index int64 0 1,000k | blob_id stringlengths 40 40 | code stringlengths 7 10.4M |
|---|---|---|
7,300 | 1305991a9cd82ddeaffff1545a35ced992e6792f | ####################################################################################
#
# Kaggle Competition: https://www.kaggle.com/c/msk-redefining-cancer-treatment
# Sponsor : Memorial Sloan Kettering Cancer Center (MSKCC)
# Author: Amrut Shintre
#
####################################################################################
#####################
# Importing Libraries
#####################
import numpy as np
import pandas as pd
import matplotlib as plt
import re
import nltk
nltk.download('stopwords')
from nltk.corpus import stopwords
from nltk.stem.porter import PorterStemmer
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.decomposition import TruncatedSVD
from sklearn.preprocessing import LabelEncoder
from sklearn.preprocessing import StandardScaler
import xgboost as xgb
from sklearn.model_selection import train_test_split
from sklearn import metrics
import gc
import random
####################
# Importing datasets
####################
# Training Dataset
train_df = pd.read_csv('training_text', sep = '\|\|', engine = 'python', names = ['ID', 'Text'],
header = None)
train_df = train_df.iloc[1:,:]
train_df.index = range(len(train_df))
train_var = pd.read_csv('training_variants')
# Testing Dataset
test_df = pd.read_csv('test_text', sep = '\|\|', engine = 'python', names = ['ID', 'Text'],
header = None)
test_var = pd.read_csv('test_variants')
# --------------------------------------------TEXT ---------------------------------------------
##############
# TextCleaning
##############
def text_cleaning(text_df):
corpus = []
for i in range(len(text_df)):
text = re.sub('[^a-zA-Z]', ' ', text_df['Text'][i]) # Removing punctuation marks,
#numbers, etc and returning only letters
text = text.lower() # Converting all the uppercase letters to lowercase
text = text.split() # Splitting a sentence into a list of strings containing a single word.
ps = PorterStemmer() # Stemming e.g. lovely -> love
text = [ps.stem(word) for word in text if not word in set(stopwords.words('english'))]
text = ' '.join(text) # Joining the cleaned words
corpus.append(text) # Appending it to the new list.
return (corpus)
# Training Text Data
corpus_train = text_cleaning(train_df)
# Testing Text Data
corpus_test = text_cleaning(test_df)
#############################################
# Term Frequency - Inverse Document Frequency
#############################################
tfidf = TfidfVectorizer()
tfidf_tr = tfidf.fit_transform(corpus_train).toarray()
tfidf_test = tfidf.transform(corpus_test).toarray()
##############################
# Singular Value Decomposition
##############################
svd = TruncatedSVD(n_components = 1000) # considering 98% variance in the Data
svd_tr = svd.fit_transform(tfidf_tr) # Fitting on cleaned training text data
svd_train = svd.transform(tfidf_test) # Transforming on cleaned testing text data
svd_tr = pd.DataFrame(svd_tr)
svd_test = pd.DataFrame(svd_train)
#explainedvar = svd.explained_variance_ratio_
#exp_var = explainedvar.cumsum()
# -------------------------------------------- VARIANTS ---------------------------------------------
####################
# Dependent Variable
####################
y = train_var['Class'].values
y = y-1
#################
# Merging Dataset
#################
# Merging the dataset for data preparation and feature engineering
df = pd.concat([train_var, test_var], axis = 0)
df = df.drop(['ID'], axis = 1)
df['ID'] = range(df.shape[0])
df.index = range(df.shape[0])
df_text = pd.concat([train_df, test_df], axis = 0)
df_text = df_text.drop('ID', axis = 1)
df_text['ID'] = range(df_text.shape[0])
df_text.index = range(df_text.shape[0])
df_all = pd.merge(df, df_text, how = 'left', on = 'ID')
################
# Missing Values
################
# Checking for missing values
column_list = train_var.columns.values.tolist()
missing_values = pd.DataFrame()
missing_values['Columns'] = column_list
for i in column_list:
missing_values['No. of missing values'] = train_var[i].isnull().values.ravel().sum()
# There are no missing values.
#######################
# Categorical Variables
#######################
# Extracting the columns having categorical Variables.
column_list = df.columns
categorical_columns = []
for i in column_list:
if df[i].dtype == 'O':
categorical_columns.append(i)
# Encoding the columns with categorical variables
# Label Encoding
for i in categorical_columns:
le = LabelEncoder()
df[i + '_le'] = le.fit_transform(df[i])
df[i + '_length'] = df[i].map(lambda x: len(str(x)))
# Feature Engineering
df_all['Gene_Share'] = df_all.apply(lambda r: sum([1 for w in r['Gene'].split(' ') if w in r['Text'].split(' ')]), axis=1)
df_all['Variation_Share'] = df_all.apply(lambda r: sum([1 for w in r['Variation'].split(' ') if w in r['Text'].split(' ')]), axis=1)
###################
# Splitting Dataset
###################
train = df_all.iloc[:len(train_var), :]
test = df_all.iloc[len(train_var):,:]
test.index = range(len(test_var))
train = train.drop(['Gene', 'Variation', 'ID', 'Text', 'Class'], axis = 1)
test = test.drop(['Gene', 'Variation', 'Text', 'ID', 'Class'], axis = 1)
train_final = pd.concat([train, svd_tr], axis = 1)
test_final = pd.concat([test, svd_test], axis = 1)
#################
# Standardization
#################
sc = StandardScaler()
train_final = sc.fit_transform(train_final)
test_final = sc.transform(test_final)
train_final = pd.DataFrame(train_final)
test_final = pd.DataFrame(test_final)
# -------------------------------------------- MODEL ---------------------------------------------
##################
# XGBoost Matrix
##################
dtrain = xgb.DMatrix(train_final, y)
dtest = xgb.DMatrix(test_final)
##################
# Cross-Validation
##################
def docv(param, iterations, nfold):
model_CV = xgb.cv(
params = param,
num_boost_round = iterations,
nfold = nfold,
dtrain = dtrain,
seed = random.randint(1, 10000),
early_stopping_rounds = 100,
maximize = False,
verbose_eval = 50)
gc.collect()
best = min(model_CV['test-mlogloss-mean'])
best_iter = model_CV.shape[0]
print (best)
return (best_iter)
#########
# Testing
#########
def doTest(param, iteration):
X_tr, X_val, y_tr, y_val = train_test_split(train_final, y, test_size = 0.2, random_state = random.randint(1,1000))
watchlist = [(xgb.DMatrix(X_tr, y_tr), 'train'), (xgb.DMatrix(X_val, y_val), 'validation')]
model = xgb.train(
params = param,
dtrain = xgb.DMatrix(X_tr, y_tr),
num_boost_round = iteration,
evals = watchlist,
verbose_eval = 50,
early_stopping_rounds = 100)
score = metrics.log_loss(y_val, model.predict(xgb.DMatrix(X_val)), labels = range(9))
predicted_class = model.predict(dtest)
print (score)
return (predicted_class)
#########
# Bagging
#########
def Bagging(N, params, best_iter):
for i in range(N):
param = params
p = doTest(param, best_iter)
if i == 0:
preds = p.copy()
else:
preds = preds + p
predictions = preds/N
predictions = pd.DataFrame(predictions)
return (predictions)
###################
# Running the Model
###################
params = {
'eta': 0.02,
'max_depth': 6,
'objective': 'multi:softprob',
'eval_metric': 'mlogloss',
'silent': False,
'seed': random.randint(1,100),
'num_class': 9
}
cross_vali = docv(params, 10000, 5)
predicted_class = Bagging(5, params, cross_vali)
# -------------------------------------------- SUBMISSION ---------------------------------------------
sub_file = pd.DataFrame()
sub_file['ID'] = test_var['ID'].values
Sub_File = pd.concat([sub_file, predicted_class], axis = 1)
Sub_File.columns = ['ID', 'Class1', 'Class2', 'Class3', 'Class4', 'Class5', 'Class6', 'Class7',
'Class8', 'Class9']
Sub_File.to_csv("submission33.csv", index = False)
# -------------------------------------------- Project Layout ---------------------------------------------
# 1) Text Cleaning
# 2) TFIDF Vectorizer and Singular Value Decomposition
# 3) Feature Engineering
# 4) Building a Model and trying out different models
# 5) Parameter Tuning
# 6) Bagged Boosting |
7,301 | aec374ffa368755350d0d75c96860f760e8524e1 | from django.shortcuts import render, redirect
from django.contrib import messages
from django.contrib.auth import authenticate, login, logout
from .models import Post
from django.shortcuts import redirect
from django.core.exceptions import ObjectDoesNotExist
def index(request):
blogs = Post.objects.filter(status=1).order_by('-created_on')[:10]
context = {'Post': blogs}
return render(request, 'blogapp/index.html', context)
def blogs(request):
return render(request, template_name='blogapp/blog.html')
def detail(request, slug):
try:
post = Post.objects.get(slug=slug)
context = {'post': post}
return render(request, 'blogapp/detail.html', context)
except ObjectDoesNotExist:
return render(request, template_name='blogapp/detail.html')
def about(request):
return render(request, template_name='blogapp/about.html')
def loginPage(request):
# form = CreateUserForm()
# context = {'form': form}
if request.method == 'POST':
username = request.POST.get('username')
password = request.POST.get('password1')
user = authenticate(username=username, password=password)
if user is not None:
login(request, user)
return redirect('index')
else:
messages.error(request, 'Username or Password Incorrect')
return render(request, 'accounts/login.html',)
else:
return render(request, 'accounts/login.html',)
def logoutUser(request):
logout(request)
return redirect('login')
def contact(request):
return render(request, template_name='blogapp/contact.html')
def products(request):
return render(request, template_name='mainapp/products.html') |
7,302 | e8ef3a5e41e68b4d219aa1403be392c51cc010e6 | """
对自定义的类进行排序
"""
import operator
class User:
def __init__(self, name, id):
self.name = name
self.id = id
def __repr__(self):
return 'User({},{})'.format(self.name, self.id)
def run():
users = [User('wang', 1), User('zhao', 4), User('chen', 3), User('wang', 2)]
# 这种方式相对速度快，也适用于min／max等
a = sorted(users, key=operator.attrgetter('id', 'name'))
print(a)
b = sorted(users, key=lambda r: (r.id, r.name))
print(b)
if __name__ == '__main__':
run() |
7,303 | 562888201719456ed2f3c32e81ffd7d2c39dabc3 | # Generated by Django 3.1.2 on 2020-10-25 01:19
import datetime
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('jobs', '0001_initial'),
]
operations = [
migrations.AddField(
model_name='job',
name='link',
field=models.URLField(null=True),
),
migrations.AddField(
model_name='job',
name='title',
field=models.CharField(default=datetime.date(2020, 10, 25), max_length=200),
preserve_default=False,
),
]
|
7,304 | 01e9ceb516a323a2017c65e368da419c6570dce2 | # -* coding: utf-8 -*-
# A headless media player based on gstreamer.
from gi.repository import Gst
Gst.init(None)
class Player:
def __init__(self, uri=None):
# Creates a playbin (plays media from an uri).
self.player = Gst.ElementFactory.make('playbin', 'player')
self.uri = uri
@property
def uri(self):
return self._uri
@uri.setter
def uri(self, value):
self._uri = value
self.player.set_state(Gst.State.NULL)
if value:
self.player.set_property('uri', value)
def play(self):
"""Start playing"""
self.player.set_state(Gst.State.PLAYING)
def pause(self):
"""Pause playing"""
self.player.set_state(Gst.State.PAUSED)
def stop(self):
self.player.set_state(Gst.State.NULL)
|
7,305 | b6ee3c980357ab22a7969c21207b34546c87092d | from .exec_generator import * |
7,306 | bb64da929ff2e1e04267518ec93a28bedb5a4de5 | # ---------------------MODULE 1 notes--------------------
# .
# .
# .
# .
# .
# .
# .
# .
# .
# .
# save as (file).py first if not it will not work
print("Hello")
# control s to save
|
7,307 | 0cf90cd7704db9f7467e458b402fadb01c701148 | from search import SearchEngine
import tkinter as tk
if __name__ == "__main__":
ghettoGoogle = SearchEngine()
def searchButtonEvent():
search_query = searchQueryWidget.get()
search_results = ghettoGoogle.search(search_query)
resultsCanvas = tk.Tk()
if search_results == None:
tk.Label(resultsCanvas,text="No results",justify=tk.LEFT).pack(fill='both')
else:
searchTextBox = tk.Text(resultsCanvas,height=20,width=100)
searchTextBox.pack(side=tk.LEFT,fill=tk.Y)
scrollBar = tk.Scrollbar(resultsCanvas)
scrollBar.pack(side=tk.RIGHT,fill=tk.Y)
scrollBar.config(command=searchTextBox.yview)
searchTextBox.config(yscrollcommand=scrollBar.set)
searchTextBox.tag_config('Link',foreground='blue')
for i in range(len(search_results)):
searchTextBox.insert(tk.END,search_results[i][0]+"\n",'Link')
searchTextBox.insert(tk.END,search_results[i][1]+"\n\n")
canvas = tk.Tk()
tk.Label(canvas, text = "Enter search query").grid(row = 0)
searchQueryWidget = tk.Entry(canvas)
searchQueryWidget.grid(row=0,column=1)
tk.Button(canvas,text="Quit",command=canvas.quit).grid(row=1,column=0,sticky=tk.W)
tk.Button(canvas,text="Search",command=searchButtonEvent).grid(row=1,column=0,sticky=tk.W)
canvas.mainloop()
|
7,308 | 282dbdb3a8d9ed914e8ca5c7fa74d2873920e18c | def area (a, b):
resultado = a * b
return (resultado)
def main():
#escribe tu código abajo de esta línea
num1 = float(input("INTRODUCE LA BASE: "))
num2 = float(input("INTRODUCE LA ALTURA: "))
print ("EL AREA DEL RECTANGULO ES: ", area (num1, num2))
pass
if __name__ == '__main__':
main()
|
7,309 | f311b803d8c0ee68bc43526f56e6b14f3a2836b8 | #### As an example below shell script can be used to execute this every 300s.
####!/bin/bash
####while true
####do
#### /usr/bin/sudo python3 /path/of/the/python/script.sh
####done
#!/usr/bin/python
import sys
import time
import paho.mqtt.client as mqtt
broker_url = "<IP_Address_of_MQTT_broker>"
broker_port = <MQTT_Broker_port>
def on_connect(client, userdata, flags, rc):
print("Connected With Result Code: {}".format(rc))
def on_message(client, userdata, message):
print("Message Recieved: "+message.payload.decode())
file_name=message.payload.decode()
file_path="/home/demouser/nagios/node-check/logs/"+file_name+".ok"
file1 = open(file_path, 'w')
file1.write(message.payload.decode()+" is up and running\n")
file1.close()
def on_disconnect(client, userdata, rc):
print("Client Got Disconnected")
client = mqtt.Client("Nagios_NodeChecker")
client.on_connect = on_connect
client.on_disconnect = on_disconnect
client.on_message = on_message
client.username_pw_set(username="<mqtt_username>",password="<mqtt_password>")
client.connect(broker_url, broker_port)
client.subscribe(topic="nagios/node_check", qos=2)
client.message_callback_add("nagios/node_check", on_message)
client.loop_start()
time.sleep(300)
client.loop_stop()
|
7,310 | b5568e84e19719f0fd72197ead47bd050e09f55d | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# groupby()
# groupby()把迭代器中相邻的重复元素挑出来放在一起：
import itertools
for key, group in itertools.groupby('ABAABBBCCAAA'):
print(key, list(group))
# 小结
# itertools模块提供的全部是处理迭代功能的函数，它们的返回值不是list，而是Iterator，只有用for循环迭代的时候才真正计算。
|
7,311 | 54d6121898dc027d6ecaf9c9e7c25391778e0d21 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# sockdemo.py
#
# test
import struct, threading, signal
a = ''
if not a:
print 'a'
else:
print 'b'
import datetime, time, os
print datetime.datetime.now().strftime('%m-%d %H:%M:%S')
def double(x): return x*x
arr = [1, 2, 3, 4, 5]
print map(double, arr)
print 2**16
print struct.calcsize('128s32sI8s')
_pack = struct.pack('128s8sI8s','abc','huad',1,'666')
print repr(_pack)
a,b,c,d = struct.unpack('128s8sI8s',_pack)
print a.strip('\00')
now = datetime.datetime.now()
isstop = False
def handler():
print 'control C'
isstop = True
def doStress():
print 123222
while not isstop:
time.sleep(1)
print 'doStress', datetime.datetime.now()
#signal.signal(signal.SIGINT, handler)
#signal.signal(signal.SIGTERM, handler)
t = threading.Thread(target=doStress, args=())
t.setDaemon(True)
t.start()
print 'complete', datetime.datetime.now()
|
7,312 | 5f84c8654c976bca2fa33e8f9ba5e28e3249253d | import numpy as np
import faiss
from util import vecs_io, vecs_util
from time import time
import os
'''
提取vecs, 输出numpy文件
'''
def vecs2numpy(fname, new_file_name, file_type, file_len=None):
if file_type == 'bvecs':
vectors, dim = vecs_io.bvecs_read_mmap(fname)
elif file_type == 'ivecs':
vectors, dim = vecs_io.ivecs_read_mmap(fname)
elif file_type == 'fvecs':
vectors, dim = vecs_io.fvecs_read_mmap(fname)
if file_len is not None:
vectors = vectors[:file_len]
vectors = vectors.astype(np.float32)
np.save(new_file_name, vectors)
return vectors
'''
创建文件夹, 提取base, query, gnd
'''
def get_base_query_gnd(config):
os.system("mkdir %s" % (config['project_data_dir']))
print("创建文件夹")
base_dir = '%s/%s' % (config['source_data_dir'], config['source_data_fname']['base'])
base_npy_dir = '%s/%s' % (config['project_data_dir'], 'dataset.npy')
base = vecs2numpy(base_dir, base_npy_dir, config['dataset_type'])
print("提取base")
query_dir = '%s/%s' % (config['source_data_dir'], config['source_data_fname']['query'])
query_npy_dir = '%s/%s' % (config['project_data_dir'], 'queries.npy')
query = vecs2numpy(query_dir, query_npy_dir, config['dataset_type'])
print("提取query")
gnd_npy_dir = '%s/%s' % (config['project_data_dir'], 'answers.npy')
# print(base_npy_dir)
# print(query_npy_dir)
# print(gnd_npy_dir)
gnd = vecs_util.get_gnd_numpy(base, query, config['k_gnd'], gnd_npy_dir)
print("提取gnd")
return base, query, gnd
if __name__ == '__main__':
fname = '/home/bz/learn-to-hash/data/sift/sift_dataset_unnorm.npy'
new_fname = '/home/bz/learn-to-hash/data/sift/sift_graph_10/test_graph.txt'
get_NN_graph(fname, new_fname, 10)
a = '/home/bz/KaHIP/deploy/graphchecker'
b = '/home/bz/learn-to-hash/data/sift/sift_graph_10/test_graph.txt'
|
7,313 | 8340872f03c1bf7c1aee0c437258ac8e44e08bb8 | # 5.2 Training a convnet from scratch on a "small dataset" (p.131)
# Preprocessing (p.133)
# Copying images to train, validation and test directories
import os, shutil
# The path to the directory where the original dataset was uncompressed
original_dataset_dir = 'E:/train/'
# The directory where we will store our smaller dataset
base_dir = 'E:/train/smaller'
os.mkdir(base_dir)
# Directories for our training, validation, and test splits
train_dir = os.path.join(base_dir, 'train')
os.mkdir(train_dir)
validation_dir = os.path.join(base_dir, 'validation')
os.mkdir(validation_dir)
test_dir = os.path.join(base_dir, 'test')
os.mkdir(test_dir)
# Directory with our training cat pictures
train_cats_dir = os.path.join(train_dir, 'cats')
os.mkdir(train_cats_dir)
# Directory with our training dog pictures
train_dogs_dir = os.path.join(train_dir, 'dogs')
os.mkdir(train_dogs_dir)
# Directory with our validation cat pictures
validation_cats_dir = os.path.join(validation_dir, 'cats')
os.mkdir(validation_cats_dir)
# Directory with our validation dog pictures
validation_dogs_dir = os.path.join(validation_dir, 'dogs')
os.mkdir(validation_dogs_dir)
# Directory with our validation cat pictures
test_cats_dir = os.path.join(test_dir, 'cats')
os.mkdir(test_cats_dir)
# Directory with our validation dog pictures
test_dogs_dir = os.path.join(test_dir, 'dogs')
os.mkdir(test_dogs_dir)
# Copy first 1000 cat images to train_cats_dir
fnames = ['cat.{}.jpg'.format(i) for i in range(1000)]
for fname in fnames:
src = os.path.join(original_dataset_dir, fname)
dst = os.path.join(train_cats_dir, fname)
shutil.copyfile(src, dst)
# Copy next 500 cat images to validation_cats_dir
fnames = ['cat.{}.jpg'.format(i) for i in range(1000, 1500)]
for fname in fnames:
src = os.path.join(original_dataset_dir, fname)
dst = os.path.join(validation_cats_dir, fname)
shutil.copyfile(src, dst)
# Copy next 500 cat images to test_cats_dir
fnames = ['cat.{}.jpg'.format(i) for i in range(1500, 2000)]
for fname in fnames:
src = os.path.join(original_dataset_dir, fname)
dst = os.path.join(test_cats_dir, fname)
shutil.copyfile(src, dst)
# Copy first 1000 dog images to train_dogs_dir
fnames = ['dog.{}.jpg'.format(i) for i in range(1000)]
for fname in fnames:
src = os.path.join(original_dataset_dir, fname)
dst = os.path.join(train_dogs_dir, fname)
shutil.copyfile(src, dst)
# Copy next 500 dog images to validation_dogs_dir
fnames = ['dog.{}.jpg'.format(i) for i in range(1000, 1500)]
for fname in fnames:
src = os.path.join(original_dataset_dir, fname)
dst = os.path.join(validation_dogs_dir, fname)
shutil.copyfile(src, dst)
# Copy next 500 dog images to test_dogs_dir
fnames = ['dog.{}.jpg'.format(i) for i in range(1500, 2000)]
for fname in fnames:
src = os.path.join(original_dataset_dir, fname)
dst = os.path.join(test_dogs_dir, fname)
shutil.copyfile(src, dst)
# 5.2.3 Building our network
from keras import layers
from keras import models
model = models.Sequential()
model.add(layers.Conv2D(32, (3, 3), activation='relu', input_shape=(150, 150, 3)))
model.add(layers.MaxPool2D((2, 2)))
model.add(layers.Conv2D(64, (3, 3), activation='relu'))
model.add(layers.MaxPool2D((2, 2)))
model.add(layers.Conv2D(128, (3, 3), activation='relu'))
model.add(layers.MaxPool2D((2, 2)))
model.add(layers.Conv2D(128, (3, 3), activation='relu'))
model.add(layers.MaxPool2D((2, 2)))
model.add(layers.Flatten())
model.add(layers.Dense(512, activation='relu'))
model.add(layers.Dense(1, activation='sigmoid'))
from keras import optimizers
model.compile(loss='binary_crossentropy',
optimizer=optimizers.RMSprop(lr=1e-4),
metrics=['acc'])
# 5.2.4 Data preprocessing (p.137)
# 1) Read the picture files.
# 2) Decode the JPEG content to RBG grids of pixels.
# 3) Convert these into floating point tensors.
# 4) Rescale the pixel values (between 0 and 255) to the [0, 1] interval
# (as you know, neural networks prefer to deal with small input values).
from keras.preprocessing.image import ImageDataGenerator
train_datagen = ImageDataGenerator(rescale=1.0 / 255)
test_datagen = ImageDataGenerator(rescale=1.0 / 255)
train_generator = train_datagen.flow_from_directory(train_dir,
target_size=(150, 150),
batch_size=20,
class_mode='binary')
validation_generator = test_datagen.flow_from_directory(validation_dir,
target_size=(150, 150),
batch_size=20,
class_mode='binary')
# Listing 5.16 Fitting our model using a batch generator (p.138)
|
7,314 | 800d87a879987c47f1a66b729932279fc8d4fa38 | #Homework 2 PyPoll
#The total number of votes cast
#A complete list of candidates who received votes
#The percentage of votes each candidate won
#The total number of votes each candidate won
#The winner of the election based on popular vote.
#First we'll import the os module
# This will allow us to create file paths across operating systems
import os
#currentDirectory = os.getcwd()
# Module for reading CSV files
import csv
csvpath = os.path.join('election_data.csv')
with open('election_data.csv') as csvfile:
# CSV reader specifies delimiter and variable that holds contents
csvreader = csv.reader(csvfile, delimiter=',')
print(csvreader)
|
7,315 | 3ef114dd35ef3995ae73bf85bbe38db4fb7045d8 |
#from __future__ import absolute_import
#import os
from celery import Celery
#from django.conf import settings
#os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'learning.settings')
app = Celery('tasks', broker="redis://localhost")
#app.config_from_object('django.conf:settings')
#app.autodiscover_tasks(lambda: settings.INSTALLED_APPS)
@app.task
def add(x, y):
return x+y
#print('Request:{0!r}'.format(self.request))
|
7,316 | 7c80c98e32f386362003ac3cd729fa9b279b8e8e | import numpy as np
import cv2
import serial
import serial.tools.list_ports
import time
import random
import math
#import mcpi.minecraft as minecraft
#import mcpi.block as block
#from house import House
#Arduino Serials
ports = list(serial.tools.list_ports.comports())
print (ports)
for p in ports:
print (p[1])
if "Arduino" in p[1]:
ser=serial.Serial(port=p[0])
else :
print ("No Arduino Device was found connected to the computer")
#time.sleep(2)
#face detection
cap =cv2.VideoCapture(1)
face_cascade = cv2.CascadeClassifier('./haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('./haarcascade_eye.xml')
lastpos=0
currentpos=0
lastdis=0
currentdis=0
lastx_d=0
currentx_d=0
shoot=0
#MC
#mc=minecraft.Minecraft.create()
#pos=mc.player.getTilePos()
#pos0=[]
#pos0.append(pos.x)
#pos0.append(pos.y)
#pos0.append(pos.z)
#des=House([pos.x+20,pos.y,pos.z],mc,block.GOLD_BLOCK.id,block.GLASS.id)
#des.buildall()
ct=0
while(True):
ct+=1
#到达目的地了吗
#if(des.isInsideHouse()):
#mc.postToChat("You win")
#break
#人脸识别，一方面投石机追踪，一方面控制MC里面人到Destinatioin
ret,img=cap.read()
center=[img.shape[0]/2,img.shape[1]/2]
faces = face_cascade.detectMultiScale(img, 1.3, 5)
tmp=0
for(x,y,w,h) in faces:
tmp+=1
if(tmp>1):
print("too many faces")
else:
for (x,y,w,h) in faces:
img = cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
roi_color = img[y:y+h, x:x+w]
x_d=x+w/2-325-73
dis=(-0.88*w+220)
angle=x_d#math.atan(x_d/dis)/3.1415926535897*180
currentpos=angle
currentdis=dis
currentx_d=x_d
if(ct==1):
lastpos=currentpos
lastdis=currentdis
lastx_d=currentx_d
#pos=mc.player.getTilePos()
#mc.player.setTilePos([pos.x+(currentx_d-lastx_d)/5,pos.y,pos.z+(currentdis-lastdis)/5])
#print(x_d)
#print(angle)
#ser.write
print(str(int(angle)).encode())
#ser.write
if(angle<0):
ser.write(str(int(angle)).encode())
else:
ser.write(("+"+str(int(angle))).encode())
time.sleep(1)
if((lastpos-currentpos)<10 and abs(angle)<15):
shoot+=1
if(shoot>1):
time.sleep(2)
#mc.player.setTilePos([0,-1000,0])
ser.write(str(10000).encode())
time.sleep(2)
shoot=0
lastpos=currentpos
lastdis=currentdis
lastx_d=currentx_d
cv2.imshow('img',img)
if cv2.waitKey(1)& 0xFF==ord('q'):
break
cap.release()
cv2.destroyAllWindows()
|
7,317 | 50e759ff24cdb8fbb5a98d9381afb13ebc1a74f1 | import json
from bottle import request, response, route, get, run, default_app
app = application = default_app()
@route('/candidate/hired', method=['POST'])
def update_delete_handler():
response.content_type = 'application/json'
return json.dumps({"hired": True})
def main():
run(host='localhost', port=8080)
|
7,318 | ad84a5bfcf82dff1f4a7e8f08f3c4243ad24de52 | from foods.fruits import *
orange.eat()
apple.eat()
|
7,319 | 2867a7b24b4911b2936cb34653fa57431c14d6a3 | #Displaying multiple images using matplotlib
import pandas as pd
import numpy as np
import cv2
import matplotlib.pyplot as plt
def main():
imgpath1="C:\Shreyas\OpenCv\DIP_OpenCV\lena.png"
imgpath2="C:\Shreyas\OpenCv\DIP_OpenCV\lena.png"
img1=cv2.imread(imgpath1,1)
img2=cv2.imread(imgpath2,1)
titles = ['Pepper Gray', 'Peppers Color']
images = [img1, img2]
for i in range(2):
plt.subplot(1, 2, i+1)
plt.imshow(images[i])
plt.title(titles[i])
plt.xticks([])
plt.yticks([])
plt.show()
if __name__ == "__main__":
main()
|
7,320 | 8142585827590f6d951f0fcc375e8511aa75e9c8 | # from https://github.com/tensorflow/models/tree/master/research/object_detection/dataset_tools
# and https://gist.github.com/saghiralfasly/ee642af0616461145a9a82d7317fb1d6
import tensorflow as tf
from object_detection.utils import dataset_util
import os
import io
import hashlib
import xml.etree.ElementTree as ET
import random
from PIL import Image
def create_example(xml_file):
tree = ET.parse(xml_file)
root = tree.getroot()
image_name = root.find('filename').text
file_name = image_name.encode('utf8')
size=root.find('size')
width = int(size[0].text)
height = int(size[1].text)
xmin = []
ymin = []
xmax = []
ymax = []
classes = []
classes_text = []
truncated = []
poses = []
difficult_obj = []
for member in root.findall('object'):
classes_text.append(member[0].text)
def class_text_to_int(row_label):
if row_label == 'car-red':
return 1
if row_label == 'car-blue':
return 2
if row_label == 'phone':
return 3
classes.append(class_text_to_int(member[0].text))
xmin.append(float(member[4][0].text) / width)
ymin.append(float(member[4][1].text) / height)
xmax.append(float(member[4][2].text) / width)
ymax.append(float(member[4][3].text) / height)
difficult_obj.append(0)
truncated.append(0)
poses.append('Unspecified'.encode('utf8'))
full_path = os.path.join('./data/images', '{}'.format(image_name))
with tf.gfile.GFile(full_path, 'rb') as fid:
encoded_jpg = fid.read()
encoded_jpg_io = io.BytesIO(encoded_jpg)
image = Image.open(encoded_jpg_io)
if image.format != 'JPEG':
raise ValueError('Image format not JPEG')
key = hashlib.sha256(encoded_jpg).hexdigest()
example = tf.train.Example(features=tf.train.Features(feature={
'image/height': dataset_util.int64_feature(height),
'image/width': dataset_util.int64_feature(width),
'image/filename': dataset_util.bytes_feature(file_name),
'image/source_id': dataset_util.bytes_feature(file_name),
'image/key/sha256': dataset_util.bytes_feature(key.encode('utf8')),
'image/encoded': dataset_util.bytes_feature(encoded_jpg),
'image/format': dataset_util.bytes_feature('jpeg'.encode('utf8')),
'image/object/bbox/xmin': dataset_util.float_list_feature(xmin),
'image/object/bbox/xmax': dataset_util.float_list_feature(xmax),
'image/object/bbox/ymin': dataset_util.float_list_feature(ymin),
'image/object/bbox/ymax': dataset_util.float_list_feature(ymax),
'image/object/class/text': dataset_util.bytes_list_feature(classes_text),
'image/object/class/label': dataset_util.int64_list_feature(classes),
'image/object/difficult': dataset_util.int64_list_feature(difficult_obj),
'image/object/truncated': dataset_util.int64_list_feature(truncated),
'image/object/view': dataset_util.bytes_list_feature(poses),
}))
return example
def main(_):
writer_train = tf.python_io.TFRecordWriter('./data/train.record')
writer_test = tf.python_io.TFRecordWriter('./data/test.record')
filename_list=tf.train.match_filenames_once("./data/annotations/*.xml")
init = (tf.global_variables_initializer(), tf.local_variables_initializer())
sess=tf.Session()
sess.run(init)
list=sess.run(filename_list)
random.shuffle(list)
i=1
tst=0
trn=0
for xml_file in list:
example = create_example(xml_file)
if (i%5)==0:
writer_test.write(example.SerializeToString())
tst=tst+1
else:
writer_train.write(example.SerializeToString())
trn=trn+1
i=i+1
print(xml_file)
writer_test.close()
writer_train.close()
print('Successfully converted dataset to TFRecord.')
print('training dataset: # ')
print(trn)
print('test dataset: # ')
print(tst)
if __name__ == '__main__':
tf.app.run() |
7,321 | 1c5cb9363c2903905f1026ede77615e8373c250b | from django.db import models
# Create your models here.
class Login(models.Model):
trinity_id = models.CharField('',max_length=200)
trinity_password = models.CharField('',max_length=500)
objects = models.Manager() |
7,322 | c91be6cc332139c5b1e7ee5a3512482d0f8620b1 |
def selectionSort(arr, low, high):
for i in range(len(arr)):
mini = i
for j in range(i + 1, len(arr)):
if arr[mini] > arr[j]:
mini = j
arr[i], arr[mini] = arr[mini], arr[i]
return arr
|
7,323 | 58667da8898c2277ecc3d9d738d6553dd3416436 | ############################################-############################################
################################ F I L E A U T H O R S ################################
# MIKE - see contacts in _doc_PACKAGE_DESCRIPTION
####################################### A B O U T #######################################
# In this module:
# I clean the out put directories
####################################### S T A R T #######################################
import _cfg_GLOBAL as CFG
import os
import LOG
import UTILITY as UTL
import datetime
def some_func():
CFG.start_clock_module = datetime.datetime.now()
LOG.write_me("\tSTART - CLEAN.py (" + datetime.datetime.now().strftime("%y-%m-%d | %H:%M") + ")")
my_root_dir = os.getcwd()
list_output_dir = list()
list_of_files = list()
LOG.write_me("\t\tList of the files deleted from the 'OUTPUT' folders:")
for root, dirs, files in os.walk(my_root_dir):
if not str(root).endswith("ABACUS"):
if "OUTPUT_" in str(root):
for file in files:
if str(file).endswith(".txt"):
rel_path_file = os.path.relpath(root, my_root_dir) + "/" + file
LOG.write_me("\t\t- " + rel_path_file )
path_file = root + "\\" + file
os.remove(path_file)
list_of_files.append(rel_path_file)
if len(list_of_files) == 0:
LOG.write_me("\t\t\t- No output file to clean")
elapsed_formatted = UTL.format_elapsed(CFG.start_clock_module)
LOG.write_me("\tEND - CLEAN.py (" + datetime.datetime.now().strftime("%y-%m-%d | %H:%M") + " | hh.mm.ss.ms " + elapsed_formatted + ")")
LOG.write_me("")
LOG.write_me("")
if __name__ == '__main__':
some_func() |
7,324 | 1ebf92cf40053e561b04a666eb1dd36f54999e2c |
if __name__ == '__main__':
import sys
import os.path
srcpath = sys.argv[1] if len(sys.argv) >= 1 else './'
verfn = sys.argv[2] if len(sys.argv) >= 2 else None
try :
with open(os.path.join(srcpath,'.svn/entries'),'r') as fp:
x = fp.read().splitlines()[3]
if verfn :
with open(verfn,'w') as fp :
fp.write(x)
else :
sys.stdout.write(x)
except IOError, e :
import traceback
traceback.print_exc()
pass
|
7,325 | 3f1715763a066fb337b3ff3d03e3736d0fb36b3f | from PyQt5 import QtCore
from PyQt5.QtWidgets import QTableWidgetItem, QDialog
from QT_view.PassportAdd import PassportAddDialog
from QT_view.PassportWin import Ui_Dialog
from Repository.Rep_Passport import PassportRepository
class PassportQt(QDialog):
def __init__(self):
super(PassportQt, self).__init__()
self.passport_rep = PassportRepository()
self.initUI()
def initUI(self):
self.ui = Ui_Dialog()
self.ui.setupUi(self)
self.ui.tableWidget.setColumnWidth(1, 259)
self.ui.tableWidget.setSelectionBehavior(1)
self.ui.tableWidget.setSelectionMode(1)
self.ui.pushButton.clicked.connect(self.click_add)
self.ui.pushButton_2.clicked.connect(self.click_edit)
self.ui.pushButton_3.clicked.connect(self.click_del)
self.ui.pushButton_4.clicked.connect(self.click_cancel)
passport = self.passport_rep.get_passports()
self.ui.tableWidget.setRowCount(len(passport))
row = 0
for i in passport:
id_passport = QTableWidgetItem(str(i['id']))
id_passport.setFlags(
QtCore.Qt.ItemIsSelectable | QtCore.Qt.ItemIsEnabled
)
serial_passport = QTableWidgetItem(i['serial'])
serial_passport.setFlags(
QtCore.Qt.ItemIsSelectable | QtCore.Qt.ItemIsEnabled
)
number_passport = QTableWidgetItem(i['number'])
number_passport.setFlags(
QtCore.Qt.ItemIsSelectable | QtCore.Qt.ItemIsEnabled
)
self.ui.tableWidget.setItem(row, 0, id_passport)
self.ui.tableWidget.setItem(row, 1, serial_passport)
self.ui.tableWidget.setItem(row, 2, number_passport)
row += 1
def click_add(self):
p_dict = {'id': -1, 'serial': "", 'number': ""}
self.passport_rep.set_dict(p_dict)
passport_add = PassportAddDialog(self.passport_rep)
if (passport_add.exec()):
passport_d = self.passport_rep.get_dict()
count_row = self.ui.tableWidget.rowCount()
self.ui.tableWidget.setRowCount(count_row + 1)
id_passport = QTableWidgetItem(str(passport_d['id']))
id_passport.setFlags(
QtCore.Qt.ItemIsSelectable | QtCore.Qt.ItemIsEnabled
)
serial = QTableWidgetItem(passport_d['serial'])
serial.setFlags(
QtCore.Qt.ItemIsSelectable | QtCore.Qt.ItemIsEnabled
)
number = QTableWidgetItem(passport_d['number'])
number.setFlags(
QtCore.Qt.ItemIsSelectable | QtCore.Qt.ItemIsEnabled
)
self.ui.tableWidget.setItem(count_row, 0, id_passport)
self.ui.tableWidget.setItem(count_row, 1, serial)
self.ui.tableWidget.setItem(count_row, 2, number)
def click_edit(self):
edit_list = self.ui.tableWidget.selectedItems()
if (len(edit_list)):
select_row = self.ui.tableWidget.currentRow()
edit_d = {'id': int(edit_list[0].text()), 'serial': edit_list[1].text(), 'number': edit_list[2].text()}
self.passport_rep.set_dict(edit_d)
passport_edit = PassportAddDialog(self.passport_rep)
if (passport_edit.exec()):
passport_d = self.passport_rep.get_dict()
id_passport = QTableWidgetItem(str(passport_d['id']))
id_passport.setFlags(
QtCore.Qt.ItemIsSelectable | QtCore.Qt.ItemIsEnabled
)
serial = QTableWidgetItem(passport_d['serial'])
serial.setFlags(
QtCore.Qt.ItemIsSelectable | QtCore.Qt.ItemIsEnabled
)
number = QTableWidgetItem(passport_d['number'])
number.setFlags(
QtCore.Qt.ItemIsSelectable | QtCore.Qt.ItemIsEnabled
)
self.ui.tableWidget.setItem(select_row, 0, id_passport)
self.ui.tableWidget.setItem(select_row, 1, serial)
self.ui.tableWidget.setItem(select_row, 2, number)
def click_del(self):
del_list = self.ui.tableWidget.selectedItems()
if (len(del_list)):
del_p = {'id': int(del_list[0].text()), 'serial': del_list[1].text(), 'number': del_list[2].text()}
self.passport_rep.del_passport(del_p)
self.ui.tableWidget.removeRow(del_list[0].row())
def click_cancel(self):
self.accept() |
7,326 | 5af5c10c149c7b0e2a969be7895780d26a4294d0 | import csv
with open('faculty.csv') as facultycsv:
emails = list() #all email addresses
for line in facultycsv:
line = line.split(',')
if line[0] == 'name' : continue
try:
email = line[3].rstrip()
emails.append(email)
except:
continue
with open('emails.csv', 'w') as emailcsv:
writer = csv.writer(emailcsv, quoting=csv.QUOTE_MINIMAL)
for email in emails:
writer.writerow([email])
|
7,327 | 956adc5961188458393b56564649ad0a3a787669 | x = 5
y = x
print(id(x))
print(id(y))
print()
y = 3
print(id(x))
print(id(y))
print()
z = [1, 4, 3, 25]
w = z
print(z)
print(w)
print(id(z))
print(id(w))
print()
w[1] = 10
print(z)
print(w)
print(id(z))
print(id(w))
# So when you assign a mutable, you're actually assigning a reference to the mutable,
# and I have the side effect that when I change an element of that list in one place,
# it gets changed in both places because it's really just one object, and functions work exactly the same way.
|
7,328 | af5ebdcd818fdf9c607240733b7b5dbb793cf55e | # put your python code here
a = int(input())
b = int(input())
# and
i = 1
if a == b:
print(a)
else:
while True:
if i // a > 0 and i % a == 0 and i // b > 0 and i % b == 0:
print(i)
break
else:
i += 1
|
7,329 | 3b9193fcd69b0387222feab96c50bf3617606cdd | from typing import List, cast
import numpy as np
from ..dataset import Transition
from .base import TransitionIterator
class RandomIterator(TransitionIterator):
_n_steps_per_epoch: int
def __init__(
self,
transitions: List[Transition],
n_steps_per_epoch: int,
batch_size: int,
n_steps: int = 1,
gamma: float = 0.99,
n_frames: int = 1,
real_ratio: float = 1.0,
generated_maxlen: int = 100000,
):
super().__init__(
transitions=transitions,
batch_size=batch_size,
n_steps=n_steps,
gamma=gamma,
n_frames=n_frames,
real_ratio=real_ratio,
generated_maxlen=generated_maxlen,
)
self._n_steps_per_epoch = n_steps_per_epoch
def _reset(self) -> None:
pass
def _next(self) -> Transition:
index = cast(int, np.random.randint(len(self._transitions)))
transition = self._transitions[index]
return transition
def _has_finished(self) -> bool:
return self._count >= self._n_steps_per_epoch
def __len__(self) -> int:
return self._n_steps_per_epoch
|
7,330 | 5c4a48de94cf5bfe67e6a74c33a317fa1da8d2fa | from django.db import models
from django.urls import reverse
from django.conf import settings
from embed_video.fields import EmbedVideoField
from django.contrib.auth.models import AbstractBaseUser
User = settings.AUTH_USER_MODEL
# Create your models here.
"""class User(models.Model):
username = models.CharField(max_length=20)
created_at = models.DateTimeField()
is_enabled = models.BooleanField(default=True)
email = models.EmailField()
password = models.CharField(max_length=20)
def __str__(self):
return self.username"""
class Post(models.Model):
is_enabled = models.BooleanField(default=True)
parent = models.ForeignKey(
'self', on_delete=models.PROTECT, blank=True, null=True, default=''
)
text = models.TextField()
created_at = models.DateTimeField(auto_now_add=True, blank=True)
author = models.ForeignKey(
User,
on_delete=models.PROTECT
)
class Meta:
ordering = ['parent_id', 'created_at']
def display_text(self):
short = " ".join(self.text.split()[0:5])
if len(short) > 20:
short = self.text[:20] + "..."
return short
display_text.short_description = 'Text'
def __str__(self):
space = " "
return f'{space.join(self.text.split()[0:5])} ({str(self.created_at)})'
def get_absolute_url(self):
return reverse('post-detail', args=[str(self.id)])
class Item(models.Model):
video = EmbedVideoField()
|
7,331 | 86345702bcd423bc31e29b1d28aa9c438629297d | # -*- coding: utf-8 -*-
"""
Created on Wed Aug 18 16:11:44 2021
@author: ignacio
"""
import matplotlib.pyplot as plt
from numpy.linalg import inv as invertir
from time import perf_counter
import numpy as np
def matriz_laplaciana(N, t=np.single): # funcion obtenida de clase
e=np.eye(N)-np.eye(N,N,1)
return t(e+e.T)
Ns = [2, 5, 10,12, 15, 20, 30, 40, 45, 50, 55, 60, 75, 100, 125, 160, 200, 250, 350, 500, 600, 800, 1000, 2000, 5000, 10000]
corridas = 10
for corrida in range(corridas):
tiempo = []
memoria = []
name = (f"single{corrida}.txt")
fid = open(name,"w")
for i in Ns:
print(f"i = {i}")
A = matriz_laplaciana(i)
t1 = perf_counter()
invertir(A)
t2 = perf_counter()
dt = t2 - t1
size = 3 * (i**2) * 32
tiempo.append(dt)
memoria.append(size)
fid.write(f"{i} {dt} {size}\n")
print(f"Tiempo transcurrido = {dt} s")
print(f"Mmoria usada = {size} bytes")
fid.flush()
fid.close()
dim = []
tim = []
mem = []
for n in range(10):
dimension = []
time = []
memory = []
with open(f"single{n}.txt", "r") as f:
lineas = [linea.split() for linea in f]
for i in lineas:
dimension.append(int(i[0]))
time.append(float(i[1]))
memory.append(int(i[2]))
dim.append(dimension)
tim.append(time)
mem.append(memory)
#Grafico superior
plt.subplot(2, 1, 1)
plt.plot(dim[0],tim[0],"-o")
plt.plot(dim[0],tim[1],"-o")
plt.plot(dim[0],tim[2],"-o")
plt.plot(dim[0],tim[3],"-o")
plt.plot(dim[0],tim[4],"-o")
plt.plot(dim[0],tim[5],"-o")
plt.plot(dim[0],tim[6],"-o")
plt.plot(dim[0],tim[7],"-o")
plt.plot(dim[0],tim[8],"-o")
plt.plot(dim[0],tim[9],"-o")
plt.yscale('log')
plt.xscale('log')
xticks = [10, 20, 50, 100, 200, 500, 1000, 2000, 5000, 10000, 20000]
xtext = ["", "", "", "", "", "", "", "", "", "", ""]
yticks = [0.1/1000, 1/1000, 10/1000, 0.1, 1, 10, 60, 600]
ytext = ["0.1 ms", "1 ms", "10 ms", "0.1 s", "1 s", "10 s", "1 min", "10 min"]
plt.yticks(yticks, ytext)
plt.xticks(xticks, xtext)
plt.title("Rendimiento caso1_single")
plt.ylabel("Tiempo transcurrido (s)")
plt.grid(True)
#Grafico inferior
plt.subplot(2, 1, 2)
plt.plot(Ns,memoria,'-ob')
plt.yscale('log')
plt.xscale('log')
xticks = [10, 20, 50, 100, 200, 500, 1000, 2000, 5000, 10000, 20000]
xtext = [10, 20, 50, 100, 200, 500, 1000, 2000, 5000, 10000, 20000]
yticks = [1000,10000, 100000, 1000000, 10000000, 100000000, 1000000000, 100000000000]
ytext = ["1 KB ", "10 KB", "100 KB", "1 MB", "10 MB", "100 MB", "1 GB", "10 GB"]
plt.axhline(y=4000000000, linestyle="--",color="black") # RAM 4 GB
plt.yticks(yticks, ytext)
plt.xticks(xticks, xtext, rotation=45)
plt.xlabel("Tamaño matriz N")
plt.ylabel("Uso memoria (bytes)")
plt.grid(True)
plt.savefig("Rendimiento caso1_single.png") |
7,332 | 84a63f60a45f1f8fc1efec8f30345a43c3c30c63 | def html_print(text, title=''):
from IPython.core.display import display, HTML
# create title for the content
display(HTML("<h4>" + str(title) + "</h4>"))
# create content
html = display(HTML("<font size=2 face=Verdana>" + text + "</font>"))
return html
|
7,333 | aafadcbf946db8ed85e3df48f5411967ec35c318 | #!/usr/bin/env python
# ----------------------------------------------------------
# RJGlass Main Program version 0.2 8/1/07
# ----------------------------------------------------------
# Copyright 2007 Michael LaBrie
#
# This file is part of RJGlass.
#
# RJGlass is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3 of the License, or
# (at your option) any later version.
# RJGlass is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
# ---------------------------------------------------------------
import sys, os, time
#Load the modules needed for RJGlass.
from OpenGL.GL import *
from OpenGL.GLUT import *
from OpenGL.GLU import *
#pygame needed for sound in server_only (so load either way)
import pygame
from pygame.locals import *
from pygame import image
from guage import * #All add on guage functions colors etc.
#This is code to import config file (config.py)
try:
import config
except ImportError:
# We're in a py2exe, so we'll append an element to the (one element)
# sys.path which points to Library.zip, to the directory that contains
# Library.zip, allowing us to import config.py
# Adds one level up from the Library.zip directory to the path, so import will go forward
sys.path.append(os.path.split(sys.path[0])[0])
import config
class screen_c(object):
#This controls what is in each screen.
def __init__(self, x, guage_list=[]):
self.guage_list = [] #list of guages to cycle through.
self.guage_index = 0
self.x = x
self.y = 0
self.width = 512
self.heigth = 768
self.add_guage_list(guage_list)
def add_guage_list(self,glist):
for g in glist:
self.append_guage(guage_dict[g])
def append_guage(self,guage):
self.guage_list.append(guage)
def cycle(self):
self.guage_index +=1
if self.guage_index >= len(self.guage_list):
self.guage_index =0
def cycle_reverse(self):
self.guage_index -=1
if self.guage_index <0:
self.guage_index = len(self.guage_list) -1
def active_guage(self):
return self.guage_list[self.guage_index]
#this is a static function not specificaly for the screen.
#the eventhandlers have references to the screens so it is easier to
#get the guage references by name through this object.
def gauge_by_name(self,name):
return guage_dict[name]
def draw(self, aircraft):
self.guage_active = self.guage_list[self.guage_index]
self.guage_active.draw(aircraft, self.x, self.y)
def InitPyGame():
glutInit(())
pygame.init()
if config.full_screen:
s = pygame.display.set_mode((1024,768), DOUBLEBUF|OPENGL|FULLSCREEN)
else:
s = pygame.display.set_mode((1024,768), DOUBLEBUF|OPENGL)
return s
def InitView(smooth, width, heigth):
global x_s, y_s, scissor
glClear(GL_COLOR_BUFFER_BIT|GL_DEPTH_BUFFER_BIT)
glLoadIdentity()
glOrtho(0,width,0.0,heigth,-1.0,1.0)
x_s = width/1024.0
y_s = heigth/768.0
glScalef(x_s, y_s, 1.0)
scissor.x_s = x_s
scissor.y_s = y_s
if smooth:
#Enable Smoothing Antianalising
glEnable(GL_LINE_SMOOTH)
glEnable(GL_BLEND)
#glBlendFunc(GL_SRC_ALPHA, GL_ZERO)
glBlendFunc(GL_SRC_ALPHA, GL_ONE_MINUS_SRC_ALPHA)
glHint(GL_LINE_SMOOTH_HINT, GL_DONT_CARE)
#glDisable(GL_DEPTH_TEST)
#Clear Screen
#glClear(GL_COLOR_BUFFER_BIT|GL_DEPTH_BUFFER_BIT)
def DisplaySplash(filename, delay, window_x, window_y):
#Display needs to be initialized first.
i = image.load(filename)
splash_image = bitmap_image(i)
#Determine the x and y coords to put in center of screen.
splash_x = (window_x / 2) - (splash_image.w/2)
splash_y = (window_y /2) - (splash_image.h/2)
glRasterPos3f(splash_x,splash_y,0)
glDrawPixels(splash_image.w, splash_image.h, GL_RGBA, GL_UNSIGNED_BYTE, splash_image.tostring)
pygame.display.flip()
time.sleep(delay)
def DrawWindow(left_screen, right_screen):
def divider(): #Dividing vertical white line between instruments
glColor(white)
glLineWidth(2.0)
glBegin(GL_LINES)
glVertex2f(512.0, 0.0)
glVertex2f(512.0, 768.0)
glEnd()
def draw_nodata(x,y): #Draw no data text on screen.
glColor(red)
glLineWidth(5.0)
glPushMatrix()
glTranslatef(x,y,0)
glScalef(0.4,0.4,1.0)
glText("NO SIM DATA", 100)
glPopMatrix()
global count
divider()
#PFD.draw(aircraft_data,250,445)
left_screen.draw(aircraft_data)
#ND.draw(aircraft_data,512+256, 400)
#FMS.draw(aircraft_data,512+256, 0)
right_screen.draw(aircraft_data)
glDisable(GL_SCISSOR_TEST) #Disable any scissoring.
draw_FPS(20,740, aircraft_data.frame_time)
#If Nodata is coming from Flight Sim, show on screen
if aircraft_data.nodata:
draw_nodata(50,500)
count = count +1 #Used for FPS calc
def MainLoop(mode, server_only):
#global window
global starttime
global count
global mode_func, left_screen, right_screen, eventhandler
# Start Event Processing Engine
starttime = time.time() # Used for FPS (Frame Per Second) Calculation
if (server_only):
#Set up correct function for selected mode
mode_func = aircraft_data.get_mode_func(mode)
else:
left_screen = screen_c(256,config.left_screen)
right_screen = screen_c(512+256,config.right_screen)
# left_screen.add_guage_list(config.left_screen)
# right_screen.add_guage_list(config.right_screen)
#Set up correct function for selected mode
mode_func = aircraft_data.get_mode_func(mode, left_screen, right_screen)
#Setup Keyboard
#keys.setup_lists(aircraft_data)
#Inititalize View
#left_screen = screen_c(256, [PFD, ND, FMS])
eventhandler = event_handler.event_handler_c(aircraft_data,FMS, right_screen, left_screen)
#Load textures, and guages that use them
FMS.load_texture()
EICAS1.load_texture()
EICAS2.load_texture()
RADIO.load_texture()
if server_only:
server_loop()
else:
graphic_loop()
def graphic_loop():
#This is the loop for the non server mode. Gauges drawn.
while not (aircraft_data.quit_flag):
glClear(GL_COLOR_BUFFER_BIT|GL_DEPTH_BUFFER_BIT) #Clear Screen
#Update globaltime
aircraft_data.globaltime = time.time()
globaltime.update(time.time())
DrawWindow(left_screen, right_screen)
pygame.display.flip() #Update screen
mode_func() #Run aircraft mode function, to do all teh calaculations etc.
# Check for keypresses
eventhandler.check_events(pygame.event.get(), globaltime.value)
def server_loop():
#This is the loop for the server only mode. No Guages Drawn
while not (aircraft_data.quit_flag):
#Update globaltime
aircraft_data.globaltime = time.time()
globaltime.update(time.time())
mode_func() #Run aircraft mode function, to do all teh calaculations etc.
time.sleep(0.01) #Throw in some time delay, since no guages are being drawn.
# Check for keypresses
#eventhandler.check_events(pygame.event.get(), globaltime.value)
def Init_Graphics(x,y):
InitPyGame()
InitView(True, x,y)
def Initialize(server_only):
#if server_only True then server will just be run, No Graphics
#Initialize count for FPS calc
global count
count = 0
if (not server_only):
Init_Graphics(config.window_x, config.window_y)
#Draw Splash Screen
if config.splash:
DisplaySplash(config.splash_filename, config.splash_delay, config.window_x, config.window_y)
def ShutDown(mode, server_only):
#Close LogFile
datafile.close()
#Close pygame mixer
pygame.mixer.quit()
#Print average Frames per second on shutdown
print "FPS ", count / (time.time() - starttime)
#Try to kill the thread if it exists. Closes it down on exit
aircraft_data.AP.quit() #only here to close debugging files if present.
if ((mode != config.TEST) & (mode != config.CLIENT)): #If simconnected connected, kill the thread.
aircraft_data.kill_SimConnect()
def CheckArg(arg, mode, server_only, addr):
if 'server' in arg:
server_only = True
elif 'guage' in arg:
server_only = False
if 'client' in arg:
mode = config.CLIENT
elif 'test' in arg:
mode = config.TEST
for a in arg:
if 'addr' in a:
addr = a.split('=')[1]
return mode, server_only, addr
#===========================================================================
#Main program starts here
#===========================================================================
#Check arguments first, and get mode and server_only flags
mode, server_only, addr = CheckArg(sys.argv, config.mode, config.server_only, config.addr)
#config.addr = addr
#print addr
Initialize(server_only)
#Import guage files.
import aircraft #Does all of the aircraft_data
import event_handler #Handles all keyboard commands
import variable
if (not server_only):
import PFD_mod
import ND_mod
import EICAS1_mod
import EICAS2_mod
import FMS_guage
import radio_mod
#Create Guages
aircraft_data = aircraft.data()
variables = variable.variable_c(aircraft_data)
if (not server_only):
PFD = PFD_mod.PFD_Guage()
ND = ND_mod.ND_Guage()
FMS = FMS_guage.FMS_guage_c()
EICAS1 = EICAS1_mod.EICAS1_guage()
EICAS2 = EICAS2_mod.EICAS2_guage()
ND.initialize(aircraft_data)
RADIO = radio_mod.radio_guage()
guage_dict= { "RADIO":RADIO,"PFD":PFD,"ND":ND,"FMS":FMS,
"EICAS1":EICAS1,"EICAS2":EICAS2 }
print "Main Loop"
#Run main, and get window size and operation mode from config file. config.py
MainLoop(mode, server_only)
#===================
# Shuting Down
#===================
ShutDown(mode, server_only)
|
7,334 | 4843239a41fe1ecff6c8c3a97aceef76a3785647 | import operator
def group_by_owners(files):
print(files, type(files))
for k, v in files.items():
# for v in k:
print(k, v)
# if k[v] == k[v]:
# print("same", v)
for f in files:
print(f[0])
for g in v:
print(g)
_files = sorted(files.items(), key=operator.itemgetter(1), reverse=False)
print("Sorted: ", _files, type(_files))
# files = files.items()
# print(files, type(files))
# return None
files = {
'Input.txt': 'Randy',
'Code.py': 'Stan',
'Output.txt': 'Randy'
}
print(group_by_owners(files))
|
7,335 | 5a13c7e3be8a0b5f3baf7106a938fc97f078c5bc | '''
Created on May 17, 2016
@author: Shauryadeep Chaudhuri
'''
import json
import tornado
from engine import Constants as c
from engine.ResultGenerator import ResultGenerator
from ..ServerLogger import ServerLogger
class GetFromURL(tornado.web.RequestHandler):
'''
This class fetches the data requested like index,schema,entry,query from the url and responds with the result
'''
def initialize(self):
self.logger = ServerLogger().getLogger()
def get(self, index=None, schema=None, entry=None, query=None):
query = dict()
resultGenerator = ResultGenerator()
query[c.OPERATION] = c.GET
if index:
query[c.INDEX] = index
if schema:
query[c.SCHEMA] = schema
if entry:
query[c.ENTRY] = entry
self.logger.debug("Internal Query Generated"+str(query))
try:
result = str(resultGenerator.processQuery(json.dumps(query)))
self.logger.info("Result fetched:" + result)
self.write(result)
except Exception as e:
self.logger.error('Error', exc_info=True)
self.write("Error: " + str(e))
|
7,336 | eb1fbe2de3c8548175eb3c8720353e466e3b68c7 | import rdflib
import csv
from time import sleep
gtypes = {}
dtypes = {}
atypes = {}
g = rdflib.Graph()
g.parse("http://geographicknowledge.de/vocab/CoreConceptData.rdf#")
g.parse("./ontology.ttl", format="ttl")
sleep(.5)
results = g.query("""
prefix skos: <http://www.w3.org/2004/02/skos/core#>
prefix ccd: <http://geographicknowledge.de/vocab/CoreConceptData.rdf#>
prefix dcat: <https://www.w3.org/TR/vocab-dcat#>
prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#>
select ?dataset ?type
where {
?dataset a dcat:Dataset , ?type .
filter (
?type in ( ccd:PointDataSet, ccd:RegionDataSet, ccd:VectorTessellation, ccd:LineDataSet )
)
}
""")
for result in results:
uri, geometry_type = result
gtypes[str(uri)] = str(geometry_type).split('#')[1]
results = g.query("""
prefix skos: <http://www.w3.org/2004/02/skos/core#>
prefix ccd: <http://geographicknowledge.de/vocab/CoreConceptData.rdf#>
prefix dcat: <https://www.w3.org/TR/vocab-dcat#>
prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#>
select ?dataset ?type
where {
?dataset a dcat:Dataset , ?type .
?type rdfs:subClassOf+ ccd:CoreConceptDataSet .
}
""")
for result in results:
uri, dtype = result
dtypes[str(uri)] = str(dtype).split('#')[1]
results = g.query("""
prefix skos: <http://www.w3.org/2004/02/skos/core#>
prefix ccd: <http://geographicknowledge.de/vocab/CoreConceptData.rdf#>
prefix ada: <http://geographicknowledge.de/vocab/AnalysisData.rdf>
prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#>
select ?dataset ?label ?type
where {
?attribute ada:ofDataSet ?dataset ;
skos:exactMatch ?concept ;
rdfs:label ?label .
optional {
?concept a ?type .
?type rdfs:subClassOf+ ccd:Attribute .
}
}
group by ?dataset ?label ?type
""")
for result in results:
dataset, label, atype = result
key = (str(dataset), str(label))
if atype is None and key not in atypes:
atypes[key] = ""
elif atype is not None:
atypes[key] = str(atype).split('#')[1]
test_gtypes = {}
test_dtypes = {}
test_atypes = {}
with open("./datasets/annotations_datasets.csv", 'r') as fin:
reader = csv.reader(fin)
next(reader)
for row in reader:
test_gtypes[row[0]] = row[1]
test_dtypes[row[0]] = row[2]
with open("./datasets/annotations_attributes.csv", 'r') as fin:
reader = csv.reader(fin)
next(reader)
for row in reader:
test_atypes[(row[0],row[1])] = row[2]
tp = 0
total = 0
fn = len(test_gtypes)
for k, v in gtypes.items():
if k not in test_gtypes: # skip some extra test datasets
continue
total += 1
if test_gtypes[k] == v:
tp += 1
fn -= 1
p = tp / total
r = tp / (tp + fn)
f = 2 * ((p * r) / (p + r))
print("Geometry type scores:")
print(f"P: {p} , R: {r} , F: {f}")
tp = 0
total = 0
fn = len(test_dtypes)
for k, v in dtypes.items():
if k not in test_dtypes:
continue
total += 1
if test_dtypes[k] == v:
tp += 1
fn -= 1
p = tp / total
r = tp / (tp + fn)
f = 2 * ((p * r) / (p + r))
print("Dataset type scores:")
print(f"P: {p} , R: {r} , F: {f}")
filter_nontypes = True
if filter_nontypes:
test_atypes = {k: v for k, v in test_atypes.items() if v != ""}
atypes = {k: v for k, v in atypes.items() if v != ""}
tp = 0
total = 0
fn = len(list(filter(lambda x: x != "", test_atypes.values())))
for k, v in atypes.items():
if k not in test_atypes:
continue
if v != "":
total += 1
if test_atypes[k] == v:
tp += 1
fn -= 1
elif v == "BooleanA" and test_atypes[k] == "NominalA": # boolean is "more" correct
tp += 1
fn -= 1
else:
print(k, v, test_atypes[k])
p = tp / total
r = tp / (tp + fn)
f = 2 * ((p * r) / (p + r))
print("Attribute type scores:")
print(f"P: {p} , R: {r} , F: {f}")
|
7,337 | 47d72379b894826dad335f098649702ade195f78 | n=int(input("Digite um número"))
m=n-1
o=n+1
print("Seu número é {} seu antecessor é {} e seu sucessor é {}".format(n,m,o)) |
7,338 | a72d878d246a459038640bf9c1deff562994b345 | def solution(skill, skill_trees):
answer = 0
for tree in skill_trees:
able = True
for i in range(len(skill) - 1, 0, -1):
index = tree.find(skill[i])
if index != -1 and i > 0:
if tree[:index].find(skill[i - 1]) == -1:
able = False
break
if able:
answer += 1
return answer
if __name__ == "__main__":
skill = "CBD"
skill_trees = ["BACDE", "CBADF", "AECB", "BDA"]
solution(skill=skill, skill_trees=skill_trees) |
7,339 | 42d26ef51bb4dafc8a0201a828652e166a3905e4 | def unique(lisst):
setlisst = set(lisst)
return len(setlisst)
print(unique({4,5,1,1,3})) |
7,340 | 8e443d136a4e9fcdd18a106192f9c097928b8c99 | from typing import List, Any, Callable, Iterable, TypeVar, Tuple
T = TypeVar('T')
def partition(pred: Callable[[T], bool], it: Iterable[T]) \
-> Tuple[List[T], List[T]]: ...
|
7,341 | 62dab85b7ab5fdae8117827b2f56bccf99615cb7 | a=[[*map(int,input().split())]for _ in range(int(input()))]
a.sort()
s=0
l0,h0=a[0]
for l,h in a:
if h0<h:s+=(l-l0)*h0;l0,h0=l,h
l1,h1=a[-1]
for l,h in a[::-1]:
if h>h1:s+=(l1-l)*h1;l1,h1=l,h
s+=(l1-l0+1)*h1
print(s) |
7,342 | 8bb86cae3387a0d4ce5987f3e3c458c8298174e0 | from .settings import *
# Heroku Configurations
# Parse database configuration from $DATABASE_URL
import dj_database_url
DATABASES = {'default': dj_database_url.config()}
# Honor the 'X-Forwarded-Proto' header for request.is_secure()
SECURE_PROXY_SSL_HEADER = ('HTTP_X_FORWARDED_PROTO', 'https')
# loading local_settings.py
try:
from .local_settings import *
except Exception as e:
pass
# ALLAUTH configuration
# Specific the login method to use
ACCOUNT_USERNAME_REQUIRED = False
# ACCOUNT_AUTHENTICATION_METHOD = "username", "email", "username_email"
# Determines the e-mail verification method during signup – choose one of “mandatory”, “optional”, or “none”.
# When set to “mandatory” the user is blocked from logging in until the email address is verified.
# Choose “optional” or “none” to allow logins with an unverified e-mail address.
# In case of “optional”, the e-mail verification mail is still sent,
# whereas in case of “none” no e-mail verification mails are sent.
ACCOUNT_EMAIL_VERIFICATION = "none"
# Determines whether or not the user is automatically logged out by a mere GET request.
# See documentation for the LogoutView for details.
ACCOUNT_LOGOUT_ON_GET = False
# Request e-mail address from 3rd import party account provider?
# E.g. using OpenID AX, or the Facebook “email” permission.
SOCIALACCOUNT_QUERY_EMAIL = True
# Dictionary containing provider specific settings.
SOCIALACCOUNT_PROVIDERS = {
'facebook': {
# we use facebook js_sdk instead od oauth2
'METHOD': 'js_sdk',
'SCOPE': ['email', 'public_profile', 'user_friends'],
# using AUTH_PARAMS to pass along other parametees
# to the FB.login JS SDK call
'AUTH_PARAMS': {'auth_type': 'reauthenticate'},
# field are fetch from the import Graph API
'FIELDS': ['first_name', 'last_name', 'email', 'birthday'],
# JS SDK return a short-lived token suitable for client-side use.
'EXCHANGE_TOKEN': True,
# Chose the current active language of the request
'LOCALE_FUNC': 'path.to.callable',
'VERIFIED_EMAIL': False,
# Facebook Graph API version
'VERSION': 'v2.7'
},
'linkedin': {
'SCOPE': ['r_emailaddress'],
'PROFILE_FIELDS': [
'id',
'first-name',
'last-name',
'email-address',
'public-profile-url'
]
}
}
# login redirect url
LOGIN_REDIRECT_URL = "/blog/jobs"
# Default settings
BOOTSTRAP3 = {
# The URL to the jQuery JavaScript file
'jquery_url': '//code.jquery.com/jquery.min.js',
# The Bootstrap base URL
'base_url': '//maxcdn.bootstrapcdn.com/bootstrap/3.3.7/',
# The complete URL to the Bootstrap CSS file (None means derive it from base_url)
'css_url': None,
# The complete URL to the Bootstrap CSS file (None means no theme)
'theme_url': None,
# The complete URL to the Bootstrap JavaScript file (None means derive it from base_url)
'javascript_url': None,
# Put JavaScript in the HEAD section of the HTML document (only relevant if you use bootstrap3.html)
'javascript_in_head': False,
# Include jQuery with Bootstrap JavaScript (affects django-bootstrap3 template tags)
'include_jquery': False,
# Label class to use in horizontal forms
'horizontal_label_class': 'col-md-3',
# Field class to use in horizontal forms
'horizontal_field_class': 'col-md-9',
# Set HTML required attribute on required fields
'set_required': True,
# Set HTML disabled attribute on disabled fields
'set_disabled': False,
# Set placeholder attributes to label if no placeholder is provided
'set_placeholder': True,
# Class to indicate required (better to set this in your Django form)
'required_css_class': '',
# Class to indicate error (better to set this in your Django form)
'error_css_class': 'has-error',
# Class to indicate success, meaning the field has valid input (better to set this in your Django form)
'success_css_class': 'has-success',
# Renderers (only set these if you have studied the source and understand the inner workings)
'formset_renderers':{
'default': 'bootstrap3.renderers.FormsetRenderer',
},
'form_renderers': {
'default': 'bootstrap3.renderers.FormRenderer',
},
'field_renderers': {
'default': 'bootstrap3.renderers.FieldRenderer',
'inline': 'bootstrap3.renderers.InlineFieldRenderer',
},
}
# Axes Configurations
# Number of login attempts allowed before a record is created for the failed logins.
AXES_LOGIN_FAILURE_LIMIT = 3
# After the number os allowed login attempts are exceeded, should we lock this IP (and optinal user agend)?
AXES_LOCK_OUT_AT_FAILURE = True
# If True, lock out / log based on an IP address AND a user agent. This means requests from different import user
# agents but from the import same IP are treated differently.
AXES_USE_USER_AGENT = True
# Defines a period of inactivity after which old failed login attempts will be forgotten. You can set to a
# python timedelta object or an integer, if you set it to be integer it will represent a number of hours
AXES_COOLOFF_TIME = 50
# Specifies a logging mechanism for axes to use
AXES_LOCKOUT_TEMPLATE = 'axes.watch_login'
# Specifies a template to render when a user is locked out. Template receives cooloff_time and failure_limit as
# context variables
AXES_LOCKOUT_TEMPLATE = None
# Specifies a URL to redirect to on lockout. If both AXES_LOCKOUT_TEMPLATE and AXES_LOCKOUT_URL are set, the template
# will be used
AXES_LOCKOUT_URL = None
# If Truem you'll see slightly more logging for Axes
AXES_VERBOSE = True
# The name of the for field that contains your usernames
# AXES_USERNAME_FORM_FIELD = username
# If True prevents to login from IP import under particular user if attempts limit exceed, otherwise lock out based on
# IP. Default: False
AXES_LOCK_OUT_BY_COMBINATION_USER_AND_IP = False
# Crispy forms will use BOOTSTRAP3 TEMPLATE PACK
CRISPY_TEMPLATE_PACK = "bootstrap3"
# Signal Admins Configurations
ADMINS = (
("Petar Pilipovic", "petar@literatillc.com"),
)
# RESTframework Permission classes configuration
REST_FRAMEWORK = {
"DEFAULT_PERMISSION_CLASSES": [
"rest_framework.permissions.DjangoModelPermissionsOrAnonReadOnly"
]
}
|
7,343 | db231ea92319414dd10ca8dfbc14e5a70ed2fe44 |
from QnA_processor.question_analysis.google_question_classifier import GoogleQuestionClassifier
def classify_question(query):
try:
"""
Get answer-type from google autoML classifier
(by making POST requests with authorization key)
"""
question_classifier = GoogleQuestionClassifier()
answer_type = question_classifier.classify_by_api_call(query)
except KeyError :
"""
Get answer-type from google autoML classifier
(without authorization key by using google package)
"""
answer_type = question_classifier.classify_by_package(query)
except:
"""
Get answer-type from custom question classifier
"""
from QnA_processor.question_analysis.custom_question_classifier import CustomQuestionClassifier
question_classifier = CustomQuestionClassifier()
answer_type = question_classifier.classify_question(query)[0]
return answer_type
# print (classify_question("How many seasons are there in a year")) |
7,344 | f704742b9e023a1c3386fed293032fd8196b875e | # -*- coding: utf-8 -*-
# Author : Seungyeon Jo
# e-mail : syjo@seculayer.co.kr
# Powered by Seculayer © 2018 AI-Core Team
from mlps.core.data.cnvrtr.ConvertAbstract import ConvertAbstract
class Substr(ConvertAbstract):
def __init__(self, **kwargs):
super().__init__(**kwargs)
def apply(self, data):
result = ''
# check blank
if self._isBlank(data) :
return [result]
s_idx = 0
e_idx = 0
if len(self.arg_list) >= 2 :
s_idx = int(self.arg_list[0])
e_idx = int(self.arg_list[1])
else:
return [result]
if s_idx > len(data):
s_idx = 0
if e_idx > len(data):
e_idx = len(data)
if e_idx == 0:
result = data[s_idx:]
else:
result = data[s_idx:e_idx]
return [result]
if __name__ == "__main__":
_str = "Korea"
print(Substr(arg_list=[0, 1]).apply(_str))
|
7,345 | 12fd4e3bfb6821205a9b65b4d236b4158ec4ef1e | #!/usr/bin/env python
#
# Copyright 2017-2021 University Of Southern California
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import logging
from sqlalchemy.exc import *
from Pegasus.db.admin.admin_loader import *
from Pegasus.db.admin.versions.base_version import BaseVersion
from Pegasus.db.schema import *
DB_VERSION = 8
log = logging.getLogger(__name__)
class Version(BaseVersion):
def __init__(self, connection):
super().__init__(connection)
def update(self, force=False):
"""
:param force:
:return:
"""
log.info("Updating to version %s" % DB_VERSION)
try:
log.info("Updating master_workflowstate...")
self.db.execute("ALTER TABLE master_workflowstate ADD reason TEXT NULL")
except (OperationalError, ProgrammingError):
pass
except Exception as e:
self.db.rollback()
log.exception(e)
raise Exception(e)
self.db.commit()
def downgrade(self, force=False):
"Downgrade is not necessary as reason accepts NULL values"
|
7,346 | 357ee02060cbfa391920b3d45dfbe16e679a6c8d | def spam(divide_by):
return 42 / divide_by
try:
print(spam(2))
print(spam(12))
print(spam(0))
print(spam(1))
print(spam("dog"))
except Exception:
print("Error: Invalid argument.")
|
7,347 | 4473971552aa48236b19dec7e7c1ea1e622d5795 | from subprocess import check_output
import json
import sys
import time
import os
import numpy as np
from hutch_python.utils import safe_load
from ophyd import EpicsSignalRO
from ophyd import EpicsSignal
from bluesky import RunEngine
from bluesky.plans import scan
from bluesky.plans import list_scan
from bluesky.plan_stubs import configure
#from bluesky.plans import list_grid_scan
from ophyd import Component as Cpt
from ophyd import Device
from pcdsdevices.epics_motor import Newport, IMS, MMC100
from pcdsdevices.interface import BaseInterface
from pcdsdevices.device_types import Trigger
from pcdsdevices.areadetector import plugins
from cxi.db import daq, seq
from cxi.db import camviewer
from cxi.db import RE
from cxi.db import foil_x, foil_y
from cxi.db import cxi_pulsepicker as pp, seq
from cxi.db import bp, bpp, bps
from cxi.plans import serp_seq_scan
from time import sleep
class User():
def __init__(self):
self._sync_markers = {0.5:0, 1:1, 5:2, 10:3, 30:4, 60:5, 120:6, 360:7}
self.evr_pp = Trigger('CXI:R48:EVR:41:TRIG0',name='evr_pp')
self.pp_delay = EpicsSignal('CXI:R48:EVR:41:TRIG0:TDES', name='pp_delay')
with safe_load('sam_x'):
self.sam_x = IMS('CXI:SC2:MMS:06', name='sam_x')
with safe_load('sam_y'):
self.sam_y = IMS('CXI:SC2:MMS:05', name='sam_y')
with safe_load('sam_z'):
self.sam_z = IMS('CXI:SC2:MMS:08', name='sam_z')
#with safe_load('sam_pitch'):
# self.sam_pitch = MMC100('CXI:USR:MMC:01', name='sam_pitch')
#with safe_load('post_sam_x'):
# self.post_sam_x = IMS('CXI:USR:MMS:27', name='post_sam_x')
#with safe_load('post_sam_y'):
# self.post_sam_y = MMC100('CXI:USR:MMC:02', name='post_sam_y')
#with safe_load('post_sam_z'):
# self.post_sam_z = MMC100('CXI:USR:MMC:03', name='post_sam_z')
with safe_load('op_focus'):
self.wfs_focus = IMS('CXI:USR:MMS:26', name='wfs_focus')
with safe_load('op_x'):
self.wfs_x = Newport('CXI:USR:MMN:09', name='wfs_x')
with safe_load('op_y'):
self.wfs_v = IMS('CXI:USR:MMS:25', name='wfs_v')
def takeRun(self, nEvents, record=True):
daq.configure(events=120, record=record)
daq.begin(events=nEvents)
daq.wait()
daq.end_run()
def get_ascan(self, motor, start, end, nsteps, nEvents, record=True):
daq.configure(nEvents, record=record, controls=[motor])
return scan([daq], motor, start, end, nsteps)
def get_dscan(self, motor, start, end, nsteps, nEvents, record=True):
daq.configure(nEvents, record=record)
currPos = motor.wm()
return scan([daq], motor, currPos+start, currPos+end, nsteps)
def ascan(self, motor, start, end, nsteps, nEvents, record=True):
daq.configure(nEvents, record=record, controls=[motor])
RE(scan([daq], motor, start, end, nsteps))
def listscan(self, motor, posList, nEvents, record=True):
daq.configure(nEvents, record=record, controls=[motor])
RE(list_scan([daq], motor, posList))
def dscan(self, motor, start, end, nsteps, nEvents, record=True):
daq.configure(nEvents, record=record, controls=[motor])
currPos = motor.wm()
RE(scan([daq], motor, currPos+start, currPos+end, nsteps))
def setupSequencer(self, flymotor, distance, deltaT_shots, pp_shot_delay=2):
## Setup sequencer for requested rate
#sync_mark = int(self._sync_markers[self._rate])
#leave the sync marker: assume no dropping.
sync_mark = int(self._sync_markers[120])
seq.sync_marker.put(sync_mark)
#seq.play_mode.put(0) # Run sequence once
seq.play_mode.put(1) # Run sequence N Times
# Determine the different sequences needed
beamDelay = int(120*deltaT_shots)-pp_shot_delay
if (beamDelay+pp_shot_delay)<4:
print('PP cannot go faster than 40 Hz in flip-flip mode, quit!')
return
fly_seq = [[185, beamDelay, 0, 0],
[187, pp_shot_delay, 0, 0]]
#logging.debug("Sequence: {}".format(fly_seq))
#calculate how often to shoot in requested distance
flyspeed = flymotor.velocity.get()
flytime = distance/flyspeed
flyshots = int(flytime/deltaT_shots)
seq.rep_count.put(flyshots) # Run sequence N Times
seq.sequence.put_seq(fly_seq)
def setPP_flipflip(self, nshots=20, deltaShots=30):
## Setup sequencer for requested rate
#sync_mark = int(self._sync_markers[self._rate])
#leave the sync marker: assume no dropping.
sync_mark = int(self._sync_markers[120])
seq.sync_marker.put(sync_mark)
#seq.play_mode.put(0) # Run sequence once
seq.play_mode.put(1) # Run sequence N Times
seq.rep_count.put(nshots) # Run sequence N Times
# Determine the different sequences needed
beamDelay = int(delta_shots)-pp_shot_delay
if (beamDelay+pp_shot_delay)<4:
print('PP cannot go faster than 40 Hz in flip-flip mode, quit!')
return
ff_seq = [[185, beamDelay, 0, 0],
[187, pp_shot_delay, 0, 0]]
#logging.debug("Sequence: {}".format(fly_seq))
seq.sequence.put_seq(ff_seq)
def set_pp_flipflop(self):
pp.flipflop(wait=True)
def runflipflip(self, start, end, nsteps,nshots=20, deltaShots=30):
self.set_pp_flipflop()
#self.setPP_flipflip(nshots=20, deltaShots=6)
for i in nsteps:
self.evr_pp.ns_delay.set(start+delta*i)
seq.start()
time.sleep(5)
def run_evr_seq_scan(self, start, env, nsteps, record=None, use_l3t=None):
"""RE the plan."""
self.set_pp_flipflop()
RE(evr_seq_plan(daq, seq, self.evr_pp, start, env, nsteps,
record=record, use_l3t=use_l3t))
def evr_seq_plan(self, daq, seq, evr, start, end, nsteps,
record=None, use_l3t=None):
"""Configure daq and do the scan, trust other code to set up the sequencer."""
yield from configure(daq, events=None, duration=None, record=record,
use_l3t=use_l3t, controls=[evr])
yield from scan([daq, seq], evr, start, end, nsteps)
def run_serp_seq_scan(self, shiftStart, shiftStop, shiftSteps, flyStart, flyStop, deltaT_shots, record=False, pp_shot_delay=2):
daq.disconnect() #make sure we start from fresh point.
shiftMotor=foil_y
flyMotor=foil_x
self.setupSequencer(flyMotor, abs(flyStop-flyStart), deltaT_shots, pp_shot_delay=pp_shot_delay)
daq.configure(-1, record=record, controls=[foil_x, foil_y])
#daq.begin(-1)
if isinstance(shiftSteps, int):
RE(serp_seq_scan(shiftMotor, np.linspace(shiftStart, shiftStop, shiftSteps), flyMotor, [flyStart, flyStop], seq))
else:
RE(serp_seq_scan(shiftMotor, np.arange(shiftStart, shiftStop, shiftSteps), flyMotor, [flyStart, flyStop], seq))
def PPburst_sequence(self, nShots=None, nOffShots=2):
if nOffShots < 2:
raise ValueError('Minimum offshots is 2')
ff_seq = [[185, 0, 0, 0]]
ff_seq.append([179, 1 , 0, 0])
ff_seq.append([179, 1 , 0, 0])
if nShots is not None:
if isinstance(nShots , int):
ff_seq.append([185, nShots-2, 0, 0])
else:
ff_seq.append([185, int(nShots*120)-2, 0, 0])
ff_seq.append([179, 2, 0, 0])
if nShots is not None:
if isinstance(nShots , int):
for i in range(nOffShots-2):
ff_seq.append([179, 1, 0, 0])
else:
for i in range(int(nOffShots*120)-2):
ff_seq.append([179, 1, 0, 0])
return ff_seq
def prepare_seq_PPburst(self, nShots=None, nOffShots=None):
## Setup sequencer for requested rate
#sync_mark = int(self._sync_markers[self._rate])
#leave the sync marker: assume no dropping.
sync_mark = int(self._sync_markers[120])
seq.sync_marker.put(sync_mark)
seq.play_mode.put(0) # Run sequence once
#seq.play_mode.put(1) # Run sequence N Times
#seq.rep_count.put(nshots) # Run sequence N Times
ff_seq = self.PPburst_sequence(nShots=nShots, nOffShots=nOffShots)
seq.sequence.put_seq(ff_seq)
def PPburst_sequence_pattern(self, nShots=None, nOffShots=None, nTimes=1):
single_burst = self.PPburst_sequence(nShots=nShots, nOffShots=nOffShots)
ff_seq = []
for i in range(nTimes):
ff_seq += single_burst
return ff_seq
def prepare_seq_PPburst_pattern(self, nShots=None, nOffShots=None, nTimes=1):
## Setup sequencer for requested rate
#sync_mark = int(self._sync_markers[self._rate])
#leave the sync marker: assume no dropping.
sync_mark = int(self._sync_markers[120])
seq.sync_marker.put(sync_mark)
seq.play_mode.put(0) # Run sequence once
#seq.play_mode.put(1) # Run sequence N Times
#seq.rep_count.put(nshots) # Run sequence N Times
ff_seq = self.PPburst_sequence_pattern(nShots=nShots, nOffShots=nOffShots, nTimes=nTimes)
seq.sequence.put_seq(ff_seq)
def dumbSnake(self, xStart, xEnd, yDelta, nRoundTrips, sweepTime):
"""
simple rastering for running at 120Hz with shutter open/close before
and after motion stop.
Need some testing how to deal with intermittent motion errors.
"""
self.sam_x.umv(xStart)
daq.connect()
daq.begin()
sleep(2)
print('Reached horizontal start position')
# looping through n round trips
for i in range(nRoundTrips):
try:
print('starting round trip %d' % (i+1))
self.sam_x.mv(xEnd)
sleep(0.1)
pp.open()
sleep(sweepTime)
pp.close()
self.sam_x.wait()
self.sam_y.mvr(yDelta)
sleep(1.2)#orignal was 1
self.sam_x.mv(xStart)
sleep(0.1)
pp.open()
sleep(sweepTime)
pp.close()
self.sam_x.wait()
self.sam_y.mvr(yDelta)
print('ypos',x.sam_y.wm())
sleep(1.2)#original was 1
except:
print('round trip %d didn not end happily' % i)
daq.end_run()
daq.disconnect()
def dumbSnake_pp(self, xStart, xEnd, yDelta, nRoundTrips, sweepTime):
"""
simple rastering for running at 120Hz with shutter open/close before
and after motion stop.
Need some testing how to deal with intermittent motion errors.
"""
self.sam_x.umv(xStart)
daq.connect()
daq.begin()
sleep(2)
print('Reached horizontal start position')
# looping through n round trips
for i in range(nRoundTrips):
try:
print('starting round trip %d' % (i+1))
self.sam_x.mv(xEnd)
sleep(0.1)
seq.start()
#sleep(sweepTime)
#pp.close()
self.sam_x.wait()
self.sam_y.mvr(yDelta)
sleep(1.2)#orignal was 1
self.sam_x.mv(xStart)
sleep(0.1)
#pp.open()
#sleep(sweepTime)
#pp.close()
seq.start()
self.sam_x.wait()
self.sam_y.mvr(yDelta)
print('ypos',x.sam_y.wm())
sleep(1.2)#original was 1
except:
print('round trip %d didn not end happily' % i)
daq.end_run()
daq.disconnect()
def dumbSnake_v(self, yStart, yEnd, xDelta, nRoundTrips, sweepTime):
"""
simple rastering for running at 120Hz with shutter open/close before
and after motion stop.
Need some testing how to deal with intermittent motion errors.
"""
self.sam_y.umv(yStart)
daq.connect()
daq.begin()
sleep(2)
print('Reached horizontal start position')
# looping through n round trips
for i in range(nRoundTrips):
try:
print('starting round trip %d' % (i+1))
self.sam_y.mv(yEnd)
sleep(0.05)
pp.open()
sleep(sweepTime)
pp.close()
self.sam_y.wait()
self.sam_x.mvr(xDelta)
sleep(1.2)#orignal was 1
self.sam_y.mv(yStart)
sleep(0.05)
pp.open()
sleep(sweepTime)
pp.close()
self.sam_y.wait()
self.sam_x.mvr(xDelta)
sleep(1.2)#original was 1
except:
print('round trip %d didn not end happily' % i)
daq.end_run()
daq.disconnect()
def dumbSnake_burst_window(self,xStart,xEnd,yDelta, nRoundTrips, sweepTime,windowlist):#for burst mode
"""
simple rastering for running at 120Hz with shutter open/close before
and after motion stop.
Need some testing how to deal with intermittent motion errors.
"""
#windowList = np.zeros([numYwindow,numXwindow],dtype=object)
self.sam_x.umv(xStart)
daq.connect()
daq.begin()
sleep(2)
print('Reached horizontal start position')
# looping through n round trips
for j in (windowList):
self.sam_y.umv(windowList)
self.sam_y.wait()
print('Windos position %f'%(self.sam_w.wm()))
for i in range(nRoundTrips):
try:
print('starting round trip %d' % (i+1))
self.sam_x.mv(xEnd)
sleep(0.05)
seq.start()#start sequence Need to be set
#sleep(sweepTime)
#pp.close()
self.sam_x.wait()
self.sam_y.mvr(yDelta)
sleep(1)#wait for turning around
self.sam_x.mv(xStart)
sleep(0.05)
#pp.open()
seq.start()#start sequence
#sleep(sweepTime)
#pp.close()
self.sam_x.wait()
self.sam_y.mvr(yDelta)
sleep(1)
except:
print('round trip %d didn not end happily' % i)
daq.end_run()
daq.disconnect()
def dumbSnake_burst(self, xStart, xEnd, yDelta, nRoundTrips, sweepTime,windowList,startgrid):#for burst mode
"""
simple rastering for running at 120Hz with shutter open/close before
and after motion stop.
sleeptime is the pp close time between window
Need some testing how to deal with intermittent motion errors.
"""
self.sam_x.umv(xStart)
self.sam_y.umv(windowList[startgrid])
daq.connect()
daq.begin()
sleep(2)
print('Reached horizontal start position')
# looping through n round trips
for j in range(len(windowList)-startgrid):
self.sam_y.umv(windowList[startgrid+j])
self.sam_y.wait()
print('Windos position %f'%(self.sam_y.wm()))
for i in range(nRoundTrips):
try:
print('starting round trip %d' % (i+1))
self.sam_x.mv(xEnd)
sleep(0.1)
seq.start()#start sequence Need to be set
#sleep(sweepTime)
#pp.close()
self.sam_x.wait()
self.sam_y.mvr(yDelta)
print('yposition',self.sam_y.wm())
sleep(1.2)#wait for turning around
self.sam_x.mv(xStart)
sleep(0.1)
#pp.open()
seq.start()#start sequence
#sleep(sweepTime)
#pp.close()
self.sam_x.wait()
self.sam_y.mvr(yDelta)
print('yposition',self.sam_y.wm())
sleep(1.2)
except:
print('round trip %d didn not end happily' % i)
daq.end_run()
daq.disconnect()
#daq.end()
#def run_serp_seq_scan_expl(self, yStart, yStop, ySteps, flyStart, flyStop, deltaT_shots, record=False, pp_shot_delay=1):
# daq.disconnect() #make sure we start from fresh point.
# self.setupSequencer(foil_y, abs(flyStop-flyStart), deltaT_shots, pp_shot_delay=pp_shot_delay)
# daq.configure(-1, record=record, controls=[foil_x, foil_y])
#daq.begin(-1)
# if isinstance(ySteps, int):
# RE(serp_seq_scan(foil_x, np.linspace(yStart, yStop, ySteps), foil_y, [flyStart, flyStop], seq))
# else:
# RE(serp_seq_scan(foil_x, np.arange(yStart, yStop, ySteps), foil_y, [flyStart, flyStop], seq))
# #daq.end()
|
7,348 | e247ffb5b6e4319ff17d0b8ae9f67e10c282c4ff |
# 多角色认证装饰器
def auth(role):
from core import admin_view,student_view,teacher_view
def deco(func):
def wrapper(*args,**kwargs):
if role == 'admin':
if admin_view.admin_user == None:
admin_view.login()
else:
res = func(*args,**kwargs)
return res
if role == 'student':
if student_view.student_user == None:
student_view.login()
else:
res = func(*args,**kwargs)
return res
if role == 'teacher':
if teacher_view.teacher_user == None:
teacher_view.login()
else:
res = func(*args,**kwargs)
return res
return wrapper
return deco |
7,349 | 8c96c38a67c2eb97e30b325e4917ba4888731118 | import json
import boto3
import os
import datetime
regionName = os.environ['AWS_REGION']
BUCKET_PATH = os.environ['BUCKET_PATH']
SENSITIVIT = os.environ['SENSITIVIT']
s3_client = boto3.client('s3', region_name=regionName)
ddb_resource = boto3.resource('dynamodb', region_name=regionName)
def lambda_handler(event, context):
# body = json.loads(event['body'])
body = event
videoPath = str(body['videoPath'])
templatePath = str(body['templatePath'])
facePath = str(body['facePath'])
targetPeople = str(body['targetPeople'])
FACES_BUCKET = facePath.split('/')[2]
FACES_OBJECT = '/'.join(facePath.split('/')[3:])
s3_client.download_file(FACES_BUCKET, FACES_OBJECT, '/tmp/faces.json')
facesJson = open('/tmp/faces.json', 'r')
facesData = json.load(facesJson)
FRAME_RATE = int(facesData['VideoMetadata']['FrameRate'])
PEOPLE = targetPeople.split(',')
timeStamps = []
scenesTime = []
i = 0
while i < len(facesData['Persons']):
try:
for target in PEOPLE:
if facesData['Persons'][i]['FaceMatches'] == []:
pass
elif facesData['Persons'][i]['FaceMatches'][0]['Face']['ExternalImageId'] == target.strip():
timeStamps.append(facesData['Persons'][i]['Timestamp'])
except IndexError:
pass
i = i+1
timeCollection = [[timeStamps[0]]]
i = 1
j = 0
while i < len(timeStamps):
if timeStamps[i] - timeCollection[j][-1] <= 1000:
timeCollection[j].append(timeStamps[i])
i = i+1
else:
j = j+1
timeCollection.append([timeStamps[i]])
for collection in timeCollection:
if collection[-1] - collection[0] >= 1000:
if collection[0] % 1000 == 0:
start = datetime.datetime.utcfromtimestamp(collection[0]//1000).strftime("%H:%M:%S") + ':00'
elif int(collection[0] % 1000 / 1000 * FRAME_RATE) < 10:
start = datetime.datetime.utcfromtimestamp(collection[0] // 1000).strftime("%H:%M:%S") + ':0' + str(int(collection[0] % 1000 / 1000 * FRAME_RATE))
else:
start = datetime.datetime.utcfromtimestamp(collection[0]//1000).strftime("%H:%M:%S") + ':' + str(int(collection[0] % 1000 / 1000 * FRAME_RATE))
if collection[-1] % 1000 == 0:
end = datetime.datetime.utcfromtimestamp(collection[-1] // 1000).strftime("%H:%M:%S") + ':00'
elif int(collection[-1] % 1000 / 1000 * FRAME_RATE) < 10:
end = datetime.datetime.utcfromtimestamp(collection[-1] // 1000).strftime("%H:%M:%S") + ':0' + str(int(collection[-1] % 1000 / 1000 * FRAME_RATE))
else:
end = datetime.datetime.utcfromtimestamp(collection[-1] // 1000).strftime("%H:%M:%S") + ':' + str(int(collection[-1] % 1000 / 1000 * FRAME_RATE))
scenesTime.append((start,end))
else:
pass
JOB_BUCKET = templatePath.split('/')[2]
JOB_OBJECT = '/'.join(templatePath.split('/')[3:])
s3_client.download_file(JOB_BUCKET, JOB_OBJECT, '/tmp/job-template.json')
finalName = []
for people in PEOPLE:
finalName.append(people.strip())
OUTPUT_NAME = '-'+'-'.join(finalName)
with open('/tmp/job-template.json', 'r') as r:
template = json.load(r)
for scene in scenesTime:
template['Settings']['Inputs'][0]['InputClippings'].append({'StartTimecode': scene[0], 'EndTimecode': scene[-1]})
template['Settings']['Inputs'][0]['FileInput'] = videoPath
template['Settings']['OutputGroups'][0]['Outputs'][0]['NameModifier'] = OUTPUT_NAME
template['Settings']['OutputGroups'][0]['OutputGroupSettings']['FileGroupSettings']['Destination'] = BUCKET_PATH
with open('/tmp/job-all.json', 'w') as w:
json.dump(template, w, indent=2)
w.close()
r.close()
mediaconvert_client = boto3.client('mediaconvert', region_name=regionName)
response = mediaconvert_client.describe_endpoints(Mode='DEFAULT')
mediaURL = response['Endpoints'][0]['Url']
mediaconvert_client = boto3.client('mediaconvert',endpoint_url=mediaURL)
with open("/tmp/job-all.json", "r") as jsonfile:
job_object = json.load(jsonfile)
mediaconvert_client.create_job(**job_object)
output = {'videoPath': videoPath,
'templatePath': templatePath,
'facePath': facePath,
'targetPerson': targetPeople,
'Frame Rate': FRAME_RATE
}
return {
'statusCode': 200,
'body': json.dumps(output)
}
|
7,350 | f9cee552dde5ecf229fda559122b4b0e780c3b88 | class Solution:
def countLetters(self, S: str) -> int:
ans = 0
for _, g in itertools.groupby(S):
cnt = len(list(g))
ans += (1 + cnt) * cnt // 2
return ans
|
7,351 | e1751cc6f76f56e62cd02d61db65f1c27a4ff1b9 | #encoding=utf-8
import pytest
from frame_project.实战2.main_page import MainPage
class TestMian:
def test_mian(self):
MainPage().goto_marketpage().goto_search().search()
if __name__ == '__main__':
pytest.main(['test_case.py','-s','-v'])
|
7,352 | 1b091d139635e90fb53b3fecc09bb879514c7b38 | import os
import json
from google.appengine.ext import webapp
from generic import JsonRpcService
class ViewService(JsonRpcService):
def json_create(self):
return "Hello, World!"
|
7,353 | 3cf2ffbc8163c2a447016c93ff4dd13e410fff2b | # -*- coding: utf-8 -*-
class Task:
def __init__(self):
self.title = ''
self.subtasks = []
def set_title(self, title):
self.title = title
def set_subtasks(self, subtasks):
self.subtasks = subtasks
|
7,354 | 98dbc6c3bdc3efb4310a2dbb7b1cc1c89eb4582b | import urllib3
with open('python.jpg', 'rb') as f:
data = f.read()
http = urllib3.PoolManager()
r = http.request('POST', 'http://httpbin.org/post', body=data, headers={'Content-Type': 'image/jpeg'})
print(r.data.decode()) |
7,355 | a9b1cc9b928b8999450b6c95656b863c476b273b | import sys
from PyQt5 import QtWidgets
from PyQt5.QtWidgets import QMainWindow, QApplication
#---Import that will load the UI file---#
from PyQt5.uic import loadUi
import detechRs_rc #---THIS IMPORT WILL DISPLAY THE IMAGES STORED IN THE QRC FILE AND _rc.py FILE--#
#--CLASS CREATED THAT WILL LOAD THE UI FILE
class Login(QMainWindow):
def __init__(self):
super(Login, self).__init__()
# --- FROM THE IMPORT PYQT5.UIC IMPORT LOADUI---##
loadUi("login_UI.ui",self)
#--- a code once the login button clicked, will call the loginFunction ---#
self.loginButton.clicked.connect(self.loginFunction)
#-- Created a function called "loginFunction" --#
def loginFunction(self):
lgUserLine=self.lgUserLine.text() #-- Getting the textbox context lgUserline --#
lgPassLine=self.lgPassLine.text() #-- Getting the textbox context lgPassline --#
#-- Will display at the terminal what you wrote in the textbox(QLineEdit) --#
print("Success, ", lgUserLine, "and ", lgPassLine)
app=QApplication(sys.argv)
loginWindow=Login()
widget=QtWidgets.QStackedWidget()
widget.addWidget(loginWindow) #-- displays all design widgets of the UI Window --#
widget.setFixedWidth(1190) #-- setting the fixed window size in width --#
widget.setFixedHeight(782) #-- setting the fixed window size in height--#
widget.show()
app.exec_() #-- window execution --# |
7,356 | bb3c42c9f87a463b9f18601c9e3897b6d21351d5 | from django.db import models
from django.utils import timezone
from django.db.models.signals import post_save
from django.urls import reverse
# Create your models here.
class Purchase(models.Model):
invoice = models.SmallIntegerField(primary_key=True,blank=False)
ch_no = models.SmallIntegerField(blank=True,null=True)
vendor = models.CharField(max_length=128, blank=False)
date = models.DateTimeField(default=timezone.now, blank=False)
description = models.TextField(max_length=4096, blank=True, null=True)
def __str__(self):
return self.vendor
def get_absolute_url(self):
return reverse('entry:purchase_detail', kwargs={'pk': self.pk})
class PurchaseDetail(models.Model):
PRODUCT_CHOICES = (
('WOOD', 'Wood'),
('GLASS', 'Glass'),
('PLASTIC', 'Plastic'),
('LEATHER', 'Leather'),
('FABRIC','Fabric'),
('STEEL', 'Steel'),
)
purchase= models.ForeignKey(Purchase,on_delete=models.CASCADE)
product_name = models.CharField(max_length=30,
choices=PRODUCT_CHOICES,
default='WOOD')
quantity = models.PositiveSmallIntegerField(blank=False)
rate = models.IntegerField(blank=False)
total = models.IntegerField(blank=False)
remarks = models.CharField(max_length=250)
def _get_total(self):
return self.quantity * self.rate
labor_total = property(_get_total)
def __str__(self):
return (self.product_name)
|
7,357 | 3328c2ae0816c146398ecde92a056d1e77683696 | import tkinter as tk
from telnetConn import telnetConnection
fields = 'Host Address', 'UserName', 'Password', 'Message To', 'Text'
def fetch(entries):
input_list = []
for entry in entries:
field = entry[0]
text = entry[1].get()
input_list.append(text)
# print('%s: "%s"' % (field, text))
telnetConnection(input_list[0],input_list[1],input_list[2],input_list[3],input_list[4])
def makeform(root, fields):
entries = []
for field in fields:
row = tk.Frame(root)
lab = tk.Label(row, width=15, text=field, anchor='w')
ent = tk.Entry(row)
row.pack(side=tk.TOP, fill=tk.X, padx=5, pady=5)
lab.pack(side=tk.LEFT)
ent.pack(side=tk.RIGHT, expand=tk.YES, fill=tk.X)
entries.append((field, ent))
return entries
if __name__ == '__main__':
root = tk.Tk()
ents = makeform(root, fields)
root.bind('<Return>', (lambda event, e=ents: fetch(e)))
btnSend = tk.Button(root, text='Send',
command=(lambda e=ents: fetch(e)))
btnSend.pack(side=tk.LEFT, padx=5, pady=5)
btnQuit = tk.Button(root, text='Quit', command=root.quit)
btnQuit.pack(side=tk.LEFT, padx=5, pady=5)
root.mainloop() |
7,358 | ff8b6bc607dac889da05b9f7e9b3595151153614 | import requests
import json
from concurrent import futures
from tqdm import trange
def main():
ex=futures.ThreadPoolExecutor(max_workers=50)
for i in trange(1,152):
url="https://api.bilibili.com/pgc/season/index/result?season_version=-1&" \
"area=-1&is_finish=-1©right=-1&season_status=-1&season_month=-1&year=-1&style_id=-1&order=3&st=1&sort=0&" \
"page={}&" \
"season_type=1&pagesize=20&type=1".format(i)
ex.submit(index_page,url)
def index_page(url):
res=requests.get(url)
res.encoding=res.apparent_encoding
next_page(res.text)
def next_page(html):
data=json.loads(html)
for i in data['data']['list']:
img_url=i['cover']
img_name=i['title']
# print(img_name)
get_img(img_url,img_name)
def get_img(img_url,img_name):
img=requests.get(img_url)
with open('img/{}.jpg'.format(img_name),'w+b') as f:
f.write(img.content)
main() |
7,359 | 2305d0b7ec0d9e08e3f1c0cedaafa6ed60786e50 | #! /usr/bin/env python3
import common, os, shutil, sys
def main():
os.chdir(common.root)
shutil.rmtree('shared/target', ignore_errors = True)
shutil.rmtree('platform/build', ignore_errors = True)
shutil.rmtree('platform/target', ignore_errors = True)
shutil.rmtree('tests/target', ignore_errors = True)
shutil.rmtree('examples/lwjgl/target', ignore_errors = True)
shutil.rmtree('examples/kwinit/target', ignore_errors = True)
shutil.rmtree('examples/jwm/target', ignore_errors = True)
shutil.rmtree('examples/swt/target', ignore_errors = True)
return 0
if __name__ == '__main__':
sys.exit(main()) |
7,360 | cf5ab10ce743aa261867501e93f498022e5908fe | #!python3
import configparser
parser = configparser.ConfigParser()
parser.read("sim.conf")
print(parser.get("config", "option1"))
print(parser.get("config", "option2"))
print(parser.get("config", "option3"))
|
7,361 | e47d6b5d46f2dd84569a2341178b2ea5e074603a | import cv2
import numpy as np
import matplotlib
matplotlib.use('agg')
import matplotlib.pyplot as plt
from keras.preprocessing.image import ImageDataGenerator
from keras.models import Sequential
from keras.layers import SeparableConv2D, Conv2D, MaxPooling2D
from keras.layers import BatchNormalization, Activation, Dropout, Flatten, Dense
from keras import backend as K
# dimensions of images.
img_width, img_height = 64,64
train_data_dir = 'data/train'
validation_data_dir = 'data/test'
nb_train_samples = 25473
nb_validation_samples = 7000
epochs = 50
batch_size = 64
if K.image_data_format() == 'channels_first':
input_shape = (3, img_width, img_height)
else:
input_shape = (img_width, img_height, 3)
model = Sequential()
convout1 = Conv2D(32, kernel_size=6, strides=2, input_shape=input_shape)
model.add(convout1)
activ1 = Activation('relu')
model.add(activ1)
convout2 = Conv2D(64, kernel_size=5, strides=1)
model.add(convout2)
activ2 = Activation('relu')
model.add(activ2)
pool1 = MaxPooling2D(pool_size=(3, 3), strides=1)
model.add(pool1)
convout3 = Conv2D(128, kernel_size=4, strides=2)
model.add(convout3)
activ3 = Activation('relu')
model.add(activ3)
convout4 = Conv2D(128, kernel_size=3, strides=1)
model.add(convout4)
activ4 = Activation('relu')
model.add(activ4)
pool2 = MaxPooling2D(pool_size=2, strides=1)
model.add(pool2)
convout5 = Conv2D(256, kernel_size=3, strides=1)
model.add(convout5)
activ5 = Activation('relu')
model.add(activ5)
pool3 = MaxPooling2D(pool_size=2, strides=1)
model.add(pool3)
model.add(Flatten())
dense1 = Dense(256)
model.add(dense1)
activ6 = Activation('relu')
model.add(activ6)
batchn = BatchNormalization()
model.add(batchn)
dense2 = Dense(184)
model.add(dense2)
activ7 = Activation('softmax')
model.add(activ7)
model.compile(loss='categorical_crossentropy',
optimizer='rmsprop',
metrics=['accuracy'])
img = cv2.imread('test.jpg')
img = cv2.resize(img, (64, 64))
img = np.expand_dims(img, axis=0)
classes = model.predict(img)
def layer_to_visualize(layer):
inputs = [K.learning_phase()] + model.inputs
_convout1_f = K.function(inputs, [layer.output])
def convout1_f(X):
# The [0] is to disable the training phase flag
return _convout1_f([0] + [X])
convolutions = convout1_f(img)
convolutions = np.squeeze(convolutions)
print ('Shape of conv:', convolutions.shape)
n = convolutions.shape[0]
n = int(np.ceil(np.sqrt(n)))
# Visualization of each filter of the layer
fig = plt.figure(figsize=(12,8))
for i in range(len(convolutions)):
ax = fig.add_subplot(n,n,i+1)
ax.imshow(convolutions[i], cmap='gray')
# Specify the layer to want to visualize
layer_to_visualize(convout1)
layer_to_visualize(activ1)
layer_to_visualize(convout2)
layer_to_visualize(activ2)
layer_to_visualize(pool1)
layer_to_visualize(convout3)
layer_to_visualize(activ3)
layer_to_visualize(convout4)
layer_to_visualize(activ4)
layer_to_visualize(pool2)
layer_to_visualize(convout5)
layer_to_visualize(activ5)
layer_to_visualize(pool3)
|
7,362 | bcc2977f36ecc775f44ae4251ce230af9abf63ba | '''
This module demonstrates how to use some functionality of python built-in csv module
'''
import csv
def csv_usage():
'''
This function demonstrates how to use csv module to read and write csv files
'''
with open('example.csv', 'r', newline='') as csvfile:
reader_c = csv.reader(csvfile, delimiter=';')
for row in reader_c:
print(', '.join(row))
with open('new-2.csv', 'w', newline='') as csvfile:
writer_c = csv.writer(csvfile, delimiter=',')
writer_c.writerow(['Name', 'Age', 'City'])
writer_c.writerow(['Joe', '25', 'Miami'])
writer_c.writerow(['Nick', '21', 'Mexico'])
if __name__ == '__main__':
csv_usage()
|
7,363 | 5066c2a5219cf1b233b4985efc7a4eb494b784ca | def gen_metadata(fn):
metadata = {}
lines = open(fn,'r').readlines()
for line in lines:
line = line.rstrip()
if len(line) == 0:
continue
elif line.startswith('#'):
continue
elif line.startswith('%'):
continue
else:
# Special case RingThresh
firstWord = line.split()[0]
if line.startswith('RingThresh'):
if 'RingThresh' not in metadata.keys():
metadata.update({'RingThresh':{}})
strippedline = line.split(firstWord)[1].strip()
secondword = strippedline.split()[0]
metadata['RingThresh'].update({secondword:strippedline.split(secondword)[1].split('#')[0].strip()})
else:
metadata.update({firstWord : line.split(firstWord)[1].split('#')[0].strip()})
return metadata
def SetupPayloads(inp):
flow_input = {
"input": {
"inject_source_endpoint_id": inp['sourceEP'],
"funcx_endpoint_non_compute": inp['sourceNCEP'],
"proc_endpoint_non_compute": inp['procNCEP'],
"inject_source_path": inp['sourcePath'],
"inject_destination_endpoint_id": inp['remoteDataEP'],
"extract_source_endpoint_id": inp['remoteDataEP'],
"funcx_endpoint_compute": inp['funcx_endpoint_compute'],
"inject_destination_path": inp['executePath'],
"extract_source_path": inp['executeResultPath'],
"extract_destination_endpoint_id": inp['destEP'],
"extract_destination_path": inp['resultPath'],
"paramFileName": inp['pfName'],
"startLayerNr": inp['startLayerNr'],
"endLayerNr": inp['endLayerNr'],
"nFrames": inp['nFrames'],
"numProcs": inp['numProcs'],
"numBlocks": inp['numBlocks'],
"timePath": inp['timePath'],
"StartFileNrFirstLayer": inp['startNrFirstLayer'],
"NrFilesPerSweep": inp['nrFilesPerSweep'],
"FileStem": inp['fileStem'],
"SeedFolder": inp['seedFolder'],
"RawFolder": inp['rawFolder'],
"darkFN": inp['darkFN'],
"StartNr": inp['startNr'],
"EndNr": inp['endNr'],
'extract_recursive': False,
'inject_recursive': True,}
}
flow_input['input'].update({
'multipletasks':[{
'startLayerNr':inp['startLayerNr'],
'endLayerNr':inp['endLayerNr'],
'numProcs':inp['numProcs'],
'nFrames':inp['nFrames'],
'numBlocks':inp['numBlocks'],
'blockNr':idx,
'timePath':inp['timePath'],
'FileStem':inp['fileStem'],
'SeedFolder':inp['seedFolder'],
'RawFolder':inp['rawFolder'],
'paramFileName':inp['pfName'],
}
for idx in range(inp['numBlocks'])
]
})
flow_input['input'].update({
'pilot':{
'dataset':f'{inp["sourcePath"]}/{inp["fileStem"]}_Layer_{str(inp["startLayerNr"]).zfill(4)}_Analysis_Time_{inp["timePath"]}/{inp["fileStem"]}_Layer_{str(inp["startLayerNr"]).zfill(4)}_Analysis_Time_{inp["timePath"]}/',
'index':inp['portal_id'],
'project':'hedm',
'source_globus_endpoint':inp['sourceEP'],
}
})
flow_input['input']['pilot'].update({
'metadata':gen_metadata(inp['pfName']),
})
flow_input['input']['pilot']['metadata'].update({
'exp_id':f'{inp["experimentName"]}_{inp["fileStem"]}_{inp["timePath"]}',
})
flow_input['input']['pilot']['metadata'].update({
'time_path':inp["timePath"],
})
flow_input['input']['pilot']['metadata'].update({
'startNr':inp["startNr"],
'endNr':inp["endNr"],
})
return flow_input
|
7,364 | 0d8a26ef4077b40e8255d5bb2ce9217b51118780 | #!/usr/bin/python3
# encoding: utf-8
"""
@author: ShuoChang
@license: (C) MIT.
@contact: changshuo@bupt.edu.cn
@software: CRNN_STN_SEQ
@file: decoder_base.py
@time: 2019/7/22 17:21
@blog: https://www.zhihu.com/people/chang-shuo-59/activities
"""
from abc import ABCMeta
from abc import abstractmethod
class DecoderBase(object):
"""
Base model for decoder
"""
__metaclass__ = ABCMeta
def __init__(self):
self._predictor = 'decoder'
self._label = None
pass
@abstractmethod
def set_label(self, label):
self._label = label
@abstractmethod
def predict(self, input_data):
pass
@abstractmethod
def loss(self, input_data):
pass
@abstractmethod
def sequence_dist(self, input_data):
pass
|
7,365 | c2dba981b0d628aebdf8cebfb890aad74a629b08 | from enum import Enum
from app.utilities.data import Prefab
class Tags(Enum):
FLOW_CONTROL = 'Flow Control'
MUSIC_SOUND = 'Music/Sound'
PORTRAIT = 'Portrait'
BG_FG = 'Background/Foreground'
DIALOGUE_TEXT = 'Dialogue/Text'
CURSOR_CAMERA = 'Cursor/Camera'
LEVEL_VARS = 'Level-wide Unlocks and Variables'
GAME_VARS = 'Game-wide Unlocks and Variables'
TILEMAP = 'Tilemap'
REGION = 'Region'
ADD_REMOVE_INTERACT_WITH_UNITS = 'Add/Remove/Interact with Units'
MODIFY_UNIT_PROPERTIES = 'Modify Unit Properties'
UNIT_GROUPS = 'Unit Groups'
MISCELLANEOUS = 'Miscellaneous'
HIDDEN = 'Hidden'
class EventCommand(Prefab):
nid: str = None
nickname: str = None
tag: Tags = Tags.HIDDEN
desc: str = ''
keywords: list = []
optional_keywords: list = []
flags: list = []
values: list = []
display_values: list = []
def __init__(self, values=None, disp_values=None):
self.values = values or []
self.display_values = disp_values or values or []
def save(self):
# Don't bother saving display values if they are identical
if self.display_values == self.values:
return self.nid, self.values
else:
return self.nid, self.values, self.display_values
def to_plain_text(self):
if self.display_values:
return ';'.join([self.nid] + self.display_values)
else:
return ';'.join([self.nid] + self.values)
def __repr__(self):
return self.to_plain_text()
class Comment(EventCommand):
nid = "comment"
nickname = '#'
tag = Tags.FLOW_CONTROL
desc = \
"""
**Lines** starting with '#' will be ignored.
"""
def to_plain_text(self):
return self.values[0]
class If(EventCommand):
nid = "if"
tag = Tags.FLOW_CONTROL
desc = \
"""
If the _Condition_ returns true, the block under this command will be executed. If it returns false, the script will search for the next **elif**, **else**, or **end** command before proceeding. If it is not a valid Python expression, the result will be treated as false.
Remember to end your **if** blocks with **end**.
The indentation is not required, but is recommended for organization of the conditional blocks.
Example:
```
if;game.check_dead('Eirika')
lose_game
elif;game.check_dead('Lyon')
win_game
else
u;Eirika
s;Eirika;Nice!
r;Eirika
end
```
"""
keywords = ['Condition']
class Elif(EventCommand):
nid = "elif"
tag = Tags.FLOW_CONTROL
desc = \
"""
Works exactly like the **if** statement, but is called only if the previous **if** or **elif** returned false.
In the following example, the **elif** will only be processed if `if;game.check_dead('Eirika')` return false.
Example:
```
if;game.check_dead('Eirika')
lose_game
elif;game.check_dead('Lyon')
win_game
else
u;Eirika
s;Eirika;Nice!
r;Eirika
end
```
"""
keywords = ['Condition']
class Else(EventCommand):
nid = "else"
tag = Tags.FLOW_CONTROL
desc = \
"""
Defines a block to be executed only if the previous **if** or **elif** returned false.
Example:
```
if;game.check_dead('Eirika')
lose_game
elif;game.check_dead('Lyon')
win_game
else
u;Eirika
s;Eirika;Nice!
r;Eirika
end
```
"""
class End(EventCommand):
nid = "end"
tag = Tags.FLOW_CONTROL
desc = \
"""
Ends a conditional block. Refer to the **if** command for more information.
"""
class Break(EventCommand):
nid = "break"
tag = Tags.FLOW_CONTROL
desc = \
"""
Immediately ends the current event.
"""
class Wait(EventCommand):
nid = "wait"
tag = Tags.FLOW_CONTROL
desc = \
"""
Pauses the execution of the script for _Time_ milliseconds.
Often used after a scene transition, cursor movement, or reinforcements to give the player a chance to take in the scene.
"""
keywords = ['Time']
class EndSkip(EventCommand):
nid = "end_skip"
tag = Tags.FLOW_CONTROL
desc = \
"""
If the player was skipping through the event script, stop the skip here. Used to prevent a single skip from skipping through an entire event.
"""
class Music(EventCommand):
nid = "music"
nickname = "m"
tag = Tags.MUSIC_SOUND
desc = \
"""
Fades in _Music_ over the course of _Time_ milliseconds. Fade in defaults to 400 milliseconds.
"""
keywords = ['Music']
optional_keywords = ['Time'] # How long to fade in (default 400)
class MusicClear(EventCommand):
nid = "music_clear"
tag = Tags.MUSIC_SOUND
desc = \
"""
Fades out the currently playing song over the course of _Time_ milliseconds. Also clears the entire song stack. Fade out defaults to 400 milliseconds.
"""
optional_keywords = ['Time'] # How long to fade out
class Sound(EventCommand):
nid = "sound"
tag = Tags.MUSIC_SOUND
desc = \
"""
Plays the _Sound_ once.
"""
keywords = ['Sound']
class ChangeMusic(EventCommand):
nid = 'change_music'
tag = Tags.MUSIC_SOUND
desc = \
"""
Changes the phase theme music. For instance, you could use this command to change the player phase theme halfway through the chapter.
"""
keywords = ['PhaseMusic', 'Music']
class AddPortrait(EventCommand):
nid = "add_portrait"
nickname = "u"
tag = Tags.PORTRAIT
desc = \
"""
Adds a portrait to the screen.
Extra flags:
1. _mirror_: Portrait will face opposite expected direction.
2. _low_priority_: Portrait will appear behind all other portraits on the screen.
3. _immediate_: Portrait will not fade in.
4. _no_block_: Portrait will fade in, but will not pause execution of event script while doing so.
"""
keywords = ['Portrait', 'ScreenPosition']
optional_keywords = ['Slide', 'ExpressionList']
flags = ["mirror", "low_priority", "immediate", "no_block"]
class MultiAddPortrait(EventCommand):
nid = "multi_add_portrait"
nickname = "uu"
tag = Tags.PORTRAIT
desc = \
"""
Adds more than one portrait to the screen at the same time. Accepts 2-4 portraits and their associated _ScreenPosition_ as input.
"""
keywords = ['Portrait', 'ScreenPosition', 'Portrait', 'ScreenPosition']
optional_keywords = ['Portrait', 'ScreenPosition', 'Portrait', 'ScreenPosition']
class RemovePortrait(EventCommand):
nid = "remove_portrait"
nickname = "r"
tag = Tags.PORTRAIT
keywords = ['Portrait']
flags = ["immediate", "no_block"]
class MultiRemovePortrait(EventCommand):
nid = "multi_remove_portrait"
nickname = "rr"
tag = Tags.PORTRAIT
keywords = ['Portrait', 'Portrait']
optional_keywords = ['Portrait', 'Portrait']
class MovePortrait(EventCommand):
nid = "move_portrait"
tag = Tags.PORTRAIT
keywords = ['Portrait', 'ScreenPosition']
flags = ["immediate", "no_block"]
class BopPortrait(EventCommand):
nid = "bop_portrait"
nickname = "bop"
tag = Tags.PORTRAIT
keywords = ['Portrait']
flags = ["no_block"]
class Expression(EventCommand):
nid = "expression"
nickname = "e"
tag = Tags.PORTRAIT
keywords = ['Portrait', 'ExpressionList']
class Speak(EventCommand):
nid = "speak"
nickname = "s"
tag = Tags.DIALOGUE_TEXT
keywords = ['Speaker', 'Text']
optional_keywords = ['ScreenPosition', 'Width', 'DialogVariant']
flags = ['low_priority']
class Transition(EventCommand):
nid = "transition"
nickname = "t"
tag = Tags.BG_FG
optional_keywords = ['Direction', 'Speed', 'Color3']
class Background(EventCommand):
# Also does remove background
nid = "change_background"
nickname = "b"
tag = Tags.BG_FG
optional_keywords = ['Panorama']
flags = ["keep_portraits"]
class DispCursor(EventCommand):
nid = "disp_cursor"
tag = Tags.CURSOR_CAMERA
keywords = ["Bool"]
class MoveCursor(EventCommand):
nid = "move_cursor"
nickname = "set_cursor"
tag = Tags.CURSOR_CAMERA
keywords = ["Position"]
flags = ["immediate"]
class CenterCursor(EventCommand):
nid = "center_cursor"
tag = Tags.CURSOR_CAMERA
keywords = ["Position"]
flags = ["immediate"]
class FlickerCursor(EventCommand):
nid = 'flicker_cursor'
nickname = 'highlight'
tag = Tags.CURSOR_CAMERA
keywords = ["Position"]
flags = ["immediate"]
class GameVar(EventCommand):
nid = 'game_var'
tag = Tags.GAME_VARS
keywords = ["Nid", "Condition"]
class IncGameVar(EventCommand):
nid = 'inc_game_var'
tag = Tags.GAME_VARS
keywords = ["Nid"]
optional_keywords = ["Condition"]
class LevelVar(EventCommand):
nid = 'level_var'
tag = Tags.LEVEL_VARS
keywords = ["Nid", "Condition"]
class IncLevelVar(EventCommand):
nid = 'inc_level_var'
tag = Tags.LEVEL_VARS
keywords = ["Nid"]
optional_keywords = ["Condition"]
class WinGame(EventCommand):
nid = 'win_game'
tag = Tags.LEVEL_VARS
class LoseGame(EventCommand):
nid = 'lose_game'
tag = Tags.LEVEL_VARS
class ActivateTurnwheel(EventCommand):
nid = 'activate_turnwheel'
tag = Tags.MISCELLANEOUS
# Whether to force the player to move the turnwheel back
# defaults to true
optional_keywords = ['Bool']
class BattleSave(EventCommand):
nid = 'battle_save'
tag = Tags.MISCELLANEOUS
class ChangeTilemap(EventCommand):
nid = 'change_tilemap'
tag = Tags.TILEMAP
keywords = ["Tilemap"]
# How much to offset placed units by
# Which tilemap to load the unit positions from
optional_keywords = ["PositionOffset", "Tilemap"]
flags = ["reload"] # Should place units in previously recorded positions
class LoadUnit(EventCommand):
nid = 'load_unit'
tag = Tags.ADD_REMOVE_INTERACT_WITH_UNITS
keywords = ["UniqueUnit"]
optional_keywords = ["Team", "AI"]
class MakeGeneric(EventCommand):
nid = 'make_generic'
tag = Tags.ADD_REMOVE_INTERACT_WITH_UNITS
# Nid, class, level, team, ai, faction, anim variant
keywords = ["String", "Klass", "String", "Team"]
optional_keywords = ["AI", "Faction", "String", "ItemList"]
class CreateUnit(EventCommand):
nid = 'create_unit'
tag = Tags.ADD_REMOVE_INTERACT_WITH_UNITS
# Unit template and new unit nid (can be '')
keywords = ["Unit", "String"]
# Unit level, position, entrytype, placement
optional_keywords = ["String", "Position", "EntryType", "Placement"]
class AddUnit(EventCommand):
nid = 'add_unit'
nickname = 'add'
tag = Tags.ADD_REMOVE_INTERACT_WITH_UNITS
keywords = ["Unit"]
optional_keywords = ["Position", "EntryType", "Placement"]
class MoveUnit(EventCommand):
nid = 'move_unit'
nickname = 'move'
tag = Tags.ADD_REMOVE_INTERACT_WITH_UNITS
keywords = ["Unit"]
optional_keywords = ["Position", "MovementType", "Placement"]
flags = ['no_block', 'no_follow']
class RemoveUnit(EventCommand):
nid = 'remove_unit'
nickname = 'remove'
tag = Tags.ADD_REMOVE_INTERACT_WITH_UNITS
keywords = ["Unit"]
optional_keywords = ["RemoveType"]
class KillUnit(EventCommand):
nid = 'kill_unit'
nickname = 'kill'
tag = Tags.ADD_REMOVE_INTERACT_WITH_UNITS
keywords = ["Unit"]
flags = ['immediate']
class RemoveAllUnits(EventCommand):
nid = 'remove_all_units'
tag = Tags.ADD_REMOVE_INTERACT_WITH_UNITS
class RemoveAllEnemies(EventCommand):
nid = 'remove_all_enemies'
tag = Tags.ADD_REMOVE_INTERACT_WITH_UNITS
class InteractUnit(EventCommand):
nid = 'interact_unit'
nickname = 'interact'
tag = Tags.ADD_REMOVE_INTERACT_WITH_UNITS
keywords = ["Unit", "Unit"]
optional_keywords = ["CombatScript", "Ability"]
class SetCurrentHP(EventCommand):
nid = 'set_current_hp'
tag = Tags.MODIFY_UNIT_PROPERTIES
keywords = ["Unit", "PositiveInteger"]
class SetCurrentMana(EventCommand):
nid = 'set_current_mana'
tag = Tags.MODIFY_UNIT_PROPERTIES
keywords = ["Unit", "PositiveInteger"]
class Resurrect(EventCommand):
nid = 'resurrect'
tag = Tags.ADD_REMOVE_INTERACT_WITH_UNITS
keywords = ["GlobalUnit"]
class Reset(EventCommand):
nid = 'reset'
tag = Tags.MODIFY_UNIT_PROPERTIES
keywords = ["Unit"]
class HasAttacked(EventCommand):
nid = 'has_attacked'
tag = Tags.MODIFY_UNIT_PROPERTIES
keywords = ["Unit"]
class HasTraded(EventCommand):
nid = 'has_traded'
tag = Tags.MODIFY_UNIT_PROPERTIES
keywords = ['Unit']
class AddGroup(EventCommand):
nid = 'add_group'
tag = Tags.UNIT_GROUPS
keywords = ["Group"]
optional_keywords = ["StartingGroup", "EntryType", "Placement"]
flags = ["create"]
class SpawnGroup(EventCommand):
nid = 'spawn_group'
tag = Tags.UNIT_GROUPS
keywords = ["Group", "CardinalDirection", "StartingGroup"]
optional_keywords = ["EntryType", "Placement"]
flags = ["create", "no_block", 'no_follow']
class MoveGroup(EventCommand):
nid = 'move_group'
nickname = 'morph_group'
tag = Tags.UNIT_GROUPS
keywords = ["Group", "StartingGroup"]
optional_keywords = ["MovementType", "Placement"]
flags = ['no_block', 'no_follow']
class RemoveGroup(EventCommand):
nid = 'remove_group'
tag = Tags.UNIT_GROUPS
keywords = ["Group"]
optional_keywords = ["RemoveType"]
class GiveItem(EventCommand):
nid = 'give_item'
tag = Tags.MODIFY_UNIT_PROPERTIES
keywords = ["GlobalUnit", "Item"]
flags = ['no_banner', 'no_choice', 'droppable']
class RemoveItem(EventCommand):
nid = 'remove_item'
tag = Tags.MODIFY_UNIT_PROPERTIES
keywords = ["GlobalUnit", "Item"]
flags = ['no_banner']
class GiveMoney(EventCommand):
nid = 'give_money'
tag = Tags.GAME_VARS
keywords = ["Integer"]
optional_keywords = ["Party"]
flags = ['no_banner']
class GiveBexp(EventCommand):
nid = 'give_bexp'
tag = Tags.GAME_VARS
keywords = ["Condition"]
optional_keywords = ["Party", "String"]
flags = ['no_banner']
class GiveExp(EventCommand):
nid = 'give_exp'
tag = Tags.MODIFY_UNIT_PROPERTIES
keywords = ["GlobalUnit", "PositiveInteger"]
class SetExp(EventCommand):
nid = 'set_exp'
tag = Tags.MODIFY_UNIT_PROPERTIES
keywords = ["GlobalUnit", "PositiveInteger"]
class GiveWexp(EventCommand):
nid = 'give_wexp'
tag = Tags.MODIFY_UNIT_PROPERTIES
keywords = ["GlobalUnit", "WeaponType", "Integer"]
flags = ['no_banner']
class GiveSkill(EventCommand):
nid = 'give_skill'
tag = Tags.MODIFY_UNIT_PROPERTIES
keywords = ["GlobalUnit", "Skill"]
flags = ['no_banner']
class RemoveSkill(EventCommand):
nid = 'remove_skill'
tag = Tags.MODIFY_UNIT_PROPERTIES
keywords = ["GlobalUnit", "Skill"]
flags = ['no_banner']
class ChangeAI(EventCommand):
nid = 'change_ai'
tag = Tags.MODIFY_UNIT_PROPERTIES
keywords = ["GlobalUnit", "AI"]
class ChangeTeam(EventCommand):
nid = 'change_team'
tag = Tags.MODIFY_UNIT_PROPERTIES
keywords = ["GlobalUnit", "Team"]
class ChangePortrait(EventCommand):
nid = 'change_portrait'
tag = Tags.MODIFY_UNIT_PROPERTIES
keywords = ["GlobalUnit", "PortraitNid"]
class ChangeStats(EventCommand):
nid = 'change_stats'
tag = Tags.MODIFY_UNIT_PROPERTIES
keywords = ["GlobalUnit", "StatList"]
flags = ['immediate']
class SetStats(EventCommand):
nid = 'set_stats'
tag = Tags.MODIFY_UNIT_PROPERTIES
keywords = ["GlobalUnit", "StatList"]
flags = ['immediate']
class AutolevelTo(EventCommand):
nid = 'autolevel_to'
tag = Tags.MODIFY_UNIT_PROPERTIES
# Second argument is level that is eval'd
keywords = ["GlobalUnit", "String"]
# Whether to actually change the unit's level
flags = ["hidden"]
class SetModeAutolevels(EventCommand):
nid = 'set_mode_autolevels'
tag = Tags.GAME_VARS
keywords = ["String"]
# Whether to actually change the unit's level
flags = ["hidden"]
class Promote(EventCommand):
nid = 'promote'
tag = Tags.MODIFY_UNIT_PROPERTIES
keywords = ["GlobalUnit"]
optional_keywords = ["Klass"]
class ChangeClass(EventCommand):
nid = 'change_class'
tag = Tags.MODIFY_UNIT_PROPERTIES
keywords = ["GlobalUnit"]
optional_keywords = ["Klass"]
class AddTag(EventCommand):
nid = 'add_tag'
tag = Tags.MODIFY_UNIT_PROPERTIES
keywords = ["GlobalUnit", "Tag"]
class RemoveTag(EventCommand):
nid = 'remove_tag'
tag = Tags.MODIFY_UNIT_PROPERTIES
keywords = ["GlobalUnit", "Tag"]
class AddTalk(EventCommand):
nid = 'add_talk'
tag = Tags.LEVEL_VARS
keywords = ["Unit", "Unit"]
class RemoveTalk(EventCommand):
nid = 'remove_talk'
tag = Tags.LEVEL_VARS
keywords = ["Unit", "Unit"]
class AddLore(EventCommand):
nid = 'add_lore'
nickname = 'unlock_lore'
tag = Tags.GAME_VARS
keywords = ["Lore"]
class RemoveLore(EventCommand):
nid = 'remove_lore'
tag = Tags.GAME_VARS
keywords = ["Lore"]
class AddBaseConvo(EventCommand):
nid = 'add_base_convo'
tag = Tags.LEVEL_VARS
keywords = ["String"]
class IgnoreBaseConvo(EventCommand):
nid = 'ignore_base_convo'
tag = Tags.LEVEL_VARS
keywords = ["String"]
class RemoveBaseConvo(EventCommand):
nid = 'remove_base_convo'
tag = Tags.LEVEL_VARS
keywords = ["String"]
class IncrementSupportPoints(EventCommand):
nid = 'increment_support_points'
tag = Tags.MODIFY_UNIT_PROPERTIES
keywords = ['GlobalUnit', 'GlobalUnit', 'PositiveInteger']
class AddMarketItem(EventCommand):
nid = 'add_market_item'
tag = Tags.GAME_VARS
keywords = ["Item"]
class RemoveMarketItem(EventCommand):
nid = 'remove_market_item'
tag = Tags.GAME_VARS
keywords = ["Item"]
class AddRegion(EventCommand):
nid = 'add_region'
tag = Tags.REGION
keywords = ["Nid", "Position", "Size", "RegionType"]
optional_keywords = ["String"]
flags = ["only_once"]
class RegionCondition(EventCommand):
nid = 'region_condition'
tag = Tags.REGION
keywords = ["Nid", "Condition"]
class RemoveRegion(EventCommand):
nid = 'remove_region'
tag = Tags.REGION
keywords = ["Nid"]
class ShowLayer(EventCommand):
nid = 'show_layer'
tag = Tags.TILEMAP
keywords = ["Layer"]
optional_keywords = ["LayerTransition"]
class HideLayer(EventCommand):
nid = 'hide_layer'
tag = Tags.TILEMAP
keywords = ["Layer"]
optional_keywords = ["LayerTransition"]
class AddWeather(EventCommand):
nid = 'add_weather'
tag = Tags.TILEMAP
keywords = ["Weather"]
class RemoveWeather(EventCommand):
nid = 'remove_weather'
tag = Tags.TILEMAP
keywords = ["Weather"]
class ChangeObjectiveSimple(EventCommand):
nid = 'change_objective_simple'
tag = Tags.LEVEL_VARS
keywords = ["String"]
class ChangeObjectiveWin(EventCommand):
nid = 'change_objective_win'
tag = Tags.LEVEL_VARS
keywords = ["String"]
class ChangeObjectiveLoss(EventCommand):
nid = 'change_objective_loss'
tag = Tags.LEVEL_VARS
keywords = ["String"]
class SetPosition(EventCommand):
nid = 'set_position'
tag = Tags.MISCELLANEOUS
keywords = ["String"]
class MapAnim(EventCommand):
nid = 'map_anim'
tag = Tags.TILEMAP
keywords = ["MapAnim", "Position"]
flags = ["no_block"]
class ArrangeFormation(EventCommand):
nid = 'arrange_formation'
tag = Tags.MISCELLANEOUS
# Puts units on formation tiles automatically
class Prep(EventCommand):
nid = 'prep'
tag = Tags.MISCELLANEOUS
optional_keywords = ["Bool", "Music"] # Pick units
class Base(EventCommand):
nid = 'base'
tag = Tags.MISCELLANEOUS
keywords = ["Panorama"]
optional_keywords = ["Music"]
class Shop(EventCommand):
nid = 'shop'
tag = Tags.MISCELLANEOUS
keywords = ["Unit", "ItemList"]
optional_keywords = ["ShopFlavor"]
class Choice(EventCommand):
nid = 'choice'
tag = Tags.MISCELLANEOUS
keywords = ['Nid', 'String', 'StringList']
optional_keywords = ['Orientation']
class ChapterTitle(EventCommand):
nid = 'chapter_title'
tag = Tags.MISCELLANEOUS
optional_keywords = ["Music", "String"]
class Alert(EventCommand):
nid = 'alert'
tag = Tags.DIALOGUE_TEXT
keywords = ["String"]
class VictoryScreen(EventCommand):
nid = 'victory_screen'
tag = Tags.MISCELLANEOUS
class RecordsScreen(EventCommand):
nid = 'records_screen'
tag = Tags.MISCELLANEOUS
class LocationCard(EventCommand):
nid = 'location_card'
tag = Tags.DIALOGUE_TEXT
keywords = ["String"]
class Credits(EventCommand):
nid = 'credits'
tag = Tags.DIALOGUE_TEXT
keywords = ["String", "String"]
flags = ['wait', 'center', 'no_split']
class Ending(EventCommand):
nid = 'ending'
tag = Tags.DIALOGUE_TEXT
keywords = ["Portrait", "String", "String"]
class PopDialog(EventCommand):
nid = 'pop_dialog'
tag = Tags.DIALOGUE_TEXT
desc = \
"""
Removes the most recent dialog text box from the screen. Generally only used in conjunction with the `ending` command to remove the Ending box during a transition.
Example:
```
ending;Coyote;Coyote, Man of Mystery;Too mysterious for words.
transition;Close
pop_dialog
transition;Open
```
"""
class Unlock(EventCommand):
nid = 'unlock'
tag = Tags.REGION
keywords = ["Unit"]
class FindUnlock(EventCommand):
nid = 'find_unlock'
tag = Tags.HIDDEN
keywords = ["Unit"]
class SpendUnlock(EventCommand):
nid = 'spend_unlock'
tag = Tags.HIDDEN
keywords = ["Unit"]
class TriggerScript(EventCommand):
nid = 'trigger_script'
tag = Tags.MISCELLANEOUS
keywords = ["Event"]
optional_keywords = ["GlobalUnit", "GlobalUnit"]
class ChangeRoaming(EventCommand):
nid = 'change_roaming'
tag = Tags.MISCELLANEOUS
desc = "Turn free roam mode on or off"
keywords = ["Bool"]
class ChangeRoamingUnit(EventCommand):
nid = 'change_roaming_unit'
tag = Tags.MISCELLANEOUS
desc = "Changes the level's current roaming unit."
keywords = ["Unit"]
class CleanUpRoaming(EventCommand):
nid = 'clean_up_roaming'
tag = Tags.MISCELLANEOUS
desc = "Removes all units other than the roaming unit"
keywords = []
class AddToInitiative(EventCommand):
nid = 'add_to_initiative'
tag = Tags.MISCELLANEOUS
desc = "Adds the specified unit to the specified point in the initiative order. 0 is the current initiative position."
keywords = ["Unit", "Integer"]
class MoveInInitiative(EventCommand):
nid = 'move_in_initiative'
tag = Tags.MISCELLANEOUS
desc = "Moves the initiative of the specified unit."
keywords = ["Unit", "Integer"]
def get_commands():
return EventCommand.__subclasses__()
def restore_command(dat):
if len(dat) == 2:
nid, values = dat
display_values = None
elif len(dat) == 3:
nid, values, display_values = dat
subclasses = EventCommand.__subclasses__()
for command in subclasses:
if command.nid == nid:
copy = command(values, display_values)
return copy
print("Couldn't restore event command!")
print(nid, values, display_values)
return None
def parse_text(text):
if text.startswith('#'):
return Comment([text])
arguments = text.split(';')
command_nid = arguments[0]
subclasses = EventCommand.__subclasses__()
for command in subclasses:
if command.nid == command_nid or command.nickname == command_nid:
cmd_args = arguments[1:]
true_cmd_args = []
command_info = command()
for idx, arg in enumerate(cmd_args):
if idx < len(command_info.keywords):
cmd_keyword = command_info.keywords[idx]
elif idx - len(command_info.keywords) < len(command_info.optional_keywords):
cmd_keyword = command_info.optional_keywords[idx - len(command_info.keywords)]
else:
cmd_keyword = "N/A"
# if parentheses exists, then they contain the "true" arg, with everything outside parens essentially as comments
if '(' in arg and ')' in arg and not cmd_keyword == 'Condition':
true_arg = arg[arg.find("(")+1:arg.find(")")]
true_cmd_args.append(true_arg)
else:
true_cmd_args.append(arg)
copy = command(true_cmd_args, cmd_args)
return copy
return None
def parse(command):
values = command.values
num_keywords = len(command.keywords)
true_values = values[:num_keywords]
flags = {v for v in values[num_keywords:] if v in command.flags}
optional_keywords = [v for v in values[num_keywords:] if v not in flags]
true_values += optional_keywords
return true_values, flags
|
7,366 | 4745d81558130440d35d277b586572f5d3f85c06 | import unittest
import userinput
class Testing(unittest.TestCase):
def test_creation(self):
x = userinput.UserInput()
self.assertNotEqual(x, None)
def test_charset_initialization(self):
x = userinput.UserInput()
self.assertEqual(x.character_set, userinput.CHARACTERS)
def test_charset_display(self):
x = userinput.UserInput()
self.assertEqual(str(x.character_set), str(x.display_characters()))
def test_charset_remove(self):
x = userinput.UserInput()
# my favourite character :)
x.remove_character('پ')
self.assertNotIn('پ', x.character_set)
def test_charset_remove_missing(self):
x = userinput.UserInput()
# my favourite character :)
try:
x.remove_character('+')
self.assertFalse(False)
except KeyError:
self.assertTrue(True)
if __name__ == '__main__':
unittest.main()
|
7,367 | e14b8d0f85042ceda955022bee08b3b3b4c2361d | # Generated by Django 3.0.8 on 2021-03-25 13:47
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('Asha', '0005_baby'),
]
operations = [
migrations.AlterField(
model_name='baby',
name='Auth_Id',
field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='Asha.BasicDetails'),
),
]
|
7,368 | a0460b100a750b685f3e831a19379b0e26da4b35 | # x = 10
#
# def increment():
# x += 1
#
# ^^ Non-working code
x = 10
def increment(number):
number += 1
return number
# If we want to change a global variable,
# we have to do it like this
x = increment(x) |
7,369 | 72b5e76f63e347d7275b0b711fa02b7f327785f6 | #!/usr/bin/python
import os
import sys
fdatadir = "/fdata/hepx/store/user/taohuang/NANOAOD/"
datasets = []; NumSample = []; sampleN_short = []
Nanodatasets = []; localdirs = {}
MCxsections = []
#doTT=True; doDY=True; doVV=True; doSingleT=True; doWjets=True; dottV=True
##DoubleEG
datasets.append('/DoubleEG/Run2016B-05Feb2018_ver1-v1/NANOAOD')
NumSample.append('-1'); sampleN_short.append('DoubleEGRun2016Bver1')
MCxsections.append(-1.0)
datasets.append('/DoubleEG/Run2016B-05Feb2018_ver2-v1/NANOAOD')
NumSample.append('-2'); sampleN_short.append('DoubleEGRun2016Bver2')
MCxsections.append(-1.0)
datasets.append('/DoubleEG/Run2016C-05Feb2018-v1/NANOAOD')
NumSample.append('-3'); sampleN_short.append('DoubleEGRun2016C')
MCxsections.append(-1.0)
datasets.append('/DoubleEG/Run2016D-05Feb2018-v1/NANOAOD')
NumSample.append('-4'); sampleN_short.append('DoubleEGRun2016D')
MCxsections.append(-1.0)
datasets.append('/DoubleEG/Run2016E-05Feb2018-v1/NANOAOD')
NumSample.append('-5'); sampleN_short.append('DoubleEGRun2016E')
MCxsections.append(-1.0)
datasets.append('/DoubleEG/Run2016F-05Feb2018-v1/NANOAOD')
NumSample.append('-6'); sampleN_short.append('DoubleEGRun2016F')
MCxsections.append(-1.0)
datasets.append('/DoubleEG/Run2016G-05Feb2018-v1/NANOAOD')
NumSample.append('-7'); sampleN_short.append('DoubleEGRun2016G')
MCxsections.append(-1.0)
datasets.append('/DoubleEG/Run2016H-05Feb2018_ver2-v1/NANOAOD')
NumSample.append('-8'); sampleN_short.append('DoubleEGRun2016Hver2')
MCxsections.append(-1.0)
datasets.append('/DoubleEG/Run2016H-05Feb2018_ver3-v1/NANOAOD')
NumSample.append('-9'); sampleN_short.append('DoubleEGRun2016Hver3')
MCxsections.append(-1.0)
##DoubleMuon
datasets.append('/DoubleMuon/Run2016B-05Feb2018_ver1-v1/NANOAOD')
NumSample.append('-10'); sampleN_short.append('DoubleMuonRun2016Bver1')
MCxsections.append(-1.0)
datasets.append('/DoubleMuon/Run2016B-05Feb2018_ver2-v1/NANOAOD')
NumSample.append('-11'); sampleN_short.append('DoubleMuonRun2016Bver2')
MCxsections.append(-1.0)
datasets.append('/DoubleMuon/Run2016C-05Feb2018-v1/NANOAOD')
NumSample.append('-12'); sampleN_short.append('DoubleMuonRun2016C')
MCxsections.append(-1.0)
datasets.append('/DoubleMuon/Run2016D-05Feb2018-v1/NANOAOD')
NumSample.append('-13'); sampleN_short.append('DoubleMuonRun2016D')
MCxsections.append(-1.0)
datasets.append('/DoubleMuon/Run2016E-05Feb2018-v1/NANOAOD')
NumSample.append('-14'); sampleN_short.append('DoubleMuonRun2016E')
MCxsections.append(-1.0)
datasets.append('/DoubleMuon/Run2016F-05Feb2018-v1/NANOAOD')
NumSample.append('-15'); sampleN_short.append('DoubleMuonRun2016F')
MCxsections.append(-1.0)
datasets.append('/DoubleMuon/Run2016G-05Feb2018-v1/NANOAOD')
NumSample.append('-16'); sampleN_short.append('DoubleMuonRun2016G')
MCxsections.append(-1.0)
datasets.append('/DoubleMuon/Run2016H-05Feb2018_ver2-v1/NANOAOD')
NumSample.append('-17'); sampleN_short.append('DoubleMuonRun2016Hver2')
MCxsections.append(-1.0)
datasets.append('/DoubleMuon/Run2016H-05Feb2018_ver3-v1/NANOAOD')
NumSample.append('-18'); sampleN_short.append('DoubleMuonRun2016Hver3')
MCxsections.append(-1.0)
#MuonEG
datasets.append('/MuonEG/Run2016B-05Feb2018_ver1-v1/NANOAOD')
NumSample.append('-19'); sampleN_short.append('MuonEGRun2016Bver2')
MCxsections.append(-1.0)
datasets.append('/MuonEG/Run2016B-05Feb2018_ver2-v1/NANOAOD')
NumSample.append('-20'); sampleN_short.append('MuonEGRun2016Bver2')
MCxsections.append(-1.0)
datasets.append('/MuonEG/Run2016C-05Feb2018-v1/NANOAOD')
NumSample.append('-21'); sampleN_short.append('MuonEGRun2016C')
MCxsections.append(-1.0)
datasets.append('/MuonEG/Run2016D-05Feb2018-v1/NANOAOD')
NumSample.append('-22'); sampleN_short.append('MuonEGRun2016D')
MCxsections.append(-1.0)
datasets.append('/MuonEG/Run2016E-05Feb2018-v1/NANOAOD')
NumSample.append('-23'); sampleN_short.append('MuonEGRun2016E')
MCxsections.append(-1.0)
datasets.append('/MuonEG/Run2016F-05Feb2018-v1/NANOAOD')
NumSample.append('-24'); sampleN_short.append('MuonEGRun2016F')
MCxsections.append(-1.0)
datasets.append('/MuonEG/Run2016G-05Feb2018-v1/NANOAOD')
NumSample.append('-25'); sampleN_short.append('MuonEGRun2016G')
MCxsections.append(-1.0)
datasets.append('/MuonEG/Run2016H-05Feb2018_ver2-v1/NANOAOD')
NumSample.append('-26'); sampleN_short.append('MuonEGRun2016Hver2')
MCxsections.append(-1.0)
datasets.append('/MuonEG/Run2016H-05Feb2018_ver3-v1/NANOAOD')
NumSample.append('-27'); sampleN_short.append('MuonEGRun2016Hver3')
MCxsections.append(-1.0)
masspoints = [260, 270, 300, 350, 400, 450, 500, 550, 600, 650, 750, 800, 900]
for mass in masspoints:
datasets.append("/GluGluToRadionToHHTo2B2VTo2L2Nu_M-%d_narrow_13TeV-madgraph-v2/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2-v1/NANOAODSIM"%mass)
NumSample.append(masspoints.index(mass)); sampleN_short.append('RadionM%d'%mass)
MCxsections.append(5.0)#by default, assume the cross section for signal is 5pb
#datasets.append("/GluGluToBulkGravitonToHHTo2B2VTo2L2Nu_M-*_narrow_13TeV-madgraph-v2/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2-v1/NANOAODSIM")
#NumSample.append('2'); sampleN_short.append('Graviton')
# TT## FIXME, use official one later
#datasets.append('/TTTo2L2Nu_13TeV-powheg/RunIISpring16MiniAODv2-PUSpring16_80X_mcRun2_asymptotic_2016_miniAODv2_v0_ext1-v1/MINIAODSIM')
datasets.append('/TTTo2L2Nu_TuneCUETP8M2_ttHtranche3_13TeV-powheg-pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM')
#datasets.append('/TTTo2L2Nu_TuneCP5_13TeV-powheg-pythia8/arizzi-RunIIFall17MiniAOD-94X-Nano01Fall17-e273b12d9f89d622a34e4bc98b05ee29/USER')
NumSample.append('13'); sampleN_short.append('TT')
#MCxsections.append(72.1)
#MCxsections.append(76.7)
MCxsections.append(87.31)
# DY
#datasets.append('/DYJetsToLL_M-10to50_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM')
datasets.append('/DYJetsToLL_M-10to50_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM')
NumSample.append('14'); sampleN_short.append('DY')
MCxsections.append(18610.0)
datasets.append('/DYToLL_0J_13TeV-amcatnloFXFX-pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6_ext1-v1/MINIAODSIM')
NumSample.append('15'); sampleN_short.append('DY')
MCxsections.append(4758.9)
datasets.append('/DYToLL_1J_13TeV-amcatnloFXFX-pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6_ext1-v1/MINIAODSIM')
NumSample.append('16'); sampleN_short.append('DY')
MCxsections.append(929.1)
datasets.append('/DYToLL_2J_13TeV-amcatnloFXFX-pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6_ext1-v1/MINIAODSIM')
NumSample.append('17'); sampleN_short.append('DY')
MCxsections.append(337.1)
# VV
datasets.append('/ZZTo2L2Q_13TeV_amcatnloFXFX_madspin_pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM')
NumSample.append('18'); sampleN_short.append('VV')
MCxsections.append(3.22)
datasets.append('/ZZTo2L2Nu_13TeV_powheg_pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM')
NumSample.append('19'); sampleN_short.append('VV')
MCxsections.append(0.564)
datasets.append('/ZZTo4L_13TeV_powheg_pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM')
NumSample.append('20'); sampleN_short.append('VV')
MCxsections.append(1.256)
#datasets.append('/WWToLNuQQ_aTGC_13TeV-madgraph-pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM')
#NumSample.append('21'); sampleN_short.append('VV')
#MCxsections.append(49.997)# ## not available now because of pdf uncertainty
#FIXME
#datasets.append('/WWTo2L2Nu_13TeV-amcatnloFXFX-madspin-pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM')
#datasets.append('/WWTo2L2Nu_13TeV-powheg/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM')
#NumSample.append('22'); sampleN_short.append('VV') ### not available now
#MCxsections.append(12.178)
datasets.append('/WZTo2L2Q_13TeV_amcatnloFXFX_madspin_pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM')
NumSample.append('23'); sampleN_short.append('VV')
MCxsections.append(5.595)
#FIXME
#datasets.append('/WZTo1L3Nu_13TeV_amcatnloFXFX_madspin_pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM')
#NumSample.append('24'); sampleN_short.append('VV') ### not available now
#MCxsections.append(3.033)
datasets.append('/WZTo1L1Nu2Q_13TeV_amcatnloFXFX_madspin_pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v3/MINIAODSIM')
NumSample.append('25'); sampleN_short.append('VV')
MCxsections.append(10.71)
datasets.append('/WZTo3LNu_TuneCUETP8M1_13TeV-powheg-pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM')
NumSample.append('26'); sampleN_short.append('VV')
MCxsections.append(4.42965)
##sT
datasets.append('/ST_t-channel_top_4f_inclusiveDecays_13TeV-powhegV2-madspin-pythia8_TuneCUETP8M1/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM')
NumSample.append('27'); sampleN_short.append('sT')
MCxsections.append(136.02)
datasets.append('/ST_t-channel_antitop_4f_inclusiveDecays_13TeV-powhegV2-madspin-pythia8_TuneCUETP8M1/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM')
NumSample.append('28'); sampleN_short.append('sT')
MCxsections.append(80.95)
datasets.append('/ST_s-channel_4f_leptonDecays_13TeV-amcatnlo-pythia8_TuneCUETP8M1/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM')
NumSample.append('29'); sampleN_short.append('sT')
MCxsections.append(3.36)
datasets.append('/ST_tW_antitop_5f_NoFullyHadronicDecays_13TeV-powheg_TuneCUETP8M1/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6_ext1-v1/MINIAODSIM')
NumSample.append('30'); sampleN_short.append('sT')
MCxsections.append(19.5545)
datasets.append('/ST_tW_top_5f_NoFullyHadronicDecays_13TeV-powheg_TuneCUETP8M1/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6_ext1-v1/MINIAODSIM')
NumSample.append('31'); sampleN_short.append('sT')
MCxsections.append(19.5545)
# W + Jets
datasets.append('/WJetsToLNu_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM')
NumSample.append('32'); sampleN_short.append('Wjet')
MCxsections.append(61526.7)
datasets.append('/WJetsToLNu_HT-100To200_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6_ext2-v1/MINIAODSIM')
NumSample.append('33'); sampleN_short.append('Wjet')
MCxsections.append(1627.45)
datasets.append('/WJetsToLNu_HT-200To400_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6_ext2-v1/MINIAODSIM')
NumSample.append('34'); sampleN_short.append('Wjet')
MCxsections.append(435.237)
datasets.append('/WJetsToLNu_HT-400To600_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6_ext1-v1/MINIAODSIM')
NumSample.append('35'); sampleN_short.append('Wjet')
MCxsections.append(59.181)
#FIXME
#datasets.append('/WJetsToLNu_HT-600To800_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6_ext1-v1/MINIAODSIM')
#NumSample.append('36'); sampleN_short.append('Wjet')### not available now
MCxsections.append(14.58)
datasets.append('/WJetsToLNu_HT-800To1200_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6_ext1-v1/MINIAODSIM')
NumSample.append('37'); sampleN_short.append('Wjet')
MCxsections.append(6.656)
datasets.append('/WJetsToLNu_HT-1200To2500_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6_ext1-v1/MINIAODSIM')
NumSample.append('38'); sampleN_short.append('Wjet')
MCxsections.append(1.608)
datasets.append('/WJetsToLNu_HT-2500ToInf_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6_ext1-v1/MINIAODSIM')
NumSample.append('39'); sampleN_short.append('Wjet')
MCxsections.append(0.0389)
# tt + V
datasets.append('/TTWJetsToQQ_TuneCUETP8M1_13TeV-amcatnloFXFX-madspin-pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM')
NumSample.append('40'); sampleN_short.append('ttV')
MCxsections.append(0.4062)
datasets.append('/TTWJetsToLNu_TuneCUETP8M1_13TeV-amcatnloFXFX-madspin-pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6_ext2-v1/MINIAODSIM')
NumSample.append('41'); sampleN_short.append('ttV')
MCxsections.append(0.2043)
datasets.append('/TTZToQQ_TuneCUETP8M1_13TeV-amcatnlo-pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/MINIAODSIM')
NumSample.append('42'); sampleN_short.append('ttV')
MCxsections.append(0.5297)
datasets.append('/TTZToLLNuNu_M-10_TuneCUETP8M1_13TeV-amcatnlo-pythia8/RunIISummer16MiniAODv2-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6_ext3-v1/MINIAODSIM')
NumSample.append('43'); sampleN_short.append('ttV')
MCxsections.append(0.2529)
alljobtypes = set(sampleN_short)
for job in alljobtypes:
localdirs[job] = []
for ijob, job in enumerate(datasets):
nsample = int(NumSample[ijob])
jobtype = sampleN_short[ijob]
dataname = ""
datadir = " "
#print "nsample ",nsample, " jobtype ",jobtype
if nsample < 0:
datadir = sampleN_short[ijob]
dataname = job
#print "real data nsample ",nsample, " datadir ",datadir
elif nsample > 0:
datadir = job.split('/')[1]
#print "MC nsample ",nsample, " datadir ",datadir, "MiniAOD dataset ",job.split('/')
#query = "dataset dataset=/%s/*/NANOAODSIM"%(datadir)
#pdata = os.popen("dasgoclient -limit=0 -query='{query}'".format(query = query))
#founddataset = False
#for line in pdata:
# #print "dataset ",line," datatype ",datadir
# if datadir in line:
# founddataset = True
# dataname = line[:-1]
#if not(founddataset):
# print "WARNING!!!!! no dataset found for ",datadir
localdirs[jobtype].append(os.path.join(fdatadir, datadir))
Nanodatasets.append("/DoubleEG/Run2016B-05Feb2018_ver1-v1/NANOAOD")
Nanodatasets.append("/DoubleEG/Run2016B-05Feb2018_ver2-v1/NANOAOD")
Nanodatasets.append("/DoubleEG/Run2016C-05Feb2018-v1/NANOAOD")
Nanodatasets.append("/DoubleEG/Run2016D-05Feb2018-v1/NANOAOD")
Nanodatasets.append("/DoubleEG/Run2016E-05Feb2018-v1/NANOAOD")
Nanodatasets.append("/DoubleEG/Run2016F-05Feb2018-v1/NANOAOD")
Nanodatasets.append("/DoubleEG/Run2016G-05Feb2018-v1/NANOAOD")
Nanodatasets.append("/DoubleEG/Run2016H-05Feb2018_ver2-v1/NANOAOD")
Nanodatasets.append("/DoubleEG/Run2016H-05Feb2018_ver3-v1/NANOAOD")
Nanodatasets.append("/DoubleMuon/Run2016B-05Feb2018_ver1-v1/NANOAOD")
Nanodatasets.append("/DoubleMuon/Run2016B-05Feb2018_ver2-v1/NANOAOD")
Nanodatasets.append("/DoubleMuon/Run2016C-05Feb2018-v1/NANOAOD")
Nanodatasets.append("/DoubleMuon/Run2016D-05Feb2018-v1/NANOAOD")
Nanodatasets.append("/DoubleMuon/Run2016E-05Feb2018-v1/NANOAOD")
Nanodatasets.append("/DoubleMuon/Run2016F-05Feb2018-v1/NANOAOD")
Nanodatasets.append("/DoubleMuon/Run2016G-05Feb2018-v1/NANOAOD")
Nanodatasets.append("/DoubleMuon/Run2016H-05Feb2018_ver2-v1/NANOAOD")
Nanodatasets.append("/DoubleMuon/Run2016H-05Feb2018_ver3-v1/NANOAOD")
Nanodatasets.append("/MuonEG/Run2016B-05Feb2018_ver1-v1/NANOAOD")
Nanodatasets.append("/MuonEG/Run2016B-05Feb2018_ver2-v1/NANOAOD")
Nanodatasets.append("/MuonEG/Run2016C-05Feb2018-v1/NANOAOD")
Nanodatasets.append("/MuonEG/Run2016D-05Feb2018-v1/NANOAOD")
Nanodatasets.append("/MuonEG/Run2016E-05Feb2018-v1/NANOAOD")
Nanodatasets.append("/MuonEG/Run2016F-05Feb2018-v1/NANOAOD")
Nanodatasets.append("/MuonEG/Run2016G-05Feb2018-v1/NANOAOD")
Nanodatasets.append("/MuonEG/Run2016H-05Feb2018_ver2-v1/NANOAOD")
Nanodatasets.append("/MuonEG/Run2016H-05Feb2018_ver3-v1/NANOAOD")
Nanodatasets.append("/GluGluToRadionToHHTo2B2VTo2L2Nu_M-260_narrow_13TeV-madgraph-v2/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2-v1/NANOAODSIM")
Nanodatasets.append("/GluGluToRadionToHHTo2B2VTo2L2Nu_M-270_narrow_13TeV-madgraph-v2/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2-v1/NANOAODSIM")
Nanodatasets.append("/GluGluToRadionToHHTo2B2VTo2L2Nu_M-300_narrow_13TeV-madgraph-v2/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2-v1/NANOAODSIM")
Nanodatasets.append("/GluGluToRadionToHHTo2B2VTo2L2Nu_M-350_narrow_13TeV-madgraph-v2/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2-v1/NANOAODSIM")
Nanodatasets.append("/GluGluToRadionToHHTo2B2VTo2L2Nu_M-400_narrow_13TeV-madgraph-v2/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2-v1/NANOAODSIM")
Nanodatasets.append("/GluGluToRadionToHHTo2B2VTo2L2Nu_M-450_narrow_13TeV-madgraph-v2/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2-v1/NANOAODSIM")
Nanodatasets.append("/GluGluToRadionToHHTo2B2VTo2L2Nu_M-500_narrow_13TeV-madgraph-v2/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2-v1/NANOAODSIM")
Nanodatasets.append("/GluGluToRadionToHHTo2B2VTo2L2Nu_M-550_narrow_13TeV-madgraph-v2/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2-v1/NANOAODSIM")
Nanodatasets.append("/GluGluToRadionToHHTo2B2VTo2L2Nu_M-600_narrow_13TeV-madgraph-v2/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2-v1/NANOAODSIM")
Nanodatasets.append("/GluGluToRadionToHHTo2B2VTo2L2Nu_M-650_narrow_13TeV-madgraph-v2/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2-v1/NANOAODSIM")
Nanodatasets.append("/GluGluToRadionToHHTo2B2VTo2L2Nu_M-750_narrow_13TeV-madgraph-v2/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2-v1/NANOAODSIM")
Nanodatasets.append("/GluGluToRadionToHHTo2B2VTo2L2Nu_M-800_narrow_13TeV-madgraph-v2/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2-v1/NANOAODSIM")
Nanodatasets.append("/GluGluToRadionToHHTo2B2VTo2L2Nu_M-900_narrow_13TeV-madgraph-v2/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2-v1/NANOAODSIM")
#TTbar
#Nanodatasets.append("/TTTo2L2Nu_TuneCP5_13TeV-powheg-pythia8/arizzi-RunIIFall17MiniAOD-94X-Nano01Fall17-e273b12d9f89d622a34e4bc98b05ee29/USER")
Nanodatasets.append('/TTTo2L2Nu_TuneCUETP8M2_ttHtranche3_13TeV-powheg-pythia8/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2-v1/NANOAODSIM')
# DY
Nanodatasets.append("/DYJetsToLL_M-10to50_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2-v1/NANOAODSIM")
Nanodatasets.append("/DYToLL_0J_13TeV-amcatnloFXFX-pythia8/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2_ext1-v1/NANOAODSIM")
Nanodatasets.append("/DYToLL_1J_13TeV-amcatnloFXFX-pythia8/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2_ext1-v1/NANOAODSIM")
Nanodatasets.append("/DYToLL_2J_13TeV-amcatnloFXFX-pythia8/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2_ext1-v1/NANOAODSIM")
# VV
Nanodatasets.append("/ZZTo2L2Q_13TeV_amcatnloFXFX_madspin_pythia8/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2-v1/NANOAODSIM")
Nanodatasets.append("/ZZTo2L2Nu_13TeV_powheg_pythia8/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2-v1/NANOAODSIM")
Nanodatasets.append("/ZZTo4L_13TeV_powheg_pythia8/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2-v1/NANOAODSIM")
#Nanodatasets.append("/WWToLNuQQ_aTGC_13TeV-madgraph-pythia8/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2-v1/NANOAODSIM")
Nanodatasets.append("/WZTo2L2Q_13TeV_amcatnloFXFX_madspin_pythia8/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2-v1/NANOAODSIM")
Nanodatasets.append("/WZTo1L1Nu2Q_13TeV_amcatnloFXFX_madspin_pythia8/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2-v1/NANOAODSIM")
Nanodatasets.append("/WZTo3LNu_TuneCUETP8M1_13TeV-powheg-pythia8/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2_ext1-v1/NANOAODSIM")
#sT
Nanodatasets.append("/ST_t-channel_top_4f_inclusiveDecays_13TeV-powhegV2-madspin-pythia8_TuneCUETP8M1/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2-v1/NANOAODSIM")
Nanodatasets.append("/ST_t-channel_antitop_4f_inclusiveDecays_13TeV-powhegV2-madspin-pythia8_TuneCUETP8M1/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2-v1/NANOAODSIM")
Nanodatasets.append("/ST_s-channel_4f_leptonDecays_13TeV-amcatnlo-pythia8_TuneCUETP8M1/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2-v1/NANOAODSIM")
Nanodatasets.append("/ST_tW_antitop_5f_NoFullyHadronicDecays_13TeV-powheg_TuneCUETP8M1/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2-v1/NANOAODSIM")
Nanodatasets.append("/ST_tW_top_5f_NoFullyHadronicDecays_13TeV-powheg_TuneCUETP8M1/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2-v1/NANOAODSIM")
#W+jets
Nanodatasets.append("/WJetsToLNu_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2_ext2-v1/NANOAODSIM")
Nanodatasets.append("/WJetsToLNu_HT-100To200_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2_ext2-v1/NANOAODSIM")
Nanodatasets.append("/WJetsToLNu_HT-200To400_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2_ext2-v1/NANOAODSIM")
Nanodatasets.append("/WJetsToLNu_HT-400To600_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2_ext1-v1/NANOAODSIM")
Nanodatasets.append("/WJetsToLNu_HT-800To1200_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2_ext1-v1/NANOAODSIM")
Nanodatasets.append("/WJetsToLNu_HT-1200To2500_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2-v1/NANOAODSIM")
Nanodatasets.append("/WJetsToLNu_HT-2500ToInf_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2_ext1-v1/NANOAODSIM")
# tt + V
Nanodatasets.append("/TTWJetsToQQ_TuneCUETP8M1_13TeV-amcatnloFXFX-madspin-pythia8/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2-v1/NANOAODSIM")
Nanodatasets.append("/TTWJetsToLNu_TuneCUETP8M1_13TeV-amcatnloFXFX-madspin-pythia8/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2_ext2-v1/NANOAODSIM")
Nanodatasets.append("/TTZToQQ_TuneCUETP8M1_13TeV-amcatnlo-pythia8/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2-v1/NANOAODSIM")
Nanodatasets.append("/TTZToLLNuNu_M-10_TuneCUETP8M1_13TeV-amcatnlo-pythia8/RunIISummer16NanoAOD-PUMoriond17_05Feb2018_94X_mcRun2_asymptotic_v2_ext3-v1/NANOAODSIM")
outAnalist = {}
outAnadir = "/fdata/hepx/store/user/taohuang/HHNtuple_20180328_fixedleptonDZeff/"
for i,datasetname in enumerate( Nanodatasets ):
sampleName = sampleN_short[i]
if NumSample[i] < 0:
sampleName = "Data"
outAnafile = os.path.join(outAnadir, Nanodatasets[i].split('/')[1])
if hasattr(outAnalist, sampleName):
outAnalist[sampleName].append(outAnafile)
else:
outAnalist[sampleName] = []
outAnalist[sampleName].append(outAnafile)
dataintxt = open("2016MCSamplelist.txt","w+")
for dataset in datasets:
dataintxt.write(dataset+"\n")
dataintxt.close()
|
7,370 | 975b2f3443e19f910c71f872484350aef9f09dd2 | class Solution:
def minimumDeviation(self, nums: List[int]) -> int:
hq, left, right, res = [], inf, 0, inf
for num in nums:
if num % 2:
num = num * 2
heapq.heappush(hq, -num)
left = min(left, num)
while True:
right = -heapq.heappop(hq)
if right - left < res:
res = right - left
if right % 2 == 0:
heapq.heappush(hq, -right // 2)
left = min(left, right // 2)
else:
break
return res
|
7,371 | 452d5d98b6c0b82a1f4ec18f29d9710a8c0f4dc9 | """
This handy script will download all wallpapears from simpledesktops.com
Requirements
============
BeautifulSoup - http://www.crummy.com/software/BeautifulSoup/
Python-Requests - http://docs.python-requests.org/en/latest/index.html
Usage
=====
cd /path/to/the/script/
python simpledesktops.py
"""
from StringIO import StringIO
from bs4 import BeautifulSoup
import requests
import os
try:
os.mkdir('walls')
except OSError:
pass
page = 1
while True:
page_request = requests.get('http://simpledesktops.com/browse/%s/' % page)
if page_request.status_code != 200:
print 'page %s does not exist' % page
break
html = BeautifulSoup(page_request.text)
images = html.findAll('img')
for image in images:
img_src = image['src']
if 'static.simpledesktops.com/desktops/' in img_src:
full_size_img = img_src.replace('.295x184_q100.png', '')
img_name = full_size_img.split('/')[-1]
img_request = requests.get(full_size_img)
img_buffer = StringIO(img_request.content)
img_file = open('walls/%s' % img_name, 'wb')
img_file.write(img_buffer.getvalue())
img_file.close()
print '%s downloaded' % img_name
print '\n================'
print 'page %s finished' % page
print '================\n'
page += 1 |
7,372 | 7c3569c43d27ba605c0dba420690e18d7f849965 | from django import forms
from .models import User,Profile
from django.contrib.auth.forms import UserCreationForm
class ProfileForm(forms.ModelForm):
''' Form for the profile '''
class Meta:
model = Profile
exclude = ('user',) ## we will create the user with the signals
class SignUpForm(UserCreationForm):
''' Sign up form fetching form the User creation form
and the email and password is necessary not the user '''
class Meta:
model = User
fields = ('email','password1','password2')
|
7,373 | 4dfdbc692858a627248cbe47d19b43c2a27ec70e | #!/usr/bin/env python
# Core Library modules
import os
# Third party modules
import nose
# First party modules
import lumixmaptool.copy as copy
# Tests
def get_parser_test():
"""Check if the evaluation model returns a parser object."""
copy.get_parser()
def parse_mapdata_test():
current_folder = os.path.dirname(os.path.realpath(__file__))
misc_folder = os.path.join(current_folder, "misc")
maplistdata_path = os.path.join(misc_folder, "MapList.dat")
result = copy.parse_mapdata(maplistdata_path)
expected = {
"num1": "00010001",
"num2": "00010001",
"regions": {
1: [
"BACK/B0000035.DFT",
"BACK/B0000036.DFT",
"BACK/B0000044.DFT",
"BACK/B0000045.DFT",
"BACK/B0000053.DFT",
"BACK/B0000054.DFT",
"NAME/N0000035.DFT",
"NAME/N0000036.DFT",
"NAME/N0000044.DFT",
"NAME/N0000045.DFT",
"NAME/N0000053.DFT",
"NAME/N0000054.DFT",
"POI/P0000035.DFT",
"POI/P0000036.DFT",
"POI/P0000044.DFT",
"POI/P0000045.DFT",
"POI/P0000053.DFT",
"POI/P0000054.DFT",
],
2: [
"BACK/B0000024.DFT",
"BACK/B0000025.DFT",
"BACK/B0000026.DFT",
"BACK/B0000027.DFT",
"BACK/B0000033.DFT",
"BACK/B0000034.DFT",
"BACK/B0000035.DFT",
"BACK/B0000036.DFT",
"BACK/B0000042.DFT",
"BACK/B0000043.DFT",
"BACK/B0000044.DFT",
"BACK/B0000045.DFT",
"NAME/N0000024.DFT",
"NAME/N0000025.DFT",
"NAME/N0000026.DFT",
"NAME/N0000027.DFT",
"NAME/N0000033.DFT",
"NAME/N0000034.DFT",
"NAME/N0000035.DFT",
"NAME/N0000036.DFT",
"NAME/N0000042.DFT",
"NAME/N0000043.DFT",
"NAME/N0000044.DFT",
"NAME/N0000045.DFT",
"POI/P0000024.DFT",
"POI/P0000025.DFT",
"POI/P0000026.DFT",
"POI/P0000027.DFT",
"POI/P0000033.DFT",
"POI/P0000034.DFT",
"POI/P0000035.DFT",
"POI/P0000036.DFT",
"POI/P0000042.DFT",
"POI/P0000043.DFT",
"POI/P0000044.DFT",
"POI/P0000045.DFT",
],
3: [
"BACK/B0000001.DFT",
"BACK/B0000008.DFT",
"BACK/B0000009.DFT",
"BACK/B0000010.DFT",
"BACK/B0000017.DFT",
"BACK/B0000018.DFT",
"BACK/B0000019.DFT",
"BACK/B0000026.DFT",
"BACK/B0000027.DFT",
"NAME/N0000001.DFT",
"NAME/N0000008.DFT",
"NAME/N0000009.DFT",
"NAME/N0000010.DFT",
"NAME/N0000017.DFT",
"NAME/N0000018.DFT",
"NAME/N0000019.DFT",
"NAME/N0000026.DFT",
"NAME/N0000027.DFT",
"POI/P0000017.DFT",
"POI/P0000018.DFT",
"POI/P0000019.DFT",
"POI/P0000026.DFT",
"POI/P0000027.DFT",
],
4: [
"BACK/B0000019.DFT",
"BACK/B0000020.DFT",
"BACK/B0000021.DFT",
"BACK/B0000022.DFT",
"BACK/B0000027.DFT",
"BACK/B0000028.DFT",
"BACK/B0000029.DFT",
"BACK/B0000030.DFT",
"BACK/B0000031.DFT",
"BACK/B0000036.DFT",
"BACK/B0000037.DFT",
"BACK/B0000038.DFT",
"BACK/B0000039.DFT",
"BACK/B0000040.DFT",
"BACK/B0000045.DFT",
"BACK/B0000046.DFT",
"BACK/B0000047.DFT",
"BACK/B0000048.DFT",
"BACK/B0000049.DFT",
"BACK/B0000054.DFT",
"NAME/N0000019.DFT",
"NAME/N0000020.DFT",
"NAME/N0000021.DFT",
"NAME/N0000022.DFT",
"NAME/N0000027.DFT",
"NAME/N0000028.DFT",
"NAME/N0000029.DFT",
"NAME/N0000030.DFT",
"NAME/N0000031.DFT",
"NAME/N0000036.DFT",
"NAME/N0000037.DFT",
"NAME/N0000038.DFT",
"NAME/N0000039.DFT",
"NAME/N0000040.DFT",
"NAME/N0000045.DFT",
"NAME/N0000046.DFT",
"NAME/N0000047.DFT",
"NAME/N0000048.DFT",
"NAME/N0000049.DFT",
"NAME/N0000054.DFT",
"POI/P0000019.DFT",
"POI/P0000020.DFT",
"POI/P0000021.DFT",
"POI/P0000022.DFT",
"POI/P0000027.DFT",
"POI/P0000028.DFT",
"POI/P0000029.DFT",
"POI/P0000030.DFT",
"POI/P0000031.DFT",
"POI/P0000036.DFT",
"POI/P0000037.DFT",
"POI/P0000038.DFT",
"POI/P0000039.DFT",
"POI/P0000040.DFT",
"POI/P0000045.DFT",
"POI/P0000046.DFT",
"POI/P0000047.DFT",
"POI/P0000048.DFT",
"POI/P0000049.DFT",
"POI/P0000054.DFT",
],
5: [
"BACK/B0000002.DFT",
"BACK/B0000003.DFT",
"BACK/B0000004.DFT",
"BACK/B0000011.DFT",
"BACK/B0000012.DFT",
"BACK/B0000013.DFT",
"BACK/B0000020.DFT",
"BACK/B0000021.DFT",
"BACK/B0000022.DFT",
"BACK/B0000029.DFT",
"BACK/B0000030.DFT",
"BACK/B0000031.DFT",
"NAME/N0000002.DFT",
"NAME/N0000003.DFT",
"NAME/N0000004.DFT",
"NAME/N0000011.DFT",
"NAME/N0000012.DFT",
"NAME/N0000013.DFT",
"NAME/N0000020.DFT",
"NAME/N0000021.DFT",
"NAME/N0000022.DFT",
"NAME/N0000029.DFT",
"NAME/N0000030.DFT",
"NAME/N0000031.DFT",
"POI/P0000003.DFT",
"POI/P0000011.DFT",
"POI/P0000012.DFT",
"POI/P0000013.DFT",
"POI/P0000020.DFT",
"POI/P0000021.DFT",
"POI/P0000022.DFT",
"POI/P0000029.DFT",
"POI/P0000030.DFT",
"POI/P0000031.DFT",
],
6: [
"BACK/B0000040.DFT",
"BACK/B0000041.DFT",
"BACK/B0000042.DFT",
"BACK/B0000049.DFT",
"BACK/B0000050.DFT",
"BACK/B0000051.DFT",
"NAME/N0000040.DFT",
"NAME/N0000041.DFT",
"NAME/N0000042.DFT",
"NAME/N0000049.DFT",
"NAME/N0000050.DFT",
"NAME/N0000051.DFT",
"POI/P0000040.DFT",
"POI/P0000041.DFT",
"POI/P0000042.DFT",
"POI/P0000049.DFT",
"POI/P0000050.DFT",
"POI/P0000051.DFT",
],
7: [
"BACK/B0000032.DFT",
"BACK/B0000033.DFT",
"BACK/B0000034.DFT",
"BACK/B0000041.DFT",
"BACK/B0000042.DFT",
"BACK/B0000043.DFT",
"BACK/B0000050.DFT",
"BACK/B0000051.DFT",
"BACK/B0000052.DFT",
"NAME/N0000032.DFT",
"NAME/N0000033.DFT",
"NAME/N0000034.DFT",
"NAME/N0000041.DFT",
"NAME/N0000042.DFT",
"NAME/N0000043.DFT",
"NAME/N0000050.DFT",
"NAME/N0000051.DFT",
"NAME/N0000052.DFT",
"POI/P0000032.DFT",
"POI/P0000033.DFT",
"POI/P0000034.DFT",
"POI/P0000041.DFT",
"POI/P0000042.DFT",
"POI/P0000043.DFT",
"POI/P0000050.DFT",
"POI/P0000051.DFT",
"POI/P0000052.DFT",
],
8: [
"BACK/B0000031.DFT",
"BACK/B0000032.DFT",
"BACK/B0000033.DFT",
"BACK/B0000040.DFT",
"BACK/B0000041.DFT",
"BACK/B0000042.DFT",
"BACK/B0000049.DFT",
"BACK/B0000050.DFT",
"BACK/B0000051.DFT",
"NAME/N0000031.DFT",
"NAME/N0000032.DFT",
"NAME/N0000033.DFT",
"NAME/N0000040.DFT",
"NAME/N0000041.DFT",
"NAME/N0000042.DFT",
"NAME/N0000049.DFT",
"NAME/N0000050.DFT",
"NAME/N0000051.DFT",
"POI/P0000031.DFT",
"POI/P0000032.DFT",
"POI/P0000033.DFT",
"POI/P0000040.DFT",
"POI/P0000041.DFT",
"POI/P0000042.DFT",
"POI/P0000049.DFT",
"POI/P0000050.DFT",
"POI/P0000051.DFT",
],
9: [
"BACK/B0000005.DFT",
"BACK/B0000006.DFT",
"BACK/B0000007.DFT",
"BACK/B0000014.DFT",
"BACK/B0000015.DFT",
"BACK/B0000016.DFT",
"BACK/B0000023.DFT",
"BACK/B0000024.DFT",
"BACK/B0000025.DFT",
"BACK/B0000032.DFT",
"BACK/B0000033.DFT",
"BACK/B0000034.DFT",
"BACK/B0000041.DFT",
"BACK/B0000042.DFT",
"BACK/B0000043.DFT",
"NAME/N0000005.DFT",
"NAME/N0000006.DFT",
"NAME/N0000007.DFT",
"NAME/N0000014.DFT",
"NAME/N0000015.DFT",
"NAME/N0000016.DFT",
"NAME/N0000023.DFT",
"NAME/N0000024.DFT",
"NAME/N0000025.DFT",
"NAME/N0000032.DFT",
"NAME/N0000033.DFT",
"NAME/N0000034.DFT",
"NAME/N0000041.DFT",
"NAME/N0000042.DFT",
"NAME/N0000043.DFT",
"POI/P0000014.DFT",
"POI/P0000015.DFT",
"POI/P0000023.DFT",
"POI/P0000024.DFT",
"POI/P0000025.DFT",
"POI/P0000032.DFT",
"POI/P0000033.DFT",
"POI/P0000034.DFT",
"POI/P0000041.DFT",
"POI/P0000042.DFT",
"POI/P0000043.DFT",
],
10: [
"BACK/B0000037.DFT",
"BACK/B0000041.DFT",
"BACK/B0000042.DFT",
"BACK/B0000043.DFT",
"BACK/B0000044.DFT",
"BACK/B0000045.DFT",
"BACK/B0000046.DFT",
"BACK/B0000050.DFT",
"BACK/B0000051.DFT",
"BACK/B0000052.DFT",
"BACK/B0000053.DFT",
"BACK/B0000054.DFT",
"NAME/N0000037.DFT",
"NAME/N0000041.DFT",
"NAME/N0000042.DFT",
"NAME/N0000043.DFT",
"NAME/N0000044.DFT",
"NAME/N0000045.DFT",
"NAME/N0000046.DFT",
"NAME/N0000050.DFT",
"NAME/N0000051.DFT",
"NAME/N0000052.DFT",
"NAME/N0000053.DFT",
"NAME/N0000054.DFT",
"POI/P0000037.DFT",
"POI/P0000041.DFT",
"POI/P0000042.DFT",
"POI/P0000043.DFT",
"POI/P0000044.DFT",
"POI/P0000045.DFT",
"POI/P0000046.DFT",
"POI/P0000050.DFT",
"POI/P0000051.DFT",
"POI/P0000052.DFT",
"POI/P0000053.DFT",
"POI/P0000054.DFT",
],
},
}
nose.tools.assert_equal(result, expected)
|
7,374 | f15bb4ab93ecb2689bf74687852e60dfa98caea9 | """Project agnostic helper functions that could be migrated to and external lib.
"""
|
7,375 | 0259fddbe3ce030030a508ce7118a6a03930aa51 | from flask import Flask
import os
app = Flask(__name__)
@app.route("/healthz")
def healthz():
return "ok"
@app.route("/alive")
def alive():
return "ok"
@app.route("/hello")
# def healthz(): # introduces application crash bug
def hello():
myhost = os.uname()[1]
body = ("V1 - Hello World! - %s" % myhost)
# body = ("V2 - Hello World! - %s" % myhost)
return body
if __name__ == "__main__":
from waitress import serve
serve(app, host="0.0.0.0", port=80)
|
7,376 | 5c643dfce9cf7a9f774957ff4819d3be8ac4f1da | #list,for replacing element we use {a[0='']}:for adding element we use {append()}
a=['somesh','aakash','sarika','datta','rudra','4mridula']
a[2] = 'nandini'
a.append('sarika')
print(a[2])
print(a)
|
7,377 | 7a920b3609bb29cd26b159b48290fa6978839416 | def bullets(chunks):
print("bullets")
final_string = "Your list in latex can be created with the following command: \n"
final_string += "> \\begin{itemize} \n"
for e in chunks:
print(final_string)
final_string += f"> \item {e} \n"
final_string += "> \end{itemize}"
return final_string
def numbers(chunks):
print("numbers")
final_string = "Your list in latex can be created with the following command: \n"
final_string += "> \\begin{enumerate} \n"
for e in chunks:
print(final_string)
final_string += f"> \item {e} \n"
final_string += "> \end{enumerate}"
return final_string
def simple_headline(chunks):
print("simple headline")
final_string = "Your list in latex can be created with the following command: \n"
final_string += "> \\begin{description} \n"
for e in chunks:
print(final_string)
final_string += "> \item["+ e + "]\hfill \\\ \n"
final_string += "> \end{description}"
return final_string |
7,378 | f8e287abc7e1a2af005aa93c25d95ce770e29bf9 | from odoo import models, fields, api
from datetime import datetime, timedelta
from odoo import exceptions
import logging
import math
_logger = logging.getLogger(__name__)
class BillOfLading(models.Model):
_name = 'freight.bol'
_description = 'Bill Of Lading'
_order = 'date_of_issue desc, write_date desc'
_rec_name = 'bol_no'
_inherit = ['mail.thread', 'mail.activity.mixin']
# Header
bol_status = fields.Selection([('01', 'Draft'), ('02', 'Original'), ('03', 'Surrender'), ('04', 'Telex Release')],
string="B/L Status", default="01", copy=False, track_visibility='onchange', store=True)
service_type = fields.Selection([('ocean', 'Ocean'), ('air', 'Air'), ('land', 'Land')], string="Shipment Mode",
default="ocean", track_visibility='onchange')
direction = fields.Selection([('import', 'Import'), ('export', 'Export')], string="Direction", default="export",
track_visibility='onchange')
cargo_type = fields.Selection([('fcl', 'FCL'), ('lcl', 'LCL')], string='Cargo Type', default="fcl",
track_visibility='onchange')
type_of_movement = fields.Selection([('cy-cy', 'CY/CY'), ('cy-cfs', 'CY/CFS'), ('cfs-cfs', 'CFS/CFS'), ('cfs-cy', 'CFS/CY')],
string='Type Of Movement', track_visibility='onchange')
booking_ref = fields.Many2one('freight.booking', string='Booking Job Ref', track_visibility='onchange',
copy=False, index=True)
no_of_original_bl = fields.Selection([('0', '0'), ('1', '1'), ('3', '3')], string="No Of original B/L",
default="0", track_visibility='onchange')
doc_form_no = fields.Char(string='Doc. Form No.', track_visibility='onchange')
service_contract_no = fields.Char(string='Service Contract No', track_visibility='onchange')
bol_no = fields.Char(string='HBL No', copy=False, readonly=True, index=True)
carrier_booking_no = fields.Char(string='Carrier Booking No', copy=False, readonly=True)
date_of_issue = fields.Date(string='Shipment Date', copy=False, default=datetime.now().date(),
track_visibility='onchange', index=True)
date_laden_on_board = fields.Date(string='Shipped on Board Date')
place_of_issue = fields.Char(string='Place of Issue', track_visibility='onchange')
export_reference = fields.Char(string='Export Reference', track_visibility='onchange')
fa_reference = fields.Char(string='Forwarding Agent and References', track_visibility='onchange')
point_country_origin = fields.Text(string='Point and Country of Origin', track_visibility='onchange')
term = fields.Char(string='Term', track_visibility='onchange', help='eg, CY-CY')
commodity = fields.Many2one('product.product', string='Commodity', track_visibility='onchange')
commodity1 = fields.Many2one('freight.commodity1', string='Commodity', track_visibility='onchange')
shipper_load = fields.Boolean('Shipper Load, Seal and Count')
analytic_account_id = fields.Many2one('account.analytic.account', string="Analytic Account",
track_visibility='always', copy=False)
@api.multi
def _get_default_commodity_category(self):
commodity_lines = self.env['freight.product.category'].search([('type', '=ilike', 'commodity')])
for commodity_line in commodity_lines:
_logger.warning('_get_default_commodity_category=' + str(commodity_line.product_category))
return commodity_line.product_category
commodity_category_id = fields.Many2one('product.category', string="Commodity Product Id",
default=_get_default_commodity_category)
# Invoice Status
invoice_status = fields.Selection([('01', 'New'),
('02', 'Partially Invoiced'),
('03', 'Fully Invoiced')],
string="Invoice Status", default="01", copy=False,
track_visibility='onchange')
invoice_paid_status = fields.Selection([('01', 'New'),
('02', 'Partially Paid'),
('03', 'Fully Paid')],
string="Invoice Paid Status", default="01", copy=False,
track_visibility='onchange')
# Party Info
customer_name = fields.Many2one('res.partner', string='Customer Name', track_visibility='onchange')
contact_name = fields.Many2one('res.partner', string='Contact Name', track_visibility='onchange')
shipper = fields.Text(string='Shipper', track_visibility='onchange',
help="The Party who shipped the freight, eg Exporter")
notify_party = fields.Text(string='Notify Party',
help="The Party who will be notified by Liner when the freight arrived",
track_visibility='onchange')
carrier_c = fields.Many2one('res.partner', string="Carrier")
consignee = fields.Text(string='Consignee', help="The Party who received the freight", track_visibility='onchange')
routing_instruction = fields.Text(string='For Delivery Of Goods Please Apply To', track_visibility='onchange')
delivery_contact = fields.Text(string='Contact for Delivery', help="Contact information for delivery of goods",
track_visibility='onchange')
unstuff_at = fields.Char(string='Unstuff At', track_visibility='onchange')
# Shipment Info
voyage_no = fields.Char(string='Voyage No', track_visibility='onchange')
vessel = fields.Char(string='Vessel Name', track_visibility='onchange')
manifest_no = fields.Char(string='Manifest No', track_visibility='onchange')
port_of_loading_input = fields.Char(string='Port of Loading', track_visibility='onchange')
port_of_discharge_input = fields.Char(string='Port of Discharge', track_visibility='onchange')
port_of_discharge_eta = fields.Date(string='Loading ETA', track_visibility='onchange')
place_of_delivery = fields.Char(string='Final Destination', track_visibility='onchange')
place_of_receipt = fields.Char(string='Place of Receipt', track_visibility='onchange')
pre_carriage_by = fields.Char(string='Pre-Carriage By', track_visibility='onchange')
# Remark
note = fields.Text(string='Remarks', track_visibility='onchange')
# System Info
sales_person = fields.Many2one('res.users', string="Salesperson", track_visibility='onchange')
company_id = fields.Many2one('res.company', 'Company', required=True, index=True, readonly=1,
default=lambda self: self.env.user.company_id.id)
# analytic_account_id = fields.Many2one('account.analytic.account', string="Analytic Account",
# track_visibility='always', copy=False)
# Line Item
cargo_line_ids = fields.One2many('freight.bol.cargo', 'cargo_line', string="Cargo Line",
copy=True, auto_join=True, track_visibility='always')
charge_line_ids = fields.One2many('freight.bol.charge', 'charge_line', string="Charge Line",
copy=True, auto_join=True, track_visibility='always')
cost_profit_ids = fields.One2many('freight.bol.cost.profit', 'bol_id', string="Cost & Profit",
copy=True, auto_join=True, track_visibility='always')
# Not Used
invoice_count = fields.Integer(string='Invoice Count', compute='_get_invoiced_count', copy=False)
vendor_bill_count = fields.Integer(string='Vendor Bill Count', compute='_get_bill_count', copy=False)
si_count = fields.Integer(string='SI Count', compute='_get_si_count', copy=False)
shipper_c = fields.Many2one('res.partner', string='Shipper')
consignee_c = fields.Many2one('res.partner', string='Consignee Name')
notify_party_c = fields.Many2one('res.partner', string='Notify Party')
total_no_of_packages_words = fields.Char(string='Total Packages', track_visibility='onchange',
help='Total no of packages or container in Words')
lines_description = fields.Integer()
line_description1 = fields.Text()
line_description2 = fields.Text()
@api.model
def create(self, vals):
vals['bol_no'] = self.env['ir.sequence'].next_by_code('hbl')
res = super(BillOfLading, self).create(vals)
return res
@api.multi
def name_get(self):
result = []
for bol in self:
name = str(bol.bol_no)
result.append((bol.id, name))
return result
@api.multi
def action_send_bl(self):
self.ensure_one()
ir_model_data = self.env['ir.model.data']
try:
template_id = \
ir_model_data.get_object_reference('sci_goexcel_freight', 'email_template_bol')[1]
except ValueError:
template_id = False
try:
compose_form_id = ir_model_data.get_object_reference('mail', 'email_compose_message_wizard_form')[1]
except ValueError:
compose_form_id = False
ctx = {
'default_model': 'freight.bol',
'default_res_id': self.ids[0],
'default_use_template': bool(template_id),
'default_template_id': template_id,
'default_composition_mode': 'comment',
'mark_so_as_sent': True,
'custom_layout': "mail.mail_notification_light",
# 'proforma': self.env.context.get('proforma', False),
'force_email': True
}
# base_url = self.env['ir.config_parameter'].sudo().get_param('web.base.url')
# ctx['action_url'] = "{}/web?db={}".format(base_url, self.env.cr.dbname)
return {
'type': 'ir.actions.act_window',
'view_type': 'form',
'view_mode': 'form',
'res_model': 'mail.compose.message',
'views': [(compose_form_id, 'form')],
'view_id': compose_form_id,
'target': 'new',
'context': ctx,
}
@api.multi
def action_invoice(self):
self.ensure_one()
view = self.env.ref('sci_goexcel_freight.invoice_view_form')
return {
'name': 'Create Invoice',
'type': 'ir.actions.act_window',
'view_type': 'form',
'view_mode': 'form',
'res_model': 'invoice.wizard',
'views': [(view.id, 'form')],
'view_id': view.id,
'target': 'new',
'context': dict(bl_id=self.id),
}
@api.multi
def action_create_vendor_bill(self):
# only lines with vendor
vendor_po = self.cost_profit_ids.filtered(lambda c: c.vendor_id)
po_lines = vendor_po.sorted(key=lambda p: p.vendor_id.id)
vendor_count = False
vendor_id = False
if not self.analytic_account_id:
values = {
'name': '%s' % self.booking_ref.booking_no,
'partner_id': self.booking_ref.customer_name.id,
'code': self.bol_no,
'company_id': self.booking_ref.company_id.id,
}
analytic_account = self.env['account.analytic.account'].sudo().create(values)
self.booking_ref.write({'analytic_account_id': analytic_account.id})
self.write({'analytic_account_id': analytic_account.id})
for line in po_lines:
if line.vendor_id != vendor_id:
vb = self.env['account.invoice']
vendor_count = True
vendor_id = line.vendor_id
value = []
vendor_bill_created = []
filtered_vb_lines = po_lines.filtered(lambda r: r.vendor_id == vendor_id)
for vb_line in filtered_vb_lines:
if not vb_line.billed:
account_id = False
price_after_converted = vb_line.cost_price * vb_line.cost_currency_rate
if vb_line.product_id.property_account_expense_id:
account_id = vb_line.product_id.property_account_expense_id
elif vb_line.product_id.categ_id.property_account_expense_categ_id:
account_id = vb_line.product_id.categ_id.property_account_expense_categ_id
value.append([0, 0, {
# 'invoice_id': vendor_bill.id or False,
'account_id': account_id.id or False,
'name': vb_line.product_id.name or '',
'product_id': vb_line.product_id.id or False,
'quantity': vb_line.cost_qty or 0.0,
'uom_id': vb_line.uom_id.id or False,
'price_unit': price_after_converted or 0.0,
'account_analytic_id': self.analytic_account_id.id,
'bl_line_id': vb_line.id,
}])
vendor_bill_created.append(vb_line)
vb_line.billed = True
# print('vendor_id=' + vendor_id.name)
if value:
vendor_bill_id = vb.create({
'type': 'in_invoice',
'invoice_line_ids': value,
'default_currency_id': self.env.user.company_id.currency_id.id,
'company_id': self.company_id.id,
'date_invoice': fields.Date.context_today(self),
'origin': self.bol_no,
'partner_id': vendor_id.id,
'account_id': vb_line.vendor_id.property_account_payable_id.id or False,
'freight_booking': self.booking_ref.id,
})
for new_vendor_bill in vendor_bill_created:
new_vendor_bill.vendor_bill_id = vendor_bill_id.id
if vendor_count is False:
raise exceptions.ValidationError('No Vendor in Cost & Profit!!!')
def action_copy_to_booking(self):
booking = self.env['freight.booking'].search([('id', '=', self.booking_ref.id),])
booking_val = {
'cargo_type': self.cargo_type or False,
'shipper_address_input': self.shipper,
'consignee_address_input': self.consignee,
'notify_party_address_input': self.notify_party,
'carrier_booking_no' : self.carrier_booking_no or False,
'voyage_no': self.voyage_no,
'port_of_loading_input': self.port_of_loading_input,
'port_of_discharge_input': self.port_of_discharge_input,
'place_of_delivery': self.place_of_delivery,
'note': self.note,
'bol_status': self.bol_status,
'no_of_original_bl': self.no_of_original_bl,
'carrier': self.carrier_c.id,
}
booking.sudo().write(booking_val)
for booking_line in booking.operation_line_ids:
booking_line.sudo().unlink()
for booking_line in booking.operation_line_ids2:
booking_line.sudo().unlink()
for line in self.cargo_line_ids:
if self.cargo_type == 'fcl':
if line.container_product_name:
operation_line_obj = self.env['freight.operations.line']
op_line = operation_line_obj.create({
'operation_id': booking.id,
'container_no': line.container_no or '',
'container_product_id': line.container_product_id.id or False,
'seal_no': line.seal_no or '',
'container_product_name': line.container_product_name or '',
'packages_no': line.packages_no_value or '',
'packages_no_uom': line.packages_no_uom.id,
'exp_net_weight': line.exp_net_weight or '',
'exp_gross_weight': line.exp_gross_weight or '',
'dim_length': line.dim_length or '',
'dim_width': line.dim_width or '',
'dim_height': line.dim_height or '',
'exp_vol': line.exp_vol or '',
'remark': line.marks or '',
})
booking.operation_line_ids = op_line
else:
if line.container_product_name:
operation_line_obj = self.env['freight.operations.line2']
op_line = operation_line_obj.create({
'operation_id2': booking.id,
'container_no': line.container_no or '',
'container_product_id': line.container_product_id.id or False,
'seal_no': line.seal_no or '',
'container_product_name': line.container_product_name or '',
'packages_no': line.packages_no_value or '',
'packages_no_uom': line.packages_no_uom.id,
'exp_net_weight': line.exp_net_weight or '',
'exp_gross_weight': line.exp_gross_weight or '',
'dim_length': line.dim_length or '',
'dim_width': line.dim_width or '',
'dim_height': line.dim_height or '',
'exp_vol': line.exp_vol or '',
'shipping_mark': line.marks or '',
})
booking.operation_line_ids2 = op_line
def action_copy_from_booking(self):
booking = self.env['freight.booking'].search([('id', '=', self.booking_ref.id)])
for line in booking.cost_profit_ids:
operation_line_obj = self.env['freight.bol.cost.profit']
op_line = operation_line_obj.create({
'bol_id': self.id,
'product_id': line.product_id.id or False,
'product_name': line.product_name or '',
'profit_qty': line.profit_qty or 0,
'list_price': line.list_price or 0,
'profit_amount': line.profit_amount or 0,
'profit_currency': line.profit_currency.id or False,
'profit_currency_rate': line.profit_currency_rate or 0,
'cost_qty': line.cost_qty or 0,
'cost_price': line.cost_price or 0,
'cost_amount': line.cost_amount or 0,
'vendor_id': line.vendor_id.id or False,
'cost_currency': line.cost_currency.id or False,
'cost_currency_rate': line.cost_currency_rate or 0,
})
def action_create_si(self):
si_obj = self.env['freight.website.si']
si_val = {
'si_status': '01',
'carrier': self.carrier_c.id or False,
'direction': self.direction or False,
'cargo_type': self.cargo_type or False,
'service_type': self.service_type or False,
'customer_name': self.customer_name.id or False,
'shipper': self.shipper,
'consignee': self.consignee,
'notify_party': self.notify_party,
'carrier_booking_ref': self.carrier_booking_no,
'voyage_no': self.voyage_no,
'port_of_loading_input': self.port_of_loading_input,
'port_of_discharge_input': self.port_of_discharge_input,
'place_of_delivery': self.place_of_delivery,
'bl_ref': self.id,
}
si = si_obj.create(si_val)
if self.cargo_type == 'fcl':
container_line = self.cargo_line_ids
si_line_obj = self.env['freight.website.si.fcl']
for line in container_line:
if line.container_product_id or line.container_no:
si_line = si_line_obj.create({
'container_product_id': line.container_product_id.id or False,
'container_product_name': line.container_product_name or False,
'fcl_line': si.id or '',
'container_no': line.container_no or '',
'packages_no': line.packages_no_value or 0.0,
'packages_no_uom': line.packages_no_uom.id,
'exp_gross_weight': line.exp_gross_weight or 0.0,
'exp_vol': line.exp_vol or 0.0,
})
si.write({'fcl_line_ids': si_line or False})
else:
container_line = self.cargo_line_ids
si_line_obj = self.env['freight.website.si.lcl']
for line in container_line:
if line.container_product_id or line.container_no:
si_line = si_line_obj.create({
'container_product_name': line.container_product_name or False,
#'container_product_id': line.container_commodity_id.id or False,
'lcl_line': si.id or '',
'container_no': line.container_no or '',
'packages_no': line.packages_no_value or 0.0,
'packages_no_uom': line.packages_no_uom.id,
'exp_gross_weight': line.exp_gross_weight or 0.0,
'exp_net_weight': line.exp_net_weight or 0.0,
'exp_vol': line.exp_vol or 0.0,
# 'remark_line': line.remark or '',
})
si.write({'lcl_line_ids': si_line or False})
@api.multi
def operation_invoices(self):
"""Show Invoice for specific Freight Operation smart Button."""
for operation in self:
invoices = self.env['account.invoice'].search([
('freight_hbl', '=', operation.id),
('type', 'in', ['out_invoice', 'out_refund']),
('state', '!=', 'cancel'),
])
action = self.env.ref('account.action_invoice_tree1').read()[0]
if len(invoices) > 1:
action['domain'] = [('id', 'in', invoices.ids)]
elif len(invoices) == 1:
action['views'] = [(self.env.ref('account.invoice_form').id, 'form')]
action['res_id'] = invoices.ids[0]
else:
action = {'type': 'ir.actions.act_window_close'}
return action
@api.multi
def operation_bill(self):
for operation in self:
# Get from the vendor bill list
vendor_bill_list = []
for cost_profit_line in operation.cost_profit_ids:
for vendor_bill_line in cost_profit_line.vendor_bill_ids:
if vendor_bill_line.type in ['in_invoice', 'in_refund']:
vendor_bill_list.append(vendor_bill_line.id)
invoices = self.env['account.invoice'].search([
('freight_hbl', '=', operation.id),
('type', 'in', ['in_invoice', 'in_refund']),
('state', '!=', 'cancel'),
])
invoice_name_list = []
for x in invoices:
invoice_name_list.append(x.id)
unique_list = []
for y in vendor_bill_list:
if invoice_name_list and len(invoice_name_list) > 0:
if y not in invoice_name_list:
unique_list.append(y)
else:
unique_list.append(y)
for z in invoice_name_list:
# if z not in vendor_bill_list:
unique_list.append(z)
if len(unique_list) > 1:
views = [(self.env.ref('account.invoice_supplier_tree').id, 'tree'),
(self.env.ref('account.invoice_supplier_form').id, 'form')]
return {
'name': 'Vendor bills',
'view_type': 'form',
'view_mode': 'tree,form',
# 'view_id': self.env.ref('account.invoice_supplier_tree').id,
'view_id': False,
'res_model': 'account.invoice',
'views': views,
# 'context': "{'type':'in_invoice'}",
'domain': [('id', 'in', unique_list)],
'type': 'ir.actions.act_window',
# 'target': 'new',
}
elif len(unique_list) == 1:
# print('in vendor bill length =1')
return {
# 'name': self.booking_no,
'view_type': 'form',
'view_mode': 'form',
'res_model': 'account.invoice',
'res_id': unique_list[0] or False, # readonly mode
# 'domain': [('id', 'in', purchase_order.ids)],
'type': 'ir.actions.act_window',
'target': 'popup', # readonly mode
}
@api.multi
def operation_si(self):
for operation in self:
si = self.env['freight.website.si'].search([('bl_ref', '=', operation.id), ])
if len(si) > 1:
views = [(self.env.ref('sci_goexcel_freight.view_tree_si').id, 'tree'),
(self.env.ref('sci_goexcel_freight.view_form_si').id, 'form')]
return {
'name': 'Shipping Instruction',
'view_type': 'form',
'view_mode': 'tree,form',
'view_id': False,
'res_model': 'freight.website.si',
'views': views,
'domain': [('id', 'in', si.ids)],
'type': 'ir.actions.act_window',
}
elif len(si) == 1:
return {
'view_type': 'form',
'view_mode': 'form',
'res_model': 'freight.website.si',
'res_id': si.id or False,
'type': 'ir.actions.act_window',
'target': 'popup', # readonly mode
}
else:
action = {'type': 'ir.actions.act_window_close'}
return action
def _get_invoiced_count(self):
for operation in self:
invoices = self.env['account.invoice'].search([
('freight_hbl', '=', operation.id),
('type', 'in', ['out_invoice','out_refund']),
('state', '!=', 'cancel'),
])
self.update({
'invoice_count': len(invoices),
#'invoice_ids': invoices,
})
def _get_bill_count(self):
# vendor bill is created from booking job, vendor bill header will have the booking job id
for operation in self:
# Get from the vendor bill list
vendor_bill_list = []
# vendor_bill_list_temp = []
for cost_profit_line in operation.cost_profit_ids:
for vendor_bill_line in cost_profit_line.vendor_bill_ids:
if vendor_bill_line.type in ['in_invoice', 'in_refund']:
vendor_bill_list.append(vendor_bill_line.id)
# vendor_bill_list_temp.append(vendor_bill_line.id)
# print('vendor_bill_list: ', len(vendor_bill_list))
# remove the duplicates in the vendor bill list
unique_vendor_bill_list = []
for i in vendor_bill_list:
if i not in unique_vendor_bill_list:
unique_vendor_bill_list.append(i)
# print('unique_vendor_bill_list: ', len(unique_vendor_bill_list))
# Get the vendor list (Create the vendor from the job)
invoices = self.env['account.invoice'].search([
('freight_hbl', '=', operation.id),
('type', 'in', ['in_invoice', 'in_refund']),
('state', '!=', 'cancel'),
])
# print('vendor bills:', len(invoices))
invoice_name_list = []
for x in invoices:
invoice_name_list.append(x.id)
unique_list = []
# for x in invoices:
# invoice_name_list.append(x.vendor_bill_id.id)
# unique_list = []
for y in unique_vendor_bill_list:
if invoice_name_list and len(invoice_name_list) > 0:
if y not in invoice_name_list:
unique_list.append(y)
else:
unique_list.append(y)
for z in invoice_name_list:
# if z not in vendor_bill_list:
unique_list.append(z)
if len(unique_list) > 0:
self.update({
'vendor_bill_count': len(unique_list),
})
def _get_si_count(self):
for operation in self:
si = self.env['freight.website.si'].search([
('bl_ref', '=', operation.id),
])
self.update({
'si_count': len(si),
})
# TS - add for Purchase Receipt
purchase_receipt_count = fields.Integer(string='Purchase Receipt Count', compute='_get_pr_count', copy=False)
def _get_pr_count(self):
# get purchase receipt (Account Voucher) on the lines
for operation in self:
# Get PR list
pr_lines = self.env['account.voucher.line'].search([
('freight_hbl', '=', operation.id),
])
pr_list = []
for pr_line in pr_lines:
if pr_line.voucher_id.state != 'cancel' and pr_line.voucher_id.voucher_type == 'purchase':
pr_list.append(pr_line.voucher_id.id)
# pr_name_list = []
# for x in pr_list:
# pr_name_list.append(x.id)
unique_list = []
for i in pr_list:
if i not in unique_list:
unique_list.append(i)
if len(unique_list) > 0:
self.update({
'purchase_receipt_count': len(unique_list),
})
@api.multi
def operation_pr(self):
for operation in self:
for operation in self:
# Get PR list
pr_lines = self.env['account.voucher.line'].search([
('freight_hbl', '=', operation.id),
])
pr_list = []
for pr_line in pr_lines:
if pr_line.voucher_id.state != 'cancel' and pr_line.voucher_id.voucher_type == 'purchase':
pr_list.append(pr_line.voucher_id.id)
# pr_name_list = []
# for x in pr_list:
# pr_name_list.append(x.id)
unique_list = []
for i in pr_list:
if i not in unique_list:
unique_list.append(i)
if len(unique_list) > 1:
views = [(self.env.ref('account_voucher.view_voucher_tree').id, 'tree'),
(self.env.ref('account_voucher.view_purchase_receipt_form').id, 'form')]
return {
'name': 'Purchase Receipt',
'view_type': 'form',
'view_mode': 'tree,form',
# 'view_id': self.env.ref('account.invoice_supplier_tree').id,
'view_id': False,
'res_model': 'account.voucher',
'views': views,
# 'context': "{'type':'in_invoice'}",
'domain': [('id', 'in', unique_list)],
'type': 'ir.actions.act_window',
# 'target': 'new',
}
elif len(unique_list) == 1:
# print('in vendor bill length =1')
return {
# 'name': self.booking_no,
'view_type': 'form',
'view_mode': 'form',
'res_model': 'account.voucher',
'res_id': unique_list[0] or False, # readonly mode
# 'domain': [('id', 'in', purchase_order.ids)],
'type': 'ir.actions.act_window',
'target': 'popup', # readonly mode
}
class CargoLine(models.Model):
_name = 'freight.bol.cargo'
_description = 'Cargo Line'
cargo_line = fields.Many2one('freight.bol', string='Cargo Line', required=True, ondelete='cascade',
index=True, copy=False)
sequence = fields.Integer(string="sequence")
marks = fields.Text(string='Marks and Numbers')
container_no = fields.Char(string="Container No.")
container_product_id = fields.Many2one('product.product', string='Container', track_visibility='onchange')
seal_no = fields.Char(string="Seal No.")
container_product_name = fields.Text(string='Description of Goods')
packages_no_value = fields.Integer(string="No. of Packages")
packages_no_uom = fields.Many2one('uom.uom', string="UoM")
exp_net_weight = fields.Float(string="Net Weight(KG)", help="Expected Weight in kg.", track_visibility='onchange')
exp_gross_weight = fields.Float(string="Gross Weight(KG)", digits=(12, 4), help="Expected Weight in kg.")
dim_length = fields.Float(string='Length', help="Length in cm", default="0.00", track_visibility='onchange')
dim_width = fields.Float(string='Width', default="0.00", help="Width in cm", track_visibility='onchange')
dim_height = fields.Float(string='Height', default="0.00", help="Height in cm", track_visibility='onchange')
exp_vol = fields.Float(string="Measurement (M3)", digits=(12, 4),
help="Expected Volume in m3 Measure")
packages_no = fields.Char(string="No. of Packages")
@api.multi
def _get_default_container_category(self):
container_lines = self.env['freight.product.category'].search([('type', '=ilike', 'container')])
for container_line in container_lines:
# _logger.warning('_get_default_container_category=' + str(container_line.product_category))
return container_line.product_category
container_category_id = fields.Many2one('product.category', string="Container Product Id",
default=_get_default_container_category)
@api.onchange('container_product_name')
def _onchange_description(self):
bl = self.env['freight.bol'].search([('bol_no', '=', self.cargo_line.bol_no)])
if self.container_product_name:
lines_description = self.container_product_name.count('\n')/20
lines_description = math.ceil(lines_description)
x = self.container_product_name.split('\n')
count = 0
line_description1 = ''
line_description2 = ''
for line in x:
if count < 20:
line_description1 = line_description1 + line + '\n'
count = count + 1
else:
line_description2 = line_description2 + line + '\n'
count = count + 1
bl.write({'lines_description': lines_description,
'line_description1': line_description1,
'line_description2': line_description2,
})
@api.model
def create(self, vals):
# _logger.warning("in create")
res = super(CargoLine, self).create(vals)
content = ""
if vals.get("marks"):
content = content + " \u2022 Marks and Numbers: " + str(vals.get("marks")) + "<br/>"
if vals.get("container_product_name"):
content = content + " \u2022 Description of Goods: " + str(vals.get("container_product_name")) + "<br/>"
if vals.get("packages_no"):
content = content + " \u2022 No. of Packages: " + str(vals.get("packages_no")) + "<br/>"
if vals.get("seal_no"):
content = content + " \u2022 Seal no: " + str(vals.get("seal_no")) + "<br/>"
if vals.get("container_no"):
content = content + " \u2022 Container No.: " + str(vals.get("container_no")) + "<br/>"
if vals.get("exp_gross_weight"):
content = content + " \u2022 Gross Weight(KG): " + str(vals.get("exp_gross_weight")) + "<br/>"
if vals.get("exp_vol"):
content = content + " \u2022 Measurement (M3): " + str(vals.get("exp_vol")) + "<br/>"
res.cargo_line.message_post(body=content)
return res
@api.multi
def write(self, vals):
# _logger.warning("in write")
res = super(CargoLine, self).write(vals)
# _logger.warning("after super write")
content = ""
if vals.get("marks"):
content = content + " \u2022 Marks and Numbers: " + str(vals.get("marks")) + "<br/>"
if vals.get("container_product_name"):
content = content + " \u2022 Description of Goods: " + str(vals.get("container_product_name")) + "<br/>"
if vals.get("packages_no"):
content = content + " \u2022 No. of Packages: " + str(vals.get("packages_no")) + "<br/>"
if vals.get("seal_no"):
content = content + " \u2022 Seal no: " + str(vals.get("seal_no")) + "<br/>"
if vals.get("container_no"):
content = content + " \u2022 Container No.: " + str(vals.get("container_no")) + "<br/>"
if vals.get("exp_gross_weight"):
content = content + " \u2022 Gross Weight(KG): " + str(vals.get("exp_gross_weight")) + "<br/>"
if vals.get("exp_vol"):
content = content + " \u2022 Measurement (M3): " + str(vals.get("exp_vol")) + "<br/>"
self.cargo_line.message_post(body=content)
return res
class ChargeLine(models.Model):
_name = 'freight.bol.charge'
_description = 'Charge Line'
charge_line = fields.Many2one('freight.bol', string='Charge Line', required=True, ondelete='cascade',
index=True, copy=False)
sequence = fields.Integer(string="sequence")
freight_charges = fields.Text(string='Freight & Charges')
rate = fields.Char(string='Rate')
per = fields.Char(string="Per")
amount = fields.Char(string="Amount")
prepaid = fields.Char(string="Prepaid")
collect = fields.Char(string="Collect")
payable_at_by = fields.Char(string="Payable at/by")
# fcl_container_qty = fields.Float(string="Qty", digits=(8, 0), track_visibility='onchange')
revenue_tons = fields.Char(string='Revenue Tons')
@api.model
def create(self, vals):
# _logger.warning("in create")
res = super(ChargeLine, self).create(vals)
content = ""
if vals.get("freight_charges"):
content = content + " \u2022 Freight & Charges: " + str(vals.get("freight_charges")) + "<br/>"
if vals.get("revenue_tons"):
content = content + " \u2022 Revenue Tons: " + str(vals.get("revenue_tons")) + "<br/>"
if vals.get("rate"):
content = content + " \u2022 Rate: " + str(vals.get("rate")) + "<br/>"
if vals.get("per"):
content = content + " \u2022 Per: " + str(vals.get("per")) + "<br/>"
if vals.get("amount"):
content = content + " \u2022 Amount: " + str(vals.get("amount")) + "<br/>"
if vals.get("prepaid"):
content = content + " \u2022 Prepaid: " + str(vals.get("prepaid")) + "<br/>"
if vals.get("collect"):
content = content + " \u2022 Collect: " + str(vals.get("collect")) + "<br/>"
if vals.get("payable_at_by"):
content = content + " \u2022 Payable at/by: " + str(vals.get("payable_at_by")) + "<br/>"
res.charge_line.message_post(body=content)
return res
@api.multi
def write(self, vals):
# _logger.warning("in write")
res = super(ChargeLine, self).write(vals)
# _logger.warning("after super write")
content = ""
if vals.get("freight_charges"):
content = content + " \u2022 Freight & Charges: " + str(vals.get("freight_charges")) + "<br/>"
if vals.get("revenue_tons"):
content = content + " \u2022 Revenue Tons: " + str(vals.get("revenue_tons")) + "<br/>"
if vals.get("rate"):
content = content + " \u2022 Rate: " + str(vals.get("rate")) + "<br/>"
if vals.get("per"):
content = content + " \u2022 Per: " + str(vals.get("per")) + "<br/>"
if vals.get("amount"):
content = content + " \u2022 Amount: " + str(vals.get("amount")) + "<br/>"
if vals.get("prepaid"):
content = content + " \u2022 Prepaid: " + str(vals.get("prepaid")) + "<br/>"
if vals.get("collect"):
content = content + " \u2022 Collect: " + str(vals.get("collect")) + "<br/>"
if vals.get("payable_at_by"):
content = content + " \u2022 Payable at/by: " + str(vals.get("payable_at_by")) + "<br/>"
self.charge_line.message_post(body=content)
return res
class CostProfit(models.Model):
_name = 'freight.bol.cost.profit'
_description = "BOL Cost & Profit"
sequence = fields.Integer(string="sequence")
bol_id = fields.Many2one('freight.bol', string='BOL ID', required=True, ondelete='cascade',
index=True, copy=False)
product_id = fields.Many2one('product.product', string="Product")
product_name = fields.Text(string="Description")
#Profit
#profit_qty = fields.Integer(string='Qty', default="1")
#profit_qty = fields.Float(string='Qty', default="1", digits=(12, 2))
list_price = fields.Float(string="Unit Price")
uom_id = fields.Many2one('uom.uom', string="UoM")
profit_gst = fields.Selection([('zer', 'ZER')], string="GST", default="zer", track_visibility='onchange')
tax_id = fields.Many2many('account.tax', string='Taxes', domain=['|', ('active', '=', False), ('active', '=', True)])
profit_currency = fields.Many2one('res.currency', 'Currency',
default=lambda self: self.env.user.company_id.currency_id.id, track_visibility='onchange')
profit_currency_rate = fields.Float(string='Rate', default="1.00", track_visibility='onchange')
profit_amount = fields.Float(string="Amt", compute="_compute_profit_amount", store=True, track_visibility='onchange')
sale_total = fields.Float(string="Total Sales", compute="_compute_sale_total", store=True, track_visibility='onchange')
#Cost
#cost_qty = fields.Integer(string='Qty', default="1", track_visibility='onchange')
profit_qty = fields.Float(string='Qty', default="1.000", digit=(12, 3))
cost_qty = fields.Float(string='Qty', default="1.000", digit=(12, 3))
cost_price = fields.Float(string="Unit Price", track_visibility='onchange')
cost_gst = fields.Selection([('zer', 'ZER')], string="Tax", default="zer", track_visibility='onchange')
vendor_id = fields.Many2one('res.partner', string="Vendor", track_visibility='onchange')
vendor_bill_id = fields.Many2one('account.invoice', string="Vendor Bill")
cost_currency = fields.Many2one('res.currency', string="Curr", required=True,
default=lambda self: self.env.user.company_id.currency_id.id, track_visibility='onchange')
cost_currency_rate = fields.Float(string='Rate', default="1.00", track_visibility='onchange')
cost_amount = fields.Float(string="Amt",
compute="_compute_cost_amount", store=True, track_visibility='onchange')
cost_total = fields.Float(string="Total Cost",
compute="_compute_cost_total", store=True, track_visibility='onchange')
# Invoice & Bill
billed = fields.Boolean(string='Billed', copy=False)
is_billed = fields.Char('Is Biiled?', compute='_compute_is_billed', store=True)
added_to_invoice = fields.Boolean(string='Invoiced', copy=False)
invoice_paid = fields.Boolean(string='Invoice Paid', copy=False)
paid = fields.Boolean(string='Paid', copy=False)
is_paid = fields.Char('Is Paid?', compute='_compute_is_paid', store=True)
invoice_id = fields.Many2one('account.invoice', string="Invoice")
inv_line_id = fields.Many2one('account.invoice.line', string="Invoice Line")
bill_id = fields.Many2one('account.invoice', string="Bill")
bill_line_id = fields.Many2one('account.invoice.line', string="Bill Line")
route_service = fields.Boolean(string='Is Route Service', default=False)
profit_total = fields.Float(string="Total Profit", compute="_compute_profit_total", store=True)
margin_total = fields.Float(string="Margin %", compute="_compute_margin_total", digits=(8,2), store=True, group_operator="avg")
vendor_id_ids = fields.Many2many('res.partner', string="Vendor List", copy=False)
vendor_bill_ids = fields.Many2many('account.invoice', string="Vendor Bill List", copy=False)
@api.one
def _set_access_for_invoiced(self):
if self.env['res.users'].has_group('account.group_account_manager'):
self.invoiced_readonly = False
else:
self.invoiced_readonly = True
invoiced_readonly = fields.Boolean(compute="_set_access_for_invoiced",
string='Is user able to modify invoiced?')
@api.depends('profit_qty', 'list_price')
def _compute_profit_amount(self):
for service in self:
if service.product_id:
service.profit_amount = service.profit_qty * service.list_price or 0.0
@api.depends('cost_qty', 'cost_price')
def _compute_cost_amount(self):
for service in self:
if service.product_id:
service.cost_amount = service.cost_qty * service.cost_price or 0.0
@api.depends('profit_amount', 'profit_currency_rate')
def _compute_sale_total(self):
for service in self:
if service.product_id:
service.sale_total = service.profit_amount * service.profit_currency_rate or 0.0
@api.onchange('profit_currency_rate')
def _onchange_profit_currency_rate(self):
for service in self:
if service.product_id:
service.sale_total = service.profit_amount * service.profit_currency_rate or 0.0
@api.onchange('profit_amount')
def _onchange_profit_amount(self):
for service in self:
if service.product_id:
service.sale_total = service.profit_amount * service.profit_currency_rate or 0.0
service.profit_total = service.sale_total - service.cost_total or 0.0
@api.depends('cost_amount', 'cost_currency_rate')
def _compute_cost_total(self):
for service in self:
if service.product_id:
service.cost_total = service.cost_amount * service.cost_currency_rate or 0.0
service.profit_total = service.sale_total - service.cost_total or 0.0
@api.depends('cost_total', 'sale_total')
def _compute_profit_total(self):
for service in self:
if service.product_id:
service.profit_total = service.sale_total - service.cost_total or 0.0
@api.depends('profit_total', 'sale_total')
def _compute_margin_total(self):
for service in self:
if service.product_id:
if service.sale_total > 0:
service.margin_total = service.profit_total / service.sale_total * 100
@api.onchange('cost_amount')
def _onchange_cost_amount(self):
for service in self:
if service.product_id:
service.cost_total = service.cost_amount * service.cost_currency_rate or 0.0
service.profit_total = service.sale_total - service.cost_total or 0.0
@api.onchange('cost_currency_rate')
def _onchange_cost_currency_rate(self):
for service in self:
if service.product_id:
service.cost_total = service.cost_amount * service.cost_currency_rate or 0.0
service.profit_total = service.sale_total - service.cost_total or 0.0
@api.onchange('product_id')
def _onchange_product_id(self):
if not self.product_id:
return {'domain': {'uom_id': []}}
vals = {}
domain = {'uom_id': [('category_id', '=', self.product_id.uom_id.category_id.id)]}
if not self.uom_id or (self.product_id.uom_id.id != self.uom_id.id):
vals['uom_id'] = self.product_id.uom_id
vals['product_name'] = self.product_id.name
self.update(vals)
if self.product_id:
self.update({
'list_price': self.product_id.list_price or 0.0,
'cost_price': self.product_id.standard_price or 0.0
})
@api.onchange('vendor_id')
def _onchange_vendor_id(self):
print('OnChange Vendor_ID')
if self.vendor_id:
if not self.billed:
self.billed = False
print('Invoiced False')
@api.multi
@api.depends('billed')
def _compute_is_billed(self):
for cost_profit_line in self:
if cost_profit_line.vendor_id:
if cost_profit_line.billed:
cost_profit_line.is_billed = 'Y'
elif not cost_profit_line.billed:
cost_profit_line.is_billed = 'N'
@api.multi
@api.depends('paid')
def _compute_is_paid(self):
for cost_profit_line in self:
if cost_profit_line.vendor_id:
if cost_profit_line.paid:
cost_profit_line.is_paid = 'Y'
elif not cost_profit_line.paid:
cost_profit_line.is_paid = 'N'
|
7,379 | 92d689e5caa2d8c65f86af0f8b49b009d162a783 | from turtle import *
from shapes import *
#1-
#1.triangle
def eTriangle():
forward(100)
right(120)
forward(100)
right(120)
forward(100)
right(120)
mainloop()
#2.square
def square():
forward(100)
right(90)
forward(100)
right(90)
forward(100)
right(90)
forward(100)
mainloop()
#3.pentagon
def pentagon():
forward(100)
right(72)
forward(100)
right(72)
forward(100)
right(72)
forward(100)
right(72)
forward(100)
mainloop()
#4.hexagon
def hexagon():
forward(100)
right(60)
forward(100)
right(60)
forward(100)
right(60)
forward(100)
right(60)
forward(100)
right(60)
forward(100)
mainloop()
#5.octagon
def octagon():
forward(100)
right(45)
forward(100)
right(45)
forward(100)
right(45)
forward(100)
right(45)
forward(100)
right(45)
forward(100)
right(45)
forward(100)
right(45)
forward(100)
mainloop()
#6.star
def star():
forward(100)
right(144)
forward(100)
right(144)
forward(100)
right(144)
forward(100)
right(144)
forward(100)
mainloop()
#7.circle
def circle():
for i in range(370):
forward(2)
right(1)
mainloop()
#2-
from shapes import *
eTriangle()
square()
pentagon()
hexagon()
octagon()
star()
circle()
mainloop()
#3-
bgcolor("MidnightBlue")
starp(20, True, "yellow", "MidnightBlue")
right (20)
forward(100)
starp(20, True, "yellow", "MidnightBlue")
right (30)
forward(150)
starp(20, True, "yellow", "MidnightBlue")
right (40)
forward(200)
starp(20, True, "yellow", "MidnightBlue")
right (50)
forward(250)
starp(20, True, "yellow", "MidnightBlue")
right (60)
forward(300)
starp(20, True, "yellow", "MidnightBlue")
forward(100)
starp(20, True, "yellow", "MidnightBlue")
forward(100)
starp(20, True, "yellow", "MidnightBlue")
left (90)
forward(300)
starp(20, True, "yellow", "MidnightBlue")
right (50)
forward (300)
starp(20, True, "yellow", "MidnightBlue")
right(50)
forward(300)
starp(20, True, "yellow", "MidnightBlue")
right (50)
forward (275)
circlep(3, True, "SlateGrey", "MidnightBlue")
right(60)
forward(20)
mainloop()
#4-
bgcolor("skyblue")
right(90)
penup()
forward(100)
right(90)
forward(200)
fillcolor("Green")
begin_fill()
forward (300)
left(90)
forward (300)
left(90)
forward(1250)
left(90)
forward(300)
left(90)
forward(1000)
end_fill()
right (90)
pendown()
rectangle(200, 450, True, "Red")
left(180)
forward(200)
left(90)
penup()
forward(100)
right(90)
pendown
rectangle(50, 100, True, "Brown")
penup()
right(90)
forward(50)
right(90)
forward(50)
right (90)
forward(10)
circle(.1, True, "Black")
penup()
forward(40)
left(90)
forward(50)
pendown()
fillcolor("grey")
begin_fill()
left (20)
forward(400)
left (75)
forward(50)
left(105)
forward(400)
left(75)
forward(50)
end_fill()
right(5)
penup()
forward(200)
right(90)
forward(200)
right(90)
left(40)
pendown()
fillcolor("brown")
begin_fill()
forward(293.717)
right(80)
forward(293.717)
right(140)
forward(450)
end_fill()
penup()
left(90)
forward(75)
left(90)
forward(75)
pendown()
square(50, True, "blue", "Black")
right(90)
square(25, False, "blue", "black")
right(90)
forward(50)
right(90)
forward(25)
square(25, False, "blue", "black")
penup()
left(90)
forward(25)
right(90)
forward(200)
pendown()
square(50, True, "blue", "Black")
right(90)
square(25, False, "blue", "black")
right(90)
forward(50)
right(90)
forward(25)
square(25, False, "blue", "black")
penup()
left(90)
forward(250)
left (90)
forward(400)
circlep(3, True, "yellow", "yellow")
mainloop()
#5-
def door():
rectangle(50, 100, True, "Brown")
penup()
right(90)
forward(50)
right(90)
forward(50)
right (90)
forward(10)
circle(.1, True, "Black")
def grass():
fillcolor("Green")
begin_fill()
forward (300)
left(90)
forward (300)
left(90)
forward(1250)
left(90)
forward(300)
left(90)
forward(1000)
end_fill()
def house():
rectangle(200, 450, True, "Red")
def roof():
fillcolor("brown")
begin_fill()
forward(293.717)
right(80)
forward(293.717)
right(140)
forward(450)
end_fill()
def window():
square(50, True, "blue", "Black")
right(90)
square(25, False, "blue", "black")
right(90)
forward(50)
right(90)
forward(25)
square(25, False, "blue", "black")
def sun():
circlep(3, True, "yellow", "yellow")
def sidewalk():
fillcolor("grey")
begin_fill()
left (20)
forward(400)
left (75)
forward(50)
left(105)
forward(400)
left(75)
forward(50)
end_fill()
bgcolor("skyblue")
right(90)
penup()
forward(100)
right(90)
forward(200)
grass()
right (90)
pendown()
house()
left(180)
forward(200)
left(90)
penup()
forward(100)
right(90)
pendown
door()
penup()
forward(40)
left(90)
forward(50)
pendown()
sidewalk()
right(5)
penup()
forward(200)
right(90)
forward(200)
right(90)
left(40)
pendown()
roof()
penup()
left(90)
forward(75)
left(90)
forward(75)
pendown()
window()
penup()
left(90)
forward(25)
right(90)
forward(200)
pendown()
window()
penup()
left(90)
forward(250)
left (90)
forward(400)
sun()
mainloop()
#6-
import random
def craystar():
color('red', 'yellow')
begin_fill()
for i in range(36):
forward(200)
left(170)
end_fill()
def craytriangle():
color('black', 'blue')
begin_fill()
i = 60
while i > 0:
forward(i)
right(120)
i -= 5
end_fill()
def craysquare():
color("green", "Blue")
begin_fill()
for i in range(12):
for i in range(4):
forward(60)
right(90)
for i in range(12):
forward (random.randint(1,60))
right(90)
end_fill()
craysquare()
forward (50)
craysquare()
forward (50)
craysquare()
forward (50)
craystar()
forward(random.randint(1,100))
right(random.randint(1, 90))
craytriangle()
forward(random.randint(1,100))
right(random.randint(1, 90))
craystar()
forward(random.randint(1,100))
right(random.randint(1, 90))
craytriangle()
forward(random.randint(1,100))
right(random.randint(1, 90))
craystar()
forward(random.randint(1,100))
right(random.randint(1, 90))
craytriangle()
mainloop() |
7,380 | e4f194c3dbc3e1d62866343642e41fa1ecdeab93 | #!/usr/bin/python3
import os, re
import csv, unittest
from langtag import langtag
from sldr.iana import Iana
langtagjson = os.path.join(os.path.dirname(__file__), '..', 'pub', 'langtags.json')
bannedchars = list(range(33, 45)) + [47] + list(range(58, 63)) + [94, 96]
def nonascii(s):
cs = [ord(x) for x in s]
if any(not (32 <= x < 123) or x in bannedchars for x in cs):
return True
class Basic(unittest.TestCase):
extraScripts = ["Toto", "Vith"]
extraLangs = ("000",
"cxh", "dsk", "dyr", "eud", "ikh", "izm", "lgs", # going in ~23/Mar/2023
'lvl', 'nzr', 'pze', 'rsw', 'tvi', 'uly', 'vjk', 'wtb', 'ycr', 'ykh', 'zem', 'zlu') # going in ~23/Mar/2023
def setUp(self):
self.fname = os.path.join(os.path.dirname(__file__), '../source/langtags.csv')
with open(self.fname) as csvfile:
reader = csv.DictReader(csvfile, restkey="_")
self.rows = list(reader)
self.fieldnames = reader.fieldnames
self.numlines = reader.line_num
self.iana = Iana()
def _region_test(self, x):
if x in self.iana.region:
return True
elif x in ("XX", "XK"):
return True
return False
def _allRows(self):
for r in self.rows:
t = langtag(r['likely_subtag'])
if t.lang.startswith("x-"):
continue
yield (r, t)
def test_lang(self):
''' Tests that all lang subtags are in iana '''
fails = []
for r, t in self._allRows():
l = langtag(r['Lang_Id'])
if l.lang != t.lang and "-" not in l.lang and "-" not in t.lang:
self.fail("{Lang_Id} has different lang to {likely_subtag} ({0} != {1})".format(l.lang, t.lang, **r))
if t.lang not in self.iana.language and "-" not in t.lang and t.lang not in self.extraLangs:
fails.append(r['Lang_Id'])
if not l.test(fname=langtagjson):
self.fail("{Lang_Id} failed conformance check".format(**r))
if len(fails):
self.fail(f"{fails} langs not in IANA")
def test_region(self):
''' Test that region values are sensible and that they equal the default region.
Unknown regions do not have to be specified. '''
for r,t in self._allRows():
reg = t.region
if not self._region_test(t.region):
self.fail("{likely_subtag} has irregular region".format(**r))
for s in r['regions'].split():
if not self._region_test(s.strip()):
self.fail("{Lang_Id} has irregular region: {0} in regions".format(s, **r))
def test_script(self):
''' Qaa? type scripts must have an -x- for the script name '''
for r, t in self._allRows():
scr = t.script
if scr is not None and (scr.startswith("Qaa") or scr.startswith("Qab")):
if scr not in ("Qaax", "Qaby", "Qabz") and (t.extensions is None or 'x' not in t.extensions):
self.fail("{Lang_Id} has no extension for script name".format(**r))
elif scr not in self.iana.script and scr not in self.extraScripts:
self.fail("{Lang_Id} has irregular script {}".format(scr, **r))
elif t.script not in self.iana.script and t.script not in self.extraScripts:
self.fail("{likely_subtag} has irregular script".format(**r))
def test_variants(self):
''' Test that all variants are in IANA '''
for r, t in self._allRows():
l = langtag(r['Lang_Id'])
if t.vars is None and l.vars is None:
continue
if sorted(t.vars) != sorted(l.vars):
self.fail("{Lang_Id} and {likely_subtag} have different variants".format(**r))
for v in t.vars:
if v not in self.iana.variant:
self.fail("{likely_subtag} has bad variant {0}".format(v, **r))
def test_csv_columns(self):
''' Test that everyone has the right number of columns '''
lc = self.fieldnames[-1]
for r in self.rows:
if len(r.get("_", [])):
self.fail("{Lang_Id} has too many columns".format(**r))
elif r[lc] is None:
self.fail("{Lang_Id} has too few columns".format(**r))
def test_pua(self):
''' Test that anything with -x- in Lang_Id has it in likely_subtag too '''
for r, t in self._allRows():
l = langtag(r['Lang_Id'])
if t.ns is None and l.ns is None:
continue
if len(t.ns) == 1 and 'x' in t.ns and len(t.ns['x']) == 1:
continue # allow a private script extension
if sorted(t.ns.keys()) != sorted(l.ns.keys()):
self.fail("{Lang_Id} and {likely_subtag} have different extension namespaces".format(**r))
for k, v in t.ns.items():
if sorted(v) != sorted(l.ns[k]):
self.fail("{Lang_Id} and {likely_subtag} have different extensions in the {0} namespace".format(k, **r))
def test_ascii(self):
''' Test that all tags are pure ascii '''
for r, t in self._allRows():
for cid in ('Lang_Id', 'likely_subtag', 'regions', 'ISO 639-3', 'Macro', 'variants'):
if nonascii(r[cid]):
self.fail("{Lang_Id} has non ASCII in column {0} value {1}".format(cid, r[cid], **r))
def test_iso639(self):
''' Test that the iso639 column is either empty or 3 lower ascii chars. '''
k = 'ISO 639-3'
for r, t in self._allRows():
if r[k] == '':
continue
if len(r[k]) != 3 or r[k].lower() != r[k] or any(not (96 < ord(x) < 123) for x in r[k]):
self.fail("{Lang_Id} has faulty ISO639 code of {ISO 639-3}".format(**r))
def test_deprecated(self):
for r, t in self._allRows():
l = langtag(r['Lang_Id'])
inf = self.iana.language.get(l.lang, {})
if 'Deprecated' in inf:
if r['deprecated'] == '':
self.fail("{Lang_Id} was deprecated: {} in IANA but not in the database".format(inf['Deprecated'], **r))
if __name__ == "__main__":
unittest.main()
|
7,381 | 6b3cb7a42c8bc665e35206b135f6aefea3439758 | """ DB models.
"""
from sqlalchemy import Column, Integer, String, ForeignKey, DateTime
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import relationship
from db.session import map_engine, replay_engine
MapBase = declarative_base(bind=map_engine)
ReplayBase = declarative_base(bind=replay_engine)
class Map(MapBase):
__tablename__ = 'map'
id = Column(Integer, primary_key=True)
name = Column(String)
size_x = Column(Integer)
size_y = Column(Integer)
lines = relationship('Line', backref='map', lazy='dynamic')
points = relationship('Point', backref='map', lazy='dynamic')
posts = relationship('Post', backref='map', lazy='dynamic')
def __repr__(self):
return "<Map(id='{}', name='{}', size_x='{}', size_y='{}')>".format(
self.id, self.name, self.size_x, self.size_y)
class Line(MapBase):
__tablename__ = 'line'
id = Column(Integer, primary_key=True)
len = Column(Integer)
p0 = Column(Integer)
p1 = Column(Integer)
map_id = Column(Integer, ForeignKey('map.id'))
def __repr__(self):
return "<Line(id='{}', len='{}', p0='{}', p1='{}', map_id='{}')>".format(
self.id, self.len, self.p0, self.p1, self.map_id)
class Point(MapBase):
__tablename__ = 'point'
id = Column(Integer, primary_key=True)
map_id = Column(Integer, ForeignKey('map.id'))
x = Column(Integer)
y = Column(Integer)
posts = relationship('Post', backref='point', lazy='dynamic')
def __repr__(self):
return "<Point(id='{}', map_id='{}', x='{}', y='{}')>".format(
self.id, self.map_id, self.x, self.y)
class Post(MapBase):
__tablename__ = 'post'
id = Column(Integer, primary_key=True)
name = Column(String)
type = Column(Integer)
population = Column(Integer)
armor = Column(Integer)
product = Column(Integer)
replenishment = Column(Integer)
map_id = Column(Integer, ForeignKey('map.id'))
point_id = Column(Integer, ForeignKey('point.id'))
def __repr__(self):
return (
"<Post(id='{}', name='{}', type='{}', population='{}', armor='{}', "
"product='{}', replenishment='{}', map_id='{}', point_id='{}')>".format(
self.id, self.name, self.type, self.population, self.armor,
self.product, self.replenishment, self.map_id, self.point_id
)
)
class Game(ReplayBase):
__tablename__ = 'game'
id = Column(Integer, primary_key=True)
name = Column(String)
date = Column(DateTime)
map_name = Column(String)
actions = relationship('Action', backref='game', lazy='dynamic')
num_players = Column(Integer)
def __repr__(self):
return "<Game(id='{}', name='{}', date='{}', map_name='{}', num_players='{}')>".format(
self.id, self.name, self.date, self.map_name, self.num_players)
class Action(ReplayBase):
__tablename__ = 'action'
id = Column(Integer, primary_key=True)
game_id = Column(Integer, ForeignKey('game.id'))
code = Column(Integer)
message = Column(String)
date = Column(DateTime)
def __repr__(self):
return "<Action(id='{}', game_id='{}', code='{}', message='{}', date='{}')>".format(
self.id, self.game_id, self.code, self.message, self.date)
|
7,382 | c6ab82d7f59faeee2a74e90a96c2348b046d0889 | #Multiple Word Palindromes
#Ex 72 extended
word = input("Word: ")
new = []
o = []
r = []
#canceling out the spaces
for i in range(len(word)):
if word[i] in ".,?!" or word[i] == ' ':
pass
else:
new.append(word[i])
#original
for i in range(len(new)):
o.append(new[i])
#reverse
for i in range(len(new)):
r.append(new[-i - 1])
print(new)
print(o)
print(r)
same_count = 0
for i in range(len(new)):
if o[i] == r[i]:
same_count += 1
else:
pass
if same_count == len(new):
print("Palindrome")
else:
print("Non Palindrome") |
7,383 | cdabb4a118cb0ef55c271a446fa190a457ebe142 | #!/usr/bin/env python
# -*- coding:utf-8 _*-
"""
:Author :weijinlong
:Time: :2020/1/10 17:22
:File :graph.py
:content:
"""
import tensorflow as tf
from .base import TFLayer
class TFModel(TFLayer):
def build_model(self):
raise NotImplementedError
def add_outputs(self, *args, **kwargs):
"""模型的输出值
:param args:
:param kwargs:
:return:
"""
outputs = {}
for value in args:
assert isinstance(value, tf.Tensor), "function add_outputs parameter's value must be tf.Tensor"
name = value.name
outputs[name.split(':')[0]] = name
for key, value in kwargs.items():
assert isinstance(value, tf.Tensor), "function add_outputs parameter's value must be tf.Tensor"
outputs[key] = value.name
self.update_outputs(outputs)
class TFCompile(TFLayer):
def compile(self):
raise NotImplementedError
def add_metrics(self, *args, **kwargs):
"""加入模型的评估指标、优化操作等，例如损失值，正确率等张量或者操作
:param args:
:param kwargs:
:return:
"""
metrics = {}
for value in args:
assert isinstance(value, (tf.Operation, tf.Tensor)), \
"function add_metrics parameter's value must be tf.Operation"
name = value.name
metrics[name.split(':')[0]] = name
for key, value in kwargs.items():
assert isinstance(value, (tf.Operation, tf.Tensor)), \
"function add_metrics parameter's value must be tf.Operation"
metrics[key] = value.name
self.update_metrics(metrics)
@property
def fetches(self):
""" 获取模型输出值或者评估值， 来优化训练模型
:return:
"""
return self.metrics
class TFComModel(TFModel, TFCompile):
"""
基于TensorFlow的复合模型，即使用一个算子构建模型的和模型的编译
"""
def build_model(self):
raise NotImplementedError
def compile(self):
pass
|
7,384 | 401c6b09edf593e00aecf5bbb1b2201effc9e78c | #
# @lc app=leetcode id=14 lang=python3
#
# [14] Longest Common Prefix
#
# @lc code=start
class Solution:
def longestCommonPrefix(self, strs: List[str]) -> str:
pass
# At the moment I just wanna test my workspace so it's working tomorrow it's time for the problems
# @lc code=end
|
7,385 | 1dd09a09f542099091d94d466ebd7cc149884eb4 | import time
from junk.keyboard_non_blocking import NonBlockingKeyboard
TICK_DURATION = 0.05
INITIAL_FOOD_LEVEL = 100
FOOD_PER_TICK = -1
FOOD_PER_FEED = 10
MAX_FOOD_LEVEL = 100
INITIAL_ENERGY_LEVEL = 50
ENERGY_PER_TICK_AWAKE = -1
ENERGY_PER_TICK_ASLEEP = 5
MAX_ENERGY_LEVEL = 100
INITIAL_IS_AWAKE = False
INITIAL_POOP_LEVEL = 0
TICKS_PER_POOP = 25
MAX_POOP_LEVEL = 10
class UnknownCommand(Exception):
pass
def _add_and_clip(x, dx, x_min, x_max):
return max(x_min, min(x_max, x + dx))
class Tamagotchi:
def __init__(self) -> None:
self._age = 0
self._food_level = INITIAL_FOOD_LEVEL
self._energy_level = INITIAL_ENERGY_LEVEL
self._poop_level = INITIAL_POOP_LEVEL
self._is_awake = INITIAL_IS_AWAKE
self._commands = {
"f": self._feed,
"c": self._clean,
"s": self._sleep,
}
def __repr__(self) -> str:
return f"Tamagotchi(is_awake={self._is_awake}, food_level={self._food_level}, energy_level={self._energy_level}, poop_level={self._poop_level}, age={self._age})"
def process_command(self, command: str) -> None:
try:
self._commands[command]()
except KeyError:
raise UnknownCommand(command)
def _feed(self) -> None:
if self._is_awake:
self._food_level = _add_and_clip(
self._food_level, FOOD_PER_FEED, 0, MAX_FOOD_LEVEL
)
def _clean(self) -> None:
self._poop_level = 0
def _sleep(self) -> None:
self._is_awake = False
def is_alive(self) -> bool:
return self._food_level > 0 and self._poop_level < MAX_POOP_LEVEL
def update(self) -> None:
self._age += 1
# Food
self._food_level = _add_and_clip(
self._food_level, FOOD_PER_TICK, 0, MAX_FOOD_LEVEL
)
# Energy
if self._energy_level >= MAX_ENERGY_LEVEL:
self._is_awake = True
if self._energy_level <= 0:
self._is_awake = False
energy_delta = (
ENERGY_PER_TICK_AWAKE if self._is_awake else ENERGY_PER_TICK_ASLEEP
)
self._energy_level = _add_and_clip(
self._energy_level, energy_delta, 0, MAX_ENERGY_LEVEL
)
# Poop
if self._age % TICKS_PER_POOP == 0:
self._poop_level += 1
def main():
tamagotchi = Tamagotchi()
with NonBlockingKeyboard() as kb:
while True:
inpt = kb.getstr()
should_quit = False
for c in inpt:
try:
tamagotchi.process_command(c)
except UnknownCommand:
if c == "q":
should_quit = True
break
else:
raise
if should_quit:
break
tamagotchi.update()
print(tamagotchi)
if not tamagotchi.is_alive():
print("tamagotchi died")
break
time.sleep(TICK_DURATION)
if __name__ == "__main__":
main()
|
7,386 | 70188d011ef60b1586864c4b85a9f9e70e5a4caf | from fastapi import FastAPI, Header, Cookie, Form, Request, requests, Body, Response, HTTPException, status, Path, Query
from fastapi.responses import HTMLResponse
from typing import Optional
from fastapi.testclient import TestClient
from typing import List, Callable
from fastapi.staticfiles import StaticFiles
from fastapi.templating import Jinja2Templates
from fastapi.exceptions import RequestValidationError
from fastapi.routing import APIRoute
from starlette.responses import JSONResponse
from pydantic import BaseModel
import uvicorn
import time
payloads = {
'peoples': [
{
'firstname': 'watcharapon',
'lastname': 'weeraborirak',
'age': '24',
'city': 'bangkok'
},
{
'firstname': 'somsak',
'lastname': 'tamjai',
'age': '22',
'city': 'bangkok'
},
{
'firstname': 'rakkana',
'lastname': 'meejai',
'age': '66',
'city': 'outcast'
},
]
}
class Item(BaseModel):
name: str
price: float
class ValidationError(APIRoute):
def get_route_handler(self) -> Callable:
original_route_handler = super().get_route_handler()
async def customer_route_handler(request: Request) -> Response:
try:
return await original_route_handler(request)
except RequestValidationError as exc:
body = await request.body()
detail = {'error': exc.errors(), 'body': body.decode()}
raise HTTPException(status_code=200, detail=detail)
return customer_route_handler
app = FastAPI()
app.router.route_class = ValidationError
app.mount('/static', StaticFiles(directory='static'), name='static')
templates = Jinja2Templates(directory='templates')
client = TestClient(app)
@app.middleware('http')
async def add_process_time_header(request: Request, call_next):
start_time = time.time()
response = await call_next(request)
process_time = time.time() - start_time
response.headers['X-Process-Time'] = '{}'.format(str(round(process_time, 4)))
return response
@app.middleware('http')
async def add_process_name(request: Request, call_next):
response = await call_next(request)
response.headers['X-Owner-Server'] = 'Kane'
return response
@app.post('/items')
async def base_model(item: Item):
item_dict = item.dict()
return {'message': item_dict}
@app.put('/items/{item_id}')
async def item_id(item_id: int, item: Item):
return {'item_id': item_id, **item.dict()}
@app.get("/items_id/{item_id}")
async def read_items(
item_id: int = Path(..., title="The ID of the item to get"),
q: Optional[str] = Query(None, alias="item-query")
):
results = {"item_id": item_id}
if q:
results.update({"q": q})
return results
@app.get('/peoples')
async def fetch_movies(query: str = None): # query param string
payload = [p[query] for p in payloads['peoples']]
return payload
@app.get('/member')
async def member(item: Item, X_Item_ID: str = Header(...)): # Header
print(X_Item_ID)
if X_Item_ID != 'member':
raise HTTPException(status_code=400, detail="X-Item-ID header invalid")
return JSONResponse(content={item.name: 'kane', item.price: 123.33})
@app.get('/member/token')
async def member_token(x_token: str = Cookie(None)):
print(x_token)
return {'message': f'success cookie {x_token}'}
@app.get('/api_body/{item_id}') # dynamic route
async def api_body(item_id: str):
return {'item_id': item_id}
@app.post('/payload_request', response_model=Item, status_code=status.HTTP_201_CREATED)
async def payload_request(item: Item):
return item
@app.post("/payload_json")
async def create_item(payload: dict = Body(...)):
print(payload)
return payload
@app.post('/form_data')
async def form_data(password: str = Form(...), username: str = Form(...)):
return {'message': {'user': username, 'pwd': password}}
@app.post('/cookies')
async def cookies(response: Response):
response.set_cookie(key='foo', value='value')
return {'message': 'cookies darken'}
@app.get('/')
@app.get('/index', tags=['dashboard'])
async def index(request: Request):
return templates.TemplateResponse('template_fastapi/login.vue', context={'request': request})
@app.get("/func_element", response_model=Item, tags=["Description"], deprecated=True)
async def func_element(item: Item):
"""
Get Data Element:
- **name**: my_name
- **price**: price
"""
return item
@app.post("/func_item", response_model=Item, tags=["Description"], summary="Create an item",
description="Create an item with all the , name, description, price, tax and a set of unique tags")
async def fuc_item(item: Item):
update_item = item.dict()
update_item['name'] = 'kane_ja'
return update_item
@app.post('/json_response', response_model=Item, tags=['Description'])
async def json_response(item: Item):
"""
Return JsonResponse
- **Item**: name
- **status**: 201
"""
return JSONResponse(content={item.name: 'kaneeang'}, status_code=201)
if __name__ == '__main__':
uvicorn.run('fastapi_route_config:app', debug=True, port=8080)
|
7,387 | 2d20bac0f11fa724b2d0a2e0676e5b9ce7682777 | # -*- coding: utf-8 -*-
# Copyright (c) 2018-2019 Linh Pham
# wwdtm_panelistvspanelist is relased under the terms of the Apache License 2.0
"""WWDTM Panelist Appearance Report Generator"""
import argparse
from collections import OrderedDict
from datetime import datetime
import json
import os
import shutil
from typing import List, Dict, Text
import mysql.connector
import pytz
from jinja2 import Environment, FileSystemLoader
def retrieve_panelist_appearance_counts(panelist_id: int,
database_connection: mysql.connector.connect
) -> List[Dict]:
"""Retrieve yearly apperance count for the requested panelist ID"""
cursor = database_connection.cursor()
query = ("SELECT YEAR(s.showdate) AS year, COUNT(p.panelist) AS count "
"FROM ww_showpnlmap pm "
"JOIN ww_shows s ON s.showid = pm.showid "
"JOIN ww_panelists p ON p.panelistid = pm.panelistid "
"WHERE pm.panelistid = %s AND s.bestof = 0 "
"AND s.repeatshowid IS NULL "
"GROUP BY p.panelist, YEAR(s.showdate) "
"ORDER BY p.panelist ASC, YEAR(s.showdate) ASC")
cursor.execute(query, (panelist_id, ))
result = cursor.fetchall()
if not result:
return None
appearances = OrderedDict()
total_appearances = 0
for row in result:
appearances[row[0]] = row[1]
total_appearances += row[1]
appearances["total"] = total_appearances
return appearances
def retrieve_all_panelist_appearance_counts(database_connection: mysql.connector.connect
) -> List[Dict]:
"""Retrieve all appearance counts for all panelists from the
database"""
cursor = database_connection.cursor()
query = ("SELECT DISTINCT p.panelistid, p.panelist "
"FROM ww_showpnlmap pm "
"JOIN ww_panelists p ON p.panelistid = pm.panelistid "
"JOIN ww_shows s ON s.showid = pm.showid "
"WHERE s.bestof = 0 AND s.repeatshowid IS NULL "
"ORDER BY p.panelist ASC")
cursor.execute(query)
result = cursor.fetchall()
if not result:
return None
panelists = []
for row in result:
panelist = {}
panelist_id = row[0]
panelist["name"] = row[1]
appearances = retrieve_panelist_appearance_counts(panelist_id=panelist_id,
database_connection=database_connection)
panelist["appearances"] = appearances
panelists.append(panelist)
return panelists
def retrieve_all_years(database_connection: mysql.connector.connect) -> List[int]:
"""Retrieve a list of all available show years"""
cursor = database_connection.cursor()
query = ("SELECT DISTINCT YEAR(s.showdate) FROM ww_shows s "
"ORDER BY YEAR(s.showdate) ASC")
cursor.execute(query)
result = cursor.fetchall()
cursor.close()
if not result:
return None
years = []
for row in result:
years.append(row[0])
return years
def load_config():
"""Load configuration values from configuration file and from
options passed into script execution"""
# Read in configuration file for default values
with open("config.json", "r") as config_file:
config_dict = json.load(config_file)
# Read in options passed in that override values from the config.json file
parser = argparse.ArgumentParser()
parser.add_argument("--ga-property-code",
dest="ga_property_code",
type=str,
help="Google Analytics Property Code (default: %(default)s)",
default=config_dict["report"]["ga_property_code"])
parser.add_argument("--css-directory",
dest="css_directory",
type=str,
help="Directory where the base CSS stylesheet file is stored "
"(default: %(default)s)",
default=config_dict["report"]["css_directory"])
parser.add_argument("--css-filename",
dest="css_filename",
type=str,
help="File name of the report CSS stylesheet file "
"(default: %(default)s)",
default=config_dict["report"]["css_filename"])
parser.add_argument("--output-directory",
dest="output_directory",
type=str,
help="Directory where the generated report will be saved "
"(default: %(default)s)",
default=config_dict["report"]["output_directory"])
parser.add_argument("--output-filename",
dest="output_filename",
type=str,
help="File name of the generated report will be saved "
"(default: %(default)s)",
default=config_dict["report"]["output_filename"])
args = parser.parse_args()
# Override the values from the config.json file if values were set via argparse
if args.ga_property_code != config_dict["report"]["ga_property_code"]:
config_dict["report"]["ga_property_code"] = args.ga_property_code
if args.css_directory != config_dict["report"]["css_directory"]:
config_dict["report"]["css_directory"] = args.css_directory
if args.css_filename != config_dict["report"]["css_filename"]:
config_dict["report"]["css_filename"] = args.css_filename
if args.output_directory != config_dict["report"]["output_directory"]:
config_dict["report"]["output_directory"] = args.output_directory
if args.output_filename != config_dict["report"]["output_filename"]:
config_dict["report"]["output_filename"] = args.output_filename
return config_dict
def render_report(show_years: List[int],
panelists: List[Dict],
report_settings: Dict
) -> Text:
"""Render appearances report using Jinja2"""
# Setup Jinja2 Template
template_loader = FileSystemLoader("./template")
template_env = Environment(loader=template_loader,
trim_blocks=True,
lstrip_blocks=True)
template_file = "report.tmpl.html"
template = template_env.get_template(template_file)
# Generate timestamp to include in page footer
time_zone = pytz.timezone("America/Los_Angeles")
rendered_date_time = datetime.now(time_zone)
# Build dictionary to pass into template renderer
render_data = {}
render_data["show_years"] = show_years
render_data["panelists"] = panelists
render_data["settings"] = report_settings
render_data["rendered_at"] = rendered_date_time.strftime("%A, %B %d, %Y %H:%M:%S %Z")
# Render the report and write out to output directory
report = template.render(render_data=render_data)
return report
def generate_output_files(rendered_report: Text,
report_settings: Dict) -> None:
"""Writes out the generated report file to file in the output directory
and copies the base CSS file to the same directory"""
css_path = os.path.join(report_settings["css_directory"],
report_settings["css_filename"])
output_path = os.path.join(report_settings["output_directory"],
report_settings["output_filename"])
# Create the output directory if it does not exist
if not os.path.isdir(report_settings["output_directory"]):
os.mkdir(report_settings["output_directory"])
# Write out the generated report
with open(output_path, "w") as output_file:
if output_file.writable():
output_file.write(rendered_report)
else:
print("Error: {} is not writable".format(output_path))
# Copy CSS file into output directory
shutil.copy2(css_path, report_settings["output_directory"])
return
def main():
"""Bootstrap database connection, retrieve panelist appearance data,
generate the report and create an output bundle"""
app_config = load_config()
database_connection = mysql.connector.connect(**app_config["database"])
panelists = retrieve_all_panelist_appearance_counts(database_connection)
show_years = retrieve_all_years(database_connection)
rendered_report = render_report(show_years=show_years,
panelists=panelists,
report_settings=app_config["report"])
generate_output_files(rendered_report=rendered_report,
report_settings=app_config["report"])
# Only run if executed as a script and not imported
if __name__ == '__main__':
main()
|
7,388 | 5172819da135600d0764033a85a4175098274806 | import numpy as np
import pandas as pd
import datetime
import time
from sklearn.tree import DecisionTreeClassifier
from sklearn.neighbors import KNeighborsClassifier
from sklearn.neighbors import KNeighborsRegressor
from sklearn.model_selection import cross_val_score
from sklearn import preprocessing
from sklearn.model_selection import KFold
def make_submission(y_predict, user_id_test, movie_id_test, name=None, date=True):
n_elements = len(y_predict)
if name is None:
name = 'submission'
if date:
name = name + '_{}'.format(time.strftime('%d-%m-%Y_%Hh%M'))
with open(name + ".csv", 'w') as f:
f.write('"USER_ID_MOVIE_ID","PREDICTED_RATING"\n')
for i in range(n_elements):
if np.isnan(y_predict[i]):
raise ValueError('NaN detected!')
line = '{:0.0f},{:0.0f},{}\n'.format(user_id_test[i],movie_id_test[i],y_predict[i])
f.write(line)
print("Submission file successfully written!")
class ModelSelection:
def __init__(self, user_data, movie_data, aggregated_data, train_data, output_train):
self.train = train_data
self.users = user_data
self.aggregated = aggregated_data
self.movies = movie_data
self.output_train = output_train
def optimizeParametersDecisionTreeClassifier(self, nb_fold, max_depth_range):
kf = KFold(n_splits=nb_fold)
depth_n_errors = np.zeros((max_depth_range.__len__(), 2))
i = 0
for depth in max_depth_range:
depth_n_errors[i][0] = depth
i += 1
#First round of cv
for train_index, test_index in kf.split(self.aggregated):
#Second round of cv
i = 0
for depth in max_depth_range:
dt = DecisionTreeClassifier(max_depth=depth)
scores = cross_val_score(dt, self.aggregated[train_index], self.output_train[train_index], cv=nb_fold, scoring='neg_mean_squared_error')
depth_n_errors[i][1] += -scores.mean()
i += 1
i = 0
for depth in max_depth_range:
depth_n_errors[i][1] /= nb_fold
i += 1
best_depth = 0
best_error = 5
#Take the best model and cross validate it on the whole data
for depth, error in depth_n_errors:
if(error < best_error):
best_error = error
best_depth = depth
#Recompute the error for this model on the whole data set
dt = DecisionTreeClassifier(max_depth=best_depth)
final_error = -cross_val_score(dt, self.aggregated, self.output_train, cv=nb_fold, scoring='neg_mean_squared_error')
return[best_depth, final_error.mean()]
def optimizeParametersKNeighborsClassifier(self, nb_fold, k_range):
kf = KFold(n_splits=nb_fold)
k_n_errors = np.zeros((k_range.__len__(), 2))
i = 0
for k in k_range:
k_n_errors[i][0] = k
i += 1
#First round of cv
for train_index, test_index in kf.split(self.aggregated):
#Second round of cv
i = 0
for k in k_range:
dt = KNeighborsClassifier(n_neighbors=k)
scores = cross_val_score(dt, self.aggregated[train_index], self.output_train[train_index], cv=nb_fold, scoring='neg_mean_squared_error')
k_n_errors[i][1] += -scores.mean()
i += 1
for i in range(k_range.__len__()):
k_n_errors[i][1] /= nb_fold
best_k = 0
best_error = 5
#Take the best model and cross validate it on the whole data
for k, error in k_n_errors:
if(error < best_error):
best_error = error
best_k = k
#Recompute the error for this model on the whole data set
dt = KNeighborsClassifier(n_neighbors=best_k)
final_error = -cross_val_score(dt, self.aggregated, self.output_train, cv=nb_fold, scoring='neg_mean_squared_error')
return[best_k, final_error.mean()]
def optimizeParametersKNeighborsRegressor(self, nb_fold, k_range):
kf = KFold(n_splits=nb_fold)
k_n_errors = np.zeros((k_range.__len__(), 2))
i = 0
for k in k_range:
k_n_errors[i][0] = k
i += 1
#First round of cv
for train_index, test_index in kf.split(self.aggregated):
#Second round of cv
i = 0
for k in k_range:
dt = KNeighborsRegressor(n_neighbors=k)
scores = cross_val_score(dt, self.aggregated[train_index], self.output_train[train_index], cv=nb_fold, scoring='neg_mean_squared_error')
k_n_errors[i][1] += -scores.mean()
i += 1
for i in range(k_range.__len__()):
k_n_errors[i][1] /= nb_fold
best_k = 0
best_error = 5
#Take the best model and cross validate it on the whole data
for k, error in k_n_errors:
if(error < best_error):
best_error = error
best_k = k
#Recompute the error for this model on the whole data set
dt = KNeighborsRegressor(n_neighbors=best_k)
final_error = -cross_val_score(dt, self.aggregated, self.output_train, cv=nb_fold, scoring='neg_mean_squared_error')
return[best_k, final_error.mean()]
users = pd.read_csv("data/user_data_normalized_28-11-2016_01h32.csv", delimiter=",")
movies = pd.read_csv("data/movie_data_normalized.csv", delimiter=",")
train = pd.read_csv("data/data_train.csv", delimiter=",")
output = pd.read_csv("data/output_train.csv", delimiter=",")["rating"]
aggregated = pd.read_csv("data/agregated_data_28-11-2016_01h50.csv", delimiter=",")
ms = ModelSelection(users.values, movies.values, aggregated.values, train.values, output)
#print(ms.optimizeParametersDecisionTreeClassifier(5, range(2,3,1)))
print(ms.optimizeParametersKNeighborsClassifier(5, range(1,5,1)))
#print(ms.optimizeParametersKNeighborsClassifier(5, range(5,10,1))) |
7,389 | ec0113dbd79e936e614bb7ee7e48d29aa616d511 | num=int(input())
i=10
while i>=1:
print(i,end=" ")
i-=1
|
7,390 | e9a1fd8464f6c1e65aa2c1af60becbfcbf050814 | import tensorflow as tf
import numpy as np
import tensorflow.contrib.layers as layers
class Model(object):
def __init__(self, batch_size=128, learning_rate=0.01, num_labels=10, keep_prob=0.5, scope="model"):
self._batch_size = batch_size
self._learning_rate = learning_rate
self._num_labels = num_labels
self._scope = scope
self._keep_prob = keep_prob
self._conv_hidden_dims = [192, 192]
with tf.variable_scope(self._scope):
self._build_model()
def _build_net(self, x, reuse=False, trainable=True, scope="inference_net"):
with tf.variable_scope(scope, reuse=reuse):
out = x
for i in range(len(self._conv_hidden_dims)):
out = layers.conv2d(out, num_outputs=self._conv_hidden_dims[i], kernel_size=(5, 5),
activation_fn=tf.nn.relu, trainable=trainable)
out = layers.dropout(out, keep_prob=self._keep_prob, is_training=trainable)
out = layers.max_pool2d(out, kernel_size=(2, 2))
out = layers.flatten(out)
out = layers.fully_connected(out, num_outputs=1000, activation_fn=tf.nn.relu, trainable=trainable)
out = layers.dropout(out, keep_prob=self._keep_prob, is_training=trainable)
logits = layers.fully_connected(out, self._num_labels, trainable=trainable)
return logits
def _build_model(self):
self.x_ = tf.placeholder(tf.float32, shape=[None, 3072], name='x_') # data gets loaded as a 32x32 vector
x = tf.reshape(self.x_, [-1, 32, 32, 3], name='x') # CIFAR dataset is shape 32,32,3
self.y = tf.placeholder(tf.float32, shape=[None, self._num_labels], name='y') # 10 labels
# self.keep_prob = tf.placeholder(tf.float32, name='dropout_prob')
self.lr = tf.placeholder(tf.float32, shape=(), name='lr')
self.logits = self._build_net(x)
cross_entropy = tf.nn.softmax_cross_entropy_with_logits(logits=self.logits, labels=self.y)
self.loss = tf.reduce_mean(cross_entropy)
optimizer = tf.train.MomentumOptimizer(self.lr, momentum=0.9, use_nesterov=True)
self.train_op = optimizer.minimize(loss=self.loss)
self.acc = tf.reduce_mean(tf.cast(tf.equal(tf.argmax(self.logits, 1), tf.argmax(self.y, 1)), dtype=tf.float32))
# for eval steps
self.val_logits = self._build_net(x, reuse=True, trainable=False)
self.val_acc = tf.reduce_mean(tf.cast(tf.equal(tf.argmax(self.val_logits, 1), tf.argmax(self.y, 1)), dtype=tf.float32))
tf.summary.scalar('loss', self.loss)
tf.summary.scalar('accuracy', self.acc)
self.merged = tf.summary.merge_all()
|
7,391 | 34a456efc72b303aed5f722bb415d30ff62addab | import numpy as np
import argparse
import torch
from gridworlds.envs import GridWorldEnv, generate_obs_dict
from gridworlds.constants import possible_objects
import nengo_spa as spa
from collections import OrderedDict
from spatial_semantic_pointers.utils import encode_point, ssp_to_loc, get_heatmap_vectors
import matplotlib.pyplot as plt
import seaborn as sns
seed=13
np.random.seed(seed)
maze_index = 0
ssp_dim = 512
n_sensors = 36
dataset = '/home/ctnuser/ssp-navigation/ssp_navigation/datasets/mixed_style_100mazes_100goals_64res_13size_13seed/maze_dataset.npz'
params = {
'continuous': True,
'fov': 360,
'n_sensors': n_sensors,
'max_sensor_dist': 10,
'normalize_dist_sensors': False,
'movement_type': 'holonomic',
'seed': seed,
# 'map_style': args.map_style,
'map_size': 10,
'fixed_episode_length': False, # Setting to false so location resets are not automatic
'episode_length': 1000, #200,
'max_lin_vel': 5,
'max_ang_vel': 5,
'dt': 0.1,
'full_map_obs': False,
'pob': 0,
'n_grid_cells': 0,
'heading': 'none',
'location': 'none',
'goal_loc': 'none',
'goal_vec': 'none',
'bc_n_ring': 0,
'hd_n_cells': 0,
'csp_dim': 0,
'goal_csp': False,
'agent_csp': False,
'goal_distance': 0,#args.goal_distance # 0 means completely random
}
obs_dict = generate_obs_dict(params)
np.random.seed(params['seed'])
data = np.load(dataset)
# n_mazes by size by size
coarse_mazes = data['coarse_mazes']
coarse_size = coarse_mazes.shape[1]
n_maps = coarse_mazes.shape[0]
# Size of map IDs. Equal to n_maps if using one-hot encoding
id_size = n_maps
map_id = np.zeros((n_maps,))
map_id[maze_index] = 1
map_id = torch.Tensor(map_id).unsqueeze(0)
# n_mazes by res by res
fine_mazes = data['fine_mazes']
xs = data['xs']
ys = data['ys']
res = fine_mazes.shape[1]
coarse_xs = np.linspace(xs[0], xs[-1], coarse_size)
coarse_ys = np.linspace(ys[0], ys[-1], coarse_size)
map_array = coarse_mazes[maze_index, :, :]
x_axis_sp = spa.SemanticPointer(data=data['x_axis_sp'])
y_axis_sp = spa.SemanticPointer(data=data['y_axis_sp'])
heatmap_vectors = get_heatmap_vectors(xs, ys, x_axis_sp, y_axis_sp)
coarse_heatmap_vectors = get_heatmap_vectors(coarse_xs, coarse_ys, x_axis_sp, y_axis_sp)
# fixed random set of locations for the goals
limit_range = xs[-1] - xs[0]
goal_sps = data['goal_sps']
goals = data['goals']
# print(np.min(goals))
# print(np.max(goals))
goals_scaled = ((goals - xs[0]) / limit_range) * coarse_size
# print(np.min(goals_scaled))
# print(np.max(goals_scaled))
n_goals = 0#10 # TODO: make this a parameter
object_locations = OrderedDict()
vocab = {}
use_dataset_goals = False
for i in range(n_goals):
sp_name = possible_objects[i]
if use_dataset_goals:
object_locations[sp_name] = goals_scaled[maze_index, i] # using goal locations from the dataset
else:
# If set to None, the environment will choose a random free space on init
object_locations[sp_name] = None
# vocab[sp_name] = spa.SemanticPointer(ssp_dim)
vocab[sp_name] = spa.SemanticPointer(data=np.random.uniform(-1, 1, size=ssp_dim)).normalized()
env = GridWorldEnv(
map_array=map_array,
object_locations=object_locations, # object locations explicitly chosen so a fixed SSP memory can be given
observations=obs_dict,
movement_type=params['movement_type'],
max_lin_vel=params['max_lin_vel'],
max_ang_vel=params['max_ang_vel'],
continuous=params['continuous'],
max_steps=params['episode_length'],
fixed_episode_length=params['fixed_episode_length'],
dt=params['dt'],
screen_width=300,
screen_height=300,
debug_ghost=True,
)
# obs = env.reset(goal_distance=params['goal_distance'])
# env.set_agent_state(np.array([6, 9, 0]))
env.set_agent_state(np.array([3, 7, 0]))
env.step(np.array([0, 0]))
env.render()
env._render_extras()
sensors = env.get_dist_sensor_readings(
state=env.state,
n_sensors=params['n_sensors'],
fov_rad=params['fov']*np.pi/180.,
max_dist=params['max_sensor_dist'],
normalize=params['normalize_dist_sensors'],
)
fig, ax = plt.subplots(1, 1, figsize=(3, 3), tight_layout=True)
ax.bar(np.arange(len(sensors)), sensors)
ax.set_ylabel('Distance')
ax.set_xlabel('Sensor Index')
sns.despine()
plt.show()
|
7,392 | 1af9fb91e69ea78709c47fca6b12e4f7a6fd17a8 | import unittest
import os
import tempfile
import numpy as np
from keras_piecewise.backend import keras
from keras_piecewise import Piecewise2D
from .util import MaxPool2D
class TestPool2D(unittest.TestCase):
@staticmethod
def _build_model(input_shape, layer, row_num, col_num, pos_type=Piecewise2D.POS_TYPE_SEGMENTS):
data_input = keras.layers.Input(shape=input_shape)
row_input = keras.layers.Input(shape=(row_num,))
col_input = keras.layers.Input(shape=(col_num,))
pool_layer = Piecewise2D(
layer=layer,
pos_type=pos_type,
)([data_input, row_input, col_input])
model = keras.models.Model(inputs=[data_input, row_input, col_input], outputs=pool_layer)
model.compile(optimizer=keras.optimizers.Adam(), loss=keras.losses.mean_squared_error)
model.summary()
return model
def test_max_2d(self):
data = [
[
[1, 3, 5, 2],
[2, 5, 6, 1],
[7, 1, 5, 3],
[7, 2, 2, 4],
],
[
[1, 3, 5, 2],
[2, 5, 6, 1],
[7, 1, 5, 3],
[7, 2, 2, 4],
],
]
rows = [
[2, 4],
[3, 4],
]
cols = [
[1, 2, 4],
[1, 3, 4],
]
model = self._build_model(
input_shape=(None, None),
layer=MaxPool2D(),
row_num=len(rows[0]),
col_num=len(cols[0]),
)
predicts = model.predict([np.asarray(data), np.asarray(rows), np.asarray(cols)]).tolist()
expected = [
[
[2.0, 5.0, 6.0],
[7.0, 2.0, 5.0],
],
[
[7.0, 6.0, 3.0],
[7.0, 2.0, 4.0],
],
]
self.assertEqual(expected, predicts)
cols = [
[1, 2, 0, 4],
[1, 3, 2, 4],
]
model = self._build_model(
input_shape=(None, None),
layer=MaxPool2D(),
row_num=len(rows[0]),
col_num=len(cols[0]),
pos_type=Piecewise2D.POS_TYPE_PAIRS,
)
model_path = os.path.join(tempfile.gettempdir(), 'keras_piece_test_save_load_%f.h5' % np.random.random())
model.save(model_path)
model = keras.models.load_model(model_path, custom_objects={
'Piecewise2D': Piecewise2D,
'MaxPool2D': MaxPool2D,
})
predicts = model.predict([np.asarray(data), np.asarray(rows), np.asarray(cols)]).tolist()
expected = [
[[2.0, 7.0]],
[[2.0, 4.0]],
]
self.assertEqual(expected, predicts)
def test_pos_type_not_implemented(self):
with self.assertRaises(NotImplementedError):
self._build_model(
input_shape=(None,),
layer=MaxPool2D(),
row_num=13,
col_num=17,
pos_type='whatever',
)
|
7,393 | 096d82e1f9e8832f6605d23c8bb324e045b6b14f | ## Script (Python) "after_rigetta"
##bind container=container
##bind context=context
##bind namespace=
##bind script=script
##bind subpath=traverse_subpath
##parameters=state_change
##title=
##
doc = state_change.object
#Aggiornamento dello stato su plominoDocument
doc.updateStatus()
if script.run_script(doc, script.id) != False:
#### OTHER CODE HERE ####
# 1. INVIO MAIL RIGETTO
if doc.naming('richiesta') != 'integrazione':
doc.sendThisMail('rigetta')
script.run_script(doc, script.id, suffix='post')
#### SCRIPT ENDS HERE ####
|
7,394 | 303d56c18cce922ace45de1b8e195ebfdd874e23 | class product(object):
def __init__(self, item_name, price, weight, brand, status = "for sale"):
self.item_name = item_name
self.price = price
self.weight = weight
self.brand = brand
self.cost = price
self.status = status
self.displayInfo()
def displayInfo(self):
print "Item name:", self.item_name
print "Price:", self.price
print "Weight:", self.weight
print "Brand:", self.brand
print "Cost:", self.cost
print "Status:", self.status
return self
def sell(self):
self.status = "Sold"
return self
def addTax(self, num):
self.cost = self.cost * (1+num)
return self
def Return(self, reason):
if reason == "Defective":
self.cost = 0
self.status = reason
elif reason == "Opened":
self.cost = self.cost * 0.80
self.status = "for sale"
elif reason == "Box":
self.status = "for sale"
return self
print "add items to inv"
product1 = product("Kona Dew", 499, 1.2, "Kona")
product2 = product("Kona Dew Plus", 799, 1.5, "Kona")
product3 = product("Kona Dr.Dew", 999, 1.2, "Kona")
product1.addTax(0.10)
product2.addTax(0.15)
product3.addTax(0.11)
print "add tax"
product1.displayInfo()
product2.displayInfo()
product3.displayInfo()
product1.sell()
product2.sell()
product3.sell()
print "sell items"
product1.displayInfo()
product2.displayInfo()
product3.displayInfo()
product1.Return("Defective")
product2.Return("Box")
product3.Return("Opened")
print "return items"
product1.displayInfo()
product2.displayInfo()
product3.displayInfo()
|
7,395 | a538c6d8c9f99bc37def5817a54c831393c051f3 | #!/usr/bin/python
try:
fh = open('testfile','w')
try:
fh.write('This is my test file for this exception')
finally:
print "Going to close file"
fh.close()
except IOError:
print" Error: can\'t find file or read data"
|
7,396 | 582cbacd26f4a3ed0b4f5c85af67758de7c05836 | ### To run the test use:
### python3 -m unittest test_script.py
import unittest
import re
class TestCustomerDetails(unittest.TestCase):
def test_cu_name(self):
### Our script has a class ConfigurationParser, which will have method ParseCuNames
cp = ConfigurationParser()
### expected names which is present on config.txt
exp_names= ['CUSTOMER_A','CUSTOMER_B']
### names return by our code
parsed_names = cp.ParseCuNames()
### Names returned by our code should be in list
self.assertEqual(list,type(parsed_names))
### Names returned by our code should be the same as expected names (exp_names)
self.assertEqual(exp_names,parsed_names)
def test_cust_vlan(self):
### Our script has a class ConfigurationParser, which will have method ParseCuNames
cp = ConfigurationParser()
### Example of the customer name from config.txt
cu_name = "CUSTOMER_A"
### Example of the vlan for CUSTOMER_A from config.txt
exp_vlan = ['100']
### ParseVlan will return a vlan number based on the give customer name
parsed_vlan = cp.ParseVlan(cu_name)
### Compare manually checked VLAN (exp_vlan) with the one calculated by the script (parsed_vlan)
self.assertEqual(exp_vlan,parsed_vlan)
class ConfigurationParser:
### my class which will implement the desired functionality
deviceConfig = open("config.txt","r").read()
def ParseCuNames(self):
### Regular expression to find the Customer name from 'ip vrf <Customer Name>' output
cuNamePattern = r"ip vrf ([a-zA-Z_]+)\n"
### findall with groups returns only matched group value.
cuNames = re.findall(cuNamePattern,deviceConfig)
return cuNames
def ParseVlan(self, cuName):
### Regex to find vlan number which is the same as sub interface number
intPattern=r"interface GigabitEthernet0\/0.([0-9]+)\n\s+encapsulation\s+dot1Q [0-9]+\n\s+ip vrf forwarding %s" % (cuName)
### Apply regex to the file to get vlan numbers
allCuSubInterfaces = re.findall(intPattern,deviceConfig)
return allCuSubInterfaces
|
7,397 | 0ebd3ca5fd29b0f2f2149dd162b37f39668f1c58 | from xgboost import XGBRegressor
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score
import pandas as pd
import numpy as np
from ghg import GHGPredictor
predictor = GHGPredictor()
dataset_df = pd.read_csv("db-wheat.csv", index_col=0)
# print(dataset_df.iloc[1])
dataset_df_2 = dataset_df.drop(columns=['Area', 'Year', 'Crop', 'Previous crop'])
# print(dataset_df_2)
dataset = dataset_df_2.to_numpy()
# print(dataset)
X, Y = dataset[:, :-1], dataset[:, -1:]
# print(X)
# print(Y)
seed = 10
test_size = 0.2
X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=test_size, random_state=seed)
# print(len(X_train))
# print(len(X_test))
# print(len(Y_train))
# print(len(Y_test))
model = XGBRegressor()
model.fit(X_train, Y_train)
# print(model)
print(dataset_df_2.columns)
print(model.feature_importances_)
# print(X_test.shape)
y_pred = model.predict(X_test)
# predictions = [round(value) for value in y_pred]
Y_test = map(lambda x: x[0], Y_test)
# print(Y_test)
res = zip(y_pred, Y_test)
# print(list(res))
ghg_predictor = GHGPredictor()
def predict(model, row):
preds = []
# print(row)
# print(row.).shape)
for perc in range(-10, 11):
new_row = row.copy()
row_copy = row.copy()
# new_row = new_row.iloc[0]
new_row = new_row.drop(labels=['Area', 'Year', 'Crop', 'Previous crop', 'Yield'])
# print(new_row.labels)
# new_row = new_row.tolist()
# print(new_row)
# print(type(new_row))
nitrogen = new_row['N'] * ((100 + perc) / 100)
new_row['N'] = nitrogen
row_copy['N'] = nitrogen
new_row = np.array([new_row])
# print(new_row)
pred = model.predict(new_row)
row_df = pd.DataFrame([row_copy])
fuel_ghg = predictor.fuel_ghg_emissions(row_df["Area"], unit="kg")
fuel_ghg = fuel_ghg.values[0]
ms_ghg = predictor.managed_soils_ghg(row_df['N'], row_df['Manure'], row_df['Area'], row_df['Crop'], row_df['Yield'])
ms_ghg = ms_ghg.values[0]
sum_ghg = fuel_ghg + ms_ghg
area = row_df['Area'].iloc[0]
# print(area)
# print(sum_ghg)
# print(row_df['N'])
# print(sum_ghg)
# GHG
# fuel = ghg_predictor.fuel_ghg_emissions()
preds.append([nitrogen, pred[0], sum_ghg])
print('{:4}% | Yield: {:.2f} | Area {} | C02_ha {:.5f} | C02 {:.5f}'.format(100 + perc, pred[0], area, sum_ghg / area, sum_ghg))
return preds
# accuracy = accuracy_score(Y_test, predictions)
# print("Accuracy: %.2f%%" % (accuracy * 100.0))
import random
rand_ind = random.randrange(0, len(dataset))
rand_row = dataset_df.iloc[rand_ind]
while rand_row['N'] == 0:
rand_ind = random.randrange(0, len(dataset))
rand_row = dataset_df.iloc[rand_ind]
# rand_row = rand_row[:-1]
preds = predict(model, rand_row)
import matplotlib.pyplot as plt
fig, ax1 = plt.subplots()
n_amount = [x[0] for x in preds]
yield_p = [x[1] for x in preds]
ghg_p = [x[2] for x in preds]
color = 'tab:red'
ax1.set_xlabel('N')
ax1.set_ylabel('Yield (t)', color=color)
ax1.set_title(f'GHG and yield predictions (Area: {rand_row["Area"]} ha)')
ax1.plot(n_amount, yield_p, color=color)
ax1.tick_params(axis='y', labelcolor=color)
ax2 = ax1.twinx() # instantiate a second axes that shares the same x-axis
color = 'tab:blue'
ax2.set_ylabel('CO2 (kg)', color=color) # we already handled the x-label with ax1
ax2.plot(n_amount, ghg_p, color=color)
ax2.tick_params(axis='y', labelcolor=color)
print(n_amount)
fig.tight_layout() # otherwise the right y-label is slightly clipped
plt.show()
|
7,398 | 7af19f69e6c419649a5999f594118ad13833a537 | # -*- coding: utf-8 -*-
"""
Created on Mon Aug 13 14:10:15 2018
9.5 项目：将一个文件夹备份到一个 ZIP 文件
@author: NEVERGUVEIP
"""
#! python3
import zipfile,os
def backupToZip(folder):
#backup the entire contents of 'folder' into a ZIP file
folder = os.path.abspath(folder)
os.chdir(folder)
#figure out the filename this code should use based on
#what files already exist.
number = 1
#从1循环检查文件名存不存在，_1.zip,_2.zip，，防止备份以前的备份文件
while True:
zipFilename = os.path.basename(folder) +'_'+str(number)+'.zip'
if not os.path.exists(zipFilename):
break
number = number +1
#creat the zip file
print('creating %s...'%(zipFilename))
backupZip = zipfile.ZipFile(zipFilename,'w')
#TODO: walk the entire folder tree and compress the files in each folder.
for foldername,subfolders,filenames in os.walk(folder):#
print('adding files in %s...'%(foldername))
#add the current folder to the zip file.
backupZip.write(foldername)
#add all the files in this folder to the ZIP file.
for filename in filenames:
newBase = os.path.basename(folder)+'_'
if filename.startswith(newBase) and filename.endswith('.zip'):
continue# don't backup the backup ZIP files
backupZip.write(os.path.join(foldername,filename))
backupZip.close()
print('......Done......')
#backupToZip(r'C:\Users\NEVERGUVEIP\Documents\GitHub\python_test')
backupToZip('.')
|
7,399 | d39965c3070ec25230b4d6977ff949b3db070ab6 | """
Add requests application (adding and managing add-requests)
"""
from flask import Blueprint
__author__ = 'Xomak'
add_requests = Blueprint('addrequests', __name__, template_folder='templates', )
from . import routes |
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