertEquals(conn.execute( "SELECT name FROM object").fetchone()[0], '"{<object \'&\' name>}"') self.assertEquals(conn.execute( "SELECT created_at FROM object").fetchone()[0], timestamp) self.assertEquals(conn.execute( "SELECT size FROM object").fetchone()[0], 124) self.assertEquals(conn.execute( "SELECT content_type FROM object").fetchone()[0], 'application/x-test') self.assertEquals(conn.execute( "SELECT etag FROM object").fetchone()[0], 'aa0749bacbc79ec65fe206943d8fe449') self.assertEquals(conn.execute( "SELECT deleted FROM object").fetchone()[0], 0) # Put new delete event sleep(.00001) timestamp = normalize_timestamp(time()) broker.put_object('"{<object \'&\' name>}"', timestamp, 0, '', '', deleted=1) with broker.get() as conn: self.assertEquals(conn.execute( "SELECT name FROM object").fetchone()[0], '"{<object \'&\' name>}"') self.assertEquals(conn.execute( "SELECT created_at FROM object").fetchone()[0], timestamp) self.assertEquals(conn.execute( "SELECT deleted FROM object").fetchone()[0], 1) # Put new event sleep(.00001) timestamp = normalize_timestamp(time()) broker.put_object('"{<object \'&\' name>}"', timestamp, 123, 'application/x-test', '5af83e3196bf99f440f31f2e1a6c9afe') with broker.get() as conn: self.assertEquals(conn.execute( "SELECT name FROM object").fetchone()[0], '"{<object \'&\' name>}"') self.assertEquals(conn.execute( "SELECT created_at FROM object").fetchone()[0], timestamp) self.assertEquals(conn.execute( "SELECT size FROM object").fetchone()[0], 123) self.assertEquals(conn.execute( "SELECT content_type FROM object").fetchone()[0], 'application/x-test') self.assertEquals(conn.execute( "SELECT etag FROM object").fetchone()[0], '5af83e3196bf99f440f31f2e1a6c9afe') self.assertEquals(conn.execute( "SELECT deleted FROM object").fetchone()[0], 0) # We'll use this later sleep(.0001) in_between_timestamp = normalize_timestamp(time()) # New post event sleep(.0001) previous_timestamp = timestamp timestamp = normalize_timestamp(time()) with broker.get() as conn: self.assertEquals(conn.execute( "SELECT name FROM object").fetchone()[0], '"{<object \'&\' name>}"') self.assertEquals(conn.execute( "SELECT created_at FROM object").fetchone()[0], previous_timestamp) self.assertEquals(conn.execute( "SELECT size FROM object").fetchone()[0], 123) self.assertEquals(conn.execute( "SELECT content_type FROM object").fetchone()[0], 'application/x-test') self.assertEquals(conn.execute( "SELECT etag FROM object").fetchone()[0], '5af83e3196bf99f440f31f2e1a6c9afe') self.assertEquals(conn.execute( "SELECT deleted FROM object").fetchone()[0], 0) # Put event from after last put but before last post timestamp = in_between_timestamp broker.put_object('"{<object \'&\' name>}"', timestamp, 456, 'application/x-test3', '6af83e3196bf99f440f31f2e1a6c9afe') with broker.get() as conn: self.assertEquals(conn.execute( "SELECT name FROM object").fetchone()[0], '"{<object \'&\' name>}"') self.assertEquals(conn.execute( "SELECT created_at FROM object").fetchone()[0], timestamp) self.assertEquals(conn.execute( "SELECT size FROM object").fetchone()[0], 456) self.assertEquals(conn.execute( "SELECT content_type FROM object").fetchone()[0], 'application/x-test3') self.assertEquals(conn.execute( "SELECT etag FROM object").fetchone()[0], '6af83e3196bf99f440f31f2e1a6c9afe') self.assertEquals(conn.execute( "SELECT deleted FROM object").fetchone()[0], 0) def test_get_info(self): """ Test swift.common.db.ContainerBroker.get_info """ broker = ContainerBroker(':memory:', account='test1', container='test2') broker.initialize(normalize_timestamp('1')) info = broker.get_info() self.assertEquals(info['account'], 'test1') self.assertEquals(info['container'], 'test2') self.assertEquals(info['hash'], '00000000000000000000000000000000') info = broker.get_info() self.assertEquals(info['object_count'], 0) self.assertEquals(info['bytes_used'], 0) broker.put_object('o1', normalize_timestamp(time()), 123, 'text/plain', '5af83e3196bf99f440f31f2e1a6c9afe') info = broker.get_info() self.assertEquals(info['object_count'], 1) self.assertEquals(info['bytes_used'], 123) sleep(.00001) broker.put_object('o2', normalize_timestamp(time()), 123, 'text/plain', '5af83e3196bf99f440f31f2e1a6c9afe') info = broker.get_info() self.assertEquals(info['object_count'], 2) self.assertEquals(info['bytes_used'], 246) sleep(.00001) broker.put_object('o2', normalize_timestamp(time()), 1000, 'text/plain', '5af83e3196bf99f440f31f2e1a6c9afe') info = broker.get_info() self.assertEquals(info['object_count'], 2) self.assertEquals(info['bytes_used'], 1123) sleep(.00001) broker.delete_object('o1', normalize_timestamp(time())) info = broker.get_info() self.assertEquals(info['object_count'], 1) self.assertEquals(info['bytes_used'], 1000) sleep(.00001) broker.delete_object('o2', normalize_timestamp(time())) info = broker.get_info() self.assertEquals(info['object_count'], 0) self.assertEquals(info['bytes_used'], 0) info = broker.get_info() self.assertEquals(info['x_container_sync_point1'], -1) self.assertEquals(info['x_container_sync_point2'], -1) def test_set_x_syncs(self): broker = ContainerBroker(':memory:', account='test1', container='test2') broker.initialize(normalize_timestamp('1')) info = broker.get_info() self.assertEquals(info['x_container_sync_point1'], -1) self.assertEquals(info['x_container_sync_point2'], -1) broker.set_x_container_sync_points(1, 2) info = broker.get_info() self.assertEquals(info['x_container_sync_point1'], 1) self.assertEquals(info['x_container_sync_point2'], 2) def test_get_report_info(self): broker = ContainerBroker(':memory:', account='test1', container='test2') broker.initialize(normalize_timestamp('1')) info = broker.get_info() self.assertEquals(info['account'], 'test1') self.assertEquals(info['container'], 'test2') self.assertEquals(info['object_count'], 0) self.assertEquals(info['bytes_used'], 0) self.assertEquals(info['reported_object_count'], 0) self.assertEquals(info['reported_bytes_used'], 0) broker.put_object('o1', normalize_timestamp(time()), 123, 'text/plain', '5af83e3196bf99f440f31f2e1a6c9afe') info = broker.get_info() self.assertEquals(info['object_count'], 1) self.assertEquals(info['bytes_used'], 123) self.assertEquals(info['reported_object_count'], 0) self.assertEquals(info['reported_bytes_used'], 0) sleep(.00001) broker.put_object('o2', normalize_timestamp(time()), 123, 'text/plain', '5af83e3196bf99f440f31f2e1a6c9afe') info = broker.get_info() self.assertEquals(info['object_count'], 2) self.assertEquals(info['bytes_used'], 246) self.assertEquals(info['reported_object_count'], 0) self.assertEquals(info['reported_bytes_used'], 0) sleep(.00001) broker.put_object('o2', normalize_timestamp(time()), 1000, 'text/plain', '5af83e3196bf99f440f31f2e1a6c9afe') info = broker.get_info() self.assertEquals(info['object_count'], 2) self.assertEquals(info['bytes_used'], 1123) self.assertEquals(info['reported_object_count'], 0) self.assertEquals(info['reported_bytes_used'], 0) put_timestamp = normalize_timestamp(time()) sleep(.001) delete_timestamp = normalize_timestamp(time()) broker.reported(put_timestamp, delete_timestamp, 2, 1123) info = broker.get_info() self.assertEquals(info['object_count'], 2) self.assertEquals(info['bytes_used'], 1123) self.assertEquals(info['reported_put_timestamp'], put_timestamp) self.assertEquals(info['reported_delete_timestamp'], delete_timestamp) self.assertEquals(info['reported_object_count'], 2) self.assertEquals(info['reported_bytes_used'], 1123) sleep(.00001) broker.delete_object('o1', normalize_timestamp(time())) info = broker.get_info() self.assertEquals(info['object_count'], 1) self.assertEquals(info['bytes_used'], 1000) self.assertEquals(info['reported_object_count'], 2) self.assertEquals(info['reported_bytes_used'], 1123) sleep(.00001) broker.delete_object('o2', normalize_timestamp(time())) info = broker.get_info() self.assertEquals(info['object_count'], 0) self.assertEquals(info['bytes_used'], 0) self.assertEquals(info['reported_object_count'], 2) self.assertEquals(info['reported_bytes_used'], 1123) def test_list_objects_iter(self): """ Test swift.common.db.ContainerBroker.list_objects_iter """ broker = ContainerBroker(':memory:', account='a', container='c') broker.initialize(normalize_timestamp('1')) for obj1 in xrange(4): for obj2 in xrange(125): broker.put_object('%d/%04d' % (obj1, obj2), normalize_timestamp(time()), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') for obj in xrange(125): broker.put_object('2/0051/%04d' % obj, normalize_timestamp(time()), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') for obj in xrange(125): broker.put_object('3/%04d/0049' % obj, normalize_timestamp(time()), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') listing = broker.list_objects_iter(100, '', None, None, '') self.assertEquals(len(listing), 100) self.assertEquals(listing[0][0], '0/0000') self.assertEquals(listing[-1][0], '0/0099') listing = broker.list_objects_iter(100, '', '0/0050', None, '') self.assertEquals(len(listing), 50) self.assertEquals(listing[0][0], '0/0000') self.assertEquals(listing[-1][0], '0/0049') listing = broker.list_objects_iter(100, '0/0099', None, None, '') self.assertEquals(len(listing), 100) self.assertEquals(listing[0][0], '0/0100') self.assertEquals(listing[-1][0], '1/0074') listing = broker.list_objects_iter(55, '1/0074', None, None, '') self.assertEquals(len(listing), 55) self.assertEquals(listing[0][0], '1/0075') self.assertEquals(listing[-1][0], '2/0004') listing = broker.list_objects_iter(10, '', None, '0/01', '') self.assertEquals(len(listing), 10) self.assertEquals(listing[0][0], '0/0100') self.assertEquals(listing[-1][0], '0/0109') listing = broker.list_objects_iter(10, '', None, '0/', '/') self.assertEquals(len(listing), 10) self.assertEquals(listing[0][0], '0/0000') self.assertEquals(listing[-1][0], '0/0009') listing = broker.list_objects_iter(10, '', None, '', '/') self.assertEquals(len(listing), 4) self.assertEquals([row[0] for row in listing], ['0/', '1/', '2/', '3/']) listing = broker.list_objects_iter(10, '2', None, None, '/') self.assertEquals(len(listing), 2) self.assertEquals([row[0] for row in listing], ['2/', '3/']) listing = broker.list_objects_iter(10, '2/',None, None, '/') self.assertEquals(len(listing), 1) self.assertEquals([row[0] for row in listing], ['3/']) listing = broker.list_objects_iter(10, '2/0050', None, '2/', '/') self.assertEquals(len(listing), 10) self.assertEquals(listing[0][0], '2/0051') self.assertEquals(listing[1][0], '2/0051/') self.assertEquals(listing[2][0], '2/0052') self.assertEquals(listing[-1][0], '2/0059') listing = broker.list_objects_iter(10, '3/0045', None, '3/', '/') self.assertEquals(len(listing), 10) self.assertEquals([row[0] for row in listing], ['3/0045/', '3/0046', '3/0046/', '3/0047', '3/0047/', '3/0048', '3/0048/', '3/0049', '3/0049/', '3/0050']) broker.put_object('3/0049/', normalize_timestamp(time()), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') listing = broker.list_objects_iter(10, '3/0048', None, None, None) self.assertEquals(len(listing), 10) self.assertEquals([row[0] for row in listing], ['3/0048/0049', '3/0049', '3/0049/', '3/0049/0049', '3/0050', '3/0050/0049', '3/0051', '3/0051/0049', '3/0052', '3/0052/0049']) listing = broker.list_objects_iter(10, '3/0048', None, '3/', '/') self.assertEquals(len(listing), 10) self.assertEquals([row[0] for row in listing], ['3/0048/', '3/0049', '3/0049/', '3/0050', '3/0050/', '3/0051', '3/0051/', '3/0052', '3/0052/', '3/0053']) listing = broker.list_objects_iter(10, None, None, '3/0049/', '/') self.assertEquals(len(listing), 2) self.assertEquals([row[0] for row in listing], ['3/0049/', '3/0049/0049']) listing = broker.list_objects_iter(10, None, None, None, None, '3/0049') self.assertEquals(len(listing), 1) self.assertEquals([row[0] for row in listing], ['3/0049/0049']) listing = broker.list_objects_iter(2, None, None, '3/', '/') self.assertEquals(len(listing), 2) self.assertEquals([row[0] for row in listing], ['3/0000', '3/0000/']) listing = broker.list_objects_iter(2, None, None, None, None, '3') self.assertEquals(len(listing), 2) self.assertEquals([row[0] for row in listing], ['3/0000', '3/0001']) def test_list_objects_iter_prefix_delim(self): """ Test swift.common.db.ContainerBroker.list_objects_iter """ broker = ContainerBroker(':memory:', account='a', container='c') broker.initialize(normalize_timestamp('1')) broker.put_object('/pets/dogs/1', normalize_timestamp(0), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') broker.put_object('/pets/dogs/2', normalize_timestamp(0), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') broker.put_object('/pets/fish/a', normalize_timestamp(0), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') broker.put_object('/pets/fish/b', normalize_timestamp(0), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') broker.put_object('/pets/fish_info.txt', normalize_timestamp(0), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') broker.put_object('/snakes', normalize_timestamp(0), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') #def list_objects_iter(self, limit, marker, prefix, delimiter, path=None, # format=None): listing = broker.list_objects_iter(100, None, None, '/pets/f', '/') self.assertEquals([row[0] for row in listing], ['/pets/fish/', '/pets/fish_info.txt']) listing = broker.list_objects_iter(100, None, None, '/pets/fish', '/') self.assertEquals([row[0] for row in listing], ['/pets/fish/', '/pets/fish_info.txt']) listing = broker.list_objects_iter(100, None, None, '/pets/fish/', '/') self.assertEquals([row[0] for row in listing], ['/pets/fish/a', '/pets/fish/b']) def test_double_check_trailing_delimiter(self): """ Test swift.common.db.ContainerBroker.list_objects_iter for a container that has an odd file with a trailing delimiter """ broker = ContainerBroker(':memory:', account='a', container='c') broker.initialize(normalize_timestamp('1')) broker.put_object('a', normalize_timestamp(time()), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') broker.put_object('a/', normalize_timestamp(time()), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') broker.put_object('a/a', normalize_timestamp(time()), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') broker.put_object('a/a/a', normalize_timestamp(time()), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') broker.put_object('a/a/b', normalize_timestamp(time()), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') broker.put_object('a/b', normalize_timestamp(time()), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') broker.put_object('b', normalize_timestamp(time()), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') broker.put_object('b/a', normalize_timestamp(time()), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') broker.put_object('b/b', normalize_timestamp(time()), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') broker.put_object('c', normalize_timestamp(time()), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') listing = broker.list_objects_iter(15, None, None, None, None) self.assertEquals(len(listing), 10) self.assertEquals([row[0] for row in listing], ['a', 'a/', 'a/a', 'a/a/a', 'a/a/b', 'a/b', 'b', 'b/a', 'b/b', 'c']) listing = broker.list_objects_iter(15, None, None, '', '/') self.assertEquals(len(listing), 5) self.assertEquals([row[0] for row in listing], ['a', 'a/', 'b', 'b/', 'c']) listing = broker.list_objects_iter(15, None, None, 'a/', '/') self.assertEquals(len(listing), 4) self.assertEquals([row[0] for row in listing], ['a/', 'a/a', 'a/a/', 'a/b']) listing = broker.list_objects_iter(15, None, None, 'b/', '/') self.assertEquals(len(listing), 2) self.assertEquals([row[0] for row in listing], ['b/a', 'b/b']) def test_chexor(self): broker = ContainerBroker(':memory:', account='a', container='c') broker.initialize(normalize_timestamp('1')) broker.put_object('a', normalize_timestamp(1), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') broker.put_object('b', normalize_timestamp(2), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') hasha = hashlib.md5('%s-%s' % ('a', '0000000001.00000')).digest() hashb = hashlib.md5('%s-%s' % ('b', '0000000002.00000')).digest() hashc = ''.join(('%2x' % (ord(a)^ord(b)) for a, b in zip(hasha, hashb))) self.assertEquals(broker.get_info()['hash'], hashc) broker.put_object('b', normalize_timestamp(3), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') hashb = hashlib.md5('%s-%s' % ('b', '0000000003.00000')).digest() hashc = ''.join(('%02x' % (ord(a)^ord(b)) for a, b in zip(hasha, hashb))) self.assertEquals(broker.get_info()['hash'], hashc) def test_newid(self): """test DatabaseBroker.newid""" broker = ContainerBroker(':memory:', account='a', container='c') broker.initialize(normalize_timestamp('1')) id = broker.get_info()['id'] broker.newid('someid') self.assertNotEquals(id, broker.get_info()['id']) def test_get_items_since(self): """test DatabaseBroker.get_items_since""" broker = ContainerBroker(':memory:', account='a', container='c') broker.initialize(normalize_timestamp('1')) broker.put_object('a', normalize_timestamp(1), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') max_row = broker.get_replication_info()['max_row'] broker.put_object('b', normalize_timestamp(2), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') items = broker.get_items_since(max_row, 1000) self.assertEquals(len(items), 1) self.assertEquals(items[0]['name'], 'b') def test_sync_merging(self): """ exercise the DatabaseBroker sync functions a bit """ broker1 = ContainerBroker(':memory:', account='a', container='c') broker1.initialize(normalize_timestamp('1')) broker2 = ContainerBroker(':memory:', account='a', container='c') broker2.initialize(normalize_timestamp('1')) self.assertEquals(broker2.get_sync('12345'), -1) broker1.merge_syncs([{'sync_point': 3, 'remote_id': '12345'}]) broker2.merge_syncs(broker1.get_syncs()) self.assertEquals(broker2.get_sync('12345'), 3) def test_merge_items(self): broker1 = ContainerBroker(':memory:', account='a', container='c') broker1.initialize(normalize_timestamp('1')) broker2 = ContainerBroker(':memory:', account='a', container='c') broker2.initialize(normalize_timestamp('1')) broker1.put_object('a', normalize_timestamp(1), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') broker1.put_object('b', normalize_timestamp(2), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') id = broker1.get_info()['id'] broker2.merge_items(broker1.get_items_since( broker2.get_sync(id), 1000), id) items = broker2.get_items_since(-1, 1000) self.assertEquals(len(items), 2) self.assertEquals(['a', 'b'], sorted([rec['name'] for rec in items])) broker1.put_object('c', normalize_timestamp(3), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') broker2.merge_items(broker1.get_items_since( broker2.get_sync(id), 1000), id) items = broker2.get_items_since(-1, 1000) self.assertEquals(len(items), 3) self.assertEquals(['a', 'b', 'c'], sorted([rec['name'] for rec in items])) def test_merge_items_overwrite(self): """test DatabaseBroker.merge_items""" broker1 = ContainerBroker(':memory:', account='a', container='c') broker1.initialize(normalize_timestamp('1')) id = broker1.get_info()['id'] broker2 = ContainerBroker(':memory:', account='a', container='c') broker2.initialize(normalize_timestamp('1')) broker1.put_object('a', normalize_timestamp(2), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') broker1.put_object('b', normalize_timestamp(3), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') broker2.merge_items(broker1.get_items_since( broker2.get_sync(id), 1000), id) broker1.put_object('a', normalize_timestamp(4), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') broker2.merge_items(broker1.get_items_since( broker2.get_sync(id), 1000), id) items = broker2.get_items_since(-1, 1000) self.assertEquals(['a', 'b'], sorted([rec['name'] for rec in items])) for rec in items: if rec['name'] == 'a': self.assertEquals(rec['created_at'], normalize_timestamp(4)) if rec['name'] == 'b': self.assertEquals(rec['created_at'], normalize_timestamp(3)) def test_merge_items_post_overwrite_out_of_order(self): """test DatabaseBroker.merge_items""" broker1 = ContainerBroker(':memory:', account='a', container='c') broker1.initialize(normalize_timestamp('1')) id = broker1.get_info()['id'] broker2 = ContainerBroker(':memory:', account='a', container='c') broker2.initialize(normalize_timestamp('1')) broker1.put_object('a', normalize_timestamp(2), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') broker1.put_object('b', normalize_timestamp(3), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') broker2.merge_items(broker1.get_items_since( broker2.get_sync(id), 1000), id) broker1.put_object('a', normalize_timestamp(4), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') broker2.merge_items(broker1.get_items_since( broker2.get_sync(id), 1000), id) items = broker2.get_items_since(-1, 1000) self.assertEquals(['a', 'b'], sorted([rec['name'] for rec in items])) for rec in items: if rec['name'] == 'a': self.assertEquals(rec['created_at'], normalize_timestamp(4)) if rec['name'] == 'b': self.assertEquals(rec['created_at'], normalize_timestamp(3)) self.assertEquals(rec['content_type'], 'text/plain') items = broker2.get_items_since(-1, 1000) self.assertEquals(['a', 'b'], sorted([rec['name'] for rec in items])) for rec in items: if rec['name'] == 'a': self.assertEquals(rec['created_at'], normalize_timestamp(4)) if rec['name'] == 'b': self.assertEquals(rec['created_at'], normalize_timestamp(3)) broker1.put_object('b', normalize_timestamp(5), 0, 'text/plain', 'd41d8cd98f00b204e9800998ecf8427e') broker2.merge_items(broker1.get_items_since( broker2.get_sync(id), 1000), id) items = broker2.get_items_since(-1, 1000) self.assertEquals(['a', 'b'], sorted([rec['name'] for rec in items])) for rec in items: if rec['name'] == 'a': self.assertEquals(rec['created_at'], normalize_timestamp(4)) if rec['name'] == 'b': self.assertEquals(rec['created_at'], normalize_timestamp(5)) self.assertEquals(rec['content_type'], 'text/plain') def premetadata_create_container_stat_table(self, conn, put_timestamp=None): """ Copied from swift.common.db.ContainerBroker before the metadata column was added; used for testing with TestContainerBrokerBeforeMetadata. Create the container_stat table which is specifc to the container DB. :param conn: DB connection object :param put_timestamp: put timestamp """ if put_timestamp is None: put_timestamp = normalize_timestamp(0) conn.executescript(""" CREATE TABLE container_stat ( account TEXT, container TEXT, created_at TEXT, put_timestamp TEXT DEFAULT '0', delete_timestamp TEXT DEFAULT '0', object_count INTEGER, bytes_used INTEGER, reported_put_timestamp TEXT DEFAULT '0', reported_delete_timestamp TEXT DEFAULT '0', reported_object_count INTEGER DEFAULT 0, reported_bytes_used INTEGER DEFAULT 0, hash TEXT default '00000000000000000000000000000000', id TEXT, status TEXT DEFAULT '', status_changed_at TEXT DEFAULT '0' ); INSERT INTO container_stat (object_count, bytes_used) VALUES (0, 0); """) conn.execute(''' UPDATE container_stat SET account = ?, container = ?, created_at = ?, id = ?, put_timestamp = ? ''', (self.account, self.container, normalize_timestamp(time()), str(uuid4()), put_timestamp)) class TestContainerBrokerBeforeMetadata(TestContainerBroker): """ Tests for swift.common.db.ContainerBroker against databases created before the metadata column was added. """ def setUp(self): self._imported_create_container_stat_table = \ ContainerBroker.create_container_stat_table ContainerBroker.create_container_stat_table = \ premetadata_create_container_stat_table broker = ContainerBroker(':memory:', account='a', container='c') broker.initialize(normalize_timestamp('1')) exc = None with broker.get() as conn: try: conn.execute('SELECT metadata FROM container_stat') except BaseException, err: exc = err self.assert_('no such column: metadata' in str(exc)) def tearDown(self): ContainerBroker.create_container_stat_table = \ self._imported_create_container_stat_table broker = ContainerBroker(':memory:', account='a', container='c') broker.initialize(normalize_timestamp('1')) with broker.get() as conn: conn.execute('SELECT metadata FROM container_stat') def prexsync_create_container_stat_table(self, conn, put_timestamp=None): """ Copied from swift.common.db.ContainerBroker before the x_container_sync_point[12] columns were added; used for testing with TestContainerBrokerBeforeXSync. Create the container_stat table which is specifc to the container DB. :param conn: DB connection object :param put_timestamp: put timestamp """ if put_timestamp is None: put_timestamp = normalize_timestamp(0) conn.executescript(""" CREATE TABLE container_stat ( account TEXT, container TEXT, created_at TEXT, put_timestamp TEXT DEFAULT '0', delete_timestamp TEXT DEFAULT '0', object_count INTEGER, bytes_used INTEGER, reported_put_timestamp TEXT DEFAULT '0', reported_delete_timestamp TEXT DEFAULT '0', reported_object_count INTEGER DEFAULT 0, reported_bytes_used INTEGER DEFAULT 0, hash TEXT default '00000000000000000000000000000000', id TEXT, status TEXT DEFAULT '', status_changed_at TEXT DEFAULT '0', metadata TEXT DEFAULT '' ); INSERT INTO container_stat (object_count, bytes_used) VALUES (0, 0); """) conn.execute(''' UPDATE container_stat SET account = ?, container = ?, created_at = ?, id = ?, put_timestamp = ? ''', (self.account, self.container, normalize_timestamp(time()), str(uuid4()), put_timestamp)) class TestContainerBrokerBeforeXSync(TestContainerBroker): """ Tests for swift.common.db.ContainerBroker against databases created before the x_container_sync_point[12] columns were added. """ def setUp(self): self._imported_create_container_stat_table = \ ContainerBroker.create_container_stat_table ContainerBroker.create_container_stat_table = \ prexsync_create_container_stat_table broker = ContainerBroker(':memory:', account='a', container='c') broker.initialize(normalize_timestamp('1')) exc = None with broker.get() as conn: try: conn.execute('''SELECT x_container_sync_point1 FROM container_stat''') except BaseException, err: exc = err self.assert_('no such column: x_container_sync_point1' in str(exc)) def tearDown(self): ContainerBroker.create_container_stat_table = \ self._imported_create_container_stat_table broker = ContainerBroker(':memory:', account='a', container='c') broker.initialize(normalize_timestamp('1')) with broker.get() as conn: conn.execute('SELECT x_container_sync_point1 FROM container_stat') class TestAccountBroker(unittest.TestCase): """ Tests for swift.common.db.AccountBroker """ def test_creation(self): """ Test swift.common.db.AccountBroker.__init__ """ broker = AccountBroker(':memory:', account='a') self.assertEqual(broker.db_file, ':memory:') got_exc = False try: with broker.get() as conn: pass except Exception: got_exc = True self.assert_(got_exc) broker.initialize(normalize_timestamp('1')) with broker.get() as conn: curs = conn.cursor() curs.execute('SELECT 1') self.assertEqual(curs.fetchall()[0][0], 1) def test_exception(self): """ Test swift.common.db.AccountBroker throwing a conn away after exception """ first_conn = None broker = AccountBroker(':memory:', account='a') broker.initialize(normalize_timestamp('1')) with broker.get() as conn: first_conn = conn try: with broker.get() as conn: self.assertEquals(first_conn, conn) raise Exception('OMG') except Exception: pass self.assert_(broker.conn is None) def test_empty(self): """ Test swift.common.db.AccountBroker.empty """ broker = AccountBroker(':memory:', account='a') broker.initialize(normalize_timestamp('1')) self.assert_(broker.empty()) broker.put_container('o', normalize_timestamp(time()), 0, 0, 0) self.assert_(not broker.empty()) sleep(.00001) broker.put_container('o', 0, normalize_timestamp(time()), 0, 0) self.assert_(broker.empty()) def test_reclaim(self): broker = AccountBroker(':memory:', account='test_account') broker.initialize(normalize_timestamp('1')) broker.put_container('c', normalize_timestamp(time()), 0, 0, 0) with broker.get() as conn: self.assertEquals(conn.execute( "SELECT count(*) FROM container " "WHERE deleted = 0").fetchone()[0], 1) self.assertEquals(conn.execute( "SELECT count(*) FROM container " "WHERE deleted = 1").fetchone()[0], 0) broker.reclaim(normalize_timestamp(time() - 999), time()) with broker.get() as conn: self.assertEquals(conn.execute( "SELECT count(*) FROM container " "WHERE deleted = 0").fetchone()[0], 1) self.assertEquals(conn.execute( "SELECT count(*) FROM container " "WHERE deleted = 1").fetchone()[0], 0) sleep(.00001) broker.put_container('c', 0, normalize_timestamp(time()), 0, 0) with broker.get() as conn: self.assertEquals(conn.execute( "SELECT count(*) FROM container " "WHERE deleted = 0").fetchone()[0], 0) self.assertEquals(conn.execute( "SELECT count(*) FROM container " "WHERE deleted = 1").fetchone()[0], 1) broker.reclaim(normalize_timestamp(time() - 999), time()) with broker.get() as conn: self.assertEquals(conn.execute( "SELECT count(*) FROM container " "WHERE deleted = 0").fetchone()[0], 0) self.assertEquals(conn.execute( "SELECT count(*) FROM container " "WHERE deleted = 1").fetchone()[0], 1) sleep(.00001) broker.reclaim(normalize_timestamp(time()), time()) with broker.get() as conn: self.assertEquals(conn.execute( "SELECT count(*) FROM container " "WHERE deleted = 0").fetchone()[0], 0) self.assertEquals(conn.execute( "SELECT count(*) FROM container " "WHERE deleted = 1").fetchone()[0], 0) # Test reclaim after deletion. Create 3 test containers broker.put_container('x', 0, 0, 0, 0) broker.put_container('y', 0, 0, 0, 0) broker.put_container('z', 0, 0, 0, 0) res = broker.reclaim(normalize_timestamp(time()), time()) # self.assertEquals(len(res), 2) # self.assert_(isinstance(res, tuple)) # containers, account_name = res # self.assert_(containers is None) # self.assert_(account_name is None) # Now delete the account broker.delete_db(normalize_timestamp(time())) res = broker.reclaim(normalize_timestamp(time()), time()) # self.assertEquals(len(res), 2) # self.assert_(isinstance(res, tuple)) # containers, account_name = res # self.assertEquals(account_name, 'test_account') # self.assertEquals(len(containers), 3) # self.assert_('x' in containers) # self.assert_('y' in containers) # self.assert_('z' in containers) # self.assert_('a' not in containers) def test_delete_container(self): """ Test swift.common.db.AccountBroker.delete_container """ broker = AccountBroker(':memory:', account='a') broker.initialize(normalize_timestamp('1')) broker.put_container('o', normalize_timestamp(time()), 0, 0, 0) with broker.get() as conn: self.assertEquals(conn.execute( "SELECT count(*) FROM container " "WHERE deleted = 0").fetchone()[0], 1) self.assertEquals(conn.execute( "SELECT count(*) FROM container " "WHERE deleted = 1").fetchone()[0], 0) sleep(.00001) broker.put_container('o', 0, normalize_timestamp(time()), 0, 0) with broker.get() as conn: self.assertEquals(conn.execute( "SELECT count(*) FROM container " "WHERE deleted = 0").fetchone()[0], 0) self.assertEquals(conn.execute( "SELECT count(*) FROM container " "WHERE deleted = 1").fetchone()[0], 1) def test_get_container_timestamp(self): """ Test swift.common.db.AccountBroker.get_container_timestamp """ broker = AccountBroker(':memory:', account='a') broker.initialize(normalize_timestamp('1')) # Create initial container timestamp = normalize_timestamp(time()) broker.put_container('container_name', timestamp, 0, 0, 0) # test extant map ts = broker.get_container_timestamp('container_name') self.assertEquals(ts, timestamp) # test missing map ts = broker.get_container_timestamp('something else') self.assertEquals(ts, None) def test_put_container(self): """ Test swift.common.db.AccountBroker.put_container """ broker = AccountBroker(':memory:', account='a') broker.initialize(normalize_timestamp('1')) # Create initial container timestamp = normalize_timestamp(time()) broker.put_container('"{<container \'&\' name>}"', timestamp, 0, 0, 0) with broker.get() as conn: self.assertEquals(conn.execute( "SELECT name FROM container").fetchone()[0], '"{<container \'&\' name>}"') self.assertEquals(conn.execute( "SELECT put_timestamp FROM container").fetchone()[0], timestamp) self.assertEquals(conn.execute( "SELECT deleted FROM container").fetchone()[0], 0) # Reput same event broker.put_container('"{<container \'&\' name>}"', timestamp, 0, 0, 0) with broker.get() as conn: self.assertEquals(conn.execute( "SELECT name FROM container").fetchone()[0], '"{<container \'&\' name>}"') self.assertEquals(conn.execute( "SELECT put_timestamp FROM container").fetchone()[0], timestamp) self.assertEquals(conn.execute( "SELECT deleted FROM container").fetchone()[0], 0) # Put new event sleep(.00001) timestamp = normalize_timestamp(time()) broker.put_container('"{<container \'&\' name>}"', timestamp, 0, 0, 0) with broker.get() as conn: self.assertEquals(conn.execute( "SELECT name FROM container").fetchone()[0], '"{<container \'&\' name>}"') self.assertEquals(conn.execute( "SELECT put_timestamp FROM container").fetchone()[0], timestamp) self.assertEquals(conn.execute( "SELECT deleted FROM container").fetchone()[0], 0) # Put old event otimestamp = normalize_timestamp(float(timestamp) - 1) broker.put_container('"{<container \'&\' name>}"', otimestamp, 0, 0, 0) with broker.get() as conn: self.assertEquals(conn.execute( "SELECT name FROM container").fetchone()[0], '"{<container \'&\' name>}"') self.assertEquals(conn.execute( "SELECT put_timestamp FROM container").fetchone()[0], timestamp) self.assertEquals(conn.execute( "SELECT deleted FROM container").fetchone()[0], 0) # Put old delete event dtimestamp = normalize_timestamp(float(timestamp) - 1) broker.put_container('"{<container \'&\' name>}"', 0, dtimestamp, 0, 0) with broker.get() as conn: self.assertEquals(conn.execute( "SELECT name FROM container").fetchone()[0], '"{<container \'&\' name>}"') self.assertEquals(conn.execute( "SELECT put_timestamp FROM container").fetchone()[0], timestamp) self.assertEquals(conn.execute( "SELECT delete_timestamp FROM container").fetchone()[0], dtimestamp) self.assertEquals(conn.execute( "SELECT deleted FROM container").fetchone()[0], 0) # Put new delete event sleep(.00001) timestamp = normalize_timestamp(time()) broker.put_container('"{<container \'&\' name>}"', 0, timestamp, 0, 0) with broker.get() as conn: self.assertEquals(conn.execute( "SELECT name FROM container").fetchone()[0], '"{<container \'&\' name>}"') self.assertEquals(conn.execute( "SELECT delete_timestamp FROM container").fetchone()[0], timestamp) self.assertEquals(conn.execute( "SELECT deleted FROM container").fetchone()[0], 1) # Put new event sleep(.00001) timestamp = normalize_timestamp(time()) broker.put_container('"{<container \'&\' name>}"', timestamp, 0, 0, 0) with broker.get() as conn: self.assertEquals(conn.execute( "SELECT name FROM container").fetchone()[0], '"{<container \'&\' name>}"') self.assertEquals(conn.execute( "SELECT put_timestamp FROM container").fetchone()[0], timestamp) self.assertEquals(conn.execute( "SELECT deleted FROM container").fetchone()[0], 0) def test_get_info(self): """ Test swift.common.db.AccountBroker.get_info """ broker = AccountBroker(':memory:', account='test1') broker.initialize(normalize_timestamp('1')) info = broker.get_info() self.assertEquals(info['account'], 'test1') self.assertEquals(info['hash'], '00000000000000000000000000000000') info = broker.get_info() self.assertEquals(info['container_count'], 0) broker.put_container('c1', normalize_timestamp(time()), 0, 0, 0) info = broker.get_info() self.assertEquals(info['container_count'], 1) sleep(.00001) broker.put_container('c2', normalize_timestamp(time()), 0, 0, 0) info = broker.get_info() self.assertEquals(info['container_count'], 2) sleep(.00001) broker.put_container('c2', normalize_timestamp(time()), 0, 0, 0) info = broker.get_info() self.assertEquals(info['container_count'], 2) sleep(.00001) broker.put_container('c1', 0, normalize_timestamp(time()), 0, 0) info = broker.get_info() self.assertEquals(info['container_count'], 1) sleep(.00001) broker.put_container('c2', 0, normalize_timestamp(time()), 0, 0) info = broker.get_info() self.assertEquals(info['container_count'], 0) def test_list_containers_iter(self): """ Test swift.common.db.AccountBroker.list_containers_iter """ broker = AccountBroker(':memory:', account='a') broker.initialize(normalize_timestamp('1')) for cont1 in xrange(4): for cont2 in xrange(125): broker.put_container('%d/%04d' % (cont1, cont2), normalize_timestamp(time()), 0, 0, 0) for cont in xrange(125): broker.put_container('2/0051/%04d' % cont, normalize_timestamp(time()), 0, 0, 0) for cont in xrange(125): broker.put_container('3/%04d/0049' % cont, normalize_timestamp(time()), 0, 0, 0) listing = broker.list_containers_iter(100, '', None, None, '') self.assertEquals(len(listing), 100) self.assertEquals(listing[0][0], '0/0000') self.assertEquals(listing[-1][0], '0/0099') listing = broker.list_containers_iter(100, '', '0/0050', None, '') self.assertEquals(len(listing), 51) self.assertEquals(listing[0][0], '0/0000') self.assertEquals(listing[-1][0], '0/0050') listing = broker.list_containers_iter(100, '0/0099', None, None, '') self.assertEquals(len(listing), 100) self.assertEquals(listing[0][0], '0/0100') self.assertEquals(listing[-1][0], '1/0074') listing = broker.list_containers_iter(55, '1/0074', None, None, '') self.assertEquals(len(listing), 55) self.assertEquals(listing[0][0], '1/0075') self.assertEquals(listing[-1][0], '2/0004') listing = broker.list_containers_iter(10, '', None, '0/01', '') self.assertEquals(len(listing), 10) self.assertEquals(listing[0][0], '0/0100') self.assertEquals(listing[-1][0], '0/0109') listing = broker.list_containers_iter(10, '', None, '0/01', '/') self.assertEquals(len(listing), 10) self.assertEquals(listing[0][0], '0/0100') self.assertEquals(listing[-1][0], '0/0109') listing = broker.list_containers_iter(10, '', None, '0/', '/') self.assertEquals(len(listing), 10) self.assertEquals(listing[0][0], '0/0000') self.assertEquals(listing[-1][0], '0/0009') listing = broker.list_containers_iter(10, '', None, '', '/') self.assertEquals(len(listing), 4) self.assertEquals([row[0] for row in listing], ['0/', '1/', '2/', '3/']) listing = broker.list_containers_iter(10, '2/', None, None, '/') self.assertEquals(len(listing), 1) self.assertEquals([row[0] for row in listing], ['3/']) listing = broker.list_containers_iter(10, '', None, '2', '/') self.assertEquals(len(listing), 1) self.assertEquals([row[0] for row in listing], ['2/']) listing = broker.list_containers_iter(10, '2/0050', None, '2/', '/') self.assertEquals(len(listing), 10) self.assertEquals(listing[0][0], '2/0051') self.assertEquals(listing[1][0], '2/0051/') self.assertEquals(listing[2][0], '2/0052') self.assertEquals(listing[-1][0], '2/0059') listing = broker.list_containers_iter(10, '3/0045', None, '3/', '/') self.assertEquals(len(listing), 10) self.assertEquals([row[0] for row in listing], ['3/0045/', '3/0046', '3/0046/', '3/0047', '3/0047/', '3/0048', '3/0048/', '3/0049', '3/0049/', '3/0050']) broker.put_container('3/0049/', normalize_timestamp(time()), 0, 0, 0) listing = broker.list_containers_iter(10, '3/0048', None, None, None) self.assertEquals(len(listing), 10) self.assertEquals([row[0] for row in listing], ['3/0048/0049', '3/0049', '3/0049/', '3/0049/0049', '3/0050', '3/0050/0049', '3/0051', '3/0051/0049', '3/0052', '3/0052/0049']) listing = broker.list_containers_iter(10, '3/0048', None, '3/', '/') self.assertEquals(len(listing), 10) self.assertEquals([row[0] for row in listing], ['3/0048/', '3/0049', '3/0049/', '3/0050', '3/0050/', '3/0051', '3/0051/', '3/0052', '3/0052/', '3/0053']) listing = broker.list_containers_iter(10, None, None, '3/0049/', '/') self.assertEquals(len(listing), 2) self.assertEquals([row[0] for row in listing], ['3/0049/', '3/0049/0049']) def test_double_check_trailing_delimiter(self): """ Test swift.common.db.AccountBroker.list_containers_iter for an account that has an odd file with a trailing delimiter """ broker = AccountBroker(':memory:', account='a') broker.initialize(normalize_timestamp('1')) broker.put_container('a', normalize_timestamp(time()), 0, 0, 0) broker.put_container('a/', normalize_timestamp(time()), 0, 0, 0) broker.put_container('a/a', normalize_timestamp(time()), 0, 0, 0) broker.put_container('a/a/a', normalize_timestamp(time()), 0, 0, 0) broker.put_container('a/a/b', normalize_timestamp(time()), 0, 0, 0) broker.put_container('a/b', normalize_timestamp(time()), 0, 0, 0) broker.put_container('b', normalize_timestamp(time()), 0, 0, 0) broker.put_container('b/a', normalize_timestamp(time()), 0, 0, 0) broker.put_container('b/b', normalize_timestamp(time()), 0, 0, 0) broker.put_container('c', normalize_timestamp(time()), 0, 0, 0) listing = broker.list_containers_iter(15, None, None, None, None) self.assertEquals(len(listing), 10) self.assertEquals([row[0] for row in listing], ['a', 'a/', 'a/a', 'a/a/a', 'a/a/b', 'a/b', 'b', 'b/a', 'b/b', 'c']) listing = broker.list_containers_iter(15, None, None, '', '/') self.assertEquals(len(listing), 5) self.assertEquals([row[0] for row in listing], ['a', 'a/', 'b', 'b/', 'c']) listing = broker.list_containers_iter(15, None, None, 'a/', '/') self.assertEquals(len(listing), 4) self.assertEquals([row[0] for row in listing], ['a/', 'a/a', 'a/a/', 'a/b']) listing = broker.list_containers_iter(15, None, None, 'b/', '/') self.assertEquals(len(listing), 2) self.assertEquals([row[0] for row in listing], ['b/a', 'b/b']) def test_chexor(self): broker = AccountBroker(':memory:', account='a') broker.initialize(normalize_timestamp('1')) broker.put_container('a', normalize_timestamp(1), normalize_timestamp(0), 0, 0) broker.put_container('b', normalize_timestamp(2), normalize_timestamp(0), 0, 0) hasha = hashlib.md5('%s-%s' % ('a', '0000000001.00000-0000000000.00000-0-0') ).digest() hashb = hashlib.md5('%s-%s' % ('b', '0000000002.00000-0000000000.00000-0-0') ).digest() hashc = \ ''.join(('%02x' % (ord(a)^ord(b)) for a, b in zip(hasha, hashb))) self.assertEquals(broker.get_info()['hash'], hashc) broker.put_container('b', normalize_timestamp(3), normalize_timestamp(0), 0, 0) hashb = hashlib.md5('%s-%s' % ('b', '0000000003.00000-0000000000.00000-0-0') ).digest() hashc = \ ''.join(('%02x' % (ord(a)^ord(b)) for a, b in zip(hasha, hashb))) self.assertEquals(broker.get_info()['hash'], hashc) def test_merge_items(self): broker1 = AccountBroker(':memory:', account='a') broker1.initialize(normalize_timestamp('1')) broker2 = AccountBroker(':memory:', account='a') broker2.initialize(normalize_timestamp('1')) broker1.put_container('a', normalize_timestamp(1), 0, 0, 0) broker1.put_container('b', normalize_timestamp(2), 0, 0, 0) id = broker1.get_info()['id'] broker2.merge_items(broker1.get_items_since( broker2.get_sync(id), 1000), id) items = broker2.get_items_since(-1, 1000) self.assertEquals(len(items), 2) self.assertEquals(['a', 'b'], sorted([rec['name'] for rec in items])) broker1.put_container('c', normalize_timestamp(3), 0, 0, 0) broker2.merge_items(broker1.get_items_since( broker2.get_sync(id), 1000), id) items = broker2.get_items_since(-1, 1000) self.assertEquals(len(items), 3) self.assertEquals(['a', 'b', 'c'], sorted([rec['name'] for rec in items])) def premetadata_create_account_stat_table(self, conn, put_timestamp): """ Copied from swift.common.db.AccountBroker before the metadata column was added; used for testing with TestAccountBrokerBeforeMetadata. Create account_stat table which is specific to the account DB. :param conn: DB connection object :param put_timestamp: put timestamp """ conn.executescript(""" CREATE TABLE account_stat ( account TEXT, created_at TEXT, put_timestamp TEXT DEFAULT '0', delete_timestamp TEXT DEFAULT '0', container_count INTEGER, object_count INTEGER DEFAULT 0, bytes_used INTEGER DEFAULT 0, hash TEXT default '00000000000000000000000000000000', id TEXT, status TEXT DEFAULT '', status_changed_at TEXT DEFAULT '0' ); INSERT INTO account_stat (container_count) VALUES (0); """) conn.execute(''' UPDATE account_stat SET account = ?, created_at = ?, id = ?, put_timestamp = ? ''', (self.account, normalize_timestamp(time()), str(uuid4()), put_timestamp)) class TestAccountBrokerBeforeMetadata(TestAccountBroker): """ Tests for swift.common.db.AccountBroker against databases created before the metadata column was added. """ def setUp(self): self._imported_create_account_stat_table = \ AccountBroker.create_account_stat_table AccountBroker.create_account_stat_table = \ premetadata_create_account_stat_table broker = AccountBroker(':memory:', account='a') broker.initialize(normalize_timestamp('1')) exc = None with broker.get() as conn: try: conn.execute('SELECT metadata FROM account_stat') except BaseException, err: exc = err self.assert_('no such column: metadata' in str(exc)) def tearDown(self): AccountBroker.create_account_stat_table = \ self._imported_create_account_stat_table broker = AccountBroker(':memory:', account='a') broker.initialize(normalize_timestamp('1')) with broker.get() as conn: conn.execute('SELECT metadata FROM account_stat') if __name__ == '__main__': unittest.main()

45.22511

94

0.58245

35d14ef7657d4272430c1b7767d4d43612636748

9,851

py

Python

python/paddle/fluid/layers/metric_op.py

LWhite027/PaddleBox

b14bcdf285dd8829e11ab12cc815ac1b1ab62694

[ "Apache-2.0" ]

10

2021-05-12T07:20:32.000Z

2022-03-04T08:21:56.000Z

python/paddle/fluid/layers/metric_op.py

AFLee/Paddle

311b3b44fc7d51d4d66d90ab8a3fc0d42231afda

[ "Apache-2.0" ]

1

2021-01-25T09:40:19.000Z

python/paddle/fluid/layers/metric_op.py

AFLee/Paddle

311b3b44fc7d51d4d66d90ab8a3fc0d42231afda

[ "Apache-2.0" ]

18

2021-05-19T08:01:49.000Z

2022-02-11T03:11:32.000Z

# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """ All layers just related to metric. """ from __future__ import print_function import warnings from ..layer_helper import LayerHelper from ..initializer import Normal, Constant from ..framework import Variable, in_dygraph_mode, _varbase_creator from .. import core from ..param_attr import ParamAttr from . import nn from ..data_feeder import check_variable_and_dtype __all__ = ['accuracy', 'auc'] def accuracy(input, label, k=1, correct=None, total=None): """ accuracy layer. Refer to the https://en.wikipedia.org/wiki/Precision_and_recall This function computes the accuracy using the input and label. If the correct label occurs in top k predictions, then correct will increment by one. Note: the dtype of accuracy is determined by input. the input and label dtype can be different. Args: input(Variable): The input of accuracy layer, which is the predictions of network. A LoDTensor or Tensor with type float32,float64. The shape is ``[sample_number, class_dim]`` . label(Variable): The label of dataset. LoDTensor or Tensor with type int32,int64. The shape is ``[sample_number, 1]`` . k(int): The top k predictions for each class will be checked. Data type is int64 or int32. correct(Variable): The correct predictions count. A Tensor with type int64 or int32. total(Variable): The total entries count. A tensor with type int64 or int32. Returns: Variable: The correct rate. A Tensor with type float32. Examples: .. code-block:: python import paddle.fluid as fluid import numpy as np data = fluid.data(name="input", shape=[-1, 32, 32], dtype="float32") label = fluid.data(name="label", shape=[-1,1], dtype="int") fc_out = fluid.layers.fc(input=data, size=10) predict = fluid.layers.softmax(input=fc_out) result = fluid.layers.accuracy(input=predict, label=label, k=5) place = fluid.CPUPlace() exe = fluid.Executor(place) exe.run(fluid.default_startup_program()) x = np.random.rand(3, 32, 32).astype("float32") y = np.array([[1],[0],[1]]) output= exe.run(feed={"input": x,"label": y}, fetch_list=[result[0]]) print(output) #[array([0.6666667], dtype=float32)] """ if in_dygraph_mode(): if correct is None: correct = _varbase_creator(dtype="int32") if total is None: total = _varbase_creator(dtype="int32") topk_out, topk_indices = nn.topk(input, k=k) _acc, _, _ = core.ops.accuracy(topk_out, topk_indices, label, correct, total) return _acc helper = LayerHelper("accuracy", **locals()) check_variable_and_dtype(input, 'input', ['float16', 'float32', 'float64'], 'accuracy') topk_out, topk_indices = nn.topk(input, k=k) acc_out = helper.create_variable_for_type_inference(dtype="float32") if correct is None: correct = helper.create_variable_for_type_inference(dtype="int32") if total is None: total = helper.create_variable_for_type_inference(dtype="int32") helper.append_op( type="accuracy", inputs={ "Out": [topk_out], "Indices": [topk_indices], "Label": [label] }, outputs={ "Accuracy": [acc_out], "Correct": [correct], "Total": [total], }) return acc_out def auc(input, label, curve='ROC', num_thresholds=2**12 - 1, topk=1, slide_steps=1): r""" **Area Under the Curve (AUC) Layer** This implementation computes the AUC according to forward output and label. It is used very widely in binary classification evaluation. Note: If input label contains values other than 0 and 1, it will be cast to `bool`. Find the relevant definitions `here <https://en.wikipedia.org\ /wiki/Receiver_operating_characteristic#Area_under_the_curve>`_. There are two types of possible curves: 1. ROC: Receiver operating characteristic; 2. PR: Precision Recall Args: input(Variable): A floating-point 2D Variable, values are in the range [0, 1]. Each row is sorted in descending order. This input should be the output of topk. Typically, this Variable indicates the probability of each label. A LoDTensor or Tensor with type float32,float64. label(Variable): A 2D int Variable indicating the label of the training data. The height is batch size and width is always 1. A LoDTensor or Tensor with type int32,int64. curve(str): Curve type, can be 'ROC' or 'PR'. Default 'ROC'. num_thresholds(int): The number of thresholds to use when discretizing the roc curve. Default 200. topk(int): only topk number of prediction output will be used for auc. slide_steps: when calc batch auc, we can not only use step currently but the previous steps can be used. slide_steps=1 means use the current step, slide_steps=3 means use current step and the previous second steps, slide_steps=0 use all of the steps. Returns: Variable: A tuple representing the current AUC. The return tuple is auc_out, batch_auc_out, [ batch_stat_pos, batch_stat_neg, stat_pos, stat_neg ] Data type is Tensor, supporting float32, float64. Examples: .. code-block:: python import paddle.fluid as fluid import numpy as np data = fluid.data(name="input", shape=[-1, 32,32], dtype="float32") label = fluid.data(name="label", shape=[-1], dtype="int") fc_out = fluid.layers.fc(input=data, size=2) predict = fluid.layers.softmax(input=fc_out) result=fluid.layers.auc(input=predict, label=label) place = fluid.CPUPlace() exe = fluid.Executor(place) exe.run(fluid.default_startup_program()) x = np.random.rand(3,32,32).astype("float32") y = np.array([1,0,1]) output= exe.run(feed={"input": x,"label": y}, fetch_list=[result[0]]) print(output) #[array([0.5])] """ helper = LayerHelper("auc", **locals()) check_variable_and_dtype(input, 'input', ['float32', 'float64'], 'auc') check_variable_and_dtype(label, 'label', ['int32', 'int64'], 'auc') auc_out = helper.create_variable_for_type_inference(dtype="float64") batch_auc_out = helper.create_variable_for_type_inference(dtype="float64") # make tp, tn, fp, fn persistable, so that can accumulate all batches. # for batch auc # we create slide_step+1 buckets, the first slide_steps buckets store # historical batch-level values, and the last bucket stores the sum values of # previous slide_step buckets. # The index of bucket that the newest batch will use is determined by batch_id mod slide_steps, # and batch_id is store in the last posision of following variable batch_stat_pos = helper.create_global_variable( persistable=True, dtype='int64', shape=[(1 + slide_steps) * (num_thresholds + 1) + 1]) batch_stat_neg = helper.create_global_variable( persistable=True, dtype='int64', shape=[(1 + slide_steps) * (num_thresholds + 1) + 1]) # for global auc # Needn't maintain the batch id stat_pos = helper.create_global_variable( persistable=True, dtype='int64', shape=[1, num_thresholds + 1]) stat_neg = helper.create_global_variable( persistable=True, dtype='int64', shape=[1, num_thresholds + 1]) for var in [batch_stat_pos, batch_stat_neg, stat_pos, stat_neg]: helper.set_variable_initializer( var, Constant( value=0.0, force_cpu=False)) # Batch AUC helper.append_op( type="auc", inputs={ "Predict": [input], "Label": [label], "StatPos": [batch_stat_pos], "StatNeg": [batch_stat_neg] }, attrs={ "curve": curve, "num_thresholds": num_thresholds, "slide_steps": slide_steps }, outputs={ "AUC": [batch_auc_out], "StatPosOut": [batch_stat_pos], "StatNegOut": [batch_stat_neg] }) # Global AUC helper.append_op( type="auc", inputs={ "Predict": [input], "Label": [label], "StatPos": [stat_pos], "StatNeg": [stat_neg] }, attrs={ "curve": curve, "num_thresholds": num_thresholds, "slide_steps": 0 }, outputs={ "AUC": [auc_out], "StatPosOut": [stat_pos], "StatNegOut": [stat_neg] }) return auc_out, batch_auc_out, [ batch_stat_pos, batch_stat_neg, stat_pos, stat_neg ]

39.09127

258

0.617501

3fad4eec46ea2d6b02d515d89bff8163657fb518

739

py

Python

configs/liteflownet2/liteflownet2_pre_M4S4R4_8x1_flyingchairs_320x448.py

hologerry/mmflow

40caf064851bd95317424e31cc137c0007a2bece

[ "Apache-2.0" ]

481

2021-11-16T07:04:23.000Z

2022-03-31T22:21:21.000Z

configs/liteflownet2/liteflownet2_pre_M4S4R4_8x1_flyingchairs_320x448.py

hologerry/mmflow

40caf064851bd95317424e31cc137c0007a2bece

[ "Apache-2.0" ]

72

2021-11-16T12:25:55.000Z

2022-03-28T13:10:45.000Z

configs/liteflownet2/liteflownet2_pre_M4S4R4_8x1_flyingchairs_320x448.py

hologerry/mmflow

40caf064851bd95317424e31cc137c0007a2bece

[ "Apache-2.0" ]

48

2021-11-16T06:48:46.000Z

2022-03-30T12:46:40.000Z

_base_ = [ '../_base_/models/liteflownet2/liteflownet2_pre_M4S4R4.py', '../_base_/datasets/flyingchairs_320x448.py', '../_base_/default_runtime.py' ] optimizer = dict(type='Adam', lr=1e-4, weight_decay=0.0004, betas=(0.9, 0.999)) optimizer_config = dict(grad_clip=None) # learning policy lr_config = dict( policy='step', by_epoch=False, gamma=0.5, step=[120000, 160000, 200000]) runner = dict(type='IterBasedRunner', max_iters=240000) checkpoint_config = dict(by_epoch=False, interval=40000) evaluation = dict(interval=40000, metric='EPE') # Weights are initialized from model of previous stage load_from = 'https://download.openmmlab.com/mmflow/liteflownet2/liteflownet2_pre_M5S5R5_8x1_flyingchairs_320x448.pth' # noqa

41.055556

125

0.756428

76984a93b2c732b02e1fefb6db23bdb08a9ef297

884

py

Python

tfxc/bigquery.py

sfujiwara/tfxc

5469862e7c6bdac89edb0bd7cbc1808b8c7e7665

[ "MIT" ]

null

tfxc/bigquery.py

sfujiwara/tfxc

5469862e7c6bdac89edb0bd7cbc1808b8c7e7665

[ "MIT" ]

null

tfxc/bigquery.py

sfujiwara/tfxc

5469862e7c6bdac89edb0bd7cbc1808b8c7e7665

[ "MIT" ]

null

from google.cloud import bigquery from tfx.types.experimental.simple_artifacts import Dataset from tfx import v1 as tfx # TODO(sfujiwara): Automatically create dataset if it does not exist. @tfx.dsl.components.component def BigQueryTableGen( project: tfx.dsl.components.Parameter[str], query: tfx.dsl.components.Parameter[str], destination: tfx.dsl.components.Parameter[str], table: tfx.dsl.components.OutputArtifact[Dataset], ): """ A custom component for TFX Pipelines. Executes query and saves the result to destination table. """ table.set_string_custom_property(key="table", value=destination) client = bigquery.Client(project=project) job_config = bigquery.job.QueryJobConfig( destination=destination, write_disposition=bigquery.job.WriteDisposition.WRITE_TRUNCATE ) _ = client.query(query, job_config=job_config)

34

95

0.757919

93b98023e6d9551444c949db1eb1b44b1863a6d9

19,641

py

Python

indico/util/mdx_latex.py

EdverCompany/indico

c4b5e7b2e3a47355d850a342ed527c09334ef336

[ "MIT" ]

null

indico/util/mdx_latex.py

EdverCompany/indico

c4b5e7b2e3a47355d850a342ed527c09334ef336

[ "MIT" ]

5

2021-04-08T19:26:47.000Z

2022-01-24T16:30:18.000Z

indico/util/mdx_latex.py

EdverCompany/indico

c4b5e7b2e3a47355d850a342ed527c09334ef336

[ "MIT" ]

2

2019-02-24T17:29:10.000Z

2021-04-08T19:23:27.000Z

# This file is part of Indico. # Copyright (C) 2002 - 2021 CERN # # Indico is free software; you can redistribute it and/or # modify it under the terms of the MIT License; see the # LICENSE file for more details. """Extension to python-markdown to support LaTeX (rather than html) output. Authored by Rufus Pollock: <http://www.rufuspollock.org/> Reworked by Julian Wulfheide (ju.wulfheide@gmail.com) and Indico Project (indico-team@cern.ch) Usage: ====== 1. Command Line. A script entitled markdown2latex.py is automatically installed. For details of usage see help:: $ markdown2latex.py -h 2. As a python-markdown extension:: >>> import markdown >>> md = markdown.Markdown(None, extensions=['latex']) >>> # text is input string ... >>> latex_out = md.convert(text) 3. Directly as a module (slight inversion of std markdown extension setup):: >>> import markdown >>> import mdx_latex >>> md = markdown.Markdown() >>> latex_mdx = mdx_latex.LaTeXExtension() >>> latex_mdx.extendMarkdown(md, markdown.__dict__) >>> out = md.convert(text) History ======= Version: 1.0 (November 15, 2006) * First working version (compatible with markdown 1.5) * Includes support for tables Version: 1.1 (January 17, 2007) * Support for verbatim and images Version: 1.2 (June 2008) * Refactor as an extension. * Make into a proper python/setuptools package. * Tested with markdown 1.7 but should work with 1.6 and (possibly) 1.5 (though pre/post processor stuff not as worked out there) Version 1.3: (July 2008) * Improvements to image output (width) Version 1.3.1: (August 2009) * Tiny bugfix to remove duplicate keyword argument and set zip_safe=False * Add [width=\textwidth] by default for included images Version 2.0: (June 2011) * PEP8 cleanup * Major rework since this was broken by new Python-Markdown releases Version 2.1: (August 2013) * Add handler for non locally referenced images, hyperlinks and horizontal rules * Update math delimiters """ import os import re import textwrap import uuid from io import BytesIO from mimetypes import guess_extension from tempfile import NamedTemporaryFile from urllib.parse import urlparse from xml.etree import ElementTree as etree import markdown import requests from lxml.html import html5parser from PIL import Image from requests.exceptions import ConnectionError, InvalidURL __version__ = '2.1' start_single_quote_re = re.compile(r"""(^|\s|")'""") start_double_quote_re = re.compile(r'''(^|\s|'|`)"''') end_double_quote_re = re.compile(r'"(,|\.|\s|$)') Image.init() IMAGE_FORMAT_EXTENSIONS = {format: ext for (ext, format) in Image.EXTENSION.items()} safe_mathmode_commands = { 'above', 'abovewithdelims', 'acute', 'aleph', 'alpha', 'amalg', 'And', 'angle', 'approx', 'arccos', 'arcsin', 'arctan', 'arg', 'array', 'Arrowvert', 'arrowvert', 'ast', 'asymp', 'atop', 'atopwithdelims', 'backslash', 'backslash', 'bar', 'Bbb', 'begin', 'beta', 'bf', 'Big', 'big', 'bigcap', 'bigcirc', 'bigcup', 'Bigg', 'bigg', 'Biggl', 'biggl', 'Biggm', 'biggm', 'Biggr', 'biggr', 'Bigl', 'bigl', 'Bigm', 'bigm', 'bigodot', 'bigoplus', 'bigotimes', 'Bigr', 'bigr', 'bigsqcup', 'bigtriangledown', 'bigtriangleup', 'biguplus', 'bigvee', 'bigwedge', 'bmod', 'bot', 'bowtie', 'brace', 'bracevert', 'brack', 'breve', 'buildrel', 'bullet', 'cap', 'cases', 'cdot', 'cdotp', 'cdots', 'check', 'chi', 'choose', 'circ', 'clubsuit', 'colon', 'cong', 'coprod', 'cos', 'cosh', 'cot', 'coth', 'cr', 'csc', 'cup', 'dagger', 'dashv', 'ddagger', 'ddot', 'ddots', 'deg', 'Delta', 'delta', 'det', 'diamond', 'diamondsuit', 'dim', 'displaylines', 'displaystyle', 'div', 'dot', 'doteq', 'dots', 'dotsb', 'dotsc', 'dotsi', 'dotsm', 'dotso', 'Downarrow', 'downarrow', 'ell', 'emptyset', 'end', 'enspace', 'epsilon', 'eqalign', 'eqalignno', 'equiv', 'eta', 'exists', 'exp', 'fbox', 'flat', 'forall', 'frac', 'frak', 'frown', 'Gamma', 'gamma', 'gcd', 'ge', 'geq', 'gets', 'gg', 'grave', 'gt', 'gt', 'hat', 'hbar', 'hbox', 'hdashline', 'heartsuit', 'hline', 'hom', 'hookleftarrow', 'hookrightarrow', 'hphantom', 'hskip', 'hspace', 'Huge', 'huge', 'iff', 'iiint', 'iint', 'Im', 'imath', 'in', 'inf', 'infty', 'int', 'intop', 'iota', 'it', 'jmath', 'kappa', 'ker', 'kern', 'Lambda', 'lambda', 'land', 'langle', 'LARGE', 'Large', 'large', 'LaTeX', 'lbrace', 'lbrack', 'lceil', 'ldotp', 'ldots', 'le', 'left', 'Leftarrow', 'leftarrow', 'leftharpoondown', 'leftharpoonup', 'Leftrightarrow', 'leftrightarrow', 'leftroot', 'leq', 'leqalignno', 'lfloor', 'lg', 'lgroup', 'lim', 'liminf', 'limits', 'limsup', 'll', 'llap', 'lmoustache', 'ln', 'lnot', 'log', 'Longleftarrow', 'longleftarrow', 'Longleftrightarrow', 'longleftrightarrow', 'longmapsto', 'Longrightarrow', 'longrightarrow', 'lor', 'lower', 'lt', 'lt', 'mapsto', 'mathbb', 'mathbf', 'mathbin', 'mathcal', 'mathclose', 'mathfrak', 'mathinner', 'mathit', 'mathop', 'mathopen', 'mathord', 'mathpunct', 'mathrel', 'mathrm', 'mathscr', 'mathsf', 'mathstrut', 'mathtt', 'matrix', 'max', 'mbox', 'mid', 'middle', 'min', 'mit', 'mkern', 'mod', 'models', 'moveleft', 'moveright', 'mp', 'mskip', 'mspace', 'mu', 'nabla', 'natural', 'ne', 'nearrow', 'neg', 'negthinspace', 'neq', 'newline', 'ni', 'nolimits', 'normalsize', 'not', 'notin', 'nu', 'nwarrow', 'odot', 'oint', 'oldstyle', 'Omega', 'omega', 'omicron', 'ominus', 'oplus', 'oslash', 'otimes', 'over', 'overbrace', 'overleftarrow', 'overleftrightarrow', 'overline', 'overrightarrow', 'overset', 'overwithdelims', 'owns', 'parallel', 'partial', 'perp', 'phantom', 'Phi', 'phi', 'Pi', 'pi', 'pm', 'pmatrix', 'pmb', 'pmod', 'pod', 'Pr', 'prec', 'preceq', 'prime', 'prod', 'propto', 'Psi', 'psi', 'qquad', 'quad', 'raise', 'rangle', 'rbrace', 'rbrack', 'rceil', 'Re', 'rfloor', 'rgroup', 'rho', 'right', 'Rightarrow', 'rightarrow', 'rightharpoondown', 'rightharpoonup', 'rightleftharpoons', 'rlap', 'rm', 'rmoustache', 'root', 'S', 'scr', 'scriptscriptstyle', 'scriptsize', 'scriptstyle', 'searrow', 'sec', 'setminus', 'sf', 'sharp', 'Sigma', 'sigma', 'sim', 'simeq', 'sin', 'sinh', 'skew', 'small', 'smallint', 'smash', 'smile', 'Space', 'space', 'spadesuit', 'sqcap', 'sqcup', 'sqrt', 'sqsubseteq', 'sqsupseteq', 'stackrel', 'star', 'strut', 'subset', 'subseteq', 'succ', 'succeq', 'sum', 'sup', 'supset', 'supseteq', 'surd', 'swarrow', 'tan', 'tanh', 'tau', 'TeX', 'text', 'textbf', 'textit', 'textrm', 'textsf', 'textstyle', 'texttt', 'Theta', 'theta', 'thinspace', 'tilde', 'times', 'tiny', 'to', 'top', 'triangle', 'triangleleft', 'triangleright', 'tt', 'underbrace', 'underleftarrow', 'underleftrightarrow', 'underline', 'underrightarrow', 'underset', 'Uparrow', 'uparrow', 'Updownarrow', 'updownarrow', 'uplus', 'uproot', 'Upsilon', 'upsilon', 'varepsilon', 'varphi', 'varpi', 'varrho', 'varsigma', 'vartheta', 'vcenter', 'vdash', 'vdots', 'vec', 'vee', 'Vert', 'vert', 'vphantom', 'wedge', 'widehat', 'widetilde', 'wp', 'wr', 'Xi', 'xi', 'zeta', '\\' } class ImageURLException(Exception): pass def unescape_html_entities(text): out = text.replace('&', '&') out = out.replace('<', '<') out = out.replace('>', '>') out = out.replace('"', '"') return out def latex_escape(text, ignore_math=True, ignore_braces=False): if text is None: return '' chars = { '#': r'\#', '$': r'\$', '%': r'\%', '&': r'\&', '~': r'\~{}', '_': r'\_', '^': r'\^{}', '\\': r'\textbackslash{}', '\x0c': '', '\x0b': '' } if not ignore_braces: chars.update({ '{': r'\{', '}': r'\}'}) math_segments = [] def substitute(x): return chars[x.group()] math_placeholder = f'[*LaTeXmath-{str(uuid.uuid4())}*]' def math_replace(m): math_segments.append(m.group(0)) return math_placeholder if ignore_math: # Extract math-mode segments and replace with placeholder text = re.sub(r'\$[^\$]+\$|\$\$(^\$)\$\$', math_replace, text) pattern = re.compile('|'.join(re.escape(k) for k in chars.keys())) res = pattern.sub(substitute, text) if ignore_math: # Sanitize math-mode segments and put them back in place math_segments = list(map(sanitize_mathmode, math_segments)) res = re.sub(re.escape(math_placeholder), lambda _: '\\protect ' + math_segments.pop(0), res) return res def sanitize_mathmode(text): def _escape_unsafe_command(m): command = m.group(1) return m.group(0) if command in safe_mathmode_commands else r'\\' + command return re.sub(r'\$[a-zA-Z]+|\$', _escape_unsafe_command, text) def escape_latex_entities(text): """Escape latex reserved characters.""" out = text out = unescape_html_entities(out) out = start_single_quote_re.sub(r'\g<1>`', out) out = start_double_quote_re.sub(r'\g<1>``', out) out = end_double_quote_re.sub(r"''\g<1>", out) out = latex_escape(out) return out def unescape_latex_entities(text): """Limit ourselves as this is only used for maths stuff.""" out = text out = out.replace('\\&', '&') return out def latex_render_error(message): """Generate nice error box in LaTeX document. :param message: The error message :returns: LaTeX code for error box """ return textwrap.dedent(r''' \begin{tcolorbox}[width=\textwidth,colback=red!5!white,colframe=red!75!black,title={Indico rendering error}] \begin{verbatim}%s\end{verbatim} \end{tcolorbox}''' % latex_escape(message)) def latex_render_image(src, alt, tmpdir, strict=False): """Generate LaTeX code that includes an arbitrary image from a URL. This involves fetching the image from a web server and figuring out its MIME type. A temporary file will be created, which is not immediately deleted since it has to be included in the LaTeX code. It should be handled by the enclosing code. :param src: source URL of the image :param alt: text to use as ``alt="..."`` :param tmpdir: the directory where to put any temporary files :param strict: whether a faulty URL should break the whole process :returns: a ``(latex_code, file_path)`` tuple, containing the LaTeX code and path to the temporary image file. """ try: if urlparse(src).scheme not in ('http', 'https'): raise ImageURLException(f'URL scheme not supported: {src}') else: try: resp = requests.get(src, verify=False, timeout=5) except InvalidURL: raise ImageURLException(f"Cannot understand URL '{src}'") except (requests.Timeout, ConnectionError): raise ImageURLException(f'Problem downloading image ({src})') except requests.TooManyRedirects: raise ImageURLException(f'Too many redirects downloading image ({src})') extension = None if resp.status_code != 200: raise ImageURLException(f'[{resp.status_code}] Error fetching image') if resp.headers.get('content-type'): extension = guess_extension(resp.headers['content-type']) # as incredible as it might seem, '.jpe' will be the answer in some Python environments if extension == '.jpe': extension = '.jpg' if not extension: try: # Try to use PIL to get file type image = Image.open(BytesIO(resp.content)) # Worst case scenario, assume it's PNG extension = IMAGE_FORMAT_EXTENSIONS.get(image.format, '.png') except OSError: raise ImageURLException('Cannot read image data. Maybe not an image file?') with NamedTemporaryFile(prefix='indico-latex-', suffix=extension, dir=tmpdir, delete=False) as tempfile: tempfile.write(resp.content) except ImageURLException as exc: if strict: raise else: return latex_render_error(f'Could not include image: {exc}'), None # Using graphicx and ajustbox package for *max width* return (textwrap.dedent(r''' \begin{figure}[H] \centering \includegraphics[max width=\linewidth]{%s} \caption{%s} \end{figure} ''' % (os.path.basename(tempfile.name), latex_escape(alt))), tempfile.name) def makeExtension(configs=None): return LaTeXExtension(configs=configs) class LaTeXExtension(markdown.Extension): def __init__(self, configs=None): self.configs = configs self.reset() def extendMarkdown(self, md, md_globals): self.md = md # remove escape pattern -- \\(.*) -- as this messes up any embedded # math and we don't need to escape stuff any more for html self.md.inlinePatterns.deregister('escape') latex_tp = LaTeXTreeProcessor(self.configs) math_pp = MathTextPostProcessor() link_pp = LinkTextPostProcessor() unescape_html_pp = UnescapeHtmlTextPostProcessor() md.treeprocessors.register(latex_tp, 'latex', md.treeprocessors._priority[-1].priority - 1) md.postprocessors.register(unescape_html_pp, 'unescape_html', md.postprocessors._priority[-1].priority - 1) md.postprocessors.register(math_pp, 'math', md.postprocessors._priority[-1].priority - 1) md.postprocessors.register(link_pp, 'link', md.postprocessors._priority[-1].priority - 1) # Needed for LaTeX postprocessors not to choke on URL-encoded urls md.inlinePatterns.register(NonEncodedAutoMailPattern(markdown.inlinepatterns.AUTOMAIL_RE, md), 'automail', 110) def reset(self): pass class NonEncodedAutoMailPattern(markdown.inlinepatterns.Pattern): """Reimplementation of AutoMailPattern to avoid URL-encoded links.""" def handleMatch(self, m): el = etree.Element('a') email = self.unescape(m.group(2)) email.removeprefix('mailto:') el.text = markdown.util.AtomicString(''.join(email)) el.set('href', f'mailto:{email}') return el class LaTeXTreeProcessor(markdown.treeprocessors.Treeprocessor): def __init__(self, configs): self.configs = configs def run(self, doc): """ Walk the dom converting relevant nodes to text nodes with relevant content. """ latex_text = self.tolatex(doc) doc.clear() doc.text = latex_text def tolatex(self, ournode): buffer = '' subcontent = '' if ournode.text: subcontent += escape_latex_entities(ournode.text) for child in ournode: subcontent += self.tolatex(child) if ournode.tag == 'h1': buffer += '\n\n\\section{%s}\n' % subcontent elif ournode.tag == 'h2': buffer += '\n\n\\subsection{%s}\n' % subcontent elif ournode.tag == 'h3': buffer += '\n\\subsubsection{%s}\n' % subcontent elif ournode.tag == 'h4': buffer += '\n\\paragraph{%s}\n' % subcontent elif ournode.tag == 'hr': buffer += r'\noindent\makebox[\linewidth]{\rule{\paperwidth}{0.4pt}}' elif ournode.tag == 'ul': # no need for leading \n as one will be provided by li buffer += ''' \\begin{itemize}%s \\end{itemize} ''' % subcontent elif ournode.tag == 'ol': # no need for leading \n as one will be provided by li buffer += ''' \\begin{enumerate}%s \\end{enumerate} ''' % subcontent elif ournode.tag == 'li': buffer += ''' \\item %s''' % subcontent.strip() elif ournode.tag == 'blockquote': # use quotation rather than quote as quotation can support multiple # paragraphs buffer += ''' \\begin{quotation} %s \\end{quotation} ''' % subcontent.strip() # ignore 'code' when inside pre tags # (mkdn produces <pre><code></code></pre>) elif (ournode.tag == 'pre' or (ournode.tag == 'pre' and ournode.parentNode.tag != 'pre')): buffer += ''' \\begin{verbatim} %s \\end{verbatim} ''' % subcontent.strip() elif ournode.tag == 'q': buffer += "`%s'" % subcontent.strip() elif ournode.tag == 'p': if self.configs.get('apply_br'): subcontent = subcontent.replace('\n', '\\\\\\relax\n') buffer += '\n%s\n' % subcontent.strip() elif ournode.tag == 'strong': buffer += '\\textbf{%s}' % subcontent.strip() elif ournode.tag == 'em': buffer += '\\emph{%s}' % subcontent.strip() elif ournode.tag in ('table', 'thead', 'tbody', 'tr', 'th', 'td'): raise RuntimeError('Unexpected table in markdown data for LaTeX') elif ournode.tag == 'img': buffer += latex_render_image(ournode.get('src'), ournode.get('alt'), tmpdir=self.configs.get('tmpdir'))[0] elif ournode.tag == 'a': # this one gets escaped in convert_link_to_latex buffer += '<a href="{}">{}</a>'.format(ournode.get('href'), subcontent) else: buffer = subcontent if ournode.tail: buffer += escape_latex_entities(ournode.tail) return buffer class UnescapeHtmlTextPostProcessor(markdown.postprocessors.Postprocessor): def run(self, text): return unescape_html_entities(text) # ========================= MATH ================================= class MathTextPostProcessor(markdown.postprocessors.Postprocessor): def run(self, instr): """ Convert all math sections in {text} whether latex, asciimathml or latexmathml formatted to latex. This assumes you are using $$ as your mathematics delimiter (*not* the standard asciimathml or latexmathml delimiter). """ def repl_1(matchobj): text = unescape_latex_entities(matchobj.group(1)) tmp = text.strip() if tmp.startswith('\\[') or tmp.startswith('\\begin'): return text else: return '\\[%s\\]\n' % text def repl_2(matchobj): text = unescape_latex_entities(matchobj.group(1)) return f'${text}${matchobj.group(2)}' # $$ ..... $$ pat = re.compile(r'^\$\$([^$]*)\$\$\s*$', re.MULTILINE) out = pat.sub(repl_1, instr) # Jones, $x=3$, is ... pat3 = re.compile(r'\$([^$]+)\$(\s|$)') out = pat3.sub(repl_2, out) # # $100 million # pat2 = re.compile('([^\$])\$([^\$])') # out = pat2.sub('\g<1>\\$\g<2>', out) # some extras due to asciimathml # out = out.replace('\\lt', '<') # out = out.replace(' * ', ' \\cdot ') # out = out.replace('\\del', '\\partial') return out # ========================== LINKS ================================= class LinkTextPostProcessor(markdown.postprocessors.Postprocessor): def run(self, instr): new_blocks = [re.sub(r'<a[^>]*>([^<]+)</a>', lambda m: convert_link_to_latex(m.group(0)).strip(), block) for block in instr.split('\n\n')] return '\n\n'.join(new_blocks) def convert_link_to_latex(instr): dom = html5parser.fragment_fromstring(instr) return '\\href{%s}{%s}' % (latex_escape(dom.get('href'), ignore_math=True), dom.text)

39.360721

120

0.600071

be23dabcf4cf24016633887ccb3fc264b5227895

14,011

py

Python

linkfinder.py

storenth/LinkFinder

f23e221aed9ed9733a9e667a0a5ec1fbd881c93d

[ "MIT" ]

null

linkfinder.py

storenth/LinkFinder

f23e221aed9ed9733a9e667a0a5ec1fbd881c93d

[ "MIT" ]

null

linkfinder.py

storenth/LinkFinder

f23e221aed9ed9733a9e667a0a5ec1fbd881c93d

[ "MIT" ]

null

#! /usr/bin/python3 # Python 3 # LinkFinder # By Gerben_Javado # Powered by storenth # Fix webbrowser bug for MacOS import os os.environ["BROWSER"] = "open" # Import libraries import re, sys, glob, html, argparse, jsbeautifier, webbrowser, subprocess, base64, ssl, xml.etree.ElementTree from gzip import GzipFile from string import Template try: from StringIO import StringIO readBytesCustom = StringIO except ImportError: from io import BytesIO readBytesCustom = BytesIO try: from urllib.request import Request, urlopen except ImportError: from urllib2 import Request, urlopen # Regex used regex_str = r""" (?:"|') # Start newline delimiter ( ((?:[a-zA-Z]{1,10}://|//) # Match a scheme [a-Z]*1-10 or // [^\"'/]{1,}\. # Match a domainname (any character + dot) [a-zA-Z]{2,}[^\"']{0,}) # The domainextension and/or path | ((?:/|\.\./|\./) # Start with /,../,./ [^"'><,;| *()(%%$^/\\\[\]] # Next character can't be... [^"'><,;|()]{1,}) # Rest of the characters can't be | ([a-zA-Z0-9_\-/]{1,}/ # Relative endpoint with / [a-zA-Z0-9_\-/]{1,} # Resource name \.(?:[a-zA-Z]{1,4}|action) # Rest + extension (length 1-4 or action) (?:[\?|#][^\"|\']{0,}|)) # ? or # mark with parameters | ([a-zA-Z0-9_\-/]{1,}/ # REST API (no extension) with / [a-zA-Z0-9_\-/]{3,} # Proper REST endpoints usually have 3+ chars (?:[\?|#][^\"|\']{0,}|)) # ? or # mark with parameters | ([a-zA-Z0-9_\-]{1,} # filename \.(?:php|asp|aspx|jsp|json| action|html|js|txt|xml) # . + extension (?:[\?|#][^\"|\']{0,}|)) # ? or # mark with parameters ) (?:"|') # End newline delimiter """ context_delimiter_str = "\n" def parser_error(errmsg): ''' Error Messages ''' # print("Usage: python %s [Options] use -h for help" % sys.argv[0]) print("Error: {}".format(errmsg), file=sys.stderr) sys.exit() def parser_input(input): ''' Parse Input ''' # Method 1 - URL if input.startswith(('http://', 'https://', 'file://', 'ftp://', 'ftps://')): return [input] # Method 2 - URL Inspector Firefox if input.startswith('view-source:'): return [input[12:]] # Method 3 - Burp file if args.burp: jsfiles = [] items = xml.etree.ElementTree.fromstring(open(args.input, "r").read()) for item in items: jsfiles.append({"js":base64.b64decode(item.find('response').text).decode('utf-8',"replace"), "url":item.find('url').text}) return jsfiles # Method 4 - Folder with a wildcard if "*" in input: paths = glob.glob(os.path.abspath(input)) for index, path in enumerate(paths): paths[index] = "file://%s" % path return (paths if len(paths) > 0 else parser_error('Input with wildcard does \ not match any files.')) # Method 5 - Local file path = "file://%s" % os.path.abspath(input) return [path if os.path.exists(input) else parser_error("file could not \ be found (maybe you forgot to add http/https).")] def send_request(url): ''' Send requests with Requests ''' q = Request(url) q.add_header('User-Agent', 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) \ AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.36') q.add_header('Accept', 'text/html,\ application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8') q.add_header('Accept-Language', 'en-US,en;q=0.8') q.add_header('Accept-Encoding', 'gzip') q.add_header('Cookie', args.cookies) try: sslcontext = ssl._create_unverified_context() response = urlopen(q, timeout=args.timeout, context=sslcontext) except Exception as err: raise Exception(err) if response.info().get('Content-Encoding') == 'gzip': data = GzipFile(fileobj=readBytesCustom(response.read())).read() elif response.info().get('Content-Encoding') == 'deflate': data = response.read().read() else: data = response.read() return data.decode('utf-8', 'replace') def getContext(list_matches, content, include_delimiter=0, context_delimiter_str="\n"): ''' Parse Input list_matches: list of tuple (link, start_index, end_index) content: content to search for the context include_delimiter Set 1 to include delimiter in context ''' items = [] for m in list_matches: match_str = m[0] match_start = m[1] match_end = m[2] context_start_index = match_start context_end_index = match_end delimiter_len = len(context_delimiter_str) content_max_index = len(content) - 1 while content[context_start_index] != context_delimiter_str and context_start_index > 0: context_start_index = context_start_index - 1 while content[context_end_index] != context_delimiter_str and context_end_index < content_max_index: context_end_index = context_end_index + 1 if include_delimiter: context = content[context_start_index: context_end_index] else: context = content[context_start_index + delimiter_len: context_end_index] item = { "link": match_str, "context": context } items.append(item) return items def parser_file(content, regex_str, mode=1, more_regex=None, no_dup=1): ''' Parse Input content: string of content to be searched regex_str: string of regex (The link should be in the group(1)) mode: mode of parsing. Set 1 to include surrounding contexts in the result more_regex: string of regex to filter the result no_dup: remove duplicated link (context is NOT counted) Return the list of ["link": link, "context": context] The context is optional if mode=1 is provided. ''' global context_delimiter_str if mode == 1: # Beautify if len(content) > 1000000: content = content.replace(";",";\r\n").replace(",",",\r\n") else: content = jsbeautifier.beautify(content) regex = re.compile(regex_str, re.VERBOSE) if mode == 1: all_matches = [(m.group(1), m.start(0), m.end(0)) for m in re.finditer(regex, content)] items = getContext(all_matches, content, context_delimiter_str=context_delimiter_str) else: items = [{"link": m.group(1)} for m in re.finditer(regex, content)] if no_dup: # Remove duplication all_links = set() no_dup_items = [] for item in items: if item["link"] not in all_links: all_links.add(item["link"]) no_dup_items.append(item) items = no_dup_items # Match Regex filtered_items = [] for item in items: # Remove other capture groups from regex results if more_regex: if re.search(more_regex, item["link"]): filtered_items.append(item) else: filtered_items.append(item) return filtered_items def cli_output(endpoints, url=None): ''' Output to CLI ''' for endpoint in endpoints: if url: print("[{}]".format(url), end=' ') print(html.escape(endpoint["link"]).encode( 'ascii', 'ignore').decode('utf8')) def html_save(html): ''' Save as HTML file and open in the browser ''' hide = os.dup(1) os.close(1) os.open(os.devnull, os.O_RDWR) try: s = Template(open('%s/template.html' % sys.path[0], 'r').read()) text_file = open(args.output, "wb") text_file.write(s.substitute(content=html).encode('utf8')) text_file.close() print("URL to access output: file://%s" % os.path.abspath(args.output)) file = "file:///%s" % os.path.abspath(args.output) if sys.platform == 'linux' or sys.platform == 'linux2': subprocess.call(["xdg-open", file]) else: webbrowser.open(file) except Exception as e: print("Output can't be saved in %s \ due to exception: %s" % (args.output, e)) finally: os.dup2(hide, 1) def check_url(url): nopelist = ["node_modules", "jquery.js"] if url[-3:] == ".js": words = url.split("/") for word in words: if word in nopelist: return False if url[:2] == "//": url = "https:" + url if url[:4] != "http": if url[:1] == "/": url = args.input + url else: url = args.input + "/" + url return url else: return False if __name__ == "__main__": # Parse command line parser = argparse.ArgumentParser() parser.add_argument("-d", "--domain", help="Input a domain to recursively parse all javascript located in a page", action="store_true") parser.add_argument("-i", "--input", help="Input a: URL, file or folder. \ For folders a wildcard can be used (e.g. '/*.js').", required="True", action="store") parser.add_argument("-o", "--output", help="Where to save the file, \ including file name. Default: output.html", action="store", default="output.html") parser.add_argument("-r", "--regex", help="RegEx for filtering purposes \ against found endpoint (e.g. ^/api/)", action="store") parser.add_argument("-b", "--burp", help="", action="store_true") parser.add_argument("-c", "--cookies", help="Add cookies for authenticated JS files", action="store", default="") default_timeout = 10 parser.add_argument("-t", "--timeout", help="How many seconds to wait for the server to send data before giving up (default: " + str(default_timeout) + " seconds)", default=default_timeout, type=int, metavar="<seconds>") args = parser.parse_args() if args.input[-1:] == "/": args.input = args.input[:-1] mode = 1 if args.output == "cli": mode = 0 # Convert input to URLs or JS files urls = parser_input(args.input) # Convert URLs to JS output = '' for url in urls: if not args.burp: try: file = send_request(url) except Exception as err: errmsg = " ".join([url, str(err)]) parser_error(errmsg) else: file = url['js'] url = url['url'] endpoints = parser_file(file, regex_str, mode, args.regex) if args.domain: for endpoint in endpoints: endpoint = html.escape(endpoint["link"]).encode('ascii', 'ignore').decode('utf8') endpoint = check_url(endpoint) if endpoint is False: continue print("Running against: " + endpoint) print("") try: file = send_request(endpoint) new_endpoints = parser_file(file, regex_str, mode, args.regex) if args.output == 'cli': cli_output(new_endpoints) else: output += ''' <h1>File: <a href="%s" target="_blank" rel="nofollow noopener noreferrer">%s</a></h1> ''' % (html.escape(endpoint), html.escape(endpoint)) for endpoint2 in new_endpoints: url = html.escape(endpoint2["link"]) header = "<div><a href='%s' class='text'>%s" % ( html.escape(url), html.escape(url) ) body = "</a><div class='container'>%s</div></div>" % html.escape( endpoint2["context"] ) body = body.replace( html.escape(endpoint2["link"]), "<span style='background-color:yellow'>%s</span>" % html.escape(endpoint2["link"]) ) output += header + body except Exception as e: print("Invalid input defined or SSL error for: " + endpoint) continue if args.output == 'cli': cli_output(endpoints, url) else: output += ''' <h1>File: <a href="%s" target="_blank" rel="nofollow noopener noreferrer">%s</a></h1> ''' % (html.escape(url), html.escape(url)) for endpoint in endpoints: url = html.escape(endpoint["link"]) header = "<div><a href='%s' class='text'>%s" % ( html.escape(url), html.escape(url) ) body = "</a><div class='container'>%s</div></div>" % html.escape( endpoint["context"] ) body = body.replace( html.escape(endpoint["link"]), "<span style='background-color:yellow'>%s</span>" % html.escape(endpoint["link"]) ) output += header + body if args.output != 'cli': html_save(output)

34.509852

149

0.523374

3fc5288cdbf71fe08846bd47f7b688da3b7df09e

4,741

py

Python

PySpectrograph/Spectrograph/Spectrograph.py

crawfordsm/pyspectrograph

4237ba4b4fe08a69e1d6487924d959f089ecca46

[ "BSD-3-Clause" ]

18

2015-01-11T21:04:59.000Z

2021-08-06T18:30:47.000Z

PySpectrograph/Spectrograph/Spectrograph.py

crawfordsm/pyspectrograph

4237ba4b4fe08a69e1d6487924d959f089ecca46

[ "BSD-3-Clause" ]

14

2015-04-23T09:39:16.000Z

2017-12-03T12:49:05.000Z

PySpectrograph/Spectrograph/Spectrograph.py

crawfordsm/pyspectrograph

4237ba4b4fe08a69e1d6487924d959f089ecca46

[ "BSD-3-Clause" ]

5

2015-04-23T08:17:37.000Z

2019-06-22T13:36:47.000Z

"""Spectrograph is a class that general describes a spectrograph. This includes describing the telescope, slit, collimator, grating, camera, and detector. HISTORY 20090912 SMC First written by SM Crawford Limitations: -Still need to verify how alpha, grating angle, beta, and camera angle to see if I can hardwire some of the tasks """ import math from .SpectrographEquations import * from .Grating import Grating from .Optics import Optics from .Slit import Slit from .Detector import Detector class Spectrograph(Grating, Optics, Slit, Detector): """A class describing a spectrograph and functions related to a spectrograph. All angles are in degrees. """ def __init__(self, camang=45, gratang=45, grating=Grating(), camera=Optics(), collimator=Optics(), telescope=Optics(), slit=Slit(), detector=Detector()): # initiate the grating self.grating = grating # initiate the telescope self.telescope = telescope # initiate the collimator self.collimator = collimator # initiate the camera self.camera = camera # initiate the slit self.slit = slit # initiate the detector self.detector = detector # set up the angles in the system self.gratang = gratang self.camang = camang return def alpha(self): return self.gratang def beta(self): return self.camang - self.gratang def gamma(self): return self.gamma def calc_wavelength(self, alpha, beta, gamma=0.0, nd=n_index): """Apply the grating equation to determine the wavelength returns wavelength in mm """ w = gratingequation(self.grating.sigma, self.grating.order, self.grating.sign, alpha, beta, gamma=gamma, nd=nd) return w def calc_angdisp(self, beta): """Calculate the angular dispersion according to m/sigma/cos beta returns angular dispersion in 1/mm """ A = calc_angdisp(self.grating.sigma, self.grating.order, beta) return A def calc_lindisp(self, beta): """Calculate the linear dispersion according to f_cam * A return linear dispersion in mm/mm """ return calc_lindisp(self.camera.focallength, self.grating.sigma, self.grating.order, beta) def calc_demagspatial(self): """Calculate the spatial demagnification returns the spatial demagnification """ return calc_demagspatial(self.collimator.focallength, self.camera.focallength) def calc_demagspectral(self, alpha, beta): """Calculate the spectral demagnification returns the spectral demagnification """ return self.calc_demagspatial() / se.calc_anamorph(alpha, beta) def calc_spatslitimage(self): """Calculate the spatial extant of the slit image return in mm """ return self.slit.width / self.calc_demagspatial() def calc_specslitimage(self, beta): """Calculate the spectral extant of the slit image return in mm """ return self.slit.width * self.calc_lindisp(beta) def calc_resolelement(self, alpha, beta): """Calculate the resolution of a single element for a filled slit return the wavelength resolution in mm """ dw = calc_resolelement(self.slit.width, self.collimator.focallength, self.grating.sigma, self.grating.order, alpha, beta) return dw def calc_resolution(self, w, alpha, beta): """Calculate the resolution at a given wavelength. w/dw returns resolution """ return w / self.calc_resolelement(alpha, beta) def calc_centralwavelength(self): """Calculate the central wavlength return waveleng in mm """ return self.calc_wavelength(self.alpha(), -self.beta()) def calc_redwavelength(self): """For the detector, calculate the maximum red wavelength Assume just the width of the detector return waveleng in mm """ dbeta = math.degrees(math.atan(0.5 * self.detector.width / self.camera.focallength)) return self.calc_wavelength(self.alpha(), -self.beta() - dbeta) def calc_bluewavelength(self): """For the detector, calculate the maximum blue wavelength Assume just the width of the detector return waveleng in mm """ dbeta = math.degrees(math.atan(0.5 * self.detector.width / self.camera.focallength)) return self.calc_wavelength(self.alpha(), -self.beta() + dbeta)

30.006329

119

0.64016

3ddf31e510a4c981fb6715ad9a61470902d8cc8b

3,751

py

Python

basis_set_exchange/tests/test_unused.py

ltalirz/basis_set_exchange

0e9601d7b37ae7672a78a335e34ac5591dd509f0

[ "BSD-3-Clause" ]

108

2018-07-09T14:23:49.000Z

2022-03-30T08:26:15.000Z

basis_set_exchange/tests/test_unused.py

susilehtola/basis_set_exchange

0185cecc56a67ad561167290fd56ac86c0c76ce7

[ "BSD-3-Clause" ]

230

2018-06-01T15:15:49.000Z

2022-03-30T12:02:11.000Z

basis_set_exchange/tests/test_unused.py

susilehtola/basis_set_exchange

0185cecc56a67ad561167290fd56ac86c0c76ce7

[ "BSD-3-Clause" ]

38

2018-07-20T15:16:47.000Z

2022-03-30T08:32:45.000Z

''' Test for unused data ''' import os import basis_set_exchange as bse from .common_testvars import data_dir, all_component_paths, all_element_paths, all_table_paths, all_metadata_files, all_families def test_unused_data(): ''' Test for any unused data in the data directory ''' # All elements contained in all component files all_component_elements = {} for component_path in all_component_paths: component_data = bse.fileio.read_json_basis(component_path) all_component_elements[component_path] = list(component_data['elements'].keys()) # All elements contained in all element files # And all element data as read from the file all_element_elements = {} all_element_data = {} for element_path in all_element_paths: element_data = bse.fileio.read_json_basis(element_path) all_element_elements[element_path] = list(element_data['elements'].keys()) all_element_data[element_path] = element_data['elements'] # Now go through what is reachable through a table file for table_path in all_table_paths: table_data = bse.fileio.read_json_basis(table_path) # What element files are linked to this table file el_files = list(table_data['elements'].items()) # Loop over the element files, and remove the corresponding entry # from all_component_elements for el, el_file in el_files: # Normalize the paths (since we will be removing them later) el_file = os.path.normpath(el_file) el_file_path = os.path.join(data_dir, el_file) el_file_data = all_element_data[el_file_path] for cfile in el_file_data[el]['components']: cfile = os.path.normpath(cfile) cfile_path = os.path.join(data_dir, cfile) if el in all_component_elements[cfile_path]: all_component_elements[cfile_path].remove(el) # Now remove the corresponding entry from all_element_elements if el in all_element_elements[el_file_path]: all_element_elements[el_file_path].remove(el) # See which ones were unused found_unused = False # Merge into one big dictionary remaining = all_component_elements remaining.update(all_element_elements) for k, v in remaining.items(): if not v: continue found_unused = True for el in v: print("Element {:3} in {} not used".format(el, k)) if found_unused: raise RuntimeError("Found unused data") def test_unused_notes(): ''' Test for orphan basis and family notes files ''' all_basis_notes = [] all_family_notes = [] for root, dirs, files in os.walk(data_dir): for basename in files: fpath = os.path.join(root, basename) fpath = os.path.relpath(fpath, data_dir) if basename.endswith('.notes'): all_basis_notes.append(fpath) elif basename.startswith('NOTES.'): all_family_notes.append(fpath) found_unused = False for bs_notes in all_basis_notes: base = os.path.splitext(bs_notes)[0] metafile = base + '.metadata.json' if metafile not in all_metadata_files: print("File {} does not have a corresponding metadata file".format(bs_notes)) found_unused = True for fam_notes in all_family_notes: fam = os.path.splitext(fam_notes)[1][1:] # Removes period if fam not in all_families: print("File {} does not have a corresponding family".format(fam_notes)) found_unused = True if found_unused: raise RuntimeError("Found unused notes files")

34.731481

128

0.659024

e167e1cd7853cce0477d7a7d211b887237ff0b03

3,562

py

Python

bindings/python/ensmallen/datasets/string/tetragenococcussolitariusnbrc100494.py

AnacletoLAB/ensmallen

b2c1b18fb1e5801712852bcc239f239e03076f09

[ "MIT" ]

5

2021-09-10T18:31:58.000Z

2022-03-24T04:28:04.000Z

bindings/python/ensmallen/datasets/string/tetragenococcussolitariusnbrc100494.py

AnacletoLAB/ensmallen_graph

b2c1b18fb1e5801712852bcc239f239e03076f09

[ "MIT" ]

18

2021-01-07T16:47:39.000Z

2021-08-12T21:51:32.000Z

bindings/python/ensmallen/datasets/string/tetragenococcussolitariusnbrc100494.py

AnacletoLAB/ensmallen

b2c1b18fb1e5801712852bcc239f239e03076f09

[ "MIT" ]

3

2021-01-14T02:20:59.000Z

2021-08-04T19:09:52.000Z

""" This file offers the methods to automatically retrieve the graph Tetragenococcus solitarius NBRC 100494. The graph is automatically retrieved from the STRING repository. References --------------------- Please cite the following if you use the data: ```bib @article{szklarczyk2019string, title={STRING v11: protein--protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets}, author={Szklarczyk, Damian and Gable, Annika L and Lyon, David and Junge, Alexander and Wyder, Stefan and Huerta-Cepas, Jaime and Simonovic, Milan and Doncheva, Nadezhda T and Morris, John H and Bork, Peer and others}, journal={Nucleic acids research}, volume={47}, number={D1}, pages={D607--D613}, year={2019}, publisher={Oxford University Press} } ``` """ from typing import Dict from ..automatic_graph_retrieval import AutomaticallyRetrievedGraph from ...ensmallen import Graph # pylint: disable=import-error def TetragenococcusSolitariusNbrc100494( directed: bool = False, preprocess: bool = True, load_nodes: bool = True, verbose: int = 2, cache: bool = True, cache_path: str = "graphs/string", version: str = "links.v11.5", **additional_graph_kwargs: Dict ) -> Graph: """Return new instance of the Tetragenococcus solitarius NBRC 100494 graph. The graph is automatically retrieved from the STRING repository. Parameters ------------------- directed: bool = False Wether to load the graph as directed or undirected. By default false. preprocess: bool = True Whether to preprocess the graph to be loaded in optimal time and memory. load_nodes: bool = True, Whether to load the nodes vocabulary or treat the nodes simply as a numeric range. verbose: int = 2, Wether to show loading bars during the retrieval and building of the graph. cache: bool = True Whether to use cache, i.e. download files only once and preprocess them only once. cache_path: str = "graphs" Where to store the downloaded graphs. version: str = "links.v11.5" The version of the graph to retrieve. The available versions are: - homology.v11.5 - physical.links.v11.5 - links.v11.5 additional_graph_kwargs: Dict Additional graph kwargs. Returns ----------------------- Instace of Tetragenococcus solitarius NBRC 100494 graph. References --------------------- Please cite the following if you use the data: ```bib @article{szklarczyk2019string, title={STRING v11: protein--protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets}, author={Szklarczyk, Damian and Gable, Annika L and Lyon, David and Junge, Alexander and Wyder, Stefan and Huerta-Cepas, Jaime and Simonovic, Milan and Doncheva, Nadezhda T and Morris, John H and Bork, Peer and others}, journal={Nucleic acids research}, volume={47}, number={D1}, pages={D607--D613}, year={2019}, publisher={Oxford University Press} } ``` """ return AutomaticallyRetrievedGraph( graph_name="TetragenococcusSolitariusNbrc100494", repository="string", version=version, directed=directed, preprocess=preprocess, load_nodes=load_nodes, verbose=verbose, cache=cache, cache_path=cache_path, additional_graph_kwargs=additional_graph_kwargs )()

33.92381

223

0.684166

8644d3c9d57f0468b133f626a088f6f5531ebd02

988

py

Python

server/gdserver/protocol.py

daimin/AiwanGobang

26ed7488403986f061a2144a14a8e870bccf226c

[ "MIT" ]

null

server/gdserver/protocol.py

daimin/AiwanGobang

26ed7488403986f061a2144a14a8e870bccf226c

[ "MIT" ]

null

server/gdserver/protocol.py

daimin/AiwanGobang

26ed7488403986f061a2144a14a8e870bccf226c

[ "MIT" ]

null

# coding:utf-8 from __future__ import absolute_import, division, print_function, \ with_statement __author__ = 'daimin' from message import Message DEFAULT = Message(0x0000) VERSION = Message(0x0001) HEARTBEAT = Message(0x0002) LOGIN = Message(0x0003) RANDOM_CHAT = Message(0x0004) FIND_CHAT = Message(0x0005) SEND_CONT = Message(0x0006) RECV_CONT = Message(0x0007) OVER_CHAT = Message(0x0008) LOGOUT = Message(0x0009) OK = DEFAULT # 大于等于0x8000用于错误表示 ERR_NONE = Message(0x8000) ERR_VERSION = Message(0x8001, data=u'错误的版本') ERR_NOT_LOGIN = Message(0x8002, data=u'你还没有登录') ERR_LOGIN_FAIL = Message(0x8003, data=u'登录失败') ERR_RANDOM_FIND = Message(0x8004) ERR_FIND_CHAT = Message(0x8005) ERR_NO_SUPPORT = Message(0x8006, data=u'不支持的协议') ERR_SEND_CONT = Message(0x8007, data=u'发送消息失败') def get_S2C_proto(tid): return Message(int(tid) + 0x1000)

27.444444

67

0.665992

3f63a75dc4b20882fd1556b89394d7d97e8f7ca2

39,710

py

Python

discord/http.py

Rayster4/discord.py-1.7.3

4a4c60a8fab7bf00eac2e9ffbb5621f68a4c6b6f

[ "MIT" ]

21

2021-03-29T05:49:35.000Z

2022-03-18T09:02:34.000Z

discord/http.py

Rayster4/discord.py-1.7.3

4a4c60a8fab7bf00eac2e9ffbb5621f68a4c6b6f

[ "MIT" ]

15

2021-04-10T11:08:09.000Z

2022-03-22T07:48:58.000Z

discord/http.py

Rayster4/discord.py-1.7.3

4a4c60a8fab7bf00eac2e9ffbb5621f68a4c6b6f

[ "MIT" ]

31

2021-03-29T05:54:57.000Z

2022-03-22T16:58:57.000Z

# -*- coding: utf-8 -*- """ The MIT License (MIT) Copyright (c) 2015-present Rapptz Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ import asyncio import json import logging import sys from urllib.parse import quote as _uriquote import weakref import aiohttp from .errors import HTTPException, Forbidden, NotFound, LoginFailure, DiscordServerError, GatewayNotFound from .gateway import DiscordClientWebSocketResponse from . import __version__, utils log = logging.getLogger(__name__) async def json_or_text(response): text = await response.text(encoding='utf-8') try: if response.headers['content-type'] == 'application/json': return json.loads(text) except KeyError: # Thanks Cloudflare pass return text class Route: BASE = 'https://discord.com/api/v7' def __init__(self, method, path, **parameters): self.path = path self.method = method url = (self.BASE + self.path) if parameters: self.url = url.format(**{k: _uriquote(v) if isinstance(v, str) else v for k, v in parameters.items()}) else: self.url = url # major parameters: self.channel_id = parameters.get('channel_id') self.guild_id = parameters.get('guild_id') @property def bucket(self): # the bucket is just method + path w/ major parameters return '{0.channel_id}:{0.guild_id}:{0.path}'.format(self) class MaybeUnlock: def __init__(self, lock): self.lock = lock self._unlock = True def __enter__(self): return self def defer(self): self._unlock = False def __exit__(self, type, value, traceback): if self._unlock: self.lock.release() # For some reason, the Discord voice websocket expects this header to be # completely lowercase while aiohttp respects spec and does it as case-insensitive aiohttp.hdrs.WEBSOCKET = 'websocket' class HTTPClient: """Represents an HTTP client sending HTTP requests to the Discord API.""" SUCCESS_LOG = '{method} {url} has received {text}' REQUEST_LOG = '{method} {url} with {json} has returned {status}' def __init__(self, connector=None, *, proxy=None, proxy_auth=None, loop=None, unsync_clock=True): self.loop = asyncio.get_event_loop() if loop is None else loop self.connector = connector self.__session = None # filled in static_login self._locks = weakref.WeakValueDictionary() self._global_over = asyncio.Event() self._global_over.set() self.token = None self.bot_token = False self.proxy = proxy self.proxy_auth = proxy_auth self.use_clock = not unsync_clock user_agent = 'DiscordBot (https://github.com/Rapptz/discord.py {0}) Python/{1[0]}.{1[1]} aiohttp/{2}' self.user_agent = user_agent.format(__version__, sys.version_info, aiohttp.__version__) def recreate(self): if self.__session.closed: self.__session = aiohttp.ClientSession(connector=self.connector, ws_response_class=DiscordClientWebSocketResponse) async def ws_connect(self, url, *, compress=0): kwargs = { 'proxy_auth': self.proxy_auth, 'proxy': self.proxy, 'max_msg_size': 0, 'timeout': 30.0, 'autoclose': False, 'headers': { 'User-Agent': self.user_agent, }, 'compress': compress } return await self.__session.ws_connect(url, **kwargs) async def request(self, route, *, files=None, form=None, **kwargs): bucket = route.bucket method = route.method url = route.url lock = self._locks.get(bucket) if lock is None: lock = asyncio.Lock() if bucket is not None: self._locks[bucket] = lock # header creation headers = { 'User-Agent': self.user_agent, 'X-Ratelimit-Precision': 'millisecond', } if self.token is not None: headers['Authorization'] = 'Bot ' + self.token if self.bot_token else self.token # some checking if it's a JSON request if 'json' in kwargs: headers['Content-Type'] = 'application/json' kwargs['data'] = utils.to_json(kwargs.pop('json')) try: reason = kwargs.pop('reason') except KeyError: pass else: if reason: headers['X-Audit-Log-Reason'] = _uriquote(reason, safe='/ ') kwargs['headers'] = headers # Proxy support if self.proxy is not None: kwargs['proxy'] = self.proxy if self.proxy_auth is not None: kwargs['proxy_auth'] = self.proxy_auth if not self._global_over.is_set(): # wait until the global lock is complete await self._global_over.wait() await lock.acquire() with MaybeUnlock(lock) as maybe_lock: for tries in range(5): if files: for f in files: f.reset(seek=tries) if form: form_data = aiohttp.FormData() for params in form: form_data.add_field(**params) kwargs['data'] = form_data try: async with self.__session.request(method, url, **kwargs) as r: log.debug('%s %s with %s has returned %s', method, url, kwargs.get('data'), r.status) # even errors have text involved in them so this is safe to call data = await json_or_text(r) # check if we have rate limit header information remaining = r.headers.get('X-Ratelimit-Remaining') if remaining == '0' and r.status != 429: # we've depleted our current bucket delta = utils._parse_ratelimit_header(r, use_clock=self.use_clock) log.debug('A rate limit bucket has been exhausted (bucket: %s, retry: %s).', bucket, delta) maybe_lock.defer() self.loop.call_later(delta, lock.release) # the request was successful so just return the text/json if 300 > r.status >= 200: log.debug('%s %s has received %s', method, url, data) return data # we are being rate limited if r.status == 429: if not r.headers.get('Via'): # Banned by Cloudflare more than likely. raise HTTPException(r, data) fmt = 'We are being rate limited. Retrying in %.2f seconds. Handled under the bucket "%s"' # sleep a bit retry_after = data['retry_after'] / 1000.0 log.warning(fmt, retry_after, bucket) # check if it's a global rate limit is_global = data.get('global', False) if is_global: log.warning('Global rate limit has been hit. Retrying in %.2f seconds.', retry_after) self._global_over.clear() await asyncio.sleep(retry_after) log.debug('Done sleeping for the rate limit. Retrying...') # release the global lock now that the # global rate limit has passed if is_global: self._global_over.set() log.debug('Global rate limit is now over.') continue # we've received a 500 or 502, unconditional retry if r.status in {500, 502}: await asyncio.sleep(1 + tries * 2) continue # the usual error cases if r.status == 403: raise Forbidden(r, data) elif r.status == 404: raise NotFound(r, data) elif r.status == 503: raise DiscordServerError(r, data) else: raise HTTPException(r, data) # This is handling exceptions from the request except OSError as e: # Connection reset by peer if tries < 4 and e.errno in (54, 10054): continue raise # We've run out of retries, raise. if r.status >= 500: raise DiscordServerError(r, data) raise HTTPException(r, data) async def get_from_cdn(self, url): async with self.__session.get(url) as resp: if resp.status == 200: return await resp.read() elif resp.status == 404: raise NotFound(resp, 'asset not found') elif resp.status == 403: raise Forbidden(resp, 'cannot retrieve asset') else: raise HTTPException(resp, 'failed to get asset') # state management async def close(self): if self.__session: await self.__session.close() def _token(self, token, *, bot=True): self.token = token self.bot_token = bot self._ack_token = None # login management async def static_login(self, token, *, bot): # Necessary to get aiohttp to stop complaining about session creation self.__session = aiohttp.ClientSession(connector=self.connector, ws_response_class=DiscordClientWebSocketResponse) old_token, old_bot = self.token, self.bot_token self._token(token, bot=bot) try: data = await self.request(Route('GET', '/users/@me')) except HTTPException as exc: self._token(old_token, bot=old_bot) if exc.response.status == 401: raise LoginFailure('Improper token has been passed.') from exc raise return data def logout(self): return self.request(Route('POST', '/auth/logout')) # Group functionality def start_group(self, user_id, recipients): payload = { 'recipients': recipients } return self.request(Route('POST', '/users/{user_id}/channels', user_id=user_id), json=payload) def leave_group(self, channel_id): return self.request(Route('DELETE', '/channels/{channel_id}', channel_id=channel_id)) def add_group_recipient(self, channel_id, user_id): r = Route('PUT', '/channels/{channel_id}/recipients/{user_id}', channel_id=channel_id, user_id=user_id) return self.request(r) def remove_group_recipient(self, channel_id, user_id): r = Route('DELETE', '/channels/{channel_id}/recipients/{user_id}', channel_id=channel_id, user_id=user_id) return self.request(r) def edit_group(self, channel_id, **options): valid_keys = ('name', 'icon') payload = { k: v for k, v in options.items() if k in valid_keys } return self.request(Route('PATCH', '/channels/{channel_id}', channel_id=channel_id), json=payload) def convert_group(self, channel_id): return self.request(Route('POST', '/channels/{channel_id}/convert', channel_id=channel_id)) # Message management def start_private_message(self, user_id): payload = { 'recipient_id': user_id } return self.request(Route('POST', '/users/@me/channels'), json=payload) def send_message(self, channel_id, content, *, tts=False, embed=None, nonce=None, allowed_mentions=None, message_reference=None): r = Route('POST', '/channels/{channel_id}/messages', channel_id=channel_id) payload = {} if content: payload['content'] = content if tts: payload['tts'] = True if embed: payload['embed'] = embed if nonce: payload['nonce'] = nonce if allowed_mentions: payload['allowed_mentions'] = allowed_mentions if message_reference: payload['message_reference'] = message_reference return self.request(r, json=payload) def send_typing(self, channel_id): return self.request(Route('POST', '/channels/{channel_id}/typing', channel_id=channel_id)) def send_files(self, channel_id, *, files, content=None, tts=False, embed=None, nonce=None, allowed_mentions=None, message_reference=None): r = Route('POST', '/channels/{channel_id}/messages', channel_id=channel_id) form = [] payload = {'tts': tts} if content: payload['content'] = content if embed: payload['embed'] = embed if nonce: payload['nonce'] = nonce if allowed_mentions: payload['allowed_mentions'] = allowed_mentions if message_reference: payload['message_reference'] = message_reference form.append({'name': 'payload_json', 'value': utils.to_json(payload)}) if len(files) == 1: file = files[0] form.append({ 'name': 'file', 'value': file.fp, 'filename': file.filename, 'content_type': 'application/octet-stream' }) else: for index, file in enumerate(files): form.append({ 'name': 'file%s' % index, 'value': file.fp, 'filename': file.filename, 'content_type': 'application/octet-stream' }) return self.request(r, form=form, files=files) async def ack_message(self, channel_id, message_id): r = Route('POST', '/channels/{channel_id}/messages/{message_id}/ack', channel_id=channel_id, message_id=message_id) data = await self.request(r, json={'token': self._ack_token}) self._ack_token = data['token'] def ack_guild(self, guild_id): return self.request(Route('POST', '/guilds/{guild_id}/ack', guild_id=guild_id)) def delete_message(self, channel_id, message_id, *, reason=None): r = Route('DELETE', '/channels/{channel_id}/messages/{message_id}', channel_id=channel_id, message_id=message_id) return self.request(r, reason=reason) def delete_messages(self, channel_id, message_ids, *, reason=None): r = Route('POST', '/channels/{channel_id}/messages/bulk_delete', channel_id=channel_id) payload = { 'messages': message_ids } return self.request(r, json=payload, reason=reason) def edit_message(self, channel_id, message_id, **fields): r = Route('PATCH', '/channels/{channel_id}/messages/{message_id}', channel_id=channel_id, message_id=message_id) return self.request(r, json=fields) def add_reaction(self, channel_id, message_id, emoji): r = Route('PUT', '/channels/{channel_id}/messages/{message_id}/reactions/{emoji}/@me', channel_id=channel_id, message_id=message_id, emoji=emoji) return self.request(r) def remove_reaction(self, channel_id, message_id, emoji, member_id): r = Route('DELETE', '/channels/{channel_id}/messages/{message_id}/reactions/{emoji}/{member_id}', channel_id=channel_id, message_id=message_id, member_id=member_id, emoji=emoji) return self.request(r) def remove_own_reaction(self, channel_id, message_id, emoji): r = Route('DELETE', '/channels/{channel_id}/messages/{message_id}/reactions/{emoji}/@me', channel_id=channel_id, message_id=message_id, emoji=emoji) return self.request(r) def get_reaction_users(self, channel_id, message_id, emoji, limit, after=None): r = Route('GET', '/channels/{channel_id}/messages/{message_id}/reactions/{emoji}', channel_id=channel_id, message_id=message_id, emoji=emoji) params = {'limit': limit} if after: params['after'] = after return self.request(r, params=params) def clear_reactions(self, channel_id, message_id): r = Route('DELETE', '/channels/{channel_id}/messages/{message_id}/reactions', channel_id=channel_id, message_id=message_id) return self.request(r) def clear_single_reaction(self, channel_id, message_id, emoji): r = Route('DELETE', '/channels/{channel_id}/messages/{message_id}/reactions/{emoji}', channel_id=channel_id, message_id=message_id, emoji=emoji) return self.request(r) def get_message(self, channel_id, message_id): r = Route('GET', '/channels/{channel_id}/messages/{message_id}', channel_id=channel_id, message_id=message_id) return self.request(r) def get_channel(self, channel_id): r = Route('GET', '/channels/{channel_id}', channel_id=channel_id) return self.request(r) def logs_from(self, channel_id, limit, before=None, after=None, around=None): params = { 'limit': limit } if before is not None: params['before'] = before if after is not None: params['after'] = after if around is not None: params['around'] = around return self.request(Route('GET', '/channels/{channel_id}/messages', channel_id=channel_id), params=params) def publish_message(self, channel_id, message_id): return self.request(Route('POST', '/channels/{channel_id}/messages/{message_id}/crosspost', channel_id=channel_id, message_id=message_id)) def pin_message(self, channel_id, message_id, reason=None): return self.request(Route('PUT', '/channels/{channel_id}/pins/{message_id}', channel_id=channel_id, message_id=message_id), reason=reason) def unpin_message(self, channel_id, message_id, reason=None): return self.request(Route('DELETE', '/channels/{channel_id}/pins/{message_id}', channel_id=channel_id, message_id=message_id), reason=reason) def pins_from(self, channel_id): return self.request(Route('GET', '/channels/{channel_id}/pins', channel_id=channel_id)) # Member management def kick(self, user_id, guild_id, reason=None): r = Route('DELETE', '/guilds/{guild_id}/members/{user_id}', guild_id=guild_id, user_id=user_id) if reason: # thanks aiohttp r.url = '{0.url}?reason={1}'.format(r, _uriquote(reason)) return self.request(r) def ban(self, user_id, guild_id, delete_message_days=1, reason=None): r = Route('PUT', '/guilds/{guild_id}/bans/{user_id}', guild_id=guild_id, user_id=user_id) params = { 'delete_message_days': delete_message_days, } if reason: # thanks aiohttp r.url = '{0.url}?reason={1}'.format(r, _uriquote(reason)) return self.request(r, params=params) def unban(self, user_id, guild_id, *, reason=None): r = Route('DELETE', '/guilds/{guild_id}/bans/{user_id}', guild_id=guild_id, user_id=user_id) return self.request(r, reason=reason) def guild_voice_state(self, user_id, guild_id, *, mute=None, deafen=None, reason=None): r = Route('PATCH', '/guilds/{guild_id}/members/{user_id}', guild_id=guild_id, user_id=user_id) payload = {} if mute is not None: payload['mute'] = mute if deafen is not None: payload['deaf'] = deafen return self.request(r, json=payload, reason=reason) def edit_profile(self, password, username, avatar, **fields): payload = { 'password': password, 'username': username, 'avatar': avatar } if 'email' in fields: payload['email'] = fields['email'] if 'new_password' in fields: payload['new_password'] = fields['new_password'] return self.request(Route('PATCH', '/users/@me'), json=payload) def change_my_nickname(self, guild_id, nickname, *, reason=None): r = Route('PATCH', '/guilds/{guild_id}/members/@me/nick', guild_id=guild_id) payload = { 'nick': nickname } return self.request(r, json=payload, reason=reason) def change_nickname(self, guild_id, user_id, nickname, *, reason=None): r = Route('PATCH', '/guilds/{guild_id}/members/{user_id}', guild_id=guild_id, user_id=user_id) payload = { 'nick': nickname } return self.request(r, json=payload, reason=reason) def edit_my_voice_state(self, guild_id, payload): r = Route('PATCH', '/guilds/{guild_id}/voice-states/@me', guild_id=guild_id) return self.request(r, json=payload) def edit_voice_state(self, guild_id, user_id, payload): r = Route('PATCH', '/guilds/{guild_id}/voice-states/{user_id}', guild_id=guild_id, user_id=user_id) return self.request(r, json=payload) def edit_member(self, guild_id, user_id, *, reason=None, **fields): r = Route('PATCH', '/guilds/{guild_id}/members/{user_id}', guild_id=guild_id, user_id=user_id) return self.request(r, json=fields, reason=reason) # Channel management def edit_channel(self, channel_id, *, reason=None, **options): r = Route('PATCH', '/channels/{channel_id}', channel_id=channel_id) valid_keys = ('name', 'parent_id', 'topic', 'bitrate', 'nsfw', 'user_limit', 'position', 'permission_overwrites', 'rate_limit_per_user', 'type', 'rtc_region') payload = { k: v for k, v in options.items() if k in valid_keys } return self.request(r, reason=reason, json=payload) def bulk_channel_update(self, guild_id, data, *, reason=None): r = Route('PATCH', '/guilds/{guild_id}/channels', guild_id=guild_id) return self.request(r, json=data, reason=reason) def create_channel(self, guild_id, channel_type, *, reason=None, **options): payload = { 'type': channel_type } valid_keys = ('name', 'parent_id', 'topic', 'bitrate', 'nsfw', 'user_limit', 'position', 'permission_overwrites', 'rate_limit_per_user', 'rtc_region') payload.update({ k: v for k, v in options.items() if k in valid_keys and v is not None }) return self.request(Route('POST', '/guilds/{guild_id}/channels', guild_id=guild_id), json=payload, reason=reason) def delete_channel(self, channel_id, *, reason=None): return self.request(Route('DELETE', '/channels/{channel_id}', channel_id=channel_id), reason=reason) # Webhook management def create_webhook(self, channel_id, *, name, avatar=None, reason=None): payload = { 'name': name } if avatar is not None: payload['avatar'] = avatar r = Route('POST', '/channels/{channel_id}/webhooks', channel_id=channel_id) return self.request(r, json=payload, reason=reason) def channel_webhooks(self, channel_id): return self.request(Route('GET', '/channels/{channel_id}/webhooks', channel_id=channel_id)) def guild_webhooks(self, guild_id): return self.request(Route('GET', '/guilds/{guild_id}/webhooks', guild_id=guild_id)) def get_webhook(self, webhook_id): return self.request(Route('GET', '/webhooks/{webhook_id}', webhook_id=webhook_id)) def follow_webhook(self, channel_id, webhook_channel_id, reason=None): payload = { 'webhook_channel_id': str(webhook_channel_id) } return self.request(Route('POST', '/channels/{channel_id}/followers', channel_id=channel_id), json=payload, reason=reason) # Guild management def get_guilds(self, limit, before=None, after=None): params = { 'limit': limit } if before: params['before'] = before if after: params['after'] = after return self.request(Route('GET', '/users/@me/guilds'), params=params) def leave_guild(self, guild_id): return self.request(Route('DELETE', '/users/@me/guilds/{guild_id}', guild_id=guild_id)) def get_guild(self, guild_id): return self.request(Route('GET', '/guilds/{guild_id}', guild_id=guild_id)) def delete_guild(self, guild_id): return self.request(Route('DELETE', '/guilds/{guild_id}', guild_id=guild_id)) def create_guild(self, name, region, icon): payload = { 'name': name, 'icon': icon, 'region': region } return self.request(Route('POST', '/guilds'), json=payload) def edit_guild(self, guild_id, *, reason=None, **fields): valid_keys = ('name', 'region', 'icon', 'afk_timeout', 'owner_id', 'afk_channel_id', 'splash', 'verification_level', 'system_channel_id', 'default_message_notifications', 'description', 'explicit_content_filter', 'banner', 'system_channel_flags', 'rules_channel_id', 'public_updates_channel_id', 'preferred_locale',) payload = { k: v for k, v in fields.items() if k in valid_keys } return self.request(Route('PATCH', '/guilds/{guild_id}', guild_id=guild_id), json=payload, reason=reason) def get_template(self, code): return self.request(Route('GET', '/guilds/templates/{code}', code=code)) def guild_templates(self, guild_id): return self.request(Route('GET', '/guilds/{guild_id}/templates', guild_id=guild_id)) def create_template(self, guild_id, payload): return self.request(Route('POST', '/guilds/{guild_id}/templates', guild_id=guild_id), json=payload) def sync_template(self, guild_id, code): return self.request(Route('PUT', '/guilds/{guild_id}/templates/{code}', guild_id=guild_id, code=code)) def edit_template(self, guild_id, code, payload): valid_keys = ( 'name', 'description', ) payload = { k: v for k, v in payload.items() if k in valid_keys } return self.request(Route('PATCH', '/guilds/{guild_id}/templates/{code}', guild_id=guild_id, code=code), json=payload) def delete_template(self, guild_id, code): return self.request(Route('DELETE', '/guilds/{guild_id}/templates/{code}', guild_id=guild_id, code=code)) def create_from_template(self, code, name, region, icon): payload = { 'name': name, 'icon': icon, 'region': region } return self.request(Route('POST', '/guilds/templates/{code}', code=code), json=payload) def get_bans(self, guild_id): return self.request(Route('GET', '/guilds/{guild_id}/bans', guild_id=guild_id)) def get_ban(self, user_id, guild_id): return self.request(Route('GET', '/guilds/{guild_id}/bans/{user_id}', guild_id=guild_id, user_id=user_id)) def get_vanity_code(self, guild_id): return self.request(Route('GET', '/guilds/{guild_id}/vanity-url', guild_id=guild_id)) def change_vanity_code(self, guild_id, code, *, reason=None): payload = {'code': code} return self.request(Route('PATCH', '/guilds/{guild_id}/vanity-url', guild_id=guild_id), json=payload, reason=reason) def get_all_guild_channels(self, guild_id): return self.request(Route('GET', '/guilds/{guild_id}/channels', guild_id=guild_id)) def get_members(self, guild_id, limit, after): params = { 'limit': limit, } if after: params['after'] = after r = Route('GET', '/guilds/{guild_id}/members', guild_id=guild_id) return self.request(r, params=params) def get_member(self, guild_id, member_id): return self.request(Route('GET', '/guilds/{guild_id}/members/{member_id}', guild_id=guild_id, member_id=member_id)) def prune_members(self, guild_id, days, compute_prune_count, roles, *, reason=None): payload = { 'days': days, 'compute_prune_count': 'true' if compute_prune_count else 'false' } if roles: payload['include_roles'] = ', '.join(roles) return self.request(Route('POST', '/guilds/{guild_id}/prune', guild_id=guild_id), json=payload, reason=reason) def estimate_pruned_members(self, guild_id, days, roles): params = { 'days': days } if roles: params['include_roles'] = ', '.join(roles) return self.request(Route('GET', '/guilds/{guild_id}/prune', guild_id=guild_id), params=params) def get_all_custom_emojis(self, guild_id): return self.request(Route('GET', '/guilds/{guild_id}/emojis', guild_id=guild_id)) def get_custom_emoji(self, guild_id, emoji_id): return self.request(Route('GET', '/guilds/{guild_id}/emojis/{emoji_id}', guild_id=guild_id, emoji_id=emoji_id)) def create_custom_emoji(self, guild_id, name, image, *, roles=None, reason=None): payload = { 'name': name, 'image': image, 'roles': roles or [] } r = Route('POST', '/guilds/{guild_id}/emojis', guild_id=guild_id) return self.request(r, json=payload, reason=reason) def delete_custom_emoji(self, guild_id, emoji_id, *, reason=None): r = Route('DELETE', '/guilds/{guild_id}/emojis/{emoji_id}', guild_id=guild_id, emoji_id=emoji_id) return self.request(r, reason=reason) def edit_custom_emoji(self, guild_id, emoji_id, *, name, roles=None, reason=None): payload = { 'name': name, 'roles': roles or [] } r = Route('PATCH', '/guilds/{guild_id}/emojis/{emoji_id}', guild_id=guild_id, emoji_id=emoji_id) return self.request(r, json=payload, reason=reason) def get_all_integrations(self, guild_id): r = Route('GET', '/guilds/{guild_id}/integrations', guild_id=guild_id) return self.request(r) def create_integration(self, guild_id, type, id): payload = { 'type': type, 'id': id } r = Route('POST', '/guilds/{guild_id}/integrations', guild_id=guild_id) return self.request(r, json=payload) def edit_integration(self, guild_id, integration_id, **payload): r = Route('PATCH', '/guilds/{guild_id}/integrations/{integration_id}', guild_id=guild_id, integration_id=integration_id) return self.request(r, json=payload) def sync_integration(self, guild_id, integration_id): r = Route('POST', '/guilds/{guild_id}/integrations/{integration_id}/sync', guild_id=guild_id, integration_id=integration_id) return self.request(r) def delete_integration(self, guild_id, integration_id): r = Route('DELETE', '/guilds/{guild_id}/integrations/{integration_id}', guild_id=guild_id, integration_id=integration_id) return self.request(r) def get_audit_logs(self, guild_id, limit=100, before=None, after=None, user_id=None, action_type=None): params = {'limit': limit} if before: params['before'] = before if after: params['after'] = after if user_id: params['user_id'] = user_id if action_type: params['action_type'] = action_type r = Route('GET', '/guilds/{guild_id}/audit-logs', guild_id=guild_id) return self.request(r, params=params) def get_widget(self, guild_id): return self.request(Route('GET', '/guilds/{guild_id}/widget.json', guild_id=guild_id)) # Invite management def create_invite(self, channel_id, *, reason=None, **options): r = Route('POST', '/channels/{channel_id}/invites', channel_id=channel_id) payload = { 'max_age': options.get('max_age', 0), 'max_uses': options.get('max_uses', 0), 'temporary': options.get('temporary', False), 'unique': options.get('unique', True) } return self.request(r, reason=reason, json=payload) def get_invite(self, invite_id, *, with_counts=True): params = { 'with_counts': int(with_counts) } return self.request(Route('GET', '/invites/{invite_id}', invite_id=invite_id), params=params) def invites_from(self, guild_id): return self.request(Route('GET', '/guilds/{guild_id}/invites', guild_id=guild_id)) def invites_from_channel(self, channel_id): return self.request(Route('GET', '/channels/{channel_id}/invites', channel_id=channel_id)) def delete_invite(self, invite_id, *, reason=None): return self.request(Route('DELETE', '/invites/{invite_id}', invite_id=invite_id), reason=reason) # Role management def get_roles(self, guild_id): return self.request(Route('GET', '/guilds/{guild_id}/roles', guild_id=guild_id)) def edit_role(self, guild_id, role_id, *, reason=None, **fields): r = Route('PATCH', '/guilds/{guild_id}/roles/{role_id}', guild_id=guild_id, role_id=role_id) valid_keys = ('name', 'permissions', 'color', 'hoist', 'mentionable') payload = { k: v for k, v in fields.items() if k in valid_keys } return self.request(r, json=payload, reason=reason) def delete_role(self, guild_id, role_id, *, reason=None): r = Route('DELETE', '/guilds/{guild_id}/roles/{role_id}', guild_id=guild_id, role_id=role_id) return self.request(r, reason=reason) def replace_roles(self, user_id, guild_id, role_ids, *, reason=None): return self.edit_member(guild_id=guild_id, user_id=user_id, roles=role_ids, reason=reason) def create_role(self, guild_id, *, reason=None, **fields): r = Route('POST', '/guilds/{guild_id}/roles', guild_id=guild_id) return self.request(r, json=fields, reason=reason) def move_role_position(self, guild_id, positions, *, reason=None): r = Route('PATCH', '/guilds/{guild_id}/roles', guild_id=guild_id) return self.request(r, json=positions, reason=reason) def add_role(self, guild_id, user_id, role_id, *, reason=None): r = Route('PUT', '/guilds/{guild_id}/members/{user_id}/roles/{role_id}', guild_id=guild_id, user_id=user_id, role_id=role_id) return self.request(r, reason=reason) def remove_role(self, guild_id, user_id, role_id, *, reason=None): r = Route('DELETE', '/guilds/{guild_id}/members/{user_id}/roles/{role_id}', guild_id=guild_id, user_id=user_id, role_id=role_id) return self.request(r, reason=reason) def edit_channel_permissions(self, channel_id, target, allow, deny, type, *, reason=None): payload = { 'id': target, 'allow': allow, 'deny': deny, 'type': type } r = Route('PUT', '/channels/{channel_id}/permissions/{target}', channel_id=channel_id, target=target) return self.request(r, json=payload, reason=reason) def delete_channel_permissions(self, channel_id, target, *, reason=None): r = Route('DELETE', '/channels/{channel_id}/permissions/{target}', channel_id=channel_id, target=target) return self.request(r, reason=reason) # Voice management def move_member(self, user_id, guild_id, channel_id, *, reason=None): return self.edit_member(guild_id=guild_id, user_id=user_id, channel_id=channel_id, reason=reason) # Relationship related def remove_relationship(self, user_id): r = Route('DELETE', '/users/@me/relationships/{user_id}', user_id=user_id) return self.request(r) def add_relationship(self, user_id, type=None): r = Route('PUT', '/users/@me/relationships/{user_id}', user_id=user_id) payload = {} if type is not None: payload['type'] = type return self.request(r, json=payload) def send_friend_request(self, username, discriminator): r = Route('POST', '/users/@me/relationships') payload = { 'username': username, 'discriminator': int(discriminator) } return self.request(r, json=payload) # Misc def application_info(self): return self.request(Route('GET', '/oauth2/applications/@me')) async def get_gateway(self, *, encoding='json', v=6, zlib=True): try: data = await self.request(Route('GET', '/gateway')) except HTTPException as exc: raise GatewayNotFound() from exc if zlib: value = '{0}?encoding={1}&v={2}&compress=zlib-stream' else: value = '{0}?encoding={1}&v={2}' return value.format(data['url'], encoding, v) async def get_bot_gateway(self, *, encoding='json', v=6, zlib=True): try: data = await self.request(Route('GET', '/gateway/bot')) except HTTPException as exc: raise GatewayNotFound() from exc if zlib: value = '{0}?encoding={1}&v={2}&compress=zlib-stream' else: value = '{0}?encoding={1}&v={2}' return data['shards'], value.format(data['url'], encoding, v) def get_user(self, user_id): return self.request(Route('GET', '/users/{user_id}', user_id=user_id)) def get_user_profile(self, user_id): return self.request(Route('GET', '/users/{user_id}/profile', user_id=user_id)) def get_mutual_friends(self, user_id): return self.request(Route('GET', '/users/{user_id}/relationships', user_id=user_id)) def change_hypesquad_house(self, house_id): payload = {'house_id': house_id} return self.request(Route('POST', '/hypesquad/online'), json=payload) def leave_hypesquad_house(self): return self.request(Route('DELETE', '/hypesquad/online')) def edit_settings(self, **payload): return self.request(Route('PATCH', '/users/@me/settings'), json=payload)

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