ytzi/the-stack-dedup-python-scored · Datasets at Hugging Face

02618a7eed33bdfbec9b651a6841eb4fcf49a22c

1,663

py

Python

utils/auth.py

BudzynskiMaciej/notifai_recruitment

56860db3a2dad6115747a675895b8f7947e7e12e

[ "MIT" ]

null

utils/auth.py

BudzynskiMaciej/notifai_recruitment

56860db3a2dad6115747a675895b8f7947e7e12e

[ "MIT" ]

2

2021-05-21T13:26:26.000Z

2022-02-10T10:04:55.000Z

utils/auth.py

BudzynskiMaciej/notifai_recruitment

56860db3a2dad6115747a675895b8f7947e7e12e

[ "MIT" ]

null

# -*- coding: utf-8 -*- from django.contrib.auth.models import User from rest_framework import authentication from rest_framework import exceptions from notifai_recruitment import settings class MasterKeyNaiveAuthentication(authentication.BaseAuthentication): """Authentication model for master key. Note: It was done the way I understood the assignment.In the task it was written that the authorization will be performed by the key in the email exchange. This solution allows you to set the master key as requested in the email. You could also set the authorization using the ready-made implementation included in the Django Rest Framework, which is TokenAuthentication. This authorization would allow tokens to be assigned to specific users. DRF requires any user to be returned upon authorization. For this authorization it will always be the first SuperUser, therefore at least one super user account is required. It may not be the best authorization for use in production, but it meets the assumption of a token sent by e-mail. In my opinion, a good authentication mechanism would be JWT(Json Web Token). """ def authenticate(self, request): request_master_key = request.META.get('HTTP_BEARER') if not request_master_key: return None super_user = User.objects.filter(is_superuser=True).first() if request_master_key != settings.MASTER_KEY: raise exceptions.AuthenticationFailed('Wrong Bearer token!') return super_user, None def authenticate_header(self, request): return 'Bearer: <MASTER_KEY>'

47.514286

120

0.736019

1,470

0.883945

0

1,006

0.604931

02623225e5d363b265ee6e56ba38be5191b44c1f

435

py

Python

scripts/issues/issue6.py

slamer59/awesome-panel

91c30bd6d6859eadf9c65b1e143952f7e64d5290

[ "Apache-2.0" ]

179

2019-12-04T14:54:53.000Z

2022-03-30T09:08:38.000Z

scripts/issues/issue6.py

slamer59/awesome-panel

91c30bd6d6859eadf9c65b1e143952f7e64d5290

[ "Apache-2.0" ]

62

2019-12-14T16:51:28.000Z

2022-03-19T18:47:12.000Z

scripts/issues/issue6.py

slamer59/awesome-panel

91c30bd6d6859eadf9c65b1e143952f7e64d5290

[ "Apache-2.0" ]

35

2019-12-08T13:19:53.000Z

2022-03-25T10:33:02.000Z

import panel as pn def main(): text_error = """ This is not formatted correctly by Markdown due to the indentation!""" text_ok = """ This is formatted correctly by Markdown! """ app = pn.Column( pn.pane.Markdown(text_error), pn.pane.HTML( "<hr>", sizing_mode="stretch_width", ), pn.pane.Markdown(text_ok), ) app.servable() main()

19.772727

75

0.542529

0

150

0.344828

02649919ebe1649e2c617d8a536cb6343e919b0b

18,257

py

Python

Electronic_Arts_Software_Engineering_Virtual_Program/Task_1/Vaxman_in_Python/vaxman.py

melwyncarlo/Virtual_Internship_Programmes

1d1ae99abd63765d69ce930438c4bd6d15bd3d45

[ "CC0-1.0" ]

null

Electronic_Arts_Software_Engineering_Virtual_Program/Task_1/Vaxman_in_Python/vaxman.py

melwyncarlo/Virtual_Internship_Programmes

1d1ae99abd63765d69ce930438c4bd6d15bd3d45

[ "CC0-1.0" ]

null

Electronic_Arts_Software_Engineering_Virtual_Program/Task_1/Vaxman_in_Python/vaxman.py

melwyncarlo/Virtual_Internship_Programmes

1d1ae99abd63765d69ce930438c4bd6d15bd3d45

[ "CC0-1.0" ]

null

# Vax-Man, a re-implementation of Pacman, in Python, with PyGame. # Forked from: https://github.com/hbokmann/Pacman # Edited by Melwyn Francis Carlo (2021) # Video link: https://youtu.be/ZrqZEC6DvMc import time import pygame # Ghosts multiply themselves every thirty seconds. GHOST_MULTIPLICATION_TIME_GAP = 30 # Thirty-two times for each ghost type. MAXIMUM_GHOSTS = 32 * 4; indigo = ( 85, 48, 141 ) yellow = ( 255, 255, 0 ) darkRed = ( 201, 33, 30 ) darkGrey = ( 28, 28, 28 ) lightGrey = ( 238, 238, 238 ) Vaxman_icon=pygame.image.load('images/Vaxman_Big.png') pygame.display.set_icon(Vaxman_icon) # Add music # Spook4 by PeriTune | http://peritune.com # Attribution 4.0 International (CC BY 4.0) # https://creativecommons.org/licenses/by/4.0/ # Music promoted by https://www.chosic.com/free-music/all/ pygame.mixer.init() pygame.mixer.music.load('peritune-spook4.mp3') pygame.mixer.music.play(-1, 0.0) # This class represents the bar at the bottom that the player controls class Wall(pygame.sprite.Sprite): # Constructor function def __init__(self,x,y,width,height, color): # Call the parent's constructor pygame.sprite.Sprite.__init__(self) # Make an indigo wall, of the size specified in the parameters self.image = pygame.Surface([width, height]) self.image.fill(color) # Make our top-left corner the passed-in location. self.rect = self.image.get_rect() self.rect.top = y self.rect.left = x # This creates all the walls in room 1 def setupRoomOne(all_sprites_list): # Make the walls. (x_pos, y_pos, width, height) wall_list=pygame.sprite.RenderPlain() # This is a list of walls. Each is in the form [x, y, width, height] walls = [ [0,0,6,600], [0,0,600,6], [0,600,606,6], [600,0,6,606], [300,0,6,66], [60,60,186,6], [360,60,186,6], [60,120,66,6], [60,120,6,126], [180,120,246,6], [300,120,6,66], [480,120,66,6], [540,120,6,126], [120,180,126,6], [120,180,6,126], [360,180,126,6], [480,180,6,126], [180,240,6,126], [180,360,246,6], [420,240,6,126], [240,240,42,6], [324,240,42,6], [240,240,6,66], [240,300,126,6], [360,240,6,66], [0,300,66,6], [540,300,66,6], [60,360,66,6], [60,360,6,186], [480,360,66,6], [540,360,6,186], [120,420,366,6], [120,420,6,66], [480,420,6,66], [180,480,246,6], [300,480,6,66], [120,540,126,6], [360,540,126,6] ] # Loop through the list. Create the wall, add it to the list. for item in walls: wall = Wall(item[0], item[1], item[2], item[3], indigo) wall_list.add(wall) all_sprites_list.add(wall) # Return our new list. return wall_list def setupGate(all_sprites_list): gate = pygame.sprite.RenderPlain() gate.add(Wall(282, 242, 42, 2, lightGrey)) all_sprites_list.add(gate) return gate # This class represents the ball # It derives from the "Sprite" class in Pygame class Block(pygame.sprite.Sprite): # Constructor. Pass in the color of the block, # and its x and y position def __init__(self, color, width, height): # Call the parent class (Sprite) constructor pygame.sprite.Sprite.__init__(self) # Create an image of the block, and fill it with a color. # This could also be an image loaded from the disk. self.image = pygame.Surface([width, height]) self.image.fill(lightGrey) self.image.set_colorkey(lightGrey) pygame.draw.ellipse(self.image,color,[0,0,width,height]) # Fetch the rectangle object that has the dimensions of the image # image. # Update the position of this object by setting the values # of rect.x and rect.y self.rect = self.image.get_rect() # This class represents the bar at the bottom that the player controls class Player(pygame.sprite.Sprite): # Set speed vector change_x=0 change_y=0 # Constructor function def __init__(self, x, y, filename): # Call the parent's constructor pygame.sprite.Sprite.__init__(self) # Set height, width self.image = pygame.image.load(filename).convert_alpha() # Make our top-left corner the passed-in location. self.rect = self.image.get_rect() self.rect.top = y self.rect.left = x self.prev_x = x self.prev_y = y # Clear the speed of the player def prevdirection(self): self.prev_x = self.change_x self.prev_y = self.change_y # Change the speed of the player def changespeed(self,x,y): self.change_x+=x self.change_y+=y # Find a new position for the player def update(self,walls,gate): # Get the old position, in case we need to go back to it old_x=self.rect.left new_x=old_x+self.change_x prev_x=old_x+self.prev_x self.rect.left = new_x old_y=self.rect.top new_y=old_y+self.change_y prev_y=old_y+self.prev_y # Did this update cause us to hit a wall? x_collide = pygame.sprite.spritecollide(self, walls, False) if x_collide: # Whoops, hit a wall. Go back to the old position self.rect.left=old_x # self.rect.top=prev_y # y_collide = pygame.sprite.spritecollide(self, walls, False) # if y_collide: # # Whoops, hit a wall. Go back to the old position # self.rect.top=old_y # print('a') else: self.rect.top = new_y # Did this update cause us to hit a wall? y_collide = pygame.sprite.spritecollide(self, walls, False) if y_collide: # Whoops, hit a wall. Go back to the old position self.rect.top=old_y # self.rect.left=prev_x # x_collide = pygame.sprite.spritecollide(self, walls, False) # if x_collide: # # Whoops, hit a wall. Go back to the old position # self.rect.left=old_x # print('b') if gate != False: gate_hit = pygame.sprite.spritecollide(self, gate, False) if gate_hit: self.rect.left=old_x self.rect.top=old_y #Inheritime Player klassist class Ghost(Player): # Change the speed of the ghost def changespeed(self,list,ghost,turn,steps,l): try: z=list[turn][2] if steps < z: self.change_x=list[turn][0] self.change_y=list[turn][1] steps+=1 else: if turn < l: turn+=1 elif ghost == "clyde": turn = 2 else: turn = 0 self.change_x=list[turn][0] self.change_y=list[turn][1] steps = 0 return [turn,steps] except IndexError: return [0,0] Pinky_directions = [ [0,-30,4], [15,0,9], [0,15,11], [-15,0,23], [0,15,7], [15,0,3], [0,-15,3], [15,0,19], [0,15,3], [15,0,3], [0,15,3], [15,0,3], [0,-15,15], [-15,0,7], [0,15,3], [-15,0,19], [0,-15,11], [15,0,9] ] Blinky_directions = [ [0,-15,4], [15,0,9], [0,15,11], [15,0,3], [0,15,7], [-15,0,11], [0,15,3], [15,0,15], [0,-15,15], [15,0,3], [0,-15,11], [-15,0,3], [0,-15,11], [-15,0,3], [0,-15,3], [-15,0,7], [0,-15,3], [15,0,15], [0,15,15], [-15,0,3], [0,15,3], [-15,0,3], [0,-15,7], [-15,0,3], [0,15,7], [-15,0,11], [0,-15,7], [15,0,5] ] Inky_directions = [ [30,0,2], [0,-15,4], [15,0,10], [0,15,7], [15,0,3], [0,-15,3], [15,0,3], [0,-15,15], [-15,0,15], [0,15,3], [15,0,15], [0,15,11], [-15,0,3], [0,-15,7], [-15,0,11], [0,15,3], [-15,0,11], [0,15,7], [-15,0,3], [0,-15,3], [-15,0,3], [0,-15,15], [15,0,15], [0,15,3], [-15,0,15], [0,15,11], [15,0,3], [0,-15,11], [15,0,11], [0,15,3], [15,0,1], ] Clyde_directions = [ [-30,0,2], [0,-15,4], [15,0,5], [0,15,7], [-15,0,11], [0,-15,7], [-15,0,3], [0,15,7], [-15,0,7], [0,15,15], [15,0,15], [0,-15,3], [-15,0,11], [0,-15,7], [15,0,3], [0,-15,11], [15,0,9], ] pl = len(Pinky_directions) - 1 bl = len(Blinky_directions) - 1 il = len(Inky_directions) - 1 cl = len(Clyde_directions) - 1 # Call this function so the Pygame library can initialize itself pygame.init() # Create an 606x606 sized screen screen = pygame.display.set_mode([606, 606]) # This is a list of 'sprites.' Each block in the program is # added to this list. The list is managed by a class called 'RenderPlain.' # Set the title of the window pygame.display.set_caption('Melly the Vax-Man') # Create a surface we can draw on background = pygame.Surface(screen.get_size()) # Used for converting color maps and such background = background.convert() # Fill the screen with a dark grey background background.fill(darkGrey) clock = pygame.time.Clock() pygame.font.init() font = pygame.font.Font("freesansbold.ttf", 24) #default locations for Vax-Man and ghosts w = 303 - 16 # Width p_h = 19 + (7 * 60) # Vax-Man height m_h = 19 + (4 * 60) # Monster height b_h = 19 + (3 * 60) # Binky height i_w = 303 - 16 - 32 # Inky width c_w = 303 + (32 - 16) # Clyde width def startGame(): all_sprites_list = pygame.sprite.RenderPlain() block_list = pygame.sprite.RenderPlain() ghosts_list = pygame.sprite.RenderPlain() vaxman_collide = pygame.sprite.RenderPlain() wall_list = setupRoomOne(all_sprites_list) gate = setupGate(all_sprites_list) # Create the player paddle object Vaxman = Player(w, p_h, "images/Vaxman_Small.png") all_sprites_list.add(Vaxman) vaxman_collide.add(Vaxman) Blinkies = [] Pinkies = [] Inkies = [] Clydes = [] # Draw the grid for row in range(19): for column in range(19): if (row == 7 or row == 8) and (column == 8 or column == 9 or column == 10): continue else: block = Block(yellow, 4, 4) # Set a random location for the block block.rect.x = (30*column+6)+26 block.rect.y = (30*row+6)+26 b_collide = pygame.sprite.spritecollide(block, wall_list, False) p_collide = pygame.sprite.spritecollide(block, vaxman_collide, False) if b_collide: continue elif p_collide: continue else: # Add the block to the list of objects block_list.add(block) all_sprites_list.add(block) bll = len(block_list) score = 0 done = False i = 0 previousTime = 0; while done == False: # ALL EVENT PROCESSING SHOULD GO BELOW THIS COMMENT currentTime = time.time(); deltaTime = currentTime - previousTime; if previousTime == 0 or deltaTime > GHOST_MULTIPLICATION_TIME_GAP: if previousTime == 0 or Blinkies: Blinkies.append( { "entity" : Ghost(w, b_h, "images/Blinky.png"), "turn" : 0, "steps" : 0 } ) ghosts_list.add(Blinkies[-1]["entity"]) all_sprites_list.add(Blinkies[-1]["entity"]) if previousTime == 0 or Pinkies: Pinkies.append( { "entity" : Ghost(w, m_h, "images/Pinky.png"), "turn" : 0, "steps" : 0 } ) ghosts_list.add(Pinkies[-1]["entity"]) all_sprites_list.add(Pinkies[-1]["entity"]) if previousTime == 0 or Inkies: Inkies.append( { "entity" : Ghost(i_w, m_h, "images/Inky.png"), "turn" : 0, "steps" : 0 } ) ghosts_list.add(Inkies[-1]["entity"]) all_sprites_list.add(Inkies[-1]["entity"]) if previousTime == 0 or Clydes: Clydes.append( { "entity" : Ghost(c_w, m_h, "images/Clyde.png"), "turn" : 0, "steps" : 0 } ) ghosts_list.add(Clydes[-1]["entity"]) all_sprites_list.add(Clydes[-1]["entity"]) previousTime = currentTime for event in pygame.event.get(): if event.type == pygame.QUIT: done=True if event.type == pygame.KEYDOWN: if event.key == pygame.K_LEFT: Vaxman.changespeed(-30,0) if event.key == pygame.K_RIGHT: Vaxman.changespeed(30,0) if event.key == pygame.K_UP: Vaxman.changespeed(0,-30) if event.key == pygame.K_DOWN: Vaxman.changespeed(0,30) if event.type == pygame.KEYUP: if event.key == pygame.K_LEFT: Vaxman.changespeed(30,0) if event.key == pygame.K_RIGHT: Vaxman.changespeed(-30,0) if event.key == pygame.K_UP: Vaxman.changespeed(0,30) if event.key == pygame.K_DOWN: Vaxman.changespeed(0,-30) # ALL EVENT PROCESSING SHOULD GO ABOVE THIS COMMENT # ALL GAME LOGIC SHOULD GO BELOW THIS COMMENT Vaxman.update(wall_list, gate) for Pinky in Pinkies: returned = Pinky["entity"].changespeed(Pinky_directions, False, Pinky["turn"], Pinky["steps"], pl) Pinky["turn"] = returned[0] Pinky["steps"] = returned[1] Pinky["entity"].changespeed(Pinky_directions, False, Pinky["turn"], Pinky["steps"], pl) Pinky["entity"].update(wall_list, False) for Blinky in Blinkies: returned = Blinky["entity"].changespeed(Blinky_directions, False, Blinky["turn"], Blinky["steps"], bl) Blinky["turn"] = returned[0] Blinky["steps"] = returned[1] Blinky["entity"].changespeed(Blinky_directions, False, Blinky["turn"], Blinky["steps"], bl) Blinky["entity"].update(wall_list, False) for Inky in Inkies: returned = Inky["entity"].changespeed(Inky_directions, False, Inky["turn"], Inky["steps"], il) Inky["turn"] = returned[0] Inky["steps"] = returned[1] Inky["entity"].changespeed(Inky_directions, False, Inky["turn"], Inky["steps"], il) Inky["entity"].update(wall_list, False) for Clyde in Clydes: returned = Clyde["entity"].changespeed(Clyde_directions, "clyde", Clyde["turn"], Clyde["steps"], cl) Clyde["turn"] = returned[0] Clyde["steps"] = returned[1] Clyde["entity"].changespeed(Clyde_directions, "clyde", Clyde["turn"], Clyde["steps"], cl) Clyde["entity"].update(wall_list, False) # See if the Vax-Man block has collided with anything. blocks_hit_list = pygame.sprite.spritecollide(Vaxman, block_list, True) # Check the list of collisions. if len(blocks_hit_list) > 0: score +=len(blocks_hit_list) # ALL GAME LOGIC SHOULD GO ABOVE THIS COMMENT # ALL CODE TO DRAW SHOULD GO BELOW THIS COMMENT screen.fill(darkGrey) wall_list.draw(screen) gate.draw(screen) text=font.render("Score: "+str(score)+"/"+str(bll), True, darkRed) screen.blit(text, [10, 10]) if score == bll: userWantsToExit = doNext("Congratulations, you won!", 145, all_sprites_list, block_list, ghosts_list, vaxman_collide, wall_list, gate) if userWantsToExit: break ghosts_hit_list = pygame.sprite.spritecollide(Vaxman, ghosts_list, True) if ghosts_hit_list: for refBlinky in Blinkies: if refBlinky["entity"] in ghosts_hit_list: Blinkies = [Blinky for Blinky in Blinkies if Blinky != refBlinky] for refPinky in Pinkies: if refPinky["entity"] in ghosts_hit_list: Pinkies = [Pinky for Pinky in Pinkies if Pinky != refPinky] for refInky in Inkies: if refInky["entity"] in ghosts_hit_list: Inkies = [Inky for Inky in Inkies if Inky != refInky] for refClyde in Clydes: if refClyde["entity"] in ghosts_hit_list: Clydes = [Clyde for Clyde in Clydes if Clyde != refClyde] all_sprites_list.draw(screen) ghosts_list.draw(screen) if len(ghosts_list) >= MAXIMUM_GHOSTS: userWantsToExit = doNext("Game Over", 235, all_sprites_list, block_list, ghosts_list, vaxman_collide, wall_list, gate) if userWantsToExit: break # ALL CODE TO DRAW SHOULD GO ABOVE THIS COMMENT pygame.display.flip() clock.tick(10) def doNext(message, left, all_sprites_list, block_list, ghosts_list, vaxman_collide, wall_list, gate): while True: # ALL EVENT PROCESSING SHOULD GO BELOW THIS COMMENT for event in pygame.event.get(): if event.type == pygame.QUIT: pygame.quit() return True if event.type == pygame.KEYDOWN: if event.key == pygame.K_ESCAPE: pygame.quit() return True if event.key == pygame.K_RETURN: del all_sprites_list del block_list del ghosts_list del vaxman_collide del wall_list del gate startGame() return False #Grey background w = pygame.Surface((400,200)) # the size of your rect w.set_alpha(10) # alpha level w.fill((128,128,128)) # this fills the entire surface screen.blit(w, (100,200)) # (0,0) are the top-left coordinates #Won or lost text1=font.render(message, True, lightGrey) screen.blit(text1, [left, 233]) text2=font.render("To play again, press ENTER.", True, lightGrey) screen.blit(text2, [135, 303]) text3=font.render("To quit, press ESCAPE.", True, lightGrey) screen.blit(text3, [165, 333]) pygame.display.flip() clock.tick(10) startGame() pygame.quit()

29.025437

143

0.570083

4,397

0.240839

0

4,319

0.236567

02672c292331f32c5416bda0b2eba29281a17676

1,320

py

Python

examples/ecr/rl_formulations/common/state_shaper.py

zhawan/maro

d8c98deea4296cdcb90efd1fb59bc571cec3a2ef

[ "MIT" ]

null

examples/ecr/rl_formulations/common/state_shaper.py

zhawan/maro

d8c98deea4296cdcb90efd1fb59bc571cec3a2ef

[ "MIT" ]

null

examples/ecr/rl_formulations/common/state_shaper.py

zhawan/maro

d8c98deea4296cdcb90efd1fb59bc571cec3a2ef

[ "MIT" ]

null

# Copyright (c) Microsoft Corporation. # Licensed under the MIT license. import numpy as np from maro.rl import AbstractStateShaper class ECRStateShaper(AbstractStateShaper): def __init__(self, *, look_back, max_ports_downstream, port_attributes, vessel_attributes): super().__init__() self._look_back = look_back self._max_ports_downstream = max_ports_downstream self._port_attributes = port_attributes self._vessel_attributes = vessel_attributes self._dim = (look_back + 1) * (max_ports_downstream + 1) * len(port_attributes) + len(vessel_attributes) def __call__(self, decision_event, snapshot_list): tick, port_idx, vessel_idx = decision_event.tick, decision_event.port_idx, decision_event.vessel_idx ticks = [tick - rt for rt in range(self._look_back-1)] future_port_idx_list = snapshot_list["vessels"][tick: vessel_idx: 'future_stop_list'].astype('int') port_features = snapshot_list["ports"][ticks: [port_idx] + list(future_port_idx_list): self._port_attributes] vessel_features = snapshot_list["vessels"][tick: vessel_idx: self._vessel_attributes] state = np.concatenate((port_features, vessel_features)) return str(port_idx), state @property def dim(self): return self._dim

45.517241

117

0.724242

1,184

0.89697

0

53

0.040152

0

119

0.090152

0267eac0bf1a3be3319a75260f8b10b9d6a39d75

2,834

py

Python

src/runner.py

Shahrukh-Badar/DeepLearning

5f6bbd6f8ace06014f10e35183442901d984b231

[ "MIT" ]

null

src/runner.py

Shahrukh-Badar/DeepLearning

5f6bbd6f8ace06014f10e35183442901d984b231

[ "MIT" ]

null

src/runner.py

Shahrukh-Badar/DeepLearning

5f6bbd6f8ace06014f10e35183442901d984b231

[ "MIT" ]

null

from os import listdir from os.path import join, isfile import json from random import randint ######################################### ## START of part that students may change from code_completion_baseline import Code_Completion_Baseline training_dir = "./../../programs_800/" query_dir = "./../../programs_200/" model_file = "./../../trained_model" use_stored_model = False max_hole_size = 2 simplify_tokens = True ## END of part that students may change ######################################### def simplify_token(token): if token["type"] == "Identifier": token["value"] = "ID" elif token["type"] == "String": token["value"] = "\"STR\"" elif token["type"] == "RegularExpression": token["value"] = "/REGEXP/" elif token["type"] == "Numeric": token["value"] = "5" # load sequences of tokens from files def load_tokens(token_dir): token_files = [join(token_dir, f) for f in listdir(token_dir) if isfile(join(token_dir, f)) and f.endswith("_tokens.json")] token_lists = [json.load(open(f)) for f in token_files] if simplify_tokens: for token_list in token_lists: for token in token_list: simplify_token(token) return token_lists # removes up to max_hole_size tokens def create_hole(tokens): hole_size = randint(1, max_hole_size) hole_start_idx = randint(1, len(tokens) - hole_size) prefix = tokens[0:hole_start_idx] expected = tokens[hole_start_idx:hole_start_idx + hole_size] suffix = tokens[hole_start_idx + hole_size:] return(prefix, expected, suffix) # checks if two sequences of tokens are identical def same_tokens(tokens1, tokens2): if len(tokens1) != len(tokens2): return False for idx, t1 in enumerate(tokens1): t2 = tokens2[idx] if t1["type"] != t2["type"] or t1["value"] != t2["value"]: return False return True ######################################### ## START of part that students may change code_completion = Code_Completion_Baseline() ## END of part that students may change ######################################### # train the network training_token_lists = load_tokens(training_dir) if use_stored_model: code_completion.load(training_token_lists, model_file) else: code_completion.train(training_token_lists, model_file) # query the network and measure its accuracy query_token_lists = load_tokens(query_dir) correct = incorrect = 0 for tokens in query_token_lists: (prefix, expected, suffix) = create_hole(tokens) completion = code_completion.query(prefix, suffix) if same_tokens(completion, expected): correct += 1 else: incorrect += 1 accuracy = correct / (correct + incorrect) print("Accuracy: " + str(correct) + " correct vs. " + str(incorrect) + " incorrect = " + str(accuracy))

32.953488

127

0.650318

0

786

0.277347

0268d3f7d9cf4572520e699a426fa385cc8944bc

4,491

py

Python

superhelp/formatters/cli_formatter.py

grantps/superhelp

d8e861bf1ad91571ac23b9c833a8cd461bb1952f

[ "MIT" ]

27

2020-05-17T20:48:43.000Z

2022-01-08T21:32:30.000Z

superhelp/formatters/cli_formatter.py

grantps/superhelp

d8e861bf1ad91571ac23b9c833a8cd461bb1952f

[ "MIT" ]

null

superhelp/formatters/cli_formatter.py

grantps/superhelp

d8e861bf1ad91571ac23b9c833a8cd461bb1952f

[ "MIT" ]

null

from pathlib import Path from textwrap import dedent from superhelp import conf from superhelp.conf import Level, Theme from superhelp.formatters.cli_extras import md2cli from superhelp.formatters.cli_extras.cli_colour import set_global_colours from superhelp.gen_utils import (get_code_desc, get_intro, get_line_numbered_snippet, layout_comment as layout) """ Note - displays properly in the terminal but not necessarily in other output e.g. Eclipse console. Lots in common with md displayer but risks of DRYing probably outweigh benefits at this stage. Probably should swap out for https://github.com/willmcgugan/rich """ TERMINAL_WIDTH = 80 MDV_CODE_BOUNDARY = "```" def get_message(message_dets, detail_level: Level): message = dedent(message_dets.message[detail_level]) if detail_level == Level.EXTRA: message = dedent(message_dets.message[Level.MAIN]) + message message = dedent(message) message = (message .replace(f" {conf.PYTHON_CODE_START}", MDV_CODE_BOUNDARY) .replace(f"\n {conf.PYTHON_CODE_END}", MDV_CODE_BOUNDARY) ) message = md2cli.main(md=message.replace('`', '')) ## They create problems in formatting return message def _need_snippet_displayed(overall_messages_dets, block_messages_dets, *, multi_block=False): """ Don't need to see the code snippet displayed when it is already visible: * because there is only one block in snippet and there is a block message for it (which will display the block i.e. the entire snippet) UNLESS there is an overall message separating them Otherwise we need it displayed. """ mono_block_snippet = not multi_block if mono_block_snippet and block_messages_dets and not overall_messages_dets: return False return True def get_formatted_help(code: str, file_path: Path, messages_dets, *, detail_level: Level = Level.BRIEF, theme_name: Theme = Theme.LIGHT, warnings_only=False, multi_block=False) -> str: """ Show by code blocks. """ set_global_colours(theme_name) md2cli.term_columns = TERMINAL_WIDTH if warnings_only: options_msg = conf.WARNINGS_ONLY_MSG else: options_msg = conf.ALL_HELP_SHOWING_MSG intro = get_intro(file_path, multi_block=multi_block) text = [ md2cli.main(layout(f"""\ # SuperHELP - Help for Humans! {intro} Currently showing {detail_level} content as requested. {options_msg}. {conf.MISSING_ADVICE_MESSAGE} ## Help by spreading the word about SuperHELP on social media. {conf.FORCE_SPLIT}Twitter: {conf.TWITTER_HANDLE}. Thanks! """ )), ] overall_messages_dets, block_messages_dets = messages_dets display_snippet = _need_snippet_displayed( overall_messages_dets, block_messages_dets, multi_block=multi_block) if display_snippet: line_numbered_snippet = get_line_numbered_snippet(code) code_desc = get_code_desc(file_path) text.append(md2cli.main(dedent( f"## {code_desc}" f"\n{MDV_CODE_BOUNDARY}\n" + line_numbered_snippet + f"\n{MDV_CODE_BOUNDARY}"))) for message_dets in overall_messages_dets: message = get_message(message_dets, detail_level) text.append(message) block_messages_dets.sort(key=lambda nt: (nt.first_line_no, nt.warning)) prev_line_no = None for message_dets in block_messages_dets: ## display code for line number (once ;-)) line_no = message_dets.first_line_no new_block = (line_no != prev_line_no) if new_block: block_has_warning_header = False text.append(md2cli.main(dedent( f'## Code block starting line {line_no:,}' f"\n{MDV_CODE_BOUNDARY}\n" + message_dets.code_str + f"\n{MDV_CODE_BOUNDARY}"))) prev_line_no = line_no if message_dets.warning and not block_has_warning_header: text.append(md2cli.main(layout("""\ ### Questions / Warnings There may be some issues with this code block you want to address. """))) block_has_warning_header = True ## process message message = get_message(message_dets, detail_level) text.append(message) formatted_help = '\n'.join(text) return formatted_help

37.115702

93

0.674905

0

1,497

0.333333

0268e7698751adcedb3a0f8d62ab2e3667fd33f3

4,941

py

Python

atom/instance.py

enthought/atom

1f194e3550d62c4ca1d79521dff97531ffe3f0ac

[ "BSD-3-Clause" ]

null

atom/instance.py

enthought/atom

1f194e3550d62c4ca1d79521dff97531ffe3f0ac

[ "BSD-3-Clause" ]

1

2020-12-04T10:11:07.000Z

2020-12-04T10:13:46.000Z

atom/instance.py

enthought/atom

1f194e3550d62c4ca1d79521dff97531ffe3f0ac

[ "BSD-3-Clause" ]

1

2020-12-04T10:05:32.000Z

#------------------------------------------------------------------------------ # Copyright (c) 2013, Enthought, Inc. # All rights reserved. #------------------------------------------------------------------------------ from .catom import ( Member, DEFAULT_FACTORY, DEFAULT_VALUE, USER_DEFAULT, VALIDATE_INSTANCE, USER_VALIDATE ) class Instance(Member): """ A value which allows objects of a given type or types. Values will be tested using the `PyObject_IsInstance` C API call. This call is equivalent to `isinstance(value, kind)` and all the same rules apply. The value of an Instance may also be set to None. """ __slots__ = () def __init__(self, kind, factory=None, args=None, kwargs=None): """ Initialize an Instance. Parameters ---------- kind : type or tuple of types The allowed type or types for the instance. factory : callable, optional An optional factory to use for creating the default value. If this is not provided and 'args' and 'kwargs' is None, then the default value will be None. args : tuple, optional If 'factory' is None, then 'kind' is a callable type and these arguments will be passed to the constructor to create the default value. kwargs : dict, optional If 'factory' is None, then 'kind' is a callable type and these keywords will be passed to the constructor to create the default value. """ if factory is not None: self.set_default_kind(DEFAULT_FACTORY, factory) elif args is not None or kwargs is not None: args = args or () kwargs = kwargs or {} factory = lambda: kind(*args, **kwargs) self.set_default_kind(DEFAULT_FACTORY, factory) else: self.set_default_kind(DEFAULT_VALUE, None) self.set_validate_kind(VALIDATE_INSTANCE, kind) class ForwardInstance(Instance): """ An Instance which delays resolving the type definition. The first time the value is accessed or modified, the type will be resolved and the forward instance will behave identically to a normal instance. """ __slots__ = () def __init__(self, resolve, factory=None, args=None, kwargs=None): """ Initialize a ForwardInstance. resolve : callable A callable which takes no arguments and returns the type or tuple of types to use for validating the values. factory : callable, optional An optional factory to use for creating the default value. If this is not provided and 'args' and 'kwargs' is None, then the default value will be None. args : tuple, optional If 'factory' is None, then 'resolve' will return a callable type and these arguments will be passed to the constructor to create the default value. kwargs : dict, optional If 'factory' is None, then 'resolve' will return a callable type and these keywords will be passed to the constructor to create the default value. """ if factory is not None: self.set_default_kind(DEFAULT_FACTORY, factory) elif args is not None or kwargs is not None: args = args or () kwargs = kwargs or {} self.set_default_kind(USER_DEFAULT, (args, kwargs)) else: self.set_default_kind(DEFAULT_VALUE, None) self.set_validate_kind(USER_VALIDATE, resolve) def default(self, owner, name): """ Called to retrieve the default value. This will resolve and instantiate the type. It will then update the internal default and validate handlers to behave like a normal instance member. """ resolve = self.validate_kind[1] kind = resolve() args, kwargs = self.default_kind[1] value = kind(*args, **kwargs) self.set_default_kind(DEFAULT_FACTORY, lambda: kind(*args, **kwargs)) self.set_validate_kind(VALIDATE_INSTANCE, kind) return value def validate(self, owner, name, old, new): """ Called to validate the value. This will resolve the type and validate the new value. It will then update the internal default and validate handlers to behave like a normal instance member. """ resolve = self.validate_kind[1] kind = resolve() if not isinstance(new, kind): raise TypeError('invalid instance type') self.set_validate_kind(VALIDATE_INSTANCE, kind) if self.default_kind[0] == USER_DEFAULT: args, kwargs = self.default_kind[1] factory = lambda: kind(*args, **kwargs) self.set_default_kind(DEFAULT_FACTORY, factory) return new

36.065693

79

0.608379

4,593

0.929569

0

2,885

0.58389

0268f15772e163a48707362a23538e64ee3c364e

4,744

py

Python

operators/elastic-cloud-eck/python/pulumi_pulumi_kubernetes_crds_operators_elastic_cloud_eck/_tables.py

pulumi/pulumi-kubernetes-crds

372c4c0182f6b899af82d6edaad521aa14f22150

[ "Apache-2.0" ]

null

operators/elastic-cloud-eck/python/pulumi_pulumi_kubernetes_crds_operators_elastic_cloud_eck/_tables.py

pulumi/pulumi-kubernetes-crds

372c4c0182f6b899af82d6edaad521aa14f22150

[ "Apache-2.0" ]

2

2020-09-18T17:12:23.000Z

2020-12-30T19:40:56.000Z

operators/elastic-cloud-eck/python/pulumi_pulumi_kubernetes_crds_operators_elastic_cloud_eck/_tables.py

pulumi/pulumi-kubernetes-crds

372c4c0182f6b899af82d6edaad521aa14f22150

[ "Apache-2.0" ]

null

# coding=utf-8 # *** WARNING: this file was generated by crd2pulumi. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** SNAKE_TO_CAMEL_CASE_TABLE = { "access_modes": "accessModes", "api_group": "apiGroup", "api_version": "apiVersion", "app_protocol": "appProtocol", "association_status": "associationStatus", "available_nodes": "availableNodes", "change_budget": "changeBudget", "client_ip": "clientIP", "cluster_ip": "clusterIP", "config_ref": "configRef", "daemon_set": "daemonSet", "data_source": "dataSource", "elasticsearch_association_status": "elasticsearchAssociationStatus", "elasticsearch_ref": "elasticsearchRef", "expected_nodes": "expectedNodes", "external_i_ps": "externalIPs", "external_name": "externalName", "external_traffic_policy": "externalTrafficPolicy", "file_realm": "fileRealm", "health_check_node_port": "healthCheckNodePort", "ip_family": "ipFamily", "kibana_association_status": "kibanaAssociationStatus", "kibana_ref": "kibanaRef", "last_probe_time": "lastProbeTime", "last_transition_time": "lastTransitionTime", "load_balancer_ip": "loadBalancerIP", "load_balancer_source_ranges": "loadBalancerSourceRanges", "match_expressions": "matchExpressions", "match_labels": "matchLabels", "max_surge": "maxSurge", "max_unavailable": "maxUnavailable", "min_available": "minAvailable", "node_port": "nodePort", "node_sets": "nodeSets", "pod_disruption_budget": "podDisruptionBudget", "pod_template": "podTemplate", "publish_not_ready_addresses": "publishNotReadyAddresses", "remote_clusters": "remoteClusters", "rolling_update": "rollingUpdate", "secret_name": "secretName", "secret_token_secret": "secretTokenSecret", "secure_settings": "secureSettings", "self_signed_certificate": "selfSignedCertificate", "service_account_name": "serviceAccountName", "session_affinity": "sessionAffinity", "session_affinity_config": "sessionAffinityConfig", "storage_class_name": "storageClassName", "subject_alt_names": "subjectAltNames", "target_port": "targetPort", "timeout_seconds": "timeoutSeconds", "topology_keys": "topologyKeys", "update_strategy": "updateStrategy", "volume_claim_templates": "volumeClaimTemplates", "volume_mode": "volumeMode", "volume_name": "volumeName", } CAMEL_TO_SNAKE_CASE_TABLE = { "accessModes": "access_modes", "apiGroup": "api_group", "apiVersion": "api_version", "appProtocol": "app_protocol", "associationStatus": "association_status", "availableNodes": "available_nodes", "changeBudget": "change_budget", "clientIP": "client_ip", "clusterIP": "cluster_ip", "configRef": "config_ref", "daemonSet": "daemon_set", "dataSource": "data_source", "elasticsearchAssociationStatus": "elasticsearch_association_status", "elasticsearchRef": "elasticsearch_ref", "expectedNodes": "expected_nodes", "externalIPs": "external_i_ps", "externalName": "external_name", "externalTrafficPolicy": "external_traffic_policy", "fileRealm": "file_realm", "healthCheckNodePort": "health_check_node_port", "ipFamily": "ip_family", "kibanaAssociationStatus": "kibana_association_status", "kibanaRef": "kibana_ref", "lastProbeTime": "last_probe_time", "lastTransitionTime": "last_transition_time", "loadBalancerIP": "load_balancer_ip", "loadBalancerSourceRanges": "load_balancer_source_ranges", "matchExpressions": "match_expressions", "matchLabels": "match_labels", "maxSurge": "max_surge", "maxUnavailable": "max_unavailable", "minAvailable": "min_available", "nodePort": "node_port", "nodeSets": "node_sets", "podDisruptionBudget": "pod_disruption_budget", "podTemplate": "pod_template", "publishNotReadyAddresses": "publish_not_ready_addresses", "remoteClusters": "remote_clusters", "rollingUpdate": "rolling_update", "secretName": "secret_name", "secretTokenSecret": "secret_token_secret", "secureSettings": "secure_settings", "selfSignedCertificate": "self_signed_certificate", "serviceAccountName": "service_account_name", "sessionAffinity": "session_affinity", "sessionAffinityConfig": "session_affinity_config", "storageClassName": "storage_class_name", "subjectAltNames": "subject_alt_names", "targetPort": "target_port", "timeoutSeconds": "timeout_seconds", "topologyKeys": "topology_keys", "updateStrategy": "update_strategy", "volumeClaimTemplates": "volume_claim_templates", "volumeMode": "volume_mode", "volumeName": "volume_name", }

39.533333

80

0.707841

0

3,795

0.799958

026b557b15ada072d61283c89f10a088c8637df4

1,416

py

Python

webapp/app.py

aleksandergurin/news

9e7d3c35857600445cb6df42ba18d289dc0e37a9

[ "BSD-3-Clause" ]

3

2015-08-20T11:08:28.000Z

2018-01-28T21:22:53.000Z

webapp/app.py

aleksandergurin/news

9e7d3c35857600445cb6df42ba18d289dc0e37a9

[ "BSD-3-Clause" ]

null

webapp/app.py

aleksandergurin/news

9e7d3c35857600445cb6df42ba18d289dc0e37a9

[ "BSD-3-Clause" ]

null

from flask import Flask, render_template from config import configs from .extensions import login_manager, db from .account import account from .frontend import frontend from webapp.session import RedisSessionInterface def create_app(config_name): app = Flask(__name__) app.config.from_object(configs[config_name]) register_session_storage(app, configs[config_name]) register_blueprints(app) init_extensions(app) add_error_pages(app) return app def register_session_storage(app, conf): if hasattr(conf, 'REDIS'): from redis import Redis host = conf.REDIS['host'] port = conf.REDIS['port'] db_num = conf.REDIS['db'] app.session_interface = RedisSessionInterface(Redis(host, port, db_num)) def register_blueprints(app): app.register_blueprint(frontend) app.register_blueprint(account) def init_extensions(app): login_manager.init_app(app) db.init_app(app) def add_error_pages(app): @app.errorhandler(401) def unauthorized(e): return render_template('errors/401.html'), 401 @app.errorhandler(403) def forbidden(e): return render_template('errors/403.html'), 403 @app.errorhandler(404) def not_found(e): return render_template('errors/404.html'), 404 @app.errorhandler(500) def internal_server_error(e): return render_template('errors/500.html'), 500

24.413793

80

0.711864

0

411

0.290254

0

91

0.064266

026bd83279fbac0f51bacbf47138a5022a5dd278

27,723

py

Python

src/ezcode/knapsack/__init__.py

zheng-gao/ez_code

fbf48990291aa57d6436d4548b0a6c25dfb8f82d

[ "MIT" ]

null

src/ezcode/knapsack/__init__.py

zheng-gao/ez_code

fbf48990291aa57d6436d4548b0a6c25dfb8f82d

[ "MIT" ]

null

src/ezcode/knapsack/__init__.py

zheng-gao/ez_code

fbf48990291aa57d6436d4548b0a6c25dfb8f82d

[ "MIT" ]

null

from typing import Callable class Knapsack: @staticmethod def best_value( capacity: int, sizes: list, values: list, quantities, min_max: Callable = max, zero_capacity_value=0, fill_to_capacity=True, output_item_list=True ): if capacity < 0: raise ValueError(f"Capacity cannot be negative: {capacity}") for s in sizes: if s <= 0: raise ValueError(f"Item sizes must be positive: {sizes}") if len(sizes) != len(values): raise ValueError(f"The length of sizes {sizes} not match the length of values {values}") if quantities: if isinstance(quantities, list): if len(quantities) != len(sizes): raise ValueError(f"The length of quantities {quantities} not match the length of sizes {sizes}") for q in quantities: if q < 0: raise ValueError(f"Item quantities cannot contain negative: {quantities}") elif quantities < 0: raise ValueError(f"Item quantities cannot be negative: {quantities}") return Knapsack.best_value_with_limited_items_1d( capacity=capacity, sizes=sizes, values=values, quantities=quantities, min_max=min_max, zero_capacity_value=zero_capacity_value, fill_to_capacity=fill_to_capacity, output_dp_table=False, output_item_list=output_item_list ) else: return Knapsack.best_value_with_unlimited_items_1d( capacity=capacity, sizes=sizes, values=values, min_max=min_max, zero_capacity_value=zero_capacity_value, fill_to_capacity=fill_to_capacity, output_dp_table=False, output_item_list=output_item_list ) @staticmethod def ways_to_fill( capacity: int, sizes: list, quantities, output_item_list=True ): if capacity < 0: raise ValueError(f"Capacity cannot be negative: {capacity}") for s in sizes: if s <= 0: raise ValueError(f"Item sizes must be positive: {sizes}") if quantities: if isinstance(quantities, list): if len(quantities) != len(sizes): raise ValueError(f"The length of quantities {quantities} not match the length of sizes {sizes}") for q in quantities: if q < 0: raise ValueError(f"Item quantities cannot contain negative: {quantities}") elif quantities < 0: raise ValueError(f"Item quantities cannot be negative: {quantities}") return Knapsack.number_of_ways_to_fill_to_capacity_with_limited_items_1d( capacity=capacity, sizes=sizes, quantities=quantities, output_dp_table=False, output_item_list=output_item_list ) else: return Knapsack.number_of_ways_to_fill_to_capacity_with_unlimited_items_1d( capacity=capacity, sizes=sizes, output_dp_table=False, output_item_list=output_item_list ) @staticmethod def best_value_with_limited_items_2d( capacity: int, sizes: list, values: list, min_max: Callable = max, zero_capacity_value=0, fill_to_capacity=True, iterate_sizes_first=True, output_dp_table=False, output_item_list=True ): """ 0-1 Knapsack Bag Capacity = C Items Sizes = [s0, s1, ... ] Items Values = [v0, v1, ... ] 2D-Array "max_value" Init Cap=[0, 1, 2, ... c_j-1, c_j, ..., C] s_0 0, 0, 0, ... 0, v_0, ..., v_0 (where c_j-1 < w0 < c_j) s_1 0, ... 0, Max Value s_i 0, Other cells will be overwritten later ... 0, s_N 0, The meaning of max_value[i][c]: Given the FIRST "i + 1" items, the max value of a bag of size "c" can make value_without_item_i = max_value[i-1][c] value_with_item_i = max_value[i - 1][c - w[i]] + v[i] max_value[i - 1][c - w[i]] means if we put item i into the bag (+v[i]), the max value that the rest of the capacity "c - w[i]" can make with a selection of the previous items if the capacity of the bag is not large enough for the item i, max_value[i][c] = max_value[i - 1][c] otherwise max_value[i][c] = max( value_without_item_i + value_with_item_i ) """ infinity = float("-inf") if min_max == max else float("inf") knapsack_init_value = infinity if fill_to_capacity else zero_capacity_value knapsack_value = [[knapsack_init_value for _ in range(capacity + 1)] for _ in range(len(sizes))] item_lists = None if output_item_list: item_lists = [[list() for _ in range(capacity + 1)] for _ in range(len(sizes))] for i in range(len(sizes)): # init first column knapsack_value[i][0] = zero_capacity_value if fill_to_capacity: knapsack_value[0][sizes[0]] = values[0] # init first row, c != w means not filled if output_item_list: item_lists[0][sizes[0]].append(0) else: for c in range(sizes[0], capacity + 1): # init first row, c < w means the bag is empty knapsack_value[0][c] = values[0] if output_item_list: item_lists[0][c].append(0) if iterate_sizes_first: # we can iterate either of the sizes or capacity first for i in range(1, len(sizes)): for c in range(1, capacity + 1): if c < sizes[i]: knapsack_value[i][c] = knapsack_value[i - 1][c] else: knapsack_value[i][c] = min_max(knapsack_value[i - 1][c], knapsack_value[i - 1][c - sizes[i]] + values[i]) if output_item_list: if knapsack_value[i][c] == knapsack_init_value: item_lists[i][c] = list() elif knapsack_value[i][c] == knapsack_value[i - 1][c]: item_lists[i][c] = item_lists[i - 1][c].copy() else: item_lists[i][c] = item_lists[i - 1][c - sizes[i]] + [i] else: for c in range(1, capacity + 1): for i in range(1, len(sizes)): if c < sizes[i]: knapsack_value[i][c] = knapsack_value[i - 1][c] else: knapsack_value[i][c] = min_max(knapsack_value[i - 1][c], knapsack_value[i - 1][c - sizes[i]] + values[i]) if output_item_list: if knapsack_value[i][c] == knapsack_init_value: item_lists[i][c] = list() elif knapsack_value[i][c] == knapsack_value[i - 1][c]: item_lists[i][c] = item_lists[i - 1][c].copy() else: item_lists[i][c] = item_lists[i - 1][c - sizes[i]] + [i] if output_dp_table: return (knapsack_value, item_lists) if output_item_list else knapsack_value else: best_value = knapsack_value[len(sizes) - 1][capacity] if output_item_list: item_list = item_lists[len(sizes) - 1][capacity] return (None, item_list) if best_value == knapsack_init_value else (best_value, item_list) else: return None if best_value == knapsack_init_value else best_value @staticmethod def best_value_with_limited_items_1d( capacity: int, sizes: list, values: list, quantities=1, min_max: Callable = max, zero_capacity_value=0, fill_to_capacity=True, output_dp_table=False, output_item_list=True ): """ Rolling dp array: copy row i-1 to row i We just need one row: knapsack_value[c] means the max value that a bag with capacity c can make Each loop will overwrite the knapsack_value[c] Cannot swap loops """ if isinstance(quantities, int): quantities_list = list() for i in range(len(sizes)): quantities_list.append(quantities) quantities = quantities_list else: assert len(sizes) == len(quantities) infinity = float("-inf") if min_max == max else float("inf") knapsack_init_value = infinity if fill_to_capacity else zero_capacity_value knapsack_value = [knapsack_init_value for _ in range(capacity + 1)] knapsack_value[0] = zero_capacity_value item_lists = None if output_item_list: item_lists = [list() for _ in range(capacity + 1)] for i in range(len(sizes)): # must loop item sizes first, because we are rolling the rows not columns for q in range(1, quantities[i] + 1): # it is same as flatten the items: sizes=[2,3] quantities=[1,2] ==> sizes=[2, 3, 3] # c < sizes[i], knapsack_value[c] won't change # Capacity is looping backward, otherwise the item will be put in to the knapsack multiple times for c in range(capacity, sizes[i] - 1, -1): knapsack_value[c] = min_max(knapsack_value[c], knapsack_value[c - sizes[i]] + values[i]) if output_item_list: if knapsack_value[c] == knapsack_init_value: item_lists[c] = list() elif knapsack_value[c] == knapsack_value[c - sizes[i]] + values[i]: item_lists[c] = item_lists[c - sizes[i]] + [i] # Another solution # for c in range(capacity, sizes[i] - 1, -1): # for q in range(1, min(quantities[i], c // sizes[i]) + 1): # knapsack_value[c] = min_max(knapsack_value[c], knapsack_value[c - q * sizes[i]] + q * values[i]) # if output_item_list: # if knapsack_value[c] == knapsack_init_value: # item_lists[c] = list() # elif knapsack_value[c] == knapsack_value[c - q * sizes[i]] + q * values[i]: # item_lists[c] = item_lists[c - q * sizes[i]] + [i] * q if output_dp_table: return (knapsack_value, item_lists) if output_item_list else knapsack_value else: best_value = knapsack_value[capacity] if output_item_list: return (None, item_lists[capacity]) if best_value == knapsack_init_value else (best_value, item_lists[capacity]) else: return None if best_value == knapsack_init_value else best_value @staticmethod def best_value_with_unlimited_items_1d( capacity: int, sizes: list, values: list, min_max: Callable = max, zero_capacity_value=0, fill_to_capacity=True, iterate_sizes_first=True, output_dp_table=False, output_item_list=True ): """ Similar to rolling row solution, but the two loops can swap the order """ infinity = float("-inf") if min_max == max else float("inf") knapsack_init_value = infinity if fill_to_capacity else zero_capacity_value knapsack_value = [knapsack_init_value for _ in range(capacity + 1)] knapsack_value[0] = zero_capacity_value item_lists = None if output_item_list: item_lists = [list() for _ in range(capacity + 1)] if iterate_sizes_first: for i in range(len(sizes)): for c in range(sizes[i], capacity + 1): # Looping forward, so items can be added multiple times knapsack_value[c] = min_max(knapsack_value[c], knapsack_value[c - sizes[i]] + values[i]) if output_item_list: if knapsack_value[c] == knapsack_init_value: item_lists[c] = list() elif knapsack_value[c] == knapsack_value[c - sizes[i]] + values[i]: item_lists[c] = item_lists[c - sizes[i]] + [i] else: for c in range(1, capacity + 1): # Looping forward, so items can be added multiple times for i in range(len(sizes)): if c >= sizes[i]: # c < sizes[i], knapsack_value[c] won't change knapsack_value[c] = min_max(knapsack_value[c], knapsack_value[c - sizes[i]] + values[i]) if output_item_list: if knapsack_value[c] == knapsack_init_value: item_lists[c] = list() elif knapsack_value[c] == knapsack_value[c - sizes[i]] + values[i]: item_lists[c] = item_lists[c - sizes[i]] + [i] if output_dp_table: return (knapsack_value, item_lists) if output_item_list else knapsack_value else: best_value = knapsack_value[capacity] if output_item_list: return (None, item_lists[capacity]) if best_value == knapsack_init_value else (best_value, item_lists[capacity]) else: return None if best_value == knapsack_init_value else best_value @staticmethod def best_value_with_unlimited_items_2d( capacity: int, sizes: list, values: list, min_max: Callable = max, zero_capacity_value=0, fill_to_capacity=True, iterate_sizes_first=True, output_dp_table=False, output_item_list=True ): infinity = float("-inf") if min_max == max else float("inf") knapsack_init_value = infinity if fill_to_capacity else zero_capacity_value knapsack_value = [[knapsack_init_value for _ in range(capacity + 1)] for _ in range(len(sizes))] item_lists = None if output_item_list: item_lists = [[list() for _ in range(capacity + 1)] for _ in range(len(sizes))] for i in range(len(sizes)): # init first column knapsack_value[i][0] = zero_capacity_value for c in range(sizes[0], capacity + 1): # init first row, c < w means the bag is empty, c != w means not fill if c % sizes[0] == 0 or not fill_to_capacity: knapsack_value[0][c] = values[0] * (c // sizes[0]) if output_item_list: item_lists[0][c].extend([0] * (c // sizes[0])) if iterate_sizes_first: # we can iterate either of the sizes or capacity first for i in range(1, len(sizes)): for c in range(1, capacity + 1): # if c < sizes[i]: # knapsack_value[i][c] = knapsack_value[i - 1][c] # else: # best_value = knapsack_init_value # for k in range(1, (c // sizes[i]) + 1): # best_value = min_max(best_value, knapsack_value[i - 1][c - k * sizes[i]] + k * values[i]) # knapsack_value[i][c] = min_max(knapsack_value[i - 1][c], best_value) knapsack_value[i][c] = knapsack_value[i - 1][c] if output_item_list: item_lists[i][c] = item_lists[i - 1][c].copy() if c >= sizes[i]: knapsack_value[i][c] = min_max(knapsack_value[i][c], knapsack_value[i][c - sizes[i]] + values[i]) if output_item_list: if knapsack_value[i][c] == knapsack_init_value: item_lists[i][c] = list() elif knapsack_value[i][c] == knapsack_value[i][c - sizes[i]] + values[i]: item_lists[i][c] = item_lists[i][c - sizes[i]] + [i] else: for c in range(1, capacity + 1): for i in range(1, len(sizes)): # if c < sizes[i]: # knapsack_value[i][c] = knapsack_value[i - 1][c] # else: # best_value = knapsack_init_value # for k in range(1, (c // sizes[i]) + 1): # best_value = min_max(best_value, knapsack_value[i - 1][c - k * sizes[i]] + k * values[i]) # knapsack_value[i][c] = min_max(knapsack_value[i - 1][c], best_value) knapsack_value[i][c] = knapsack_value[i - 1][c] if output_item_list: item_lists[i][c] = item_lists[i - 1][c].copy() if c >= sizes[i]: knapsack_value[i][c] = min_max(knapsack_value[i][c], knapsack_value[i][c - sizes[i]] + values[i]) if output_item_list: if knapsack_value[i][c] == knapsack_init_value: item_lists[i][c] = list() elif knapsack_value[i][c] == knapsack_value[i][c - sizes[i]] + values[i]: item_lists[i][c] = item_lists[i][c - sizes[i]] + [i] if output_dp_table: return (knapsack_value, item_lists) if output_item_list else knapsack_value else: best_value = knapsack_value[len(sizes) - 1][capacity] if output_item_list: item_list = item_lists[len(sizes) - 1][capacity] return (None, item_list) if best_value == knapsack_init_value else (best_value, item_list) else: return None if best_value == knapsack_init_value else best_value @staticmethod def number_of_ways_to_fill_to_capacity_with_unlimited_items_2d( capacity: int, sizes: list, output_dp_table=False, output_item_list=True ): """ number_of_ways[i][c] means given the FIRST i + 1 items, the number of ways to make capacity c number_of_ways[i][c] = number_of_ways[i - 1][c] + number_of_ways[i][c - sizes[i]] """ number_of_ways = [[0 for _ in range(capacity + 1)] for _ in range(len(sizes))] combo_lists = None if output_item_list: combo_lists = [[None for _ in range(capacity + 1)] for _ in range(len(sizes))] for i in range(len(sizes)): # init first column number_of_ways[i][0] = 1 # no item for 0 capacity is 1 way if output_item_list: combo_lists[i][0] = [[]] # empty list for no item combo for c in range(sizes[0], capacity + 1): # init first row if c % sizes[0] == 0: number_of_ways[0][c] = 1 if output_item_list: combo_lists[0][c] = [[0] * (c // sizes[0])] # one combo of all the item 0 for i in range(1, len(sizes)): for c in range(1, capacity + 1): number_of_ways[i][c] = number_of_ways[i - 1][c] if c >= sizes[i]: number_of_ways[i][c] += number_of_ways[i][c - sizes[i]] # On the same line, no i - 1 if output_item_list: combo_lists[i][c] = combo_lists[i - 1][c] if c >= sizes[i] and combo_lists[i][c - sizes[i]] is not None: new_combo_list = list() for combo in combo_lists[i][c - sizes[i]]: new_combo_list.append(combo + [i]) combo_lists[i][c] = combo_lists[i][c] + new_combo_list if combo_lists[i][c] is not None else new_combo_list if output_dp_table: return (number_of_ways, combo_lists) if output_item_list else number_of_ways else: best_value = number_of_ways[len(sizes) - 1][capacity] if output_item_list: combo_list = combo_lists[len(sizes) - 1][capacity] return (best_value, combo_list) else: return best_value @staticmethod def number_of_ways_to_fill_to_capacity_with_unlimited_items_1d( capacity: int, sizes: list, output_dp_table=False, output_item_list=True ): """ number_of_ways[c] means the number of ways to make capacity c rolling row[i-1] over to row[i] number_of_ways[c] = number_of_ways[c] + number_of_ways[c - sizes[i]] """ number_of_ways = [0 for _ in range(capacity + 1)] combo_lists = None if output_item_list: combo_lists = [None for _ in range(capacity + 1)] number_of_ways[0] = 1 # no item for 0 capacity is 1 way if output_item_list: combo_lists[0] = [[]] # empty list for no item combo for i in range(len(sizes)): for c in range(sizes[i], capacity + 1): # c starts from sizes[i] (c >= sizes[i]) number_of_ways[c] += number_of_ways[c - sizes[i]] # + (c > sizes[i] and c % sizes[i] == 0) if output_item_list: if combo_lists[c - sizes[i]] is not None: new_combo_list = list() for combo in combo_lists[c - sizes[i]]: new_combo_list.append(combo + [i]) combo_lists[c] = combo_lists[c] + new_combo_list if combo_lists[c] is not None else new_combo_list if output_dp_table: return (number_of_ways, combo_lists) if output_item_list else number_of_ways else: best_value = number_of_ways[capacity] if output_item_list: combo_list = combo_lists[capacity] return (best_value, combo_list) else: return best_value @staticmethod def number_of_ways_to_fill_to_capacity_with_limited_items_2d( capacity: int, sizes: list, output_dp_table=False, output_item_list=True ): """ number_of_ways[i][c] means given the FIRST i items, the number of ways to make capacity c number_of_ways[i][c] = number_of_ways[i - 1][c] + number_of_ways[i - 1][c - sizes[i]] number_of_ways[i - 1][c] means without item[i], only use FIRST i - 1 items, the number of combos number_of_ways[i - 1][c - sizes[i]] means with item[i], every combo that make c-sizes[i] can add item[i] to get a new combo that make """ number_of_ways = [[0 for _ in range(capacity + 1)] for _ in range(len(sizes))] combo_lists = None if output_item_list: combo_lists = [[None for _ in range(capacity + 1)] for _ in range(len(sizes))] for i in range(len(sizes)): # init first column number_of_ways[i][0] = 1 # no item for 0 capacity is 1 way if output_item_list: combo_lists[i][0] = [[]] # empty list for no item combo if sizes[0] <= capacity: # init first row number_of_ways[0][sizes[0]] = 1 if output_item_list: combo_lists[0][sizes[0]] = [[0]] for i in range(1, len(sizes)): for c in range(1, capacity + 1): # if c < sizes[i]: # number_of_ways[i][c] = number_of_ways[i - 1][c] # elif c == sizes[i]: # number_of_ways[i][c] = number_of_ways[i - 1][c] + number_of_ways[i - 1][c - sizes[i]] number_of_ways[i][c] = number_of_ways[i - 1][c] if c >= sizes[i]: number_of_ways[i][c] += number_of_ways[i - 1][c - sizes[i]] if output_item_list: if combo_lists[i - 1][c] is not None: combo_lists[i][c] = combo_lists[i - 1][c] if c >= sizes[i] and combo_lists[i - 1][c - sizes[i]] is not None: new_combo_list = list() for combo in combo_lists[i - 1][c - sizes[i]]: new_combo_list.append(combo + [i]) combo_lists[i][c] = combo_lists[i][c] + new_combo_list if combo_lists[i][c] is not None else new_combo_list if output_dp_table: return (number_of_ways, combo_lists) if output_item_list else number_of_ways else: best_value = number_of_ways[len(sizes) - 1][capacity] if output_item_list: combo_list = combo_lists[len(sizes) - 1][capacity] return (best_value, combo_list) else: return best_value @staticmethod def number_of_ways_to_fill_to_capacity_with_limited_items_1d( capacity: int, sizes: list, quantities=1, output_dp_table=False, output_item_list=True ): """ number_of_ways[c] means the number of ways to make capacity c number_of_ways[c] = number_of_ways[c] + number_of_ways[c - sizes[i]] """ if isinstance(quantities, int): quantities_list = list() for i in range(len(sizes)): quantities_list.append(quantities) quantities = quantities_list else: assert len(sizes) == len(quantities) number_of_ways = [0 for _ in range(capacity + 1)] combo_lists = None if output_item_list: combo_lists = [None for _ in range(capacity + 1)] number_of_ways[0] = 1 # no item for 0 capacity is 1 way if output_item_list: combo_lists[0] = [[]] # empty list for no item combo for i in range(len(sizes)): for q in range(1, quantities[i] + 1): for c in range(capacity, sizes[i] - 1, -1): # c >= sizes[i] number_of_ways[c] += number_of_ways[c - sizes[i]] if output_item_list: if combo_lists[c - sizes[i]] is not None: new_combo_list = list() for combo in combo_lists[c - sizes[i]]: new_combo_list.append(combo + [i]) combo_lists[c] = combo_lists[c] + new_combo_list if combo_lists[c] is not None else new_combo_list if output_dp_table: return (number_of_ways, combo_lists) if output_item_list else number_of_ways else: best_value = number_of_ways[capacity] if output_item_list: combo_list = combo_lists[capacity] # It might have duplicates unique_combo_list = list() if combo_list: combo_set = set() for i, combo in enumerate(combo_list): t = tuple(combo.sort()) if t not in combo_set: unique_combo_list.append(combo) combo_set.add(t) return (len(unique_combo_list), unique_combo_list) return (best_value, combo_list) else: return best_value

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026d6883b4b4ef48ca95ca7facd1d38932ace6a3

26

py

Python

env/lib/python3.7/site-packages/grpc/_grpcio_metadata.py

PrudhviGNV/speechemotion

c99b4a7f644e1fd495cb5e6750ada0dd50d8b86f

[ "MIT" ]

5

2019-04-16T20:43:47.000Z

2020-10-24T22:35:39.000Z

Lib/site-packages/grpc/_grpcio_metadata.py

caiyongji/Anaconda-py36.5-tensorflow-built-env

f4eb40b5ca3f49dfc929ff3ad2b4bb877e9663e2

[ "PSF-2.0" ]

2

2021-04-30T20:43:55.000Z

2021-06-10T21:34:23.000Z

Lib/site-packages/grpc/_grpcio_metadata.py

caiyongji/Anaconda-py36.5-tensorflow-built-env

f4eb40b5ca3f49dfc929ff3ad2b4bb877e9663e2

[ "PSF-2.0" ]

3

2019-08-03T13:47:09.000Z

2021-08-03T14:20:25.000Z

__version__ = """1.19.0"""

26

0.576923

0

12

0.461538

027134b2e08ff17613c7279b030cfe1fcf0d8e8e

309

py

Python

pycon/tutorials/urls.py

azkarmoulana/pycon

931388e6f640c35b892bb4b2d12581ba7ec8cf4e

[ "BSD-3-Clause" ]

154

2015-01-17T02:29:24.000Z

2022-03-20T20:37:24.000Z

pycon/tutorials/urls.py

azkarmoulana/pycon

931388e6f640c35b892bb4b2d12581ba7ec8cf4e

[ "BSD-3-Clause" ]

316

2015-01-10T04:01:50.000Z

2020-09-30T20:18:08.000Z

pycon/tutorials/urls.py

azkarmoulana/pycon

931388e6f640c35b892bb4b2d12581ba7ec8cf4e

[ "BSD-3-Clause" ]

89

2015-01-10T05:25:21.000Z

2022-02-27T03:28:59.000Z

from django.conf.urls import url, patterns from .views import tutorial_email, tutorial_message urlpatterns = patterns("", # flake8: noqa url(r"^mail/(?P<pk>\d+)/(?P<pks>[0-9,]+)/$", tutorial_email, name="tutorial_email"), url(r"^message/(?P<pk>\d+)/$", tutorial_message, name="tutorial_message"), )

34.333333

88

0.679612

0

114

0.368932

027194484ee86822b39b3b119ff07d71c83e4daa

895

py

Python

setup.py

oleks/gigalixir-cli

d1b1c303e24be548ddc895165e34652c378f4347

[ "MIT" ]

null

setup.py

oleks/gigalixir-cli

d1b1c303e24be548ddc895165e34652c378f4347

[ "MIT" ]

null

setup.py

oleks/gigalixir-cli

d1b1c303e24be548ddc895165e34652c378f4347

[ "MIT" ]

null

from setuptools import setup, find_packages setup( name='gigalixir', url='https://github.com/gigalixir/gigalixir-cli', author='Jesse Shieh', author_email='jesse@gigalixir.com', version='1.1.10', packages=find_packages(), include_package_data=True, install_requires=[ 'click~=6.7', 'requests~=2.20.0', 'stripe~=1.51.0', 'rollbar~=0.13.11', 'pygments~=2.2.0', ], entry_points=''' [console_scripts] gigalixir=gigalixir:cli ''', setup_requires=[ 'pytest-runner', ], tests_require=[ 'pytest', 'HTTPretty', 'sure', ], extras_require={ 'dev': [ 'Sphinx', 'sphinx_rtd_theme', 'sphinx-tabs', ], 'test': [ 'pytest', 'HTTPretty', 'sure', ], } )

20.813953

53

0.492737

0

362

0.404469

02723743e00e16a13861c25c7c9d6a4bb4b3f93e

254

py

Python

runTest.py

Amedeo91/cushypost_integration

fc7ffc9daf535ed5bcfdee4933a7a57340a583b2

[ "MIT" ]

1

2021-10-06T06:23:40.000Z

runTest.py

Amedeo91/cushypost_integration

fc7ffc9daf535ed5bcfdee4933a7a57340a583b2

[ "MIT" ]

null

runTest.py

Amedeo91/cushypost_integration

fc7ffc9daf535ed5bcfdee4933a7a57340a583b2

[ "MIT" ]

null

import os import unittest dir_path = os.path.dirname(os.path.realpath(__file__)) suite = unittest.TestLoader().discover(dir_path, pattern='test_*.py') result = unittest.TextTestRunner(verbosity=3).run(suite) print(result) assert result.wasSuccessful()

25.4

69

0.787402

0

11

0.043307

02735e99efa8906c66196996cdf60aedba9354a2

6,145

py

Python

tests/test_pydent/test_models/models/test_plan.py

aquariumbio/trident

d1712cae544103fb145e3171894e4b35141f6813

[ "MIT" ]

5

2019-01-21T11:12:05.000Z

2020-03-05T20:52:14.000Z

tests/test_pydent/test_models/models/test_plan.py

aquariumbio/pydent

d1712cae544103fb145e3171894e4b35141f6813

[ "MIT" ]

28

2020-11-18T02:07:09.000Z

2021-06-08T15:49:41.000Z

tests/test_pydent/test_models/models/test_plan.py

aquariumbio/trident

d1712cae544103fb145e3171894e4b35141f6813

[ "MIT" ]

2

2021-02-27T19:23:45.000Z

2021-09-14T10:29:07.000Z

import pytest from pydent.models import Plan def test_plan_constructor(fake_session): g = fake_session.Plan.new() assert g.name is not None print(g.plan_associations) assert g.operations is None assert g.wires == [] g = Plan(name="MyPlan", status="running") assert g.name == "MyPlan" assert g.status == "running" def test_add_operation(fake_session): op = fake_session.Operation.load({"id": 4}) p = fake_session.Plan.new() # add first operation assert p.operations is None p.add_operation(op) assert p.operations == [op] # add second operation op2 = fake_session.Operation.load({"id": 5}) p.add_operation(op2) assert p.operations == [op, op2] def test_add_operations(fake_session): op = fake_session.Operation.load({"id": 4}) op2 = fake_session.Operation.load({"id": 5}) ops = [op, op2] p = fake_session.Plan.new() p.add_operations(ops) assert p.operations == [op, op2] @pytest.fixture(scope="function") def fake_plan(fake_session): p = fake_session.Plan.new() op1 = fake_session.Operation.load({}) op2 = fake_session.Operation.load({}) src = fake_session.FieldValue.load( { "name": "myinput", "parent_class": "Operation", "operation": op1, "role": "output", } ) dest = fake_session.FieldValue.load( { "name": "myoutput", "parent_class": "Operation", "operation": op2, "role": "input", } ) op1.field_values = [src] op2.field_values = [dest] return p, src, dest def test_wire(fake_plan): p, src, dest = fake_plan p.add_operations([src.operation, dest.operation]) p.wire(src, dest) assert len(p.wires) == 1 assert p.wires[0].source.name == "myinput" assert p.wires[0].destination.name == "myoutput" print(p.wires) def test_plan_copy(example_plan): """Copying plans should anonymize operations and wires.""" copied_plan = example_plan.copy() assert copied_plan.operations for op in copied_plan.operations: assert op.id is None assert op.operation_type_id is not None assert op.field_values is not None for fv in op.field_values: assert fv.id is None assert fv.parent_id is None assert fv.field_type_id is not None # TODO: make this adeterministic test """def test_new_plan(session): p = fake_session.Plan.new() p.connect_to_session(session) assert p.operations is None assert p.plan_associations is None p.id = 1000000 assert p.operations == [] assert p.plan_associations == []""" # def test_submit(session): # primer = session.SampleType.find(1).samples[-1] # # # get Order Primer operation type # ot = session.OperationType.find(328) # # # create an operation # order_primer = ot.instance() # # # set io # order_primer.set_output("Primer", sample=primer) # order_primer.set_input("Urgent?", value="no") # # # create a new plan and add operations # p = session.Plan(name="MyPlan") # p.add_operation(order_primer) # # # save the plan # p.create() # # # estimate the cost # p.estimate_cost() # # # show the plan # p.show() # # # submit the plan # p.submit(session.current_user, session.current_user.budgets[0]) # def test_submit_pcr(session): # def get_op(name): # return session.OperationType.where( # {'name': name, 'deployed': True})[-1].instance() # # make_pcr_fragment = get_op('Make PCR Fragment') # pour_gel = get_op('Pour Gel') # run_gel = get_op('Run Gel') # extract_gel_slice = get_op('Extract Gel Slice') # purify_gel = get_op('Purify Gel Slice') # # # setup pcr # make_pcr_fragment.set_input('Forward Primer', # item=session.Item.find(81867)) # make_pcr_fragment.set_input('Reverse Primer', # item=session.Item.find(57949)) # make_pcr_fragment.set_input('Template', item=session.Item.find(61832)) # make_pcr_fragment.set_output('Fragment', # sample=session.Sample.find(16976)) # # # setup outputs # # run_gel.set_output(sample=session.Sample.find(16976)) # # extract_gel_slice.set_output(sample=session.Sample.find(16976)) # # purify_gel.set_output(sample=session.Sample.find(16976)) # # purify_gel.pour_gel(sample=session.Sample.find(16976)) # # # new plan # p = session.fake_session.Plan.new() # p.add_operations([make_pcr_fragment, pour_gel, run_gel, # extract_gel_slice, purify_gel]) # # p.add_wires([ # (make_pcr_fragment.output("Fragment"), run_gel.input("Fragment")), # (pour_gel.output("Lane"), run_gel.input("Gel")), # (run_gel.output("Fragment"), extract_gel_slice.input("Fragment")), # (extract_gel_slice.output("Fragment"), purify_gel.input("Gel")) # ]) # # make_pcr_fragment.set_output("Fragment", # sample=session.Sample.find(16976)) # # # pdata = p.to_save_json() # # # wire up the operations # # p.wire(make_pcr_fragment.outputs[0], run_gel.input('Fragment')) # # p.wire(pour_gel.outputs[0], run_gel.input('Gel')) # # p.wire(run_gel.outputs[0], extract_gel_slice.input('Fragment')) # # p.wire(extract_gel_slice.outputs[0], purify_gel.input('Gel')) # # # save the plan # p.create() # # # estimate the cost # p.estimate_cost() # # p.validate() # # # show the plan # p.show() # # # submit the plan # p.submit(session.current_user, session.current_user.budgets[0]) # # TODO: having difficulty patching plans/operations here... # def test_replan(session): # # p = session.Plan.find(79797) # newplan = p.replan() # newplan.print() # # for op in newplan.operations: # if op.operation_type.name == "Make PCR Fragment": # op.set_input('Template', item=session.Item.find(57124)) # newplan.patch(newplan.to_save_json())

28.581395

76

0.621318

0

661

0.107567

0

3,936

0.640521

0273c9fe7bf28f09a7dc46bd636570ab46c8a8fa

611

py

Python

FusionIIIT/applications/gymkhana/migrations/0007_auto_20200608_2210.py

sabhishekpratap5/sonarcubeTest2

9bd8105e457f6feb8c38fa94b335e54783fca99e

[ "bzip2-1.0.6" ]

2

2020-01-24T16:34:54.000Z

2020-08-01T05:09:24.000Z

FusionIIIT/applications/gymkhana/migrations/0007_auto_20200608_2210.py

sabhishekpratap5/sonarcubeTest2

9bd8105e457f6feb8c38fa94b335e54783fca99e

[ "bzip2-1.0.6" ]

1

2021-05-05T09:50:22.000Z

FusionIIIT/applications/gymkhana/migrations/0007_auto_20200608_2210.py

sabhishekpratap5/sonarcubeTest2

9bd8105e457f6feb8c38fa94b335e54783fca99e

[ "bzip2-1.0.6" ]

4

2020-01-16T17:00:08.000Z

2020-06-30T15:58:32.000Z

# -*- coding: utf-8 -*- # Generated by Django 1.11.27 on 2020-06-08 22:10 from __future__ import unicode_literals from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('gymkhana', '0006_form_available'), ] operations = [ migrations.RemoveField( model_name='form_available', name='id', ), migrations.AddField( model_name='form_available', name='roll', field=models.CharField(default=2016001, max_length=7, primary_key=True, serialize=False), ), ]

24.44

101

0.610475

452

0.739771

0

145

0.237316

027588263d8cfcf1854016d6bcb09a5b8fcae300

1,899

py

Python

config/presets/Modes/Python/T - Bits H/main.py

The-XOR/EYESY_OS

6a5e3d0bc5574ba2311e0c7e81c600c3af7a3e34

[ "BSD-3-Clause" ]

18

2021-03-06T05:39:30.000Z

2022-03-25T17:59:23.000Z

presets/Modes/Python/T - Bits H/main.py

jqrsound/EYESY_OS_for_RasPiSound

ac117b91cd84ad4c0566bd1a7d4c7b1ccc01cf62

[ "BSD-3-Clause" ]

null

presets/Modes/Python/T - Bits H/main.py

jqrsound/EYESY_OS_for_RasPiSound

ac117b91cd84ad4c0566bd1a7d4c7b1ccc01cf62

[ "BSD-3-Clause" ]

4

2021-03-14T18:38:42.000Z

2021-07-11T14:31:18.000Z

import os import pygame import random trigger = False x = 0 y = 0 height = 720 width = 1280 linelength = 50 lineAmt = 20 displace = 10 xpos = [random.randrange(-200,1280) for i in range(0, lineAmt + 2)] xpos1 = [(xpos[i]+displace) for i in range(0, lineAmt + 2)] xr = 360 yr = 240 def setup(screen, etc): global trigger, x, y, height, width, xpos, lineAmt, xpos1, linelength, displace, xr, yr xr = etc.xres yr = etc.yres height = yr width = xr linelength = ((50*xr)/1280) lineAmt = ((20*xr)/1280) displace = ((10*xr)/1280) xpos = [random.randrange(int((-200*xr)/1280),xr) for i in range(0, lineAmt + 2)] xpos1 = [(xpos[i]+displace) for i in range(0, lineAmt + 2)] pass def draw(screen, etc): global trigger, x, y, height, width, xpos, lineAmt, xpos1, linelength, displace, xr, yr etc.color_picker_bg(etc.knob5) displace = ((10*xr)/1280) linewidth = (height / lineAmt) linelength = int(etc.knob2*((300*xr)/1280)+1) color = etc.color_picker(etc.knob4) minus = (etc.knob3*0.5)+0.5 shadowColor = (etc.bg_color[0]*minus, etc.bg_color[1]*minus, etc.bg_color[2]*minus) if etc.audio_trig or etc.midi_note_new : trigger = True if trigger == True : lineAmt = int(etc.knob1*((100*yr)/720) + 2) xpos = [random.randrange(int((-200*xr)/1280),xr) for i in range(0, lineAmt + 2)] xpos1 = [(xpos[i]+displace) for i in range(0, lineAmt + 2)] for k in range(0, lineAmt + 2) : x = xpos1[k] + linelength y = (k * linewidth) + int(linewidth/2)- 1 pygame.draw.line(screen, shadowColor, (xpos1[k], y+displace), (x, y+displace), linewidth) for j in range(0, lineAmt + 2) : x = xpos[j] + linelength y = (j * linewidth) + int(linewidth/2)- 1 pygame.draw.line(screen, color, (xpos[j], y), (x, y), linewidth) trigger = False

31.131148

97

0.604529

0

0275d85ad826b0b81b83f4f373f69ae66117d9ed

2,577

py

Python

ext/std/code/mi.py

iazarov/metrixplusplus

322777cba4e089502dd6053749b07a7be9da65b2

[ "MIT" ]

null

ext/std/code/mi.py

iazarov/metrixplusplus

322777cba4e089502dd6053749b07a7be9da65b2

[ "MIT" ]

null

ext/std/code/mi.py

iazarov/metrixplusplus

322777cba4e089502dd6053749b07a7be9da65b2

[ "MIT" ]

null

# # Metrix++, Copyright 2009-2019, Metrix++ Project # Link: https://github.com/metrixplusplus/metrixplusplus # # This file is a part of Metrix++ Tool. # import mpp.api class Plugin(mpp.api.Plugin, mpp.api.IConfigurable, mpp.api.Child, mpp.api.MetricPluginMixin): def declare_configuration(self, parser): self.parser = parser parser.add_option("--std.code.maintindex.simple", "--scmis", action="store_true", default=False, help="Enables collection of simple maintainability index metric." " It uses std.code.line:code, std.code.complexity:cyclomatic" " metrics to rank level of maintainability." " Lower value of this metric indicates better maintainability." " [default: %default]") def configure(self, options): self.is_active_simple = options.__dict__['std.code.maintindex.simple'] if self.is_active_simple == True: required_opts = ['std.code.complexity.cyclomatic', 'std.code.lines.code'] for each in required_opts: if options.__dict__[each] == False: self.parser.error('option --std.code.maintindex.simple: requires --{0} option'. format(each)) def initialize(self): self.declare_metric(self.is_active_simple, self.Field('simple', int), { 'std.code.complexity':(None, self.RankedComplexityCounter), 'std.code.lines':(None, self.RankedLinesCounter), }, # set none, because this plugin is not interested in parsing the code marker_type_mask=mpp.api.Marker.T.NONE) super(Plugin, self).initialize(fields=self.get_fields()) if self.is_active() == True: self.subscribe_by_parents_name('std.code.complexity') self.subscribe_by_parents_name('std.code.lines') class RankedComplexityCounter(mpp.api.MetricPluginMixin.RankedCounter): rank_source = ('std.code.complexity', 'cyclomatic') rank_ranges = [(None, 7), (8, 11), (12, 19), (20, 49), (50, None)] class RankedLinesCounter(mpp.api.MetricPluginMixin.RankedCounter): rank_source = ('std.code.lines', 'code') rank_ranges = [(None, 124), (125, 249), (250, 499), (500, 999), (1000, None)]

45.210526

100

0.568879

2,379

0.923166

0

819

0.317811

027b51903bbc31466f05349aa598a39bb4d2919d

447

py

Python

6.00.1x/quiz/flatten.py

NicholasAsimov/courses

d60981f25816445578eb9e89bbbeef2d38eaf014

[ "MIT" ]

null

6.00.1x/quiz/flatten.py

NicholasAsimov/courses

d60981f25816445578eb9e89bbbeef2d38eaf014

[ "MIT" ]

null

6.00.1x/quiz/flatten.py

NicholasAsimov/courses

d60981f25816445578eb9e89bbbeef2d38eaf014

[ "MIT" ]

null

def flatten(aList): ''' aList: a list Returns a copy of aList, which is a flattened version of aList ''' if aList == []: return aList if type(aList[0]) == list: return flatten(aList[0]) + flatten(aList[1:]) return aList[:1] + flatten(aList[1:]) aList = [[1, 'a', ['cat'], 2], [[[3]], 'dog'], 4, 5] print flatten(aList) testCase = [1, 'a', 'cat', 2, 3, 'dog', 4, 5] print flatten(aList) == testCase

22.35

66

0.548098

0

122

0.272931

027cdd147516550681b095c7591faaa5e2b26a2b

9,960

py

Python

copo_code/copo/algo_svo/svo_env.py

decisionforce/CoPO

3a06a48522b901db2e380a62a0efb5e8a30cd079

[ "Apache-2.0" ]

37

2021-11-01T03:30:30.000Z

2022-03-29T08:38:12.000Z

copo_code/copo/algo_svo/svo_env.py

decisionforce/CoPO

3a06a48522b901db2e380a62a0efb5e8a30cd079

[ "Apache-2.0" ]

null

copo_code/copo/algo_svo/svo_env.py

decisionforce/CoPO

3a06a48522b901db2e380a62a0efb5e8a30cd079

[ "Apache-2.0" ]

4

2021-11-05T06:55:34.000Z

2022-01-04T07:08:37.000Z

""" Usage: Call get_svo_env(env_class) to get the real env class! """ from collections import defaultdict from math import cos, sin import numpy as np from gym.spaces import Box from metadrive.envs.marl_envs.marl_tollgate import TollGateObservation, MultiAgentTollgateEnv from metadrive.obs.state_obs import LidarStateObservation from metadrive.utils import get_np_random, norm, clip from copo.utils import get_rllib_compatible_env class SVOObsForRound(LidarStateObservation): @property def observation_space(self): space = super(SVOObsForRound, self).observation_space assert isinstance(space, Box) assert len(space.shape) == 1 length = space.shape[0] + 1 space = Box( low=np.array([space.low[0]] * length), high=np.array([space.high[0]] * length), shape=(length,), dtype=space.dtype ) return space class SVOObsForRoundForTollgate(TollGateObservation): @property def observation_space(self): space = super(SVOObsForRoundForTollgate, self).observation_space assert isinstance(space, Box) assert len(space.shape) == 1 length = space.shape[0] + 1 space = Box( low=np.array([space.low[0]] * length), high=np.array([space.high[0]] * length), shape=(length,), dtype=space.dtype ) return space class SVOObsForRoundForTollgate(TollGateObservation): @property def observation_space(self): space = super(SVOObsForRoundForTollgate, self).observation_space assert isinstance(space, Box) assert len(space.shape) == 1 length = space.shape[0] + 1 space = Box( low=np.array([space.low[0]] * length), high=np.array([space.high[0]] * length), shape=(length, ), dtype=space.dtype ) return space class SVOEnv: @classmethod def default_config(cls): config = super(SVOEnv, cls).default_config() config.update( dict( neighbours_distance=20, # Two mode to compute utility for each vehicle: # "linear": util = r_me * svo + r_other * (1 - svo), svo in [0, 1] # "angle": util = r_me * cos(svo) + r_other * sin(svo), svo in [0, pi/2] # "angle" seems to be more stable! svo_mode="angle", svo_dist="uniform", # "uniform" or "normal" svo_normal_std=0.3, # The initial STD of normal distribution, might change by calling functions. return_native_reward=False, include_ego_reward=False, # Whether to force set the svo force_svo=-100 ) ) return config def __init__(self, config=None): super(SVOEnv, self).__init__(config) self.svo_map = {} if hasattr(super(SVOEnv, self), "_update_distance_map"): # The parent env might be CCEnv, so we don't need to do this again! self._parent_has_distance_map = True else: self.distance_map = defaultdict(lambda: defaultdict(lambda: float("inf"))) self._parent_has_distance_map = False assert self.config["svo_mode"] in ["linear", "angle"] assert self.config["svo_dist"] in ["uniform", "normal"] assert self.config["svo_normal_std"] > 0.0 self.force_svo = self.config["force_svo"] # Only used in normal SVO distribution # SVO is always in range [0, 1], but the real SVO degree is in [-pi/2, pi/2]. self.current_svo_mean = 0.0 # Set to 0 degree. self.current_svo_std = self.config["svo_normal_std"] def get_single_observation(self, vehicle_config): # TODO we should generalize this function in future! if issubclass(self.__class__, MultiAgentTollgateEnv): return SVOObsForRoundForTollgate(vehicle_config) else: return SVOObsForRound(vehicle_config) def _get_reset_return(self): self.svo_map.clear() self._update_distance_map() obses = super(SVOEnv, self)._get_reset_return() ret = {} for k, o in obses.items(): svo, ret[k] = self._add_svo(o) self.svo_map[k] = svo return ret def step(self, actions): # step the environment o, r, d, i = super(SVOEnv, self).step(actions) self._update_distance_map() # add SVO into observation, also update SVO map and info. ret = {} for k, v in o.items(): svo, ret[k] = self._add_svo(v, self.svo_map[k] if k in self.svo_map else None, k) if k not in self.svo_map: self.svo_map[k] = svo if i[k]: i[k]["svo"] = svo if self.config["return_native_reward"]: return ret, r, d, i # compute the SVO-weighted rewards new_rewards = {} for k, own_r in r.items(): other_rewards = [] if self.config["include_ego_reward"]: other_rewards.append(own_r) # neighbours = self._find_k_nearest(k, K) neighbours = self._find_in_range_for_svo(k, self.config["neighbours_distance"]) for other_k in neighbours: if other_k is None: break else: other_rewards.append(r[other_k]) if len(other_rewards) == 0: other_reward = own_r else: other_reward = np.mean(other_rewards) # svo_map stores values in [-1, 1] if self.config["svo_mode"] == "linear": new_r = self.svo_map[k] * own_r + (1 - self.svo_map[k]) * other_reward elif self.config["svo_mode"] == "angle": svo = self.svo_map[k] * np.pi / 2 new_r = cos(svo) * own_r + sin(svo) * other_reward else: raise ValueError("Unknown SVO mode: {}".format(self.config["svo_mode"])) new_rewards[k] = new_r return ret, new_rewards, d, i def set_force_svo(self, v): self.force_svo = v def _add_svo(self, o, svo=None, agent_name=None): if self.force_svo != -100: if self.config["svo_dist"] == "normal": svo = get_np_random().normal(loc=self.force_svo, scale=self.current_svo_std) else: svo = self.force_svo elif svo is not None: pass else: if self.config["svo_dist"] == "normal": svo = get_np_random().normal(loc=self.current_svo_mean, scale=self.current_svo_std) svo = clip(svo, -1, 1) else: svo = get_np_random().uniform(-1, 1) # print("For agent {}, we assign new SVO {} deg! Current mean {} deg, std {}.".format( # agent_name, svo * 90, self.current_svo_mean * 90, self.current_svo_std)) output_svo = (svo + 1) / 2 return svo, np.concatenate([o, [output_svo]]) def set_svo_dist(self, mean, std): assert self.config["svo_dist"] == "normal" self.current_svo_mean = mean self.current_svo_std = std assert std > 0.0 def _find_in_range_for_svo(self, v_id, distance): if distance <= 0: return [] max_distance = distance dist_to_others = self.distance_map[v_id] dist_to_others_list = sorted(dist_to_others, key=lambda k: dist_to_others[k]) ret = [ dist_to_others_list[i] for i in range(len(dist_to_others_list)) if dist_to_others[dist_to_others_list[i]] < max_distance ] return ret def _update_distance_map(self): if self._parent_has_distance_map: return super(SVOEnv, self)._update_distance_map() self.distance_map.clear() keys = list(self.vehicles.keys()) for c1 in range(0, len(keys) - 1): for c2 in range(c1 + 1, len(keys)): k1 = keys[c1] k2 = keys[c2] p1 = self.vehicles[k1].position p2 = self.vehicles[k2].position distance = norm(p1[0] - p2[0], p1[1] - p2[1]) self.distance_map[k1][k2] = distance self.distance_map[k2][k1] = distance def get_svo_env(env_class, return_env_class=False): name = env_class.__name__ class TMP(SVOEnv, env_class): pass TMP.__name__ = name TMP.__qualname__ = name if return_env_class: return TMP return get_rllib_compatible_env(TMP) if __name__ == '__main__': # env = SVOEnv({"num_agents": 8, "neighbours_distance": 3, "svo_mode": "angle", "force_svo": 0.9}) env = get_svo_env( MultiAgentTollgateEnv, return_env_class=True )({ "num_agents": 8, "neighbours_distance": 3, "svo_mode": "angle", "svo_dist": "normal" }) o = env.reset() assert env.observation_space.contains(o) assert all([0 <= oo[-1] <= 1.0 for oo in o.values()]) total_r = 0 ep_s = 0 for i in range(1, 100000): o, r, d, info = env.step({k: [0.0, 1.0] for k in env.vehicles.keys()}) assert env.observation_space.contains(o) assert all([0 <= oo[-1] <= 1.0 for oo in o.values()]) for r_ in r.values(): total_r += r_ print("SVO: {}".format({kkk: iii["svo"] if "svo" in iii else None for kkk, iii in info.items()})) ep_s += 1 if d["__all__"]: print( "Finish! Current step {}. Group Reward: {}. Average reward: {}".format( i, total_r, total_r / env.agent_manager.next_agent_count ) ) break if len(env.vehicles) == 0: total_r = 0 print("Reset") env.reset() env.close()

35.44484

113

0.570482

8,008

0.804016

0

2,196

0.220482

0

1,622

0.162851

027d3d4607b5f1e18cfb2663664c754672a047c8

1,995

py

Python

tests/test_renderer.py

derlin/get-html

ea6d81f424ed0a60a37a52b95dd5b27c85cf0852

[ "Apache-2.0" ]

11

2020-03-02T08:38:37.000Z

2021-11-19T05:03:20.000Z

tests/test_renderer.py

derlin/get-html

ea6d81f424ed0a60a37a52b95dd5b27c85cf0852

[ "Apache-2.0" ]

2

2020-03-02T11:43:12.000Z

2020-03-10T07:59:07.000Z

tests/test_renderer.py

derlin/get-html

ea6d81f424ed0a60a37a52b95dd5b27c85cf0852

[ "Apache-2.0" ]

2

2020-03-02T08:13:53.000Z

2020-03-09T21:15:26.000Z

from get_html.html_renderer import HtmlRenderer import pytest import re @pytest.fixture(scope='module') def renderer(): r = HtmlRenderer() try: yield r finally: r.close() def test_response(renderer: HtmlRenderer): url = 'http://www.twitter.com' # this will redirect to https://twitter.com r = renderer.render(url) assert r.status_code == 200 assert r.reason == 'OK', 'reason not ok' assert r.text == r.content.decode(r.encoding), 'wrong encoding' assert len(r.history) > 0, 'no redirect ??' def test_404(renderer: HtmlRenderer): r = renderer.render('https://github.com/afadfadfaf/adsfa-not-exist') assert r.status_code == 404 assert r.reason == 'Not Found' @pytest.mark.parametrize( 'url', [ 'https://meertjes-stuff.blogspot.com/search/label/Link%20Your%20Stuff', # whut ?? this one is strange 'https://www.investing.com/indices/major-indices', # has websocket # 'http://data.fis-ski.com/dynamic/athlete-biography.html?sector=AL&competitorid=147749&type=result', # don't remember, but was problematic ]) def test_potentially_problematic_urls(renderer: HtmlRenderer, url): r = renderer.render(url) assert r.status_code == 200 assert len(r.content) > 0 def test_manipulate_page(renderer: HtmlRenderer): url = 'https://9gag.com/' r = renderer.render(url) num_articles = len(re.findall('<article', r.text)) # async def fn(page): # assert page is not None # for _ in range(10): # await page._keyboard.down('PageDown') async def fn(page): # https://github.com/miyakogi/pyppeteer/issues/205#issuecomment-470886682 await page.evaluate('{window.scrollBy(0, document.body.scrollHeight);}') r = renderer.render(url, manipulate_page_func=fn) num_articles_after_scroll = len(re.findall('<article', r.text)) print(num_articles, num_articles_after_scroll) assert num_articles_after_scroll > num_articles

32.704918

148

0.680201

0

94

0.047118

666

0.333835

182

0.091228

777

0.389474

027e6a3b136fbe978f346957d7b86c2022fa6ea2

724

py

Python

resources/include-lists/string_manipulator_util.py

e-loughlin/CppCodeGenerator

638f80f9df21d709d1240bb3bd43f9d43dd2e3ac

[ "MIT" ]

6

2019-09-30T10:27:15.000Z

2020-12-20T14:46:24.000Z

resources/include-lists/string_manipulator_util.py

e-loughlin/CppCodeGenerator

638f80f9df21d709d1240bb3bd43f9d43dd2e3ac

[ "MIT" ]

4

2019-11-25T18:14:29.000Z

2019-12-09T20:47:29.000Z

resources/include-lists/string_manipulator_util.py

emloughl/CppCodeGenerator

638f80f9df21d709d1240bb3bd43f9d43dd2e3ac

[ "MIT" ]

1

2021-12-01T07:03:31.000Z

import sys import os import ntpath def readFile(filePath): with open(filePath, "r") as file: return file.read() def writeToDisk(filePath, stringToSave): with open(filePath, "w+") as newFile: newFile.write(stringToSave) def main(): filePath = os.path.abspath("./qt-includes.txt") stuff = readFile(filePath) stuff = stuff.replace(" ", "\n") lines = stuff.split("\n") newLines = [] for line in lines: line = line.replace("(", "").replace(")", "") if line[0] != "Q": line = line[1:] newLines.append(line) stuff = "\n".join(newLines) writeToDisk("qt-includes-new.txt", stuff) if __name__ == "__main__": main()

20.111111

53

0.574586

0

85

0.117403

027e798c00ba61f438e908e5871d0e08cf7a12f8

2,205

py

Python

build/lib/henmedlib/functions/hounsfield.py

schmitzhenninglmu/henmedlib

196b63710f092470ab21173cfcc0b14e65778f33

[ "MIT" ]

null

build/lib/henmedlib/functions/hounsfield.py

schmitzhenninglmu/henmedlib

196b63710f092470ab21173cfcc0b14e65778f33

[ "MIT" ]

null

build/lib/henmedlib/functions/hounsfield.py

schmitzhenninglmu/henmedlib

196b63710f092470ab21173cfcc0b14e65778f33

[ "MIT" ]

1

2019-09-20T10:59:25.000Z

__author__ = "Henning Schmitz" import numpy as np def calculate_hounsfield_unit(mu, mu_water, mu_air): """ Given linear attenuation coefficients the function calculates the corresponding Hounsfield units. :param mu: Attenuation coefficient to determine corresponding Hounsfield unit. :param mu_water: Constant linear attenuation coefficient for water :param mu_air: Constant linear attenuation coefficient for air :return: Hounsfield unit corresponding to mu """ HU = 1000 * ((mu - mu_water) / (mu_water - mu_air)) return HU def calculate_hounsfield_unit_parameterless(mu): """ Given linear attenuation coefficients the function calculates the corresponding Hounsfield units. :param mu: Attenuation coefficient to determine corresponding Hounsfield unit. :return: Hounsfield unit corresponding to mu """ HU = mu * 65536-1024 return HU def create_array_with_hounsfield_units(image_data, mu_water, mu_air): """ Given 3d array with linear attenuation coefficients the function calculates the corresponding Hounsfield units. :param image_data: 3d array corresponding to image :param mu: Attenuation coefficient to determine corresponding Hounsfield unit. :param mu_water: Constant linear attenuation coefficient for water :param mu_air: Constant linear attenuation coefficient for air :return: 3d array calculated in Hounsfield unit """ # print dimensions of array dim_x = np.size(image_data, 0) dim_y = np.size(image_data, 1) dim_slice = np.size(image_data, 2) # loop through array count = 0 iterations = dim_x * dim_y * dim_slice # loop through x direction for i in range(0, dim_x): # loop through y direction for j in range(0, dim_y): # loop through slices for k in range(0, dim_slice): image_data[i][j][k] = calculate_hounsfield_unit(image_data[i][j][k], mu_water, mu_air) count += 1 if count % (0.1 * iterations) == 0: print(round(count / iterations, 1) * 100, "% progress") return image_data

38.017241

116

0.677098

0

1,254

0.568707

027ff59d51aedead00128b3b38fec073cc323ee3

1,028

py

Python

coaddExtract.py

rbliu/LSST_DM_Scripts

0a32ba629a2b52d3add407e92ab8ff4bc3cbd64d

[ "MIT" ]

null

coaddExtract.py

rbliu/LSST_DM_Scripts

0a32ba629a2b52d3add407e92ab8ff4bc3cbd64d

[ "MIT" ]

null

coaddExtract.py

rbliu/LSST_DM_Scripts

0a32ba629a2b52d3add407e92ab8ff4bc3cbd64d

[ "MIT" ]

null

# -*- coding: utf-8 -*- #!/usr/bin/env python ## last modified by Robert Liu at 7/29/2019 ## This script is used to extract data (and WCS info) in the image extension of a coadd patch. ## Ext 0 = primaryHDU, Ext 1 = image, Ext 2 = mask, Ext 3 = variancce. ## Then, the output fits file can be used by SWarp to assemble a mosaic coadd image. import re import sys import numpy as np from astropy.io import fits from astropy import wcs if len(sys.argv) != 3: print("Usage: python coaddExtract.py {coadd_image} {extracted_image}", file=sys.stderr) exit(1); coadd_patch = sys.argv[1] extracted_patch = sys.argv[2] # Open the fits image hdu = fits.open(coadd_patch) # Create a new HDU. Save the data of Ext1 to it. hdu1 = fits.PrimaryHDU(hdu[1].data) print('Coadd patch loaded.') # Extract WCS info and append to the new HDU. w = wcs.WCS(hdu[1].header) wcs_keys = w.to_header() hdu1.header += wcs_keys print('WCS information appened.') # Write the new HDU hdu1.writeto(extracted_patch) print('New coadd image saved!\n')

28.555556

94

0.715953

0

604

0.587549

02824286d75d00e50642afe49b18a9fd9681523d

22

py

Python

backend_server/backend_globals.py

MSNLAB/SmartEye

40b38190aeff5d5b970c8cbf43e8781634b38028

[ "MIT", "Unlicense" ]

17

2021-06-27T04:33:13.000Z

2022-03-21T02:54:52.000Z

backend_server/backend_globals.py

MSNLAB/SmartEye

40b38190aeff5d5b970c8cbf43e8781634b38028

[ "MIT", "Unlicense" ]

null

backend_server/backend_globals.py

MSNLAB/SmartEye

40b38190aeff5d5b970c8cbf43e8781634b38028

[ "MIT", "Unlicense" ]

2

2021-10-31T05:14:24.000Z

2022-03-25T18:53:49.000Z

global loaded_model

5.5

19

0.818182

0

02842784fc821e743357ee9efac57212bf1f6827

326

py

Python

src/utils.py

fabiob/wwwsqldesigner-aws

5518eae682e8228be30b094c6015054b3cddf8f3

[ "MIT" ]

null

src/utils.py

fabiob/wwwsqldesigner-aws

5518eae682e8228be30b094c6015054b3cddf8f3

[ "MIT" ]

null

src/utils.py

fabiob/wwwsqldesigner-aws

5518eae682e8228be30b094c6015054b3cddf8f3

[ "MIT" ]

1

2021-04-04T09:41:51.000Z

from .env import S3_PREFIX def respond(body=None, mime="text/plain", code=200, headers={}): h = {"Content-Type": mime} h.update(headers) return {"statusCode": code, "body": body, "headers": h} def fn(keyword): return f'{S3_PREFIX}{keyword}.xml' def fix(filename): return filename[len(S3_PREFIX):-4]

20.375

64

0.650307

0

80

0.245399

028456bd34d14ef1d7f23ca7f443c4b9f0404a35

4,071

py

Python

waferscreen/inst_control/inactive/agilent_34970A.py

chw3k5/WaferScreen

c0ca7fe939fe7cd0b722b7d6129b148c03a7505c

[ "Apache-2.0" ]

1

2021-07-30T19:06:07.000Z

waferscreen/inst_control/inactive/agilent_34970A.py

chw3k5/WaferScreen

c0ca7fe939fe7cd0b722b7d6129b148c03a7505c

[ "Apache-2.0" ]

8

2021-04-22T20:47:48.000Z

2021-07-30T19:06:01.000Z

waferscreen/inst_control/inactive/agilent_34970A.py

chw3k5/WaferScreen

c0ca7fe939fe7cd0b722b7d6129b148c03a7505c

[ "Apache-2.0" ]

null

import serial class Agilent34970A: def __init__(self): self.timeout = 10 self.baudrate = 4800 self.bytesize = serial.EIGHTBITS self.parity = serial.PARITY_NONE self.stopbits = serial.STOPBITS_ONE xonxoff = True self.s = serial.Serial(port='/dev/ttyUSB3', timeout=self.timeout, baudrate=self.baudrate, bytesize=self.bytesize, parity=self.parity, stopbits=self.stopbits, xonxoff=True) def reset(self): self.s.write('*RST\n') def closeSwitch(self, board, switch): self.s.write('ROUT:CLOS (@' + str(board) + str(switch).zfill(2) + ')\n') def checkClosed(self, board, switch): self.s.write('ROUT:CLOS? (@' + str(board) + str(switch).zfill(2) + ')\n') sto = self.s.readline() if int(sto) == 0: print 'Switch open' elif int(sto) == 1: print 'Switch closed' def measureResistance(self, board, switch, Range="AUTO", Resolution="AUTO"): if Resolution == "AUTO": self.s.write( 'MEAS:RES? ' + str(Range) + ',(@' + str(board) + str(switch).zfill(2) + ')\n') else: self.s.write( 'MEAS:RES? ' + str(Range) + ',' + str(Resolution) + ',(@' + str(board) + str(switch).zfill(2) + ')\n') return float(self.s.readline()) def measureFrequency(self, board, switch, Range="AUTO", Resolution="AUTO"): if Resolution == "AUTO": self.s.write( 'MEAS:FREQ? ' + str(Range) + ',(@' + str(board) + str(switch).zfill(2) + ')\n') else: self.s.write( 'MEAS:FREQ? ' + str(Range) + ',' + str(Resolution) + ',(@' + str(board) + str(switch).zfill(2) + ')\n') return float(self.s.readline()) def measurePeriod(self, board, switch, Range="AUTO", Resolution="AUTO"): if Resolution == "AUTO": self.s.write( 'MEAS:PER? ' + str(Range) + ',(@' + str(board) + str(switch).zfill(2) + ')\n') else: self.s.write( 'MEAS:PER? ' + str(Range) + ',' + str(Resolution) + ',(@' + str(board) + str(switch).zfill(2) + ')\n') return float(self.s.readline()) def measureACCurrent(self, board, switch, Range="AUTO", Resolution="AUTO"): if Resolution == "AUTO": self.s.write( 'MEAS:CURR:AC? ' + str(Range) + ',(@' + str(board) + str(switch).zfill(2) + ')\n') else: self.s.write( 'MEAS:CURR:AC? ' + str(Range) + ',' + str(Resolution) + ',(@' + str(board) + str(switch).zfill(2) + ')\n') return float(self.s.readline()) def measureDCCurrent(self, board, switch, Range="AUTO", Resolution="AUTO"): if Resolution == "AUTO": self.s.write( 'MEAS:CURR:DC? ' + str(Range) + ',(@' + str(board) + str(switch).zfill(2) + ')\n') else: self.s.write( 'MEAS:CURR:DC? ' + str(Range) + ',' + str(Resolution) + ',(@' + str(board) + str(switch).zfill(2) + ')\n') return float(self.s.readline()) def measureACVoltage(self, board, switch, Range="AUTO", Resolution="AUTO"): if Resolution == "AUTO": self.s.write( 'MEAS:VOLT:AC? ' + str(Range) + ',(@' + str(board) + str(switch).zfill(2) + ')\n') else: self.s.write( 'MEAS:VOLT:AC? ' + str(Range) + ',' + str(Resolution) + ',(@' + str(board) + str(switch).zfill(2) + ')\n') return float(self.s.readline()) def measureDCVoltage(self, board, switch, Range="AUTO", Resolution="AUTO"): if Resolution == "AUTO": self.s.write( 'MEAS:VOLT:DC? ' + str(Range) + ',(@' + str(board) + str(switch).zfill(2) + ')\n') else: self.s.write( 'MEAS:VOLT:DC? ' + str(Range) + ',' + str(Resolution) + ',(@' + str(board) + str(switch).zfill(2) + ')\n') return float(self.s.readline())

39.911765

119

0.503316

4,055

0.99607

0

578

0.14198

0285c8a2ee84e232d1b5d465f4047d255ab9153e

2,318

py

Python

force_wfmanager/gui/tests/test_click_run.py

force-h2020/force-wfmanager

bcd488cd37092cacd9d0c81b544ee8c1654d1d92

[ "BSD-2-Clause" ]

1

2019-08-19T16:02:20.000Z

force_wfmanager/gui/tests/test_click_run.py

force-h2020/force-wfmanager

bcd488cd37092cacd9d0c81b544ee8c1654d1d92

[ "BSD-2-Clause" ]

396

2017-07-18T15:19:55.000Z

2021-05-03T06:23:06.000Z

force_wfmanager/gui/tests/test_click_run.py

force-h2020/force-wfmanager

bcd488cd37092cacd9d0c81b544ee8c1654d1d92

[ "BSD-2-Clause" ]

2

2019-03-05T16:23:10.000Z

2020-04-16T08:59:11.000Z

# (C) Copyright 2010-2020 Enthought, Inc., Austin, TX # All rights reserved. import unittest import sys import os from unittest import mock from click.testing import CliRunner import force_wfmanager.gui.run from force_wfmanager.tests.dummy_classes.dummy_wfmanager import \ DummyWfManager from force_wfmanager.version import __version__ def mock_run_constructor(*args, **kwargs): mock_wf_run = mock.Mock(spec=force_wfmanager.gui.run) mock_wf_run.main = lambda: None class TestClickRun(unittest.TestCase): def test_click_cli_version(self): clirunner = CliRunner() clirunner.invoke(force_wfmanager.gui.run.force_wfmanager, args="--version") def test_click_cli_main(self): with mock.patch('force_wfmanager.gui.run') as mock_run: mock_run.side_effect = mock_run_constructor force_wfmanager.gui.run.force_wfmanager() self.assertTrue(mock_run.force_wfmanager.called) def test_run_with_debug(self): with mock.patch('force_wfmanager.gui.run.WfManager') as mock_wf: mock_wf.return_value = DummyWfManager() force_wfmanager.gui.run.main( window_size=(1650, 1080), debug=True, profile=False, workflow_file=None ) self.log = force_wfmanager.gui.run.logging.getLogger(__name__) self.assertEqual(self.log.getEffectiveLevel(), 10) def test_run_with_profile(self): with mock.patch('force_wfmanager.gui.run.WfManager') as mock_wf: mock_wf.return_value = DummyWfManager() force_wfmanager.gui.run.main( window_size=(1650, 1080), debug=False, profile=True, workflow_file=None ) root = ('force_wfmanager-{}-{}.{}.{}' .format(__version__, sys.version_info.major, sys.version_info.minor, sys.version_info.micro)) exts = ['.pstats', '.prof'] files_exist = [False] * len(exts) for ind, ext in enumerate(exts): files_exist[ind] = os.path.isfile(root + ext) os.remove(root + ext) self.assertTrue(all(files_exist))

34.088235

74

0.615617

1,831

0.789905

0

228

0.098361

0286818653d925685a7dbe2ea01784b7a5521b18

675

py

Python

menu.py

shaolinbertrand/RPG

77292c54baa14baf9e09d036be67592bb8f2c093

[ "MIT" ]

null

menu.py

shaolinbertrand/RPG

77292c54baa14baf9e09d036be67592bb8f2c093

[ "MIT" ]

null

menu.py

shaolinbertrand/RPG

77292c54baa14baf9e09d036be67592bb8f2c093

[ "MIT" ]

null

from cadastrarJogador import cadastra_jogador from cadastrarMonstros import cadastra_monstro from atualizaJogador import atualiza from combate import combate_iniciado while True: print('Bem vindo ao RPG selecione a opção desenjada') print('[0] - Cadastrar Novo Jogador\n[1] - Atualizar Jogador\n[2] - Cadastrar Novo Monstro\n[3] Iniciar Combate\n[4]-Sair do sistema') o = int(input('Entre com o numero da opção desejada: ')) if o == 0: cadastra_jogador() elif o == 1: cadastra_monstro() elif o == 2: atualiza() elif o == 3: combate_iniciado() elif o == 4: break else: print('Opção invalida')

33.75

138

0.665185

0

235

0.345081

02869a45220bc3cd768ae9f192b46417fa96c690

4,354

py

Python

plugin_manager/accounts/models.py

ahharu/plugin-manager

43d5e2c6e25ed8f50eedf7fd876fbc04f75d94bb

[ "MIT" ]

null

plugin_manager/accounts/models.py

ahharu/plugin-manager

43d5e2c6e25ed8f50eedf7fd876fbc04f75d94bb

[ "MIT" ]

null

plugin_manager/accounts/models.py

ahharu/plugin-manager

43d5e2c6e25ed8f50eedf7fd876fbc04f75d94bb

[ "MIT" ]

null

""" Custom user model for deployments. """ import urllib import hashlib import base64 import random from authtools.models import AbstractEmailUser from django.db import models from django.utils.translation import ugettext_lazy as _ from django.db.models.signals import post_save from .managers import DeployUserManager from plugin_manager.hosts.models import Host from plugin_manager.accounts.model_managers import DeployUserActiveManager from plugin_manager.core.mixins.models import TrackingFields class DeployUser(AbstractEmailUser, TrackingFields): """ Custom user class for deployments. Email as username using django-custom-user. """ AMELIA = 'amelia.min.css' CERULEAN = 'cerulean.min.css' COSMO = 'cosmo.min.css' CYBORG = 'cyborg.min.css' DARKLY = 'darkly.min.css' FLATLY = 'flatly.min.css' JOURNAL = 'journal.min.css' LUMEN = 'lumen.min.css' READABLE = 'readable.min.css' SIMPLEX = 'simplex.min.css' SLATE = 'slate.min.css' SPACELAB = 'spacelab.min.css' SUPERHERO = 'superhero.min.css' UNITED = 'united.min.css' YETI = 'yeti.min.css' TEMPLATES = ( (AMELIA, 'Amelia'), (CERULEAN, 'Cerulean'), (COSMO, 'Cosmo'), (CYBORG, 'Cyborg'), (DARKLY, 'Darkly'), (FLATLY, 'Flatly'), (JOURNAL, 'Journal'), (LUMEN, 'Lumen'), (READABLE, 'Readable'), (SIMPLEX, 'Simplex'), (SLATE, 'Slate'), (SPACELAB, 'Spacelab'), (SUPERHERO, 'Superhero'), (UNITED, 'United'), (YETI, 'Yeti'), ) active_records = DeployUserActiveManager() first_name = models.CharField(_('first name'), max_length=30, blank=False) last_name = models.CharField(_('last name'), max_length=30, blank=False) template = models.CharField(max_length=255, blank=True, choices=TEMPLATES, default=YETI) objects = DeployUserManager() def __unicode__(self): return u'{} {}'.format(self.first_name, self.last_name) @property def role(self): """ Assumes the user is only assigned to one role and return it """ return self.group_strigify() def _get_groups(self): if not hasattr(self, '_cached_groups'): self._cached_groups = list(self.groups.values_list("name", flat=True)) return self._cached_groups def user_is_admin(self): if not self.pk: return False return "Admin" in self._get_groups() def user_is_deployer(self): if not self.pk: return False return "Deployer" in self._get_groups() def user_is_historian(self): if not self.pk: return False return "Historian" in self._get_groups() def group_strigify(self): """ Converts this user's group(s) to a string and returns it. """ return "/".join(self._get_groups()) def gravatar(self, size=20): """ Construct a gravatar image address for the user """ default = "mm" gravatar_url = "http://www.gravatar.com/avatar/" + hashlib.md5( self.email.lower()).hexdigest() + "?" gravatar_url += urllib.urlencode({'d': default, 's': str(size)}) return gravatar_url class APIKey(models.Model): apikey = models.CharField(max_length=255, primary_key=True) deployuser = models.ForeignKey(DeployUser) class Meta: unique_together = (("apikey", "deployuser"),) class PermissionHost(models.Model): user = models.ForeignKey(DeployUser) host = models.ForeignKey(Host) def __unicode__(self): return u'User: {} Host: {}'.format(self.user, self.host) def generate_APIKey(sender, instance, created, **kwargs): if created: apikey = APIKey() apikey.apikey = base64.b64encode(hashlib.sha256( str(random.getrandbits(256))).digest(), random.choice( ['rA', 'aZ', 'gQ', 'hH', 'hG', 'aR', 'DD'])).rstrip('==') apikey.deployuser = instance apikey.save() post_save.connect(generate_APIKey, sender=DeployUser)

29.221477

78

0.595315

3,312

0.76068

0

158

0.036288

0

949

0.21796

02871af56c42a72cf7ba11b3dac2fc5de68923f2

1,007

py

Python

heads/fc1024_normalize.py

ahmdtaha/tf_retrieval_baseline

31b1588f888cecc1d4287f77bd046314956482d5

[ "Apache-2.0" ]

37

2019-06-01T02:11:48.000Z

2021-12-31T06:27:42.000Z

heads/fc1024_normalize.py

ahmdtaha/tf_retrieval_baseline

31b1588f888cecc1d4287f77bd046314956482d5

[ "Apache-2.0" ]

1

2019-06-21T03:20:59.000Z

2019-09-03T14:20:04.000Z

heads/fc1024_normalize.py

ahmdtaha/tf_retrieval_baseline

31b1588f888cecc1d4287f77bd046314956482d5

[ "Apache-2.0" ]

6

2019-10-11T10:21:56.000Z

2022-03-09T06:22:57.000Z

import tensorflow as tf from tensorflow.contrib import slim def head(endpoints, embedding_dim, is_training, weights_regularizer=None): predict_var = 0 input = endpoints['model_output'] endpoints['head_output'] = slim.fully_connected( input, 1024, normalizer_fn=slim.batch_norm, normalizer_params={ 'decay': 0.9, 'epsilon': 1e-5, 'scale': True, 'is_training': is_training, 'updates_collections': tf.GraphKeys.UPDATE_OPS, }, weights_regularizer=weights_regularizer ) input_1 = endpoints['head_output'] endpoints['emb_raw'] = slim.fully_connected( input_1, embedding_dim + predict_var, activation_fn=None,weights_regularizer=weights_regularizer, weights_initializer=tf.orthogonal_initializer(), scope='emb') endpoints['emb'] = tf.nn.l2_normalize(endpoints['emb_raw'], -1) # endpoints['data_sigma'] = None print('Normalize batch embedding') return endpoints

33.566667

105

0.675273

0

184

0.182721

02875f5951726e518af5547e018727a57f4c2846

1,144

py

Python

vendor/github.com/elastic/beats/topbeat/tests/system/test_base.py

ninjasftw/libertyproxybeat

b8acafe86ad285f091bf69b59d2ebd1da80dcf5e

[ "Apache-2.0" ]

37

2016-01-25T10:52:59.000Z

2021-05-08T11:44:39.000Z

vendor/github.com/elastic/beats/topbeat/tests/system/test_base.py

ninjasftw/libertyproxybeat

b8acafe86ad285f091bf69b59d2ebd1da80dcf5e

[ "Apache-2.0" ]

35

2016-01-25T09:19:28.000Z

2017-11-20T23:29:35.000Z

vendor/github.com/elastic/beats/topbeat/tests/system/test_base.py

ninjasftw/libertyproxybeat

b8acafe86ad285f091bf69b59d2ebd1da80dcf5e

[ "Apache-2.0" ]

23

2016-01-25T09:15:05.000Z

2020-12-14T06:08:31.000Z

from topbeat import BaseTest import os import shutil import time """ Contains tests for base config """ class Test(BaseTest): def test_invalid_config(self): """ Checks stop when input and topbeat defined """ shutil.copy("./config/topbeat-input-invalid.yml", os.path.join(self.working_dir, "invalid.yml")) exit_code = self.run_beat(config="invalid.yml", extra_args=["-N"]) assert exit_code == 1 assert self.log_contains( "'topbeat' and 'input' are both set in config.") is True def test_old_config(self): """ Test that old config still works with deprecation warning """ shutil.copy("./config/topbeat-old.yml", os.path.join(self.working_dir, "topbeat-old.yml")) topbeat = self.start_beat(config="topbeat-old.yml", extra_args=["-N"]) time.sleep(1) topbeat.check_kill_and_wait() assert self.log_contains( "Using 'input' in configuration is deprecated and is scheduled to " "be removed in Topbeat 6.0. Use 'topbeat' instead.") is True

28.6

79

0.612762

1,035

0.90472

0

480

0.41958

0289963af258cded39c2b0dcfaad0d26f59c24b0

7,133

py

Python

JapanSize.py

AleksanderLidtke/XKCD

47c5029d9737390a910184adc66efc1347b84441

[ "MIT" ]

null

JapanSize.py

AleksanderLidtke/XKCD

47c5029d9737390a910184adc66efc1347b84441

[ "MIT" ]

null

JapanSize.py

AleksanderLidtke/XKCD

47c5029d9737390a910184adc66efc1347b84441

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ Throughout my travels I've discovered that most people, including myself, do not realise many things about our Planet's size. For example, the latitude and longitude of certain regions (South America is much further east than the US) or the relative size of countries (Japan is surprisingly long). Thus, I've created this script to understand such things a bit better. It compares the sizes of Japan and Europe, which is the most recent surprise I came across. The shape data were aquired from [Global Administrative Areas](http://www.gadm.org/country) website. Thus, their **redistribution, or commercial use is not allowed without prior permission**. Created on Sun May 7 14:13:47 2017 @author: Alek """ from mpl_toolkits.basemap import Basemap import numpy, shapefile, os, matplotlib.pyplot matplotlib.pyplot.xkcd() # Here we go. def plotPrefecture(*,shp,colour,bMap,axes,latOff=0,longOff=0,lwdth=0.5): """ Plot a prefecture from a shapefile. Kwargs ------- * shp - shape as returned by :func:`shapefile.Reader.shapes`, * colour - colour accepted by :func:`matplotlib.pyplot.Axes.plot', * bMap - instance of :class:`mpl_toolkits.basemap.Basemap` used to project the shape onto a map, * axes - :class:`matplotlib.pyplot.Axes` instance where to plot, * latOff,longOff - deg, by how much to offset the `shp` lattitudes and longitudes before plotting, * lwdth - line width as accepted by :func:`matplotlib.pyplot.Axes.plot'. """ if len(shp.parts)==1: # Only one region in this shape. vertices=numpy.array(shp.points) bMap.plot(vertices[:,0]+longOff,vertices[:,1]+latOff,color=colour, lw=lwdth,ls='-',latlon=True,ax=axes) else: # This shape has islands, disjoint regions and what-not. for ip in range(len(shp.parts)): # For every part of the shape. # Indices that get the slice with this part of the shape. lower=shp.parts[ip] if ip==len(shp.parts)-1: upper=len(shp.points) # Last part. else: upper=shp.parts[ip+1] # Next part starts at idx parts[ip+1] partVertices=numpy.array(shp.points[lower:upper]) bMap.plot(partVertices[:,0]+longOff,partVertices[:,1]+latOff, color=colour,lw=lwdth,ls='-',latlon=True,ax=axes) # Various font sizes. ticksFontSize=18 labelsFontSizeSmall=20 labelsFontSize=30 titleFontSize=34 legendFontSize=20 matplotlib.rc('xtick',labelsize=ticksFontSize) matplotlib.rc('ytick',labelsize=ticksFontSize) cm=matplotlib.pyplot.cm.get_cmap('viridis') # Read a shapefile with Japan's cartography data. shapeRdr0=shapefile.Reader(os.path.join('borders','JPN_adm0')) # Country. shapeRdr1=shapefile.Reader(os.path.join('borders','JPN_adm1')) # Prefectures. shapeRdr2=shapefile.Reader(os.path.join('borders','JPN_adm2')) # Towns. shape=shapeRdr0.shapes()[0] if shape.shapeType != shapefile.POLYGON: raise ValueError('Shape not polygon with shapeType={}'.format(shape.shapeType )) vertices=numpy.array(shape.points) # 2D array of coordinates. # Where to centre different maps and where to translate Japan to. latJpn=37 # Where to centre one map, i.e. over Japan. Lat/lon in degrees. lonJpn=138 latCtr=40 # Where to centre the Europe's map. Lat/lon in degrees. lonCtr=10 dLonJ=10 # Plot Japan at these coordinates over the map of Europe. dLatJ=50 ' Mercator projection, a.k.a. "the things you learn in schools".' fig,ax=matplotlib.pyplot.subplots(1,2,figsize=(16,8)) # The whole Planet. mercMapP=Basemap(projection='merc',llcrnrlat=-80,urcrnrlat=80,llcrnrlon=-180, urcrnrlon=180,lat_ts=10,ax=ax[0],resolution='c') mercMapP.drawcoastlines(linewidth=0.5) mercMapP.drawcountries(linewidth=0.25) mercMapP.drawparallels(numpy.arange(-90.,91.,30.)) mercMapP.drawmeridians(numpy.arange(-180.,181.,60.)) ax[0].set_title(r'$Our\ Planet$',fontsize=titleFontSize) plotPrefecture(shp=shape,colour='gold',lwdth=1,bMap=mercMapP,axes=ax[0]) # Only Europe. mercMapE=Basemap(projection='merc',llcrnrlat=30,urcrnrlat=75,llcrnrlon=-25, urcrnrlon=40,lat_ts=10,ax=ax[1],resolution='l') mercMapE.drawcoastlines(linewidth=0.5) mercMapE.drawcountries(linewidth=0.25) mercMapE.drawparallels(numpy.arange(mercMapE.latmin,mercMapE.latmax,10.)) mercMapE.drawmeridians(numpy.arange(mercMapE.lonmin,mercMapE.lonmax,15.)) ax[1].set_title(r'$Europe$',fontsize=titleFontSize) plotPrefecture(shp=shape,colour='gold',lwdth=2,bMap=mercMapE,axes=ax[1], latOff=dLatJ-latJpn,longOff=dLonJ-lonJpn) fig.show() ' One figure with orthonormal maps centred on Japan and Europe.' fig,ax=matplotlib.pyplot.subplots(1,2,figsize=(16,8)) # Centred on Japan. ortnMapJ=Basemap(projection='ortho',lat_0=latJpn,lon_0=lonJpn,resolution='c', ax=ax[0]) ortnMapJ.drawcoastlines(linewidth=0.5) ortnMapJ.drawcountries(linewidth=0.25) ortnMapJ.drawmeridians(numpy.arange(0,360,30)) ortnMapJ.drawparallels(numpy.arange(-90,90,30)) ax[0].set_title(r'${}$'.format(shapeRdr0.records()[0][4]),fontsize=titleFontSize) plotPrefecture(shp=shape,colour='gold',lwdth=2,bMap=ortnMapJ,axes=ax[0]) # Plot all the prefectures. cNorm=matplotlib.colors.Normalize(vmin=0,vmax=shapeRdr1.numRecords) scalarMap=matplotlib.cm.ScalarMappable(norm=cNorm,cmap=cm) prefectures=shapeRdr1.shapes() prefRecords=shapeRdr1.records() for i in range(shapeRdr1.numRecords): if prefRecords[i][9]=='Prefecture': plotPrefecture(shp=prefectures[i],colour=scalarMap.to_rgba(i), lwdth=0.5,bMap=ortnMapJ,axes=ax[0]) # Centred on Europe. ortnMapE=Basemap(projection='ortho',lat_0=latCtr,lon_0=lonCtr,resolution='c', ax=ax[1]) ortnMapE.drawcoastlines(linewidth=0.5) ortnMapE.drawcountries(linewidth=0.25) ortnMapE.drawmeridians(numpy.arange(0,360,30)) ortnMapE.drawparallels(numpy.arange(-90,90,30)) ax[1].set_title(r'${}\ over\ Europe$'.format(shapeRdr0.records()[0][4]), fontsize=titleFontSize) plotPrefecture(shp=shape,colour='gold',lwdth=2,bMap=ortnMapE,axes=ax[1], latOff=dLatJ-latJpn,longOff=dLonJ-lonJpn) fig.show() ' Japan and Kitakyushu overlaid on Europe.' fig,ax=matplotlib.pyplot.subplots(1,1,figsize=(16,8)) mercMapE=Basemap(projection='merc',llcrnrlat=30,urcrnrlat=75,llcrnrlon=-25, urcrnrlon=40,lat_ts=10,ax=ax,resolution='l') mercMapE.drawcoastlines(linewidth=0.5) mercMapE.drawcountries(linewidth=0.25) mercMapE.drawparallels(numpy.arange(mercMapE.latmin,mercMapE.latmax,10.)) mercMapE.drawmeridians(numpy.arange(mercMapE.lonmin,mercMapE.lonmax,15.)) ax.set_title(r'$Europe,\ true\ lat.$',fontsize=titleFontSize) plotPrefecture(shp=shape,colour='gold',lwdth=2,bMap=mercMapE,axes=ax, latOff=0,longOff=dLonJ-lonJpn) # Show annotation at the true latitude. xKIT,yKIT=mercMapE.projtran(130.834730+dLonJ-lonJpn,33.8924837) xTXT,yTXT=mercMapE.projtran(110.834730+dLonJ-lonJpn,45.8924837) ax.scatter([xKIT],[yKIT],s=50,c='crimson') ax.annotate('Here', xy=(xKIT,yKIT),xytext=(xTXT,yTXT),color='crimson', arrowprops=dict(facecolor='crimson', shrink=0.05)) fig.show()

43.493902

91

0.728305

0

2,550

0.357493

028a79224d1b3b0d7d2cc26a3b2408f89ff5f8c5

7,252

py

Python

lstm_toyexample.py

dsriaditya999/LSTM-Toy-Example

850f7923122b547c1fd25b3b1dc739e8c5db2570

[ "MIT" ]

null

lstm_toyexample.py

dsriaditya999/LSTM-Toy-Example

850f7923122b547c1fd25b3b1dc739e8c5db2570

[ "MIT" ]

null

lstm_toyexample.py

dsriaditya999/LSTM-Toy-Example

850f7923122b547c1fd25b3b1dc739e8c5db2570

[ "MIT" ]

null

# -*- coding: utf-8 -*- # Importing Libraries """ # Commented out IPython magic to ensure Python compatibility. import torch import numpy as np import pandas as pd import seaborn as sns import matplotlib.pyplot as plt import torch.nn as nn from tqdm import tqdm_notebook from sklearn.preprocessing import MinMaxScaler # %matplotlib inline torch.manual_seed(0) """# Loading Dataset""" sns.get_dataset_names() flight_data = sns.load_dataset("flights") flight_data.head() """# Preprocessing""" # Changing the plot size figsize = plt.rcParams["figure.figsize"] figsize[0] = 15 figsize[1] = 5 plt.rcParams["figure.figsize"] = figsize # Plotting the data plt.title("Time Series Representation of Data") plt.xlabel("Months") plt.ylabel("Passengers") plt.grid(True) plt.autoscale(axis = "x",tight=True) plt.plot(flight_data["passengers"]) #Please note that this is univariate time series data : consisting of one variable passengers # data = flight_data["passengers"].values.astype(float) print(data) print(len(data)) # Train-Test Split # Consider the last the 12 months data as evaluation data for testing the model's behaviour train_window = 12 train_data = data[:-train_window] test_data = data[-train_window:] print(len(train_data)) print(len(test_data)) # Normalizing the train-data scaler = MinMaxScaler(feature_range=(-1,1)) train_data_normalized = scaler.fit_transform(train_data.reshape(-1,1)) print(train_data_normalized[:10]) # Converting to Torch Tensor train_data_normalized = torch.FloatTensor(train_data_normalized).view(-1) print(train_data_normalized) # Final step is creating sequences of length 12 (12 months data) from the train-data and # the label for each sequence is the passenger_data for the (12+1)th Month def create_in_sequences(input_data,tw): in_seq = [] L = len(input_data) for i in range(L-tw): train_seq = input_data[i:i+tw] train_label = input_data[i+tw:i+tw+1] in_seq.append((train_seq,train_label)) return in_seq # Therefore, we get 120 train sequences along with the label value train_in_seq = create_in_sequences(train_data_normalized,train_window) print(len(train_in_seq)) print(train_in_seq[:5]) """# The Model Please note that the model considered here is: 1. LSTM layer with a univariate input sequence of length 12 and LSTM's previous hidden cell consisting of previous hidden state and previous cell state of length 100 and also , the size of LSTM's output is 100 2. The second layer is a Linear layer of 100 inputs from the LSTM's output and a single output size """ class LSTM(nn.Module): #LSTM Class inheriting the inbuilt nn.Module class for neural networks def __init__(self,input_size = 1,hidden_layer_size = 100, output_size = 1): super().__init__() #Calls the init function of the nn.Module superclass for being able to access its features self.hidden_layer_size = hidden_layer_size # Defines the size of h(t-1) [Previous hidden output] and c(t-1) [previous cell state] self.lstm = nn.LSTM(input_size,hidden_layer_size,dropout = 0.45) # definining the LSTM with univariate input,output and with a dropout regularization of 0.45 self.linear = nn.Linear(hidden_layer_size,output_size) # Linear layer which returns the weighted sum of 100 outputs from the LSTM self.hidden_cell = (torch.ones(1,1,self.hidden_layer_size), # This is the previous hidden state torch.ones(1,1,self.hidden_layer_size)) # This is the previous cell state def forward(self,input_seq): lstm_out, self.hidden_cell = self.lstm(input_seq.view(len(input_seq),1,-1),self.hidden_cell) #returns 1200 outputs from each of the 100 output neurons for the 12 valued sequence predictions = self.linear(lstm_out.view(len(input_seq),-1)) # Reshaped to make it compatible as an input to the linear layer return predictions[-1] # The last element contains the prediction model = LSTM() print(model) """# Loss Function and Learning Algorithm (Optimizer) Please note that for this simple model , * Loss Function considered is *Mean Squared Error* and * Optimization Function used is Stochastic Version of **Adam** *Optimizer*. """ loss_fn = nn.MSELoss() # Mean Squared Error Loss Function optimizer = torch.optim.Adam(model.parameters(),lr = 0.0002) # Adam Learning Algorithm """# Training""" epochs = 450 loss_plot = [] for epoch in tqdm_notebook(range(epochs), total=epochs, unit="epoch"): for seq,label in train_in_seq: optimizer.zero_grad() # makes the gradients zero for each new sequence model.hidden_cell = (torch.zeros(1,1,model.hidden_layer_size), # Initialising the previous hidden state and cell state for each new sequence torch.zeros(1,1,model.hidden_layer_size)) y_pred = model(seq) # Automatically calls the forward pass loss = loss_fn(y_pred,label) # Determining the loss loss.backward() # Backpropagation of loss and gradients computation optimizer.step() # Weights and Bias Updation loss_plot.append(loss.item()) # Some Bookkeeping plt.plot(loss_plot,'r-') plt.xlabel("Epochs") plt.ylabel("Loss : MSE") plt.show() print(loss_plot[-1]) """# Making Prediction Please note that for comparison purpose we use the training data's values and predicted data values to predict the number of passengers for the test data months and then compare them """ fut_pred = 12 test_inputs = train_data_normalized[-train_window: ].tolist() print(test_inputs) print(len(test_inputs)) model.eval() # Makes the model ready for evaluation for i in range(fut_pred): seq = torch.FloatTensor(test_inputs[-train_window: ]) # Converting to a tensor with torch.no_grad(): # Stops adding to the computational flow graph (stops being prepared for backpropagation) model.hidden_cell = (torch.zeros(1,1,model.hidden_layer_size), torch.zeros(1,1,model.hidden_layer_size)) test_inputs.append(model(seq).item()) predicted_outputs_normalized = [] predicted_outputs_normalized = test_inputs[-train_window: ] print(predicted_outputs_normalized) print(len(predicted_outputs_normalized)) """# Postprocessing""" predicted_outputs = scaler.inverse_transform(np.array(predicted_outputs_normalized).reshape(-1,1)) print(predicted_outputs) x = np.arange(132, 144, 1) print(x) """# Final Output""" figsize = plt.rcParams["figure.figsize"] figsize[0] = 15 figsize[1] = 5 plt.rcParams["figure.figsize"] = figsize plt.title('Month vs Passenger') plt.ylabel('Total Passengers') plt.grid(True) plt.autoscale(axis='x', tight=True) plt.plot(flight_data['passengers']) plt.plot(x,predicted_outputs) plt.show() figsize = plt.rcParams["figure.figsize"] figsize[0] = 15 figsize[1] = 5 plt.rcParams["figure.figsize"] = figsize plt.title('Month vs Passenger') plt.ylabel('Total Passengers') plt.grid(True) plt.autoscale(axis='x', tight=True) plt.plot(flight_data['passengers'][-train_window-5: ]) plt.plot(x,predicted_outputs) plt.show() """**Please observe that the model is able to get the trend of the passengers but it can be further fine-tuned by adding appropriate regularization methods**"""

34.046948

212

0.734694

1,387

0.191258

0

3,469

0.478351

028b6c5908aab150cc0d4d671ccfb977919ebe32

22,929

py

Python

api/chat.py

Jecosine/blivechat

d398e4913e0c76d93d3f5402938dc59ea1424ec6

[ "MIT" ]

null

api/chat.py

Jecosine/blivechat

d398e4913e0c76d93d3f5402938dc59ea1424ec6

[ "MIT" ]

null

api/chat.py

Jecosine/blivechat

d398e4913e0c76d93d3f5402938dc59ea1424ec6

[ "MIT" ]

null

# -*- coding: utf-8 -*- import asyncio import enum import json import logging import random import time import uuid from typing import * import aiohttp import tornado.websocket import api.base import blivedm.blivedm as blivedm import config import models.avatar import models.translate import models.log logger = logging.getLogger(__name__) class Command(enum.IntEnum): HEARTBEAT = 0 JOIN_ROOM = 1 ADD_TEXT = 2 ADD_GIFT = 3 ADD_MEMBER = 4 ADD_SUPER_CHAT = 5 DEL_SUPER_CHAT = 6 UPDATE_TRANSLATION = 7 _http_session = aiohttp.ClientSession(timeout=aiohttp.ClientTimeout(total=10)) room_manager: Optional['RoomManager'] = None def init(): global room_manager room_manager = RoomManager() class Room(blivedm.BLiveClient): HEARTBEAT_INTERVAL = 10 # 重新定义parse_XXX是为了减少对字段名的依赖，防止B站改字段名 def __parse_danmaku(self, command): info = command['info'] if info[3]: room_id = info[3][3] medal_level = info[3][0] else: room_id = medal_level = 0 return self._on_receive_danmaku(blivedm.DanmakuMessage( None, None, None, info[0][4], None, None, info[0][9], None, info[1], info[2][0], info[2][1], info[2][2], None, None, info[2][5], info[2][6], None, medal_level, None, None, room_id, None, None, info[4][0], None, None, None, None, info[7] )) def __parse_gift(self, command): data = command['data'] return self._on_receive_gift(blivedm.GiftMessage( data['giftName'], data['num'], data['uname'], data['face'], None, data['uid'], data['timestamp'], None, None, None, None, None, data['coin_type'], data['total_coin'] )) def __parse_buy_guard(self, command): data = command['data'] return self._on_buy_guard(blivedm.GuardBuyMessage( data['uid'], data['username'], data['guard_level'], None, None, None, None, data['start_time'], None )) def __parse_super_chat(self, command): data = command['data'] return self._on_super_chat(blivedm.SuperChatMessage( data['price'], data['message'], None, data['start_time'], None, None, data['id'], None, None, data['uid'], data['user_info']['uname'], data['user_info']['face'], None, None, None, None, None, None, None )) _COMMAND_HANDLERS = { **blivedm.BLiveClient._COMMAND_HANDLERS, 'DANMU_MSG': __parse_danmaku, 'SEND_GIFT': __parse_gift, 'GUARD_BUY': __parse_buy_guard, 'SUPER_CHAT_MESSAGE': __parse_super_chat } def __init__(self, room_id): super().__init__(room_id, session=_http_session, heartbeat_interval=self.HEARTBEAT_INTERVAL) self.clients: List['ChatHandler'] = [] self.auto_translate_count = 0 async def init_room(self): await super().init_room() return True def stop_and_close(self): if self.is_running: future = self.stop() future.add_done_callback(lambda _future: asyncio.ensure_future(self.close())) else: asyncio.ensure_future(self.close()) def send_message(self, cmd, data): body = json.dumps({'cmd': cmd, 'data': data}) models.log.add_danmaku(self.room_id, body) for client in self.clients: try: client.write_message(body) except tornado.websocket.WebSocketClosedError: room_manager.del_client(self.room_id, client) def send_message_if(self, can_send_func: Callable[['ChatHandler'], bool], cmd, data): body = json.dumps({'cmd': cmd, 'data': data}) for client in filter(can_send_func, self.clients): try: client.write_message(body) except tornado.websocket.WebSocketClosedError: room_manager.del_client(self.room_id, client) async def _on_receive_danmaku(self, danmaku: blivedm.DanmakuMessage): asyncio.ensure_future(self.__on_receive_danmaku(danmaku)) async def __on_receive_danmaku(self, danmaku: blivedm.DanmakuMessage): if danmaku.uid == self.room_owner_uid: author_type = 3 # 主播 elif danmaku.admin: author_type = 2 # 房管 elif danmaku.privilege_type != 0: # 1总督，2提督，3舰长 author_type = 1 # 舰队 else: author_type = 0 need_translate = self._need_translate(danmaku.msg) if need_translate: translation = models.translate.get_translation_from_cache(danmaku.msg) if translation is None: # 没有缓存，需要后面异步翻译后通知 translation = '' else: need_translate = False else: translation = '' id_ = uuid.uuid4().hex # 为了节省带宽用list而不是dict self.send_message(Command.ADD_TEXT, make_text_message( await models.avatar.get_avatar_url(danmaku.uid), int(danmaku.timestamp / 1000), danmaku.uname, author_type, danmaku.msg, danmaku.privilege_type, danmaku.msg_type, danmaku.user_level, danmaku.urank < 10000, danmaku.mobile_verify, 0 if danmaku.room_id != self.room_id else danmaku.medal_level, id_, translation )) if need_translate: await self._translate_and_response(danmaku.msg, id_) async def _on_receive_gift(self, gift: blivedm.GiftMessage): avatar_url = models.avatar.process_avatar_url(gift.face) models.avatar.update_avatar_cache(gift.uid, avatar_url) if gift.coin_type != 'gold': # 丢人 return id_ = uuid.uuid4().hex self.send_message(Command.ADD_GIFT, { 'id': id_, 'avatarUrl': avatar_url, 'timestamp': gift.timestamp, 'authorName': gift.uname, 'totalCoin': gift.total_coin, 'giftName': gift.gift_name, 'num': gift.num }) async def _on_buy_guard(self, message: blivedm.GuardBuyMessage): asyncio.ensure_future(self.__on_buy_guard(message)) async def __on_buy_guard(self, message: blivedm.GuardBuyMessage): id_ = uuid.uuid4().hex self.send_message(Command.ADD_MEMBER, { 'id': id_, 'avatarUrl': await models.avatar.get_avatar_url(message.uid), 'timestamp': message.start_time, 'authorName': message.username, 'privilegeType': message.guard_level }) async def _on_super_chat(self, message: blivedm.SuperChatMessage): avatar_url = models.avatar.process_avatar_url(message.face) models.avatar.update_avatar_cache(message.uid, avatar_url) need_translate = self._need_translate(message.message) if need_translate: translation = models.translate.get_translation_from_cache(message.message) if translation is None: # 没有缓存，需要后面异步翻译后通知 translation = '' else: need_translate = False else: translation = '' id_ = str(message.id) self.send_message(Command.ADD_SUPER_CHAT, { 'id': id_, 'avatarUrl': avatar_url, 'timestamp': message.start_time, 'authorName': message.uname, 'price': message.price, 'content': message.message, 'translation': translation }) if need_translate: asyncio.ensure_future(self._translate_and_response(message.message, id_)) async def _on_super_chat_delete(self, message: blivedm.SuperChatDeleteMessage): self.send_message(Command.ADD_SUPER_CHAT, { 'ids': list(map(str, message.ids)) }) def _need_translate(self, text): cfg = config.get_config() return ( cfg.enable_translate and (not cfg.allow_translate_rooms or self.room_id in cfg.allow_translate_rooms) and self.auto_translate_count > 0 and models.translate.need_translate(text) ) async def _translate_and_response(self, text, msg_id): translation = await models.translate.translate(text) if translation is None: return self.send_message_if( lambda client: client.auto_translate, Command.UPDATE_TRANSLATION, make_translation_message( msg_id, translation ) ) def make_text_message(avatar_url, timestamp, author_name, author_type, content, privilege_type, is_gift_danmaku, author_level, is_newbie, is_mobile_verified, medal_level, id_, translation): return [ # 0: avatarUrl avatar_url, # 1: timestamp timestamp, # 2: authorName author_name, # 3: authorType author_type, # 4: content content, # 5: privilegeType privilege_type, # 6: isGiftDanmaku 1 if is_gift_danmaku else 0, # 7: authorLevel author_level, # 8: isNewbie 1 if is_newbie else 0, # 9: isMobileVerified 1 if is_mobile_verified else 0, # 10: medalLevel medal_level, # 11: id id_, # 12: translation translation ] def make_translation_message(msg_id, translation): return [ # 0: id msg_id, # 1: translation translation ] class RoomManager: def __init__(self): self._rooms: Dict[int, Room] = {} async def get_room(self, room_id): if room_id not in self._rooms: if not await self._add_room(room_id): return room = self._rooms.get(room_id, None) return room async def add_client(self, room_id, client: 'ChatHandler'): if room_id not in self._rooms: if not await self._add_room(room_id): client.close() return room = self._rooms.get(room_id, None) if room is None: return room.clients.append(client) logger.info('%d clients in room %s', len(room.clients), room_id) if client.auto_translate: room.auto_translate_count += 1 await client.on_join_room() def del_client(self, room_id, client: 'ChatHandler'): room = self._rooms.get(room_id, None) if room is None: return try: room.clients.remove(client) except ValueError: # _add_room未完成，没有执行到room.clients.append pass else: logger.info('%d clients in room %s', len(room.clients), room_id) if client.auto_translate: room.auto_translate_count = max(0, room.auto_translate_count - 1) if not room.clients: self._del_room(room_id) async def _add_room(self, room_id): if room_id in self._rooms: return True logger.info('Creating room %d', room_id) self._rooms[room_id] = room = Room(room_id) if await room.init_room(): # start new log file room.start() logger.info('%d rooms', len(self._rooms)) return True else: self._del_room(room_id) return False def _del_room(self, room_id): room = self._rooms.get(room_id, None) if room is None: return logger.info('Removing room %d', room_id) for client in room.clients: client.close() room.stop_and_close() self._rooms.pop(room_id, None) logger.info('%d rooms', len(self._rooms)) # noinspection PyAbstractClass class ChatHandler(tornado.websocket.WebSocketHandler): HEARTBEAT_INTERVAL = 10 RECEIVE_TIMEOUT = HEARTBEAT_INTERVAL + 5 def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self._heartbeat_timer_handle = None self._receive_timeout_timer_handle = None self.room_id = None self.auto_translate = False def open(self): logger.info('Websocket connected %s', self.request.remote_ip) self._heartbeat_timer_handle = asyncio.get_event_loop().call_later( self.HEARTBEAT_INTERVAL, self._on_send_heartbeat ) self._refresh_receive_timeout_timer() def _on_send_heartbeat(self): self.send_message(Command.HEARTBEAT, {}) self._heartbeat_timer_handle = asyncio.get_event_loop().call_later( self.HEARTBEAT_INTERVAL, self._on_send_heartbeat ) def _refresh_receive_timeout_timer(self): if self._receive_timeout_timer_handle is not None: self._receive_timeout_timer_handle.cancel() self._receive_timeout_timer_handle = asyncio.get_event_loop().call_later( self.RECEIVE_TIMEOUT, self._on_receive_timeout ) def _on_receive_timeout(self): logger.warning('Client %s timed out', self.request.remote_ip) self._receive_timeout_timer_handle = None self.close() def on_close(self): logger.info('Websocket disconnected %s room: %s', self.request.remote_ip, str(self.room_id)) if self.has_joined_room: room_manager.del_client(self.room_id, self) if self._heartbeat_timer_handle is not None: self._heartbeat_timer_handle.cancel() self._heartbeat_timer_handle = None if self._receive_timeout_timer_handle is not None: self._receive_timeout_timer_handle.cancel() self._receive_timeout_timer_handle = None def on_message(self, message): try: # 超时没有加入房间也断开 if self.has_joined_room: self._refresh_receive_timeout_timer() body = json.loads(message) cmd = body['cmd'] if cmd == Command.HEARTBEAT: pass elif cmd == Command.JOIN_ROOM: if self.has_joined_room: return self._refresh_receive_timeout_timer() self.room_id = int(body['data']['roomId']) logger.info('Client %s is joining room %d', self.request.remote_ip, self.room_id) try: cfg = body['data']['config'] self.auto_translate = cfg['autoTranslate'] except KeyError: pass asyncio.ensure_future(room_manager.add_client(self.room_id, self)) else: logger.warning('Unknown cmd, client: %s, cmd: %d, body: %s', self.request.remote_ip, cmd, body) except Exception: logger.exception('on_message error, client: %s, message: %s', self.request.remote_ip, message) # 跨域测试用 def check_origin(self, origin): if self.application.settings['debug']: return True return super().check_origin(origin) @property def has_joined_room(self): return self.room_id is not None def send_message(self, cmd, data): body = json.dumps({'cmd': cmd, 'data': data}) try: self.write_message(body) except tornado.websocket.WebSocketClosedError: self.close() async def on_join_room(self): if self.application.settings['debug']: await self.send_test_message() # 不允许自动翻译的提示 if self.auto_translate: cfg = config.get_config() if cfg.allow_translate_rooms and self.room_id not in cfg.allow_translate_rooms: self.send_message(Command.ADD_TEXT, make_text_message( models.avatar.DEFAULT_AVATAR_URL, int(time.time()), 'blivechat', 2, 'Translation is not allowed in this room. Please download to use translation', 0, False, 60, False, True, 0, uuid.uuid4().hex, '' )) # 测试用 async def send_test_message(self): base_data = { 'avatarUrl': await models.avatar.get_avatar_url(300474), 'timestamp': int(time.time()), 'authorName': 'xfgryujk', } text_data = make_text_message( base_data['avatarUrl'], base_data['timestamp'], base_data['authorName'], 0, '我能吞下玻璃而不伤身体', 0, False, 20, False, True, 0, uuid.uuid4().hex, '' ) member_data = { **base_data, 'id': uuid.uuid4().hex, 'privilegeType': 3 } gift_data = { **base_data, 'id': uuid.uuid4().hex, 'totalCoin': 450000, 'giftName': '摩天大楼', 'num': 1 } sc_data = { **base_data, 'id': str(random.randint(1, 65535)), 'price': 30, 'content': 'The quick brown fox jumps over the lazy dog', 'translation': '' } self.send_message(Command.ADD_TEXT, text_data) text_data[2] = '主播' text_data[3] = 3 text_data[4] = "I can eat glass, it doesn't hurt me." text_data[11] = uuid.uuid4().hex self.send_message(Command.ADD_TEXT, text_data) self.send_message(Command.ADD_MEMBER, member_data) self.send_message(Command.ADD_SUPER_CHAT, sc_data) sc_data['id'] = str(random.randint(1, 65535)) sc_data['price'] = 100 sc_data['content'] = '敏捷的棕色狐狸跳过了懒狗' self.send_message(Command.ADD_SUPER_CHAT, sc_data) # self.send_message(Command.DEL_SUPER_CHAT, {'ids': [sc_data['id']]}) self.send_message(Command.ADD_GIFT, gift_data) gift_data['id'] = uuid.uuid4().hex gift_data['totalCoin'] = 1245000 gift_data['giftName'] = '小电视飞船' self.send_message(Command.ADD_GIFT, gift_data) # noinspection PyAbstractClass class RoomInfoHandler(api.base.ApiHandler): _host_server_list_cache = blivedm.DEFAULT_DANMAKU_SERVER_LIST async def get(self): room_id = int(self.get_query_argument('roomId')) logger.info('Client %s is getting room info %d', self.request.remote_ip, room_id) room_id, owner_uid = await self._get_room_info(room_id) host_server_list = await self._get_server_host_list(room_id) if owner_uid == 0: # 缓存3分钟 self.set_header('Cache-Control', 'private, max-age=180') else: # 缓存1天 self.set_header('Cache-Control', 'private, max-age=86400') self.write({ 'roomId': room_id, 'ownerUid': owner_uid, 'hostServerList': host_server_list }) @staticmethod async def _get_room_info(room_id): try: async with _http_session.get(blivedm.ROOM_INIT_URL, params={'room_id': room_id} ) as res: if res.status != 200: logger.warning('room %d _get_room_info failed: %d %s', room_id, res.status, res.reason) return room_id, 0 data = await res.json() except (aiohttp.ClientConnectionError, asyncio.TimeoutError): logger.exception('room %d _get_room_info failed', room_id) return room_id, 0 if data['code'] != 0: logger.warning('room %d _get_room_info failed: %s', room_id, data['message']) return room_id, 0 room_info = data['data']['room_info'] return room_info['room_id'], room_info['uid'] @classmethod async def _get_server_host_list(cls, _room_id): return cls._host_server_list_cache # 连接其他host必须要key # try: # async with _http_session.get(blivedm.DANMAKU_SERVER_CONF_URL, params={'id': room_id, 'type': 0} # ) as res: # if res.status != 200: # logger.warning('room %d _get_server_host_list failed: %d %s', room_id, # res.status, res.reason) # return cls._host_server_list_cache # data = await res.json() # except (aiohttp.ClientConnectionError, asyncio.TimeoutError): # logger.exception('room %d _get_server_host_list failed', room_id) # return cls._host_server_list_cache # # if data['code'] != 0: # logger.warning('room %d _get_server_host_list failed: %s', room_id, data['message']) # return cls._host_server_list_cache # # host_server_list = data['data']['host_list'] # if not host_server_list: # logger.warning('room %d _get_server_host_list failed: host_server_list is empty') # return cls._host_server_list_cache # # cls._host_server_list_cache = host_server_list # return host_server_list # noinspection PyAbstractClass class AvatarHandler(api.base.ApiHandler): async def get(self): uid = int(self.get_query_argument('uid')) avatar_url = await models.avatar.get_avatar_url_or_none(uid) if avatar_url is None: avatar_url = models.avatar.DEFAULT_AVATAR_URL # 缓存3分钟 self.set_header('Cache-Control', 'private, max-age=180') else: # 缓存1天 self.set_header('Cache-Control', 'private, max-age=86400') self.write({ 'avatarUrl': avatar_url }) # noinspection PyAbstractClass # handle reply message class ReplyHandler(api.base.ApiHandler): def get(self): self.write('pong') async def post(self): uid = None if self.json_args['uid'] == -1 else self.json_args['uid'] avatar_url = await models.avatar.get_avatar_url(uid) text_message = make_text_message( avatar_url=avatar_url, timestamp=int(time.time()), author_name=self.json_args['name'], author_type=3, content=self.json_args['content'], author_level=0, id_=uuid.uuid4().hex, privilege_type=0, is_newbie=0, is_gift_danmaku=0, is_mobile_verified=True, medal_level=0, translation=0 ) # get room room: Room = await room_manager.get_room(room_id=self.json_args['room_id']) room.send_message(Command.ADD_TEXT, text_message)

34.019288

111

0.584326

21,544

0.925469

0

2,325

0.099875

12,763

0.548262

3,863

0.165944

65f43d030f26c2fcb657f044a4435543df49146f

954

py

Python

gan.py

AtlantixJJ/LBSGAN

e91d500d4a9c02dd5e3bfcbd9a9eca96dc60102a

[ "BSD-2-Clause" ]

1

2019-06-09T02:43:35.000Z

gan.py

AtlantixJJ/LBSGAN

e91d500d4a9c02dd5e3bfcbd9a9eca96dc60102a

[ "BSD-2-Clause" ]

null

gan.py

AtlantixJJ/LBSGAN

e91d500d4a9c02dd5e3bfcbd9a9eca96dc60102a

[ "BSD-2-Clause" ]

null

import argparse import os import sys import time import torch import torch.nn.functional as F import torchvision import models, lib cfg = lib.config.BaseConfig() cfg.parse() print('Preparing model') gen_model = cfg.gen_function( upsample=cfg.upsample, map_size=cfg.map_size, out_dim=cfg.out_dim) disc_model = cfg.disc_function( downsample=cfg.downsample, in_dim=cfg.out_dim) if cfg.num_gpu > 1: gen_model = torch.nn.DataParallel(gen_model) disc_model = torch.nn.DataParallel(disc_model) gen_model.cuda() disc_model.cuda() print(gen_model) print(disc_model) print("=> Generator") print(gen_model) print("=> Discriminator") print(disc_model) if cfg.args.delayed_batch_size > -1: trainer = lib.train.DelayLBSTrainer(gen_model=gen_model, disc_model=disc_model, dataloader=cfg.dl, cfg=cfg) else: trainer = lib.train.BaseGANTrainer(gen_model=gen_model, disc_model=disc_model, dataloader=cfg.dl, cfg=cfg) trainer.train()

24.461538

111

0.765199

0

49

0.051363

65f47a4c6cbf9c3cbfef8996d91a66023d1ce4f0

1,475

py

Python

leetcode/minimumAreaRectangle.py

federicoemartinez/problem_solving

d0352f76bc21ed67d6851a159a00f70a892934b9

[ "MIT" ]

null

leetcode/minimumAreaRectangle.py

federicoemartinez/problem_solving

d0352f76bc21ed67d6851a159a00f70a892934b9

[ "MIT" ]

null

leetcode/minimumAreaRectangle.py

federicoemartinez/problem_solving

d0352f76bc21ed67d6851a159a00f70a892934b9

[ "MIT" ]

null

# https://leetcode.com/problems/minimum-area-rectangle/description/ """ Given a set of points in the xy-plane, determine the minimum area of a rectangle formed from these points, with sides parallel to the x and y axes. If there isn't any rectangle, return 0. Example 1: Input: [[1,1],[1,3],[3,1],[3,3],[2,2]] Output: 4 Example 2: Input: [[1,1],[1,3],[3,1],[3,3],[4,1],[4,3]] Output: 2 Note: 1 <= points.length <= 500 0 <= points[i][0] <= 40000 0 <= points[i][1] <= 40000 All points are distinct. """ from collections import defaultdict class Solution: def minAreaRect(self, points): """ :type points: List[List[int]] :rtype: int """ same_x = defaultdict(lambda:set()) same_y = defaultdict(lambda:set()) for (x,y) in points: same_x[x].add((x,y)) same_y[y].add((x,y)) best_area = None for (x,y) in points: for same_x_point in same_x[x]: if same_x_point[1] < y:continue for same_y_point in same_y[y]: if same_y_point[0] < x: continue if (same_y_point[0], same_x_point[1]) in same_y[same_x_point[1]]: area = abs(same_x_point[1] - y) * abs(same_y_point[0] - x) if area > 0 and (best_area is None or best_area > area): best_area = area return 0 if best_area is None else best_area

27.314815

147

0.553898

887

0.601356

0

583

0.395254

65f96718aa17ce886b225fbdf113223d6df0b594

3,002

py

Python

code/google_sheet_writing.py

BastinFlorian/BoondManager-Auto-Holidays-Validation

28ae01d997132745018666952829771d5f8d99a3

[ "MIT" ]

null

code/google_sheet_writing.py

BastinFlorian/BoondManager-Auto-Holidays-Validation

28ae01d997132745018666952829771d5f8d99a3

[ "MIT" ]

18

2020-03-24T17:24:10.000Z

2022-03-12T00:29:56.000Z

code/google_sheet_writing.py

BastinFlorian/BoondManager-Auto-Holidays-Validation

28ae01d997132745018666952829771d5f8d99a3

[ "MIT" ]

null

'''Functions writing the needed informations in the google drive spreadsheet From CP, RTT and holidays request : create a worksheet per employee -- write_info_in_worksheet(info_paie, out_attente, out_valide, name, sh, problemes_date, problemes_type_conge) ''' from google_sheet_access import * # Write in worksheet at the specific cells def write_info_in_worksheet(info_paie, out_attente, out_valide, name, sh, problemes_date, problemes_type_conge): wks = acces_worksheet(sh, name) cp_to_add = out_attente[name].loc["CP"].tolist() rtt_to_add = out_attente[name].loc["RTT"].tolist() indice_row_pb_date = 8 indice_col_pb_date = 9 indice_row_pb_conge = 9 indice_col_pb_conge = 9 if (name in problemes_date.keys()): pb_date_name = problemes_date[name] update_cell(wks, indice_row_pb_date, indice_col_pb_date, " ".join(pb_date_name)) if (name in problemes_type_conge.keys()): pb_type_conge_name = problemes_type_conge[name] update_cell(wks, indice_row_pb_conge, indice_col_pb_conge, " ".join(pb_type_conge_name)) indice_col_cp = 2 indice_col_rtt = 3 indice_row_cp_rtt = 13 indice_row_cp_rtt_validees = 12 for (x, y) in zip(cp_to_add, rtt_to_add): indice_col_cp += 2 indice_col_rtt += 2 if (x + y == 0 or indice_col_rtt > 13): continue update_cell(wks, indice_row_cp_rtt, indice_col_cp, x) update_cell(wks, indice_row_cp_rtt, indice_col_rtt, y) if name in out_valide.keys(): cp_valide_to_add = out_valide[name].loc["CP"].tolist() rtt_valide_to_add = out_valide[name].loc["RTT"].tolist() indice_col_cp = 2 indice_col_rtt = 3 for (x, y) in zip(cp_valide_to_add, rtt_valide_to_add): indice_col_cp += 2 indice_col_rtt += 2 if (x + y == 0): continue update_cell(wks, indice_row_cp_rtt_validees, indice_col_cp, x) update_cell(wks, indice_row_cp_rtt_validees, indice_col_rtt, y) df_name = info_paie[info_paie["NOM Prénom"] == name] if (df_name.empty): df_name = info_paie[info_paie["nom"].str.contains(name.upper().replace(" ", "|"), regex=True)] if len(df_name) != 1: df_name = info_paie[info_paie[info_paie["prenom"].apply(lambda x: x.lower()) \ .str.contains(name.lower().replace(" ", "|"), regex=True)]] if len(df_name) != 1: df_name = info_paie[info_paie["NOM Prénom"] == name] if (df_name.empty): print("ERROR : FICHE DE PAIE NOT FOUND FOR --- %s." % name) else: row_cp_n = 6 row_cp_n1 = 7 col_cp_n_n1 = 6 row_rtt = 6 col_rtt = 7 update_cell(wks, row_cp_n, col_cp_n_n1, float(df_name["Congé_N_solde"])) update_cell(wks, row_cp_n1, col_cp_n_n1, float(df_name["Congé_N_1_solde"])) update_cell(wks, row_rtt, col_rtt, float(df_name["RTT_solde"])) print("%s done"%(name))

37.061728

112

0.651899

0

478

0.159015

65f9d6849276abc9d2abce58b864383e8eca894c

531

py

Python

madlib.py

Yukthi-C/python_learing

340579e2bb767e8fdb209f705fdf12058e8e150f

[ "MIT" ]

null

madlib.py

Yukthi-C/python_learing

340579e2bb767e8fdb209f705fdf12058e8e150f

[ "MIT" ]

null

madlib.py

Yukthi-C/python_learing

340579e2bb767e8fdb209f705fdf12058e8e150f

[ "MIT" ]

null

ad1 = input(f"Adjective1: ") ad2 = input(f"Adjective2: ") part1 = input(f"body part: ") dish = input(f"Dish: ") madlib=f"One day, a {ad1} fox invited a stork for dinner. \ Stork was very {ad2} with the invitation – she reached the fox’s home on time and knocked at the door with her {part1}.\ The fox took her to the dinner table and served some {dish} in shallow bowls for both of them.\ As the bowl was too shallow for the stork, she couldn’t have soup at all. But, the fox licked up his soup quickly." print(f"{madlib}")

59

121

0.706215

0

458

0.852886

65fb489a3669c5076b79a0d2bdaf7df0aec3faeb

3,114

py

Python

algofi/v1/send_keyreg_online_transaction.py

Algofiorg/algofi-py-sdk

6100a6726d36db4d4d3287064f0ad1d0b9a05e03

[ "MIT" ]

38

2021-12-30T02:32:57.000Z

2022-03-23T22:09:16.000Z

algofi/v1/send_keyreg_online_transaction.py

Algofiorg/algofi-py-sdk

6100a6726d36db4d4d3287064f0ad1d0b9a05e03

[ "MIT" ]

4

2021-11-03T00:14:46.000Z

2022-03-28T02:17:33.000Z

algofi/v1/send_keyreg_online_transaction.py

Algofiorg/algofi-py-sdk

6100a6726d36db4d4d3287064f0ad1d0b9a05e03

[ "MIT" ]

8

2021-12-15T05:29:55.000Z

2022-02-08T03:45:11.000Z

from algosdk.future.transaction import ApplicationNoOpTxn from .prepend import get_init_txns from ..utils import Transactions, TransactionGroup, int_to_bytes from ..contract_strings import algofi_manager_strings as manager_strings def prepare_send_keyreg_online_transactions(sender, suggested_params, storage_account, vote_pk, selection_pk, state_proof_pk, vote_first, vote_last, vote_key_dilution, manager_app_id, supported_market_app_ids, supported_oracle_app_ids): """Returns a :class:`TransactionGroup` object representing a send keyreg transaction group transaction against the algofi protocol. The sender instructs the algo vault to register itself online to participate in Algorand's consensus. NOTE: The storage account address must be registered with a participation node in order for the account to participate in consensus. It is unsafe to register an account online without registering it with a participation node. See https://developer.algorand.org/docs/run-a-node/participate/generate_keys :param sender: account address for the sender :type sender: string :param suggested_params: suggested transaction params :type suggested_params: :class:`algosdk.future.transaction.SuggestedParams` object :param storage_account: storage account address for sender :type storage_account: string :param vote_pk: vote key :type vote_pk: bytes :param selection_pk: selection key :type selection_pk: bytes :param state_proof_pk: state proof key :type state_proof_pk: bytes :param vote_first: first round to vote in consensus :type vote_first: int :param vote_last: last round to vote in consensus :type vote_last: int :param vote_key_dilution: vote key dilution :type vote_key_dilution: int :param manager_app_id: id of the manager application :type manager_app_id: int :param supported_market_app_ids: list of supported market application ids :type supported_market_app_ids: list :param supported_oracle_app_ids: list of supported oracle application ids :type supported_oracle_app_ids: list :return: :class:`TransactionGroup` object representing a claim rewards transaction :rtype: :class:`TransactionGroup` """ prefix_transactions = get_init_txns( transaction_type=Transactions.SEND_KEYREG_ONLINE_TXN, sender=sender, suggested_params=suggested_params, manager_app_id=manager_app_id, supported_market_app_ids=supported_market_app_ids, supported_oracle_app_ids=supported_oracle_app_ids, storage_account=storage_account ) txn0 = ApplicationNoOpTxn( sender=sender, sp=suggested_params, index=manager_app_id, app_args=[manager_strings.send_keyreg_txn.encode(), vote_pk, selection_pk, state_proof_pk, int_to_bytes(vote_first), int_to_bytes(vote_last), int_to_bytes(vote_key_dilution)], accounts=[storage_account], ) txn_group = TransactionGroup(prefix_transactions + [txn0]) return txn_group

48.65625

168

0.756583

0

1,777

0.570649

65fdd0400541291beac65b8a408eaf8121f2b56b

402

py

Python

server/resources/platform.py

simon-dube/CARMIN-server

1481d2c4231458d33119c57ab2e3e480375da63b

[ "MIT" ]

1

2018-03-12T23:08:12.000Z

server/resources/platform.py

simon-dube/CARMIN-server

1481d2c4231458d33119c57ab2e3e480375da63b

[ "MIT" ]

15

2018-03-15T04:23:31.000Z

2018-06-28T21:46:15.000Z

server/resources/platform.py

simon-dube/CARMIN-server

1481d2c4231458d33119c57ab2e3e480375da63b

[ "MIT" ]

null

from flask_restful import Resource from server.platform_properties import PLATFORM_PROPERTIES from server.resources.models.platform_properties import PlatformPropertiesSchema from server.resources.decorators import marshal_response class Platform(Resource): @marshal_response(PlatformPropertiesSchema()) def get(self): return PlatformPropertiesSchema().load(PLATFORM_PROPERTIES).data

36.545455

80

0.840796

167

0.415423

0

137

0.340796

0

65febfc830676365453c5d43b397d3e86ac87c5f

471

py

Python

invenio_flow/decorators.py

egabancho/invenio-flow

583e55d17ab6aabd20bc4a46d098f034c0d0f693

[ "MIT" ]

null

invenio_flow/decorators.py

egabancho/invenio-flow

583e55d17ab6aabd20bc4a46d098f034c0d0f693

[ "MIT" ]

null

invenio_flow/decorators.py

egabancho/invenio-flow

583e55d17ab6aabd20bc4a46d098f034c0d0f693

[ "MIT" ]

null

# -*- coding: utf-8 -*- # # Copyright (C) 2020 Esteban J. G. Gabancho. # # Invenio-Flow is free software; you can redistribute it and/or modify it # under the terms of the MIT License; see LICENSE file for more details. """Useful decorators.""" from celery import shared_task from .api import Task def task(*args, **kwargs): """Wrapper around shared task to set default base class.""" kwargs.setdefault('base', Task) return shared_task(*args, **kwargs)

23.55

73

0.694268

0

303

0.643312

65ff6cff89c7853c15b51290646017146b4909fa

2,460

py

Python

backend/offchain/types/fund_pull_pre_approval_types.py

tanshuai/reference-wallet

e8efec4acc6af6e319cf075c10693ddf7754cc83

[ "Apache-2.0" ]

14

2020-12-17T08:03:51.000Z

2022-03-26T04:21:18.000Z

backend/offchain/types/fund_pull_pre_approval_types.py

tanshuai/reference-wallet

e8efec4acc6af6e319cf075c10693ddf7754cc83

[ "Apache-2.0" ]

20

2020-12-15T12:02:56.000Z

2021-05-19T23:37:34.000Z

backend/offchain/types/fund_pull_pre_approval_types.py

tanshuai/reference-wallet

e8efec4acc6af6e319cf075c10693ddf7754cc83

[ "Apache-2.0" ]

12

2020-12-10T16:35:27.000Z

2022-02-01T04:06:10.000Z

import typing from dataclasses import dataclass, field as datafield from .command_types import CommandType class FundPullPreApprovalStatus: # Pending user/VASP approval pending = "pending" # Approved by the user/VASP and ready for use valid = "valid" # User/VASP did not approve the pre-approval request rejected = "rejected" # Approval has been closed by the user/VASP and can no longer be used closed = "closed" class TimeUnit: day = "day" week = "week" month = "month" year = "year" @dataclass(frozen=True) class CurrencyObject: amount: int currency: str @dataclass(frozen=True) class ScopedCumulativeAmountObject: unit: str = datafield( metadata={ "valid-values": [TimeUnit.day, TimeUnit.week, TimeUnit.month, TimeUnit.year] } ) value: int max_amount: CurrencyObject class FundPullPreApprovalType: save_sub_account = "save_sub_account" consent = "consent" @dataclass(frozen=True) class FundPullPreApprovalScopeObject: type: str = datafield( metadata={ "valid-values": [ FundPullPreApprovalType.save_sub_account, FundPullPreApprovalType.consent, ] } ) expiration_timestamp: int max_cumulative_amount: typing.Optional[ScopedCumulativeAmountObject] = datafield( default=None ) max_transaction_amount: typing.Optional[CurrencyObject] = datafield(default=None) @dataclass(frozen=True) class FundPullPreApprovalObject: funds_pull_pre_approval_id: str = datafield(metadata={"write_once": True}) address: str = datafield(metadata={"write_once": True}) biller_address: str = datafield(metadata={"write_once": True}) scope: FundPullPreApprovalScopeObject status: str = datafield( metadata={ "valid-values": [ FundPullPreApprovalStatus.pending, FundPullPreApprovalStatus.valid, FundPullPreApprovalStatus.rejected, FundPullPreApprovalStatus.closed, ] } ) description: typing.Optional[str] = datafield(default=None) @dataclass(frozen=True) class FundPullPreApprovalCommandObject: fund_pull_pre_approval: FundPullPreApprovalObject _ObjectType: str = datafield( default=CommandType.FundPullPreApprovalCommand, metadata={"valid-values": [CommandType.FundPullPreApprovalCommand]}, )

27.032967

88

0.681301

2,207

0.897154

0

1,806

0.734146

0

371

0.150813

65ffb62169d811cc14af150c5eafa69ec8772792

19,924

py

Python

data/battle_animation_scripts.py

kielbasiago/WorldsCollide

5aa7cffdecd14754c9eaa83cd0ad4d0282cc2cc2

[ "MIT" ]

7

2022-01-15T02:53:53.000Z

2022-02-17T00:51:32.000Z

data/battle_animation_scripts.py

asilverthorn/WorldsCollide

5aa7cffdecd14754c9eaa83cd0ad4d0282cc2cc2

[ "MIT" ]

8

2022-01-16T02:45:24.000Z

2022-03-21T02:08:27.000Z

data/battle_animation_scripts.py

asilverthorn/WorldsCollide

5aa7cffdecd14754c9eaa83cd0ad4d0282cc2cc2

[ "MIT" ]

5

2022-01-15T02:53:38.000Z

2022-01-19T17:42:10.000Z

# List of addresses within the Battle Animation Scripts for the following commands which cause screen flashes: # B0 - Set background palette color addition (absolute) # B5 - Add color to background palette (relative) # AF - Set background palette color subtraction (absolute) # B6 - Subtract color from background palette (relative) # By changing address + 1 to E0 (for absolute) or F0 (for relative), it causes no change to the background color (that is, no flash) BATTLE_ANIMATION_FLASHES = { "Goner": [ 0x100088, # AF E0 - set background color subtraction to 0 (black) 0x10008C, # B6 61 - increase background color subtraction by 1 (red) 0x100092, # B6 31 - decrease background color subtraction by 1 (yellow) 0x100098, # B6 81 - increase background color subtraction by 1 (cyan) 0x1000A1, # B6 91 - decrease background color subtraction by 1 (cyan) 0x1000A3, # B6 21 - increase background color subtraction by 1 (yellow) 0x1000D3, # B6 8F - increase background color subtraction by 15 (cyan) 0x1000DF, # B0 FF - set background color addition to 31 (white) 0x100172, # B5 F2 - decrease background color addition by 2 (white) ], "Final KEFKA Death": [ 0x10023A, # B0 FF - set background color addition to 31 (white) 0x100240, # B5 F4 - decrease background color addition by 4 (white) 0x100248, # B0 FF - set background color addition to 31 (white) 0x10024E, # B5 F4 - decrease background color addition by 4 (white) ], "Atom Edge": [ # Also True Edge 0x1003D0, # AF E0 - set background color subtraction to 0 (black) 0x1003DD, # B6 E1 - increase background color subtraction by 1 (black) 0x1003E6, # B6 E1 - increase background color subtraction by 1 (black) 0x10044B, # B6 F1 - decrease background color subtraction by 1 (black) 0x100457, # B6 F1 - decrease background color subtraction by 1 (black) ], "Boss Death": [ 0x100476, # B0 FF - set background color addition to 31 (white) 0x10047C, # B5 F4 - decrease background color addition by 4 (white) 0x100484, # B0 FF - set background color addition to 31 (white) 0x100497, # B5 F4 - decrease background color addition by 4 (white) ], "Transform into Magicite": [ 0x100F30, # B0 FF - set background color addition to 31 (white) 0x100F3F, # B5 F2 - decrease background color addition by 2 (white) 0x100F4E, # B5 F2 - decrease background color addition by 2 (white) ], "Purifier": [ 0x101340, # AF E0 - set background color subtraction to 0 (black) 0x101348, # B6 62 - increase background color subtraction by 2 (red) 0x101380, # B6 81 - increase background color subtraction by 1 (cyan) 0x10138A, # B6 F1 - decrease background color subtraction by 1 (black) ], "Wall": [ 0x10177B, # AF E0 - set background color subtraction to 0 (black) 0x10177F, # B6 61 - increase background color subtraction by 1 (red) 0x101788, # B6 51 - decrease background color subtraction by 1 (magenta) 0x101791, # B6 81 - increase background color subtraction by 1 (cyan) 0x10179A, # B6 31 - decrease background color subtraction by 1 (yellow) 0x1017A3, # B6 41 - increase background color subtraction by 1 (magenta) 0x1017AC, # B6 91 - decrease background color subtraction by 1 (cyan) 0x1017B5, # B6 51 - decrease background color subtraction by 1 (magenta) ], "Pearl": [ 0x10190E, # B0 E0 - set background color addition to 0 (white) 0x101913, # B5 E2 - increase background color addition by 2 (white) 0x10191E, # B5 F1 - decrease background color addition by 1 (white) 0x10193E, # B6 C2 - increase background color subtraction by 2 (blue) ], "Ice 3": [ 0x101978, # B0 FF - set background color addition to 31 (white) 0x10197B, # B5 F4 - decrease background color addition by 4 (white) 0x10197E, # B5 F4 - decrease background color addition by 4 (white) 0x101981, # B5 F4 - decrease background color addition by 4 (white) 0x101984, # B5 F4 - decrease background color addition by 4 (white) 0x101987, # B5 F4 - decrease background color addition by 4 (white) 0x10198A, # B5 F4 - decrease background color addition by 4 (white) 0x10198D, # B5 F4 - decrease background color addition by 4 (white) 0x101990, # B5 F4 - decrease background color addition by 4 (white) ], "Fire 3": [ 0x1019FA, # B0 9F - set background color addition to 31 (red) 0x101A1C, # B5 94 - decrease background color addition by 4 (red) ], "Sleep": [ 0x101A23, # AF E0 - set background color subtraction to 0 (black) 0x101A29, # B6 E1 - increase background color subtraction by 1 (black) 0x101A33, # B6 F1 - decrease background color subtraction by 1 (black) ], "7-Flush": [ 0x101B43, # AF E0 - set background color subtraction to 0 (black) 0x101B47, # B6 61 - increase background color subtraction by 1 (red) 0x101B4D, # B6 51 - decrease background color subtraction by 1 (magenta) 0x101B53, # B6 81 - increase background color subtraction by 1 (cyan) 0x101B59, # B6 31 - decrease background color subtraction by 1 (yellow) 0x101B5F, # B6 41 - increase background color subtraction by 1 (magenta) 0x101B65, # B6 91 - decrease background color subtraction by 1 (cyan) 0x101B6B, # B6 51 - decrease background color subtraction by 1 (magenta) ], "H-Bomb": [ 0x101BC5, # B0 E0 - set background color addition to 0 (white) 0x101BC9, # B5 E1 - increase background color addition by 1 (white) 0x101C13, # B5 F1 - decrease background color addition by 1 (white) ], "Revenger": [ 0x101C62, # AF E0 - set background color subtraction to 0 (black) 0x101C66, # B6 81 - increase background color subtraction by 1 (cyan) 0x101C6C, # B6 41 - increase background color subtraction by 1 (magenta) 0x101C72, # B6 91 - decrease background color subtraction by 1 (cyan) 0x101C78, # B6 21 - increase background color subtraction by 1 (yellow) 0x101C7E, # B6 51 - decrease background color subtraction by 1 (magenta) 0x101C84, # B6 81 - increase background color subtraction by 1 (cyan) 0x101C86, # B6 31 - decrease background color subtraction by 1 (yellow) 0x101C8C, # B6 91 - decrease background color subtraction by 1 (cyan) ], "Phantasm": [ 0x101DFD, # AF E0 - set background color subtraction to 0 (black) 0x101E03, # B6 E1 - increase background color subtraction by 1 (black) 0x101E07, # B0 FF - set background color addition to 31 (white) 0x101E0D, # B5 F4 - decrease background color addition by 4 (white) 0x101E15, # B6 E2 - increase background color subtraction by 2 (black) 0x101E1F, # B0 FF - set background color addition to 31 (white) 0x101E27, # B5 F4 - decrease background color addition by 4 (white) 0x101E2F, # B6 E2 - increase background color subtraction by 2 (black) 0x101E3B, # B6 F1 - decrease background color subtraction by 1 (black) ], "TigerBreak": [ 0x10240D, # B0 FF - set background color addition to 31 (white) 0x102411, # B5 F2 - decrease background color addition by 2 (white) 0x102416, # B5 F2 - decrease background color addition by 2 (white) ], "Metamorph": [ 0x102595, # AF E0 - set background color subtraction to 0 (black) 0x102599, # B6 61 - increase background color subtraction by 1 (red) 0x1025AF, # B6 71 - decrease background color subtraction by 1 (red) ], "Cat Rain": [ 0x102677, # B0 FF - set background color addition to 31 (white) 0x10267B, # B5 F1 - decrease background color addition by 1 (white) ], "Charm": [ 0x1026EE, # B0 FF - set background color addition to 31 (white) 0x1026FB, # B5 F1 - decrease background color addition by 1 (white) ], "Mirager": [ 0x102791, # B0 FF - set background color addition to 31 (white) 0x102795, # B5 F2 - decrease background color addition by 2 (white) ], "SabreSoul": [ 0x1027D3, # B0 FF - set background color addition to 31 (white) 0x1027DA, # B5 F2 - decrease background color addition by 2 (white) ], "Back Blade": [ 0x1028D3, # AF FF - set background color subtraction to 31 (black) 0x1028DF, # B6 F4 - decrease background color subtraction by 4 (black) ], "RoyalShock": [ 0x102967, # B0 FF - set background color addition to 31 (white) 0x10296B, # B5 F2 - decrease background color addition by 2 (white) 0x102973, # B5 F2 - decrease background color addition by 2 (white) ], "Overcast": [ 0x102C3A, # AF E0 - set background color subtraction to 0 (black) 0x102C55, # B6 E1 - increase background color subtraction by 1 (black) 0x102C8D, # B6 F1 - decrease background color subtraction by 1 (black) 0x102C91, # B6 F1 - decrease background color subtraction by 1 (black) ], "Disaster": [ 0x102CEE, # AF E0 - set background color subtraction to 0 (black) 0x102CF2, # B6 E1 - increase background color subtraction by 1 (black) 0x102D19, # B6 F1 - decrease background color subtraction by 1 (black) ], "ForceField": [ 0x102D3A, # B0 E0 - set background color addition to 0 (white) 0x102D48, # B5 E1 - increase background color addition by 1 (white) 0x102D64, # B5 F1 - decrease background color addition by 1 (white) ], "Terra/Tritoch Lightning": [ 0x102E05, # B0 E0 - set background color addition to 0 (white) 0x102E09, # B5 81 - increase background color addition by 1 (red) 0x102E24, # B5 61 - increase background color addition by 1 (cyan) ], "S. Cross": [ 0x102EDA, # AF E0 - set background color subtraction to 0 (black) 0x102EDE, # B6 E2 - increase background color subtraction by 2 (black) 0x102FA8, # B6 F2 - decrease background color subtraction by 2 (black) 0x102FB1, # B0 E0 - set background color addition to 0 (white) 0x102FBE, # B5 E2 - increase background color addition by 2 (white) 0x102FD9, # B5 F2 - decrease background color addition by 2 (white) ], "Mind Blast": [ 0x102FED, # B0 E0 - set background color addition to 0 (white) 0x102FF1, # B5 81 - increase background color addition by 1 (red) 0x102FF7, # B5 91 - decrease background color addition by 1 (red) 0x102FF9, # B5 21 - increase background color addition by 1 (blue) 0x102FFF, # B5 31 - decrease background color addition by 1 (blue) 0x103001, # B5 C1 - increase background color addition by 1 (yellow) 0x103007, # B5 91 - decrease background color addition by 1 (red) 0x10300D, # B5 51 - decrease background color addition by 1 (green) 0x103015, # B5 E2 - increase background color addition by 2 (white) 0x10301F, # B5 F1 - decrease background color addition by 1 (white) ], "Flare Star": [ 0x1030F5, # B0 E0 - set background color addition to 0 (white) 0x103106, # B5 81 - increase background color addition by 1 (red) 0x10310D, # B5 E2 - increase background color addition by 2 (white) 0x103123, # B5 71 - decrease background color addition by 1 (cyan) 0x10312E, # B5 91 - decrease background color addition by 1 (red) ], "Quasar": [ 0x1031D2, # AF E0 - set background color subtraction to 0 (black) 0x1031D6, # B6 E1 - increase background color subtraction by 1 (black) 0x1031FA, # B6 F1 - decrease background color subtraction by 1 (black) ], "R.Polarity": [ 0x10328B, # B0 FF - set background color addition to 31 (white) 0x103292, # B5 F1 - decrease background color addition by 1 (white) ], "Rippler": [ 0x1033C6, # B0 FF - set background color addition to 31 (white) 0x1033CA, # B5 F1 - decrease background color addition by 1 (white) ], "Step Mine": [ 0x1034D9, # B0 FF - set background color addition to 31 (white) 0x1034E0, # B5 F4 - decrease background color addition by 4 (white) ], "L.5 Doom": [ 0x1035E6, # B0 FF - set background color addition to 31 (white) 0x1035F6, # B5 F4 - decrease background color addition by 4 (white) ], "Megazerk": [ 0x103757, # B0 80 - set background color addition to 0 (red) 0x103761, # B5 82 - increase background color addition by 2 (red) 0x10378F, # B5 92 - decrease background color addition by 2 (red) 0x103795, # B5 92 - decrease background color addition by 2 (red) 0x10379B, # B5 92 - decrease background color addition by 2 (red) 0x1037A1, # B5 92 - decrease background color addition by 2 (red) 0x1037A7, # B5 92 - decrease background color addition by 2 (red) 0x1037AD, # B5 92 - decrease background color addition by 2 (red) 0x1037B3, # B5 92 - decrease background color addition by 2 (red) 0x1037B9, # B5 92 - decrease background color addition by 2 (red) 0x1037C0, # B5 92 - decrease background color addition by 2 (red) ], "Schiller": [ 0x103819, # B0 FF - set background color addition to 31 (white) 0x10381D, # B5 F4 - decrease background color addition by 4 (white) ], "WallChange": [ 0x10399E, # B0 FF - set background color addition to 31 (white) 0x1039A3, # B5 F2 - decrease background color addition by 2 (white) 0x1039A9, # B5 F2 - decrease background color addition by 2 (white) 0x1039AF, # B5 F2 - decrease background color addition by 2 (white) 0x1039B5, # B5 F2 - decrease background color addition by 2 (white) 0x1039BB, # B5 F2 - decrease background color addition by 2 (white) 0x1039C1, # B5 F2 - decrease background color addition by 2 (white) 0x1039C7, # B5 F2 - decrease background color addition by 2 (white) 0x1039CD, # B5 F2 - decrease background color addition by 2 (white) 0x1039D4, # B5 F2 - decrease background color addition by 2 (white) ], "Ultima": [ 0x1056CB, # AF 60 - set background color subtraction to 0 (red) 0x1056CF, # B6 C2 - increase background color subtraction by 2 (blue) 0x1056ED, # B0 FF - set background color addition to 31 (white) 0x1056F5, # B5 F1 - decrease background color addition by 1 (white) ], "Bolt 3": [ # Also Giga Volt 0x10588E, # B0 FF - set background color addition to 31 (white) 0x105893, # B5 F4 - decrease background color addition by 4 (white) 0x105896, # B5 F4 - decrease background color addition by 4 (white) 0x105899, # B5 F4 - decrease background color addition by 4 (white) 0x10589C, # B5 F4 - decrease background color addition by 4 (white) 0x1058A1, # B5 F4 - decrease background color addition by 4 (white) 0x1058A6, # B5 F4 - decrease background color addition by 4 (white) 0x1058AB, # B5 F4 - decrease background color addition by 4 (white) 0x1058B0, # B5 F4 - decrease background color addition by 4 (white) ], "X-Zone": [ 0x105A5D, # B0 FF - set background color addition to 31 (white) 0x105A6A, # B5 F2 - decrease background color addition by 2 (white) 0x105A79, # B5 F2 - decrease background color addition by 2 (white) ], "Dispel": [ 0x105DC2, # B0 FF - set background color addition to 31 (white) 0x105DC9, # B5 F1 - decrease background color addition by 1 (white) 0x105DD2, # B5 F1 - decrease background color addition by 1 (white) 0x105DDB, # B5 F1 - decrease background color addition by 1 (white) 0x105DE4, # B5 F1 - decrease background color addition by 1 (white) 0x105DED, # B5 F1 - decrease background color addition by 1 (white) ], "Muddle": [ # Also L.3 Muddle, Confusion 0x1060EA, # B0 FF - set background color addition to 31 (white) 0x1060EE, # B5 F1 - decrease background color addition by 1 (white) ], "Shock": [ 0x1068BE, # B0 FF - set background color addition to 31 (white) 0x1068D0, # B5 F1 - decrease background color addition by 1 (white) ], "Bum Rush": [ 0x106C3E, # B0 E0 - set background color addition to 0 (white) 0x106C47, # B0 E0 - set background color addition to 0 (white) 0x106C53, # B0 E0 - set background color addition to 0 (white) 0x106C7E, # B0 FF - set background color addition to 31 (white) 0x106C87, # B0 E0 - set background color addition to 0 (white) 0x106C95, # B0 FF - set background color addition to 31 (white) 0x106C9E, # B0 E0 - set background color addition to 0 (white) ], "Stunner": [ 0x1071BA, # B0 20 - set background color addition to 0 (blue) 0x1071C1, # B5 24 - increase background color addition by 4 (blue) 0x1071CA, # B5 24 - increase background color addition by 4 (blue) 0x1071D5, # B5 24 - increase background color addition by 4 (blue) 0x1071DE, # B5 24 - increase background color addition by 4 (blue) 0x1071E9, # B5 24 - increase background color addition by 4 (blue) 0x1071F2, # B5 24 - increase background color addition by 4 (blue) 0x1071FD, # B5 24 - increase background color addition by 4 (blue) 0x107206, # B5 24 - increase background color addition by 4 (blue) 0x107211, # B5 24 - increase background color addition by 4 (blue) 0x10721A, # B5 24 - increase background color addition by 4 (blue) 0x10725A, # B5 32 - decrease background color addition by 2 (blue) ], "Quadra Slam": [ # Also Quadra Slice 0x1073DC, # B0 FF - set background color addition to 31 (white) 0x1073EE, # B5 F2 - decrease background color addition by 2 (white) 0x1073F3, # B5 F2 - decrease background color addition by 2 (white) 0x107402, # B0 5F - set background color addition to 31 (green) 0x107424, # B5 54 - decrease background color addition by 4 (green) 0x107429, # B5 54 - decrease background color addition by 4 (green) 0x107436, # B0 3F - set background color addition to 31 (blue) 0x107458, # B5 34 - decrease background color addition by 4 (blue) 0x10745D, # B5 34 - decrease background color addition by 4 (blue) 0x107490, # B0 9F - set background color addition to 31 (red) 0x1074B2, # B5 94 - decrease background color addition by 4 (red) 0x1074B7, # B5 94 - decrease background color addition by 4 (red) ], "Slash": [ 0x1074F4, # B0 FF - set background color addition to 31 (white) 0x1074FD, # B5 F2 - decrease background color addition by 2 (white) 0x107507, # B5 F2 - decrease background color addition by 2 (white) ], "Flash": [ 0x107850, # B0 FF - set background color addition to 31 (white) 0x10785C, # B5 F1 - decrease background color addition by 1 (white) ] }

58.428152

133

0.630546

0

14,428

0.724152

65ffed323033ff0ac5225d3d784dead8adf418b4

2,643

py

Python

Jumpscale/tools/capacity/reality_parser.py

threefoldtech/JumpscaleX

5fb073a82aeb0e66fc7d9660c45a1e31bc094bfa

[ "Apache-2.0" ]

2

2019-05-09T07:21:25.000Z

2019-08-05T06:37:53.000Z

Jumpscale/tools/capacity/reality_parser.py

threefoldtech/JumpscaleX

5fb073a82aeb0e66fc7d9660c45a1e31bc094bfa

[ "Apache-2.0" ]

664

2018-12-19T12:43:44.000Z

2019-08-23T04:24:42.000Z

Jumpscale/tools/capacity/reality_parser.py

threefoldtech/jumpscale10

5fb073a82aeb0e66fc7d9660c45a1e31bc094bfa

[ "Apache-2.0" ]

7

2019-05-03T07:14:37.000Z

2019-08-05T12:36:52.000Z

""" this module contain the logic of parsing the actual usage of the ressource unit of a zero-os node """ from .units import GiB from sal_zos.disks.Disks import StorageType class RealityParser: def __init__(self): self._ressources = {"mru": 0.0, "cru": 0.0, "hru": 0.0, "sru": 0.0} def get_report(self, disks, storage_pools, total_cpu_nr, used_cpu, used_memory): self._ressources["mru"] = _parse_memory(used_memory) self._ressources["cru"] = _parse_cpu(total_cpu_nr, used_cpu) storage = _parse_storage(disks, storage_pools) self._ressources["sru"] = storage["sru"] self._ressources["hru"] = storage["hru"] return Report(**self._ressources) class Report: def __init__(self, cru, mru, hru, sru): self._cru = round(cru, 2) self._mru = round(mru, 2) self._hru = round(hru, 2) self._sru = round(sru, 2) @property def CRU(self): return self._cru @property def MRU(self): return self._mru @property def SRU(self): return self._sru @property def HRU(self): return self._hru def __repr__(self): return str(dict(cru=self.CRU, mru=self.MRU, hru=self.HRU, sru=self.SRU)) __str__ = __repr__ def _parse_storage(disks, storage_pools): disk_mapping = {} for disk in disks: for part in disk.partitions: if part.devicename not in disk_mapping: disk_mapping[part.devicename] = disk.type ressoures = {"sru": 0, "hru": 0} for sp in storage_pools: if len(sp.devices) <= 0: continue if sp.mountpoint == "/mnt/storagepools/sp_zos-cache": continue disk_type = disk_mapping[sp.devices[0]] size = sp.fsinfo["data"]["used"] if disk_type in [StorageType.HDD, StorageType.ARCHIVE]: ressoures["hru"] += size / GiB elif disk_type in [StorageType.SSD, StorageType.NVME]: ressoures["sru"] += size / GiB else: raise ValueError("disk type %s is not valid" % disk.type.name) return ressoures def _parse_cpu(total_cpu_nr, used_cpu): # self._node.client.aggregator.query("machine.CPU.percent") cpu_percentages = [value["current"]["3600"]["avg"] for value in used_cpu.values()] return (total_cpu_nr * sum(cpu_percentages)) / 100 def _parse_memory(used_memory): """ convert the used memory in bytes to ressource units :param used_memory: amount of used memory in bytes :type used_memory: float :return: number of MRU :rtype: float """ return used_memory / GiB

26.69697

97

0.626182

1,091

0.412788

0

212

0.080212

0

523

0.197881

5a01dafbd8cdef4d174904ccd475a2627ada858d

3,314

py

Python

fsem/similarity_measures/jaro.py

sajith-rahim/fs-em

2e8dde8b5f36ee1e1dfc5407611ec2fb91630c2a

[ "BSD-3-Clause" ]

null

fsem/similarity_measures/jaro.py

sajith-rahim/fs-em

2e8dde8b5f36ee1e1dfc5407611ec2fb91630c2a

[ "BSD-3-Clause" ]

null

fsem/similarity_measures/jaro.py

sajith-rahim/fs-em

2e8dde8b5f36ee1e1dfc5407611ec2fb91630c2a

[ "BSD-3-Clause" ]

null

import math __all__ = ['get_jaro_distance'] __author__ = 'Jean-Bernard Ratte - jean.bernard.ratte@unary.ca' """ Find the Jaro Winkler Distance which indicates the similarity score between two Strings. The Jaro measure is the weighted sum of percentage of matched characters from each file and transposed characters. Winkler increased this measure for matching initial characters. This implementation is based on the Jaro Winkler similarity algorithm from http://en.wikipedia.org/wiki/Jaro%E2%80%93Winkler_distance This Python implementation is based on the Apache StringUtils implementation from http://commons.apache.org/proper/commons-lang/apidocs/src-html/org/apache/commons/lang3/StringUtils.html#line.7141 """ def get_jaro_distance(first, second, winkler=True, winkler_ajustment=True, scaling=0.1): """ :param first: word to calculate distance for :param second: word to calculate distance with :param winkler: same as winkler_ajustment :param winkler_ajustment: add an adjustment factor to the Jaro of the distance :param scaling: scaling factor for the Winkler adjustment :return: Jaro distance adjusted (or not) """ if not first or not second: raise JaroDistanceException("Cannot calculate distance from NoneType ({0}, {1})".format( first.__class__.__name__, second.__class__.__name__)) jaro = _score(first, second) cl = min(len(_get_prefix(first, second)), 4) if all([winkler, winkler_ajustment]): # 0.1 as scaling factor return round((jaro + (scaling * cl * (1.0 - jaro))) * 100.0) / 100.0 return jaro def _score(first, second): shorter, longer = first.lower(), second.lower() if len(first) > len(second): longer, shorter = shorter, longer m1 = _get_matching_characters(shorter, longer) m2 = _get_matching_characters(longer, shorter) if len(m1) == 0 or len(m2) == 0: return 0.0 return (float(len(m1)) / len(shorter) + float(len(m2)) / len(longer) + float(len(m1) - _transpositions(m1, m2)) / len(m1)) / 3.0 def _get_diff_index(first, second): if first == second: return -1 if not first or not second: return 0 max_len = min(len(first), len(second)) for i in range(0, max_len): if not first[i] == second[i]: return i return max_len def _get_prefix(first, second): if not first or not second: return "" index = _get_diff_index(first, second) if index == -1: return first elif index == 0: return "" else: return first[0:index] def _get_matching_characters(first, second): common = [] limit = math.floor(min(len(first), len(second)) / 2) for i, l in enumerate(first): left, right = int(max(0, i - limit)), int(min(i + limit + 1, len(second))) if l in second[left:right]: common.append(l) second = second[0:second.index(l)] + '*' + second[second.index(l) + 1:] return ''.join(common) def _transpositions(first, second): return math.floor(len([(f, s) for f, s in zip(first, second) if not f == s]) / 2.0) class JaroDistanceException(Exception): def __init__(self, message): super(Exception, self).__init__(message)

31.561905

118

0.658117

125

0.037719

0

1,130

0.340978

5a0258dc0630fde008fae59e8ca2f2322000aca2

732

py

Python

UnitTests/FullAtomModel/PDB2Coords/test.py

dendisuhubdy/TorchProteinLibrary

89f0f6c311658b9313484cd92804682a251b1b97

[ "MIT" ]

null

UnitTests/FullAtomModel/PDB2Coords/test.py

dendisuhubdy/TorchProteinLibrary

89f0f6c311658b9313484cd92804682a251b1b97

[ "MIT" ]

null

UnitTests/FullAtomModel/PDB2Coords/test.py

dendisuhubdy/TorchProteinLibrary

89f0f6c311658b9313484cd92804682a251b1b97

[ "MIT" ]

null

import sys import os import matplotlib.pylab as plt import numpy as np import mpl_toolkits.mplot3d.axes3d as p3 import seaborn as sea import torch from TorchProteinLibrary import FullAtomModel if __name__=='__main__': # p2c = FullAtomModel.PDB2Coords.PDB2CoordsBiopython() p2c = FullAtomModel.PDB2CoordsUnordered() coords, res, anames, num_atoms = p2c(["f4TQ1_B.pdb"]) print (coords.size()) print (res.size()) print (anames.size()) print (num_atoms) coords = coords.numpy() coords = coords.reshape(int(coords.shape[1]/3), 3) fig = plt.figure() ax = fig.add_subplot(111, projection='3d') x = coords[:,0] y = coords[:,1] z = coords[:,2] ax.scatter(x,y,z) plt.show()

24.4

58

0.674863

0

81

0.110656

5a025cdbfc11bf834d39b1a16efe1582cdd5e329

4,306

py

Python

vae/scripts/gm_vae_fc_toy.py

ondrejba/vae

23f179637ca45c20d4e5f74e8c56b62f57554ef4

[ "MIT" ]

1

2019-11-23T20:51:58.000Z

vae/scripts/gm_vae_fc_toy.py

ondrejba/vae

23f179637ca45c20d4e5f74e8c56b62f57554ef4

[ "MIT" ]

null

vae/scripts/gm_vae_fc_toy.py

ondrejba/vae

23f179637ca45c20d4e5f74e8c56b62f57554ef4

[ "MIT" ]

1

2021-12-01T07:29:39.000Z

import argparse import collections import os import numpy as np import matplotlib.pyplot as plt from .. import toy_dataset from .. import gm_vae_fc def main(args): # gpu settings if args.gpus is not None: os.environ["CUDA_VISIBLE_DEVICES"] = args.gpus # generate and show dataset train_data = toy_dataset.get_dataset() print("training data:") plt.scatter(train_data[:, 0], train_data[:, 1]) plt.show() # build model num_clusters = 4 x_size = 2 w_size = 2 input_size = 2 model = gm_vae_fc.GM_VAE( input_size, [120, 120], [120, 120, input_size], [120], num_clusters, x_size, w_size, gm_vae_fc.GM_VAE.LossType.L2, args.weight_decay, args.learning_rate, clip_z_prior=args.clip_z_prior ) model.build_all() model.start_session(gpu_memory=args.gpu_memory_fraction) # train model epoch_size = len(train_data) // args.batch_size losses = collections.defaultdict(list) epoch_losses = collections.defaultdict(list) for train_step in range(args.num_training_steps): epoch_step = train_step % epoch_size if train_step > 0 and train_step % 1000 == 0: print("step {:d}".format(train_step)) if epoch_step == 0 and train_step > 0: losses["total"].append(np.mean(epoch_losses["total"])) losses["output"].append(np.mean(epoch_losses["output"])) losses["w KL divergence"].append(np.mean(epoch_losses["w KL divergence"])) losses["x KL divergence"].append(np.mean(epoch_losses["x KL divergence"])) losses["z KL divergence"].append(np.mean(epoch_losses["z KL divergence"])) losses["regularization"].append(np.mean(epoch_losses["regularization"])) epoch_losses = collections.defaultdict(list) samples = train_data[epoch_step * args.batch_size : (epoch_step + 1) * args.batch_size] loss, output_loss, w_kl_loss, x_kl_loss, z_kl_loss, reg_loss = model.train(samples) epoch_losses["total"].append(loss) epoch_losses["output"].append(output_loss) epoch_losses["w KL divergence"].append(w_kl_loss) epoch_losses["x KL divergence"].append(x_kl_loss) epoch_losses["z KL divergence"].append(z_kl_loss) epoch_losses["regularization"].append(reg_loss) # plot losses for key, value in losses.items(): plt.plot(list(range(1, len(value) + 1)), value, label=key) plt.legend() plt.xlabel("epoch") plt.show() x_encodings, w_encodings = model.encode(train_data, args.batch_size) y_decodings = model.predict_from_x_sample(x_encodings) # plot x print("encodings to x:") plt.scatter(x_encodings[:, 0], x_encodings[:, 1]) plt.show() # plot w print("encodings to w:") plt.scatter(w_encodings[:, 0], w_encodings[:, 1]) plt.show() # plot reconstruction print("reconstructions:") plt.scatter(y_decodings[:, 0], y_decodings[:, 1]) plt.show() # plot samples from mixtures w_samples = np.random.normal(0, 1, size=(100, w_size)) c_mu, c_sd = model.get_clusters(w_samples) print("cluster centroids:") for c_idx in range(num_clusters): plt.scatter(c_mu[:, c_idx, 0], c_mu[:, c_idx, 1], label="cluster {:d}".format(c_idx + 1)) plt.legend() plt.show() print("cluster samples:") for c_idx in range(num_clusters): x_samples = c_mu[:, c_idx, :] + np.random.normal(0, 1, size=(100, x_size)) * c_sd[:, c_idx, :] y_samples = model.predict_from_x_sample(x_samples) plt.scatter(y_samples[:, 0], y_samples[:, 1], label="cluster {:d}".format(c_idx + 1)) plt.legend() plt.show() model.stop_session() if __name__ == "__main__": parser = argparse.ArgumentParser() parser.add_argument("--num-training-steps", type=int, default=100000) parser.add_argument("--learning-rate", type=float, default=0.0001) parser.add_argument("--batch-size", type=int, default=50) parser.add_argument("--weight-decay", type=float, default=0.0) parser.add_argument("--clip-z-prior", type=float, default=1.4) parser.add_argument("--gpus", default=None) parser.add_argument("--gpu-memory-fraction", default=None, type=float) parsed = parser.parse_args() main(parsed)

31.202899

107

0.65699

0

691

0.160474

5a042bec8f40b0fa98c21fc7bd7c2df868d70903

520

py

Python

Python/354.py

JWang169/LintCodeJava

b75b06fa1551f5e4d8a559ef64e1ac29db79c083

[ "CNRI-Python" ]

1

2020-12-10T05:36:15.000Z

Python/354.py

JWang169/LintCodeJava

b75b06fa1551f5e4d8a559ef64e1ac29db79c083

[ "CNRI-Python" ]

null

Python/354.py

JWang169/LintCodeJava

b75b06fa1551f5e4d8a559ef64e1ac29db79c083

[ "CNRI-Python" ]

3

2020-04-06T05:55:08.000Z

2021-08-29T14:26:54.000Z

class Solution: def maxEnvelopes(self, envelopes: List[List[int]]) -> int: if not envelopes: return 0 pairs = sorted(envelopes, key=lambda x: (x[0], -x[1])) result = [] for pair in pairs: height = pair[1] if len(result) == 0 or height > result[-1]: result.append(height) else: index = bisect.bisect_left(result, height) result[index] = height return len(result)

34.666667

62

0.492308

503

0.967308

0

5a054c6f2f48cad9dc180b59f6e0034f5b144f73

331

py

Python

codes/day06/03.py

Youngfellows/HPyBaseCode

94d11872795d85b8c4387b650e82edcd20da0667

[ "Apache-2.0" ]

null

codes/day06/03.py

Youngfellows/HPyBaseCode

94d11872795d85b8c4387b650e82edcd20da0667

[ "Apache-2.0" ]

null

codes/day06/03.py

Youngfellows/HPyBaseCode

94d11872795d85b8c4387b650e82edcd20da0667

[ "Apache-2.0" ]

null

class Dog: def __init__(self, newColor): self.color = newColor def bark(self): print("---旺旺叫----") def printColor(self): print("颜色为：%s"%self.color) def test(AAA): AAA.printColor() wangcai = Dog("白") #wangcai.printColor() xiaoqiang = Dog("黑") #xiaoqiang.printColor() test(wangcai)

15.045455

34

0.592145

203

0.581662

0

88

0.252149

5a05e2efcbe249cfc654b1e6e98561ecca3c15b5

1,158

py

Python

LC_problems/699.py

Howardhuang98/Blog

cf58638d6d0bbf55b95fe08e43798e7dd14219ac

[ "MIT" ]

null

LC_problems/699.py

Howardhuang98/Blog

cf58638d6d0bbf55b95fe08e43798e7dd14219ac

[ "MIT" ]

null

LC_problems/699.py

Howardhuang98/Blog

cf58638d6d0bbf55b95fe08e43798e7dd14219ac

[ "MIT" ]

null

#!/usr/bin/env python # -*- encoding: utf-8 -*- """ @File : 699.py @Contact : huanghoward@foxmail.com @Modify Time : 2022/5/26 17:22 ------------ """ from typing import List class Solution: def fallingSquares(self, positions: List[List[int]]) -> List[int]: height = [p[1] for p in positions] for i, (left, l) in enumerate(positions): if i == 0: continue else: for j in range(i): # left,left+l # positions[j][0],positions[j][0] + positions[j][1] if not left >= positions[j][0] + positions[j][1] and not left + l <= positions[j][0]: height[i] = max(height[i], height[j] + l) ans = [] for i, h in enumerate(height): if i == 0: ans.append(h) continue else: if h < ans[-1]: ans.append(ans[-1]) else: ans.append(h) return ans if __name__ == '__main__': s = Solution() print(s.fallingSquares([[9, 6], [2, 2], [2, 6]]))

28.95

105

0.443005

857

0.740069

0

243

0.209845

5a05e7be3fed210c95055f9564a15535552003ac

5,150

py

Python

plastid/test/functional/test_metagene.py

joshuagryphon/plastid

e63a818e33766b01d84b3ac9bc9f55e6a1ece42f

[ "BSD-3-Clause" ]

31

2016-04-05T09:58:29.000Z

2022-01-18T11:58:30.000Z

plastid/test/functional/test_metagene.py

joshuagryphon/plastid

e63a818e33766b01d84b3ac9bc9f55e6a1ece42f

[ "BSD-3-Clause" ]

49

2015-09-15T19:50:13.000Z

2022-01-06T18:17:35.000Z

plastid/test/functional/test_metagene.py

joshuagryphon/plastid

e63a818e33766b01d84b3ac9bc9f55e6a1ece42f

[ "BSD-3-Clause" ]

14

2017-02-08T09:38:57.000Z

2020-09-16T02:32:46.000Z

#!/usr/bin/env python """Test suite for :py:mod:`plastid.bin.metagene`""" import tempfile import os from pkg_resources import resource_filename, cleanup_resources from nose.plugins.attrib import attr from plastid.test.functional.base import execute_helper from plastid.test.ref_files import ( RPATH, REF_FILES, COUNT_OPTIONS, ANNOTATION_OPTIONS, MASK_OPTIONS, ) from plastid.bin.test_table_equality import main as table_test from plastid.bin.metagene import main from plastid.util.services.decorators import catch_stderr #=============================================================================== # INDEX: global constants used by tests #=============================================================================== TEST_INFO = { "test_method": catch_stderr()(main), "module_name": "plastid.bin.metagene", "ref_file_path": resource_filename("plastid", "test/data/command_line"), "temp_file_path": tempfile.mkdtemp(prefix="metagene"), } _basename = os.path.join(TEST_INFO["temp_file_path"], "test_metagene") #=============================================================================== # INDEX: tests #=============================================================================== tests = [ # test generate cds start ( "generate %s_cds_start --downstream 100 %s %s" % (_basename, ANNOTATION_OPTIONS, MASK_OPTIONS), [REF_FILES["yeast_metagene_cds_start"], REF_FILES["yeast_metagene_cds_start_bed"]], [ _basename + "_cds_start_rois.txt", _basename + "_cds_start_rois.bed", ], ["", "--no_header"] ), # test generate cds stop ( "generate %s_cds_stop --upstream 100 --landmark cds_stop %s %s" % (_basename, ANNOTATION_OPTIONS, MASK_OPTIONS), [ REF_FILES["yeast_metagene_cds_stop"], REF_FILES["yeast_metagene_cds_stop_bed"], ], [ _basename + "_cds_stop_rois.txt", _basename + "_cds_stop_rois.bed", ], ["", "--no_header"] ), # test count cds start with --norm_region ( "count %s %s_cds_start --keep --norm_region 70 150 %s" % (REF_FILES["yeast_metagene_cds_start"], _basename, COUNT_OPTIONS), [ REF_FILES["yeast_metagene_cds_start_profile"], REF_FILES["yeast_metagene_cds_start_normcounts"], REF_FILES["yeast_metagene_cds_start_rawcounts"], ], [ _basename + "_cds_start_metagene_profile.txt", _basename + "_cds_start_normcounts.txt.gz", _basename + "_cds_start_rawcounts.txt.gz" ], ["", "--no_header", "--no_header"] ), # test count cds stop with --norm_region ( "count %s %s_cds_stop --keep --norm_region 0 80 %s" % (REF_FILES["yeast_metagene_cds_stop"], _basename, COUNT_OPTIONS), [ REF_FILES["yeast_metagene_cds_stop_profile"], REF_FILES["yeast_metagene_cds_stop_normcounts"], REF_FILES["yeast_metagene_cds_stop_rawcounts"], ], [ _basename + "_cds_stop_metagene_profile.txt", _basename + "_cds_stop_normcounts.txt.gz", _basename + "_cds_stop_rawcounts.txt.gz" ], ["", "--no_header", "--no_header"] ), # test count cds start, using --normalize_over ( "count %s %s_cds_start --keep --normalize_over 20 100 %s" % (REF_FILES["yeast_metagene_cds_start"], _basename, COUNT_OPTIONS), [ REF_FILES["yeast_metagene_cds_start_profile"], REF_FILES["yeast_metagene_cds_start_normcounts"], REF_FILES["yeast_metagene_cds_start_rawcounts"], ], [ _basename + "_cds_start_metagene_profile.txt", _basename + "_cds_start_normcounts.txt.gz", _basename + "_cds_start_rawcounts.txt.gz" ], ["", "--no_header", "--no_header"] ), # test count cds stop, using --normalize_over ( "count %s %s_cds_stop --keep --normalize_over '-100' '-20' %s" % (REF_FILES["yeast_metagene_cds_stop"], _basename, COUNT_OPTIONS), [ REF_FILES["yeast_metagene_cds_stop_profile"], REF_FILES["yeast_metagene_cds_stop_normcounts"], REF_FILES["yeast_metagene_cds_stop_rawcounts"], ], [ _basename + "_cds_stop_metagene_profile.txt", _basename + "_cds_stop_normcounts.txt.gz", _basename + "_cds_stop_rawcounts.txt.gz" ], ["", "--no_header", "--no_header"] ), ] """Functional tests of :py:mod:`plastid.bin.metagene`. Tests are specified as tuples of: 1. Command-line style arguments to pass to :py:func:`main` 2. A list of reference files that output should be compared against 3. A list of output files created by running :py:func:`main` with the arguments provided in (1) 4. A list of strings specifying how equality should be evaluated """ #=============================================================================== # INDEX: test functions #=============================================================================== @attr(test="functional") @attr(speed="slow") def do_test(): for x in execute_helper(TEST_INFO, tests): yield x

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0.594175

0

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122

0.023689

0

2,981

0.578835

5a0619271eef494f524dc719a9ba4f63c1373613

4,967

py

Python

tests/router/test_router.py

macneiln/ombott

f18f6e0e639f20efb63b137edbab8c8b3871d354

[ "MIT" ]

null

tests/router/test_router.py

macneiln/ombott

f18f6e0e639f20efb63b137edbab8c8b3871d354

[ "MIT" ]

null

tests/router/test_router.py

macneiln/ombott

f18f6e0e639f20efb63b137edbab8c8b3871d354

[ "MIT" ]

null

import pytest from ombott.router import RadiRouter, Route from ombott.router.errors import RouteMethodError route_meth_handler_path = [ ('/foo/bar', 'GET', 'foo_bar:get', '/foo/bar'), ('/foo/bar', 'POST', 'foo_bar:post', '/foo/bar/'), ('/foo/bar', ['PUT', 'PATCH'], 'foo_bar:put,patch', 'foo/bar'), ('foo@/named/foo', ['PUT', 'PATCH'], 'foo@:put,patch', '/named/foo'), ('bar@/named/bar', ['PUT', 'PATCH'], 'bar@:put,patch', '/named/bar'), ('/foo/bar1', 'GET', 404, ['/foo/ba', '/foo/ba12']), ('/foo/bar1', 'POST', 405, '/foo/bar1:PATCH'), ('/foo/<re(pro.+?(?=l))>le/:user/bar', 'GET', dict(user='tom'), '/foo/profile/tom/bar'), ('/re/{re(to.)}/bar', 'GET', 're:get', '/re/tom/bar'), ('/re/{:re(to.)}/bar', 'PUT', 're:put', '/re/tom/bar'), ('/re/{name:re(to.)}/bar', 'POST', dict(name='tom'), '/re/tom/bar'), ('/re/{name:re(to.)}/bar1', 'GET', dict(name='tos'), '/re/tos/bar1'), ('/re/{surname:re(to.)}/bar2', 'GET', dict(surname='tok'), '/re/tok/bar2/'), ('/path/{pth:path()}/end', 'GET', dict(pth='this/path/to'), '/path/this/path/to/end'), ('/path1/{pth:path()}end', 'GET', dict(pth='this/path/to-'), '/path1/this/path/to-end'), ] def expand_params(): ret = [] for it in route_meth_handler_path: rule, meth, handler, path = it name = None if '@' in rule: name, rule = rule.split('@', 1) if not isinstance(path, list): path = [path] for p in path: ret.append([name, rule, meth, handler, p]) return ret def make_router(): router = RadiRouter() for it in route_meth_handler_path: rule, meth, handler, path = it name = None if '@' in rule: name, rule = rule.split('@', 1) router.add(rule, meth, handler, name=name or None) return router def exist_rule_paths(): seen = set() ret = [] for it in expand_params(): name, rule, meth, handler, path = it print(name or '<no>', rule) pattern = RadiRouter.to_pattern(rule) if handler not in [404, 405] and pattern not in seen: ret.append([name, rule, path]) seen.add(pattern) return ret @pytest.fixture def fresh_router(): return make_router() @pytest.fixture(scope='class') def router(): return make_router() @pytest.fixture def routes(): return route_meth_handler_path[:] @pytest.fixture(params = expand_params()) def routes_iter(request): return request.param class TestRoutes: def test_routes(self, router, routes_iter): name, rule, meth, handler, path = routes_iter path, _, path_meth = path.partition(':') end_point, err404_405 = router.resolve(path, path_meth or meth) if end_point is None: assert handler in {404, 405} assert err404_405[0] == handler else: assert handler is not None route_meth, params, hooks = end_point assert route_meth.handler == handler if isinstance(meth, str): assert route_meth.name == meth else: assert route_meth.name == meth[0] if params: assert params == handler if name: assert router[name][meth] is route_meth def test_overwrite_error(): router = RadiRouter() route = '/foo/bar' def h(): pass router.add(route, ['GET', 'POST'], h) with pytest.raises(RouteMethodError) as exc_info: router.add(route, 'GET', h) assert route in str(exc_info.value) assert 'already registered' in str(exc_info.value) def test_str_repr(): router = RadiRouter() route = '/foo/bar' def h(): pass router.add(route, ['GET', 'POST'], h) end_point, err404_405 = router.resolve(route, 'GET') route_meth, *_ = end_point assert h.__qualname__ in str(route_meth) assert 'GET' in str(route_meth) assert h.__qualname__ in repr(route_meth) assert route in repr(route_meth) class TestRemove: @pytest.mark.parametrize( 'name, rule, path', exist_rule_paths() ) def test_remove_route(self, router: RadiRouter, name, rule, path): route = router[{rule}] assert route assert router.resolve(path) is route if name: assert router[name] is route router.remove(rule) assert router.resolve(path) is None assert router[{rule}] is None if name: assert router[name] is None route_meth, err = router.resolve(path, 'GET') assert err[0] == 404 def test_remove_method(fresh_router: RadiRouter): router = fresh_router route: Route = router.resolve('/foo/bar') assert route['GET'] route.remove_method('GET') assert 'GET' not in route.methods route_meth, err = router.resolve('/foo/bar', 'GET') assert err[0] == 405 assert router.resolve('/foo/bar')

29.742515

92

0.582444

1,385

0.27884

0

850

0.171129

0

934

0.188041

5a06baf447f7c7644ae324b314d4d848bee4ba67

12,225

py

Python

app_api/serializers.py

pkucsie/SIEPServer

00b0637eb8302135dfc772fccd18cd749a93e5c6

[ "Apache-2.0" ]

2

2021-02-12T10:02:42.000Z

2021-03-15T13:08:04.000Z

app_api/serializers.py

pkucsie/SIEPServer

00b0637eb8302135dfc772fccd18cd749a93e5c6

[ "Apache-2.0" ]

null

app_api/serializers.py

pkucsie/SIEPServer

00b0637eb8302135dfc772fccd18cd749a93e5c6

[ "Apache-2.0" ]

null

import datetime import time from utils import utils from rest_framework import serializers from rest_framework.relations import StringRelatedField from app_api.models import Album, Info, Order, Coupon, Integral, Notice, Lesson, Question, Cart, Setup, User, Bill, Address, Catalog, Log, \ ReadType, Teacher, Comment, \ Hot, Recharge, LabelFollow, Student, Navigation, Read, Article, History, Qa, ArticleType, UserNotice, Slider, \ UserLesson, Nav, LabelType, \ IntegralType, Label, Footer, CommonPathConfig, StudentType, LessonType, LessonHardType, Chapter, Term, QaType, \ RechargeAction, RechargePay, \ CouponRange, CouponStatus, OrderItem, OrderStatus, Consult, ReadChapterItem, ReadChapter, LogType, VipGuest, Judge, \ Organization, TaskTimeline, Project, Score, WXAdmin, WXUser class ConsultSerializer(serializers.ModelSerializer): class Meta: model = Consult fields = "__all__" class OrderStatusSerializer(serializers.ModelSerializer): class Meta: model = OrderStatus fields = ["text", "code"] class OrderItemSerializer(serializers.ModelSerializer): class Meta: model = OrderItem fields = "__all__" class OrderWaySerializer(serializers.ModelSerializer): class Meta: model = RechargePay fields = ["text", "code"] class OrderListSerializer(serializers.ModelSerializer): status = OrderStatusSerializer() way = OrderWaySerializer() list = OrderItemSerializer(many=True) class Meta: model = Order fields = "__all__" class OrderSerializer(serializers.ModelSerializer): class Meta: model = Order fields = "__all__" class OrderInfoSerializer(serializers.ModelSerializer): list = OrderItemSerializer(many=True) class Meta: model = Order fields = "__all__" class CouponRangeSerializer(serializers.ModelSerializer): class Meta: model = CouponRange fields = ["text", "code"] class CouponStatusSerializer(serializers.ModelSerializer): class Meta: model = CouponStatus fields = ["text", "code"] class CouponSerializer(serializers.ModelSerializer): range = CouponRangeSerializer() status = CouponStatusSerializer() starttime = serializers.DateTimeField(format="%Y.%m.%d") endtime = serializers.DateTimeField(format="%Y.%m.%d") class Meta: model = Coupon fields = "__all__" class IntegralSerializer(serializers.ModelSerializer): class Meta: model = Integral fields = "__all__" class UserNoticeSerializer(serializers.ModelSerializer): class Meta: model = UserNotice fields = "__all__" class NoticeSerializer(serializers.ModelSerializer): class Meta: model = Notice fields = "__all__" class LabelTypeHomeSerializer(serializers.ModelSerializer): class Meta: model = LabelType fields = ["code", "title"] class LabelTypeSerializer(serializers.ModelSerializer): text = serializers.CharField(source="title") class Meta: model = LabelType fields = ["code", "text"] class LessonTypeSerializer(serializers.ModelSerializer): class Meta: model = LessonType fields = ["code", "text"] class LabelSerializer(serializers.ModelSerializer): type = LabelTypeSerializer() class Meta: model = Label fields = "__all__" class LabelInnerLessonSerializer(serializers.ModelSerializer): class Meta: model = Label fields = ["title"] class LessonHardTypeSerializer(serializers.ModelSerializer): class Meta: model = LessonHardType fields = ["code", "text"] class TaskTimelineSerializer(serializers.ModelSerializer): class Meta: model = TaskTimeline fields = "__all__" class OrganizationSerializer(serializers.ModelSerializer): class Meta: model = Organization fields = "__all__" class VipGuestSerializer(serializers.ModelSerializer): class Meta: model = VipGuest fields = "__all__" class JudgeSerializer(serializers.ModelSerializer): class Meta: model = Judge fields = "__all__" class ScoreSerializer(serializers.ModelSerializer): class Meta: model = Score fields = "__all__" class ProjectSerializer(serializers.ModelSerializer): class Meta: model = Project fields = "__all__" class TeacherSerializer(serializers.ModelSerializer): class Meta: model = Teacher fields = "__all__" class LessonSerializer(serializers.ModelSerializer): category = LabelTypeSerializer() type = LessonTypeSerializer() labels = StringRelatedField(many=True) teacher = TeacherSerializer() class Meta: model = Lesson fields = "__all__" class LessonInfoSerializer(serializers.ModelSerializer): category = LabelTypeSerializer() type = LessonTypeSerializer() labels = StringRelatedField(many=True) hard = LessonHardTypeSerializer() teacher = TeacherSerializer() class Meta: model = Lesson fields = "__all__" class TermSerializer(serializers.ModelSerializer): class Meta: model = Term fields = "__all__" class ChapterSerializer(serializers.ModelSerializer): term = TermSerializer(many=True) class Meta: model = Chapter fields = "__all__" class QuestionSerializer(serializers.ModelSerializer): class Meta: model = Question fields = "__all__" class CartSerializer(serializers.ModelSerializer): class Meta: model = Cart fields = "__all__" class UserSerializer(serializers.ModelSerializer): class Meta: model = User fields = "__all__" class AddressSerializer(serializers.ModelSerializer): class Meta: model = Address fields = "__all__" class CatalogSerializer(serializers.ModelSerializer): class Meta: model = Catalog fields = "__all__" class LogTypeSerializer(serializers.ModelSerializer): class Meta: model = LogType fields = ["text", "code"] class LogSerializer(serializers.ModelSerializer): type = LogTypeSerializer() class Meta: model = Log fields = "__all__" class ReadTypeSerializer(serializers.ModelSerializer): class Meta: model = ReadType fields = "__all__" class CommentSerializer(serializers.ModelSerializer): class Meta: model = Comment fields = "__all__" class HotSerializer(serializers.ModelSerializer): class Meta: model = Hot fields = "__all__" class RechargeActionSerializer(serializers.ModelSerializer): class Meta: model = RechargeAction fields = ["text", "code"] class RechargePaySerializer(serializers.ModelSerializer): action = RechargeActionSerializer class Meta: model = RechargePay fields = ["text", "code"] class RechargeListSerializer(serializers.ModelSerializer): action = RechargeActionSerializer() way = RechargePaySerializer() class Meta: model = Recharge fields = "__all__" class BillSerializer(serializers.ModelSerializer): way = RechargePaySerializer() orderno = serializers.SerializerMethodField() class Meta: model = Bill fields = "__all__" @staticmethod def get_orderno(obj): year = datetime.datetime.now().year month = datetime.datetime.now().month day = datetime.datetime.now().day if month < 10: month = f'0{month}' if day < 10: day = f'0{day}' return f'{year}{month}{day}{int(time.time())}' class RechargeSerializer(serializers.ModelSerializer): class Meta: model = Recharge fields = "__all__" class LabelFollowSerializer(serializers.ModelSerializer): class Meta: model = LabelFollow fields = "__all__" class StudentTypeSerializer(serializers.ModelSerializer): class Meta: model = StudentType fields = ["code", "text"] class StudentSerializer(serializers.ModelSerializer): type = StudentTypeSerializer() class Meta: model = Student fields = "__all__" class NavigationSerializer(serializers.ModelSerializer): class Meta: model = Navigation fields = "__all__" class ReadChapterItemSerializer(serializers.ModelSerializer): class Meta: model = ReadChapterItem fields = "__all__" class ReadChapterSerializer(serializers.ModelSerializer): data = ReadChapterItemSerializer(source="chapter_item", many=True) class Meta: model = ReadChapter fields = "__all__" class ReadSerializer(serializers.ModelSerializer): author = TeacherSerializer() tryRead = serializers.SerializerMethodField() class Meta: model = Read fields = "__all__" @staticmethod def get_tryRead(obj): chapters = ReadChapter.objects.filter(read=obj).values_list("id", flat=True) chapter_items = ReadChapterItem.objects.filter(read_chapter_id__in=chapters, isTry=True).values_list("title", flat=True) return chapter_items class ReadInfoSerializer(serializers.ModelSerializer): author = TeacherSerializer() chapter = ReadChapterSerializer(many=True) class Meta: model = Read fields = "__all__" class ArticleSerializer(serializers.ModelSerializer): type = serializers.IntegerField(source="type.code") class Meta: model = Article fields = "__all__" class HistorySerializer(serializers.ModelSerializer): class Meta: model = History fields = "__all__" class QaTypeSerializer(serializers.ModelSerializer): class Meta: model = QaType fields = ["text", "code"] class QaSerializer(serializers.ModelSerializer): status = QaTypeSerializer(source="type") class Meta: model = Qa fields = "__all__" class ArticleTypeSerializer(serializers.ModelSerializer): class Meta: model = ArticleType fields = "__all__" class SliderSerializer(serializers.ModelSerializer): class Meta: model = Slider fields = "__all__" class UserLessonSerializer(serializers.ModelSerializer): type = LessonTypeSerializer() class Meta: model = UserLesson fields = "__all__" class NavSerializer(serializers.ModelSerializer): class Meta: model = Nav fields = "__all__" class IntegralTypeSerializer(serializers.ModelSerializer): class Meta: model = IntegralType fields = "__all__" class FooterSerializer(serializers.ModelSerializer): class Meta: model = Footer fields = "__all__" class CommonPathConfigSerializer(serializers.ModelSerializer): class Meta: model = CommonPathConfig fields = "__all__" class AlbumSerializer(serializers.ModelSerializer): class Meta: model = Album fields = "__all__" class InfoSerializer(serializers.ModelSerializer): class Meta: model = Info fields = "__all__" class SetupSerializer(serializers.ModelSerializer): class Meta: model = Setup fields = "__all__" class WxuserSerializer(serializers.ModelSerializer): def to_representation(self, instance): """Convert `username` to lowercase.""" ret = super().to_representation(instance) ret['USER_LOGIN_TIME'] = utils.get_agostr(ret['USER_LOGIN_TIME']) ret['USER_BIRTH'] = utils.get_age(ret['USER_BIRTH']) return ret class Meta: model = WXUser fields = "__all__" class WxuserFullSerializer(serializers.ModelSerializer): def to_representation(self, instance): """Convert `username` to lowercase.""" ret = super().to_representation(instance) ret['USER_BIRTH'] = utils.get_ymd(ret['USER_BIRTH']) return ret class Meta: model = WXUser fields = "__all__" class WxadminSerializer(serializers.ModelSerializer): class Meta: model = WXAdmin fields = "__all__"

23.41954

140

0.674683

11,203

0.916401

0

612

0.050061

0

954

0.078037

5a07b3f93f0df160b35b13e2ca081e2f2413ce44

718

py

Python

6_API/pytorch/configure.py

misoA/DeepCalendar

50cafc1e70f125f3b6b42cd88e1e9dd071676b49

[ "MIT" ]

null

6_API/pytorch/configure.py

misoA/DeepCalendar

50cafc1e70f125f3b6b42cd88e1e9dd071676b49

[ "MIT" ]

3

2019-01-14T06:59:24.000Z

2019-01-14T07:48:38.000Z

6_API/pytorch/configure.py

misoA/DeepCalendar

50cafc1e70f125f3b6b42cd88e1e9dd071676b49

[ "MIT" ]

5

2019-01-08T05:01:26.000Z

2021-05-17T23:34:51.000Z

# -*- coding: utf-8 -*- # This file is made to configure every file number at one place # Choose the place you are training at # AWS : 0, Own PC : 1 PC = 1 path_list = ["/jet/prs/workspace/", "."] url = path_list[PC] clothes = ['shirt', 'jeans', 'blazer', 'chino-pants', 'jacket', 'coat', 'hoody', 'training-pants', 't-shirt', 'polo-shirt', 'knit', 'slacks', 'sweat-shirt'] schedule = ['party', 'trip', 'sport', 'work', 'speech', 'daily', 'school', 'date'] weather = ['snow', 'sunny', 'cloudy', 'rain']

17.95

63

0.431755

0

371

0.516713

5a0835b17e7c0f765c8aa93d7341da5395fe71d2

32

py

Python

provider/__init__.py

depop/django-oauth2-provider

afcdef72747233dc0259a4bc068a8086ba7a69d3

[ "MIT" ]

1

2020-05-10T00:11:05.000Z

provider/__init__.py

depop/django-oauth2-provider

afcdef72747233dc0259a4bc068a8086ba7a69d3

[ "MIT" ]

1

2016-05-23T15:22:41.000Z

provider/__init__.py

depop/django-oauth2-provider

afcdef72747233dc0259a4bc068a8086ba7a69d3

[ "MIT" ]

null

__version__ = "0.2.7+depop.6.1"

16

31

0.65625

0

17

0.53125

5a0841fa1b97d80f5fc2c97be82b59ce57dfb2d4

7,381

py

Python

python/craftassist/voxel_models/subcomponent_classifier.py

kayburns/craftassist

07909493d320afc2c9ff428d0891bc3acd4dc68f

[ "MIT" ]

null

python/craftassist/voxel_models/subcomponent_classifier.py

kayburns/craftassist

07909493d320afc2c9ff428d0891bc3acd4dc68f

[ "MIT" ]

null

python/craftassist/voxel_models/subcomponent_classifier.py

kayburns/craftassist

07909493d320afc2c9ff428d0891bc3acd4dc68f

[ "MIT" ]

null

""" Copyright (c) Facebook, Inc. and its affiliates. """ import logging import queue from multiprocessing import Queue, Process import sys import os from mc_memory_nodes import InstSegNode, PropSegNode from heuristic_perception import all_nearby_objects from shapes import get_bounds VISION_DIR = os.path.dirname(os.path.realpath(__file__)) CRAFTASSIST_DIR = os.path.join(VISION_DIR, "../") SEMSEG_DIR = os.path.join(VISION_DIR, "semantic_segmentation/") sys.path.append(CRAFTASSIST_DIR) sys.path.append(SEMSEG_DIR) import build_utils as bu from semseg_models import SemSegWrapper # TODO all "subcomponent" operations are replaced with InstSeg class SubcomponentClassifierWrapper: def __init__(self, agent, model_path, vocab_path, perceive_freq=0): self.agent = agent self.memory = self.agent.memory self.perceive_freq = perceive_freq self.true_temp = 1 if model_path is not None: self.subcomponent_classifier = SubComponentClassifier( voxel_model_path=model_path, vocab_path=vocab_path, ) self.subcomponent_classifier.start() else: self.subcomponent_classifier = None def perceive(self, force=False): if self.perceive_freq == 0 and not force: return if self.perceive_freq > 0 and self.agent.count % self.perceive_freq != 0 and not force: return if self.subcomponent_classifier is None: return # TODO don't all_nearby_objects again, search in memory instead to_label = [] # add all blocks in marked areas for pos, radius in self.agent.areas_to_perceive: for obj in all_nearby_objects(self.agent.get_blocks, pos, radius): to_label.append(obj) # add all blocks near the agent for obj in all_nearby_objects(self.agent.get_blocks, self.agent.pos): to_label.append(obj) for obj in to_label: # (6, 69, 11) in [b[0] for b in obj] self.subcomponent_classifier.block_objs_q.put(obj) # everytime we try to retrieve as many recognition results as possible while not self.subcomponent_classifier.loc2labels_q.empty(): loc2labels, obj = self.subcomponent_classifier.loc2labels_q.get() # (6, 69, 11) in [b[0] for b in obj] loc2ids = dict(obj) label2blocks = {} def contaminated(blocks): """ Check if blocks are still consistent with the current world """ mx, Mx, my, My, mz, Mz = get_bounds(blocks) yzxb = self.agent.get_blocks(mx, Mx, my, My, mz, Mz) for b, _ in blocks: x, y, z = b if loc2ids[b][0] != yzxb[y - my, z - mz, x - mx, 0]: return True return False for loc, labels in loc2labels.items(): b = (loc, loc2ids[loc]) for l in labels: if l in label2blocks: label2blocks[l].append(b) else: label2blocks[l] = [b] labels_str = " ".join(list(label2blocks.keys())) if len(labels_str) == 1: self.agent.send_chat( "I found this in the scene: " + labels_str ) elif len(labels_str) > 1: self.agent.send_chat( "I found these in the scene: " + labels_str ) for l, blocks in label2blocks.items(): ## if the blocks are contaminated we just ignore if not contaminated(blocks): #locs = [loc for loc, idm in blocks] InstSegNode.create( self.memory, blocks, [l, 'semseg']) def update(self, label, blocks, house): pass #self.subcomponent_classifier.to_update_q.put((label, blocks, house)) class SubComponentClassifier(Process): """ A classifier class that calls a voxel model to output object tags. """ def __init__(self, voxel_model_path=None, vocab_path=None, true_temp=1): super().__init__() if voxel_model_path is not None: logging.info( "SubComponentClassifier using voxel_model_path={}".format(voxel_model_path) ) self.model = SemSegWrapper(voxel_model_path, vocab_path) else: raise Exception("specify a segmentation model") self.block_objs_q = Queue() # store block objects to be recognized self.loc2labels_q = Queue() # store loc2labels dicts to be retrieved by the agent #self.to_update_q = Queue() self.daemon = True def run(self): """ The main recognition loop of the classifier """ while True: # run forever #for _ in range(100): # print("If I print here, it solves the bug ¯\_(ツ)_/¯, priority thing?") tb = self.block_objs_q.get(block=True, timeout=None) loc2labels = self._watch_single_object(tb) for k in loc2labels.keys(): loc2labels[k].append("house") self.loc2labels_q.put((loc2labels, tb)) #try: # label, blocks, house = self.to_update_q.get_nowait() # self.update(label, blocks, house) #except queue.Empty: # pass def _watch_single_object(self, tuple_blocks, t=1): """ Input: a list of tuples, where each tuple is ((x, y, z), [bid, mid]). This list represents a block object. Output: a dict of (loc, [tag1, tag2, ..]) pairs for all non-air blocks. """ def get_tags(p): """ convert a list of tag indices to a list of tags """ return [self.model.tags[i][0] for i in p] def apply_offsets(cube_loc, offsets): """ Convert the cube location back to world location """ return (cube_loc[0] + offsets[0], cube_loc[1] + offsets[1], cube_loc[2] + offsets[2]) np_blocks, offsets = bu.blocks_list_to_npy(blocks=tuple_blocks, xyz=True) pred = self.model.segment_object(np_blocks, T=t) # convert prediction results to string tags return dict([(apply_offsets(loc, offsets), get_tags([p])) for loc, p in pred.items()]) def recognize(self, list_of_tuple_blocks): """ Multiple calls to _watch_single_object """ tags = dict() for tb in list_of_tuple_blocks: tags.update(self._watch_single_object(tb)) return tags def update(self, label, blocks, house): # changes can come in from adds or removals, if add, update house logging.info("Updated label {}".format(label)) if blocks[0][0][0] > 0: house += blocks blocks = [(xyz, (1, 0)) for xyz, _ in blocks] np_house, offsets = bu.blocks_list_to_npy(blocks=house, xyz=True) np_blocks, _ = bu.blocks_list_to_npy( blocks=blocks, xyz=False, offsets=offsets, shape=np_house.shape) # shape is still xyz bc of shape arg self.model.update(label, np_blocks, np_house)

38.243523

116

0.582441

6,731

0.911442

0

1,941

0.26283

5a0b2d031fe808c99bfba67eaa85c3e839cc5992

197

py

Python

tests/test_problem16.py

nolanwrightdev/blind-75-python

b92ef3449eb0143c760ddd339897a3f0a2972830

[ "MIT" ]

6

2020-02-01T23:29:51.000Z

2022-02-20T20:46:56.000Z

tests/test_problem16.py

nolanwrightdev/blind-75-python

b92ef3449eb0143c760ddd339897a3f0a2972830

[ "MIT" ]

null

tests/test_problem16.py

nolanwrightdev/blind-75-python

b92ef3449eb0143c760ddd339897a3f0a2972830

[ "MIT" ]

null

import unittest from problems.problem16 import solution class Test(unittest.TestCase): def test(self): self.assertTrue(solution([2, 3, 1, 1, 4])) self.assertFalse(solution([3, 2, 1, 0, 4]))

21.888889

45

0.71066

138

0.700508

0

5a0b50f8318c63395085bc807823eccbb8a5e4b9

510

py

Python

project/dynamic.py

andresitodeguzman/smspy

29b9feb4356de5dbd1a5d222d38d45396a349d23

[ "Apache-2.0" ]

4

2017-01-27T05:15:09.000Z

2020-12-08T13:24:19.000Z

project/dynamic.py

andresitodeguzman/smspy

29b9feb4356de5dbd1a5d222d38d45396a349d23

[ "Apache-2.0" ]

1

2019-05-20T15:09:53.000Z

project/dynamic.py

andresitodeguzman/smspy

29b9feb4356de5dbd1a5d222d38d45396a349d23

[ "Apache-2.0" ]

null

## ## DYNAMIC ## ## Import the module explicitly (import dynamics.<module_name> as module_name) import dynamics.root as root ## Register all modules for checking here. If something interferes, rearrange the order ## module_name_ = module_name.do(params) def responseQuery(number, body): # Available params n = number b = body # Do actions root_ = root.do(n,b) if root_: return root_ else: # Returns False if all actions returns False return False

21.25

88

0.666667

0

295

0.578431

5a0bac916180eec03144ad684ddb2ec3547f8ee7

288

py

Python

accounts/urls.py

mishrakeshav/Django-Real-Estate-Website

4f6146ad8d13003f890677c2c1af82b26c69678b

[ "MIT" ]

null

accounts/urls.py

mishrakeshav/Django-Real-Estate-Website

4f6146ad8d13003f890677c2c1af82b26c69678b

[ "MIT" ]

7

2021-04-08T20:21:35.000Z

2022-01-13T03:27:33.000Z

accounts/urls.py

mishrakeshav/Django-Real-Estate-Website

4f6146ad8d13003f890677c2c1af82b26c69678b

[ "MIT" ]

null

from django.urls import path from . import views urlpatterns = [ path('login', views.login, name = 'login'), path('register', views.register, name = 'register'), path('logout', views.logout, name = 'logout'), path('dashboard', views.dashboard, name = 'dashboard'), ]

28.8

59

0.645833

0

72

0.25

5a0e378937b9fd8ab97a5e345d693d92224ab800

4,333

py

Python

src/past/types/oldstr.py

kianmeng/python-future

80523f383fbba1c6de0551e19d0277e73e69573c

[ "MIT" ]

908

2015-01-01T21:20:45.000Z

2022-03-29T20:47:16.000Z

src/past/types/oldstr.py

kianmeng/python-future

80523f383fbba1c6de0551e19d0277e73e69573c

[ "MIT" ]

402

2015-01-04T01:30:19.000Z

2022-03-24T11:56:38.000Z

src/past/types/oldstr.py

kianmeng/python-future

80523f383fbba1c6de0551e19d0277e73e69573c

[ "MIT" ]

305

2015-01-18T19:29:37.000Z

2022-03-24T09:40:09.000Z

""" Pure-Python implementation of a Python 2-like str object for Python 3. """ from numbers import Integral from past.utils import PY2, with_metaclass if PY2: from collections import Iterable else: from collections.abc import Iterable _builtin_bytes = bytes class BaseOldStr(type): def __instancecheck__(cls, instance): return isinstance(instance, _builtin_bytes) def unescape(s): r""" Interprets strings with escape sequences Example: >>> s = unescape(r'abc\\def') # i.e. 'abc\\\\def' >>> print(s) 'abc\def' >>> s2 = unescape('abc\\ndef') >>> len(s2) 8 >>> print(s2) abc def """ return s.encode().decode('unicode_escape') class oldstr(with_metaclass(BaseOldStr, _builtin_bytes)): """ A forward port of the Python 2 8-bit string object to Py3 """ # Python 2 strings have no __iter__ method: @property def __iter__(self): raise AttributeError def __dir__(self): return [thing for thing in dir(_builtin_bytes) if thing != '__iter__'] # def __new__(cls, *args, **kwargs): # """ # From the Py3 bytes docstring: # bytes(iterable_of_ints) -> bytes # bytes(string, encoding[, errors]) -> bytes # bytes(bytes_or_buffer) -> immutable copy of bytes_or_buffer # bytes(int) -> bytes object of size given by the parameter initialized with null bytes # bytes() -> empty bytes object # # Construct an immutable array of bytes from: # - an iterable yielding integers in range(256) # - a text string encoded using the specified encoding # - any object implementing the buffer API. # - an integer # """ # # if len(args) == 0: # return super(newbytes, cls).__new__(cls) # # Was: elif isinstance(args[0], newbytes): # # We use type() instead of the above because we're redefining # # this to be True for all unicode string subclasses. Warning: # # This may render newstr un-subclassable. # elif type(args[0]) == newbytes: # return args[0] # elif isinstance(args[0], _builtin_bytes): # value = args[0] # elif isinstance(args[0], unicode): # if 'encoding' not in kwargs: # raise TypeError('unicode string argument without an encoding') # ### # # Was: value = args[0].encode(**kwargs) # # Python 2.6 string encode() method doesn't take kwargs: # # Use this instead: # newargs = [kwargs['encoding']] # if 'errors' in kwargs: # newargs.append(kwargs['errors']) # value = args[0].encode(*newargs) # ### # elif isinstance(args[0], Iterable): # if len(args[0]) == 0: # # What is this? # raise ValueError('unknown argument type') # elif len(args[0]) > 0 and isinstance(args[0][0], Integral): # # It's a list of integers # value = b''.join([chr(x) for x in args[0]]) # else: # raise ValueError('item cannot be interpreted as an integer') # elif isinstance(args[0], Integral): # if args[0] < 0: # raise ValueError('negative count') # value = b'\x00' * args[0] # else: # value = args[0] # return super(newbytes, cls).__new__(cls, value) def __repr__(self): s = super(oldstr, self).__repr__() # e.g. b'abc' on Py3, b'abc' on Py3 return s[1:] def __str__(self): s = super(oldstr, self).__str__() # e.g. "b'abc'" or "b'abc\\ndef' # TODO: fix this: assert s[:2] == "b'" and s[-1] == "'" return unescape(s[2:-1]) # e.g. 'abc' or 'abc\ndef' def __getitem__(self, y): if isinstance(y, Integral): return super(oldstr, self).__getitem__(slice(y, y+1)) else: return super(oldstr, self).__getitem__(y) def __getslice__(self, *args): return self.__getitem__(slice(*args)) def __contains__(self, key): if isinstance(key, int): return False def __native__(self): return bytes(self) __all__ = ['oldstr']

31.860294

95

0.558505

3,714

0.857143

0

62

0.014309

0

2,766

0.638357

5a0e75196f538319c5078d09117599bf367b0df0

1,208

py

Python

app/api/utlis/models.py

jurekpawlikowski/flask-boilerplate

15b7e6c4e0241a7d59dbca543e023a22b17b9903

[ "MIT" ]

3

2017-08-05T08:57:37.000Z

2021-03-03T09:09:03.000Z

app/api/utlis/models.py

jurekpawlikowski/flask-boilerplate

15b7e6c4e0241a7d59dbca543e023a22b17b9903

[ "MIT" ]

null

app/api/utlis/models.py

jurekpawlikowski/flask-boilerplate

15b7e6c4e0241a7d59dbca543e023a22b17b9903

[ "MIT" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- from datetime import datetime from sqlalchemy.event import listen from app.factory import db class BaseModel(db.Model): """ Base model with `created_at` and `updated_at` fields """ __abstract__ = True fields_to_serialize = [] created_at = db.Column(db.DateTime, nullable=False, default=datetime.utcnow) updated_at = db.Column(db.DateTime, nullable=False, default=datetime.utcnow) def save(self): db.session.add(self) db.session.commit() def delete(self): db.session.delete(self) db.session.commit() @classmethod def all(cls): return cls.query.all() def serialize(self, fields=None): serialized = {} for field in fields or self.fields_to_serialize: field_value = getattr(self, field) if isinstance(field_value, datetime): field_value = field_value.isoformat() serialized[field] = field_value return serialized def set_updated_at(target, value, oldvalue): """ Set updated_at value """ value.updated_at = datetime.now() listen(BaseModel, "before_update", set_updated_at)

23.686275

80

0.647351

885

0.732616

0

61

0.050497

0

163

0.134934

5a0ebed0bb4e1667aef392ee3608c9732dd33560

278

py

Python

systest/tests/test_rm.py

devconsoft/pycred

d72bdae2e703a87a7424f08af326834281b83fee

[ "MIT" ]

null

systest/tests/test_rm.py

devconsoft/pycred

d72bdae2e703a87a7424f08af326834281b83fee

[ "MIT" ]

5

2018-07-01T22:53:24.000Z

2018-07-17T21:54:10.000Z

systest/tests/test_rm.py

devconsoft/pycred

d72bdae2e703a87a7424f08af326834281b83fee

[ "MIT" ]

null

def test_rm_long_opt_help(pycred): pycred('rm --help') def test_rm_short_opt_help(pycred): pycred('rm -h') def test_rm_none_existing_store_gives_exit_code_2(pycred, workspace): with workspace(): pycred('rm non-existing-store user', expected_exit_code=2)

23.166667

69

0.73741

0

46

0.165468

5a0fd6978a62253af90bdbf0d79e056e97e5921d

1,391

py

Python

source/tweaks/cms_plugins.py

mverleg/svsite

5c9dbcacf81020cf0c1960e337bdd33113acd597

[ "BSD-3-Clause" ]

null

source/tweaks/cms_plugins.py

mverleg/svsite

5c9dbcacf81020cf0c1960e337bdd33113acd597

[ "BSD-3-Clause" ]

142

2015-06-05T07:53:09.000Z

2020-03-31T18:37:07.000Z

source/tweaks/cms_plugins.py

mdilli/svsite

5c9dbcacf81020cf0c1960e337bdd33113acd597

[ "BSD-3-Clause" ]

null

""" Raw HTML widget. Adapted/copied from https://github.com/makukha/cmsplugin-raw-html """ from cms.plugin_base import CMSPluginBase from cms.plugin_pool import plugin_pool from django.template import Template from django.utils.safestring import mark_safe from .models import RawHtmlModel, CMSMember from django.utils.translation import ugettext as _ class RawHtmlPlugin(CMSPluginBase): model = RawHtmlModel name = 'HTML' render_template = 'cms/raw_html_widget.html' text_enabled = True def render(self, context, instance, placeholder): context.update({ 'body': mark_safe(Template(instance.body).render(context)), 'object': instance, 'placeholder': placeholder }) return context plugin_pool.register_plugin(RawHtmlPlugin) class MemberPlugin(CMSPluginBase): """ This needs to be defined in `tweaks` because it has to be after `cms`, whereas `AUTH_USER_MODEL` needs to be loaded before `cms`. """ model = CMSMember # model where plugin data are saved module = _('Member') name = _('Member info') # name of the plugin in the interface render_template = 'members_widget.html' def render(self, context, instance, placeholder): context.update(dict( inst=instance, title=instance.title, description=instance.description, users=instance.members.all(), )) return context plugin_pool.register_plugin(MemberPlugin) # register the plugin

24.839286

79

0.757009

918

0.659957

0

424

0.304817

5a1046d61cc7585c8ffb76dc65a2afa1c14d62a9

3,296

py

Python

tests/test_trackings.py

EugeneLiu/aftership-sdk-python

37184272869452734d616b31295a4ac883051f5d

[ "MIT" ]

null

tests/test_trackings.py

EugeneLiu/aftership-sdk-python

37184272869452734d616b31295a4ac883051f5d

[ "MIT" ]

null

tests/test_trackings.py

EugeneLiu/aftership-sdk-python

37184272869452734d616b31295a4ac883051f5d

[ "MIT" ]

null

from unittest import TestCase, mock import pytest from requests import Response import aftership class TrackingTestCase(TestCase): def setUp(self): self.slug = "4px" self.tracking_number = "HH19260817" self.tracking_id = "k5lh7dy7vvqeck71p5loe011" @pytest.mark.vcr() def test_create_tracking(self): response = aftership.tracking.create_tracking( tracking={"slug": self.slug, "tracking_number": self.tracking_number} ) @pytest.mark.vcr() def test_get_tracking(self): response = aftership.tracking.get_tracking(slug=self.slug, tracking_number=self.tracking_number) # @pytest.mark.vcr() # def test_delete_tracking(self): # response = aftership.tracking.delete_tracking(slug='china-ems',tracking_number='1234567890') @pytest.mark.vcr() def test_list_trackings(self): response = aftership.tracking.list_trackings(slug=self.slug, limit=1) @pytest.mark.vcr() def test_update_tracking(self): response = aftership.tracking.update_tracking(tracking_id=self.tracking_id, tracking={"title": "new title"}) @pytest.mark.vcr() def test_retrack(self): response = aftership.tracking.retrack(tracking_id=self.tracking_id) @pytest.mark.vcr() def test_get_last_checkpoint(self): response = aftership.tracking.get_last_checkpoint(tracking_id=self.tracking_id) class TrackingWithAdditionalFieldsTestCase(TestCase): def setUp(self): self.tracking_id = "wuuxyb7ohjx55kmpt5r7y017" self.slug = "postnl-3s" self.tracking_number = "3SKAAG5995399" self.destination_country = "ESP" self.postal_code = "46970" @pytest.mark.vcr() def test_create_tracking(self): response = aftership.tracking.create_tracking( tracking={ "slug": self.slug, "tracking_number": self.tracking_number, "tracking_destination_country": self.destination_country, "tracking_postal_code": self.postal_code, } ) @pytest.mark.vcr() def test_get_tracking(self): response = aftership.tracking.get_tracking( slug=self.slug, tracking_number=self.tracking_number, tracking_destination_country=self.destination_country, tracking_postal_code=self.postal_code, ) @pytest.mark.vcr() def test_get_tracking_by_id(self): response = aftership.tracking.get_tracking(tracking_id=self.tracking_id) @pytest.mark.vcr() def test_update_tracking(self): response = aftership.tracking.update_tracking(tracking_id=self.tracking_id, tracking={"title": "new title"}) @pytest.mark.vcr() def test_get_last_checkpoint(self): response = aftership.tracking.get_last_checkpoint(tracking_id=self.tracking_id) @pytest.mark.vcr() def test_get_tracking_with_internal_error(self): with self.assertRaises(aftership.exception.InternalError): response = aftership.tracking.get_tracking( slug=self.slug, tracking_number=self.tracking_number, tracking_destination_country=self.destination_country, tracking_postal_code=self.postal_code, )

34.694737

116

0.681129

3,191

0.968143

0

2,491

0.755765

0

392

0.118932

5a105c110cc6114a77deee02c167af5066ada602

1,089

py

Python

071_caixaeletronico.py

laissilveira/python-exercises

906f7e46878b296ecb9b9df9fd39ec1e362ce3a4

[ "MIT" ]

null

071_caixaeletronico.py

laissilveira/python-exercises

906f7e46878b296ecb9b9df9fd39ec1e362ce3a4

[ "MIT" ]

null

071_caixaeletronico.py

laissilveira/python-exercises

906f7e46878b296ecb9b9df9fd39ec1e362ce3a4

[ "MIT" ]

null

# Calcula a quantidade de notas de cada valor a serem sacadas em uma caixa eletrônico print('=' * 30) print('{:^30}'.format('CAIXA ELETRÔNICO')) print('=' * 30) valor = int(input('Valor a ser sacado: R$ ')) # notas de real (R$) existentes tot200 = valor // 200 tot100 = (valor % 200) // 100 tot50 = ((valor % 200) % 100) // 50 tot20 = (((valor % 200) % 100) % 50) // 20 tot10 = ((((valor % 200) % 100) % 50) % 20) //10 tot5 = (((((valor % 200) % 100) % 50) % 20) % 10) // 5 tot2 = ((((((valor % 200) % 100) % 50) % 20) % 10) % 5) // 2 while True: if tot200 > 0: print(f'Total de {tot200} cédula(s) de R$ 200,00.') if tot100 > 0: print(f'Total de {tot100} cédula(s) de R$ 100,00.') if tot50 > 0: print(f'Total de {tot50} cédula(s) de R$ 50,00.') if tot20 > 0: print(f'Total de {tot20} cédula(s) de R$ 20,00.') if tot10 > 0: print(f'Total de {tot10} cédula(s) de R$ 10,00.') if tot5 > 0: print(f'Total de {tot5} cédula(s) de R$ 5,00.') if tot2 > 0: print(f'Total de {tot2} cédula(s) de R$ 2,00.') break

36.3

85

0.543618

0

476

0.433515

5a1066f50cc73cde3a7e5f65b4cffbe41ddedc46

575

py

Python

2020/04/Teil 1 - V01.py

HeWeMel/adventofcode

90acb10f03f21ef388673bbcf132d04972175970

[ "MIT" ]

1

2020-12-12T19:34:59.000Z

2020/04/Teil 1 - V01.py

HeWeMel/adventofcode

90acb10f03f21ef388673bbcf132d04972175970

[ "MIT" ]

null

2020/04/Teil 1 - V01.py

HeWeMel/adventofcode

90acb10f03f21ef388673bbcf132d04972175970

[ "MIT" ]

null

import sys lines=[] new=True lc=0 with open('input.txt', 'r') as f: for line in f: line=line[:-1] # remove new line char if line=='': lc+=1 new=True else: if new: lines.append(line) new=False else: lines[lc] = lines[lc] + " " + line valids=0 for line in lines: valid=True for must in ['byr', 'iyr', 'eyr', 'hgt', 'hcl', 'ecl', 'pid']: if line.find(must)==-1: valid=False if valid: valids += 1 print(valids)

19.166667

66

0.452174

0

76

0.132174

5a10f64e9ccb60f772e7fb4e5d093560ebd8cdb4

9,366

py

Python

src/falconpy/quick_scan.py

CrowdStrike/falconpy

e7245202224647a2c8d134e72f27d2f6c667a1ce

[ "Unlicense" ]

111

2020-11-19T00:44:18.000Z

2022-03-03T21:02:32.000Z

src/falconpy/quick_scan.py

CrowdStrike/falconpy

e7245202224647a2c8d134e72f27d2f6c667a1ce

[ "Unlicense" ]

227

2020-12-05T03:02:27.000Z

2022-03-22T14:12:42.000Z

src/falconpy/quick_scan.py

CrowdStrike/falconpy

e7245202224647a2c8d134e72f27d2f6c667a1ce

[ "Unlicense" ]

47

2020-11-23T21:00:14.000Z

2022-03-28T18:30:19.000Z

"""Falcon Quick Scan API Interface Class _______ __ _______ __ __ __ | _ .----.-----.--.--.--.--| | _ | |_.----|__| |--.-----. |. 1___| _| _ | | | | _ | 1___| _| _| | <| -__| |. |___|__| |_____|________|_____|____ |____|__| |__|__|__|_____| |: 1 | |: 1 | |::.. . | CROWDSTRIKE FALCON |::.. . | FalconPy `-------' `-------' OAuth2 API - Customer SDK This is free and unencumbered software released into the public domain. Anyone is free to copy, modify, publish, use, compile, sell, or distribute this software, either in source code form or as a compiled binary, for any purpose, commercial or non-commercial, and by any means. In jurisdictions that recognize copyright laws, the author or authors of this software dedicate any and all copyright interest in the software to the public domain. We make this dedication for the benefit of the public at large and to the detriment of our heirs and successors. We intend this dedication to be an overt act of relinquishment in perpetuity of all present and future rights to this software under copyright law. 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 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. For more information, please refer to <https://unlicense.org> """ from ._util import force_default, process_service_request, handle_single_argument from ._payload import generic_payload_list, aggregate_payload from ._service_class import ServiceClass from ._endpoint._quick_scan import _quick_scan_endpoints as Endpoints class QuickScan(ServiceClass): """The only requirement to instantiate an instance of this class is one of the following: - a valid client_id and client_secret provided as keywords. - a credential dictionary with client_id and client_secret containing valid API credentials { "client_id": "CLIENT_ID_HERE", "client_secret": "CLIENT_SECRET_HERE" } - a previously-authenticated instance of the authentication service class (oauth2.py) - a valid token provided by the authentication service class (oauth2.py) """ @force_default(defaults=["body"], default_types=["dict"]) def get_scans_aggregates(self: object, body: dict = None, **kwargs) -> dict: """Get scans aggregations as specified via json in request body. Keyword arguments: body -- full body payload, not required when using other keywords. { "date_ranges": [ { "from": "string", "to": "string" } ], "field": "string", "filter": "string", "interval": "string", "min_doc_count": 0, "missing": "string", "name": "string", "q": "string", "ranges": [ { "From": 0, "To": 0 } ], "size": 0, "sort": "string", "sub_aggregates": [ null ], "time_zone": "string", "type": "string" } date_ranges -- List of dictionaries. field -- String. filter -- FQL syntax. String. interval -- String. min_doc_count -- Minimum number of documents required to match. Integer. missing -- String. name -- Scan name. String. q -- FQL syntax. String. ranges -- List of dictionaries. size -- Integer. sort -- FQL syntax. String. sub_aggregates -- List of strings. time_zone -- String. type -- String. This method only supports keywords for providing arguments. This method does not support body payload validation. Returns: dict object containing API response. HTTP Method: POST Swagger URL https://assets.falcon.crowdstrike.com/support/api/swagger.html#/quick-scan/GetScansAggregates """ if not body: body = aggregate_payload(submitted_keywords=kwargs) return process_service_request( calling_object=self, endpoints=Endpoints, operation_id="GetScansAggregates", body=body ) @force_default(defaults=["parameters"], default_types=["dict"]) def get_scans(self: object, *args, parameters: dict = None, **kwargs) -> dict: """Check the status of a volume scan. Time required for analysis increases with the number of samples in a volume but usually it should take less than 1 minute. Keyword arguments: ids -- One or more remediation IDs. String or list of strings. parameters - full parameters payload, not required if ids is provided as a keyword. Arguments: When not specified, the first argument to this method is assumed to be 'ids'. All others are ignored. Returns: dict object containing API response. HTTP Method: GET Swagger URL https://assets.falcon.crowdstrike.com/support/api/swagger.html#/quick-scan/GetScans """ return process_service_request( calling_object=self, endpoints=Endpoints, operation_id="GetScans", keywords=kwargs, params=handle_single_argument(args, parameters, "ids") ) @force_default(defaults=["body"], default_types=["dict"]) def scan_samples(self: object, *args, body: dict = None, **kwargs) -> dict: """Get scans aggregations as specified via json in request body. Keyword arguments: body -- full body payload, not required when samples keyword is provided. { "samples": [ "string" ] } samples -- SHA256(s) of the samples to scan. Must have been previously submitted using SampleUploadV3 (SampleUploads class). String or list of strings. Arguments: When not specified, the first argument to this method is assumed to be 'samples'. All others are ignored. Returns: dict object containing API response. HTTP Method: POST Swagger URL https://assets.falcon.crowdstrike.com/support/api/swagger.html#/quick-scan/ScanSamples """ if not body: body = generic_payload_list(submitted_arguments=args, submitted_keywords=kwargs, payload_value="samples" ) return process_service_request( calling_object=self, endpoints=Endpoints, operation_id="ScanSamples", body=body, body_validator={"samples": list} if self.validate_payloads else None, body_required=["samples"] if self.validate_payloads else None ) @force_default(defaults=["parameters"], default_types=["dict"]) def query_submissions(self: object, parameters: dict = None, **kwargs) -> dict: """Find IDs for submitted scans by providing an FQL filter and paging details. Returns a set of volume IDs that match your criteria. Keyword arguments: filter -- The filter expression that should be used to limit the results. FQL syntax. limit -- The maximum number of records to return. [integer, 1-5000] offset -- The integer offset to start retrieving records from. parameters - full parameters payload, not required if using other keywords. sort -- The property to sort by. FQL syntax. This method only supports keywords for providing arguments. Returns: dict object containing API response. HTTP Method: GET Swagger URL https://assets.falcon.crowdstrike.com/support/api/swagger.html#/quick-scan/QuerySubmissionsMixin0 """ return process_service_request( calling_object=self, endpoints=Endpoints, operation_id="QuerySubmissionsMixin0", keywords=kwargs, params=parameters ) # These method names align to the operation IDs in the API but # do not conform to snake_case / PEP8 and are defined here for # backwards compatibility / ease of use purposes GetScansAggregates = get_scans_aggregates GetScans = get_scans ScanSamples = scan_samples QuerySubmissionsMixin0 = query_submissions # The legacy name for this class does not conform to PascalCase / PEP8 # It is defined here for backwards compatibility purposes only. Quick_Scan = QuickScan # pylint: disable=C0103

40.025641

105

0.604527

7,228

0.771728

0

6,303

0.672966

0

7,052

0.752936

5a118345944c61aa57f158d2bab247572f49c59f

353

py

Python

images/auth-service/settings.d/00-settings.py

ESGF/esgf-docker

95f5b76c85be65920810795484786a13865f4ac1

[ "Apache-2.0" ]

3

2018-04-16T00:58:30.000Z

2020-10-07T17:58:02.000Z

images/auth-service/settings.d/00-settings.py

ESGF/esgf-docker

95f5b76c85be65920810795484786a13865f4ac1

[ "Apache-2.0" ]

115

2017-01-10T20:12:42.000Z

2021-03-03T16:11:48.000Z

images/auth-service/settings.d/00-settings.py

ESGF/esgf-docker

95f5b76c85be65920810795484786a13865f4ac1

[ "Apache-2.0" ]

21

2017-08-28T15:20:24.000Z

2021-02-09T00:08:49.000Z

# Application definition INSTALLED_APPS = [ 'django.contrib.staticfiles', 'django.contrib.sessions', 'authenticate', ] ROOT_URLCONF = 'auth_service.urls' WSGI_APPLICATION = 'auth_service.wsgi.application' # Use a non database session engine SESSION_ENGINE = 'django.contrib.sessions.backends.signed_cookies' SESSION_COOKIE_SECURE = False

23.533333

66

0.776204

0

225

0.637394

5a12d4be2ea76f2966c05949af40280a754ab4f5

3,641

py

Python

tests/test_gru.py

nsuke/hyrnn

b3efcc7b004d8402344467bf319f1d86324d11e5

[ "Apache-2.0" ]

73

2019-04-08T08:17:39.000Z

2022-03-29T03:48:07.000Z

tests/test_gru.py

nsuke/hyrnn

b3efcc7b004d8402344467bf319f1d86324d11e5

[ "Apache-2.0" ]

10

2019-03-19T04:24:07.000Z

2021-02-25T00:19:24.000Z

tests/test_gru.py

nsuke/hyrnn

b3efcc7b004d8402344467bf319f1d86324d11e5

[ "Apache-2.0" ]

14

2019-05-06T09:42:37.000Z

2021-07-17T17:18:05.000Z

import hyrnn import torch.nn def test_MobiusGRU_no_packed_just_works(): input_size = 4 hidden_size = 3 batch_size = 5 gru = hyrnn.nets.MobiusGRU(input_size, hidden_size, hyperbolic_input=False) timestops = 10 sequence = torch.randn(timestops, batch_size, input_size) out, ht = gru(sequence) # out: (seq_len, batch, num_directions * hidden_size) # ht: (num_layers * num_directions, batch, hidden_size) assert out.shape[0] == timestops assert out.shape[1] == batch_size assert out.shape[2] == hidden_size assert ht.shape[0] == 1 assert ht.shape[1] == batch_size assert ht.shape[2] == hidden_size def test_MobiusGRU_2_layers_no_packed_just_works(): input_size = 4 hidden_size = 3 batch_size = 5 num_layers = 2 gru = hyrnn.nets.MobiusGRU( input_size, hidden_size, num_layers=num_layers, hyperbolic_input=False ) timestops = 10 sequence = torch.randn(timestops, batch_size, input_size) out, ht = gru(sequence) # out: (seq_len, batch, num_directions * hidden_size) # ht: (num_layers * num_directions, batch, hidden_size) assert out.shape[0] == timestops assert out.shape[1] == batch_size assert out.shape[2] == hidden_size assert ht.shape[0] == num_layers assert ht.shape[1] == batch_size assert ht.shape[2] == hidden_size def test_mobius_gru_loop_just_works(): input_size = 4 hidden_size = 3 num_sequences = 3 seqs = torch.nn.utils.rnn.pack_sequence( [ torch.zeros(10, input_size), torch.zeros(5, input_size), torch.zeros(1, input_size), ] ) loop_params = dict() loop_params["h0"] = torch.zeros(num_sequences, hidden_size, requires_grad=False) loop_params["input"] = seqs.data loop_params["weight_ih"] = torch.nn.Parameter( torch.randn(3 * hidden_size, input_size) ) loop_params["weight_hh"] = torch.nn.Parameter( torch.randn(3 * hidden_size, hidden_size) ) loop_params["bias"] = torch.randn(3, hidden_size) loop_params["c"] = 1.0 loop_params["nonlin"] = None loop_params["hyperbolic_input"] = True loop_params["hyperbolic_hidden_state0"] = True loop_params["batch_sizes"] = seqs.batch_sizes hyrnn.nets.mobius_gru_loop(**loop_params) def test_MobiusGRU_with_packed_just_works(): input_size = 4 hidden_size = 3 gru = hyrnn.nets.MobiusGRU(input_size, hidden_size, hyperbolic_input=False) seqs = torch.nn.utils.rnn.pack_sequence( [ torch.zeros(10, input_size), torch.zeros(5, input_size), torch.zeros(1, input_size), ] ) h, ht = gru(seqs) assert h.data.size(0) == 16 # sum of times assert h.data.size(1) == hidden_size # ht: (num_layers * num_directions, batch, hidden_size) assert ht.size(2) == hidden_size assert ht.size(1) == 3 # batch size assert ht.size(0) == 1 # num layers def test_MobiusGRU_2_layers_with_packed_just_works(): input_size = 4 hidden_size = 3 gru = hyrnn.nets.MobiusGRU( input_size, hidden_size, num_layers=2, hyperbolic_input=False) seqs = torch.nn.utils.rnn.pack_sequence([ torch.zeros(10, input_size), torch.zeros(5, input_size), torch.zeros(1, input_size) ]) h, ht = gru(seqs) assert h.data.size(0) == 16 # sum of times assert h.data.size(1) == hidden_size # ht: (num_layers * num_directions, batch, hidden_size) assert ht.size(2) == hidden_size assert ht.size(1) == 3 # batch size assert ht.size(0) == 2 # num layers

31.938596

84

0.651744

0

509

0.139797

5a12f3dfdcd98b07c6a9e2f6f164d8d44b462308

1,190

py

Python

ecogvis/signal_processing/common_referencing.py

NKI-ECOG/ecogVIS

f65212fc238e5b2588a4674a6aa1236f99e7d833

[ "BSD-3-Clause" ]

13

2020-04-01T22:39:24.000Z

2022-03-04T13:27:51.000Z

ecogvis/signal_processing/common_referencing.py

NKI-ECOG/ecogVIS

f65212fc238e5b2588a4674a6aa1236f99e7d833

[ "BSD-3-Clause" ]

56

2020-04-01T14:27:21.000Z

2022-03-23T21:33:06.000Z

ecogvis/signal_processing/common_referencing.py

luiztauffer/ecogVIS

c97e79a20b3af1074a3a5e1f1ad864a580c97e04

[ "BSD-3-Clause" ]

11

2020-05-15T17:48:53.000Z

2022-02-01T23:55:12.000Z

from __future__ import division import numpy as np __all__ = ['subtract_CAR', 'subtract_common_median_reference'] def subtract_CAR(X, b_size=16): """ Compute and subtract common average reference in 16 channel blocks. """ channels, time_points = X.shape s = channels // b_size r = channels % b_size X_1 = X[:channels-r].copy() X_1 = X_1.reshape((s, b_size, time_points)) X_1 -= np.nanmean(X_1, axis=1, keepdims=True) if r > 0: X_2 = X[channels-r:].copy() X_2 -= np.nanmean(X_2, axis=0, keepdims=True) X = np.vstack([X_1.reshape((s*b_size, time_points)), X_2]) return X else: return X_1.reshape((s*b_size, time_points)) def subtract_common_median_reference(X, channel_axis=-2): """ Compute and subtract common median reference for the entire grid. Parameters ---------- X : ndarray (..., n_channels, n_time) Data to common median reference. Returns ------- Xp : ndarray (..., n_channels, n_time) Common median referenced data. """ median = np.nanmedian(X, axis=channel_axis, keepdims=True) Xp = X - median return Xp

23.8

71

0.616807

0

437

0.367227

5a13150c841953f716f3e772e7c48bc269734ed8

3,701

py

Python

rackspace/heat_store/catalog/tests.py

rohithkumar-rackspace/rcbops

fb690bc528499bbf9aebba3ab0cce0b4dffd9e35

[ "Apache-2.0" ]

null

rackspace/heat_store/catalog/tests.py

rohithkumar-rackspace/rcbops

fb690bc528499bbf9aebba3ab0cce0b4dffd9e35

[ "Apache-2.0" ]

null

rackspace/heat_store/catalog/tests.py

rohithkumar-rackspace/rcbops

fb690bc528499bbf9aebba3ab0cce0b4dffd9e35

[ "Apache-2.0" ]

null

#!/usr/bin/env python import unittest import mox import six.moves.urllib.request as urlrequest from six import StringIO from solution import Solution class TestSolution(unittest.TestCase): def setUp(self): self.mox = mox.Mox() pass def tearDown(self): self.mox.VerifyAll() self.mox.UnsetStubs() def test_create_solution(self): s = Solution('test_data/example/info.yaml') self.assertEqual(len(s.id), 32) self.assertEqual(s.title, 'the_title') self.assertEqual(s.logo, 'test_data/example/the_logo.png') self.assertEqual(s.release, '0.1') self.assertEqual(s.short_description, '<p>The short description</p>') self.assertIn('This is the <em>long</em> description', s.long_description) self.assertIn('src="test_data/example/diagram.png"', s.long_description) self.assertIn('alt="here is a diagram"', s.long_description) self.assertIn('<strong>architecture</strong>', s.architecture) self.assertIn('Design spec #1', s.design_specs) self.assertIn('Design spec #2', s.design_specs) self.assertEqual(s.heat_template, 'example.yaml') self.assertEqual(s.env_file, 'env.yaml') def test_incomplete_solution(self): lines = open('test_data/example/info.yaml').readlines() # ensure the solution isn't imported if any of the items # below are missing missing_list = ['name', 'short_desc', 'long_desc', 'heat_template', 'release'] self.mox.StubOutWithMock(urlrequest, 'urlopen') for missing in missing_list: yaml = [line for line in lines if missing not in line] urlrequest.urlopen( 'http://example.com/no-{0}.yaml'.format(missing)) \ .AndReturn(StringIO('\n'.join(yaml))) self.mox.ReplayAll() for missing in missing_list: with self.assertRaises(KeyError): Solution('http://example.com/no-{0}.yaml'.format(missing)) def test_parameter_types(self): s = Solution('test_data/example/info.yaml') params = s.get_parameter_types(None) self.assertEqual(len(params), 5) self.assertEqual(params[0]['name'], 'floating-network-id') self.assertEqual(params[0]['type'], 'comma_delimited_list') self.assertIn(params[0]['default'], params[0]['constraints'][0]['allowed_values']) self.assertIn('_mapping', params[0]) self.assertEqual(params[0]['_mapping'], {'first_network': '11', 'second_network': '22', 'third_network': '33'}) self.assertEqual(s.map_parameter(params, 'floating-network-id', 'second_network'), '22') self.assertEqual(params[1]['name'], 'flavor') self.assertEqual(params[1]['type'], 'comma_delimited_list') self.assertIn(params[1]['default'], 'm1.small') self.assertEqual(params[2]['name'], 'image') self.assertEqual(params[2]['type'], 'comma_delimited_list') self.assertIn(params[2]['default'], params[2]['constraints'][0]['allowed_values']) self.assertEqual(params[3]['name'], 'image-count') self.assertEqual(params[3]['type'], 'number') self.assertEqual(params[4]['name'], 'keyname') self.assertEqual(params[4]['type'], 'comma_delimited_list') self.assertIn(params[4]['default'], params[4]['constraints'][0]['allowed_values']) if __name__ == '__main__': unittest.main()

39.795699

80

0.599838

3,497

0.94488

0

1,055

0.285058

5a13d8b3614f878639aab1f5c25f37f50a754ad3

17

py

Python

tests/errors/semantic/ex4.py

toddrme2178/pyccel

deec37503ab0c5d0bcca1a035f7909f7ce8ef653

[ "MIT" ]

null

tests/errors/semantic/ex4.py

toddrme2178/pyccel

deec37503ab0c5d0bcca1a035f7909f7ce8ef653

[ "MIT" ]

null

tests/errors/semantic/ex4.py

toddrme2178/pyccel

deec37503ab0c5d0bcca1a035f7909f7ce8ef653

[ "MIT" ]

null

x is 1 y is None

5.666667

9

0.647059

0

5a15278549975dbd09dff5e97bcd011523d42479

4,784

py

Python

GetTopK.py

unsuthee/SemanticHashingWeekSupervision

2b2498c70ad3184203855222efde861211edcaea

[ "MIT" ]

19

2018-10-30T08:36:49.000Z

2020-09-11T08:08:47.000Z

GetTopK.py

unsuthee/SemanticHashingWeekSupervision

2b2498c70ad3184203855222efde861211edcaea

[ "MIT" ]

1

2019-10-12T07:03:06.000Z

2020-03-08T09:22:00.000Z

GetTopK.py

unsuthee/SemanticHashingWeekSupervision

2b2498c70ad3184203855222efde861211edcaea

[ "MIT" ]

6

2018-09-05T09:07:34.000Z

2020-04-07T16:58:08.000Z

################################################################################################################ # Author: Suthee Chaidaroon # schaidaroon@scu.edu ################################################################################################################ import numpy as np import os from utils import * from tqdm import tqdm import scipy.io import torch import torch.autograd as autograd from torch.autograd import Variable import torch.nn as nn import torch.nn.functional as F ################################################################################################################# def GetTopK_UsingCosineSim(outfn, queries, documents, TopK, queryBatchSize=10, docBatchSize=100): n_docs = documents.shape[0] n_queries = queries.shape[0] query_row = 0 with open(outfn, 'w') as out_fn: for q_idx in tqdm(range(0, n_queries, queryBatchSize), desc='Query', ncols=0): query_batch_s_idx = q_idx query_batch_e_idx = min(query_batch_s_idx + queryBatchSize, n_queries) queryMats = torch.cuda.FloatTensor(queries[query_batch_s_idx:query_batch_e_idx].toarray()) queryNorm2 = torch.norm(queryMats, 2, dim=1) queryNorm2.unsqueeze_(1) queryMats.unsqueeze_(2) scoreList = [] indicesList = [] #print('{}: perform cosine sim ...'.format(q_idx)) for idx in tqdm(range(0, n_docs, docBatchSize), desc='Doc', leave=False, ncols=0): batch_s_idx = idx batch_e_idx = min(batch_s_idx + docBatchSize, n_docs) n_doc_in_batch = batch_e_idx - batch_s_idx #if batch_s_idx > 1000: # break candidateMats = torch.cuda.FloatTensor(documents[batch_s_idx:batch_e_idx].toarray()) candidateNorm2 = torch.norm(candidateMats, 2, dim=1) candidateNorm2.unsqueeze_(0) candidateMats.unsqueeze_(2) candidateMats = candidateMats.permute(2, 1, 0) # compute cosine similarity queryMatsExpand = queryMats.expand(queryMats.size(0), queryMats.size(1), candidateMats.size(2)) candidateMats = candidateMats.expand_as(queryMatsExpand) cos_sim_scores = torch.sum(queryMatsExpand * candidateMats, dim=1) / (queryNorm2 * candidateNorm2) K = min(TopK, n_doc_in_batch) scores, indices = torch.topk(cos_sim_scores, K, dim=1, largest=True) del cos_sim_scores del queryMatsExpand del candidateMats del candidateNorm2 scoreList.append(scores) indicesList.append(indices + batch_s_idx) all_scores = torch.cat(scoreList, dim=1) all_indices = torch.cat(indicesList, dim=1) _, indices = torch.topk(all_scores, TopK, dim=1, largest=True) topK_indices = torch.gather(all_indices, 1, indices) #all_topK_indices.append(topK_indices) #all_topK_scores.append(scores) del queryMats del queryNorm2 del scoreList del indicesList topK_indices = topK_indices.cpu().numpy() for row in topK_indices: out_fn.write("{}:".format(query_row)) outtext = ','.join([str(col) for col in row]) out_fn.write(outtext) out_fn.write('\n') query_row += 1 torch.cuda.empty_cache() ################################################################################################################# import argparse parser = argparse.ArgumentParser() parser.add_argument("--gpunum") parser.add_argument("--dataset") parser.add_argument("--usetrain", action='store_true') args = parser.parse_args() if args.gpunum: print("Use GPU #:{}".format(args.gpunum)) gpunum = args.gpunum else: print("Use GPU #0 as a default gpu") gpunum = "0" os.environ["CUDA_VISIBLE_DEVICES"]=gpunum if args.dataset: print("load {} dataset".format(args.dataset)) dataset = args.dataset else: parser.error("Need to provide the dataset.") data = Load_Dataset("data/ng20.mat") print("num train:{} num tests:{}".format(data.n_trains, data.n_tests)) if args.usetrain: print("use train as a query corpus") query_corpus = data.train out_fn = "bm25/{}_train_top101.txt".format(dataset) else: print("use test as a query corpus") query_corpus = data.test out_fn = "bm25/{}_test_top101.txt".format(dataset) print("save the result to {}".format(out_fn)) GetTopK_UsingCosineSim(out_fn, query_corpus, data.train, TopK=101, queryBatchSize=500, docBatchSize=100)

36.519084

114

0.567517

0

1,037

0.216764

5a16e96d11bf3bbabd290d8e7eb17ada9e705ea1

1,065

py

Python

migrate_from_fnordcredit.py

stratum0/Matekasse

9b48a8a07978a150e1df1b13b394791044cce82e

[ "MIT" ]

1

2019-07-13T16:25:06.000Z

migrate_from_fnordcredit.py

stratum0/Matekasse

9b48a8a07978a150e1df1b13b394791044cce82e

[ "MIT" ]

10

2020-01-09T16:14:19.000Z

2021-03-07T17:04:30.000Z

migrate_from_fnordcredit.py

stratum0/Matekasse

9b48a8a07978a150e1df1b13b394791044cce82e

[ "MIT" ]

1

2021-06-01T07:21:03.000Z

from matekasse import create_app, db from matekasse.models import User, Transaction import sqlite3 import argparse parser = argparse.ArgumentParser(allow_abbrev=False) parser.add_argument("-p", "--path", action='store', type=str, required=True, help="Path to fnordcredit database") inp = parser.parse_args() app = create_app() ctx = app.app_context() ctx.push() try: conn = sqlite3.connect(inp.path) cursor = conn.cursor() cursor.execute('SELECT * FROM user') rows = cursor.fetchall() for r in rows: user = r[5] credit = r[1] * 100 newuser = User(username=user, credit=credit) db.session.add(newuser) '''cursor.execute('SELECT * FROM transaction') rows = cursor.fetchall() for r in rows: user = r[5] trans = r[2] * 100 newtrans = Transaction(userid=user, credit=trans) db.session.add(newtrans)''' db.session.commit() except sqlite3.Error as error: print(error) finally: if conn: conn.close() print('Migration complete') ctx.pop() exit()

25.97561

113

0.650704

0

324

0.304225

5a17b8b4d053d2409ae3602977dee83dcbebc0b2

4,340

py

Python

scripts/lc/ARES/testing/run_rose_tool.py

ouankou/rose

76f2a004bd6d8036bc24be2c566a14e33ba4f825

[ "BSD-3-Clause" ]

488

2015-01-09T08:54:48.000Z

2022-03-30T07:15:46.000Z

scripts/lc/ARES/testing/run_rose_tool.py

ouankou/rose

76f2a004bd6d8036bc24be2c566a14e33ba4f825

[ "BSD-3-Clause" ]

174

2015-01-28T18:41:32.000Z

2022-03-31T16:51:05.000Z

scripts/lc/ARES/testing/run_rose_tool.py

ouankou/rose

76f2a004bd6d8036bc24be2c566a14e33ba4f825

[ "BSD-3-Clause" ]

146

2015-04-27T02:48:34.000Z

2022-03-04T07:32:53.000Z

#!/usr/bin/env python """Runs a ROSE tool. If the tool does not return status 0, then runs the corresponding non-ROSE compiler. Records whether the tool succeeded, in passed.txt and failed.txt, but always returns status 0. """ import argparse import inspect import os from support.local_logging import Logger from support.runner import Runner _SEPARATOR = "================================================================================" class ROSERunner (object): def __init__(self): # Will be a Namespace (e.g. can refer to self._args_defined.command_args): self._args_defined = None # Will be a list: self._args_remaining = None self._current_dir = "" self._failed_file = None self._failed_file_path = "" self._logger = Logger("run_rose_tool.ROSERunner") self._parser = None self._passed_file = None self._passed_file_path = "" self._primary_command = "" self._runner = Runner() self._script_dir = "" self._secondary_command = "" self._define_args() def _define_args(self): """ This script passes all its arguments on to the called programs, so there are no argus defined. """ parser = argparse.ArgumentParser( description="""Runs a ROSE tool. If the tool does not return status 0, then runs the corresponding non-ROSE compiler. Records whether the tool succeeded, in passed.txt and failed.txt, but always returns status 0. """) # We want ALL the arguments, so, we are using parse_known_arguments # below instead and commenting this out for now: ## This matches the first positional and all remaining/following args: #parser.add_argument('command_args', nargs=argparse.REMAINDER) self._parser = parser def _process_args(self): self._args_defined, self._args_remaining = self._parser.parse_known_args() self._logger.debug("defined args\n" + str(self._args_defined)) self._logger.debug("remaining args\n" + str(self._args_remaining)) self._current_dir = os.getcwd() #self._script_dir = os.path.dirname(os.path.abspath(__file__)) # Robustly get this script's directory, even when started by exec or execfiles: script_rel_path = inspect.getframeinfo(inspect.currentframe()).filename self._script_dir = os.path.dirname(os.path.abspath(script_rel_path)) self._primary_command = "/g/g17/charles/code/ROSE/rose-0.9.10.64-intel-18.0.1.mpi/tutorial/identityTranslator" self._secondary_command = "/usr/tce/packages/mvapich2/mvapich2-2.2-intel-18.0.1/bin/mpicxx" self._passed_file_path = os.path.join (self._script_dir, "passed.txt") self._failed_file_path = os.path.join (self._script_dir, "failed.txt") def _log_success(self, args): self._logger.success("\n" + _SEPARATOR + "\nPASSED") self._logger.debug("Will log to passed file:") self._logger.debug(args) self._passed_file.write(str(args) + '\n') def _log_failure(self, args): self._logger.problem("\n" + _SEPARATOR + "\nFAILED") self._logger.debug("Will log to failed file:") self._logger.debug(args) self._failed_file.write(str(args) + '\n') def _run_command (self, args, dir): self._logger.info("\n" + _SEPARATOR) self._runner.callOrLog(args, dir) def run(self): """ Run the primary command. If it fails, run the secondary command. If that fails, let the exception (Runner.Failed) propagate. """ self._logger.set_debug_off() #self._logger._logger.setLevel(Logger.ERROR) self._process_args() self._passed_file = open(self._passed_file_path, 'a') self._failed_file = open(self._failed_file_path, 'a') try: primary_args = [self._primary_command] + self._args_remaining self._run_command(primary_args, self._current_dir) self._log_success(primary_args) except Runner.Failed, e: self._log_failure(primary_args) secondary_args = [self._secondary_command] + self._args_remaining self._run_command(secondary_args, self._current_dir) def main(): ROSERunner().run() if __name__ == '__main__': main()

41.333333

118

0.653917

3,818

0.879724

0

1,665

0.383641

5a18641e63b3fcad6914df89d4ba92c48cbaed17

951

py

Python

source/odp/migrations/0003_auto_20201121_0919.py

kssvrk/BhoonidhiODP

e222087629250ea4ccd1ae8d8903d9ff400c13b4

[ "BSD-3-Clause" ]

null

source/odp/migrations/0003_auto_20201121_0919.py

kssvrk/BhoonidhiODP

e222087629250ea4ccd1ae8d8903d9ff400c13b4

[ "BSD-3-Clause" ]

null

source/odp/migrations/0003_auto_20201121_0919.py

kssvrk/BhoonidhiODP

e222087629250ea4ccd1ae8d8903d9ff400c13b4

[ "BSD-3-Clause" ]

null

# Generated by Django 3.1.2 on 2020-11-21 09:19 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('odp', '0002_auto_20201121_0659'), ] operations = [ migrations.CreateModel( name='ProcessGroup', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('group_name', models.CharField(max_length=100, unique=True)), ('group_description', models.CharField(blank=True, max_length=5000, null=True)), ('created_at', models.DateTimeField(auto_now_add=True)), ('updated_at', models.DateTimeField(auto_now=True)), ], ), migrations.AddField( model_name='processcatalogue', name='group_id', field=models.ManyToManyField(to='odp.ProcessGroup'), ), ]

32.793103

114

0.59306

858

0.902208

0

200

0.210305

5a18bfbbcf6c30bc2b6197bebec5c6f5638d264b

935

py

Python

test/auth/test_client_credentials.py

membranepotential/mendeley-python-sdk

0336f0164f4d409309e813cbd0140011b5b2ff8f

[ "Apache-2.0" ]

103

2015-01-12T00:40:51.000Z

2022-03-29T07:02:06.000Z

test/auth/test_client_credentials.py

membranepotential/mendeley-python-sdk

0336f0164f4d409309e813cbd0140011b5b2ff8f

[ "Apache-2.0" ]

26

2015-01-10T04:08:41.000Z

2021-02-05T16:31:37.000Z

test/auth/test_client_credentials.py

membranepotential/mendeley-python-sdk

0336f0164f4d409309e813cbd0140011b5b2ff8f

[ "Apache-2.0" ]

43

2015-03-04T18:11:06.000Z

2022-03-13T02:33:34.000Z

from oauthlib.oauth2 import InvalidClientError, MissingTokenError import pytest from test import configure_mendeley, cassette def test_should_get_authenticated_session(): mendeley = configure_mendeley() auth = mendeley.start_client_credentials_flow() with cassette('fixtures/auth/client_credentials/get_authenticated_session.yaml'): session = auth.authenticate() assert session.token['access_token'] assert session.host == 'https://api.mendeley.com' def test_should_throw_exception_on_incorrect_credentials(): mendeley = configure_mendeley() mendeley.client_secret += '-invalid' auth = mendeley.start_client_credentials_flow() # We should never get an access token back # and the OAuth library should be unhappy about that with cassette('fixtures/auth/client_credentials/incorrect_credentials.yaml'), pytest.raises(MissingTokenError): auth.authenticate()

34.62963

115

0.764706

0

270

0.28877

5a18ed1bc8e6b13c94274ea7e8252580407f9a6b

338

py

Python

problem/01000~09999/06137/6137.py3.py

njw1204/BOJ-AC

1de41685725ae4657a7ff94e413febd97a888567

[ "MIT" ]

1

2019-04-19T16:37:44.000Z

problem/01000~09999/06137/6137.py3.py

njw1204/BOJ-AC

1de41685725ae4657a7ff94e413febd97a888567

[ "MIT" ]

1

2019-04-20T11:42:44.000Z

problem/01000~09999/06137/6137.py3.py

njw1204/BOJ-AC

1de41685725ae4657a7ff94e413febd97a888567

[ "MIT" ]

3

2019-04-19T16:37:47.000Z

2021-10-25T00:45:00.000Z

s=[] for i in range(int(input())): s.append(input()) cnt=0 while s: flag=True for i in range(len(s)//2): if s[i]<s[-(i+1)]: print(s[0],end='') s.pop(0) flag=False break elif s[-(i+1)]<s[i]: print(s[-1],end='') s.pop() flag=False break if flag: print(s[-1],end='') s.pop() cnt+=1 if cnt%80==0: print()

15.363636

29

0.52071

0

6

0.017751

5a1bae372e9a9d499e2d0814cd4b789a6fdb51ad

2,072

py

Python

test/test_thirty.py

jakubtuchol/dailycodingproblem

9f0f3193f1746e949e16febace5aa5622dc5d4dc

[ "MIT" ]

1

2020-10-13T20:54:37.000Z

test/test_thirty.py

jakubtuchol/dailycodingproblem

9f0f3193f1746e949e16febace5aa5622dc5d4dc

[ "MIT" ]

null

test/test_thirty.py

jakubtuchol/dailycodingproblem

9f0f3193f1746e949e16febace5aa5622dc5d4dc

[ "MIT" ]

null

from src.thirty import edit_distance from src.thirty import find_second_largest_node from src.thirty import make_palindrome from src.thirty import powerset from src.data_structures import BinaryNode class TestEditDistance: """ Problem #31 """ def test_provided_example(self): assert 3 == edit_distance('kitten', 'sitting') def test_empty_examples(self): assert 7 == edit_distance('', 'sitting') assert 6 == edit_distance('kitten', '') def test_equal_examples(self): assert 0 == edit_distance('', '') assert 0 == edit_distance('kitten', 'kitten') def test_none_in_common(self): assert 3 == edit_distance('abc', 'xyz') class TestMakePalindrome: """ Problem #34 """ def test_provided_example(self): assert 'ecarace' == make_palindrome('race') def test_another_example(self): assert 'elgoogle' == make_palindrome('google') class TestFindSecondLargestNode: """ Problem #36 """ def test_on_left(self): root = BinaryNode(5) root.left = BinaryNode(3) assert 3 == find_second_largest_node(root).val def test_on_right(self): root = BinaryNode(2) root.right = BinaryNode(4) assert 2 == find_second_largest_node(root).val def test_balanced(self): root = BinaryNode(2) root.left = BinaryNode(1) root.right = BinaryNode(3) assert 2 == find_second_largest_node(root).val def test_less_than_two_elements(self): root = BinaryNode(2) assert not find_second_largest_node(root) class TestPowerset: """ Problem #37 """ def test_three(self): expected_set = [ [], [1], [2], [3], [1, 2], [1, 3], [2, 3], [1, 2, 3], ] calculated_set = powerset([1, 2, 3]) assert len(calculated_set) == len(expected_set) for elt in calculated_set: assert elt in expected_set def test_empty(self): assert [[]] == powerset([])

22.769231

55

0.605695

1,861

0.898166

0

209

0.100869

5a1be255168c22e03a6a98004add6394315035a9

3,947

py

Python

src/google_music_proto/musicmanager/utils.py

ddboline/google-music-proto

d3af3a1fe911edcd083482c9a6e8bde5a2902462

[ "MIT" ]

null

src/google_music_proto/musicmanager/utils.py

ddboline/google-music-proto

d3af3a1fe911edcd083482c9a6e8bde5a2902462

[ "MIT" ]

null

src/google_music_proto/musicmanager/utils.py

ddboline/google-music-proto

d3af3a1fe911edcd083482c9a6e8bde5a2902462

[ "MIT" ]

null

__all__ = [ 'generate_client_id', 'get_album_art', 'get_transcoder', 'transcode_to_mp3', ] import os import shutil import subprocess from base64 import b64encode from binascii import unhexlify from hashlib import md5 import audio_metadata # The id is found by: getting md5sum of audio, base64 encode md5sum, removing trailing '='. def generate_client_id(song): if not isinstance(song, audio_metadata.Format): song = audio_metadata.load(song) md5sum = None if isinstance(song, audio_metadata.FLAC): md5sum = unhexlify(song.streaminfo.md5) else: m = md5() audio_size = song.streaminfo._size with open(song.filepath, 'rb') as f: f.seek(song.streaminfo._start) # Speed up by reading in chunks read = 0 while True: read_size = min(audio_size - read, 65536) if not read_size: break read += read_size data = f.read(read_size) m.update(data) md5sum = m.digest() client_id = b64encode(md5sum).rstrip(b'=').decode('ascii') return client_id def get_album_art(song): if not isinstance(song, audio_metadata.Format): song = audio_metadata.load(song) album_art = next( ( picture.data for picture in song.pictures if picture.type == 3 ), None ) return album_art def get_transcoder(): """Return the path to a transcoder (ffmpeg or avconv) with MP3 support.""" transcoders = ['ffmpeg', 'avconv'] transcoder_details = {} for transcoder in transcoders: command_path = shutil.which(transcoder) if command_path is None: transcoder_details[transcoder] = 'Not installed.' continue stdout = subprocess.run( [command_path, '-codecs'], stdout=subprocess.PIPE, stderr=subprocess.DEVNULL, universal_newlines=True, ).stdout mp3_encoding_support = ( 'libmp3lame' in stdout and 'disable-libmp3lame' not in stdout ) if mp3_encoding_support: transcoder_details[transcoder] = "MP3 encoding support." break else: transcoder_details[transcoder] = "No MP3 encoding support." else: raise ValueError( f"ffmpeg or avconv must be in the path and support mp3 encoding." "\nDetails: {transcoder_details}" ) return command_path def _transcode(command, input_=None): try: transcode = subprocess.run( command, input=input_, stdout=subprocess.PIPE, stderr=subprocess.PIPE, ) transcode.check_returncode() except (OSError, subprocess.CalledProcessError) as e: error_msg = f"Transcode command '{' '.join(command)}' failed: {e}. " if 'No such file or directory' in str(e): error_msg += '\nffmpeg or avconv must be installed PATH.' if transcode.stderr is not None: error_msg += f"\nstderr: '{transcode.stderr}'" e.message = error_msg raise else: return transcode.stdout def transcode_to_mp3(song, *, slice_start=None, slice_duration=None, quality='320k'): command_path = get_transcoder() input_ = None if isinstance(song, audio_metadata.Format): if hasattr(song.filepath, 'read'): raise ValueError("Audio metadata must be from a file.") # command = [command_path, '-i', '-'] # input_ = song.filepath.read() else: command = [command_path, '-i', song.filepath] elif isinstance(song, bytes): command = [command_path, '-i', '-'] input_ = song elif isinstance(song, str): command = [command_path, '-i', song] elif isinstance(song, os.PathLike): command = [command_path, '-i', song.__fspath__()] else: raise ValueError( "'song' must be os.PathLike, filepath string, a file/bytes-like object, or binary data." ) if slice_duration is not None: command.extend(['-t', str(slice_duration)]) if slice_start is not None: command.extend(['-ss', str(slice_start)]) if isinstance(quality, int): command.extend(['-q:a', str(quality)]) elif isinstance(quality, str): command.extend(['-b:a', str(quality)]) # Use 's16le' to not output id3 headers. command.extend(['-f', 's16le', '-c', 'libmp3lame', '-']) return _transcode(command, input_=input_)

23.777108

91

0.701292

0

975

0.247023

5a1c4a115bd07e61146d8a14b7bb3639da60f1ea

8,731

py

Python

Other/SocialNetwork/Solver.py

lesyk/Evolife

8e3dd1aab84061f7ce082f3a4b1bac0b2e31bc4a

[ "MIT" ]

null

Other/SocialNetwork/Solver.py

lesyk/Evolife

8e3dd1aab84061f7ce082f3a4b1bac0b2e31bc4a

[ "MIT" ]

null

Other/SocialNetwork/Solver.py

lesyk/Evolife

8e3dd1aab84061f7ce082f3a4b1bac0b2e31bc4a

[ "MIT" ]

null

## {{{ http://code.activestate.com/recipes/303396/ (r1) '''equation solver using attributes and introspection''' from __future__ import division class Solver(object): '''takes a function, named arg value (opt.) and returns a Solver object''' def __init__(self,f,**args): self._f=f self._args={} # see important note on order of operations in __setattr__ below. for arg in f.func_code.co_varnames[0:f.func_code.co_argcount]: self._args[arg]=None self._setargs(**args) def __repr__(self): argstring=','.join(['%s=%s' % (arg,str(value)) for (arg,value) in self._args.items()]) if argstring: return 'Solver(%s,%s)' % (self._f.func_code.co_name, argstring) else: return 'Solver(%s)' % self._f.func_code.co_name def __getattr__(self,name): '''used to extract function argument values''' self._args[name] return self._solve_for(name) def __setattr__(self,name,value): '''sets function argument values''' # Note - once self._args is created, no new attributes can # be added to self.__dict__. This is a good thing as it throws # an exception if you try to assign to an arg which is inappropriate # for the function in the solver. if self.__dict__.has_key('_args'): if name in self._args: self._args[name]=value else: raise KeyError, name else: object.__setattr__(self,name,value) def _setargs(self,**args): '''sets values of function arguments''' for arg in args: self._args[arg] # raise exception if arg not in _args setattr(self,arg,args[arg]) def _solve_for(self,arg): '''Newton's method solver''' TOL=0.0000001 # tolerance ITERLIMIT=1000 # iteration limit CLOSE_RUNS=10 # after getting close, do more passes args=self._args if self._args[arg]: x0=self._args[arg] else: x0=1 if x0==0: x1=1 else: x1=x0*1.1 def f(x): '''function to solve''' args[arg]=x return self._f(**args) fx0=f(x0) n=0 while 1: # Newton's method loop here fx1 = f(x1) if fx1==0 or x1==x0: # managed to nail it exactly break if abs(fx1-fx0)<TOL: # very close close_flag=True if CLOSE_RUNS==0: # been close several times break else: CLOSE_RUNS-=1 # try some more else: close_flag=False if n>ITERLIMIT: print "Failed to converge; exceeded iteration limit" break slope=(fx1-fx0)/(x1-x0) if slope==0: if close_flag: # we're close but have zero slope, finish break else: print 'Zero slope and not close enough to solution' break x2=x0-fx0/slope # New 'x1' fx0 = fx1 x0=x1 x1=x2 n+=1 self._args[arg]=x1 return x1 ## end of http://code.activestate.com/recipes/303396/ }}} ######### Example ############ ##from math import cos ## ##def toto(x,A): ## return A-cos(x) ## ##T = Solver(toto) ##T.A = 0 ##print 2 * T.x ######### Fin Example ############ def competence(BottomCompetence, Quality): return BottomCompetence + (1-BottomCompetence)*Quality def Profit(b, K, friendQuality, r, NFriends): Risk = 1 for f in range(NFriends): Risk *= (1 - K * r**f * competence(b, friendQuality)) return 1 - Risk def IntegralProfit(b, K, friendQuality, r, NFriends): Sum = 0 for FQ in range(int(friendQuality * 100.01)): Sum += Profit(b, K, FQ/100.1, r, NFriends) return Sum / 100.01 def CompetitiveSignal(b, K, q, r, NFriends, cost): profit = Profit(b, K, q, r, NFriends) integralProfit = IntegralProfit(b, K, q, r, NFriends) return (competence(b, q) * profit - (1-b) * ralProfit) / cost def CompetitiveSignal1FriendsB0(K, q, cost): # special case 1 friend and no bottom competence return K*q**2/(2*cost) def CompetitiveSignal2FriendsB0(K, q, r, cost): # special case 2 friends and no bottom competence return (-2*K**2*r*q**3/(3*cost)+K*q**2*(1+r)/(2*cost)) def CompetitiveSignal3Friends(b, q, r, cost): # special case 3 friends return (1-b)*((1+r+r**2)*(b*q+(1-b)*q**2/2) - 2*r*(1+r+r**2)*(b**2*q + (1-b)**2*q**3/3 +2*b*(1-b)*q**2/2) + 3*r**3 *(b**3*q + 3*b**2*(1-b)*q**2/2 + 3*b*(1-b)**2*q**3/3 + (1-b)**3*q**4/4) )/cost def CompetitiveSignal3FriendsB0(q, r, cost): # special case 3 friends and no bottom competence return (1+r+r**2) *q**2/(2*cost) - 2*r*(1+r+r**2) *q**3/(3*cost) + 3*r**3* q**4/(4*cost) def Equil2Friends(b, K, C, eta, r, deltag): # for two friends ro = 0 S_eta = competence(b, eta) S_tau = competence(b,(1+eta)/2) bh = K * S_tau *(1+r) - K**2 * r * S_tau**2 - C * deltag bl = (1 - (1 - (1-ro)*K*S_tau - ro * K * S_eta)*(1 - K*r*(1-ro)*S_tau - ro*K*r*S_eta)) + C * deltag # return bh-bl #return (1-S_eta)*(1 + r/2 - 3*r*S_eta/2) - 4 * C * deltag return K*(1-b)*(1-eta)*(1+r-K*r*(2*b + (1-b)*(3*eta+1)/2))/4 - C*deltag def EquilManyFriends(b, K, C, eta, r, deltag, NF): S_eta = competence(b, eta) S_tau = competence(b,(1+eta)/2) return Profit(b,K,S_tau,r,NF) - Profit(b,K,S_eta,r,NF) - 2*C*deltag def SubEquilManyFriends(b, K, C, eta, tau, theta, r, deltag, NF): S_eta = competence(b, eta) S_tau = competence(b, tau) SubMiddle = competence(b, (theta+eta)/2) ## return Profit(b,K,S_tau,r,NF) - Profit(b,K,SubMiddle,r,NF) - 2*C*deltag / S_eta return Profit(b,K,S_tau,r,NF) - Profit(b,K,SubMiddle,r,NF) - 2*C*deltag def UniformSignalB0(K, C, eta, r, deltag, NF): b = 0 # otherwise false S_eta = competence(b, eta) S_tau = competence(b,(1+eta)/2) Pu = (Profit(b,K,S_tau,r,NF) + Profit(b,K,S_eta,r,NF)) /2 Pc = IntegralProfit(b, K, eta, r, NF) return ( S_eta * Pu - Pc ) / C def UniformBenefitB0(K, C, eta, theta, r, deltag, NF, sm, ro): b = 0 # otherwise false S_eta = competence(b, eta) S_theta = competence(b, theta) S_tau = competence(b,(1+eta)/2) Ptau = (1 + ro + ro*ro/4)/2 #Ptau = (1 + ro)/2 return Ptau * Profit(b,K,S_tau,r,NF) + (1-Ptau) * Profit(b,K,theta,r,NF) - (C*sm+ro*deltag)/S_theta def DiffBenefitB0(K, C, eta, theta, r, deltag, NF, sm, ro): S_theta = competence(b, theta) return UniformBenefitB0(K, C, eta, theta, r, deltag, NF, sm, ro) \ - IntegralProfit(b, K, theta, r, NF)/S_theta Equil = Solver(EquilManyFriends) #Equil = Solver(Equil2Friends) Equil.deltag = deltag = 1.2 * 0.11 # Learning noise Equil.b = b = 0.0 # BottomCompetence Equil.K = K = 1.0 Equil.r = r = 0.6 # RankEffect Equil.NF = NF = 2 # Number of friends Equil.C = C = 0.6 # Cost #Equil.ro = 0.0 # shift from uniform signal Equil.eta = 0.1 # threshold for uniform signal (initialization) ETA = Equil.eta OffSet = 0 print Equil #print '%d\t%d' % (int(round(100* ETA)),(100*CompetitiveSignal(b,K,ETA, r, NF, C))) #print 'Eta: %d\t competitive signal in Eta: %d' % (int(round(100* ETA)),(100*CompetitiveSignal3FriendsB0(ETA, r, C))), print 'Eta: %d\t competitive signal in Eta: %d' % (int(round(100* ETA)),(100*CompetitiveSignal2FriendsB0(1,ETA, r, C))), # sm = CompetitiveSignal3FriendsB0(ETA, r, C) sm = UniformSignalB0(K, C, ETA, r, deltag, NF) print 'sm: %d' % (100 * sm), SubEquil = Solver(SubEquilManyFriends) SubEquil.deltag = deltag # Learning noise SubEquil.b = b # BottomCompetence SubEquil.K = K SubEquil.r = r # RankEffect SubEquil.NF = NF # Number of friends SubEquil.C = C # Cost SubEquil.eta = ETA SubEquil.tau = ETA SubEquil.theta = 0.1 # initialization THETA = SubEquil.theta print 'Theta: %d' % (100 * THETA), ### 2nd iteration ##SubEquil.eta = THETA ##SubEquil.theta = 0.1 # initialization ##THTHETA = SubEquil.theta ##print 'ThTheta: %d' % (100 * THTHETA), print #print SubEquil """ for q in range(1,int(round(100* THETA)),1): # print CompetitiveSignal3Friends(0,q/100.0,0.6,0.6), print "%01.1f\t" % (100 * CompetitiveSignal1FriendsB0(K,q/100.0,C)), #print "%01.1f\t" % (10000 * CompetitiveSignal3FriendsB0(q/100.0,r,C)/q), for q in range(int(round(100* THETA)),101,1): print "%01.1f\t" % (100 * sm), #print "%01.1f\t" % (10000 * sm/q), print """ ##for q in range(1,int(round(100* ETA)),1): ## print "%01.2f\t" % (100 * IntegralProfit(b,K,q/100.0,r,NF)), ##print ##for ro in range(-190, 190, 1): ## Equil.ro = ro/100.0 ## Equil.eta = 0.01 ## ETA = Equil.eta ## print '%d\t' % (int(round(100* ETA))), ##print ##for dtheta in range(-5, 10): ## theta = ETA - dtheta / 100.0 ## print theta ## for ro in range(-5,5,1): ## print "%01.1f\t" % (100 * DiffBenefitB0(K, C, ETA, theta, r, deltag, NF, sm, ro/100.0)), ## print #print "%01.1f\t" % (100 * DiffBenefitB0(K, C, ETA, ETA, r, deltag, NF, sm, 0.0)) __author__ = 'Dessalles'

31.293907

195

0.611499

2,588

0.296415

0

3,460

0.396289

5a1c596e4aa4f0daea1821382fed5edc2f1a2f2c

15,459

py

Python

server/graph.py

Alpacron/vertex-cover

cfdace128f1578f9613e30990b9a87cc64ffb988

[ "MIT" ]

null

server/graph.py

Alpacron/vertex-cover

cfdace128f1578f9613e30990b9a87cc64ffb988

[ "MIT" ]

15

2021-04-03T08:28:58.000Z

2021-06-07T15:08:08.000Z

server/graph.py

Alpacron/vertex-cover

cfdace128f1578f9613e30990b9a87cc64ffb988

[ "MIT" ]

1

2021-05-21T13:16:51.000Z

import json import random class Graph: """ Graph data structure G = (V, E). Vertices contain the information about the edges. """ def __init__(self, graph=None): if graph is None: graph = {} is_weighted = graph is not None and any( True for x in graph if len(graph[x]) > 0 and isinstance(graph[x][0], list)) graph2 = {} for vertex in graph.keys(): if is_weighted: graph2.update({str(vertex): [int(e[0]) for e in graph[vertex]]}) else: graph2.update({str(vertex): [int(e) for e in graph[vertex]]}) self.graph = graph2 def __str__(self): return json.dumps(self.graph) def to_adj_matrix(self): keys = sorted(self.graph.keys()) size = len(keys) matrix = [[0] * size for _ in range(size)] for a, b in [(keys.index(str(a)), keys.index(str(b))) for a, row in self.graph.items() for b in row]: matrix[a][b] = 2 if (a == b) else 1 return matrix def generate_graph(self, n: int, p: float): """ Initialize from n vertices. """ # Add vertices for i in range(n): self.add_vertex(i) # Add edges according to probability e = [False, True] probability = [1 - p, p] for v in self.vertices(): for u in self.vertices(): if u > v and not self.is_connected(u, v) and random.choices(e, probability)[0]: self.add_edge(u, v) return self.graph def vertices(self): """ Returns a list of all vertices in the graph. """ return [int(i) for i in self.graph] def edges(self): """ Returns a list of all edges in the graph. """ edges = [] for vertex in self.graph: for neighbour in self.graph[vertex]: if not ((int(neighbour), int(vertex)) in edges or (int(vertex), int(neighbour)) in edges): edges += [(int(vertex), int(neighbour))] return edges def add_vertex(self, u: int): """ Add a vertex to the graph. """ if u not in self.vertices(): self.graph[str(u)] = [] def remove_vertex(self, u: int): """ Remove vertex from graph. """ if u in self.vertices(): del self.graph[str(u)] def add_edge(self, u: int, v: int): """ Add an edge to the graph. """ assert u in self.vertices() and v in self.vertices() self.graph[str(u)].append(v) self.graph[str(v)].append(u) def remove_edge(self, u: int, v: int): """ Remove an edge from the graph. """ assert u in self.vertices() and v in self.vertices() self.graph[str(u)].remove(v) self.graph[str(v)].remove(u) def remove_all_edges(self, v: int): if v in self.vertices(): edges = list(self.graph[str(v)]) for e in edges: self.remove_edge(e, v) def is_connected(self, u: int, v: int): """ Check if two vertices are connected. """ assert u in self.vertices() and v in self.vertices() if v not in self.graph[str(u)]: return False return True def connect_two_random_vertices(self): """ Randomly connect two vertices. """ vertices = [v for v in self.vertices() if len(self.graph[str(v)]) < len(self.vertices()) - 1] if len(vertices) > 0: v1 = random.choice(vertices) items = [v for v in vertices if v not in [v1] + self.graph[str(v1)]] if len(items) > 0: v2 = random.choice(items) if not self.is_connected(v1, v2): self.add_edge(v1, v2) def connect_vertex_to_random(self, v: int): assert v in self.vertices() vertices = [u for u in self.vertices() if len(self.graph[str(u)]) < len(self.vertices()) - 1 and u not in [v] + self.graph[str(v)]] if len(vertices) > 0: v2 = random.choice(vertices) not_connected = [u for u in vertices if len(self.graph[str(u)]) == 0] if len(not_connected) > 0: v2 = random.choice(not_connected) if not self.is_connected(v, v2): self.add_edge(v, v2) def remove_random_edge(self, v: int): vertices = [u for u in self.vertices() if u in self.graph[str(v)]] if len(vertices) > 0: self.remove_edge(v, random.choice(vertices)) def find_sub_graph(self, vertex: int, sub_graph: [int]): """ Find subgraph connected to vertex. """ for i in self.graph[str(vertex)]: if i not in sub_graph: sub_graph = self.find_sub_graph(i, sub_graph + [i]) return sub_graph def connect_all_sub_graphs(self): """ Find all disconnected sub graphs, select a random vertex in each of them and add an edge between those two vertices. """ vertex = random.choice(self.vertices()) while True: sub = self.find_sub_graph(vertex, [vertex]) if len(sub) == len(self.vertices()): break for v in self.vertices(): if v not in sub: self.add_edge(random.choice(sub), v) break def connect_two_sub_graphs(self): """ Find two disconnected sub graphs, select a random vertex in each of them and add an edge between those two vertices. """ vertices = self.vertices() vertex = random.choice(vertices) sub = self.find_sub_graph(vertex, [vertex]) for v in vertices: if v not in sub: self.add_edge(random.choice(sub), v) break def vertex_cover_brute(self, k: int, depth: int = 1, vertices: [int] = None, edges: [(int, int)] = None, best: [int] = None, best_covered: [(int, int)] = None, current: [int] = None, current_covered: [(int, int)] = None): """ Find minimum required vertices that cover all edges. """ # All edges in graph if edges is None: edges = self.edges() # All vertices in graph if vertices is None: vertices = self.vertices() # Best case result [vertex] if best is None: best = [] # Edges best vertices cover [(vertex, vertex)] if best_covered is None: best_covered = [] # Current result in recursion [vertex] if current is None: current = [] # Edges current vertices in recursion cover [(vertex, vertex)] if current_covered is None: current_covered = [] # If there are more vertices > k, return all vertices if k >= len(vertices): return vertices, edges # If current has less vertices than result and contains all edges, return if k == -1 and len(current_covered) == len(edges) and (best == [] or len(current) < len(best)): return current, current_covered # If k is equal to current and current covers more edges than best, return if k == len(current) and len(current_covered) > len(best_covered): return current, current_covered # Get all vertices that have not been covered and shuffle them ver = [u for u in vertices if len(current) == 0 or u > current[-1]] random.shuffle(ver) # Recursively do this for all vertices, until a solution is found. if (k == -1 or len(current) < k) and (best == [] or len(current) < len(best)): for v in ver: c = current_covered + [e for e in self.vertex_cover(v, depth) if not (e in current_covered or (e[1], e[0]) in current_covered)] best, best_covered = self.vertex_cover_brute(k, depth, vertices, edges, best, best_covered, current + [v], c) return best, best_covered def vertex_cover(self, v: int, reach: int = 1, current_depth: int = 0, covered: [(int, int)] = None): if covered is None: covered = [] if current_depth < reach: for u in [e for e in self.graph[str(v)] if not ((v, e) in covered or (e, v) in covered)]: covered = self.vertex_cover(u, reach, current_depth + 1, covered + [(v, u)]) return covered def increase_pendant_vertices(self): non_pendant_vertices = [u for u in self.vertices() if not self.is_pendant(u)] if len(non_pendant_vertices) > 0: v = random.choice(non_pendant_vertices) while not self.is_pendant(v): remaining_non_pendant_vertices = [u for u in self.graph[str(v)] if not self.is_pendant(u) and not u == v] if len(remaining_non_pendant_vertices) > 0: if self.degree(v) > 1: self.remove_edge(v, random.choice(remaining_non_pendant_vertices)) else: self.add_edge(v, random.choice(remaining_non_pendant_vertices)) else: if self.degree(v) > 1: self.remove_edge(v, random.choice(self.graph[str(v)])) else: self.connect_vertex_to_random(v) def decrease_pendant_vertices(self): pendant_vertices = [v for v in self.vertices() if self.is_pendant(v)] if len(pendant_vertices) > 0: vertex = random.choice(pendant_vertices) self.remove_edge(vertex, random.choice(self.graph[str(vertex)])) def increase_tops_vertices(self, k: int): non_tops_vertices = [v for v in self.vertices() if not self.is_tops(v, k)] if len(non_tops_vertices) > 0: v = random.choice(non_tops_vertices) while not self.is_tops(v, k) and self.degree(v) + 1 < len(self.vertices()): self.connect_vertex_to_random(v) def decrease_tops_vertices(self, k: int): tops_vertices = [v for v in self.vertices() if self.is_tops(v, k)] if len(tops_vertices) > 0: v = random.choice(tops_vertices) while self.is_tops(v, k) and self.degree(v) > 0: self.remove_random_edge(v) def decrease_isolated_vertices(self): isolated_vertices = [v for v in self.vertices() if self.is_isolated(v)] self.connect_vertex_to_random(random.choice(isolated_vertices)) def increase_isolated_vertices(self): non_isolated_vertices = [v for v in self.vertices() if not self.is_isolated(v)] if len(non_isolated_vertices) > 0: v = random.choice(non_isolated_vertices) self.remove_all_edges(v) def degree(self, v: int, depth: int = 1): if depth == 1: return len(self.graph[str(v)]) return len(self.vertex_cover(v, depth)) def is_isolated(self, vertex: int): return self.degree(vertex) == 0 def is_pendant(self, vertex: int): return self.degree(vertex) == 1 def is_tops(self, vertex: int, k: int): return self.degree(vertex) > k def highest_degree_vertex(self, vertices: [int] = None): if vertices is None: vertices = self.vertices() k = -1 vertex = random.choice(vertices) for v in vertices: if len(self.graph[str(v)]) > k: vertex = v return vertex def visualize_kernelization(self, k: int): isolated = [v for v in self.vertices() if self.is_isolated(v)] pendant = [v for v in self.vertices() if self.is_pendant(v)] tops = [v for v in self.vertices() if self.is_tops(v, k)] return {"isolated": isolated, "pendant": pendant, "tops": tops} def kernelization(self, k: int): covered = [] # 1. If k > 0 and v is a vertex of degree greater than k, remove v from the graph and decrease k by one. # Every vertex cover of size k must contain v, since other wise too many of its neighbours would have to # be picked to cover the incident edges. Thus, an optimal vertex cover for the original graph may be # formed from a cover of the reduced problem by adding v back to the cover. while k > 0: # Get all tops for k. tops = [v for v in self.vertices() if self.is_tops(v, k)] # If tops is not empty. if len(tops) > 0: # Remove random v from tops and decrease k by one. v = tops[0] self.remove_vertex(v) covered.append(v) k -= 1 else: break # 2. If v is an isolated vertex, remove it. Since, any v cannot cover any edges it is not a part of the # minimal vertex cover. isolated = [v for v in self.vertices() if self.is_isolated(v)] for vertex in isolated: self.remove_vertex(vertex) # 3. If more than k^2 edges remain in the graph, and neither of the previous two rules can be applied, # then the graph cannot contain a vertex cover of size k. For, after eliminating all vertices of degree # greater than k, each remaining vertex can only cover at most k edges and a set of k vertices could only # cover at most k^2 edges. In this case, the instance may be replaced by an instance with two vertices, # one edge, and k = 0, which also has no solution. if len(self.edges()) > k ** 2 and k != -1: return {}, None return self.graph, covered def approximation(self): # Initialize the empty cover. cover = [] edges = self.edges() # Consider a set of all edges in a graph. while edges: # Pick an arbitrary edges (u, v) from that set and add both u and v to the cover. u, v = random.choice(edges) cover.append(u) cover.append(v) # Remove all edges from that set that are incident on u or v. edges = [e for e in edges if e[0] is not u and e[0] is not v and e[1] is not u and e[1] is not v] # Return the result return cover def tree_approximation(self): # Initialize the empty cover cover = [] leaves = [v for v in self.vertices() if self.is_pendant(v)] parents = [node for parents in [self.graph[str(leave)] for leave in leaves] for node in parents] # While there exists leaves in the graph. while leaves: # Add all parents to the cover. for parent in parents: cover.append(parent) # Remove all leaves and their parents from the graph. for node in leaves + parents: self.remove_all_edges(node) self.remove_vertex(node) # Recalculate leaves and parents leaves = [node for node in self.vertices() if self.is_pendant(node)] parents = [node for parents in [self.graph[str(leave)] for leave in leaves] for node in parents] return cover

37.982801

113

0.559545

15,430

0.998124

0

3,129

0.202406

5a1caac07eb9f441668b6c4d0592a3fd8fa4aefc

576

py

Python

ex4.py

AyeAyeZin/python_exercises

77079dcd7809dd2967180ffd30df0166dd53edb4

[ "MIT" ]

null

ex4.py

AyeAyeZin/python_exercises

77079dcd7809dd2967180ffd30df0166dd53edb4

[ "MIT" ]

null

ex4.py

AyeAyeZin/python_exercises

77079dcd7809dd2967180ffd30df0166dd53edb4

[ "MIT" ]

null

cars=100 cars_in_space=5 drivers=20 pasengers=70 car_not_driven=cars-drivers cars_driven=drivers carpool_capacity=cars_driven*space_in_a_car average_passengers_percar=passengers/cars_driven print("There are", cars,"cars availble") print("There are only",drivers,"drivers availble") print("There will be",car_not_driven,"empty cars today") print("There are",cars_in_space,"space availble in car") print("We can transport",carpool_capacity,"peopletoday.") print("We have", passengers,"to carpool today.") print("We need to put about", average_passengers_per_car,"in each car.")

36

72

0.805556

0

223

0.387153

5a1cb185553a265ef90a6017854334865e3cc339

304

py

Python

python_docs/05Functions/01Definition.py

Matheus-IT/lang-python-related

dd2e5d9b9f16d3838ba1670fdfcba1fa3fe305e9

[ "MIT" ]

null

python_docs/05Functions/01Definition.py

Matheus-IT/lang-python-related

dd2e5d9b9f16d3838ba1670fdfcba1fa3fe305e9

[ "MIT" ]

null

python_docs/05Functions/01Definition.py

Matheus-IT/lang-python-related

dd2e5d9b9f16d3838ba1670fdfcba1fa3fe305e9

[ "MIT" ]

null

# Definição de função def soma(a2, b2): # Os parâmetros aqui precisam ter outro nome print(f'A = {a2} e B = {b2}') s = a2 + b2 print(f'A soma vale A + B = {s}') # Programa principal a = int(input('Digite um valor para A: ')) b = int(input('Digite um valor para B: ')) soma(a, b)

25.333333

63

0.582237

0

193

0.624595

5a1d0c02ec27af98a78a24a6f4e896b2268b6a0f

852

py

Python

python/number.py

Dahercode/datalumni-test

9587400bddafd1c32e97655727c5d3dbbfd17574

[ "MIT" ]

1

2020-02-18T16:56:38.000Z

python/number.py

Dahercode/datalumni-test

9587400bddafd1c32e97655727c5d3dbbfd17574

[ "MIT" ]

null

python/number.py

Dahercode/datalumni-test

9587400bddafd1c32e97655727c5d3dbbfd17574

[ "MIT" ]

null

# Your code goes here tab=[] for i in range(1000) : tab.append(i) tab2=[] for i in range(len(tab)): if sum([ int(c) for c in str(tab[i]) ]) <= 10: tab2.append(tab[i]) tab3=[] for i in range(len(tab2)): a=str(tab2[i]) if a[len(a)-2] == '4': tab3.append(tab2[i]) tab4=[] for i in range(len(tab3)): if len(str(tab3[i]))>=2 : tab4.append(tab3[i]) tab5=[] for i in range(len(tab4)): a=str(tab4[i]) if a.find('7')==-1 and a.find('1')==-1: tab5.append(tab4[i]) tab6=[] for i in range(len(tab5)): a=str(tab5[i]) if ((int(a[0])+int(a[1]))%2) != 0: tab6.append(tab5[i]) tab7=[] for i in range(len(tab6)): a=str(tab6[i]) if str(len(a)) == a[len(a)-1]: tab7.append(tab6[i]) print(tab7) mystery_number=tab7[0] print(f'Le nombre mystère est le : {mystery_number}')

18.933333

53

0.543427

0

77

0.09027

5a1d385aaac2b104c89e97a052215f1dccd44141

3,885

py

Python

backend/src/baserow/contrib/database/migrations/0016_token_tokenpermission.py

ashishdhngr/baserow

b098678d2165eb7c42930ee24dc6753a3cb520c3

[ "MIT" ]

null

backend/src/baserow/contrib/database/migrations/0016_token_tokenpermission.py

ashishdhngr/baserow

b098678d2165eb7c42930ee24dc6753a3cb520c3

[ "MIT" ]

null

backend/src/baserow/contrib/database/migrations/0016_token_tokenpermission.py

ashishdhngr/baserow

b098678d2165eb7c42930ee24dc6753a3cb520c3

[ "MIT" ]

null

# Generated by Django 2.2.11 on 2020-10-23 08:35 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), ("core", "0001_initial"), ("database", "0015_emailfield"), ] operations = [ migrations.CreateModel( name="Token", fields=[ ( "id", models.AutoField( auto_created=True, primary_key=True, serialize=False, verbose_name="ID", ), ), ( "name", models.CharField( max_length=100, help_text="The human readable name of the token for the user.", ), ), ( "key", models.CharField( db_index=True, max_length=32, unique=True, help_text="The unique token key that can be used to authorize " "for the table row endpoints.", ), ), ("created", models.DateTimeField(auto_now=True)), ( "group", models.ForeignKey( on_delete=django.db.models.deletion.CASCADE, to="core.Group", help_text="Only the tables of the group can be accessed.", ), ), ( "user", models.ForeignKey( on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL, help_text="The user that owns the token.", ), ), ], options={ "ordering": ("id",), }, ), migrations.CreateModel( name="TokenPermission", fields=[ ( "id", models.AutoField( auto_created=True, primary_key=True, serialize=False, verbose_name="ID", ), ), ( "type", models.CharField( choices=[ ("create", "Create"), ("read", "Read"), ("update", "Update"), ("delete", "Delete"), ], max_length=6, ), ), ( "database", models.ForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to="database.Database", ), ), ( "table", models.ForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to="database.Table", ), ), ( "token", models.ForeignKey( on_delete=django.db.models.deletion.CASCADE, to="database.Token" ), ), ], ), ]

32.647059

88

0.344916

3,725

0.958816

0

548

0.141055

5a1f561a631ec5529e54bc7090d1958be5eb6f6f

1,639

py

Python

setup.py

davidharvey1986/rrg

26b4658f14279af21af1a61d57e9936daf315a71

[ "MIT" ]

2

2019-11-18T12:51:09.000Z

2019-12-11T03:13:51.000Z

setup.py

davidharvey1986/rrg

26b4658f14279af21af1a61d57e9936daf315a71

[ "MIT" ]

5

2017-06-09T10:06:27.000Z

2019-07-19T11:28:18.000Z

setup.py

davidharvey1986/rrg

26b4658f14279af21af1a61d57e9936daf315a71

[ "MIT" ]

2

2017-07-19T15:48:33.000Z

2017-08-09T16:07:20.000Z

#!/usr/local/bin/python3 import sys,os,string,glob,subprocess from setuptools import setup,Extension from setuptools.command.build_ext import build_ext from setuptools.command.install import install import numpy long_description = """\ This module uses the RRG method to measure the shapes of galaxies in Hubble Space Telescope data """ #sudo python3 setup.py sdist upload -r pypi version='0.1.2' INCDIRS=['.'] packages = ['pyRRG', 'RRGtools','asciidata'] package_dir = {'RRGtools':'./lib/RRGtools', 'pyRRG':'./src', 'asciidata':'./lib/asciidata'} package_data = {'pyRRG': ['psf_lib/*/*','sex_files/*','*.pkl']} setup ( name = "pyRRG", version = version, author = "David Harvey", author_email = "david.harvey@epfl.ch", description = "pyRRG module", license = 'MIT', packages = packages, package_dir = package_dir, package_data = package_data, scripts = ['scripts/pyRRG'], url = 'https://github.com/davidharvey1986/pyRRG', # use the URL to the github repo download_url = 'https://github.com/davidharvey1986/pyRRG/archive/'+version+'.tar.gz', install_requires=['scikit-learn',\ 'numpy', \ 'ipdb', 'pyraf',\ 'scipy'], )

32.78

101

0.494814

0

626

0.38194

5a2032ec76e617ec97b415d06f3a42408d534a65

635

py

Python

restbed/core/api.py

mr-tenders/restbed

68d36536286203048ce01f1467d3db7ee108bebb

[ "MIT" ]

null

restbed/core/api.py

mr-tenders/restbed

68d36536286203048ce01f1467d3db7ee108bebb

[ "MIT" ]

null

restbed/core/api.py

mr-tenders/restbed

68d36536286203048ce01f1467d3db7ee108bebb

[ "MIT" ]

null

""" restbed core api """ import pyinsane2 from typing import List class CoreApi(object): scanner: pyinsane2.Scanner = None scan_session: pyinsane2.ScanSession = None @staticmethod def initialize(): """ initialize SANE, don't call if unit testing (well that's the hope...) """ pyinsane2.init() def select_device(self): devs: List[pyinsane2.Scanner] = pyinsane2.get_devices() self.scanner = devs[0] return self.scanner def start_scanning(self): pyinsane2.maximize_scan_area(self.scanner) self.scan_session = self.scanner.scan()

22.678571

63

0.63937

566

0.891339

0

170

0.267717

0

125

0.19685

5a20458f16a895f14563ad81b494f0d3c1292dbf

736

py

Python

secure_notes_client/thread_pool.py

rlee287/secure-notes-client

56d5fcce1d2eeb46de22aac63131fe7214b6f185

[ "MIT" ]

null

secure_notes_client/thread_pool.py

rlee287/secure-notes-client

56d5fcce1d2eeb46de22aac63131fe7214b6f185

[ "MIT" ]

4

2019-07-10T01:34:12.000Z

2019-08-20T01:52:31.000Z

secure_notes_client/thread_pool.py

rlee287/secure-notes-client

56d5fcce1d2eeb46de22aac63131fe7214b6f185

[ "MIT" ]

null

from concurrent.futures import ThreadPoolExecutor import time from PySide2.QtCore import QCoreApplication thread_pool=None def init_thread_pool(): global thread_pool thread_pool=ThreadPoolExecutor() def deinit_thread_pool(): global thread_pool thread_pool.shutdown() def submit_task(function,*args,**kwargs): global thread_pool return thread_pool.submit(function,*args,**kwargs) #TODO: find a less hacky way to keep events processed def async_run_await_result(function,*args,**kwargs): future_obj=thread_pool.submit(function,*args,**kwargs) while not future_obj.done(): QCoreApplication.processEvents() time.sleep(0.1) future_result=future_obj.result() return future_result

26.285714

58

0.762228

0

53

0.072011

5a2274118fccaff1a7fc9becbc4b24e208209e91

10,463

py

Python

Fairness_attack/data_utils.py

Ninarehm/attack

0d5a6b842d4e81484540151d879036e9fe2184f1

[ "MIT" ]

8

2021-03-08T17:13:42.000Z

2022-03-31T00:57:53.000Z

Fairness_attack/data_utils.py

lutai14/attack

773024c7b86be112521a2243f2f809a54891c81f

[ "MIT" ]

null

Fairness_attack/data_utils.py

lutai14/attack

773024c7b86be112521a2243f2f809a54891c81f

[ "MIT" ]

1

2022-02-10T22:36:11.000Z

from __future__ import division from __future__ import print_function from __future__ import absolute_import from __future__ import unicode_literals import json import numpy as np import scipy.sparse as sparse import defenses import upper_bounds class NumpyEncoder(json.JSONEncoder): def default(self, obj): if isinstance(obj, np.ndarray): assert len(np.shape(obj)) == 1 # Can only handle 1D ndarrays return obj.tolist() elif isinstance(obj, np.floating): return float(obj) elif isinstance(obj, np.int16): return str(obj) else: return super(NumpyEncoder, self).default(obj) def get_class_map(): return {-1: 0, 1: 1} def get_centroids(X, Y, class_map): num_classes = len(set(Y)) num_features = X.shape[1] centroids = np.zeros((num_classes, num_features)) for y in set(Y): centroids[class_map[y], :] = np.mean(X[Y == y, :], axis=0) return centroids def get_centroid_vec(centroids): assert centroids.shape[0] == 2 centroid_vec = centroids[0, :] - centroids[1, :] centroid_vec /= np.linalg.norm(centroid_vec) centroid_vec = np.reshape(centroid_vec, (1, -1)) return centroid_vec # Can speed this up if necessary def get_sqrt_inv_cov(X, Y, class_map): num_classes = len(set(Y)) num_features = X.shape[1] sqrt_inv_covs = np.zeros((num_classes, num_features, num_features)) for y in set(Y): cov = np.cov(X[Y == y, :], rowvar=False) U_cov, S_cov, _ = np.linalg.svd(cov + 1e-6 * np.eye(num_features)) print(' min eigenvalue of cov after 1e-6 reg is %s' % np.min(S_cov)) sqrt_inv_covs[class_map[y], ...] = U_cov.dot(np.diag(1 / np.sqrt(S_cov)).dot(U_cov.T)) return sqrt_inv_covs # Can speed this up if necessary def get_data_params(X, Y, percentile): num_classes = len(set(Y)) num_features = X.shape[1] centroids = np.zeros((num_classes, num_features)) class_map = get_class_map() centroids = get_centroids(X, Y, class_map) # Get radii for sphere sphere_radii = np.zeros(2) dists = defenses.compute_dists_under_Q( X, Y, Q=None, centroids=centroids, class_map=class_map, norm=2) for y in set(Y): sphere_radii[class_map[y]] = np.percentile(dists[Y == y], percentile) # Get vector between centroids centroid_vec = get_centroid_vec(centroids) # Get radii for slab slab_radii = np.zeros(2) for y in set(Y): dists = np.abs( (X[Y == y, :].dot(centroid_vec.T) - centroids[class_map[y], :].dot(centroid_vec.T))) slab_radii[class_map[y]] = np.percentile(dists, percentile) return class_map, centroids, centroid_vec, sphere_radii, slab_radii def vstack(A, B): if (sparse.issparse(A) or sparse.issparse(B)): return sparse.vstack((A, B), format='csr') else: return np.concatenate((A, B), axis=0) def add_points(x, y, X, Y, num_copies=1): if num_copies == 0: return X, Y x = np.array(x).reshape(-1) if sparse.issparse(X): X_modified = sparse.vstack(( X, sparse.csr_matrix( np.tile(x, num_copies).reshape(-1, len(x))))) else: X_modified = np.append( X, np.tile(x, num_copies).reshape(-1, len(x)), axis=0) Y_modified = np.append(Y, np.tile(y, num_copies)) return X_modified, Y_modified def copy_random_points(X, Y, mask_to_choose_from=None, target_class=1, num_copies=1, random_seed=18, replace=False): # Only copy from points where mask_to_choose_from == True np.random.seed(random_seed) combined_mask = (np.array(Y, dtype=int) == target_class) if mask_to_choose_from is not None: combined_mask = combined_mask & mask_to_choose_from idx_to_copy = np.random.choice( np.where(combined_mask)[0], size=num_copies, replace=replace) if sparse.issparse(X): X_modified = sparse.vstack((X, X[idx_to_copy, :])) else: X_modified = np.append(X, X[idx_to_copy, :], axis=0) Y_modified = np.append(Y, Y[idx_to_copy]) return X_modified, Y_modified def threshold(X): return np.clip(X, 0, np.max(X)) def rround(X, random_seed=3, return_sparse=True): if sparse.issparse(X): X = X.toarray() X_frac, X_int = np.modf(X) X_round = X_int + (np.random.random_sample(X.shape) < X_frac) if return_sparse: return sparse.csr_matrix(X_round) else: return X_round def rround_with_repeats(X, Y, repeat_points, random_seed=3, return_sparse=True): X_round = rround(X, random_seed=random_seed, return_sparse=return_sparse) assert Y.shape[0] == X.shape[0] if repeat_points > 1: pos_idx = 0 neg_idx = 0 for i in range(X_round.shape[0]): if Y[i] == 1: if pos_idx % repeat_points == 0: last_pos_x = X_round[i, :] else: X_round[i, :] = last_pos_x pos_idx += 1 else: if neg_idx % repeat_points == 0: last_neg_x = X_round[i, :] else: X_round[i, :] = last_neg_x neg_idx += 1 return X_round def project_onto_sphere(X, Y, radii, centroids, class_map): for y in set(Y): idx = class_map[y] radius = radii[idx] centroid = centroids[idx, :] shifts_from_center = X[Y == y, :] - centroid dists_from_center = np.linalg.norm(shifts_from_center, axis=1) shifts_from_center[dists_from_center > radius, :] *= radius / np.reshape(dists_from_center[dists_from_center > radius], (-1, 1)) X[Y == y, :] = shifts_from_center + centroid print("Number of (%s) points projected onto sphere: %s" % (y, np.sum(dists_from_center > radius))) return X def project_onto_slab(X, Y, v, radii, centroids, class_map): """ v^T x needs to be within radius of v^T centroid. v is 1 x d and normalized. """ v = np.reshape(v / np.linalg.norm(v), (1, -1)) for y in set(Y): idx = class_map[y] radius = radii[idx] centroid = centroids[idx, :] # If v^T x is too large, then dists_along_v is positive # If it's too small, then dists_along_v is negative dists_along_v = (X[Y == y, :] - centroid).dot(v.T) shifts_along_v = np.reshape( dists_along_v - np.clip(dists_along_v, -radius, radius), (1, -1)) X[Y == y, :] -= shifts_along_v.T.dot(v) print("Number of (%s) points projected onto slab: %s" % (y, np.sum(np.abs(dists_along_v) > radius))) return X def get_projection_fn( X_clean, Y_clean, sphere=True, slab=True, non_negative=False, less_than_one=False, use_lp_rounding=False, percentile=90): print(X_clean) goal = 'find_nearest_point' class_map, centroids, centroid_vec, sphere_radii, slab_radii = get_data_params(X_clean, Y_clean, percentile) if use_lp_rounding or non_negative or less_than_one or (sphere and slab): if use_lp_rounding: projector = upper_bounds.Minimizer( d=X_clean.shape[1], use_sphere=sphere, use_slab=slab, non_negative=non_negative, less_than_one=less_than_one, constrain_max_loss=False, goal=goal, X=X_clean ) projector = upper_bounds.Minimizer( d=X_clean.shape[1], use_sphere=sphere, use_slab=slab, non_negative=non_negative, less_than_one=less_than_one, constrain_max_loss=False, goal=goal, X=X_clean ) else: projector = upper_bounds.Minimizer( d=X_clean.shape[1], use_sphere=sphere, use_slab=slab, non_negative=non_negative, less_than_one=less_than_one, constrain_max_loss=False, goal=goal ) # Add back low-rank projection if we move back to just sphere+slab def project_onto_feasible_set( X, Y, theta=None, bias=None, ): num_examples = X.shape[0] proj_X = np.zeros_like(X) for idx in range(num_examples): x = X[idx, :] y = Y[idx] class_idx = class_map[y] centroid = centroids[class_idx, :] sphere_radius = sphere_radii[class_idx] slab_radius = slab_radii[class_idx] proj_X[idx, :] = projector.minimize_over_feasible_set( None, x, centroid, centroid_vec, sphere_radius, slab_radius) num_projected = np.sum(np.max(X - proj_X, axis=1) > 1e-6) print('Projected %s examples.' % num_projected) return proj_X else: def project_onto_feasible_set(X, Y, theta=None, bias=None): if sphere: X = project_onto_sphere(X, Y, sphere_radii, centroids, class_map) elif slab: X = project_onto_slab(X, Y, centroid_vec, slab_radii, centroids, class_map) return X return project_onto_feasible_set def filter_points_outside_feasible_set(X, Y, centroids, centroid_vec, sphere_radii, slab_radii, class_map): sphere_dists = defenses.compute_dists_under_Q( X, Y, Q=None, centroids=centroids, class_map=class_map) slab_dists = defenses.compute_dists_under_Q( X, Y, Q=centroid_vec, centroids=centroids, class_map=class_map) idx_to_keep = np.array([True] * X.shape[0]) for y in set(Y): idx_to_keep[np.where(Y == y)[0][sphere_dists[Y == y] > sphere_radii[class_map[y]]]] = False idx_to_keep[np.where(Y == y)[0][slab_dists[Y == y] > slab_radii[class_map[y]]]] = False print(np.sum(idx_to_keep)) return X[idx_to_keep, :], Y[idx_to_keep]

31.610272

136

0.581

423

0.040428

0

682

0.065182

5a23d3f4e52679a350233bbde834e4fd8f3310ec

74

py

Python

pytracetable/__init__.py

filwaitman/pytracetable

eb884953e179fc65677a9e3b3c70fde1b1439ccb

[ "MIT" ]

1

2016-02-10T20:28:00.000Z

pytracetable/__init__.py

filwaitman/pytracetable

eb884953e179fc65677a9e3b3c70fde1b1439ccb

[ "MIT" ]

1

2020-05-27T18:12:10.000Z

pytracetable/__init__.py

filwaitman/pytracetable

eb884953e179fc65677a9e3b3c70fde1b1439ccb

[ "MIT" ]

null

from pytracetable.core import tracetable __all__ = [ 'tracetable', ]

12.333333

40

0.716216

0

12

0.162162

5a24938eab3876854f2631917fd72abe26cefe64

1,518

py

Python

quandl_data_retriever/server.py

fabiomolinar/quandl-data-retriever

d9359922cb222ac519f7d9e4dd892bbcf6b1b2d0

[ "MIT" ]

null

quandl_data_retriever/server.py

fabiomolinar/quandl-data-retriever

d9359922cb222ac519f7d9e4dd892bbcf6b1b2d0

[ "MIT" ]

null

quandl_data_retriever/server.py

fabiomolinar/quandl-data-retriever

d9359922cb222ac519f7d9e4dd892bbcf6b1b2d0

[ "MIT" ]

null

""" Server module Quandl API limits: Authenticated users have a limit of 300 calls per 10 seconds, 2,000 calls per 10 minutes and a limit of 50,000 calls per day. """ import urllib import logging from twisted.internet import reactor from twisted.web.client import Agent, readBody from . import settings from . import resources logger = logging.getLogger(settings.LOG_NAME + ".server") def main(): from .data import data_list try: resource_name = data_list[0]["resource"] resource = resources.__dict__[resource_name] key = data_list[0]["api_key"] key = settings.__dict__[key] resource = resource(key) except KeyError as e: logger.warning("KeyError while trying to instantiate Resource class with : " + str(e)) else: # TODO: go to next item pass url = resource.get_url(data_list[0]["url"]) agent = Agent(reactor) d = agent.request( str.encode(data_list[0]["method"], "utf-8"), str.encode(url, "ascii") ) def cbResponse(response): if response.code == 200: def cbBody(body): resource.save(body) pass d = readBody(response) d.addCallback(cbBody) return d d.addCallback(cbResponse) def cbShutdown(ignored): if not ignored: logger.warning("request failed.") reactor.stop() d.addBoth(cbShutdown) reactor.run() if __name__ == "__main__": main()

26.172414

94

0.614625

0

334

0.220026

5a24a53e97cdff184ba28a85fbb3b5ee4e244277

4,696

py

Python

actingweb/deprecated_db_gae/db_subscription_diff.py

gregertw/actingweb

e1c8f66451f547c920c64c4e2a702698e3a0d299

[ "BSD-3-Clause" ]

null

actingweb/deprecated_db_gae/db_subscription_diff.py

gregertw/actingweb

e1c8f66451f547c920c64c4e2a702698e3a0d299

[ "BSD-3-Clause" ]

null

actingweb/deprecated_db_gae/db_subscription_diff.py

gregertw/actingweb

e1c8f66451f547c920c64c4e2a702698e3a0d299

[ "BSD-3-Clause" ]

null

from builtins import object from google.appengine.ext import ndb import logging """ DbSubscriptionDiff handles all db operations for a subscription diff DbSubscriptionDiffList handles list of subscriptions diffs Google datastore for google is used as a backend. """ __all__ = [ 'DbSubscriptionDiff', 'DbSubscriptionDiffList', ] class SubscriptionDiff(ndb.Model): id = ndb.StringProperty(required=True) subid = ndb.StringProperty(required=True) timestamp = ndb.DateTimeProperty(auto_now_add=True) diff = ndb.TextProperty() seqnr = ndb.IntegerProperty() class DbSubscriptionDiff(object): """ DbSubscriptionDiff does all the db operations for subscription diff objects The actor_id must always be set. """ def get(self, actor_id=None, subid=None, seqnr=None): """ Retrieves the subscriptiondiff from the database """ if not actor_id and not self.handle: return None if not subid and not self.handle: logging.debug("Attempt to get subscriptiondiff without subid") return None if not self.handle: if not seqnr: self.handle = SubscriptionDiff.query(SubscriptionDiff.id == actor_id, SubscriptionDiff.subid == subid ).get() else: self.handle = SubscriptionDiff.query(SubscriptionDiff.id == actor_id, SubscriptionDiff.subid == subid, SubscriptionDiff.seqnr == seqnr ).get() if self.handle: t = self.handle return { "id": t.id, "subscriptionid": t.subid, "timestamp": t.timestamp, "data": t.diff, "sequence": t.seqnr, } else: return None def create(self, actor_id=None, subid=None, diff=None, seqnr=None): """ Create a new subscription diff """ if not actor_id or not subid: logging.debug("Attempt to create subscriptiondiff without actorid or subid") return False if not seqnr: seqnr = 1 if not diff: diff = '' self.handle = SubscriptionDiff(id=actor_id, subid=subid, diff=diff, seqnr=seqnr) self.handle.put(use_cache=False) return True def delete(self): """ Deletes the subscription diff in the database """ if not self.handle: return False self.handle.key.delete() self.handle = None return True def __init__(self): self.handle = None class DbSubscriptionDiffList(object): """ DbSubscriptionDiffList does all the db operations for list of diff objects The actor_id must always be set. """ def fetch(self, actor_id=None, subid=None): """ Retrieves the subscription diffs of an actor_id from the database as an array""" if not actor_id: return None if not subid: self.handle = SubscriptionDiff.query(SubscriptionDiff.id == actor_id).order(SubscriptionDiff.seqnr).fetch(use_cache=False) else: self.handle = SubscriptionDiff.query(SubscriptionDiff.id == actor_id, SubscriptionDiff.subid == subid).order(SubscriptionDiff.seqnr).fetch(use_cache=False) self.diffs = [] if self.handle: for t in self.handle: self.diffs.append( { "id": t.id, "subscriptionid": t.subid, "timestamp": t.timestamp, "diff": t.diff, "sequence": t.seqnr, }) return self.diffs else: return [] def delete(self, seqnr=None): """ Deletes all the fetched subscription diffs in the database Optional seqnr deletes up to (excluding) a specific seqnr """ if not self.handle: return False if not seqnr or not isinstance(seqnr, int): seqnr = 0 for p in self.handle: if seqnr == 0 or p.seqnr <= seqnr: p.key.delete() self.handle = None return True def __init__(self): self.handle = None

33.304965

134

0.5296

4,336

0.923339

0

1,098

0.233816

5a24c50dca0ab02ce229e044f402eb5085a1288a

1,703

py

Python

azure-mgmt-iothub/azure/mgmt/iothub/models/ip_filter_rule.py

JonathanGailliez/azure-sdk-for-python

f0f051bfd27f8ea512aea6fc0c3212ee9ee0029b

[ "MIT" ]

1

2021-09-07T18:36:04.000Z

azure-mgmt-iothub/azure/mgmt/iothub/models/ip_filter_rule.py

JonathanGailliez/azure-sdk-for-python

f0f051bfd27f8ea512aea6fc0c3212ee9ee0029b

[ "MIT" ]

2

2019-10-02T23:37:38.000Z

2020-10-02T01:17:31.000Z

azure-mgmt-iothub/azure/mgmt/iothub/models/ip_filter_rule.py

JonathanGailliez/azure-sdk-for-python

f0f051bfd27f8ea512aea6fc0c3212ee9ee0029b

[ "MIT" ]

1

2019-06-17T22:18:23.000Z

# coding=utf-8 # -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for # license information. # # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is # regenerated. # -------------------------------------------------------------------------- from msrest.serialization import Model class IpFilterRule(Model): """The IP filter rules for the IoT hub. All required parameters must be populated in order to send to Azure. :param filter_name: Required. The name of the IP filter rule. :type filter_name: str :param action: Required. The desired action for requests captured by this rule. Possible values include: 'Accept', 'Reject' :type action: str or ~azure.mgmt.iothub.models.IpFilterActionType :param ip_mask: Required. A string that contains the IP address range in CIDR notation for the rule. :type ip_mask: str """ _validation = { 'filter_name': {'required': True}, 'action': {'required': True}, 'ip_mask': {'required': True}, } _attribute_map = { 'filter_name': {'key': 'filterName', 'type': 'str'}, 'action': {'key': 'action', 'type': 'IpFilterActionType'}, 'ip_mask': {'key': 'ipMask', 'type': 'str'}, } def __init__(self, **kwargs): super(IpFilterRule, self).__init__(**kwargs) self.filter_name = kwargs.get('filter_name', None) self.action = kwargs.get('action', None) self.ip_mask = kwargs.get('ip_mask', None)

36.234043

77

0.603641

1,187

0.697005

0

1,225

0.719319

5a29b2a7e94aa859d4fcd87428416a71deaf7e01

551

py

Python

4344.py

yzkim9501/Baekjoon

222e55d0bd65cbb66f1f5486652ad8c697817844

[ "Unlicense" ]

null

4344.py

yzkim9501/Baekjoon

222e55d0bd65cbb66f1f5486652ad8c697817844

[ "Unlicense" ]

null

4344.py

yzkim9501/Baekjoon

222e55d0bd65cbb66f1f5486652ad8c697817844

[ "Unlicense" ]

null

# 대학생 새내기들의 90%는 자신이 반에서 평균은 넘는다고 생각한다. 당신은 그들에게 슬픈 진실을 알려줘야 한다. # 첫째 줄에는 테스트 케이스의 개수 C가 주어진다. # 둘째 줄부터 각 테스트 케이스마다 학생의 수 N(1 ≤ N ≤ 1000, N은 정수)이 첫 수로 주어지고, 이어서 N명의 점수가 주어진다. 점수는 0보다 크거나 같고, 100보다 작거나 같은 정수이다. # 각 케이스마다 한 줄씩 평균을 넘는 학생들의 비율을 반올림하여 소수점 셋째 자리까지 출력한다. def avg(l): s=0 for i in l: s+=i return((s-l[0])/l[0]) t=int(input()) for _ in range(t): a=list(map(int,input().split())) c=0 for j in range(1,a[0]+1): if a[j]>avg(a): c+=1 print(str('{:,.3f}'.format(round(c/a[0]*100,3)))+"%")

25.045455

114

0.555354

0

605

0.685164

5a29f8551225fbef514f169502222d4f73af2984

4,531

py

Python

tests/dualtor/test_standby_tor_upstream_mux_toggle.py

AndoniSanguesa/sonic-mgmt

bac8b9bf7c51008ceab75e83ce68fa9473a7d2ec

[ "Apache-2.0" ]

1

2021-09-24T08:40:57.000Z

tests/dualtor/test_standby_tor_upstream_mux_toggle.py

AndoniSanguesa/sonic-mgmt

bac8b9bf7c51008ceab75e83ce68fa9473a7d2ec

[ "Apache-2.0" ]

null

tests/dualtor/test_standby_tor_upstream_mux_toggle.py

AndoniSanguesa/sonic-mgmt

bac8b9bf7c51008ceab75e83ce68fa9473a7d2ec

[ "Apache-2.0" ]

null

import pytest import logging import ipaddress import json import re import time from tests.common.dualtor.dual_tor_mock import * from tests.common.helpers.assertions import pytest_assert as pt_assert from tests.common.dualtor.dual_tor_utils import rand_selected_interface, verify_upstream_traffic, get_crm_nexthop_counter from tests.common.utilities import compare_crm_facts from tests.common.config_reload import config_reload from tests.common.dualtor.mux_simulator_control import toggle_all_simulator_ports from tests.common.fixtures.ptfhost_utils import change_mac_addresses, run_garp_service, run_icmp_responder logger = logging.getLogger(__file__) pytestmark = [ pytest.mark.topology('t0'), pytest.mark.usefixtures('apply_mock_dual_tor_tables', 'apply_mock_dual_tor_kernel_configs', 'run_garp_service', 'run_icmp_responder') ] PAUSE_TIME = 10 def get_l2_rx_drop(host, itfs): """ Return L2 rx packet drop counter for given interface """ res = {} stdout = host.shell("portstat -j")['stdout'] match = re.search("Last cached time was.*\n", stdout) if match: stdout = re.sub("Last cached time was.*\n", "", stdout) data = json.loads(stdout) return int(data[itfs]['RX_DRP']) def clear_portstat(dut): dut.shell("portstat -c") @pytest.fixture(scope='module', autouse=True) def test_cleanup(rand_selected_dut): """ Issue a config reload at the end of module """ yield config_reload(rand_selected_dut) def test_standby_tor_upstream_mux_toggle( rand_selected_dut, tbinfo, ptfadapter, rand_selected_interface, require_mocked_dualtor, toggle_all_simulator_ports, set_crm_polling_interval): itfs, ip = rand_selected_interface PKT_NUM = 100 # Step 1. Set mux state to standby and verify traffic is dropped by ACL rule and drop counters incremented set_mux_state(rand_selected_dut, tbinfo, 'standby', [itfs], toggle_all_simulator_ports) # Wait sometime for mux toggle time.sleep(PAUSE_TIME) crm_facts0 = rand_selected_dut.get_crm_facts() # Verify packets are not go up verify_upstream_traffic(host=rand_selected_dut, ptfadapter=ptfadapter, tbinfo=tbinfo, itfs=itfs, server_ip=ip['server_ipv4'].split('/')[0], pkt_num=PKT_NUM, drop=True) time.sleep(5) # Verify dropcounter is increased drop_counter = get_l2_rx_drop(rand_selected_dut, itfs) pt_assert(drop_counter >= PKT_NUM, "RX_DRP for {} is expected to increase by {} actually {}".format(itfs, PKT_NUM, drop_counter)) # Step 2. Toggle mux state to active, and verify traffic is not dropped by ACL and fwd-ed to uplinks; verify CRM show and no nexthop objects are stale set_mux_state(rand_selected_dut, tbinfo, 'active', [itfs], toggle_all_simulator_ports) # Wait sometime for mux toggle time.sleep(PAUSE_TIME) # Verify packets are not go up verify_upstream_traffic(host=rand_selected_dut, ptfadapter=ptfadapter, tbinfo=tbinfo, itfs=itfs, server_ip=ip['server_ipv4'].split('/')[0], pkt_num=PKT_NUM, drop=False) # Step 3. Toggle mux state to standby, and verify traffic is dropped by ACL; verify CRM show and no nexthop objects are stale set_mux_state(rand_selected_dut, tbinfo, 'standby', [itfs], toggle_all_simulator_ports) # Wait sometime for mux toggle time.sleep(PAUSE_TIME) # Verify packets are not go up again verify_upstream_traffic(host=rand_selected_dut, ptfadapter=ptfadapter, tbinfo=tbinfo, itfs=itfs, server_ip=ip['server_ipv4'].split('/')[0], pkt_num=PKT_NUM, drop=True) # Verify dropcounter is increased drop_counter = get_l2_rx_drop(rand_selected_dut, itfs) pt_assert(drop_counter >= PKT_NUM, "RX_DRP for {} is expected to increase by {} actually {}".format(itfs, PKT_NUM, drop_counter)) crm_facts1 = rand_selected_dut.get_crm_facts() unmatched_crm_facts = compare_crm_facts(crm_facts0, crm_facts1) pt_assert(len(unmatched_crm_facts)==0, 'Unmatched CRM facts: {}'.format(json.dumps(unmatched_crm_facts, indent=4)))

41.568807

154

0.670492

0

146

0.032222

192

0.042375

0

1,182

0.26087

5a2a01adbfb1b632775069e902a5a1facd9c2f69

3,308

py

Python

birdsong_recognition/dataset.py

YingyingF/birdsong_recognition

4f8a2ccb900898a02d4454a5f1c206125f23fa44

[ "Apache-2.0" ]

null

birdsong_recognition/dataset.py

YingyingF/birdsong_recognition

4f8a2ccb900898a02d4454a5f1c206125f23fa44

[ "Apache-2.0" ]

null

birdsong_recognition/dataset.py

YingyingF/birdsong_recognition

4f8a2ccb900898a02d4454a5f1c206125f23fa44

[ "Apache-2.0" ]

null

# AUTOGENERATED! DO NOT EDIT! File to edit: dataset.ipynb (unless otherwise specified). __all__ = ['load_mp3', 'get_sample_label', 'preprocess_file', 'pad_by_zeros', 'split_file_by_window_size', 'wrapper_split_file_by_window_size', 'create_dataset_fixed_size', 'get_spectrogram', 'add_channel_dim'] # Cell def load_mp3(file): sample = tf.io.read_file(file) sample_audio = tfio.audio.decode_mp3(sample) return sample_audio # Cell def get_sample_label(file): sample = load_mp3(file) label = tf.argmax(tf.strings.split(file, '/')[1] == np.array(ebirds)) return sample, label # Cell def preprocess_file(sample_audio, label): # Only look at the first channel sample_audio = sample_audio[:,0] sample_audio_scaled = (sample_audio - tf.math.reduce_min(sample_audio))/(tf.math.reduce_max(sample_audio) - tf.math.reduce_min(sample_audio)) sample_audio_scaled = 2*(sample_audio_scaled - 0.5) return sample_audio_scaled, label # Cell def pad_by_zeros(sample, min_file_size, last_sample_size): padding_size = min_file_size - last_sample_size sample_padded = tf.pad(sample, paddings=[[tf.constant(0), padding_size]]) return sample_padded # Cell def split_file_by_window_size(sample, label): # number of subsamples given none overlapping window size. subsample_count = int(np.round(sample.shape[0]/min_file_size)) # ignore extremely long files for now subsample_limit = 75 if subsample_count <= subsample_limit: # if the last sample is at least half the window size, then pad it, if not, clip it. last_sample_size = sample.shape[0]%min_file_size if last_sample_size/min_file_size > 0.5: sample = pad_by_zeros(sample, min_file_size, last_sample_size) else: sample = sample[:subsample_count*min_file_size] sample = tf.reshape(sample, shape=[subsample_count, min_file_size]) label = tf.pad(tf.expand_dims(label, axis=0), paddings=[[0, subsample_count-1]], constant_values=label.numpy()) else: sample = tf.reshape(sample[:subsample_limit*min_file_size], shape=[subsample_limit, min_file_size]) label = tf.pad(tf.expand_dims(label, axis=0), paddings=[[0, 74]], constant_values=label.numpy()) return sample, label # Cell def wrapper_split_file_by_window_size(sample, label): sample, label = tf.py_function(split_file_by_window_size, inp=(sample, label), Tout=(sample.dtype, label.dtype)) return sample, label # Cell def create_dataset_fixed_size(ds): iterator = iter(ds) sample, label = iterator.next() samples_all = tf.unstack(sample) labels_all = tf.unstack(label) while True: try: sample, label = iterator.next() sample = tf.unstack(sample) label = tf.unstack(label) samples_all = tf.concat([samples_all, sample], axis=0) labels_all = tf.concat([labels_all, label], axis=0) except: break return samples_all, labels_all # Cell def get_spectrogram(sample, label): spectrogram = tfio.experimental.audio.spectrogram(sample, nfft=512, window=512, stride=256) return spectrogram, label # Cell def add_channel_dim(sample, label): sample = tf.expand_dims(sample, axis=-1) return sample, label

39.380952

145

0.703144

0

537

0.162334

5a2a02d3be8c76f34df0d751d6f767892052893d

492

py

Python

Lib/objc/_SplitKit.py

kanishpatel/Pyto

feec7a1a54f635a6375fa7ede074ff35afbfbb95

[ "MIT" ]

null

Lib/objc/_SplitKit.py

kanishpatel/Pyto

feec7a1a54f635a6375fa7ede074ff35afbfbb95

[ "MIT" ]

null

Lib/objc/_SplitKit.py

kanishpatel/Pyto

feec7a1a54f635a6375fa7ede074ff35afbfbb95

[ "MIT" ]

null

''' Classes from the 'SplitKit' framework. ''' try: from rubicon.objc import ObjCClass except ValueError: def ObjCClass(name): return None def _Class(name): try: return ObjCClass(name) except NameError: return None PodsDummy_SplitKit = _Class('PodsDummy_SplitKit') InstantPanGestureRecognizer = _Class('SplitKit.InstantPanGestureRecognizer') HandleView = _Class('SplitKit.HandleView') SPKSplitViewController = _Class('SPKSplitViewController')

21.391304

76

0.731707

0

149

0.302846

5a2a102330d36f9fe8e0e169c14680aef835ac84

3,743

py

Python

wiki_music/gui_lib/search_and_replace.py

marian-code/wikipedia-music-tags

e8836c23b7b7e43661b59afd1bfc18d381b95d4a

[ "MIT" ]

5

2019-01-28T21:53:14.000Z

2020-06-27T08:52:36.000Z

wiki_music/gui_lib/search_and_replace.py

marian-code/wikipedia-music-tags

e8836c23b7b7e43661b59afd1bfc18d381b95d4a

[ "MIT" ]

4

2019-01-15T16:33:59.000Z

2020-05-20T08:09:02.000Z

wiki_music/gui_lib/search_and_replace.py

marian-code/wikipedia-music-tags

e8836c23b7b7e43661b59afd1bfc18d381b95d4a

[ "MIT" ]

1

2020-04-15T11:00:20.000Z

"""Module controling search and replace tab.""" import logging from wiki_music.constants import GUI_HEADERS from wiki_music.gui_lib import BaseGui, CheckableListModel from wiki_music.gui_lib.qt_importer import QMessageBox, QPushButton, QIcon, QStyle __all__ = ["Replacer"] log = logging.getLogger(__name__) log.debug("finished gui search & replace imports") class Replacer(BaseGui): """Controls the search and replace tab in GUI. Warnings -------- This class is not ment to be instantiated, only inherited. """ def __init__(self) -> None: super().__init__() self.replace_tag_selector_model = CheckableListModel() self._fill_tags_list() def _fill_tags_list(self): """Create a checkable list with table column name headers.""" for tag in GUI_HEADERS: self.replace_tag_selector_model.add(tag) self.replace_tag_selector_view.setModel( self.replace_tag_selector_model) def _setup_search_replace(self): """Connect to signals essential for search and replace tab.""" # re-run search when search columns are reselected self.replace_tag_selector_model.itemChanged.connect( self._search_replace_run) # re-run search when options are checked self.search_support_re.stateChanged.connect( self._search_replace_run) self.search_support_wildcard.stateChanged.connect( self._search_replace_run) self.search_case_sensitive.stateChanged.connect( self._search_replace_run) # connect to control buttons self.search_next.clicked.connect(self.tableView.search_next) self.search_previous.clicked.connect(self.tableView.search_previous) self.replace_one.clicked.connect( lambda: self.tableView.replace_one( self.search_string_input.text(), self.replace_string_input.text())) self.replace_all.clicked.connect( lambda: self.tableView.replace_all( self.search_string_input.text(), self.replace_string_input.text() )) # search is run interacively as user is typing self.search_string_input.textChanged.connect( self._search_replace_run) # on tab change change selection and search highlight mode self.tool_tab.currentChanged.connect( self.tableView.set_search_visibility) # seems that filtering is done by rows # self.search_string_input.textChanged.connect( # self.proxy.setFilterFixedString) def _search_replace_run(self, string: str): """Process search parameters and call table search method. Parameters ---------- string: str string to search for """ if (self.search_support_re.isChecked() and self.search_support_wildcard.isChecked()): msg = QMessageBox(QMessageBox.Warning, "Warning", "Attempting to use regex and wildcards at once " "may return unexpected results. " "Do you want to proceed?", QMessageBox.Yes | QMessageBox.No) if msg.exec_() == QMessageBox.No: return else: log.warning("Wildcard and regex used at once in search") self.tableView.search_string( self.search_string_input.text(), self.search_case_sensitive.isChecked(), self.search_support_re.isChecked(), self.search_support_wildcard.isChecked(), self.replace_tag_selector_model.get_checked_indices() )

35.647619

82

0.6428

3,379

0.902752

0

1,028

0.274646