code stringlengths 2k 1.04M | repo_path stringlengths 5 517 | parsed_code stringlengths 0 1.04M | quality_prob float64 0.02 0.95 | learning_prob float64 0.02 0.93 |
|---|---|---|---|---|
import pygame
import pygame.mixer
pygame.mixer.init()
WINDOW_HEIGHT = 720
WINDOW_WIDTH = 1008
WINDOW_SCREEN = pygame.display.set_mode((WINDOW_WIDTH, WINDOW_HEIGHT))
MAP_HEIGHT = 720
MAP_WIDTH = 672
WINDOW_OFFSET = WINDOW_WIDTH - MAP_WIDTH
WORLD_CEILING = -30
FPS = 60
#COLORS
BLACK = (0, 0, 0)
RED = (255, 0, 0)
YELL... | CONSTS.py | import pygame
import pygame.mixer
pygame.mixer.init()
WINDOW_HEIGHT = 720
WINDOW_WIDTH = 1008
WINDOW_SCREEN = pygame.display.set_mode((WINDOW_WIDTH, WINDOW_HEIGHT))
MAP_HEIGHT = 720
MAP_WIDTH = 672
WINDOW_OFFSET = WINDOW_WIDTH - MAP_WIDTH
WORLD_CEILING = -30
FPS = 60
#COLORS
BLACK = (0, 0, 0)
RED = (255, 0, 0)
YELL... | 0.229708 | 0.086671 |
import sqlite3
db = sqlite3.connect('C:/Users/lapri/PycharmProjects/Practica1.Libros/app/data/prueba.db')
cursor = db.cursor()
tablas = [
"""
CREATE TABLE IF NOT EXISTS Libro(
LSBN INTEGER PRIMARY KEY,
AUTOR TEXT NOT NULL,
CANTIDADP INTEGER NOT NULL,
PUBLICACION INTEGER NOT NULL,
NOMBRELIBRO ... | Practica1.Libros/app/__init__.py | import sqlite3
db = sqlite3.connect('C:/Users/lapri/PycharmProjects/Practica1.Libros/app/data/prueba.db')
cursor = db.cursor()
tablas = [
"""
CREATE TABLE IF NOT EXISTS Libro(
LSBN INTEGER PRIMARY KEY,
AUTOR TEXT NOT NULL,
CANTIDADP INTEGER NOT NULL,
PUBLICACION INTEGER NOT NULL,
NOMBRELIBRO ... | 0.063671 | 0.07843 |
import datetime
import json
import time
import twitter
import pyperclip
from datastructures.priority_queue import PriorityQueue
from selenium import webdriver
from selenium.webdriver.chrome.service import Service
from selenium.webdriver.common.action_chains import ActionChains
from selenium.webdriver.commo... | wordle_solve.py |
import datetime
import json
import time
import twitter
import pyperclip
from datastructures.priority_queue import PriorityQueue
from selenium import webdriver
from selenium.webdriver.chrome.service import Service
from selenium.webdriver.common.action_chains import ActionChains
from selenium.webdriver.commo... | 0.317638 | 0.080213 |
__author__ = "Anvesh"
__version__ = "0.1"
import ctypes
import io
import logging
import os
import requests
from PIL import Image, ImageFilter
from screeninfo import get_monitors
from config import curr_dir, client_id, url
logging.basicConfig(filename="src/moody-desktop.log",
forma... | main.py | __author__ = "Anvesh"
__version__ = "0.1"
import ctypes
import io
import logging
import os
import requests
from PIL import Image, ImageFilter
from screeninfo import get_monitors
from config import curr_dir, client_id, url
logging.basicConfig(filename="src/moody-desktop.log",
forma... | 0.267313 | 0.064742 |
import sys
import numpy
from OpenGL.GL import *
from OpenGL.GLU import *
from OpenGL import GLX
import pyopencl as cl
class raycl(object):
def __init__(self, texture, tex_dim, world):
self.tex_dim = tex_dim
self.world = world
self.clinit()
self.loadProgram("raytrace.cl")
... | raycl.py | import sys
import numpy
from OpenGL.GL import *
from OpenGL.GLU import *
from OpenGL import GLX
import pyopencl as cl
class raycl(object):
def __init__(self, texture, tex_dim, world):
self.tex_dim = tex_dim
self.world = world
self.clinit()
self.loadProgram("raytrace.cl")
... | 0.281406 | 0.165492 |
import logging
import os
from sys import platform
import numpy as np
import yaml
import igibson
from igibson.envs.igibson_env import iGibsonEnv
from igibson.objects.articulated_object import URDFObject
from igibson.objects.ycb_object import YCBObject
from igibson.render.mesh_renderer.mesh_renderer_cpu import MeshRend... | igibson/examples/objects/load_objects.py | import logging
import os
from sys import platform
import numpy as np
import yaml
import igibson
from igibson.envs.igibson_env import iGibsonEnv
from igibson.objects.articulated_object import URDFObject
from igibson.objects.ycb_object import YCBObject
from igibson.render.mesh_renderer.mesh_renderer_cpu import MeshRend... | 0.439747 | 0.306735 |
import gym
import numpy as np
from ray.rllib import SampleBatch
from ray.rllib.agents.impala import vtrace
from ray.rllib.agents.impala.vtrace_policy import _make_time_major, BEHAVIOUR_LOGITS
from ray.rllib.models import ModelCatalog
from ray.rllib.models.tf.tf_action_dist import MultiActionDistribution, Categorical
fr... | func-approx/agents/impala_cpc_ma_comm.py | import gym
import numpy as np
from ray.rllib import SampleBatch
from ray.rllib.agents.impala import vtrace
from ray.rllib.agents.impala.vtrace_policy import _make_time_major, BEHAVIOUR_LOGITS
from ray.rllib.models import ModelCatalog
from ray.rllib.models.tf.tf_action_dist import MultiActionDistribution, Categorical
fr... | 0.883123 | 0.175097 |
import sys
from com.l2jfrozen.gameserver.model.quest import State
from com.l2jfrozen.gameserver.model.quest import QuestState
from com.l2jfrozen.gameserver.model.quest.jython import QuestJython as JQuest
qn = "247_PossessorOfAPreciousSoul_4"
#NPC
CARADINE = 31740
LADY_OF_LAKE = 31745
#QUEST ITEM
CARADINE_LETTER_LAST... | datapack/data/scripts/quests/247_PossessorOfAPreciousSoul_4/__init__.py | import sys
from com.l2jfrozen.gameserver.model.quest import State
from com.l2jfrozen.gameserver.model.quest import QuestState
from com.l2jfrozen.gameserver.model.quest.jython import QuestJython as JQuest
qn = "247_PossessorOfAPreciousSoul_4"
#NPC
CARADINE = 31740
LADY_OF_LAKE = 31745
#QUEST ITEM
CARADINE_LETTER_LAST... | 0.201735 | 0.142978 |
import argparse
from conjur.argument_parser.parser_utils import command_description, command_epilog, formatter, \
title_formatter
from conjur.wrapper.argparse_wrapper import ArgparseWrapper
# pylint: disable=too-few-public-methods
class ListParser:
"""Partial class of the ArgParseBuilder.
This class add th... | conjur/argument_parser/_list_parser.py | import argparse
from conjur.argument_parser.parser_utils import command_description, command_epilog, formatter, \
title_formatter
from conjur.wrapper.argparse_wrapper import ArgparseWrapper
# pylint: disable=too-few-public-methods
class ListParser:
"""Partial class of the ArgParseBuilder.
This class add th... | 0.63341 | 0.08886 |
import os
import sys
import reframe as rfm
import reframe.utility.sanity as sn
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__),
'../common'))) # noqa: E402
import sphexa.hooks as hooks
# {{{ class SphExa_STAT_Check
@rfm.simple_test
class SphExa_STAT_Check(rfm.RegressionTest, h... | reframechecks/debug/cray_stat.py |
import os
import sys
import reframe as rfm
import reframe.utility.sanity as sn
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__),
'../common'))) # noqa: E402
import sphexa.hooks as hooks
# {{{ class SphExa_STAT_Check
@rfm.simple_test
class SphExa_STAT_Check(rfm.RegressionTest, h... | 0.140897 | 0.214527 |
from settings import *
import numpy as np
import struct
def _bool2int(x, dw):
y = 0
for i,j in enumerate(x):
y += j<<(i * dw)
return y
def _quantize(mat, dw, dq, is_complement=True):
FIX_POINT_MAX = 2 ** (dw - 1) - 1
FIX_POINT_MIN = - 2 ** (dw - 1)
FIX_POINT_SCALE = 2 ** dq
UINT_M... | util/data.py |
from settings import *
import numpy as np
import struct
def _bool2int(x, dw):
y = 0
for i,j in enumerate(x):
y += j<<(i * dw)
return y
def _quantize(mat, dw, dq, is_complement=True):
FIX_POINT_MAX = 2 ** (dw - 1) - 1
FIX_POINT_MIN = - 2 ** (dw - 1)
FIX_POINT_SCALE = 2 ** dq
UINT_M... | 0.346652 | 0.355523 |
from __future__ import unicode_literals
from django.db import migrations, models
import django.contrib.gis.db.models.fields
import common.models.base
import django.utils.timezone
import django.db.models.deletion
from django.conf import settings
import mfl_gis.models
import uuid
class Migration(migrations.Migration):... | admin_offices/migrations/0001_initial.py | from __future__ import unicode_literals
from django.db import migrations, models
import django.contrib.gis.db.models.fields
import common.models.base
import django.utils.timezone
import django.db.models.deletion
from django.conf import settings
import mfl_gis.models
import uuid
class Migration(migrations.Migration):... | 0.549641 | 0.105027 |
""" Tools for annotating an input image """
from collections import OrderedDict
import logging
import cv2
import numpy as np
logger = logging.getLogger(__name__) # pylint: disable=invalid-name
class Annotate():
""" Annotate an input image """
def __init__(self, image, alignments, original_roi=None):
... | faceswap/tools/alignments/annotate.py | """ Tools for annotating an input image """
from collections import OrderedDict
import logging
import cv2
import numpy as np
logger = logging.getLogger(__name__) # pylint: disable=invalid-name
class Annotate():
""" Annotate an input image """
def __init__(self, image, alignments, original_roi=None):
... | 0.907469 | 0.264056 |
from enum import Enum
from __about__ import __date__, __summary__, __title__, __version__
class Args(Enum):
BACKEND = "backend"
BV = "bv"
CORES = "cores"
DEBUG = "debug"
FAIR = "fair"
CORES_FROM = "from"
KEEP_FILES = "keep_files"
INCLUDE = "include"
PROPERTY = "property"
NO_PR... | cli.py |
from enum import Enum
from __about__ import __date__, __summary__, __title__, __version__
class Args(Enum):
BACKEND = "backend"
BV = "bv"
CORES = "cores"
DEBUG = "debug"
FAIR = "fair"
CORES_FROM = "from"
KEEP_FILES = "keep_files"
INCLUDE = "include"
PROPERTY = "property"
NO_PR... | 0.835249 | 0.136752 |
import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
class ContrastiveLoss(nn.Module):
"""
Contrastive loss
Takes embeddings of two samples and a target label == 1 if samples are from the same class and label == 0 otherwise
"""
def __init__(self, margin):
... | netharn/criterions/losses.py |
import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
class ContrastiveLoss(nn.Module):
"""
Contrastive loss
Takes embeddings of two samples and a target label == 1 if samples are from the same class and label == 0 otherwise
"""
def __init__(self, margin):
... | 0.93835 | 0.699043 |
import numpy as np
def check_gaps(loc_t_arr, t_thresh, verbose=False):
"""
"""
# If the masked array contains gaps larger than the thresh
# split the mask and take the submask which corresponds to
# the largest duration subarray.
# If there's not enough evnets for a gap, exit
if loc_t_... | src/stay_classification/gap_tools.py | import numpy as np
def check_gaps(loc_t_arr, t_thresh, verbose=False):
"""
"""
# If the masked array contains gaps larger than the thresh
# split the mask and take the submask which corresponds to
# the largest duration subarray.
# If there's not enough evnets for a gap, exit
if loc_t_... | 0.368974 | 0.683056 |
import re
import csv
import ipaddress
__version__ = 1.0
# Each route will have the following values
class Route_Template(object):
def __init__(self):
self.route = {}
self.protocol = []
self.metric = []
self.next_hop = []
self.age = []
self.interface = []
def __r... | route_parse_nxos.py | import re
import csv
import ipaddress
__version__ = 1.0
# Each route will have the following values
class Route_Template(object):
def __init__(self):
self.route = {}
self.protocol = []
self.metric = []
self.next_hop = []
self.age = []
self.interface = []
def __r... | 0.522933 | 0.118768 |
# Import python modules.
from __future__ import absolute_import
import json
import logging
import os
# Import external modules.
import requests
log = logging.getLogger(__name__)
class PluginCache(object):
"""Manages the list of plugins available in the update center."""
PLUGINS_URL="https://updates.jenkins-ci... | _states/jenkins_plugin.py | # Import python modules.
from __future__ import absolute_import
import json
import logging
import os
# Import external modules.
import requests
log = logging.getLogger(__name__)
class PluginCache(object):
"""Manages the list of plugins available in the update center."""
PLUGINS_URL="https://updates.jenkins-ci... | 0.768646 | 0.134009 |
import pygame
from typing import Dict
import settings
import scoreboard
class Display:
'''
Display object has fields and methods to draw objects to the screen and display different game states
Args:
surface (pygame.Surface): game screen
logo (pygame.Surface): game logo
... | game/display.py | import pygame
from typing import Dict
import settings
import scoreboard
class Display:
'''
Display object has fields and methods to draw objects to the screen and display different game states
Args:
surface (pygame.Surface): game screen
logo (pygame.Surface): game logo
... | 0.780997 | 0.367469 |
import logging
import signal
import subprocess
import sys
import os
import psutil
import cook
import cook.io_helper as cio
def launch_process(command, environment):
"""Launches the process using the command and specified environment.
Parameters
----------
command: string
The command to exe... | executor/cook/subprocess.py |
import logging
import signal
import subprocess
import sys
import os
import psutil
import cook
import cook.io_helper as cio
def launch_process(command, environment):
"""Launches the process using the command and specified environment.
Parameters
----------
command: string
The command to exe... | 0.547706 | 0.338268 |
import datetime
import math
from bson.objectid import ObjectId
from mongoschema.bson_utils import get_dtype, _get_int
class TestMapper(object):
def test_for_null_one(self):
assert get_dtype(None) == "null"
def test_for_null_two(self):
assert get_dtype("") != "null"
def test_for_null_th... | tests/test_bson_utils.py | import datetime
import math
from bson.objectid import ObjectId
from mongoschema.bson_utils import get_dtype, _get_int
class TestMapper(object):
def test_for_null_one(self):
assert get_dtype(None) == "null"
def test_for_null_two(self):
assert get_dtype("") != "null"
def test_for_null_th... | 0.385259 | 0.506591 |
import sys
import xapian
# We require at least two command line arguments.
if len(sys.argv) < 3:
print >> sys.stderr, "Usage: %s PATH_TO_DATABASE QUERY [-- [DOCID...]]" % sys.argv[0]
sys.exit(1)
try:
# Open the database for searching.
database = xapian.Database(sys.argv[1])
# Start an enquire se... | docs/examples/simpleexpand.py |
import sys
import xapian
# We require at least two command line arguments.
if len(sys.argv) < 3:
print >> sys.stderr, "Usage: %s PATH_TO_DATABASE QUERY [-- [DOCID...]]" % sys.argv[0]
sys.exit(1)
try:
# Open the database for searching.
database = xapian.Database(sys.argv[1])
# Start an enquire se... | 0.259732 | 0.291926 |
class PrettyTable(list):
""" Overridden list class which takes a 2-dimensional list of
the form [[1,2,3],[4,5,6]], and renders HTML and LaTeX Table in
IPython Notebook. For LaTeX export two styles can be chosen."""
def __init__(self, initlist=[], extra_header=None, print_latex_longtable=True,... | src/PrettyTable.py |
class PrettyTable(list):
""" Overridden list class which takes a 2-dimensional list of
the form [[1,2,3],[4,5,6]], and renders HTML and LaTeX Table in
IPython Notebook. For LaTeX export two styles can be chosen."""
def __init__(self, initlist=[], extra_header=None, print_latex_longtable=True,... | 0.580233 | 0.523603 |
import esphome.codegen as cg
import esphome.config_validation as cv
from esphome import automation
from esphome.components import time
from esphome.const import CONF_TIME_ID, CONF_ID, CONF_TRIGGER_ID
from esphome.py_compat import string_types
sun_ns = cg.esphome_ns.namespace('sun')
Sun = sun_ns.class_('Sun')
SunTrigg... | esphome/components/sun/__init__.py | import esphome.codegen as cg
import esphome.config_validation as cv
from esphome import automation
from esphome.components import time
from esphome.const import CONF_TIME_ID, CONF_ID, CONF_TRIGGER_ID
from esphome.py_compat import string_types
sun_ns = cg.esphome_ns.namespace('sun')
Sun = sun_ns.class_('Sun')
SunTrigg... | 0.46393 | 0.224533 |
from numpy import mean, zeros
from copy import deepcopy
class Ensemble(object):
"""
Class represents ensemble learning technique. In short, ensemble techniques predict output over a meta learner
that it self is supplied with output of a number of base learners.
Attributes:
base_learner: Base l... | src/algorithms/common/ensemble.py | from numpy import mean, zeros
from copy import deepcopy
class Ensemble(object):
"""
Class represents ensemble learning technique. In short, ensemble techniques predict output over a meta learner
that it self is supplied with output of a number of base learners.
Attributes:
base_learner: Base l... | 0.943387 | 0.488039 |
from flask_restx import Api as BaseApi
from collections import OrderedDict
from werkzeug.datastructures import MultiDict
from flask_restx.reqparse import Argument
class Api(BaseApi):
"""Custom Flask-RESTPlus Api subclass for overriding default root route
NOTE: endpoint of route '/' must be named 'root'::
... | qwc_services_core/api.py | from flask_restx import Api as BaseApi
from collections import OrderedDict
from werkzeug.datastructures import MultiDict
from flask_restx.reqparse import Argument
class Api(BaseApi):
"""Custom Flask-RESTPlus Api subclass for overriding default root route
NOTE: endpoint of route '/' must be named 'root'::
... | 0.809615 | 0.17172 |
from copy import deepcopy
class TwoTeamsGame:
def __init__(self, team1, team2, player_selector):
"""
:param team1: array of easyAI-supported objects. See Player module
:param team2: array of easyAI-supported objects.
:param player_selector constructor for objects of type AbstractO... | easyAI/TwoTeamsGame.py | from copy import deepcopy
class TwoTeamsGame:
def __init__(self, team1, team2, player_selector):
"""
:param team1: array of easyAI-supported objects. See Player module
:param team2: array of easyAI-supported objects.
:param player_selector constructor for objects of type AbstractO... | 0.772445 | 0.459015 |
from world import *
from maingui import *
from colors import *
import numpy
import sys
try:
# i386-only optimization with Psyco
# NOT TESTED: May be a memory hog and compilation may be a time hog as well!
import psyco
psyco.full()
except ImportError:
pass
"""
The main entry point of the simula... | main.py |
from world import *
from maingui import *
from colors import *
import numpy
import sys
try:
# i386-only optimization with Psyco
# NOT TESTED: May be a memory hog and compilation may be a time hog as well!
import psyco
psyco.full()
except ImportError:
pass
"""
The main entry point of the simula... | 0.341253 | 0.492615 |
from pathlib import Path
import re
INPUTFILE = "input.txt"
SAMPLE_CASES = [
("1 + 2 * 3 + 4 * 5 + 6", 71),
("1 + (2 * 3) + (4 * (5 + 6))", 51),
("2 * 3 + (4 * 5)", 26),
("5 + (8 * 3 + 9 + 3 * 4 * 3)", 437),
("5 * 9 * (7 * 3 * 3 + 9 * 3 + (8 + 6 * 4))", 12240),
("((2 + 4 * 9) * (6 + 9 * 8 + 6) ... | day18/day18.py | from pathlib import Path
import re
INPUTFILE = "input.txt"
SAMPLE_CASES = [
("1 + 2 * 3 + 4 * 5 + 6", 71),
("1 + (2 * 3) + (4 * (5 + 6))", 51),
("2 * 3 + (4 * 5)", 26),
("5 + (8 * 3 + 9 + 3 * 4 * 3)", 437),
("5 * 9 * (7 * 3 * 3 + 9 * 3 + (8 + 6 * 4))", 12240),
("((2 + 4 * 9) * (6 + 9 * 8 + 6) ... | 0.553505 | 0.379695 |
import sys
import fileinput
import operator
users = 1800000
def init_dict(dict_data):
global users
for i in range(users):
dict_data[i] = 0
def print_dict(dict_type, dict_data):
print(dict_type)
for key, value in sorted(dict_data.items()):
print(key, value)
print("\n")
def pri... | scripts/pq-data-process.py | import sys
import fileinput
import operator
users = 1800000
def init_dict(dict_data):
global users
for i in range(users):
dict_data[i] = 0
def print_dict(dict_type, dict_data):
print(dict_type)
for key, value in sorted(dict_data.items()):
print(key, value)
print("\n")
def pri... | 0.064087 | 0.203688 |
import numpy as np
from sklearn.base import BaseEstimator, TransformerMixin
class TrfJitter(BaseEstimator, TransformerMixin):
def __init__(self, snrdb, p=1, verbose=0):
self.snrdb = snrdb
self.snr = 10 ** (self.snrdb/10)
self.p = p
self.verbose = verbose
def fit(self, X, y=None... | code/data_tools/pipelines/augmentation.py | import numpy as np
from sklearn.base import BaseEstimator, TransformerMixin
class TrfJitter(BaseEstimator, TransformerMixin):
def __init__(self, snrdb, p=1, verbose=0):
self.snrdb = snrdb
self.snr = 10 ** (self.snrdb/10)
self.p = p
self.verbose = verbose
def fit(self, X, y=None... | 0.624752 | 0.28736 |
import enum
class Instruction(enum.Enum):
load = 0
send_short = 1
send_medium = 2
send_long = 3
start_timer = 4
stop_timer = 5
barrier_send = 6
recv_medium = 7
end = 8
barrier_wait = 9
send_long_fifo = 10
send_medium_fifo = 11
read_local = 12
class Instructions(obje... | tests/hls_kernel_data.py | import enum
class Instruction(enum.Enum):
load = 0
send_short = 1
send_medium = 2
send_long = 3
start_timer = 4
stop_timer = 5
barrier_send = 6
recv_medium = 7
end = 8
barrier_wait = 9
send_long_fifo = 10
send_medium_fifo = 11
read_local = 12
class Instructions(obje... | 0.281406 | 0.136033 |
import sys
import os
import re
import datetime
def main(args):
if len(args) < 3:
print("Usage: {} <ifile> <odir>".format(args[0]))
return -1
ifile = args[1]
odir = args[2]
with open(ifile) as ifh:
lines = [l.rstrip().strip() for l in ifh]
papers = []
current_paper ... | scripts/parse_talks.py |
import sys
import os
import re
import datetime
def main(args):
if len(args) < 3:
print("Usage: {} <ifile> <odir>".format(args[0]))
return -1
ifile = args[1]
odir = args[2]
with open(ifile) as ifh:
lines = [l.rstrip().strip() for l in ifh]
papers = []
current_paper ... | 0.076965 | 0.123049 |
from pathlib import Path
import base64
import datetime as dt
import dateutil
import json
import requests
from O365 import Account
CONFIG_FILE = 'calendar_sync_garoon_outlook.json'
WEEKS = 2
MAX_EVENT_NUM = 100
def get_period():
now = dt.datetime.now().astimezone()
#print(now.tzinfo, now.isoformat())
end =... | calendar_sync_garoon_outlook.py | from pathlib import Path
import base64
import datetime as dt
import dateutil
import json
import requests
from O365 import Account
CONFIG_FILE = 'calendar_sync_garoon_outlook.json'
WEEKS = 2
MAX_EVENT_NUM = 100
def get_period():
now = dt.datetime.now().astimezone()
#print(now.tzinfo, now.isoformat())
end =... | 0.210766 | 0.070752 |
import json
from os import listdir
from os.path import isfile, join
import random
# read all the tasks and make sure that they're following the right pattern
tasks_path = 'tasks/'
expected_keys = [
"Definition",
"Positive Examples",
"Negative Examples",
"Instances",
'Contributors',
'Categories... | src/test_all.py | import json
from os import listdir
from os.path import isfile, join
import random
# read all the tasks and make sure that they're following the right pattern
tasks_path = 'tasks/'
expected_keys = [
"Definition",
"Positive Examples",
"Negative Examples",
"Instances",
'Contributors',
'Categories... | 0.376852 | 0.511961 |
import dataclasses
import unittest
import twitterbyconfig as tbc
@dataclasses.dataclass
class PythonTwitterList:
id: int = None
name: str = None
mode: str = None
@dataclasses.dataclass
class PythonTwitterUser:
id: int = None
screen_name: str = None
class TestTwitterList(unittest.TestCase):
def test_T... | tests/test_twitter_list.py | import dataclasses
import unittest
import twitterbyconfig as tbc
@dataclasses.dataclass
class PythonTwitterList:
id: int = None
name: str = None
mode: str = None
@dataclasses.dataclass
class PythonTwitterUser:
id: int = None
screen_name: str = None
class TestTwitterList(unittest.TestCase):
def test_T... | 0.499512 | 0.315762 |
import numpy as np
import Kinematic.forward as forward
import Optimizer.objectives as obj
from Optimizer import feasibility_check, path
def get_feasible_optimum(*, q, par, q_close=None,
status=None, verbose=0,
return_cost=False):
if status is None:
status... | Optimizer/choose_optimum.py | import numpy as np
import Kinematic.forward as forward
import Optimizer.objectives as obj
from Optimizer import feasibility_check, path
def get_feasible_optimum(*, q, par, q_close=None,
status=None, verbose=0,
return_cost=False):
if status is None:
status... | 0.511717 | 0.399519 |
import torch
import torch.nn as nn
from src.backbones.convlstm import ConvLSTM, BConvLSTM
from src.backbones.ltae import LTAE2d
class UTAE(nn.Module):
def __init__(
self,
input_dim,
encoder_widths=[64, 64, 64, 128],
decoder_widths=[32, 32, 64, 128],
out_conv=[32, 20],
... | src/backbones/utae.py | import torch
import torch.nn as nn
from src.backbones.convlstm import ConvLSTM, BConvLSTM
from src.backbones.ltae import LTAE2d
class UTAE(nn.Module):
def __init__(
self,
input_dim,
encoder_widths=[64, 64, 64, 128],
decoder_widths=[32, 32, 64, 128],
out_conv=[32, 20],
... | 0.946498 | 0.449453 |
import os
import re
import click
from crontab import CronTab
from .helpers import validate_time
from .methods import archie_reboot
@click.group(name='reboot')
def reboot():
"""Reboot"""
pass
@click.command(name="now")
@click.pass_context
def reboot_now(ctx):
"""Reboot router"""
archie_reboot(ctx.... | archie_cli/reboot.py | import os
import re
import click
from crontab import CronTab
from .helpers import validate_time
from .methods import archie_reboot
@click.group(name='reboot')
def reboot():
"""Reboot"""
pass
@click.command(name="now")
@click.pass_context
def reboot_now(ctx):
"""Reboot router"""
archie_reboot(ctx.... | 0.280222 | 0.070977 |
import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
import random
from memory import BatchMaker
from config import gamma, lambda_gae, epsilon_clip, ciritic_coefficient, entropy_coefficient, epoch_k, batch_size
import warnings
class PPO(nn.Module):
def __init__(self, num_inputs,... | PG/7-PPO/model.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
import random
from memory import BatchMaker
from config import gamma, lambda_gae, epsilon_clip, ciritic_coefficient, entropy_coefficient, epoch_k, batch_size
import warnings
class PPO(nn.Module):
def __init__(self, num_inputs,... | 0.944125 | 0.561275 |
import numpy as np
import cv2
from PIL import Image
import os
def cv2_imread(file_path):
cv_img = cv2.imdecode(np.fromfile(file_path, dtype=np.uint8), -1)
return cv_img
def read_img_string(img_str):
img_array = img_str.split('_')
img_array = list(map(int, img_array))
return img_arr... | mask-prediction/get_envelope.py | import numpy as np
import cv2
from PIL import Image
import os
def cv2_imread(file_path):
cv_img = cv2.imdecode(np.fromfile(file_path, dtype=np.uint8), -1)
return cv_img
def read_img_string(img_str):
img_array = img_str.split('_')
img_array = list(map(int, img_array))
return img_arr... | 0.156041 | 0.187746 |
from sqlite3 import Error as SQLiteError
from vsutillib.sql import SqlDb
from .. import config
class SqlJobsTable(SqlDb):
"""
SqlJobsDB class to access sqlite database for saving jobs
Args:
**dbFile** (str, pathlib.Path): database file.
"""
def __init__(self, dbFile=None):
# ini... | MKVBatchMultiplex/jobs/SqlJobsTable.py | from sqlite3 import Error as SQLiteError
from vsutillib.sql import SqlDb
from .. import config
class SqlJobsTable(SqlDb):
"""
SqlJobsDB class to access sqlite database for saving jobs
Args:
**dbFile** (str, pathlib.Path): database file.
"""
def __init__(self, dbFile=None):
# ini... | 0.667148 | 0.070816 |
import pygame, random
from settings import *
vec = pygame.math.Vector2
class Enemy:
def __init__(self, app, position, index):
self.app = app
self.grid_position = position
self.pixel_position = self.get_pixel_position()
self.starting_position = [position.x, position.y]
self.... | enemy.py | import pygame, random
from settings import *
vec = pygame.math.Vector2
class Enemy:
def __init__(self, app, position, index):
self.app = app
self.grid_position = position
self.pixel_position = self.get_pixel_position()
self.starting_position = [position.x, position.y]
self.... | 0.589244 | 0.18909 |
from nose.tools import assert_equal
from networkx import asyn_lpa, Graph
def test_empty_graph():
# empty graph
test = Graph()
# ground truth
ground_truth = set()
communities = asyn_lpa.asyn_lpa_communities(test)
result = {frozenset(c) for c in communities}
assert_equal(result, ground_tru... | networkx/algorithms/community/tests/test_asyn_lpa.py | from nose.tools import assert_equal
from networkx import asyn_lpa, Graph
def test_empty_graph():
# empty graph
test = Graph()
# ground truth
ground_truth = set()
communities = asyn_lpa.asyn_lpa_communities(test)
result = {frozenset(c) for c in communities}
assert_equal(result, ground_tru... | 0.762159 | 0.629162 |
__all__ = ['SubpixelAlignment', 'PairwiseDistance', 'PRTF', 'PSD', 'EigenMode']
import itertools
from tqdm import tqdm
import numpy as np
from numpy.linalg import svd
from scipy.ndimage import fourier_shift
from skimage.registration import phase_cross_correlation
def SubpixelAlignment(input, error = None, ref = None... | PRModule/eval.py |
__all__ = ['SubpixelAlignment', 'PairwiseDistance', 'PRTF', 'PSD', 'EigenMode']
import itertools
from tqdm import tqdm
import numpy as np
from numpy.linalg import svd
from scipy.ndimage import fourier_shift
from skimage.registration import phase_cross_correlation
def SubpixelAlignment(input, error = None, ref = None... | 0.744378 | 0.465327 |
import pandas as pd
import requests as rq
import os
from time import sleep
baseURL = "https://maps.googleapis.com/maps/api/streetview?"
size = "size=640x480&"
location = "location="
keyfrag = "&key="
imgDir = "../streetview/PPImages/"
logFile = "dlLog.log"
def getDownloadedList():
files = os.listdir(imgDir)
... | scripts/crawlPlacepulse.py | import pandas as pd
import requests as rq
import os
from time import sleep
baseURL = "https://maps.googleapis.com/maps/api/streetview?"
size = "size=640x480&"
location = "location="
keyfrag = "&key="
imgDir = "../streetview/PPImages/"
logFile = "dlLog.log"
def getDownloadedList():
files = os.listdir(imgDir)
... | 0.056659 | 0.064007 |
from eadapi import scrapead
import os.path as path_os
from json import loads, dumps
DIR_NAME, _ = path_os.split(path_os.abspath(__file__))
session = None
## Code for fun
from time import sleep
import sys
TIME_LESS = 0.05
TIME = 0.07
TIME_MORE = 0.1
WAIT_TIME = 1
def print_letra(letra):
sys.stdout.write(letra)... | main.py | from eadapi import scrapead
import os.path as path_os
from json import loads, dumps
DIR_NAME, _ = path_os.split(path_os.abspath(__file__))
session = None
## Code for fun
from time import sleep
import sys
TIME_LESS = 0.05
TIME = 0.07
TIME_MORE = 0.1
WAIT_TIME = 1
def print_letra(letra):
sys.stdout.write(letra)... | 0.106319 | 0.147986 |
import datetime
from google.appengine.ext import ndb
START_SKIP = 60
LEARN_FACTOR = 5
MAX_MINUTES = 60 * 24 * 365 * 2
def fix_datetime(d):
for k in d:
if isinstance(d[k], datetime.datetime):
d[k] = d[k].isoformat()
return d
class JsonModel(ndb.Model):
def to_jdict(self):
d... | sil_model.py | import datetime
from google.appengine.ext import ndb
START_SKIP = 60
LEARN_FACTOR = 5
MAX_MINUTES = 60 * 24 * 365 * 2
def fix_datetime(d):
for k in d:
if isinstance(d[k], datetime.datetime):
d[k] = d[k].isoformat()
return d
class JsonModel(ndb.Model):
def to_jdict(self):
d... | 0.459804 | 0.117547 |
from sklearn.neighbors import KNeighborsClassifier
from sklearn.model_selection import train_test_split
from sklearn.datasets import load_iris
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D # Needed for projection='3d'
from sklearn.manifold import TSNE
from pylmnn import LargeMarginNeare... | examples/demo_plot_features.py | from sklearn.neighbors import KNeighborsClassifier
from sklearn.model_selection import train_test_split
from sklearn.datasets import load_iris
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D # Needed for projection='3d'
from sklearn.manifold import TSNE
from pylmnn import LargeMarginNeare... | 0.953449 | 0.837088 |
import os
import json
import argparse
import numpy as np
from PIL import Image
from tqdm import tqdm
import torch
from torchvision import models, transforms
import torch.nn.functional as F
from skimage.measure import compare_ssim as ssim
import torch.nn as nn
frame2file = {1: 'disc_dataset_first_frame.json... | eval_scripts/eval_disc_dataset.py | import os
import json
import argparse
import numpy as np
from PIL import Image
from tqdm import tqdm
import torch
from torchvision import models, transforms
import torch.nn.functional as F
from skimage.measure import compare_ssim as ssim
import torch.nn as nn
frame2file = {1: 'disc_dataset_first_frame.json... | 0.644337 | 0.335569 |
# ./libCommon.py
from glob import glob
from json import dumps, load, loads
from os import path, environ, remove, stat, mkdir as MKDIR
import logging
import pandas as PD
from sys import version_info
from time import time, sleep
from traceback import print_exc
try :
if version_info.major ==3 :
fr... | libCommon.py |
# ./libCommon.py
from glob import glob
from json import dumps, load, loads
from os import path, environ, remove, stat, mkdir as MKDIR
import logging
import pandas as PD
from sys import version_info
from time import time, sleep
from traceback import print_exc
try :
if version_info.major ==3 :
fr... | 0.141193 | 0.06236 |
import pytest
from textwrap import dedent
@pytest.mark.alac
def test_alac_1(db_empty, cards_cli):
"""
Starting from an empty list.
1. Add 3 items
2. Make sure they show up in the list.
3. Change the owner on a card. Verify change.
4. Change the done state on a card. Verify change.
5. Chang... | tests/cli/test_alac.py | import pytest
from textwrap import dedent
@pytest.mark.alac
def test_alac_1(db_empty, cards_cli):
"""
Starting from an empty list.
1. Add 3 items
2. Make sure they show up in the list.
3. Change the owner on a card. Verify change.
4. Change the done state on a card. Verify change.
5. Chang... | 0.634204 | 0.523177 |
import xml.etree.ElementTree as ET
class brocade_preprovision(object):
"""Auto generated class.
"""
def __init__(self, **kwargs):
self._callback = kwargs.pop('callback')
def preprovision_rbridge_id_rbridge_id(self, **kwargs):
"""Auto Generated Code
"""
con... | pynos/versions/ver_7/ver_7_1_0/yang/brocade_preprovision.py | import xml.etree.ElementTree as ET
class brocade_preprovision(object):
"""Auto generated class.
"""
def __init__(self, **kwargs):
self._callback = kwargs.pop('callback')
def preprovision_rbridge_id_rbridge_id(self, **kwargs):
"""Auto Generated Code
"""
con... | 0.501953 | 0.062189 |
import eel
import os
import glob
import shutil
import codecs
from OpenGL.GL import *
from OpenGL.WGL import *
from ctypes import *
import numpy
import pyaudio
import array
import re
class FileSystem():
def __init__(self):
self.categoryDir = './category'
self.extension = '.glsl'
... | main.py | import eel
import os
import glob
import shutil
import codecs
from OpenGL.GL import *
from OpenGL.WGL import *
from ctypes import *
import numpy
import pyaudio
import array
import re
class FileSystem():
def __init__(self):
self.categoryDir = './category'
self.extension = '.glsl'
... | 0.205296 | 0.073364 |
from matplotlib.pyplot import axis
import numpy as np
import cv2
from PIL import Image
import torch
IMAGENET_MEAN, IMAGENET_STD = np.array(
[0.485, 0.456, 0.406]), np.array([0.229, 0.224, 0.225])
def crop_image(image, bbox):
"""Crops area from image specified as bbox. Always returns area of size as bbox fil... | mvn/utils/img.py | from matplotlib.pyplot import axis
import numpy as np
import cv2
from PIL import Image
import torch
IMAGENET_MEAN, IMAGENET_STD = np.array(
[0.485, 0.456, 0.406]), np.array([0.229, 0.224, 0.225])
def crop_image(image, bbox):
"""Crops area from image specified as bbox. Always returns area of size as bbox fil... | 0.907588 | 0.70246 |
from greww.data.mysql import (databases,
tables,
make_database,
make_table,
remove_database,
remove_table,
table_primary_start)
from greww.... | greww/data/mysql/_zilean/build.py | from greww.data.mysql import (databases,
tables,
make_database,
make_table,
remove_database,
remove_table,
table_primary_start)
from greww.... | 0.275617 | 0.169612 |
import project_config
import psycopg2
try:
conn = psycopg2.connect(dbname=project_config.dbname, user=project_config.user,
host=project_config.host, password=project_config.password)
print("connected to db")
except:
print("I am unable to connect to the database")
cur = conn.cursor()
# this query... | bike_grid_calc.py | import project_config
import psycopg2
try:
conn = psycopg2.connect(dbname=project_config.dbname, user=project_config.user,
host=project_config.host, password=project_config.password)
print("connected to db")
except:
print("I am unable to connect to the database")
cur = conn.cursor()
# this query... | 0.248443 | 0.325092 |
def serialize(root, A):
#code here
# vals = []
def doit(node):
nonlocal A
if node:
A.append(node.data)
doit(node.left)
doit(node.right)
else:
A.append('#')
# print(vals)
doit(root)
return A
#Function to des... | Amazon/Serialize and Deserialize.py | def serialize(root, A):
#code here
# vals = []
def doit(node):
nonlocal A
if node:
A.append(node.data)
doit(node.left)
doit(node.right)
else:
A.append('#')
# print(vals)
doit(root)
return A
#Function to des... | 0.280222 | 0.304752 |
import matplotlib.pyplot as plt
import numpy as np
from distributions import Binomial_distribution, Discrete_uniform_distribution
def plotDistributeBar(ax, data, label='', width=0.3, offset=0, title='Probability Distribution of true'):
ax.bar(np.arange(len(data))+offset,data,width=width,label=label)
fontSize ... | src/KL_divergence.py | import matplotlib.pyplot as plt
import numpy as np
from distributions import Binomial_distribution, Discrete_uniform_distribution
def plotDistributeBar(ax, data, label='', width=0.3, offset=0, title='Probability Distribution of true'):
ax.bar(np.arange(len(data))+offset,data,width=width,label=label)
fontSize ... | 0.539469 | 0.612281 |
import pytest
from os_tornado.settings import Settings
@pytest.fixture(scope="function")
def settings():
return Settings()
def test_get_tornado_app_settings(settings):
from os_tornado.settings import TORNADO_APP_SETTINGS_PREFIX
from os_tornado.settings import get_tornado_app_settings
key = TORNADO_A... | tests/test_settings.py | import pytest
from os_tornado.settings import Settings
@pytest.fixture(scope="function")
def settings():
return Settings()
def test_get_tornado_app_settings(settings):
from os_tornado.settings import TORNADO_APP_SETTINGS_PREFIX
from os_tornado.settings import get_tornado_app_settings
key = TORNADO_A... | 0.382026 | 0.458531 |
from flask_rest_jsonapi import ResourceDetail, ResourceList, ResourceRelationship
import urllib.error
from app.api.bootstrap import api
from app.api.helpers.db import safe_query
from app.api.helpers.exceptions import UnprocessableEntity
from app.api.schema.event_topics import EventTopicSchema
from app.models import db... | app/api/event_topics.py | from flask_rest_jsonapi import ResourceDetail, ResourceList, ResourceRelationship
import urllib.error
from app.api.bootstrap import api
from app.api.helpers.db import safe_query
from app.api.helpers.exceptions import UnprocessableEntity
from app.api.schema.event_topics import EventTopicSchema
from app.models import db... | 0.505127 | 0.064095 |
import flask_login
from sqlalchemy import (
Boolean, Column, DateTime, ForeignKey, Integer, String, Text
)
from sqlalchemy.orm import declarative_base, relationship
from sqlalchemy.schema import Table
Base = declarative_base()
class User(flask_login.UserMixin):
"""User model."""
pass
class Conference(... | mngt/models.py | import flask_login
from sqlalchemy import (
Boolean, Column, DateTime, ForeignKey, Integer, String, Text
)
from sqlalchemy.orm import declarative_base, relationship
from sqlalchemy.schema import Table
Base = declarative_base()
class User(flask_login.UserMixin):
"""User model."""
pass
class Conference(... | 0.845017 | 0.245458 |
from __future__ import unicode_literals
from django.contrib import messages
from django.http import HttpResponseRedirect
from django.shortcuts import render
from webscanners.models import burp_scan_result_db, \
acunetix_scan_db, acunetix_scan_result_db
from jiraticketing.models import jirasetting
import hashlib
... | webscanners/acunetixscanner/views.py |
from __future__ import unicode_literals
from django.contrib import messages
from django.http import HttpResponseRedirect
from django.shortcuts import render
from webscanners.models import burp_scan_result_db, \
acunetix_scan_db, acunetix_scan_result_db
from jiraticketing.models import jirasetting
import hashlib
... | 0.413832 | 0.04365 |
import numpy as np
import cv2
class colorcheck():
def __init__(self):
#self.r = 0
#self.g = 0
#self.b = 0
#self.shape = (0, 0, 0)
self.size = 10
def checkcamera(self):
try:
cap = cv2.VideoCapture(1)
except:
cap = cv2.Vid... | camera.py | import numpy as np
import cv2
class colorcheck():
def __init__(self):
#self.r = 0
#self.g = 0
#self.b = 0
#self.shape = (0, 0, 0)
self.size = 10
def checkcamera(self):
try:
cap = cv2.VideoCapture(1)
except:
cap = cv2.Vid... | 0.072608 | 0.184878 |
import os
import sys
import pickle
import argparse
import numpy as np
sys.path.append(os.getcwd())
from solnml.bandits.second_layer_bandit import SecondLayerBandit
from solnml.components.utils.constants import MULTICLASS_CLS, BINARY_CLS, REGRESSION, CLS_TASKS
from solnml.datasets.utils import load_train_test_data
from... | scripts/create_algorithm_meta_info.py | import os
import sys
import pickle
import argparse
import numpy as np
sys.path.append(os.getcwd())
from solnml.bandits.second_layer_bandit import SecondLayerBandit
from solnml.components.utils.constants import MULTICLASS_CLS, BINARY_CLS, REGRESSION, CLS_TASKS
from solnml.datasets.utils import load_train_test_data
from... | 0.310904 | 0.103477 |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
from future import standard_library
standard_library.install_aliases()
from builtins import *
from django.db import transaction
from django.contrib.auth.models import Use... | test_project/personnel/tests/django_auth_user_test.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
from future import standard_library
standard_library.install_aliases()
from builtins import *
from django.db import transaction
from django.contrib.auth.models import Use... | 0.640523 | 0.116312 |
import logging
from .config import config_manager
# deprecated
CONFIG_MANAGER = config_manager
def block_processor(*args, **kwargs): # pragma: no cover
import vpype_cli
logging.warning(
"!!! `@vpype.block_processor` is deprecated, "
"use `@vpype_cli.block_processor` instead."
)
ret... | vpype/_deprecated.py | import logging
from .config import config_manager
# deprecated
CONFIG_MANAGER = config_manager
def block_processor(*args, **kwargs): # pragma: no cover
import vpype_cli
logging.warning(
"!!! `@vpype.block_processor` is deprecated, "
"use `@vpype_cli.block_processor` instead."
)
ret... | 0.500977 | 0.109944 |
import pandas as pd
import seaborn as sns
df = pd.read_csv('data/src/iris.csv', index_col=0)
# df = sns.load_dataset("iris")
print(df.head())
# sepal_length sepal_width petal_length petal_width species
# 0 5.1 3.5 1.4 0.2 setosa
# 1 4.9 3.0 1.... | notebook/seaborn_pairplot.py |
import pandas as pd
import seaborn as sns
df = pd.read_csv('data/src/iris.csv', index_col=0)
# df = sns.load_dataset("iris")
print(df.head())
# sepal_length sepal_width petal_length petal_width species
# 0 5.1 3.5 1.4 0.2 setosa
# 1 4.9 3.0 1.... | 0.351756 | 0.192369 |
from django import forms
from django.db import models
from django.db.models import CASCADE
from users.models import ProgramType, DisciplineType, HostelType
import enum
# model for leave
from django.urls import reverse
class PlaceType(enum.Enum):
NAT = 'Native'
OTH = 'Other'
class LeaveStatus... | app/models.py | from django import forms
from django.db import models
from django.db.models import CASCADE
from users.models import ProgramType, DisciplineType, HostelType
import enum
# model for leave
from django.urls import reverse
class PlaceType(enum.Enum):
NAT = 'Native'
OTH = 'Other'
class LeaveStatus... | 0.203945 | 0.08733 |
r"""A module for finding the differences between two HDF5 log files.
Compares two log files (referred to as A and B) for differences.
Provides functions for generating a human-readable summary. Log files
are represented as a dict whose values are either numpy.ndarray
objects or dict objects that are similarly struct... | analysis/util/h5comp.py |
r"""A module for finding the differences between two HDF5 log files.
Compares two log files (referred to as A and B) for differences.
Provides functions for generating a human-readable summary. Log files
are represented as a dict whose values are either numpy.ndarray
objects or dict objects that are similarly struct... | 0.639061 | 0.520253 |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
import copy
import math
import torch
from torch import nn
import torch.nn.functional as F
from torch.autograd import Function
from model.decode import generic_decode
from utils.image import... | src/lib/model/networks/base_model.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
import copy
import math
import torch
from torch import nn
import torch.nn.functional as F
from torch.autograd import Function
from model.decode import generic_decode
from utils.image import... | 0.904421 | 0.281856 |
import numpy as np
def solve_power(self, LUT, Rs):
"""Solve EEC to achieve given input / output power with respect to voltage and current constraints
Parameters
----------
self : ElecLUTdq
a ElecLUTdq object
LUT : LUTdq
Calculated look-up table
Rs: float
Stator phase r... | pyleecan/Methods/Simulation/ElecLUTdq/solve_power.py | import numpy as np
def solve_power(self, LUT, Rs):
"""Solve EEC to achieve given input / output power with respect to voltage and current constraints
Parameters
----------
self : ElecLUTdq
a ElecLUTdq object
LUT : LUTdq
Calculated look-up table
Rs: float
Stator phase r... | 0.866387 | 0.488588 |
from collections import OrderedDict
from enum import Enum
from .base import Message
from ..bot import Bot
class AtableMessage(Message):
def __init__(self, msgtype: str, atMobiles: list = None, isAtAll: bool = None):
super(AtableMessage, self).__init__(msgtype)
if atMobiles or isAtAll:
... | dtb/message/message.py | from collections import OrderedDict
from enum import Enum
from .base import Message
from ..bot import Bot
class AtableMessage(Message):
def __init__(self, msgtype: str, atMobiles: list = None, isAtAll: bool = None):
super(AtableMessage, self).__init__(msgtype)
if atMobiles or isAtAll:
... | 0.541651 | 0.453806 |
from django.views.generic import View, FormView, TemplateView, UpdateView, CreateView, ListView
from django.contrib.messages.views import SuccessMessageMixin
from django.contrib.auth.mixins import PermissionRequiredMixin
from django.shortcuts import render, redirect
from django.contrib.auth import authenticate, login, ... | user/views.py | from django.views.generic import View, FormView, TemplateView, UpdateView, CreateView, ListView
from django.contrib.messages.views import SuccessMessageMixin
from django.contrib.auth.mixins import PermissionRequiredMixin
from django.shortcuts import render, redirect
from django.contrib.auth import authenticate, login, ... | 0.393968 | 0.077797 |
import copy
import pytest
from p2p.exceptions import (
HandshakeFailure,
HandshakeFailureTooManyPeers,
MalformedMessage,
NoMatchingPeerCapabilities,
)
from p2p.peer_pool import COMMON_PEER_CONNECTION_EXCEPTIONS
from p2p.tracking.connection import (
get_timeout_for_failure,
register_error,
)
... | tests/p2p/test_connection_tracker_timeout_for_failure.py | import copy
import pytest
from p2p.exceptions import (
HandshakeFailure,
HandshakeFailureTooManyPeers,
MalformedMessage,
NoMatchingPeerCapabilities,
)
from p2p.peer_pool import COMMON_PEER_CONNECTION_EXCEPTIONS
from p2p.tracking.connection import (
get_timeout_for_failure,
register_error,
)
... | 0.505127 | 0.250959 |
import oecs.priority_queue
class EntityManager(object):
def __init__(self):
#This allows access to specific entities
#sEntityType:(sEntityName:entity)
self._dEntities = {}
#This orders the entities so that the ones with the highest draw
# priority will be first in the lis... | oecs/entity_manager.py | import oecs.priority_queue
class EntityManager(object):
def __init__(self):
#This allows access to specific entities
#sEntityType:(sEntityName:entity)
self._dEntities = {}
#This orders the entities so that the ones with the highest draw
# priority will be first in the lis... | 0.5144 | 0.327265 |
import numpy as np
import tensorflow as tf
import hetu as ht
def test_embedding(executor_ctx=ht.gpu(0)):
embedding = ht.Variable('embeddingtable', value=np.random.rand(5, 5))
index = ht.Variable(name="index")
ids = [[0, 1], [0, 1]]
ids = np.array(ids)
ids = ht.array(ids, ctx=executor_ctx)
y = ... | tests/test_embedding_op.py | import numpy as np
import tensorflow as tf
import hetu as ht
def test_embedding(executor_ctx=ht.gpu(0)):
embedding = ht.Variable('embeddingtable', value=np.random.rand(5, 5))
index = ht.Variable(name="index")
ids = [[0, 1], [0, 1]]
ids = np.array(ids)
ids = ht.array(ids, ctx=executor_ctx)
y = ... | 0.486088 | 0.532425 |
import warnings
import csv
import collections
from functools import reduce
import itertools
import pandas as pd
import numpy as np
import yfinance as yf
import matplotlib.pyplot as plt
import sklearn
import pmdarima as pm
import arch
from arch.__future__ import reindexing
from sklearn.decomposition import PCA
from skl... | front_end/static/backtest.py | import warnings
import csv
import collections
from functools import reduce
import itertools
import pandas as pd
import numpy as np
import yfinance as yf
import matplotlib.pyplot as plt
import sklearn
import pmdarima as pm
import arch
from arch.__future__ import reindexing
from sklearn.decomposition import PCA
from skl... | 0.451689 | 0.315578 |
from __future__ import unicode_literals
import sys
from curtsies.fmtfuncs import bold, green, magenta, cyan, red, plain
from bpython.curtsiesfrontend import interpreter
from bpython._py3compat import py3
from bpython.test import mock, unittest
pypy = 'PyPy' in sys.version
class TestInterpreter(unittest.TestCase)... | env/lib/python2.7/site-packages/bpython/test/test_interpreter.py |
from __future__ import unicode_literals
import sys
from curtsies.fmtfuncs import bold, green, magenta, cyan, red, plain
from bpython.curtsiesfrontend import interpreter
from bpython._py3compat import py3
from bpython.test import mock, unittest
pypy = 'PyPy' in sys.version
class TestInterpreter(unittest.TestCase)... | 0.548674 | 0.286038 |
import os
import pdb
import torch
import torch.nn as nn
import torchvision.models as models
from . import util
# https://pytorch.org/docs/stable/torchvision/models.html
# models.resnet50((pretrained=True, progress=True)), resnet18, inception_v3
#-----------------------------------------------------------------... | src/models.py |
import os
import pdb
import torch
import torch.nn as nn
import torchvision.models as models
from . import util
# https://pytorch.org/docs/stable/torchvision/models.html
# models.resnet50((pretrained=True, progress=True)), resnet18, inception_v3
#-----------------------------------------------------------------... | 0.750004 | 0.287104 |
from __future__ import absolute_import
import sys
import weakref
# weak reference to installed hooks
_IMPORT_HOOKS = weakref.WeakValueDictionary()
# must have _IMPORT_HOOKS to bootstrap hook disabling
from .inhibit import DISABLED_TYPES
def path(file_path):
"""
Include module code from a file identified by i... | include/__init__.py | from __future__ import absolute_import
import sys
import weakref
# weak reference to installed hooks
_IMPORT_HOOKS = weakref.WeakValueDictionary()
# must have _IMPORT_HOOKS to bootstrap hook disabling
from .inhibit import DISABLED_TYPES
def path(file_path):
"""
Include module code from a file identified by i... | 0.665411 | 0.214547 |
import textwrap
from json.decoder import JSONDecodeError
from typing import Dict, Iterator
from yaml import YAMLError
from .jsonutil import loadjson_all, dumpjson
from .nodes import Constant, Empty, Node
from .parser import Parser, Environment
from .util import treat
from .value import Value
from .yamlutil import dum... | jinsi/api.py | import textwrap
from json.decoder import JSONDecodeError
from typing import Dict, Iterator
from yaml import YAMLError
from .jsonutil import loadjson_all, dumpjson
from .nodes import Constant, Empty, Node
from .parser import Parser, Environment
from .util import treat
from .value import Value
from .yamlutil import dum... | 0.675122 | 0.306345 |
import logging
import os
from django.apps import AppConfig
from django.conf import settings
VERSION = (0, 8, 2)
__version__ = '.'.join((str(i) for i in VERSION))
default_app_config = __name__ + '.App'
logger = logging.getLogger(__name__)
class App(AppConfig):
name = 'theming'
class Defaults:
THEMI... | theming/__init__.py | import logging
import os
from django.apps import AppConfig
from django.conf import settings
VERSION = (0, 8, 2)
__version__ = '.'.join((str(i) for i in VERSION))
default_app_config = __name__ + '.App'
logger = logging.getLogger(__name__)
class App(AppConfig):
name = 'theming'
class Defaults:
THEMI... | 0.179531 | 0.041211 |
import re
import enum
import requests
from abc import *
from urllib.parse import urlparse, parse_qs
from bs4 import BeautifulSoup
from requests import HTTPError
class MediaSourceType(enum.Enum):
NONE = 0
ARTICLE = 1
YOUTUBE = 2
class CardViewInfo:
def __init__(self, ms_type=MediaSourceType.NONE, ur... | preview_card/cardview.py | import re
import enum
import requests
from abc import *
from urllib.parse import urlparse, parse_qs
from bs4 import BeautifulSoup
from requests import HTTPError
class MediaSourceType(enum.Enum):
NONE = 0
ARTICLE = 1
YOUTUBE = 2
class CardViewInfo:
def __init__(self, ms_type=MediaSourceType.NONE, ur... | 0.560974 | 0.102484 |
from mozurestsdk.mozuclient import default as default_client
from mozurestsdk.mozuurl import MozuUrl;
from mozurestsdk.urllocation import UrlLocation
class PublicCard(object):
def __init__(self, mozuClient = None):
self.client = mozuClient or default_client();
def create(self,request, responseFields = None)... | mozurestsdk/commerce/payments/publiccard.py | from mozurestsdk.mozuclient import default as default_client
from mozurestsdk.mozuurl import MozuUrl;
from mozurestsdk.urllocation import UrlLocation
class PublicCard(object):
def __init__(self, mozuClient = None):
self.client = mozuClient or default_client();
def create(self,request, responseFields = None)... | 0.512693 | 0.104843 |
from tango import AttrWriteType, DevState, DispLevel
from tango.server import Device, attribute, command, device_property
from time import sleep
import serial
class AgilisAGP(Device):
"""AgilisAGP
This controls an Agilis Conex AGP actuator
"""
Port = device_property(dtype='str', default_value='/... | AgilisAGP.py | from tango import AttrWriteType, DevState, DispLevel
from tango.server import Device, attribute, command, device_property
from time import sleep
import serial
class AgilisAGP(Device):
"""AgilisAGP
This controls an Agilis Conex AGP actuator
"""
Port = device_property(dtype='str', default_value='/... | 0.419053 | 0.093017 |
from math import ceil
from re import findall
from selenium.webdriver.common.keys import Keys
from .time_util import sleep
def get_links_for_tag(browser, tag, amount):
"""Fetches the number of links specified
by amount and returns a list of links"""
browser.get('https://www.instagram.com/explore/tags/'
... | instapy/like_util.py | from math import ceil
from re import findall
from selenium.webdriver.common.keys import Keys
from .time_util import sleep
def get_links_for_tag(browser, tag, amount):
"""Fetches the number of links specified
by amount and returns a list of links"""
browser.get('https://www.instagram.com/explore/tags/'
... | 0.509032 | 0.085939 |
from os import system, path
from kafka_cli.create_service import CreateService
import yaml
from time import sleep
class RunKafka:
def __init__(self, parser):
self._parser = parser
self._setting = None
self._args = None
def __call__(self, args):
self._args = args
# make... | src/kafka_bus/kafka_cli/run_kafka.py | from os import system, path
from kafka_cli.create_service import CreateService
import yaml
from time import sleep
class RunKafka:
def __init__(self, parser):
self._parser = parser
self._setting = None
self._args = None
def __call__(self, args):
self._args = args
# make... | 0.16492 | 0.095518 |
from tensorflow import make_tensor_proto
from tensorflow_serving.apis import prediction_log_pb2
from tensorflow_serving.apis import predict_pb2
from datetime import datetime
import subprocess
import os
import tensorflow as tf
import pickle
from tensorflow.keras.regularizers import L2
import faiss
import tensorflow as t... | mind/v1/main.py | from tensorflow import make_tensor_proto
from tensorflow_serving.apis import prediction_log_pb2
from tensorflow_serving.apis import predict_pb2
from datetime import datetime
import subprocess
import os
import tensorflow as tf
import pickle
from tensorflow.keras.regularizers import L2
import faiss
import tensorflow as t... | 0.611962 | 0.130784 |
from datetime import datetime
from django.db import models
from django.contrib.auth.models import AbstractUser
# Create your models here.
class UserProfile(AbstractUser):
"""
用户
"""
GRADE_TYPE = (
(1, "大学一年级"),
(2, "大学二年级"),
(3, "大学三年级"),
(4, "大学四年级"),
)
name =... | apps/user/models.py | from datetime import datetime
from django.db import models
from django.contrib.auth.models import AbstractUser
# Create your models here.
class UserProfile(AbstractUser):
"""
用户
"""
GRADE_TYPE = (
(1, "大学一年级"),
(2, "大学二年级"),
(3, "大学三年级"),
(4, "大学四年级"),
)
name =... | 0.466359 | 0.158728 |
import json
from behave import when
import pubnub
from pubnub.exceptions import PubNubException
def execute_pam_call(context):
context.grant_result = context.peer.grant_token().channels(
list(context.resources_to_grant["CHANNEL"].values())
).groups(
list(context.resources_to_grant["CHANNEL_GR... | tests/acceptance/pam/steps/when_steps.py | import json
from behave import when
import pubnub
from pubnub.exceptions import PubNubException
def execute_pam_call(context):
context.grant_result = context.peer.grant_token().channels(
list(context.resources_to_grant["CHANNEL"].values())
).groups(
list(context.resources_to_grant["CHANNEL_GR... | 0.347869 | 0.157137 |
from lxml import etree
from span_data import Cspan
class Ccoreference:
"""
This class encapsulates a coreference object in KAF/NAF
"""
def __init__(self,node=None,type='NAF'):
"""
Constructor of the object
@type node: xml Element or None (to create and empty one)
@param ... | KafNafParserPy/coreference_data.py | from lxml import etree
from span_data import Cspan
class Ccoreference:
"""
This class encapsulates a coreference object in KAF/NAF
"""
def __init__(self,node=None,type='NAF'):
"""
Constructor of the object
@type node: xml Element or None (to create and empty one)
@param ... | 0.753557 | 0.365174 |
from functools import singledispatch
from typing import (Any,
Callable,
Iterable,
Sequence,
Tuple,
TypeVar,
Union)
from bentley_ottmann.planar import segments_cross_or_overlap
from ground.base import... | tests/utils.py | from functools import singledispatch
from typing import (Any,
Callable,
Iterable,
Sequence,
Tuple,
TypeVar,
Union)
from bentley_ottmann.planar import segments_cross_or_overlap
from ground.base import... | 0.83752 | 0.374733 |
import numpy as np
from scipy.special import logsumexp, gammaln
from astropy import constants, units as au
from astropy.units import Quantity
Gauss = 1e-4 * au.T
au.set_enabled_equivalencies(au.dimensionless_angles())
def pad_with_absorbing_boundary_conditions(k2, k02, N, *coords, dn_max=0.05):
if dn_max is None... | born_rime/potentials.py | import numpy as np
from scipy.special import logsumexp, gammaln
from astropy import constants, units as au
from astropy.units import Quantity
Gauss = 1e-4 * au.T
au.set_enabled_equivalencies(au.dimensionless_angles())
def pad_with_absorbing_boundary_conditions(k2, k02, N, *coords, dn_max=0.05):
if dn_max is None... | 0.791861 | 0.424352 |
import numpy as np
import pandas as pd
from matplotlib import dates
from scipy.interpolate import interp1d
class System:
'''
Class of whole system
'''
def __init__(self, farms, c_matrix,delta_time,temperature_input =None,inital_start=0):
'''
:params:
farms Ein list... | Simulator_engine/System_3_FO.py | import numpy as np
import pandas as pd
from matplotlib import dates
from scipy.interpolate import interp1d
class System:
'''
Class of whole system
'''
def __init__(self, farms, c_matrix,delta_time,temperature_input =None,inital_start=0):
'''
:params:
farms Ein list... | 0.075952 | 0.382401 |
from rest_app.domain import Book, BookUpdate, BookNotFoundException
from typing import List, Optional
from datetime import date
import re
class MemoryBookStorage:
"""Base storage for books that save data in memory."""
def __init__(self):
self.id_counter = 0
self.books = []
@staticmetho... | src/rest_app/storage/memory.py | from rest_app.domain import Book, BookUpdate, BookNotFoundException
from typing import List, Optional
from datetime import date
import re
class MemoryBookStorage:
"""Base storage for books that save data in memory."""
def __init__(self):
self.id_counter = 0
self.books = []
@staticmetho... | 0.844216 | 0.258882 |
import io
import gzip
import argparse
import os
from str_utils import *
import pickle
from time import time, strftime
class FreebaseDumpFilter:
def __init__(self, fbids_filename, map_fbid_nodeindex_filename):
self.now = strftime("%Y_%m_%d_%H_%M")
self.fbid_nodeindex_map = self.load_nodes(fbids_fil... | src/fb_dump_filter.py |
import io
import gzip
import argparse
import os
from str_utils import *
import pickle
from time import time, strftime
class FreebaseDumpFilter:
def __init__(self, fbids_filename, map_fbid_nodeindex_filename):
self.now = strftime("%Y_%m_%d_%H_%M")
self.fbid_nodeindex_map = self.load_nodes(fbids_fil... | 0.306942 | 0.12921 |
def tests_compiler():
"""Test Compiler"""
import platform
import subprocess
from compilertools.compilers._core import _get_arch_and_cpu
from compilertools.compilers.llvm import Compiler
cmd = {
"python": "",
"--version": "",
"-dumpversion": "",
"not_found": False... | tests/test_compilers_llvm.py | def tests_compiler():
"""Test Compiler"""
import platform
import subprocess
from compilertools.compilers._core import _get_arch_and_cpu
from compilertools.compilers.llvm import Compiler
cmd = {
"python": "",
"--version": "",
"-dumpversion": "",
"not_found": False... | 0.430866 | 0.270556 |
import unittest
from cozy.target_syntax import *
from cozy.syntax_tools import mk_lambda, pprint, fresh_var, free_vars, alpha_equivalent
from cozy.typecheck import retypecheck
from cozy.solver import satisfy, valid
from cozy.evaluation import eval, construct_value
from cozy.synthesis.acceleration import optimized_in
... | tests/semantics.py | import unittest
from cozy.target_syntax import *
from cozy.syntax_tools import mk_lambda, pprint, fresh_var, free_vars, alpha_equivalent
from cozy.typecheck import retypecheck
from cozy.solver import satisfy, valid
from cozy.evaluation import eval, construct_value
from cozy.synthesis.acceleration import optimized_in
... | 0.456168 | 0.510985 |
import os
import base64
import pygame as pg
pg.init()
class Cycle(object):
'''
Sets the values for the time and season functionality
'''
def __init__(self):
'''
6 seconds = 1 day
60 seconds = 10 days
1 maintenance cycle = 3 seconds = 1 day
1 earn cycle = 1/2 mi... | modules/backend.py | import os
import base64
import pygame as pg
pg.init()
class Cycle(object):
'''
Sets the values for the time and season functionality
'''
def __init__(self):
'''
6 seconds = 1 day
60 seconds = 10 days
1 maintenance cycle = 3 seconds = 1 day
1 earn cycle = 1/2 mi... | 0.386995 | 0.229967 |