index int64 | repo_name string | branch_name string | path string | content string | import_graph string |
|---|---|---|---|---|---|
548 | EricHughesABC/T2EPGviewer | refs/heads/master | /simple_pandas_plot.py | # -*- coding: utf-8 -*-
"""
Created on Thu Jul 20 10:29:38 2017
@author: neh69
"""
import os
import sys
import numpy as np
import pandas as pd
import lmfit as lm
import matplotlib
import matplotlib.pyplot as plt
import seaborn as sns
from PyQt5 import QtCore, QtWidgets
import visionplot_widgets
... | {"/visionplot_widgets.py": ["/t2fit.py", "/ImageData.py", "/epgT2paramsDialog.py", "/azzT2paramsDialog.py"], "/simple_pandas_plot.py": ["/visionplot_widgets.py", "/mriplotwidget.py", "/ImageData.py"]} |
549 | EricHughesABC/T2EPGviewer | refs/heads/master | /ImageData.py | # -*- coding: utf-8 -*-
"""
Created on Tue Mar 6 14:55:05 2018
@author: ERIC
"""
import os
import numpy as np
import pandas as pd
import nibabel
class T2imageData():
def __init__(self):
self.currentSlice = None
self.currentEcho = None
self.T2imagesDirpath = None
... | {"/visionplot_widgets.py": ["/t2fit.py", "/ImageData.py", "/epgT2paramsDialog.py", "/azzT2paramsDialog.py"], "/simple_pandas_plot.py": ["/visionplot_widgets.py", "/mriplotwidget.py", "/ImageData.py"]} |
550 | EricHughesABC/T2EPGviewer | refs/heads/master | /azzT2paramsDialog.py | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'azz_fit_parameters_dialog.ui'
#
# Created by: PyQt5 UI code generator 5.6
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore, QtGui, QtWidgets
class AzzT2paramsDialog(object):
def __init__(... | {"/visionplot_widgets.py": ["/t2fit.py", "/ImageData.py", "/epgT2paramsDialog.py", "/azzT2paramsDialog.py"], "/simple_pandas_plot.py": ["/visionplot_widgets.py", "/mriplotwidget.py", "/ImageData.py"]} |
553 | olof98johansson/SentimentAnalysisNLP | refs/heads/main | /main.py | import train
import preprocessing
def run():
'''
Training function to run the training process after specifying parameters
'''
preprocessing.config.paths = ['./training_data/depressive1.json',
'./training_data/depressive2.json',
'./t... | {"/main.py": ["/train.py", "/preprocessing.py"], "/train.py": ["/models.py", "/preprocessing.py"], "/models.py": ["/preprocessing.py"], "/preprocessing.py": ["/data_cleaning.py", "/twint_scraping.py"], "/predict.py": ["/models.py", "/train.py", "/preprocessing.py", "/data_cleaning.py", "/twint_scraping.py"]} |
554 | olof98johansson/SentimentAnalysisNLP | refs/heads/main | /train.py | import torch
import torch.nn as nn
import models
import preprocessing
from collections import defaultdict
import time
import os
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
sns.set_style('darkgrid')
from celluloid import Camera
def Logger(elapsed_time, epoch, epochs, tr_loss, tr_acc, val_l... | {"/main.py": ["/train.py", "/preprocessing.py"], "/train.py": ["/models.py", "/preprocessing.py"], "/models.py": ["/preprocessing.py"], "/preprocessing.py": ["/data_cleaning.py", "/twint_scraping.py"], "/predict.py": ["/models.py", "/train.py", "/preprocessing.py", "/data_cleaning.py", "/twint_scraping.py"]} |
555 | olof98johansson/SentimentAnalysisNLP | refs/heads/main | /twint_scraping.py | # NOTE: TWINT NEEDS TO BE INSTALLEED BY THE FOLLOWING COMMAND:
# pip install --user --upgrade git+https://github.com/twintproject/twint.git@origin/master#egg=twint
# OTHERWISE IT WON'T WORK
import twint
import nest_asyncio
nest_asyncio.apply()
from dateutil import rrule
from datetime import datetime, timedelta
def g... | {"/main.py": ["/train.py", "/preprocessing.py"], "/train.py": ["/models.py", "/preprocessing.py"], "/models.py": ["/preprocessing.py"], "/preprocessing.py": ["/data_cleaning.py", "/twint_scraping.py"], "/predict.py": ["/models.py", "/train.py", "/preprocessing.py", "/data_cleaning.py", "/twint_scraping.py"]} |
556 | olof98johansson/SentimentAnalysisNLP | refs/heads/main | /models.py | import torch
import torch.nn as nn
import preprocessing
import os
import numpy as np
class ModelUtils:
'''
A utility class to save and load model weights
'''
def save_model(save_path, model):
root, ext = os.path.splitext(save_path)
if not ext:
save_path = root + '.pth'
... | {"/main.py": ["/train.py", "/preprocessing.py"], "/train.py": ["/models.py", "/preprocessing.py"], "/models.py": ["/preprocessing.py"], "/preprocessing.py": ["/data_cleaning.py", "/twint_scraping.py"], "/predict.py": ["/models.py", "/train.py", "/preprocessing.py", "/data_cleaning.py", "/twint_scraping.py"]} |
557 | olof98johansson/SentimentAnalysisNLP | refs/heads/main | /preprocessing.py | import data_cleaning
import twint_scraping
import os
from collections import Counter
from sklearn.preprocessing import LabelEncoder
from sklearn.model_selection import train_test_split
from torch.utils.data import Dataset, DataLoader
import torch
class config:
'''
Configuration class to store and tune globa... | {"/main.py": ["/train.py", "/preprocessing.py"], "/train.py": ["/models.py", "/preprocessing.py"], "/models.py": ["/preprocessing.py"], "/preprocessing.py": ["/data_cleaning.py", "/twint_scraping.py"], "/predict.py": ["/models.py", "/train.py", "/preprocessing.py", "/data_cleaning.py", "/twint_scraping.py"]} |
558 | olof98johansson/SentimentAnalysisNLP | refs/heads/main | /predict.py | import models
import train
import preprocessing
import data_cleaning
import os
import torch
import twint_scraping
import numpy as np
from torch.utils.data import Dataset, DataLoader
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
sns.set_style('darkgrid')
import pandas_alive
class Config:
... | {"/main.py": ["/train.py", "/preprocessing.py"], "/train.py": ["/models.py", "/preprocessing.py"], "/models.py": ["/preprocessing.py"], "/preprocessing.py": ["/data_cleaning.py", "/twint_scraping.py"], "/predict.py": ["/models.py", "/train.py", "/preprocessing.py", "/data_cleaning.py", "/twint_scraping.py"]} |
559 | olof98johansson/SentimentAnalysisNLP | refs/heads/main | /data_cleaning.py |
import json
import csv
import re
def load_json(path):
'''
Loads collected data in json format, checks it and then converts to csv format
Input: path - path and file name to the collected json data (type: string)
Output: keys - list of features/keys of the dataframe (type: list of strings)
... | {"/main.py": ["/train.py", "/preprocessing.py"], "/train.py": ["/models.py", "/preprocessing.py"], "/models.py": ["/preprocessing.py"], "/preprocessing.py": ["/data_cleaning.py", "/twint_scraping.py"], "/predict.py": ["/models.py", "/train.py", "/preprocessing.py", "/data_cleaning.py", "/twint_scraping.py"]} |
566 | DiegoArcelli/BlocksWorld | refs/heads/main | /cnn.py | import numpy as np
import matplotlib.pyplot as plt
from keras.datasets import mnist
from keras.layers import Conv2D
from keras.layers import MaxPool2D
from keras.layers import Flatten
from keras.layers import Dense
from keras.layers import Dropout
from keras import Sequential
# file per allenare e salvare la rete neur... | {"/launch.py": ["/load_state.py", "/utils.py", "/blocks_world.py", "/search_algs.py"], "/search_algs.py": ["/utils.py", "/blocks_world.py"], "/blocks_world.py": ["/utils.py"], "/main.py": ["/load_state.py", "/utils.py", "/blocks_world.py", "/search_algs.py"]} |
567 | DiegoArcelli/BlocksWorld | refs/heads/main | /launch.py | import tkinter as tk
from tkinter.filedialog import askopenfilename
from PIL import Image, ImageTk
from load_state import prepare_image
from utils import draw_state
from blocks_world import BlocksWorld
from search_algs import *
# file che contiene l'implementazione dell'interfaccia grafica per utilizzare il programma
... | {"/launch.py": ["/load_state.py", "/utils.py", "/blocks_world.py", "/search_algs.py"], "/search_algs.py": ["/utils.py", "/blocks_world.py"], "/blocks_world.py": ["/utils.py"], "/main.py": ["/load_state.py", "/utils.py", "/blocks_world.py", "/search_algs.py"]} |
568 | DiegoArcelli/BlocksWorld | refs/heads/main | /utils.py | import heapq
import functools
import numpy as np
import cv2 as cv
import matplotlib.pyplot as plt
class PriorityQueue:
"""A Queue in which the minimum (or maximum) element (as determined by f and
order) is returned first.
If order is 'min', the item with minimum f(x) is
returned first; if order is 'max... | {"/launch.py": ["/load_state.py", "/utils.py", "/blocks_world.py", "/search_algs.py"], "/search_algs.py": ["/utils.py", "/blocks_world.py"], "/blocks_world.py": ["/utils.py"], "/main.py": ["/load_state.py", "/utils.py", "/blocks_world.py", "/search_algs.py"]} |
569 | DiegoArcelli/BlocksWorld | refs/heads/main | /search_algs.py | from aima3.search import *
from utils import *
from collections import deque
from blocks_world import BlocksWorld
import sys
# file che contiene le implementazioni degli algoritmi di ricerca
node_expanded = 0 # numero di nodi espansi durante la ricerca
max_node = 0 # massimo numero di nodi presenti nella frontiera ... | {"/launch.py": ["/load_state.py", "/utils.py", "/blocks_world.py", "/search_algs.py"], "/search_algs.py": ["/utils.py", "/blocks_world.py"], "/blocks_world.py": ["/utils.py"], "/main.py": ["/load_state.py", "/utils.py", "/blocks_world.py", "/search_algs.py"]} |
570 | DiegoArcelli/BlocksWorld | refs/heads/main | /blocks_world.py | from aima3.search import *
from utils import *
import numpy as np
import cv2 as cv
import matplotlib.pyplot as plt
# file che contine l'implementazione del problema basata con AIMA
class BlocksWorld(Problem):
def __init__(self, initial, goal):
super().__init__(initial, goal)
# restituisce il numero... | {"/launch.py": ["/load_state.py", "/utils.py", "/blocks_world.py", "/search_algs.py"], "/search_algs.py": ["/utils.py", "/blocks_world.py"], "/blocks_world.py": ["/utils.py"], "/main.py": ["/load_state.py", "/utils.py", "/blocks_world.py", "/search_algs.py"]} |
571 | DiegoArcelli/BlocksWorld | refs/heads/main | /main.py | from PIL import Image, ImageTk
from load_state import prepare_image
from utils import draw_state
from blocks_world import BlocksWorld
from search_algs import *
import argparse
from inspect import getfullargspec
# file che definisce lo script da linea di comando per utilizzare il programma
if __name__ == "__main__":
... | {"/launch.py": ["/load_state.py", "/utils.py", "/blocks_world.py", "/search_algs.py"], "/search_algs.py": ["/utils.py", "/blocks_world.py"], "/blocks_world.py": ["/utils.py"], "/main.py": ["/load_state.py", "/utils.py", "/blocks_world.py", "/search_algs.py"]} |
572 | DiegoArcelli/BlocksWorld | refs/heads/main | /load_state.py | import cv2 as cv
import numpy as np
import matplotlib.pyplot as plt
import glob
from tensorflow import keras
from math import ceil
deteced = [np.array([]) for x in range(6)] # lista che contiene le immagini delle cifre
poisitions = [None for x in range(6)] # lista che contiene la posizione delle cifre nell'immagine
de... | {"/launch.py": ["/load_state.py", "/utils.py", "/blocks_world.py", "/search_algs.py"], "/search_algs.py": ["/utils.py", "/blocks_world.py"], "/blocks_world.py": ["/utils.py"], "/main.py": ["/load_state.py", "/utils.py", "/blocks_world.py", "/search_algs.py"]} |
592 | digital-sustainability/swiss-procurement-classifier | refs/heads/master | /runOldIterations.py | from train import ModelTrainer
from collection import Collection
import pandas as pd
import logging
import traceback
import os
logging.basicConfig()
logger = logging.getLogger(__name__)
logger.setLevel(logging.INFO)
# === THESIS ===
anbieter_config = {
'Construction': [
'Alpiq AG',
'Swisscom',
... | {"/runOldIterations.py": ["/train.py", "/collection.py"], "/train.py": ["/db.py"], "/learn.py": ["/db.py"], "/helpers.py": ["/db.py"], "/runIterations.py": ["/learn.py", "/collection.py"]} |
593 | digital-sustainability/swiss-procurement-classifier | refs/heads/master | /train.py | import pandas as pd
import math
from datetime import datetime
from sklearn.utils import shuffle
from sklearn.model_selection import train_test_split, cross_val_score
from sklearn.ensemble import RandomForestClassifier, GradientBoostingClassifier
from sklearn.tree import DecisionTreeClassifier
from sklearn.metrics impor... | {"/runOldIterations.py": ["/train.py", "/collection.py"], "/train.py": ["/db.py"], "/learn.py": ["/db.py"], "/helpers.py": ["/db.py"], "/runIterations.py": ["/learn.py", "/collection.py"]} |
594 | digital-sustainability/swiss-procurement-classifier | refs/heads/master | /learn.py | import pandas as pd
import numpy as np
import math
import re
from datetime import datetime
from sklearn.utils import shuffle
from sklearn.model_selection import train_test_split, cross_val_score
from sklearn.ensemble import RandomForestClassifier, GradientBoostingClassifier
from sklearn.tree import DecisionTreeClassifi... | {"/runOldIterations.py": ["/train.py", "/collection.py"], "/train.py": ["/db.py"], "/learn.py": ["/db.py"], "/helpers.py": ["/db.py"], "/runIterations.py": ["/learn.py", "/collection.py"]} |
595 | digital-sustainability/swiss-procurement-classifier | refs/heads/master | /helpers.py | from db import connection, engine
import math
import pandas as pd
import numpy as np
from sklearn import tree
from sklearn.model_selection import train_test_split
from sklearn.metrics import confusion_matrix, accuracy_score, roc_curve, auc
# =====================
# SQL SELECT STATEMENTS
# =====================
# @pa... | {"/runOldIterations.py": ["/train.py", "/collection.py"], "/train.py": ["/db.py"], "/learn.py": ["/db.py"], "/helpers.py": ["/db.py"], "/runIterations.py": ["/learn.py", "/collection.py"]} |
596 | digital-sustainability/swiss-procurement-classifier | refs/heads/master | /collection.py | import json
import pandas as pd
import warnings
class Collection():
algorithms = ['gradient_boost', 'decision_tree', 'random_forest']
def __init__(self):
self.list = []
def append(self, item):
self.list.append(item)
def __iter__(self):
return iter(self.list)
def get_al... | {"/runOldIterations.py": ["/train.py", "/collection.py"], "/train.py": ["/db.py"], "/learn.py": ["/db.py"], "/helpers.py": ["/db.py"], "/runIterations.py": ["/learn.py", "/collection.py"]} |
597 | digital-sustainability/swiss-procurement-classifier | refs/heads/master | /db.py | import configparser
import sqlalchemy
# git update-index --skip-worktree config.ini
config = configparser.ConfigParser()
config.read("config.ini")
connection_string = 'mysql+' + config['database']['connector'] + '://' + config['database']['user'] + ':' + config['database']['password'] + '@' + config['database']['... | {"/runOldIterations.py": ["/train.py", "/collection.py"], "/train.py": ["/db.py"], "/learn.py": ["/db.py"], "/helpers.py": ["/db.py"], "/runIterations.py": ["/learn.py", "/collection.py"]} |
598 | digital-sustainability/swiss-procurement-classifier | refs/heads/master | /runIterations.py | from learn import ModelTrainer
from collection import Collection
import pandas as pd
import logging
import traceback
import os
logging.basicConfig()
logger = logging.getLogger(__name__)
logger.setLevel(logging.INFO)
# === THESIS ===
anbieter_config = {
'Construction': [
'Alpiq AG',
'KIBAG',
... | {"/runOldIterations.py": ["/train.py", "/collection.py"], "/train.py": ["/db.py"], "/learn.py": ["/db.py"], "/helpers.py": ["/db.py"], "/runIterations.py": ["/learn.py", "/collection.py"]} |
610 | AmosGarner/PyLife | refs/heads/master | /pylife.py | import sys, argparse
import numpy as np
import matplotlib.pyplot as plot
import matplotlib.animation as animation
from helper import *
from displayTextSpawner import displayText
from inputValidator import validateInput
paused = True
iteration = 0
def update(frameNumber, image, grid, gridSize):
newGrid = grid.cop... | {"/pylife.py": ["/helper.py", "/displayTextSpawner.py", "/inputValidator.py"]} |
611 | AmosGarner/PyLife | refs/heads/master | /inputValidator.py | from alphaNumLib import *
alphaNumArray = alphaArray + numArray + specialArray
def validateInput(input):
if(checkInAlphaNumSpec(input)):
return True
else:
return False
def checkInAlphaNumSpec(input):
inputCharArray = list(input.lower())
for value in inputCharArray:
if value no... | {"/pylife.py": ["/helper.py", "/displayTextSpawner.py", "/inputValidator.py"]} |
612 | AmosGarner/PyLife | refs/heads/master | /displayTextSpawner.py | import numpy as np
ON = 255
OFF = 0
vals = [ON, OFF]
def displayText(input, gridSize):
grid = generateBlankGroup(gridSize)
index = 1
x = gridSize / 2
for value in list(input):
print(5 * index)
print(gridSize)
if 5*index >= gridSize:
index = 1
x = gridSiz... | {"/pylife.py": ["/helper.py", "/displayTextSpawner.py", "/inputValidator.py"]} |
613 | AmosGarner/PyLife | refs/heads/master | /helper.py | import numpy as np
import matplotlib.pyplot as plot
import matplotlib.animation as animation
ON = 255
OFF = 0
vals = [ON, OFF]
def randomGrid(gridSize):
return np.random.choice(vals, gridSize*gridSize, p=[0.2, 0.8]).reshape(gridSize, gridSize)
def addGlider(row, col, grid):
glider = np.array([[OFF, OFF, ON],... | {"/pylife.py": ["/helper.py", "/displayTextSpawner.py", "/inputValidator.py"]} |
624 | jettaponB/Practice | refs/heads/main | /Test07.py | import tkinter as tk
def show_output():
number = int(number_input.get())
if number == 0:
output_label.configure(text='ผิด')
return
output = ''
for i in range(1, 13):
output += str(number) + ' * ' + str(i)
output += ' = ' + str(number * i) + '\n'
output_label.confi... | {"/Test14.py": ["/class_tank.py"], "/Test05.py": ["/shape.py"]} |
625 | jettaponB/Practice | refs/heads/main | /Test13.py | class Tank:
def __init__(self, name, ammo) -> None:
self.name = name
self.ammo = ammo
first_tank = Tank('Serie1', 3)
print(first_tank.name)
second_tank = Tank('Serie2', 5)
print(second_tank.name) | {"/Test14.py": ["/class_tank.py"], "/Test05.py": ["/shape.py"]} |
626 | jettaponB/Practice | refs/heads/main | /class_tank.py | class Tank:
def __init__(self, name, ammo) -> None:
self.name = name
self.ammo = ammo
def add_ammo(self, ammo):
if self.ammo + ammo <= 10:
self.ammo += ammo
def fire_ammo(self):
if self.ammo > 0:
self.ammo -= 1 | {"/Test14.py": ["/class_tank.py"], "/Test05.py": ["/shape.py"]} |
627 | jettaponB/Practice | refs/heads/main | /Test12.py | # message = 'วัชราวลี'
# result = len(message)
# print(result)
# message = 'วัชราวลี'
# result = 'วัช' in message
# print(result)
# message = '0982612325'
# result = message.isdigit()
# print(result)
# message = 'Just Python'
# result = message.replace('Python', 'Rabbit')
# print(result)
message = 'กระต่าย, กระรอก,... | {"/Test14.py": ["/class_tank.py"], "/Test05.py": ["/shape.py"]} |
628 | jettaponB/Practice | refs/heads/main | /Test10.py | # quests = ['ปลูกต้นมะม่วง', 'ล้างปลา', 'เผาถ่าน']
# if 'ล้างปลา' in quests:
# print('ทำงานเสร็จ')
#----------------------------------------------------
# quests = ['ปลูกต้นมะม่วง', 'ล้างปลา', 'เผาถ่าน']
# max_quests = 5
# if len(quests) < max_quests:
# quests.append('จับปลาดุก')
# print(quests)
#---------... | {"/Test14.py": ["/class_tank.py"], "/Test05.py": ["/shape.py"]} |
629 | jettaponB/Practice | refs/heads/main | /shape.py | def get_circle_area(radius):
return 22 / 7 * (radius ** 2)
def get_triangle_area(width, heigth):
return 1 / 2 * width * heigth
def get_rectangle_area(width, heigth):
return width * heigth | {"/Test14.py": ["/class_tank.py"], "/Test05.py": ["/shape.py"]} |
630 | jettaponB/Practice | refs/heads/main | /Test14.py | import class_tank as CT
first_tank = CT.Tank('Serie1', 3)
first_tank.fire_ammo()
print(first_tank.ammo)
first_tank.fire_ammo()
first_tank.fire_ammo()
print(first_tank.ammo)
first_tank.add_ammo(4)
print(first_tank.ammo)
| {"/Test14.py": ["/class_tank.py"], "/Test05.py": ["/shape.py"]} |
631 | jettaponB/Practice | refs/heads/main | /test09.py | import tkinter as tk
def show_output():
number = int(input_number.get())
output = ''
for i in range(1, 13):
output += str(number) + ' * ' + str(i) + ' = ' + str(number * i) + '\n'
output_label.configure(text=output)
window = tk.Tk()
window.title('โปรแกรมคำนวนสูตรคูณ')
window.minsize(widt... | {"/Test14.py": ["/class_tank.py"], "/Test05.py": ["/shape.py"]} |
632 | jettaponB/Practice | refs/heads/main | /Test02.py | score = 55
if score >= 80:
print('Grade A')
print('dafdaf')
elif score >= 70:
print('Grade B')
elif score >= 60:
print('Grade C')
else:
print('Grade F')
| {"/Test14.py": ["/class_tank.py"], "/Test05.py": ["/shape.py"]} |
633 | jettaponB/Practice | refs/heads/main | /Test03.py | # number = 1
# double = number * 2
# print(number)
# for i in range(1, 7):
# double = i * 2
# print(double)
# for i in range(1, 7):
# if i % 3 == 0:
# continue
# print(i)
for i in range(1, 7):
if i % 3 == 0:
break
print(i) | {"/Test14.py": ["/class_tank.py"], "/Test05.py": ["/shape.py"]} |
634 | jettaponB/Practice | refs/heads/main | /Test01.py | # x = '4.5'
# y = str(12)
# z = x + y
# print(z)
# final_score = 15
#
# age = 25 # ตัวเลขจำนวนเต็ม (integer)
# weight = 66.6 # ตัวเลขทศนิยม (Float)
# first_name = 'ศักรินทร์' # ข้อความ (String)
# has_notebook = True # Boolean
x = 5
y = 2
a1 = x + y # 7
a2 = x - y # 3
a3 = x *... | {"/Test14.py": ["/class_tank.py"], "/Test05.py": ["/shape.py"]} |
635 | jettaponB/Practice | refs/heads/main | /Test08.py | import tkinter as tk
def set_message():
text = text_input.get()
title_label.configure(text=text)
window = tk.Tk()
window.title('Desktop Application')
window.minsize(width=300, height=400)
title_label = tk.Label(master=window, text='กรุณาระบุข้อความ')
title_label.pack()
text_input = tk.Entry(master=window)
t... | {"/Test14.py": ["/class_tank.py"], "/Test05.py": ["/shape.py"]} |
636 | jettaponB/Practice | refs/heads/main | /Test04.py | # def get_box_area(width, length, height):
# box_area = width * length * height
# print(box_area)
#
# get_box_area(4, 4, 2)
# get_box_area(width=1, length=1, height=2)
def get_box_area(width, length, height):
if width < 0 or length < 0 or height < 0:
return 0
box_area = width * length * heig... | {"/Test14.py": ["/class_tank.py"], "/Test05.py": ["/shape.py"]} |
637 | jettaponB/Practice | refs/heads/main | /Test11.py | book = {
'name': 'C++',
'price': '299',
'page': '414'
}
# #ตัวแปลทีละตัว ... ตัวแปรจะเยอะเกิน
# book_name = 'C++'
# book_price = 299
# book_page = 414
# #เก็บใน List ... ลืมว่าข้อมูลไหนอยู่ที่ index ไหน
# book_data = ['C++', 299, 414]
#book['place'] = 'MU Salaya'
book.pop('price')
print(book) | {"/Test14.py": ["/class_tank.py"], "/Test05.py": ["/shape.py"]} |
638 | jettaponB/Practice | refs/heads/main | /Test05.py | import shape as sh
circle = sh.get_circle_area(10)
print(circle)
triangle = sh.get_triangle_area(width=6, heigth=7)
print(triangle) | {"/Test14.py": ["/class_tank.py"], "/Test05.py": ["/shape.py"]} |
640 | jerry5841314/Ensemble-Pytorch | refs/heads/master | /torchensemble/utils/logging.py | import os
import time
import logging
def set_logger(log_file=None, log_console_level="info", log_file_level=None):
"""Bind the default logger with console and file stream output."""
def _get_level(level):
if level.lower() == 'debug':
return logging.DEBUG
elif level.lower() == 'inf... | {"/torchensemble/tests/test_fast_geometric.py": ["/torchensemble/utils/logging.py"]} |
641 | jerry5841314/Ensemble-Pytorch | refs/heads/master | /torchensemble/tests/test_fast_geometric.py | import torch
import pytest
import numpy as np
import torch.nn as nn
from torch.utils.data import TensorDataset, DataLoader
from torchensemble import FastGeometricClassifier as clf
from torchensemble import FastGeometricRegressor as reg
from torchensemble.utils.logging import set_logger
set_logger("pytest_fast_geomet... | {"/torchensemble/tests/test_fast_geometric.py": ["/torchensemble/utils/logging.py"]} |
653 | AlenaPliusnina/Flask_API | refs/heads/main | /app/api.py | import json
from datetime import datetime
from flask import request, make_response
from flask_restful import Resource, Api
from flask import g
from app import app, db
from flask_httpauth import HTTPBasicAuth
from app.models import User, Post, Comment
from app.schemes import posts_schema, post_schema, comment_schema,... | {"/app/api.py": ["/app/__init__.py", "/app/models.py", "/app/schemes.py"], "/app/models.py": ["/app/__init__.py"], "/app/schemes.py": ["/app/__init__.py", "/app/models.py"]} |
654 | AlenaPliusnina/Flask_API | refs/heads/main | /app/models.py | from datetime import datetime
from flask_bcrypt import generate_password_hash, check_password_hash
from app import db
class User(db.Model):
__tablename__ = 'users'
id = db.Column(db.Integer, primary_key=True, nullable=False)
username = db.Column(db.String(80), unique=True, nullable=False)
email = db.... | {"/app/api.py": ["/app/__init__.py", "/app/models.py", "/app/schemes.py"], "/app/models.py": ["/app/__init__.py"], "/app/schemes.py": ["/app/__init__.py", "/app/models.py"]} |
655 | AlenaPliusnina/Flask_API | refs/heads/main | /app/__init__.py | from config import Config
from flask import Flask
from flask_sqlalchemy import SQLAlchemy
from flask_migrate import Migrate
def create_app():
app = Flask(__name__)
app.config.from_object(Config)
app.debug = True
return app
app = create_app()
db = SQLAlchemy(app)
migrate = Migrate(app, db)
from ap... | {"/app/api.py": ["/app/__init__.py", "/app/models.py", "/app/schemes.py"], "/app/models.py": ["/app/__init__.py"], "/app/schemes.py": ["/app/__init__.py", "/app/models.py"]} |
656 | AlenaPliusnina/Flask_API | refs/heads/main | /app/schemes.py | from flask_marshmallow import Marshmallow
from app import app
from app.models import User, Post, Comment
ma = Marshmallow(app)
class CommentSchema(ma.Schema):
class Meta:
fields = ("id", "post_id", "author_id", "title", "content", "publication_datetime")
model = Comment
ordered = True
... | {"/app/api.py": ["/app/__init__.py", "/app/models.py", "/app/schemes.py"], "/app/models.py": ["/app/__init__.py"], "/app/schemes.py": ["/app/__init__.py", "/app/models.py"]} |
657 | kstandvoss/TFCA | refs/heads/master | /run.py | from argparse import Namespace
import co2_dataset
import os
import time
# Settings
data_path = 'CO2/monthly_in_situ_c... | {"/run.py": ["/co2_dataset.py"]} |
658 | kstandvoss/TFCA | refs/heads/master | /co2_dataset.py | # coding: utf-8
import nengo
import nengo_dl
import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from scipy import signal
import argparse
import pdb
def main(args):
co2_data = pd.read_csv(args.data_path, usecols=[0,4,5,6,7,8,9])
co2_data.columns = ['Date', 'standar... | {"/run.py": ["/co2_dataset.py"]} |
660 | gabilew/Joint-Forecasting-and-Interpolation-of-GS | refs/heads/master | /pytorch_gsp/utils/gsp.py | import torch
import torch.nn as nn
import numpy as np
from torch.autograd import Variable
import scipy
from sklearn.metrics.pairwise import rbf_kernel
def complement(S,N):
V = set(np.arange(0,N,1))
return np.array(list(V-set(S)))
class Reconstruction(nn.Module):
def __init__(self,V, sample, freqs, dom... | {"/main/seattle_train_sggru_semisupervised.py": ["/data/Load_data.py", "/data/Dataloader.py", "/pytorch_gsp/train/train_rnn.py", "/pytorch_gsp/utils/gsp.py", "/pytorch_gsp/models/sggru.py"], "/data/Dataloader.py": ["/pytorch_gsp/utils/gsp.py"], "/pytorch_gsp/models/sggru.py": ["/pytorch_gsp/utils/gsp.py"]} |
661 | gabilew/Joint-Forecasting-and-Interpolation-of-GS | refs/heads/master | /data/Load_data.py | import math
import sys
import time
import numpy as np
import pandas as pd
from sklearn.metrics.pairwise import rbf_kernel
def USA_data(directory ):
""""TODO: include the GSOD dataset"""
signals = pd.read_csv( directory + 'Usa_temp.csv')
if "Unnamed: 0" in signals.columns:
signals.drop(columns="... | {"/main/seattle_train_sggru_semisupervised.py": ["/data/Load_data.py", "/data/Dataloader.py", "/pytorch_gsp/train/train_rnn.py", "/pytorch_gsp/utils/gsp.py", "/pytorch_gsp/models/sggru.py"], "/data/Dataloader.py": ["/pytorch_gsp/utils/gsp.py"], "/pytorch_gsp/models/sggru.py": ["/pytorch_gsp/utils/gsp.py"]} |
662 | gabilew/Joint-Forecasting-and-Interpolation-of-GS | refs/heads/master | /main/seattle_train_sggru_semisupervised.py | import os
import time
import torch
import argparse
import numpy as np
import pandas as pd
import time
from data.Load_data import Seattle_data
from data.Dataloader import *
from pytorch_gsp.train.train_rnn import Evaluate, Train
from pytorch_gsp.utils.gsp import ( greedy_e_opt, spectral_components)
from pytorch_gsp.... | {"/main/seattle_train_sggru_semisupervised.py": ["/data/Load_data.py", "/data/Dataloader.py", "/pytorch_gsp/train/train_rnn.py", "/pytorch_gsp/utils/gsp.py", "/pytorch_gsp/models/sggru.py"], "/data/Dataloader.py": ["/pytorch_gsp/utils/gsp.py"], "/pytorch_gsp/models/sggru.py": ["/pytorch_gsp/utils/gsp.py"]} |
663 | gabilew/Joint-Forecasting-and-Interpolation-of-GS | refs/heads/master | /data/Dataloader.py |
import time
import numpy as np
import pandas as pd
import torch
import torch.utils.data as utils
from pytorch_gsp.utils.gsp import complement
def PrepareSequence(data, seq_len = 10, pred_len = 1):
time_len = data.shape[0]
sequences, labels = [], []
for i in range(time_len - seq_len - pred_len)... | {"/main/seattle_train_sggru_semisupervised.py": ["/data/Load_data.py", "/data/Dataloader.py", "/pytorch_gsp/train/train_rnn.py", "/pytorch_gsp/utils/gsp.py", "/pytorch_gsp/models/sggru.py"], "/data/Dataloader.py": ["/pytorch_gsp/utils/gsp.py"], "/pytorch_gsp/models/sggru.py": ["/pytorch_gsp/utils/gsp.py"]} |
664 | gabilew/Joint-Forecasting-and-Interpolation-of-GS | refs/heads/master | /main/__init.py | import os
import sys
current_dir = os.path.split(os.path.dirname(os.path.realpath(__file__)))[0]
sys.path.append(os.path.join(current_dir, 'data'))
print(sys.path) | {"/main/seattle_train_sggru_semisupervised.py": ["/data/Load_data.py", "/data/Dataloader.py", "/pytorch_gsp/train/train_rnn.py", "/pytorch_gsp/utils/gsp.py", "/pytorch_gsp/models/sggru.py"], "/data/Dataloader.py": ["/pytorch_gsp/utils/gsp.py"], "/pytorch_gsp/models/sggru.py": ["/pytorch_gsp/utils/gsp.py"]} |
665 | gabilew/Joint-Forecasting-and-Interpolation-of-GS | refs/heads/master | /setup.py | from setuptools import setup, find_packages
setup(
name='Joint-Forecasting-and-Interpolation-of-Graph-Signals-Using-Deep-Learning',
version='0.1.0',
author='Gabriela Lewenfus',
author_email='gabriela.lewenfus@gmail.com',
packages=find_packages(),
install_requires = ['scipy>=1.4.1', 'pandas>=0.15', '... | {"/main/seattle_train_sggru_semisupervised.py": ["/data/Load_data.py", "/data/Dataloader.py", "/pytorch_gsp/train/train_rnn.py", "/pytorch_gsp/utils/gsp.py", "/pytorch_gsp/models/sggru.py"], "/data/Dataloader.py": ["/pytorch_gsp/utils/gsp.py"], "/pytorch_gsp/models/sggru.py": ["/pytorch_gsp/utils/gsp.py"]} |
666 | gabilew/Joint-Forecasting-and-Interpolation-of-GS | refs/heads/master | /pytorch_gsp/train/train_rnn.py | ### training code ####
import sys
import time
import numpy as np
import torch
from torch.autograd import Variable
toolbar_width=20
def Train(model, train_dataloader, valid_dataloader, learning_rate = 1e-5, epochs = 300, patience = 10,
verbose=1, gpu = True, sample = None, optimizer = 'rmsprop'):
if optimize... | {"/main/seattle_train_sggru_semisupervised.py": ["/data/Load_data.py", "/data/Dataloader.py", "/pytorch_gsp/train/train_rnn.py", "/pytorch_gsp/utils/gsp.py", "/pytorch_gsp/models/sggru.py"], "/data/Dataloader.py": ["/pytorch_gsp/utils/gsp.py"], "/pytorch_gsp/models/sggru.py": ["/pytorch_gsp/utils/gsp.py"]} |
667 | gabilew/Joint-Forecasting-and-Interpolation-of-GS | refs/heads/master | /pytorch_gsp/models/sggru.py | import torch.utils.data as utils
import torch.nn.functional as F
import torch
import torch.nn as nn
from torch.autograd import Variable
from torch.nn.parameter import Parameter
import numpy as np
import pandas as pd
import time
from pytorch_gsp.utils.gsp import (spectral_components, Reconstruction)
class SpectralGrap... | {"/main/seattle_train_sggru_semisupervised.py": ["/data/Load_data.py", "/data/Dataloader.py", "/pytorch_gsp/train/train_rnn.py", "/pytorch_gsp/utils/gsp.py", "/pytorch_gsp/models/sggru.py"], "/data/Dataloader.py": ["/pytorch_gsp/utils/gsp.py"], "/pytorch_gsp/models/sggru.py": ["/pytorch_gsp/utils/gsp.py"]} |
677 | AntLouiz/DatapathWay | refs/heads/master | /li.py | # Intruçoes que o programa reconhece
FUNCTIONS = {
'101011': 'sw',
'100011': 'lw',
'100000': 'add',
'100010': 'sub',
'100101': 'or',
'100100': 'and'
}
| {"/logic.py": ["/utils.py"], "/core.py": ["/memory.py", "/logic.py", "/instructions.py", "/control.py"], "/control.py": ["/utils.py"], "/instructions.py": ["/li.py", "/utils.py"], "/memory.py": ["/utils.py"], "/main.py": ["/core.py"]} |
678 | AntLouiz/DatapathWay | refs/heads/master | /utils.py | def to_integer(binary_number):
if not isinstance(binary_number, str):
raise Exception()
return int(binary_number, 2)
def to_binary(number):
if not isinstance(number, int):
raise Exception()
return "{:0b}".format(number)
def extend_to_bits(binary_number, bits = 32):
if not isins... | {"/logic.py": ["/utils.py"], "/core.py": ["/memory.py", "/logic.py", "/instructions.py", "/control.py"], "/control.py": ["/utils.py"], "/instructions.py": ["/li.py", "/utils.py"], "/memory.py": ["/utils.py"], "/main.py": ["/core.py"]} |
679 | AntLouiz/DatapathWay | refs/heads/master | /logic.py | from utils import (
extend_to_bits,
to_binary,
to_integer,
to_binaryC2,
to_decimalC2
)
class ALU:
def makeSum(self, a, b):
result = to_decimalC2(a) + to_decimalC2(b)
if result > (2**31 -1) or result < -(2**31):
print("{}OVERFLOW OCURRENCE{}".format("-" * 20, "-... | {"/logic.py": ["/utils.py"], "/core.py": ["/memory.py", "/logic.py", "/instructions.py", "/control.py"], "/control.py": ["/utils.py"], "/instructions.py": ["/li.py", "/utils.py"], "/memory.py": ["/utils.py"], "/main.py": ["/core.py"]} |
680 | AntLouiz/DatapathWay | refs/heads/master | /core.py | from memory import RegistersBank, Memory
from logic import ALU
from instructions import PC
from control import (
ControlSw,
ControlLw,
ControlAdd,
ControlSub,
ControlAnd,
ControlOr,
)
class CPU:
def __init__(self):
self.alu = ALU()
self.pc = PC()
self.registers = Re... | {"/logic.py": ["/utils.py"], "/core.py": ["/memory.py", "/logic.py", "/instructions.py", "/control.py"], "/control.py": ["/utils.py"], "/instructions.py": ["/li.py", "/utils.py"], "/memory.py": ["/utils.py"], "/main.py": ["/core.py"]} |
681 | AntLouiz/DatapathWay | refs/heads/master | /control.py | import abc
from utils import to_integer, to_decimalC2
class BaseControl(abc.ABC):
def __init__(self, cpu):
self.cpu = cpu
@abc.abstractmethod
def execute(self):
pass
class ControlAdd(BaseControl):
def execute(self):
instruction = self.cpu.pc.next_instruction
regist... | {"/logic.py": ["/utils.py"], "/core.py": ["/memory.py", "/logic.py", "/instructions.py", "/control.py"], "/control.py": ["/utils.py"], "/instructions.py": ["/li.py", "/utils.py"], "/memory.py": ["/utils.py"], "/main.py": ["/core.py"]} |
682 | AntLouiz/DatapathWay | refs/heads/master | /instructions.py | from li import FUNCTIONS
from utils import extend_to_bits
class MipsInstruction:
op = None
rs = None
rt = None
rd = None
shamt = None
func = None
offset = None
instruction_type = None
instruction = None
def __init__(self, instruction):
if not (isinstance(instruction, st... | {"/logic.py": ["/utils.py"], "/core.py": ["/memory.py", "/logic.py", "/instructions.py", "/control.py"], "/control.py": ["/utils.py"], "/instructions.py": ["/li.py", "/utils.py"], "/memory.py": ["/utils.py"], "/main.py": ["/core.py"]} |
683 | AntLouiz/DatapathWay | refs/heads/master | /memory.py | import random
from utils import to_binary, extend_to_bits, to_binaryC2
class BaseMemory:
def __init__(self):
self.data = {}
def set_value(self, address, value):
"""
Set a value with a given address
"""
self.data[address] = value
return True
def get_valu... | {"/logic.py": ["/utils.py"], "/core.py": ["/memory.py", "/logic.py", "/instructions.py", "/control.py"], "/control.py": ["/utils.py"], "/instructions.py": ["/li.py", "/utils.py"], "/memory.py": ["/utils.py"], "/main.py": ["/core.py"]} |
684 | AntLouiz/DatapathWay | refs/heads/master | /main.py | from core import CPU
if __name__ == "__main__":
cpu = CPU()
cpu.execute()
| {"/logic.py": ["/utils.py"], "/core.py": ["/memory.py", "/logic.py", "/instructions.py", "/control.py"], "/control.py": ["/utils.py"], "/instructions.py": ["/li.py", "/utils.py"], "/memory.py": ["/utils.py"], "/main.py": ["/core.py"]} |
686 | yueyoum/smoke | refs/heads/master | /test/mail_exception_test.py | import sys
from wsgiref.simple_server import make_server
sys.path.append('..')
from app import App
from smoke.exceptions import EmailExceptionMiddleware
def exception_func_1():
return exception_func_2()
def exception_func_2():
return exception_func_3()
def exception_func_3():
return 1 / 0
app = Email... | {"/test/mail_exception_test.py": ["/smoke/exceptions.py"], "/smoke/exceptions.py": ["/smoke/functional/__init__.py"]} |
687 | yueyoum/smoke | refs/heads/master | /test/app.py | class App(object):
def __init__(self, hook_func=None):
self.hook_func = hook_func
def __call__(self, environ, start_response):
html = """<html>
<body><table>{0}</table></body>
</html>"""
def _get_env(k, v):
return """<tr><td>{0}</td><td>{1}</td></tr>""".form... | {"/test/mail_exception_test.py": ["/smoke/exceptions.py"], "/smoke/exceptions.py": ["/smoke/functional/__init__.py"]} |
688 | yueyoum/smoke | refs/heads/master | /smoke/exceptions.py | # -*- coding: utf-8 -*-
import sys
import traceback
class ExceptionMiddleware(object):
def __init__(self, wrap_app, smoke_html=False):
self.wrap_app = wrap_app
self.smoke_html = smoke_html
def __call__(self, environ, start_response):
try:
return self.wrap_app(environ, sta... | {"/test/mail_exception_test.py": ["/smoke/exceptions.py"], "/smoke/exceptions.py": ["/smoke/functional/__init__.py"]} |
689 | yueyoum/smoke | refs/heads/master | /smoke/functional/__init__.py | from mail import send_mail
| {"/test/mail_exception_test.py": ["/smoke/exceptions.py"], "/smoke/exceptions.py": ["/smoke/functional/__init__.py"]} |
690 | Sprunth/TFO2ReelLogger | refs/heads/master | /db.py | import os.path
import sqlite3
import Scraper
import sys
def create_db():
conn = sqlite3.connect('reellog.db')
c = conn.cursor()
c.execute('''CREATE TABLE reellog
(lure text, body text, location text, species text, level integer, weight real, class text,
unique(lure, body, location, species, level... | {"/db.py": ["/Scraper.py"]} |
691 | Sprunth/TFO2ReelLogger | refs/heads/master | /Scraper.py | from bs4 import BeautifulSoup
from pprint import pprint
from functools import reduce
import sys
def scrape(html_file_path):
soup = BeautifulSoup(open(html_file_path), 'html.parser')
rows = soup.find_all('tr')
commands = list()
for row in rows[1:]:
cols = row.find_all('td')
lure_st... | {"/db.py": ["/Scraper.py"]} |
702 | leopesi/pool_budget | refs/heads/master | /projeto/dimensoes/customclass/estruturas/__init__.py | from .dimensao import Dimensao | {"/projeto/dimensoes/customclass/estruturas/__init__.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py"], "/projeto/dimensoes/models.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py", "/projeto/dimensoes/customclass/objetos/filtro.py", "/projeto/dimensoes/customclass/objetos/motor.py"], "/projeto... |
703 | leopesi/pool_budget | refs/heads/master | /projeto/dimensoes/migrations/0018_auto_20200611_1905.py | # Generated by Django 3.0.3 on 2020-06-11 22:05
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('dimensoes', '0017_auto_20200611_1859'),
]
operations = [
migrations.RenameField(
model_name='clientemodel',
old_name... | {"/projeto/dimensoes/customclass/estruturas/__init__.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py"], "/projeto/dimensoes/models.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py", "/projeto/dimensoes/customclass/objetos/filtro.py", "/projeto/dimensoes/customclass/objetos/motor.py"], "/projeto... |
704 | leopesi/pool_budget | refs/heads/master | /projeto/dimensoes/migrations/0005_dimensaomodel_data.py | # Generated by Django 3.0.3 on 2020-03-17 17:11
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('dimensoes', '0004_auto_20200317_0933'),
]
operations = [
migrations.AddField(
model_name='dimensaomodel',
name='data... | {"/projeto/dimensoes/customclass/estruturas/__init__.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py"], "/projeto/dimensoes/models.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py", "/projeto/dimensoes/customclass/objetos/filtro.py", "/projeto/dimensoes/customclass/objetos/motor.py"], "/projeto... |
705 | leopesi/pool_budget | refs/heads/master | /projeto/dimensoes/migrations/0012_auto_20200603_1916.py | # Generated by Django 3.0.3 on 2020-06-03 22:16
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('dimensoes', '0011_auto_20200516_1518'),
]
operations = [
migrations.AlterField(
model_name='clientemodel',
name='tel... | {"/projeto/dimensoes/customclass/estruturas/__init__.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py"], "/projeto/dimensoes/models.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py", "/projeto/dimensoes/customclass/objetos/filtro.py", "/projeto/dimensoes/customclass/objetos/motor.py"], "/projeto... |
706 | leopesi/pool_budget | refs/heads/master | /projeto/dimensoes/migrations/0009_auto_20200504_1529.py | # Generated by Django 3.0.3 on 2020-05-04 18:29
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('dimensoes', '0008_remove_precificacaomodel_custo'),
]
operations = [
migrations.DeleteModel(
name='PrecificacaoModel',
)... | {"/projeto/dimensoes/customclass/estruturas/__init__.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py"], "/projeto/dimensoes/models.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py", "/projeto/dimensoes/customclass/objetos/filtro.py", "/projeto/dimensoes/customclass/objetos/motor.py"], "/projeto... |
707 | leopesi/pool_budget | refs/heads/master | /projeto/dimensoes/migrations/0014_dimensaomodel_profundidade_media.py | # Generated by Django 3.0.3 on 2020-06-04 18:56
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('dimensoes', '0013_remove_dimensaomodel_profundidade_media'),
]
operations = [
migrations.AddField(
model_name='dimensaomodel',
... | {"/projeto/dimensoes/customclass/estruturas/__init__.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py"], "/projeto/dimensoes/models.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py", "/projeto/dimensoes/customclass/objetos/filtro.py", "/projeto/dimensoes/customclass/objetos/motor.py"], "/projeto... |
708 | leopesi/pool_budget | refs/heads/master | /projeto/dimensoes/migrations/0010_auto_20200511_1521.py | # Generated by Django 3.0.3 on 2020-05-11 18:21
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('dimensoes', '0009_auto_20200504_1529'),
]
operations = [
migrations.AlterField(
model_name='dimensaomodel',
name='co... | {"/projeto/dimensoes/customclass/estruturas/__init__.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py"], "/projeto/dimensoes/models.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py", "/projeto/dimensoes/customclass/objetos/filtro.py", "/projeto/dimensoes/customclass/objetos/motor.py"], "/projeto... |
709 | leopesi/pool_budget | refs/heads/master | /projeto/dimensoes/migrations/0017_auto_20200611_1859.py | # Generated by Django 3.0.3 on 2020-06-11 21:59
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('dimensoes', '0016_auto_20200611_1852'),
]
operations = [
migrations.RenameField(
model_name='clientemodel',
old_name='numero... | {"/projeto/dimensoes/customclass/estruturas/__init__.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py"], "/projeto/dimensoes/models.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py", "/projeto/dimensoes/customclass/objetos/filtro.py", "/projeto/dimensoes/customclass/objetos/motor.py"], "/projeto... |
710 | leopesi/pool_budget | refs/heads/master | /projeto/dimensoes/migrations/0013_remove_dimensaomodel_profundidade_media.py | # Generated by Django 3.0.3 on 2020-06-04 18:33
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('dimensoes', '0012_auto_20200603_1916'),
]
operations = [
migrations.RemoveField(
model_name='dimensaomodel',
name='profundid... | {"/projeto/dimensoes/customclass/estruturas/__init__.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py"], "/projeto/dimensoes/models.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py", "/projeto/dimensoes/customclass/objetos/filtro.py", "/projeto/dimensoes/customclass/objetos/motor.py"], "/projeto... |
711 | leopesi/pool_budget | refs/heads/master | /projeto/dimensoes/migrations/0001_initial.py | # Generated by Django 3.0.3 on 2020-03-16 18:43
from django.db import migrations, models
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='ClienteModel',
fields=[
('id', models.AutoF... | {"/projeto/dimensoes/customclass/estruturas/__init__.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py"], "/projeto/dimensoes/models.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py", "/projeto/dimensoes/customclass/objetos/filtro.py", "/projeto/dimensoes/customclass/objetos/motor.py"], "/projeto... |
712 | leopesi/pool_budget | refs/heads/master | /projeto/dimensoes/migrations/0004_auto_20200317_0933.py | # Generated by Django 3.0.3 on 2020-03-17 12:33
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('dimensoes', '0003_remove_dimensaomodel_data'),
]
operations = [
migrations.AlterField(
model_name='dimensaomodel',
n... | {"/projeto/dimensoes/customclass/estruturas/__init__.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py"], "/projeto/dimensoes/models.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py", "/projeto/dimensoes/customclass/objetos/filtro.py", "/projeto/dimensoes/customclass/objetos/motor.py"], "/projeto... |
713 | leopesi/pool_budget | refs/heads/master | /projeto/dimensoes/migrations/0011_auto_20200516_1518.py | # Generated by Django 3.0.3 on 2020-05-16 18:18
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('dimensoes', '0010_auto_20200511_1521'),
]
operations = [
migrations.AlterField(
model_name='clientemodel',
name='tel... | {"/projeto/dimensoes/customclass/estruturas/__init__.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py"], "/projeto/dimensoes/models.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py", "/projeto/dimensoes/customclass/objetos/filtro.py", "/projeto/dimensoes/customclass/objetos/motor.py"], "/projeto... |
714 | leopesi/pool_budget | refs/heads/master | /projeto/dimensoes/migrations/0006_auto_20200318_1831.py | # Generated by Django 3.0.3 on 2020-03-18 21:31
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('dimensoes', '0005_dimensaomodel_data'),
]
operations = [
migrations.AlterField(
model_name='dimensaomodel',
name='pr... | {"/projeto/dimensoes/customclass/estruturas/__init__.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py"], "/projeto/dimensoes/models.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py", "/projeto/dimensoes/customclass/objetos/filtro.py", "/projeto/dimensoes/customclass/objetos/motor.py"], "/projeto... |
715 | leopesi/pool_budget | refs/heads/master | /projeto/dimensoes/migrations/0008_remove_precificacaomodel_custo.py | # Generated by Django 3.0.3 on 2020-04-29 20:30
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('dimensoes', '0007_auto_20200408_1540'),
]
operations = [
migrations.RemoveField(
model_name='precificacaomodel',
name='custo... | {"/projeto/dimensoes/customclass/estruturas/__init__.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py"], "/projeto/dimensoes/models.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py", "/projeto/dimensoes/customclass/objetos/filtro.py", "/projeto/dimensoes/customclass/objetos/motor.py"], "/projeto... |
716 | leopesi/pool_budget | refs/heads/master | /projeto/dimensoes/migrations/0003_remove_dimensaomodel_data.py | # Generated by Django 3.0.3 on 2020-03-16 21:38
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('dimensoes', '0002_auto_20200316_1609'),
]
operations = [
migrations.RemoveField(
model_name='dimensaomodel',
name='data',
... | {"/projeto/dimensoes/customclass/estruturas/__init__.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py"], "/projeto/dimensoes/models.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py", "/projeto/dimensoes/customclass/objetos/filtro.py", "/projeto/dimensoes/customclass/objetos/motor.py"], "/projeto... |
717 | leopesi/pool_budget | refs/heads/master | /projeto/dimensoes/migrations/0016_auto_20200611_1852.py | # Generated by Django 3.0.3 on 2020-06-11 21:52
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('dimensoes', '0015_auto_20200604_1710'),
]
operations = [
migrations.RemoveField(
model_name='dimensaomodel',
name='s... | {"/projeto/dimensoes/customclass/estruturas/__init__.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py"], "/projeto/dimensoes/models.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py", "/projeto/dimensoes/customclass/objetos/filtro.py", "/projeto/dimensoes/customclass/objetos/motor.py"], "/projeto... |
718 | leopesi/pool_budget | refs/heads/master | /projeto/dimensoes/migrations/0007_auto_20200408_1540.py | # Generated by Django 3.0.3 on 2020-04-08 18:40
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('dimensoes', '0006_auto_20200318_1831'),
]
operations = [
migrations.CreateModel(
name='PrecificacaoModel',
fields=[
... | {"/projeto/dimensoes/customclass/estruturas/__init__.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py"], "/projeto/dimensoes/models.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py", "/projeto/dimensoes/customclass/objetos/filtro.py", "/projeto/dimensoes/customclass/objetos/motor.py"], "/projeto... |
719 | leopesi/pool_budget | refs/heads/master | /projeto/dimensoes/migrations/0015_auto_20200604_1710.py | # Generated by Django 3.0.3 on 2020-06-04 20:10
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('dimensoes', '0014_dimensaomodel_profundidade_media'),
]
operations = [
migrations.RemoveField(
model_name='dimensaomodel',
n... | {"/projeto/dimensoes/customclass/estruturas/__init__.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py"], "/projeto/dimensoes/models.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py", "/projeto/dimensoes/customclass/objetos/filtro.py", "/projeto/dimensoes/customclass/objetos/motor.py"], "/projeto... |
720 | leopesi/pool_budget | refs/heads/master | /projeto/dimensoes/migrations/0019_auto_20200618_1520.py | # Generated by Django 3.0.3 on 2020-06-18 18:20
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('dimensoes', '0018_auto_20200611_1905'),
]
operations = [
migrations.AlterField(
model_name='clientemodel',
name='num... | {"/projeto/dimensoes/customclass/estruturas/__init__.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py"], "/projeto/dimensoes/models.py": ["/projeto/dimensoes/customclass/estruturas/dimensao.py", "/projeto/dimensoes/customclass/objetos/filtro.py", "/projeto/dimensoes/customclass/objetos/motor.py"], "/projeto... |
735 | moddevices/mod-devel-cli | refs/heads/master | /modcli/cli.py | import click
import crayons
from modcli import context, auth, __version__, bundle
_sso_disclaimer = '''SSO login requires you have a valid account in MOD Forum (https://forum.moddevices.com).
If your browser has an active session the credentials will be used for this login. Confirm?'''
@click.group(context_settings... | {"/modcli/cli.py": ["/modcli/__init__.py"], "/modcli/config.py": ["/modcli/__init__.py", "/modcli/utils.py"], "/modcli/auth.py": ["/modcli/__init__.py"], "/modcli/bundle.py": ["/modcli/__init__.py", "/modcli/utils.py"]} |
736 | moddevices/mod-devel-cli | refs/heads/master | /modcli/__init__.py | from modcli import config
__version__ = '1.1.3'
context = config.read_context()
| {"/modcli/cli.py": ["/modcli/__init__.py"], "/modcli/config.py": ["/modcli/__init__.py", "/modcli/utils.py"], "/modcli/auth.py": ["/modcli/__init__.py"], "/modcli/bundle.py": ["/modcli/__init__.py", "/modcli/utils.py"]} |
737 | moddevices/mod-devel-cli | refs/heads/master | /setup.py | import re
import sys
from setuptools import setup
with open('modcli/__init__.py', 'r') as fh:
version = re.search(r'^__version__\s*=\s*[\'"]([^\'"]*)[\'"]', fh.read(), re.MULTILINE).group(1)
if sys.version_info[0] < 3:
raise Exception("Must be using Python 3")
setup(
name='mod-devel-cli',
python_req... | {"/modcli/cli.py": ["/modcli/__init__.py"], "/modcli/config.py": ["/modcli/__init__.py", "/modcli/utils.py"], "/modcli/auth.py": ["/modcli/__init__.py"], "/modcli/bundle.py": ["/modcli/__init__.py", "/modcli/utils.py"]} |
738 | moddevices/mod-devel-cli | refs/heads/master | /modcli/settings.py | import os
CONFIG_DIR = os.path.expanduser('~/.config/modcli')
URLS = {
'labs': ('https://api-labs.moddevices.com/v2', 'https://pipeline-labs.moddevices.com/bundle/'),
'dev': ('https://api-dev.moddevices.com/v2', 'https://pipeline-dev.moddevices.com/bundle/'),
}
DEFAULT_ENV = 'labs'
| {"/modcli/cli.py": ["/modcli/__init__.py"], "/modcli/config.py": ["/modcli/__init__.py", "/modcli/utils.py"], "/modcli/auth.py": ["/modcli/__init__.py"], "/modcli/bundle.py": ["/modcli/__init__.py", "/modcli/utils.py"]} |
739 | moddevices/mod-devel-cli | refs/heads/master | /modcli/config.py | import base64
import json
import os
import stat
import re
from modcli import settings
from modcli.utils import read_json_file
def read_context():
context = CliContext.read(settings.CONFIG_DIR)
if len(context.environments) == 0:
for env_name, urls in settings.URLS.items():
context.add_env... | {"/modcli/cli.py": ["/modcli/__init__.py"], "/modcli/config.py": ["/modcli/__init__.py", "/modcli/utils.py"], "/modcli/auth.py": ["/modcli/__init__.py"], "/modcli/bundle.py": ["/modcli/__init__.py", "/modcli/utils.py"]} |
740 | moddevices/mod-devel-cli | refs/heads/master | /modcli/auth.py | import socket
import webbrowser
from http.server import BaseHTTPRequestHandler, HTTPServer
from urllib import parse
import click
import requests
from click import Abort
from modcli import __version__
def login(username: str, password: str, api_url: str):
result = requests.post('{0}/users/tokens'.format(api_url)... | {"/modcli/cli.py": ["/modcli/__init__.py"], "/modcli/config.py": ["/modcli/__init__.py", "/modcli/utils.py"], "/modcli/auth.py": ["/modcli/__init__.py"], "/modcli/bundle.py": ["/modcli/__init__.py", "/modcli/utils.py"]} |
741 | moddevices/mod-devel-cli | refs/heads/master | /modcli/bundle.py | import os
import shutil
import subprocess
import tempfile
from hashlib import md5
import click
import crayons
import requests
from modcli import context
from modcli.utils import read_json_file
def publish(project_file: str, packages_path: str, keep_environment: bool=False, bundles: list=None,
show_resul... | {"/modcli/cli.py": ["/modcli/__init__.py"], "/modcli/config.py": ["/modcli/__init__.py", "/modcli/utils.py"], "/modcli/auth.py": ["/modcli/__init__.py"], "/modcli/bundle.py": ["/modcli/__init__.py", "/modcli/utils.py"]} |
742 | moddevices/mod-devel-cli | refs/heads/master | /modcli/utils.py | import json
import os
def read_json_file(path: str):
if not os.path.isfile(path):
return {}
with open(path, 'r') as file:
contents = file.read()
return json.loads(contents)
| {"/modcli/cli.py": ["/modcli/__init__.py"], "/modcli/config.py": ["/modcli/__init__.py", "/modcli/utils.py"], "/modcli/auth.py": ["/modcli/__init__.py"], "/modcli/bundle.py": ["/modcli/__init__.py", "/modcli/utils.py"]} |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.