text stringlengths 0 1.05M | meta dict |
|---|---|
from .find_first import find_first
from noodles import (gather, schedule, unpack)
from typing import (Any, Callable, Iterable)
@schedule
def all(pred: Callable, xs: Iterable):
"""
Check whether all the elements of the iterable `xs`
fullfill predicate `pred`.
:param pred:
predicate function
... | {
"repo_name": "NLeSC/noodles",
"path": "noodles/patterns/functional_patterns.py",
"copies": "1",
"size": "2834",
"license": "apache-2.0",
"hash": -1316269530389409000,
"line_mean": 22.4214876033,
"line_max": 73,
"alpha_frac": 0.6443189838,
"autogenerated": false,
"ratio": 4.008486562942008,
"co... |
from findLocation import findLocation
import sys
import datetime
import time
from search import search
from time import mktime
from datetime import datetime
reload(sys)
sys.setdefaultencoding('UTF8')
def printResults(results,start,num):
if(num > len(results.items()) - 1):
num = len(results.items()) - 1
... | {
"repo_name": "bkach/TravelTerminal",
"path": "program.py",
"copies": "1",
"size": "3314",
"license": "mit",
"hash": 2256770382385308700,
"line_mean": 35.4175824176,
"line_max": 133,
"alpha_frac": 0.6182860591,
"autogenerated": false,
"ratio": 3.1682600382409176,
"config_test": false,
"has_no... |
from findSentence import sentenceGrab
from phoneticWords import findPhonetics
from phoneticIndex import findPhoneticIndex
from random import randint
from math import floor
import sys
def main():
library = sys.argv[1]
subject = sys.argv[2]
dictionary = "/usr/share/dict/words"
phonetics = findPhonetics... | {
"repo_name": "Jflinchum/pow-generator",
"path": "powGenerator.py",
"copies": "1",
"size": "1567",
"license": "mit",
"hash": -8027242550020417000,
"line_mean": 30.9795918367,
"line_max": 139,
"alpha_frac": 0.6432673899,
"autogenerated": false,
"ratio": 3.5532879818594103,
"config_test": false,
... |
from fine_mapping_pipeline.ucsc import snp_utilities
from collections import Iterator
class Snp:
"""
Class reperesents a SNP with a chromosome and position for use in downstream
analyses.
"""
def __init__(self, chrom, pos,rs_id):
self._chrom = chrom
self._pos = int(pos)
... | {
"repo_name": "smilefreak/fine_mapping_pipeline",
"path": "fine_mapping_pipeline/snp_list.py",
"copies": "2",
"size": "1762",
"license": "mit",
"hash": -7349742596642650000,
"line_mean": 25.2985074627,
"line_max": 95,
"alpha_frac": 0.5119182747,
"autogenerated": false,
"ratio": 3.6180698151950716... |
from fine_tune import *
import copy
import os
import preprocessing
import shutil
import time
submission_folder_path = "/tmp/submissions"
def generate_prediction(estimator,
X_train,
Y_train,
X_test,
submission_file_content... | {
"repo_name": "nixingyang/Kaggle-Competitions",
"path": "Claims Management/solution.py",
"copies": "1",
"size": "4190",
"license": "mit",
"hash": 5463515503203604000,
"line_mean": 38.9047619048,
"line_max": 110,
"alpha_frac": 0.5338902148,
"autogenerated": false,
"ratio": 4.132149901380671,
"co... |
from FingerCurled import FingerCurled
from FingerPosition import FingerPosition
from FingerDataFormation import FingerDataFormation
def determine_position(curled_positions, finger_positions, known_finger_poses, min_threshold):
obtained_positions = {}
for finger_pose in known_finger_poses:
score_at... | {
"repo_name": "dedoogong/asrada",
"path": "HandPose_Detector/DeterminePositions.py",
"copies": "1",
"size": "10158",
"license": "apache-2.0",
"hash": 1326346948913765000,
"line_mean": 34.2708333333,
"line_max": 112,
"alpha_frac": 0.586532782,
"autogenerated": false,
"ratio": 3.180338134001252,
... |
from fingered import *
import random
import csv
import sys
from plotgraph import *
import time
def run():
records = random.randrange(200, 1000)
inst3=Xf("r")
inst3.setStats(records,2,(2, random.randrange(50, 200)),[-1,0],[False,False],0,100000, 0.3 * records)
inst3.FormData()
inst4=Xf("s")
inst4.setStats(record... | {
"repo_name": "vishnuprathish/constrained-data-generator",
"path": "new.py",
"copies": "1",
"size": "3536",
"license": "apache-2.0",
"hash": -5183482203799492000,
"line_mean": 32.046728972,
"line_max": 186,
"alpha_frac": 0.7203054299,
"autogenerated": false,
"ratio": 2.7996832937450513,
"config... |
from fingered import *
import random
import csv
import sys
def caac():
records = random.randrange(200,500)
inst3=Xf("r")
inst3.setStats(records,2,(2,records/10),[-1,0],[False,False],0,40000)
inst3.FormData()
inst4=Xf("s")
inst4.setStats(100,2,(2,10),[-1,0],[False,True],0,40000)
inst4.FormData()
print inst3
... | {
"repo_name": "vishnuprathish/constrained-data-generator",
"path": "file1.py",
"copies": "1",
"size": "1614",
"license": "apache-2.0",
"hash": -7609737249368255000,
"line_mean": 18.6829268293,
"line_max": 123,
"alpha_frac": 0.6412639405,
"autogenerated": false,
"ratio": 2.412556053811659,
"conf... |
from fingerprint.tags.tagBase import Tag
from ua_parser import user_agent_parser
tor4 = "Tor 4.X"
tor5 = "Tor 5.X"
tor6 = "Tor 6.X"
torbrowser70 = "Tor Browser 7.0"
chrome = "Chrome"
firefox = "Firefox" #NB: A Tor browser cannot have the Firefox tag
edge = "Edge"
ie = "IE"
bot = "Bot"
others = "Other browsers"
class... | {
"repo_name": "amberlu/FP_Modified",
"path": "fingerprint/tags/browser.py",
"copies": "2",
"size": "1543",
"license": "mit",
"hash": 5099611781770617000,
"line_mean": 32.5434782609,
"line_max": 87,
"alpha_frac": 0.5605962411,
"autogenerated": false,
"ratio": 3.428888888888889,
"config_test": fa... |
from fingui import Entry, Menu
from glob import glob
class AutocompletePathEntry(Entry):
menu = None
def showSuggestions(self, newValue):
suggestions = glob(newValue + '*')
if not newValue or newValue[-1] != '/':
suggestions += glob(newValue + '/*')
if newValue in suggest... | {
"repo_name": "TaylorSMarks/FinGUI",
"path": "example.py",
"copies": "1",
"size": "1318",
"license": "mit",
"hash": 6310104233056217000,
"line_mean": 25.38,
"line_max": 112,
"alpha_frac": 0.5872534143,
"autogenerated": false,
"ratio": 3.7765042979942693,
"config_test": false,
"has_no_keywords... |
from finite_field_op import FiniteFieldNumber
class ExtendedGcdEuclidean:
def __init__(self, modulo_num, another_num):
self.r_list = list([modulo_num, another_num])
self.q_list = list([None, None])
self.x_list = list([FiniteFieldNumber(1, False), FiniteFieldNumber(0, False)])
self.... | {
"repo_name": "YcheLanguageStudio/PythonStudy",
"path": "crpytography/libs/extended_euclidean_poly.py",
"copies": "1",
"size": "1375",
"license": "mit",
"hash": -7900289893848566000,
"line_mean": 41.96875,
"line_max": 95,
"alpha_frac": 0.5941818182,
"autogenerated": false,
"ratio": 3.132118451025... |
from .finite import is_finite
from .groups import dihedral_group
from .insertion_encodable import InsertionEncodablePerms
from .polynomial import PolyPerms
from .symmetry import (
all_symmetry_sets,
antidiagonal_set,
complement_set,
inverse_set,
lex_min,
reverse_set,
rotate_90_clockwise_set,... | {
"repo_name": "PermutaTriangle/Permuta",
"path": "permuta/permutils/__init__.py",
"copies": "1",
"size": "1207",
"license": "bsd-3-clause",
"hash": -4924859480698235000,
"line_mean": 26.4318181818,
"line_max": 87,
"alpha_frac": 0.7166528583,
"autogenerated": false,
"ratio": 3.0869565217391304,
... |
from finsymbols import get_nasdaq_symbols, get_nyse_symbols, get_sp500_symbols
from pyhoofinance.defs import *
from pyhoofinance.historicdata import get_number_of_historical_quotes
from pyhoofinance.quotedata import get_quote, get_quotes
from datetime import datetime
class QuoteDataKeys:
"""
Mapping of pyhoof... | {
"repo_name": "innes213/TradingTools",
"path": "tradingtools/utils/equitydata.py",
"copies": "1",
"size": "3133",
"license": "bsd-2-clause",
"hash": 948313181270273900,
"line_mean": 32.6989247312,
"line_max": 89,
"alpha_frac": 0.646026173,
"autogenerated": false,
"ratio": 3.044703595724004,
"co... |
from finsymbols import get_nasdaq_symbols, get_nyse_symbols, get_sp500_symbols
from pyhoofinance.historicdata import get_number_of_historical_quotes
from datetime import datetime
class SymbolList:
SP500 = 'sp500'
NASDAQ = 'nasdaq' # sector and industry data are bad
NYSE = 'nyse'
class FinSymbolsKeys:
... | {
"repo_name": "innes213/TradingTools",
"path": "tradingtools/utils/utils.py",
"copies": "1",
"size": "1904",
"license": "bsd-2-clause",
"hash": -1213938264505288000,
"line_mean": 33.6363636364,
"line_max": 87,
"alpha_frac": 0.6202731092,
"autogenerated": false,
"ratio": 3.232597623089983,
"conf... |
from fiona.transform import transform_geom
from rasterio.crs import CRS
from shapely.errors import TopologicalError
from shapely.geometry import (
box,
GeometryCollection,
shape,
mapping,
MultiPoint,
MultiLineString,
MultiPolygon,
Polygon,
LinearRing,
LineString,
base,
)
from... | {
"repo_name": "ungarj/mapchete",
"path": "mapchete/io/_geometry_operations.py",
"copies": "1",
"size": "7811",
"license": "mit",
"hash": -4212262820877810000,
"line_mean": 28.5871212121,
"line_max": 88,
"alpha_frac": 0.6031237998,
"autogenerated": false,
"ratio": 4.0916710319539025,
"config_tes... |
from fipy.matrices.pysparseMatrix import _PysparseMeshMatrix
from fipy.solvers.solver import Solver
import numpy
from scipy.sparse import csr_matrix
from pyamg import smoothed_aggregation_solver
class PyAMGSolver(Solver):
"""
The PyAMGSolver class.
"""
def __init__(self, *args, **kwargs):
if k... | {
"repo_name": "pombreda/pyamg",
"path": "Examples/FiPyFormulation/PyAMGSolver.py",
"copies": "1",
"size": "1767",
"license": "bsd-3-clause",
"hash": 7439504531513543000,
"line_mean": 27.9672131148,
"line_max": 72,
"alpha_frac": 0.5834748161,
"autogenerated": false,
"ratio": 3.7044025157232703,
... |
from fireant.dataset.fields import Field
from fireant.dataset.klass import DataSet
from fireant.queries.builder import (
DataSetBlenderQueryBuilder,
DimensionChoicesQueryBuilder,
)
from fireant.utils import (
deepcopy,
immutable,
ordered_distinct_list_by_attr,
)
def _wrap_dataset_fields(dataset):
... | {
"repo_name": "mikeengland/fireant",
"path": "fireant/dataset/data_blending.py",
"copies": "2",
"size": "6200",
"license": "apache-2.0",
"hash": 1165744871279244300,
"line_mean": 36.5757575758,
"line_max": 120,
"alpha_frac": 0.6683870968,
"autogenerated": false,
"ratio": 4.3175487465181055,
"co... |
from fireant.dataset.references import DayOverDay
from unittest import TestCase
from fireant import (
DaysOverDays,
DayOverDay,
WeeksOverWeeks,
WeekOverWeek,
MonthsOverMonths,
MonthOverMonth,
QuartersOverQuarters,
QuarterOverQuarter,
YearsOverYears,
YearOverYear,
)
class Cumul... | {
"repo_name": "mikeengland/fireant",
"path": "fireant/tests/dataset/test_references.py",
"copies": "2",
"size": "3216",
"license": "apache-2.0",
"hash": -3303306314306054700,
"line_mean": 38.2195121951,
"line_max": 90,
"alpha_frac": 0.6831467662,
"autogenerated": false,
"ratio": 3.510917030567686... |
from fireant.dataset.totals import Rollup
from .finders import find_filters_for_totals
def adapt_for_totals_query(totals_dimension, dimensions, filters):
"""
Adapt filters for totals query. This function will select filters for total dimensions depending on the
apply_filter_to_totals values for the filter... | {
"repo_name": "kayak/fireant",
"path": "fireant/queries/totals_helper.py",
"copies": "2",
"size": "1151",
"license": "apache-2.0",
"hash": -1474311748336042500,
"line_mean": 41.6296296296,
"line_max": 118,
"alpha_frac": 0.7410947003,
"autogenerated": false,
"ratio": 4.343396226415094,
"config_t... |
from firebase_admin import messaging
from firebase_admin.exceptions import FirebaseError, InvalidArgumentError, InternalError, UnavailableError
from firebase_admin.messaging import QuotaExceededError, SenderIdMismatchError, ThirdPartyAuthError, UnregisteredError
from mock import patch, Mock, ANY
import unittest2
from... | {
"repo_name": "bdaroz/the-blue-alliance",
"path": "tests/helpers_tests/test_tbans_helper.py",
"copies": "1",
"size": "33235",
"license": "mit",
"hash": 8154617465720894000,
"line_mean": 43.730820996,
"line_max": 158,
"alpha_frac": 0.620851512,
"autogenerated": false,
"ratio": 3.994111284701358,
... |
from firebase_admin import messaging
from models.notifications.requests.request import Request
# Fix positional argument warnings - can remove once we upgrade to firebase-admin=4.0.0
from googleapiclient import _helpers
_helpers.positional_parameters_enforcement = _helpers.POSITIONAL_IGNORE
MAXIMUM_TOKENS = 500
c... | {
"repo_name": "phil-lopreiato/the-blue-alliance",
"path": "models/notifications/requests/fcm_request.py",
"copies": "2",
"size": "3997",
"license": "mit",
"hash": 5252739702191778000,
"line_mean": 42.9230769231,
"line_max": 108,
"alpha_frac": 0.6735051288,
"autogenerated": false,
"ratio": 4.32575... |
from firebase.firebase import FirebaseApplication
from exceptions import SQLError, ValidationError
__all__ = [
'Adaptor',
'ModelManager',
'SyncManager'
]
class Adaptor(object):
"""Manager for one db instance
"""
def __init__(self, session, fire_url):
"""Init adaptor
Args:
... | {
"repo_name": "newpro/firebase-alchemy",
"path": "firebase_alchemy/manager.py",
"copies": "1",
"size": "8179",
"license": "mit",
"hash": -2891335472497356300,
"line_mean": 37.2196261682,
"line_max": 112,
"alpha_frac": 0.5647389656,
"autogenerated": false,
"ratio": 4.508820286659317,
"config_tes... |
from firebase import FirebaseApplication, FirebaseAuthentication
#from firebase import Firebase
import firebase
from celery.decorators import task
from ansible import utils
import ansible.runner, json, os
@task()
def ansible_jeneric_testing(job_id):
# firebase authentication
SECRET = os.environ['SECRET']
... | {
"repo_name": "rackeric/destiny",
"path": "dcelery/tasks.py",
"copies": "1",
"size": "6462",
"license": "apache-2.0",
"hash": 5674261442190208000,
"line_mean": 29.0558139535,
"line_max": 120,
"alpha_frac": 0.6505725781,
"autogenerated": false,
"ratio": 3.6385135135135136,
"config_test": false,
... |
from firebase import firebase
from django.conf import settings
from funcy import mapcat, walk
from time import time
import logging
logger = logging.getLogger('workers')
APPLICANTS_KEY = 'applicants'
def fb_url(base):
return "https://%s.firebaseio.com/" % base
fauth = firebase.FirebaseAuthentication(settings.FIR... | {
"repo_name": "popara/jonny-api",
"path": "firestone/__init__.py",
"copies": "1",
"size": "1402",
"license": "mit",
"hash": 5205715791337464000,
"line_mean": 21.253968254,
"line_max": 101,
"alpha_frac": 0.6476462197,
"autogenerated": false,
"ratio": 2.976645435244161,
"config_test": false,
"h... |
from firebase import firebase
from multiprocessing import Pool
from psycopg2 import connect
from psycopg2.extensions import QuotedString
import requests
import time
def postgres_escape(result, column):
if column in ["type", "by", "url", "title", "text"]:
try:
return QuotedString(result[column].... | {
"repo_name": "benhamner/hacker-news-scrape",
"path": "src/scrape.py",
"copies": "1",
"size": "3496",
"license": "bsd-3-clause",
"hash": -879524862577390700,
"line_mean": 37,
"line_max": 158,
"alpha_frac": 0.5629290618,
"autogenerated": false,
"ratio": 3.6530825496342736,
"config_test": false,
... |
from firebase import firebase
from Utils import LoggingManager
from Settings import DefineManager
firebaseDatabase = None
def GetFirebaseConnection(firebaseAddress = ""):
global firebaseDatabase
LoggingManager.PrintLogMessage("FirebaseDatabaseManager", "GetFirebaseConnection", "getting firebase connection", ... | {
"repo_name": "I2MAX-LearningProject/Flask-server",
"path": "Core/FirebaseDatabaseManager.py",
"copies": "1",
"size": "8253",
"license": "mit",
"hash": 3701331219018266000,
"line_mean": 49.6319018405,
"line_max": 214,
"alpha_frac": 0.7202229492,
"autogenerated": false,
"ratio": 4.254123711340206,... |
from firebase import firebase
import config
CONFIG_FILE_PATH = "/root/data/dash-board/docker/config.ini"
def main():
appconfig = config.getConfiguration(CONFIG_FILE_PATH)
if appconfig is None:
message = "Error parsing config file"
raise Exception(message)
print appconfig
required_con... | {
"repo_name": "mjsrs/dash-board",
"path": "docker/database_maintenance.py",
"copies": "1",
"size": "1447",
"license": "mit",
"hash": -3336942948880208400,
"line_mean": 38.1081081081,
"line_max": 116,
"alpha_frac": 0.6530753283,
"autogenerated": false,
"ratio": 3.7780678851174936,
"config_test":... |
from firebase import firebase
import ENV_VAR as ENV
fb = firebase.FirebaseApplication(ENV.FIREBASE_LINK, None)
def contact_list_extractor(group="default"):
contact_list = {}
user_data = fb.get("/user", None)
if group == "default":
contact_list["user"] = extract_user_contact(user_data)
con... | {
"repo_name": "leglars/ThinkingofYou",
"path": "AM-flask/app/dbAPI.py",
"copies": "1",
"size": "4795",
"license": "mit",
"hash": 4992062184912303000,
"line_mean": 28.237804878,
"line_max": 101,
"alpha_frac": 0.5685088634,
"autogenerated": false,
"ratio": 3.7578369905956115,
"config_test": false... |
from firebase import firebase
import os
import datetime
import json
import logging
from boto.s3.connection import S3Connection
from boto.s3.key import Key
## FIREBASE ACCESS INFO ##
firebase_url = 'https://your-app.firebaseio.com/' #Or get from environment variable
firebase_secret = os.environ['FIREBASE_SECRET']
fireb... | {
"repo_name": "designed27/firebase-backup-s3-python",
"path": "backup-firebase.py",
"copies": "1",
"size": "1486",
"license": "mit",
"hash": 8466622801061996000,
"line_mean": 28.137254902,
"line_max": 102,
"alpha_frac": 0.7281292059,
"autogenerated": false,
"ratio": 3.1549893842887475,
"config_... |
from firebase import firebase
import os
import datetime
import json
import logging
from boto.s3.connection import S3Connection
from boto.s3.key import Key
# Firebase Access Info
firebase_url = os.environ['FIREBASE_URL']
firebase_secret = os.environ['FIREBASE_SECRET']
firebase_username = os.environ['FIREBASE_USERNAME']... | {
"repo_name": "ericcecchi/whichcraft-backup",
"path": "backup-firebase.py",
"copies": "1",
"size": "1278",
"license": "mit",
"hash": 3039324734757601000,
"line_mean": 26.1914893617,
"line_max": 102,
"alpha_frac": 0.7316118936,
"autogenerated": false,
"ratio": 3.021276595744681,
"config_test": f... |
from firebase import firebase
import subprocess
import json
import datetime
import requests
import config
CONFIG_FILE_PATH = "/root/data/dash-board/docker/mjsrsconfig.ini"
def chunks(s, n):
for start in range(0, len(s), n):
yield s[start:start+n]
def get_price(request, exchange, market):
exchanges ... | {
"repo_name": "mjsrs/dash-board",
"path": "docker/mjsrssync.py",
"copies": "1",
"size": "6993",
"license": "mit",
"hash": 252697911639358,
"line_mean": 40.874251497,
"line_max": 165,
"alpha_frac": 0.5994565995,
"autogenerated": false,
"ratio": 3.333174451858913,
"config_test": true,
"has_no_k... |
from firebase import firebase
import sys
import requests
import MySQLdb
import json
def readFile():
with open("Isbn_Txt_Files/list_of_1000_isbn.txt") as file:
isbnArray = file.read().splitlines()
return isbnArray
def connectToBookUp():
try:
db = MySQLdb.connect(unix_socket ="/Application... | {
"repo_name": "aryamccarthy/Bookup",
"path": "Web_App/Database/Firebase/manageDatabase.py",
"copies": "1",
"size": "4755",
"license": "mit",
"hash": 3665302702415772000,
"line_mean": 23.0151515152,
"line_max": 143,
"alpha_frac": 0.5457413249,
"autogenerated": false,
"ratio": 3.8879803761242844,
... |
from firebase import firebase
class CreatePatient:
def __init__(self,patient_username,patient_password,patient_name,patient_phone_number,patient_insurance,patient_address):
self.user_username=patient_username
self.user_password=patient_password
self.user_name=patient_name
self.user_number=patient_phone_number... | {
"repo_name": "IT-Department-Projects/OOAD-Project",
"path": "Flask_App/admin_application.py",
"copies": "1",
"size": "7817",
"license": "mit",
"hash": 6940179494701577000,
"line_mean": 31.3016528926,
"line_max": 139,
"alpha_frac": 0.6986056032,
"autogenerated": false,
"ratio": 2.948698604300264,... |
from firebase import firebase
import pyrebase
config = {
"apiKey": "AIzaSyDiL1XGJxQqqd8WCnwx6FQvzapSphklSmk",
"authDomain": "tardy-ccd34.firebaseapp.com",
"databaseURL": "https://tardy-ccd34.firebaseio.com",
"storageBucket": "tardy-ccd34.appspot.com",
"serviceAccount": "tardy-ccd34-firebase-admins... | {
"repo_name": "MaxLinCode/tardy-HackIllinois-2017",
"path": "backend/loadData.py",
"copies": "1",
"size": "2055",
"license": "mit",
"hash": 8236236500253992000,
"line_mean": 28.3571428571,
"line_max": 91,
"alpha_frac": 0.6082725061,
"autogenerated": false,
"ratio": 2.9869186046511627,
"config_t... |
from firebase import firebase
import builtins #I'm so sorry
def update():
fb = firebase.FirebaseApplication("https://adamtestbotstats.firebaseio.com", None)
blazeDb = []
btcLedger = []
stocks = []
K = list()
for user in builtins.blazeDB:
K.append(user)
sortedK = sorted(K,... | {
"repo_name": "noisemaster/AdamTestBot",
"path": "src/atbFirebase.py",
"copies": "2",
"size": "1714",
"license": "mit",
"hash": 4781987177070474000,
"line_mean": 35.2608695652,
"line_max": 86,
"alpha_frac": 0.5297549592,
"autogenerated": false,
"ratio": 3.541322314049587,
"config_test": false,
... |
from firebase_repo import FirebaseRepo
from utils import TimeUtils
class OccupancyRatesRepository(FirebaseRepo):
__occupancy_rates_ODS_node_name = 'parkingArea'
__occupancy_rate_node_name = 'occupancyRate'
__unknown_occupancy_value = 'UNKNOWN'
def __init__(self):
FirebaseRepo.__init__(self)
... | {
"repo_name": "DriverCity/SPARK",
"path": "src/cloud/occupancy_rates_repo.py",
"copies": "1",
"size": "2295",
"license": "mit",
"hash": -1335204851545858300,
"line_mean": 37.8983050847,
"line_max": 106,
"alpha_frac": 0.5694989107,
"autogenerated": false,
"ratio": 3.7135922330097086,
"config_tes... |
from firecares.celery import app
from django.db import connection
from django.core.mail import mail_admins
@app.task(queue='email')
def send_mail(email):
"""
Asynchronously sends an email.
"""
return email.send()
@app.task(queue='email')
def email_admins(subject, message):
"""
Asynchronously... | {
"repo_name": "FireCARES/firecares",
"path": "firecares/tasks/email.py",
"copies": "1",
"size": "1197",
"license": "mit",
"hash": -4258577998758138400,
"line_mean": 27.5,
"line_max": 109,
"alpha_frac": 0.6700083542,
"autogenerated": false,
"ratio": 3.6717791411042944,
"config_test": false,
"h... |
from firecares.celery import app
from django.db import connections
from django.db.utils import ConnectionDoesNotExist
from firecares.firestation.models import create_quartile_views
from firecares.firestation.models import FireDepartment, create_quartile_views
from firecares.firestation.models import NFIRSStatistic as n... | {
"repo_name": "meilinger/firecares",
"path": "firecares/tasks/update.py",
"copies": "1",
"size": "4715",
"license": "mit",
"hash": 2316477026073225000,
"line_mean": 35.5503875969,
"line_max": 170,
"alpha_frac": 0.6513255567,
"autogenerated": false,
"ratio": 3.5910129474485912,
"config_test": fa... |
from firecares.celery import app
from django.db import connections
from django.db.utils import ConnectionDoesNotExist
from firecares.firestation.models import FireDepartment, create_quartile_views
from firecares.firestation.models import NFIRSStatistic as nfirs
from fire_risk.models import DIST, NotEnoughRecords
from f... | {
"repo_name": "HunterConnelly/firecares",
"path": "firecares/tasks/update.py",
"copies": "1",
"size": "5206",
"license": "mit",
"hash": -3104654375455096000,
"line_mean": 35.1527777778,
"line_max": 151,
"alpha_frac": 0.6509796389,
"autogenerated": false,
"ratio": 3.4753004005340453,
"config_tes... |
from firecares.celery import app
from firecares.firestation.models import FireDepartment
from django.db import connection
from django.core.mail import mail_admins
@app.task(queue='email')
def send_mail(email):
"""
Asynchronously sends an email.
"""
return email.send()
@app.task(queue='email')
def ens... | {
"repo_name": "meilinger/firecares",
"path": "firecares/tasks/email.py",
"copies": "1",
"size": "1085",
"license": "mit",
"hash": -2273051085014052900,
"line_mean": 30.9411764706,
"line_max": 109,
"alpha_frac": 0.6838709677,
"autogenerated": false,
"ratio": 3.7030716723549486,
"config_test": fa... |
from firecares.firestation.models import FireStation
from django.db import transaction
from django.core.management.base import BaseCommand
def batch_qs(qs, batch_size=1000):
"""
Returns a (start, end, total, queryset) tuple for each batch in the given
queryset.
"""
total = qs.count()
for star... | {
"repo_name": "meilinger/firecares",
"path": "firecares/firestation/management/commands/set_departments.py",
"copies": "2",
"size": "2603",
"license": "mit",
"hash": -1067951829015098800,
"line_mean": 30.743902439,
"line_max": 91,
"alpha_frac": 0.4817518248,
"autogenerated": false,
"ratio": 4.758... |
from firecares.settings.base import *
INSTALLED_APPS += ('debug_toolbar', 'fixture_magic')
MIDDLEWARE_CLASSES += ('debug_toolbar.middleware.DebugToolbarMiddleware', )
# The Django Debug Toolbar will only be shown to these client IPs.
INTERNAL_IPS = (
'127.0.0.1',
)
DEBUG_TOOLBAR_CONFIG = {
'INTERCEPT_REDIRE... | {
"repo_name": "meilinger/firecares",
"path": "firecares/settings/local.py",
"copies": "1",
"size": "1150",
"license": "mit",
"hash": -7401269204783604000,
"line_mean": 20.2962962963,
"line_max": 75,
"alpha_frac": 0.6339130435,
"autogenerated": false,
"ratio": 3.314121037463977,
"config_test": f... |
from firecares.settings.base import *
INSTALLED_APPS += ('debug_toolbar', 'fixture_magic')
MIDDLEWARE_CLASSES += ('debug_toolbar.middleware.DebugToolbarMiddleware', )
# The Django Debug Toolbar will only be shown to these client IPs.
INTERNAL_IPS = (
'127.0.0.1',
)
DEBUG_TOOLBAR_CONFIG = {
'INTERCEPT_REDIR... | {
"repo_name": "garnertb/firecares",
"path": "firecares/settings/local.py",
"copies": "1",
"size": "1033",
"license": "mit",
"hash": -1398044133099406300,
"line_mean": 19.66,
"line_max": 75,
"alpha_frac": 0.6553727009,
"autogenerated": false,
"ratio": 3.2586750788643535,
"config_test": false,
... |
from firecares.settings.base import * # noqa
INSTALLED_APPS += ('debug_toolbar', 'fixture_magic', 'django_extensions') # noqa
MIDDLEWARE_CLASSES += ('debug_toolbar.middleware.DebugToolbarMiddleware', ) # noqa
# The Django Debug Toolbar will only be shown to these client IPs.
INTERNAL_IPS = (
'127.0.0.1',
)
D... | {
"repo_name": "HunterConnelly/firecares",
"path": "firecares/settings/local.py",
"copies": "1",
"size": "1203",
"license": "mit",
"hash": 1639746608679952100,
"line_mean": 21.2777777778,
"line_max": 83,
"alpha_frac": 0.6325852037,
"autogenerated": false,
"ratio": 3.3140495867768593,
"config_tes... |
from firecares.settings.base import * # noqa
INSTALLED_APPS.extend(['debug_toolbar', 'fixture_magic', 'django_extensions']) # noqa
for i, app in enumerate(INSTALLED_APPS):
if app == 'django.contrib.staticfiles':
insert_point = i
INSTALLED_APPS.insert(insert_point,'whitenoise.runserver_nostatic')
MIDDLE... | {
"repo_name": "FireCARES/firecares",
"path": "firecares/settings/local.py",
"copies": "1",
"size": "2469",
"license": "mit",
"hash": 8537624881259391000,
"line_mean": 25.2659574468,
"line_max": 85,
"alpha_frac": 0.6123936817,
"autogenerated": false,
"ratio": 3.292,
"config_test": false,
"has_... |
from firecares.tasks.update import update_nfirs_counts
from django.core.management.base import BaseCommand
from firecares.firestation.models import FireDepartment, FireStation
from firecares.firecares_core.models import Address
from django.db import transaction
from django.contrib.gis.geos import Point
from datetime im... | {
"repo_name": "garnertb/firecares",
"path": "firecares/firestation/management/commands/add_station.py",
"copies": "2",
"size": "3674",
"license": "mit",
"hash": -3004372515782548000,
"line_mean": 38.085106383,
"line_max": 130,
"alpha_frac": 0.5255851932,
"autogenerated": false,
"ratio": 5.0745856... |
from firedrake import (Constant, Function, FunctionSpace,
NonlinearVariationalProblem, NonlinearVariationalSolver, TestFunction,
VectorFunctionSpace, dot, dx, grad, inner, nabla_grad, assemble, TrialFunction)
from .util import *
class EnergyEq(object):
def __init__(se... | {
"repo_name": "JuLuSi/incflow",
"path": "incflow/energy_eq.py",
"copies": "1",
"size": "2914",
"license": "mit",
"hash": -4831427137776015000,
"line_mean": 27.8514851485,
"line_max": 102,
"alpha_frac": 0.5288263555,
"autogenerated": false,
"ratio": 3.2163355408388523,
"config_test": false,
"h... |
from firedrake import dx, BrokenElement, Function, FunctionSpace
from firedrake.parloops import par_loop, READ, WRITE, INC
from firedrake.slope_limiter.vertex_based_limiter import VertexBasedLimiter
__all__ = ["ThetaLimiter", "NoLimiter"]
class ThetaLimiter(object):
"""
A vertex based limiter for fields in t... | {
"repo_name": "firedrakeproject/dcore",
"path": "gusto/limiters.py",
"copies": "2",
"size": "6705",
"license": "mit",
"hash": 7989098233306268000,
"line_mean": 41.4367088608,
"line_max": 96,
"alpha_frac": 0.5021625652,
"autogenerated": false,
"ratio": 4.046469523234761,
"config_test": false,
... |
from firedrake import *
from firedrake.assemble import create_assembly_callable
from firedrake.utils import cached_property
from pyop2.profiling import timed_region
import base
class HDGProblem(base.Problem):
name = "HDG Helmholtz"
def __init__(self, N, degree, quadrilaterals, dimension):
super(HDG... | {
"repo_name": "thomasgibson/tabula-rasa",
"path": "HDG_CG_comp/hdg_problem.py",
"copies": "1",
"size": "4511",
"license": "mit",
"hash": -5152647373457586000,
"line_mean": 29.0733333333,
"line_max": 75,
"alpha_frac": 0.5508756373,
"autogenerated": false,
"ratio": 3.5491738788355627,
"config_tes... |
from firedrake import *
from firedrake import op2
from firedrake.petsc import PETSc
from argparse import ArgumentParser
import pandas as pd
import numpy as np
import sys
def fmax(f):
fmax = op2.Global(1, np.finfo(float).min, dtype=float)
op2.par_loop(op2.Kernel("""
static void maxify(double *a, double *b) {
... | {
"repo_name": "thomasgibson/firedrake-hybridization",
"path": "convergence_tests/williamson_2.py",
"copies": "1",
"size": "12566",
"license": "mit",
"hash": -880120155572536800,
"line_mean": 32.1556728232,
"line_max": 95,
"alpha_frac": 0.5028648735,
"autogenerated": false,
"ratio": 3.256284011401... |
from firedrake import *
from firedrake.petsc import PETSc
from argparse import ArgumentParser
import sys
parser = ArgumentParser(description="""Linear gravity wave system.""",
add_help=False)
parser.add_argument("--refinements",
default=4,
type=int,
... | {
"repo_name": "thomasgibson/firedrake-hybridization",
"path": "gravity_wave/gravity_waves.py",
"copies": "1",
"size": "6369",
"license": "mit",
"hash": 3449947399513546000,
"line_mean": 29.3285714286,
"line_max": 85,
"alpha_frac": 0.5675930287,
"autogenerated": false,
"ratio": 2.9418013856812935,... |
from firedrake import *
from firedrake.petsc import PETSc
from argparse import ArgumentParser
parser = ArgumentParser(description=("""
Williamson 5 test case.
"""), add_help=False)
parser.add_argument("--refinements",
default=3,
type=int,
action="store",
... | {
"repo_name": "thomasgibson/firedrake-hybridization",
"path": "williamson_tests/williamson_5_mod.py",
"copies": "1",
"size": "7405",
"license": "mit",
"hash": 584388462201109000,
"line_mean": 32.5067873303,
"line_max": 92,
"alpha_frac": 0.5281566509,
"autogenerated": false,
"ratio": 3.11658249158... |
from firedrake import *
from firedrake.petsc import PETSc
from firedrake.utils import cached_property
from pyop2.profiling import timed_stage
import numpy as np
from solver import GravityWaveSolver
def fmax(f):
fmax = op2.Global(1, np.finfo(float).min, dtype=float)
op2.par_loop(op2.Kernel("""
void maxify(doub... | {
"repo_name": "thomasgibson/tabula-rasa",
"path": "gravity_waves/problem.py",
"copies": "1",
"size": "10588",
"license": "mit",
"hash": 5496528880040669000,
"line_mean": 34.2933333333,
"line_max": 93,
"alpha_frac": 0.5156781262,
"autogenerated": false,
"ratio": 3.512939615129396,
"config_test":... |
from firedrake import *
from firedrake.petsc import PETSc
from firedrake.utils import cached_property
from pyop2.profiling import timed_stage
import numpy as np
def fmax(f):
fmax = op2.Global(1, np.finfo(float).min, dtype=float)
op2.par_loop(op2.Kernel("""
void maxify(double *a, double *b) {
a[0] = a[0] <... | {
"repo_name": "thomasgibson/tabula-rasa",
"path": "SWE/solver.py",
"copies": "1",
"size": "15689",
"license": "mit",
"hash": 6202320406922927000,
"line_mean": 31.4824016563,
"line_max": 79,
"alpha_frac": 0.4804640194,
"autogenerated": false,
"ratio": 3.5303780378037803,
"config_test": false,
... |
from firedrake import *
from firedrake.petsc import PETSc
from function_spaces import construct_spaces
from ksp_monitor import KSPMonitor
from solver import GravityWaveSolver
from argparse import ArgumentParser
import math
import numpy as np
import sys
PETSc.Log.begin()
parser = ArgumentParser(description="""Linear g... | {
"repo_name": "thomasgibson/firedrake-hybridization",
"path": "gravity_wave/gw-3d.py",
"copies": "1",
"size": "7097",
"license": "mit",
"hash": -2349264853906094000,
"line_mean": 29.8565217391,
"line_max": 99,
"alpha_frac": 0.5478371143,
"autogenerated": false,
"ratio": 3.330361332707649,
"conf... |
from firedrake import *
from firedrake.petsc import PETSc
from slepc4py import SLEPc
# Geometry
Lx = 1. # Zonal length
Ly = 1. # Meridonal length
n0 = 25 # Spatial resolution
mesh = Re... | {
"repo_name": "francispoulin/firedrakeQG",
"path": "basin_modes_qg.py",
"copies": "1",
"size": "2574",
"license": "mit",
"hash": 7697168574102122000,
"line_mean": 23.9902912621,
"line_max": 85,
"alpha_frac": 0.6258741259,
"autogenerated": false,
"ratio": 2.8568257491675917,
"config_test": false... |
from firedrake import *
from firedrake.petsc import PETSc
from slepc4py import SLEPc
#OPERATORS
zcross = lambda i: as_vector((-i[1],i[0]))
#gradperp = lambda i: as_vector((-i.dx(1),i.dx(0)))
# Geometry
Lx = 1. # Zonal length
Ly = 1. ... | {
"repo_name": "francispoulin/firedrakeQG",
"path": "basin_modes_sw.py",
"copies": "1",
"size": "2558",
"license": "mit",
"hash": 3978635479161646000,
"line_mean": 27.4222222222,
"line_max": 75,
"alpha_frac": 0.6145426114,
"autogenerated": false,
"ratio": 2.7654054054054056,
"config_test": false... |
from firedrake import *
from firedrake.utils import cached_property
from pyop2.profiling import timed_stage
import numpy as np
from solver import GravityWaveSolver
def fmax(f):
fmax = op2.Global(1, np.finfo(float).min, dtype=float)
op2.par_loop(op2.Kernel("""
void maxify(double *a, double *b) {
a[0] = a[0... | {
"repo_name": "thomasgibson/tabula-rasa",
"path": "gravity_waves/profile_problem.py",
"copies": "1",
"size": "7450",
"license": "mit",
"hash": -1707446404575641600,
"line_mean": 33.1743119266,
"line_max": 87,
"alpha_frac": 0.5483221477,
"autogenerated": false,
"ratio": 3.444290337494221,
"confi... |
from firedrake import *
from firedrake.utils import cached_property
import base
class CGProblem(base.Problem):
name = "CG Helmholtz"
@cached_property
def function_space(self):
return FunctionSpace(self.mesh, "CG", self.degree)
@cached_property
def u(self):
return Function(self.... | {
"repo_name": "thomasgibson/tabula-rasa",
"path": "HDG_CG_comp/cg_problem.py",
"copies": "1",
"size": "1850",
"license": "mit",
"hash": 8629256558186416000,
"line_mean": 25.0563380282,
"line_max": 72,
"alpha_frac": 0.5875675676,
"autogenerated": false,
"ratio": 3.5576923076923075,
"config_test"... |
from firedrake import *
from petsc4py import PETSc
class AssembledSchurPC(PCBase):
"""
Preconditioner for the Schur complement
The preconditioner matrix is assembled by explicitly matrix multiplying
:math:`A10*Minv*A10`.
Here:
- :math:`A01`, :math:`A10` are the assembled sub-blocks of the s... | {
"repo_name": "tkarna/cofs",
"path": "thetis/assembledschur.py",
"copies": "1",
"size": "3374",
"license": "mit",
"hash": 5326043413033693000,
"line_mean": 36.9101123596,
"line_max": 161,
"alpha_frac": 0.6138114997,
"autogenerated": false,
"ratio": 3.168075117370892,
"config_test": false,
"ha... |
from firedrake import *
from pyop2.profiling import timed_stage
__all__ = ['GravityWaveSolver']
class GravityWaveSolver(object):
def __init__(self, W2, W3, Wb, dt, c, N, khat,
coriolis,
maxiter=1000, tolerance=1.E-6,
hybridization=False,
monit... | {
"repo_name": "thomasgibson/tabula-rasa",
"path": "gravity_waves/solver.py",
"copies": "1",
"size": "6061",
"license": "mit",
"hash": 2404975495059962000,
"line_mean": 32.6722222222,
"line_max": 79,
"alpha_frac": 0.4552054116,
"autogenerated": false,
"ratio": 3.5927682276229995,
"config_test": ... |
from firedrake import *
import numpy as np
<<<<<<< HEAD
import matplotlib.pyplot as plt
=======
#import matplotlib.pyplot as plt
>>>>>>> 61ee2dee86887d2fb8938c6229f63272ab31d0f1
# Geometry
Lx = 1. # Zonal length
Ly = 1. # Merid... | {
"repo_name": "francispoulin/firedrakeQG",
"path": "linear_stommel_qg.py",
"copies": "1",
"size": "2637",
"license": "mit",
"hash": 6393491093489087000,
"line_mean": 30.0235294118,
"line_max": 95,
"alpha_frac": 0.5764125901,
"autogenerated": false,
"ratio": 3.1580838323353295,
"config_test": fa... |
from firedrake import *
import numpy as np
import matplotlib.pyplot as plt
# Operators
zcross = lambda u: as_vector((-u[1], u[0]))
gradperp = lambda u: as_vector((-u.dx(1), u.dx(0)))
# Geometry
Lx = 1.0
Ly = 1.0
n0 = 25
mesh = RectangleMesh(n0, n0, Lx, Ly, reorder=None)
# Function and Vector Spaces
Vdg = Fini... | {
"repo_name": "francispoulin/firedrakeQG",
"path": "linear_stommel_sw.py",
"copies": "1",
"size": "2584",
"license": "mit",
"hash": 7808204862360423000,
"line_mean": 25.6391752577,
"line_max": 109,
"alpha_frac": 0.5913312693,
"autogenerated": false,
"ratio": 2.7286166842661035,
"config_test": f... |
from firedrake import *
import numpy as np
import ufl
#import matplotlib.pyplot as plt
# Geometry
Lx = 1. # Zonal length
Ly = 1. # Meridonal length
n0 = 50 # Spatial resolution
mesh =... | {
"repo_name": "francispoulin/firedrakeQG",
"path": "linear_munk_qg.py",
"copies": "1",
"size": "2757",
"license": "mit",
"hash": -1113283490273471700,
"line_mean": 29.2967032967,
"line_max": 113,
"alpha_frac": 0.5723612622,
"autogenerated": false,
"ratio": 3.161697247706422,
"config_test": fals... |
from firedrake import *
import numpy as np
degree = 1
quadrilateral = True
# Parameters for Gaussian.
a = 6
sigma = 5
c = 50.
def gaussian(x):
return a * np.exp(-((x-50.)**2)/(2*sigma**2))
def function_space(mesh, degree, quadrilateral):
"""Create the required mixed function space."""
if quadrilatera... | {
"repo_name": "dham/idealised_coast",
"path": "coast.py",
"copies": "1",
"size": "2204",
"license": "mit",
"hash": -2414886868423000600,
"line_mean": 24.3333333333,
"line_max": 87,
"alpha_frac": 0.5367513612,
"autogenerated": false,
"ratio": 2.990502035278155,
"config_test": false,
"has_no_ke... |
from firedrake import *
import numpy as np
#OPERATORS
gradperp = lambda i: as_vector((-i.dx(1),i.dx(0)))
# Geometry
Lx = 1. # Zonal length
Ly = 1. # Meridonal length
n0 = 20 # Spatial... | {
"repo_name": "francispoulin/firedrakeQG",
"path": "fofonoff_qg.py",
"copies": "1",
"size": "2880",
"license": "mit",
"hash": 8583986104031612000,
"line_mean": 31.7272727273,
"line_max": 95,
"alpha_frac": 0.5413194444,
"autogenerated": false,
"ratio": 3.482466747279323,
"config_test": false,
... |
from firedrake import *
import os
import sys
import pandas as pd
import seaborn
import matplotlib
import numpy as np
from matplotlib import pyplot as plt
FONTSIZE = 16
MARKERSIZE = 10
LINEWIDTH = 2
data = "W2-convergence-test-hybridization.csv"
if not os.path.exists(data):
print("Cannot find data file '%s'" % da... | {
"repo_name": "thomasgibson/firedrake-hybridization",
"path": "convergence_tests/plot_convergence.py",
"copies": "1",
"size": "3813",
"license": "mit",
"hash": -2878123860250989600,
"line_mean": 25.8521126761,
"line_max": 69,
"alpha_frac": 0.5948072384,
"autogenerated": false,
"ratio": 2.95810705... |
from firedrake import *
import sys
import petsc4py
petsc4py.init(sys.argv)
from petsc4py import PETSc
__all__ = ["P1HMultiGrid"]
class P1HMultiGrid(object):
"""
"""
def __init__(self, S, fine_solution, omega_c2=1):
"""
"""
self.lambda_f = fine_solution
self.trace_ope... | {
"repo_name": "thomasgibson/firedrake-hybridization",
"path": "gravity_wave/p1_hybrid_mg.py",
"copies": "1",
"size": "5539",
"license": "mit",
"hash": 364775094455577150,
"line_mean": 32.5696969697,
"line_max": 77,
"alpha_frac": 0.4795089366,
"autogenerated": false,
"ratio": 3.608469055374593,
... |
from firedrake import *
__all__ = ["construct_spaces"]
def construct_spaces(mesh, order=1):
"""Builds the compatible finite element spaces
for the linear compressible gravity wave system.
The following spaces are constructed:
W2: The HDiv velocity space
W3: The L2 pressure space
Wb: The Ch... | {
"repo_name": "thomasgibson/firedrake-hybridization",
"path": "gravity_wave/function_spaces.py",
"copies": "1",
"size": "1865",
"license": "mit",
"hash": -7962413889921112000,
"line_mean": 29.0806451613,
"line_max": 66,
"alpha_frac": 0.6407506702,
"autogenerated": false,
"ratio": 3.35431654676258... |
from firedrake import (split, LinearVariationalProblem, Constant,
LinearVariationalSolver, TestFunctions, TrialFunctions,
TestFunction, TrialFunction, lhs, rhs, DirichletBC, FacetNormal,
div, dx, jump, avg, dS_v, dS_h, ds_v, ds_t, ds_b, ds_tb, inner,
... | {
"repo_name": "thomasgibson/firedrake-hybridization",
"path": "compressible_examples/schur_complement_solver.py",
"copies": "1",
"size": "8204",
"license": "mit",
"hash": 97291236458856290,
"line_mean": 38.8252427184,
"line_max": 110,
"alpha_frac": 0.5683812774,
"autogenerated": false,
"ratio": 3... |
from firedrake.petsc import PETSc
from argparse import ArgumentParser
from driver import run_profliler
import sys
PETSc.Log.begin()
parser = ArgumentParser(description=("""
Profile of 3D compressible solver for the Euler equations (dry atmosphere).
"""), add_help=False)
parser.add_argument("--hybridization",
... | {
"repo_name": "thomasgibson/firedrake-hybridization",
"path": "profile_compressible_solver/run_profiler.py",
"copies": "1",
"size": "3906",
"license": "mit",
"hash": -756484009454727700,
"line_mean": 32.1016949153,
"line_max": 75,
"alpha_frac": 0.5040962622,
"autogenerated": false,
"ratio": 4.297... |
from firedrake.petsc import PETSc
from firedrake import COMM_WORLD, parameters
from argparse import ArgumentParser
from pyop2.profiling import timed_stage
from mpi4py import MPI
import pandas as pd
import sys
import os
from profile_problem import ProfileGravityWaveSolver as Solver
parameters["pyop2_options"]["lazy_e... | {
"repo_name": "thomasgibson/tabula-rasa",
"path": "gravity_waves/run_profiler.py",
"copies": "1",
"size": "9265",
"license": "mit",
"hash": -7898506028893112000,
"line_mean": 32.4476534296,
"line_max": 76,
"alpha_frac": 0.5610361576,
"autogenerated": false,
"ratio": 3.435298479792362,
"config_t... |
from Firefly.const import (CONTACT, CONTACT_CLOSED, CONTACT_OPEN, EVENT_ACTION_OFF, EVENT_ACTION_ON, MOTION, MOTION_ACTIVE, MOTION_INACTIVE, NOT_PRESENT, PRESENCE, PRESENT, SENSOR_DRY, SENSOR_WET,
WATER)
from Firefly.helpers.device import *
def metaDimmer(min=0, max=100, command=True, requ... | {
"repo_name": "Firefly-Automation/Firefly",
"path": "Firefly/helpers/metadata/metadata.py",
"copies": "1",
"size": "15952",
"license": "apache-2.0",
"hash": 7317399768636689000,
"line_mean": 29.3847619048,
"line_max": 265,
"alpha_frac": 0.6411108325,
"autogenerated": false,
"ratio": 3.59279279279... |
from Firefly.helpers.events import (Event, Command)
from Firefly.const import (EVENT_TYPE_UPDATE, EVENT_TYPE_COMMAND, EVENT_ACTION_ACTIVE, COMMAND_NOTIFY, COMMAND_SPEECH,
ACTION_OFF)
import unittest
from unittest import mock
from unittest.mock import patch
class EventTest(unittest.TestCase)... | {
"repo_name": "Firefly-Automation/Firefly",
"path": "tests/test_events.py",
"copies": "1",
"size": "2140",
"license": "apache-2.0",
"hash": -4650552188875905000,
"line_mean": 34.6666666667,
"line_max": 118,
"alpha_frac": 0.6710280374,
"autogenerated": false,
"ratio": 3.434991974317817,
"config_... |
from Firefly import logging
from Firefly.automation.const import AUTOMATION_INTERFACE
from Firefly.automation.routine.const import ROUTINE_EXECUTE, ROUTINE_ICON, ROUTINE_MODE, ROUTINE_ROUTINE
from Firefly.automation.routine.metadata import METADATA, TITLE
from Firefly.const import COMMAND_NOTIFY, SERVICE_NOTIFICATION, ... | {
"repo_name": "Firefly-Automation/Firefly",
"path": "Firefly/automation/routine/routine.py",
"copies": "1",
"size": "6728",
"license": "apache-2.0",
"hash": -1645732273307153000,
"line_mean": 32.4726368159,
"line_max": 186,
"alpha_frac": 0.6510107015,
"autogenerated": false,
"ratio": 3.4555726759... |
from Firefly import logging
from Firefly.automation import Automation
from Firefly.helpers.events import Command
from Firefly.const import AUTHOR
# TODO: move this to automation
from Firefly.util.conditions import check_conditions
TITLE = 'Time Based Actions'
COMMANDS = ['ADD_ACTION']
def Setup(firefly, package, **... | {
"repo_name": "Firefly-Automation/Firefly",
"path": "Firefly/automation/time_based_actions.py",
"copies": "1",
"size": "1217",
"license": "apache-2.0",
"hash": -3122338976118049300,
"line_mean": 18.9508196721,
"line_max": 96,
"alpha_frac": 0.6409202958,
"autogenerated": false,
"ratio": 3.53779069... |
from Firefly import logging
from Firefly.automation import Automation
from Firefly.helpers.events import Command
from Firefly.const import SERVICE_NOTIFICATION, COMMAND_NOTIFY, AUTHOR, CONTACT_CLOSED, CONTACT_OPEN, SWITCH_ON, SWITCH_OFF
from Firefly.automation.triggers import Triggers
from Firefly.helpers.conditions im... | {
"repo_name": "Firefly-Automation/Firefly",
"path": "Firefly/automation/event_based_action.py",
"copies": "1",
"size": "6868",
"license": "apache-2.0",
"hash": 7828294097738470000,
"line_mean": 33.5175879397,
"line_max": 123,
"alpha_frac": 0.6814210833,
"autogenerated": false,
"ratio": 3.69247311... |
from Firefly import logging
from Firefly.automation import Automation
from Firefly.helpers.events import Command
from Firefly.const import SERVICE_NOTIFICATION, COMMAND_NOTIFY, AUTHOR
TITLE = 'Firefly Routines'
COMMANDS = ['add_action', 'execute']
def Setup(firefly, package, **kwargs):
logging.message('Entering %s... | {
"repo_name": "Firefly-Automation/Firefly",
"path": "Firefly/automation/routine_old.py",
"copies": "1",
"size": "1858",
"license": "apache-2.0",
"hash": 6777461041518592000,
"line_mean": 27.5846153846,
"line_max": 92,
"alpha_frac": 0.6776103337,
"autogenerated": false,
"ratio": 3.4407407407407407... |
from Firefly import logging
from Firefly.automation.triggers import Trigger, Triggers
from Firefly.const import TYPE_AUTOMATION, API_INFO_REQUEST
import asyncio
from Firefly import aliases
import uuid
from Firefly.helpers.events import Request
from Firefly.helpers.conditions import Conditions
from Firefly.helpers.actio... | {
"repo_name": "Firefly-Automation/Firefly",
"path": "Firefly/automation/automation.py",
"copies": "1",
"size": "5091",
"license": "apache-2.0",
"hash": 7464350788828792000,
"line_mean": 24.7171717172,
"line_max": 79,
"alpha_frac": 0.6597917894,
"autogenerated": false,
"ratio": 3.7488954344624448,... |
from Firefly import logging
from Firefly.components.hue.hue_device import HueDevice
from Firefly.components.virtual_devices import AUTHOR
from Firefly.const import (ACTION_LEVEL, ACTION_OFF, ACTION_ON, ACTION_TOGGLE, DEVICE_TYPE_SWITCH, EVENT_ACTION_OFF, LEVEL, STATE, SWITCH)
TITLE = 'Firefly Hue Group'
DEVICE_TYPE = ... | {
"repo_name": "Firefly-Automation/Firefly",
"path": "Firefly/components/hue/hue_group.py",
"copies": "1",
"size": "1182",
"license": "apache-2.0",
"hash": 4466732934830167000,
"line_mean": 24.6956521739,
"line_max": 138,
"alpha_frac": 0.6700507614,
"autogenerated": false,
"ratio": 3.2561983471074... |
from Firefly import logging
from Firefly.components.hue.hue_device import HueDevice
from Firefly.components.virtual_devices import AUTHOR
from Firefly.const import ACTION_LEVEL, ACTION_OFF, ACTION_ON, ACTION_TOGGLE, DEVICE_TYPE_SWITCH, LEVEL, STATE, SWITCH
TITLE = 'Firefly Hue Light'
DEVICE_TYPE = DEVICE_TYPE_SWITCH
A... | {
"repo_name": "Firefly-Automation/Firefly",
"path": "Firefly/components/hue/hue_light.py",
"copies": "1",
"size": "1122",
"license": "apache-2.0",
"hash": 4407870212495998000,
"line_mean": 25.0930232558,
"line_max": 118,
"alpha_frac": 0.6702317291,
"autogenerated": false,
"ratio": 3.2807017543859... |
from Firefly import logging
from Firefly.components.zwave.device_types.switch import ZwaveSwitch
from Firefly.const import ACTION_OFF, ACTION_ON, LEVEL, SWITCH
from Firefly.services.alexa.alexa_const import ALEXA_SMARTPLUG
TITLE = 'Aeotec Smart Dimmer 6'
BATTERY = 'battery'
ALARM = 'alarm'
POWER_METER = 'power_meter'... | {
"repo_name": "Firefly-Automation/Firefly",
"path": "Firefly/components/zwave/aeotec/zw099_smart_dimmer_6.py",
"copies": "1",
"size": "2281",
"license": "apache-2.0",
"hash": 6745651106136388000,
"line_mean": 27.1604938272,
"line_max": 112,
"alpha_frac": 0.6795265235,
"autogenerated": false,
"rat... |
from Firefly import logging
from Firefly.components.zwave.device_types.switch import ZwaveSwitch
from Firefly.const import ACTION_OFF, ACTION_ON, SWITCH
from Firefly.services.alexa.alexa_const import ALEXA_SMARTPLUG
TITLE = 'Aeotec Smart Switch 5'
BATTERY = 'battery'
ALARM = 'alarm'
POWER_METER = 'power_meter'
VOLTAG... | {
"repo_name": "Firefly-Automation/Firefly",
"path": "Firefly/components/zwave/aeotec/dsc06106_smart_energy_switch.py",
"copies": "1",
"size": "3263",
"license": "apache-2.0",
"hash": 2387524849108015600,
"line_mean": 29.4953271028,
"line_max": 140,
"alpha_frac": 0.6840330984,
"autogenerated": false... |
from Firefly import logging
from Firefly.components.zwave.device_types.water_sensor import ZwaveWaterSensor
from Firefly.const import SENSOR_DRY, WATER
ALARM = 'alarm'
BATTERY = 'battery'
TITLE = 'DSB45 Aeotec Water Sensor'
COMMANDS = []
REQUESTS = [ALARM, BATTERY, WATER]
INITIAL_VALUES = {
'_alarm': False,
'... | {
"repo_name": "Firefly-Automation/Firefly",
"path": "Firefly/components/zwave/aeotec/dsb45_water_sensor.py",
"copies": "1",
"size": "1889",
"license": "apache-2.0",
"hash": -699435299193311700,
"line_mean": 28.0615384615,
"line_max": 110,
"alpha_frac": 0.6749602965,
"autogenerated": false,
"ratio... |
from Firefly import logging
from Firefly.const import ACTION_OFF, ACTION_ON, COMMAND_SET_LIGHT, DEVICE_TYPE_SWITCH, LEVEL, SWITCH
from Firefly.helpers.device import COLOR, COLOR_TEMPERATURE, COLOR_RED, COLOR_GREEN, COLOR_BLUE, COLOR_BRI, COLOR_HEX, COLOR_HUE, COLOR_SAT
from Firefly.helpers.device.device import Device
f... | {
"repo_name": "Firefly-Automation/Firefly",
"path": "Firefly/helpers/device_types/light.py",
"copies": "1",
"size": "6012",
"license": "apache-2.0",
"hash": 1714426936761764400,
"line_mean": 28.3268292683,
"line_max": 192,
"alpha_frac": 0.6580172987,
"autogenerated": false,
"ratio": 3.35491071428... |
from Firefly import logging
from Firefly.const import ACTION_OFF, ACTION_ON, COMMAND_SET_LIGHT, DEVICE_TYPE_SWITCH, LEVEL, SWITCH
from Firefly.helpers.device import *
from Firefly.helpers.device.device import Device
from Firefly.helpers.metadata.metadata import action_battery, action_dimmer, action_on_off_switch, actio... | {
"repo_name": "Firefly-Automation/Firefly",
"path": "Firefly/helpers/device_types/switch.py",
"copies": "1",
"size": "5854",
"license": "apache-2.0",
"hash": -3196182140174142500,
"line_mean": 30.6432432432,
"line_max": 192,
"alpha_frac": 0.669115135,
"autogenerated": false,
"ratio": 3.4783125371... |
from Firefly import logging
from Firefly.const import (ALIAS_FILE)
import json
class Alias(object):
def __init__(self, alias_file=ALIAS_FILE):
self._alias_file = alias_file
self._aliases = {}
self.read_file()
def read_file(self):
with open(self._alias_file) as file:
self._aliases = json.loa... | {
"repo_name": "Firefly-Automation/Firefly",
"path": "Firefly/helpers/alias.py",
"copies": "1",
"size": "1857",
"license": "apache-2.0",
"hash": -4817869766412732000,
"line_mean": 29.4590163934,
"line_max": 100,
"alpha_frac": 0.6225094238,
"autogenerated": false,
"ratio": 3.438888888888889,
"con... |
from Firefly import logging
from Firefly.const import CONTACT, CONTACT_CLOSED, CONTACT_OPEN
from Firefly.helpers.device import *
from Firefly.helpers.device.device import Device
from Firefly.helpers.metadata.metadata import action_contact, action_text
ALARM = 'alarm'
DEVICE_TYPE_CONTACT_SENSOR = 'contact_sensor'
COM... | {
"repo_name": "Firefly-Automation/Firefly",
"path": "Firefly/helpers/device_types/contact_sensor.py",
"copies": "1",
"size": "2617",
"license": "apache-2.0",
"hash": 5567096315464838000,
"line_mean": 31.7125,
"line_max": 200,
"alpha_frac": 0.7103553687,
"autogenerated": false,
"ratio": 3.58493150... |
from Firefly import logging
from Firefly.const import DEVICE_TYPE_WATER_SENSOR, SENSOR_DRY, SENSOR_WET, WATER
from Firefly.helpers.device import *
from Firefly.helpers.device.device import Device
from Firefly.helpers.metadata.metadata import action_text, action_water_dry
ALARM = 'alarm'
COMMANDS = []
REQUESTS = [AL... | {
"repo_name": "Firefly-Automation/Firefly",
"path": "Firefly/helpers/device_types/water_sensor.py",
"copies": "1",
"size": "2538",
"license": "apache-2.0",
"hash": 4491098981271261000,
"line_mean": 31.1265822785,
"line_max": 198,
"alpha_frac": 0.7009456265,
"autogenerated": false,
"ratio": 3.4297... |
from Firefly import logging
from Firefly.const import (EVENT_ACTION_ANY, EVENT_ACTON_TYPE, TIME)
from typing import List
class Subscriptions(object):
"""Subscriptions.
Subscriptions should be stored like so:
{ DEVICE_SUBSCRIBED_TO: {EVENT_ACTION: [LIST_OF_SUBSCRIBERS], ...} }
"""
# TODO: Add functionality... | {
"repo_name": "Firefly-Automation/Firefly",
"path": "Firefly/helpers/subscribers.py",
"copies": "1",
"size": "14928",
"license": "apache-2.0",
"hash": 7222613464370044000,
"line_mean": 33.9601873536,
"line_max": 121,
"alpha_frac": 0.6191050375,
"autogenerated": false,
"ratio": 3.9109248100602567,... |
from Firefly import logging
from Firefly.const import (IS_DARK, IS_LIGHT, IS_MODE, IS_NOT_MODE, IS_NOT_TIME_RANGE, IS_TIME_RANGE)
class Conditions(object):
def __init__(self, is_dark: bool=None, is_light: bool=None, is_mode: list=None, is_not_mode: list=None, last_mode: list=None, before_time=None, after_time=None, ... | {
"repo_name": "Firefly-Automation/Firefly",
"path": "Firefly/helpers/conditions.py",
"copies": "1",
"size": "1325",
"license": "apache-2.0",
"hash": -3912726666957384700,
"line_mean": 34.8378378378,
"line_max": 207,
"alpha_frac": 0.6686792453,
"autogenerated": false,
"ratio": 3.0389908256880735,
... |
from Firefly import logging
from Firefly.const import (IS_DARK, IS_LIGHT, IS_MODE, IS_NOT_MODE, IS_NOT_TIME_RANGE, IS_TIME_RANGE)
def check_conditions(firefly, condition: dict) -> bool:
verify = True
if not condition:
return True
for c, value in condition.items():
if c == IS_DARK:
verify &= check... | {
"repo_name": "Firefly-Automation/Firefly",
"path": "Firefly/util/conditions.py",
"copies": "1",
"size": "1257",
"license": "apache-2.0",
"hash": -6357116248980543000,
"line_mean": 27.5681818182,
"line_max": 116,
"alpha_frac": 0.6809864757,
"autogenerated": false,
"ratio": 3.198473282442748,
"c... |
from Firefly import logging
from Firefly.const import LUX, MOTION, MOTION_ACTIVE, MOTION_INACTIVE
from Firefly.helpers.device import *
from Firefly.helpers.device.device import Device
from Firefly.helpers.metadata.metadata import action_motion, action_text
# TODO: Add support for temp reporting.
# from Firefly.service... | {
"repo_name": "Firefly-Automation/Firefly",
"path": "Firefly/helpers/device_types/multi_sensor.py",
"copies": "1",
"size": "4411",
"license": "apache-2.0",
"hash": -3335169480054297000,
"line_mean": 33.7322834646,
"line_max": 198,
"alpha_frac": 0.6982543641,
"autogenerated": false,
"ratio": 3.346... |
from Firefly import logging
from Firefly.helpers.conditions import Conditions
from Firefly.helpers.events import Command
from Firefly import scheduler
class Action(object):
def __init__(self, ff_id, command, source, conditions=None, force=False, **kwargs):
self._ff_id = ff_id
self._command = command
sel... | {
"repo_name": "Firefly-Automation/Firefly",
"path": "Firefly/helpers/action.py",
"copies": "1",
"size": "1905",
"license": "apache-2.0",
"hash": 7381087653585159000,
"line_mean": 25.8450704225,
"line_max": 94,
"alpha_frac": 0.667191601,
"autogenerated": false,
"ratio": 3.5875706214689265,
"conf... |
from Firefly import logging
from Firefly.helpers.events import Command
from Firefly import aliases
from difflib import get_close_matches
from Firefly.const import (ACTION_LEVEL, ACTION_OFF, ACTION_ON, ALEXA_OFF_REQUEST, ALEXA_ON_REQUEST,
ALEXA_SET_COLOR_REQUEST, ALEXA_SET_COLOR_TEMP_REQUEST, ... | {
"repo_name": "Firefly-Automation/Firefly",
"path": "Firefly/services/alexa/alexa.py",
"copies": "1",
"size": "4981",
"license": "apache-2.0",
"hash": 7691483705087672000,
"line_mean": 33.5902777778,
"line_max": 131,
"alpha_frac": 0.6617145152,
"autogenerated": false,
"ratio": 3.5151729004940013,... |
from Firefly import logging
from Firefly.helpers.service import Service
from Firefly.helpers.events import Command
from Firefly.const import COMMAND_NOTIFY, SERVICE_NOTIFICATION, NOTIFY_DEFAULT, PRIORITY_NORMAL
import asyncio
'''
Notification service may have its own config file to save device mappings into
'''
TITLE... | {
"repo_name": "Firefly-Automation/Firefly",
"path": "Firefly/services/notification.py",
"copies": "1",
"size": "2386",
"license": "apache-2.0",
"hash": 8605857833788548000,
"line_mean": 29.5897435897,
"line_max": 107,
"alpha_frac": 0.6978206203,
"autogenerated": false,
"ratio": 3.5665171898355754... |
from Firefly import logging
from Firefly import aliases
from typing import TypeVar
from Firefly.const import (EVENT_TYPE_COMMAND, COMMAND_NOTIFY, COMMAND_SPEECH, COMMAND_ROUTINE, EVENT_TYPE_REQUEST)
COMMAND_TYPE = TypeVar('COMMAND', dict, str)
class Event(object):
"""
Events are messages sent between apps and co... | {
"repo_name": "Firefly-Automation/Firefly",
"path": "Firefly/helpers/events.py",
"copies": "1",
"size": "3748",
"license": "apache-2.0",
"hash": 5950881317397677000,
"line_mean": 25.0347222222,
"line_max": 118,
"alpha_frac": 0.6368729989,
"autogenerated": false,
"ratio": 3.66015625,
"config_tes... |
from Firefly import logging
# from rgb_cie import Converter
from Firefly.components.hue.ct_fade import CTFade
from Firefly.components.virtual_devices import AUTHOR
from Firefly.const import ACTION_LEVEL, ACTION_OFF, ACTION_ON, ACTION_TOGGLE, COMMAND_SET_LIGHT, COMMAND_UPDATE, DEVICE_TYPE_COLOR_LIGHT, EVENT_ACTION_OFF, ... | {
"repo_name": "Firefly-Automation/Firefly",
"path": "Firefly/components/hue/hue_device.py",
"copies": "1",
"size": "14627",
"license": "apache-2.0",
"hash": -8952530023109579000,
"line_mean": 28.0218253968,
"line_max": 176,
"alpha_frac": 0.5712039379,
"autogenerated": false,
"ratio": 3.2161389621... |
from Firefly import logging
from typing import Dict
GROUP = 'group'
ROOM = 'room'
ZONE = 'zone'
class DeviceGroups(object):
def __init__(self, firefly):
self.firefly = firefly
self._groups = Groups(self)
self._rooms = Rooms(self)
self._zones = Zones(self)
@property
def groups(self):
return... | {
"repo_name": "Firefly-Automation/Firefly",
"path": "Firefly/helpers/device_groups.py",
"copies": "1",
"size": "4448",
"license": "apache-2.0",
"hash": 5145087792710454000,
"line_mean": 22.2879581152,
"line_max": 81,
"alpha_frac": 0.6175809353,
"autogenerated": false,
"ratio": 3.4136607828089027,... |
from Firefly import logging
from Firefly.helpers.device_types.multi_sensor import MultiSensor
from Firefly.components.zwave.zwave_device import ZwaveDevice
from openzwave.network import ZWaveNode
from Firefly.const import MOTION, STATE, LUX, MOTION_INACTIVE, MOTION_ACTIVE, AUTHOR, DEVICE_TYPE_MOTION
from openzwave.val... | {
"repo_name": "Firefly-Automation/Firefly",
"path": "Firefly/components/zwave/device_types/motion_sensor.py",
"copies": "1",
"size": "2015",
"license": "apache-2.0",
"hash": -7597626486031129000,
"line_mean": 27,
"line_max": 161,
"alpha_frac": 0.6878411911,
"autogenerated": false,
"ratio": 3.2978... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.