repository_name stringlengths 7 107 | function_path stringlengths 4 190 | function_identifier stringlengths 1 236 | language stringclasses 1
value | function stringlengths 9 647k | docstring stringlengths 5 488k | function_url stringlengths 71 285 | context stringlengths 0 2.51M | license stringclasses 5
values |
|---|---|---|---|---|---|---|---|---|
quantopian/qdb | qdb/comm.py | RemoteCommandManager.command_list | python | def command_list(self, tracer, payload):
if not self.payload_check(payload, 'list'):
return self.next_command.tailcall(tracer)
filename = payload.get('file') or tracer.default_file
try:
if tracer.skip_fn(filename):
raise KeyError
if not (payl... | List the contents of a file and defer to user control. | https://github.com/quantopian/qdb/blob/c25018d2f0979589a38a07667478cb6022d57ed9/qdb/comm.py#L556-L599 | from __future__ import print_function
from abc import ABCMeta, abstractmethod
import atexit
from bdb import Breakpoint
import errno
from functools import partial
import json
import os
from pprint import pprint
import signal
import socket
from struct import pack, unpack
from textwrap import dedent
from logbook import Lo... | Apache License 2.0 |
dojoteef/dvae | dvae/models/factory.py | ModelFactoryFunction.define_model | python | def define_model(self, graph, reuse=None, **kwargs):
pass | Return a new model. | https://github.com/dojoteef/dvae/blob/93665f17b346a3f42dea7c607e4c5f8365b5895d/dvae/models/factory.py#L91-L93 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from abc import abstractmethod
from abc import abstractproperty
from abc import ABCMeta as AbstractBaseClass
from six import iteritems
from six.moves import xrange
import tensorflow as tf
from dvae.datasets.da... | Apache License 2.0 |
speleo3/pymol-psico | psico/electrostatics.py | validate_apbs_exe | python | def validate_apbs_exe(exe):
import os, subprocess
if exe:
exe = cmd.exp_path(exe)
else:
try:
import freemol.apbs
exe = freemol.apbs.get_exe_path()
except:
pass
if not exe:
exe = cmd.exp_path('$SCHRODINGER/utilities/apbs')
... | Get and validate apbs executable.
Raise CmdException if not found or broken. | https://github.com/speleo3/pymol-psico/blob/4e5402b4dca9a509b34a03691f12dc49e93c4973/psico/electrostatics.py#L47-L73 | from __future__ import print_function
from pymol import cmd, CmdException
template_apbs_in = '''
read
mol pqr "{pqrfile}"
end
elec
mg-auto
mol 1
fgcent {fgcent} # fine grid center
cgcent mol 1 # coarse grid center
fglen {fglen}
cglen {cglen}
dime {dime}
lpbe # l=linear, n... | BSD 2-Clause Simplified License |
harmon758/harmonbot | Discord/cogs/cryptography.py | Cryptography.encode_blake2b | python | async def encode_blake2b(self, ctx, *, message: str):
digest = crypto_hashes.Hash(crypto_hashes.BLAKE2b(64), backend = openssl_backend)
digest.update(message.encode("UTF-8"))
await ctx.embed_reply(digest.finalize()) | 64-byte digest BLAKE2b | https://github.com/harmon758/harmonbot/blob/def3849beabdaea5e0f9c594dcf6d6d8980782bd/Discord/cogs/cryptography.py#L175-L179 | from discord.ext import commands
import hashlib
import sys
from typing import Optional
import zlib
from cryptography.hazmat.backends.openssl import backend as openssl_backend
from cryptography.hazmat.primitives import hashes as crypto_hashes
import pygost.gost28147
import pygost.gost28147_mac
import pygost.gost34112012... | MIT License |
jaegertracing/jaeger-client-python | jaeger_client/thrift_gen/jaeger/Collector.py | Client.submitBatches | python | def submitBatches(self, batches):
self._seqid += 1
future = self._reqs[self._seqid] = concurrent.Future()
self.send_submitBatches(batches)
return future | Parameters:
- batches | https://github.com/jaegertracing/jaeger-client-python/blob/a6c973158bf9b02cd7f5a966ccfd29ab86c44a5b/jaeger_client/thrift_gen/jaeger/Collector.py#L70-L78 | import six
from six.moves import xrange
from thrift.Thrift import TType, TMessageType, TException, TApplicationException
import logging
from .ttypes import *
from thrift.Thrift import TProcessor
from thrift.transport import TTransport
from thrift.protocol import TBinaryProtocol, TProtocol
try:
from thrift.protocol im... | Apache License 2.0 |
zhaozhibin/dl-based-intelligent-diagnosis-benchmark | AE_Datasets/R_NA/datasets/XJTU.py | data_load | python | def data_load(filename,label):
fl = pd.read_csv(filename)
fl = fl["Horizontal_vibration_signals"]
fl = fl.values
fl = fl.reshape(-1,1)
data=[]
lab=[]
start,end=0,signal_size
while end<=fl.shape[0]:
data.append(fl[start:end])
lab.append(label)
start +=signal_size
... | This function is mainly used to generate test data and training data.
filename:Data location | https://github.com/zhaozhibin/dl-based-intelligent-diagnosis-benchmark/blob/6dca48f36c2a0bceaad8329089100045fe440bbb/AE_Datasets/R_NA/datasets/XJTU.py#L53-L70 | import os
import pandas as pd
from sklearn.model_selection import train_test_split
from datasets.SequenceDatasets import dataset
from datasets.sequence_aug import *
from tqdm import tqdm
signal_size=1024
label1 = [i for i in range(0,5)]
label2 = [i for i in range(5,10)]
label3 = [i for i in range(10,15)]
def get_files(... | MIT License |
micom-dev/micom | micom/community.py | Community.__init__ | python | def __init__(
self,
taxonomy,
model_db=None,
id=None,
name=None,
rel_threshold=1e-6,
solver=None,
progress=True,
max_exchange=100,
mass=1,
):
super(Community, self).__init__(id, name)
logger.info("building new micom mode... | Create a new community object.
`micom` builds a community from a taxonomy which may simply be a list
of model files in its simplest form. Usually, the taxonomy will contain
additional information such as annotations for the individuals (for
instance phylum, organims or species) and abun... | https://github.com/micom-dev/micom/blob/b8e3eda8a97ed2fe08e1416711d3a4f1f98bc3a9/micom/community.py#L40-L299 | import re
import pickle
import cobra
import pandas as pd
from optlang.symbolics import Zero
from micom.db import load_zip_model_db, load_manifest
from micom.util import (
load_model,
join_models,
add_var_from_expression,
adjust_solver_config,
clean_ids,
compartment_id,
COMPARTMENT_RE,
)
from... | Apache License 2.0 |
geophysics-ubonn/reda | lib/reda/eis/units.py | get_label | python | def get_label(parameter, ptype, flavor=None, mpl=None):
if flavor is not None:
if flavor not in ('latex', 'mathml'):
raise Exception('flavor not recognized: {}'.format(flavor))
else:
if mpl is None:
raise Exception('either the flavor or mpl must be provided')
rend... | Return the label of a given SIP parameter
Parameters
----------
parameter : str
type of parameter, e.g. rmag|rpha|cre|cim
ptype : string
material|meas. Either return the material property (e.g. resistivity)
or the measurement parameter (e.g., impedance)
flavor : string, opti... | https://github.com/geophysics-ubonn/reda/blob/5be52ecb184f45f0eabb23451f039fec3d9537c5/lib/reda/eis/units.py#L47-L90 | labels = {
'rmag': {
'material': {
'latex': r'$|\rho|~[\Omega m]$',
'mathml': r'$|\rho| [\Omega m]$',
},
'meas': {
'latex': r'$|Z|~[\Omega]$',
'mathml': r'$|Z| [\Omega]$',
},
},
'rpha': {
'material': {
'latex... | MIT License |
microsoft/univl | modules/until_module.py | PreTrainedModel.from_pretrained | python | def from_pretrained(cls, config, state_dict=None, *inputs, **kwargs):
model = cls(config, *inputs, **kwargs)
if state_dict is None:
return model
model = cls.init_preweight(model, state_dict)
return model | Instantiate a PreTrainedModel from a pre-trained model file or a pytorch state dict.
Download and cache the pre-trained model file if needed. | https://github.com/microsoft/univl/blob/0a7c07f566a3b220731f4abcaa6e1ee59a686596/modules/until_module.py#L166-L177 | import logging
import numpy as np
import torch
from torch import nn
import torch.nn.functional as F
import math
from modules.until_config import PretrainedConfig
logger = logging.getLogger(__name__)
def gelu(x):
return x * 0.5 * (1.0 + torch.erf(x / math.sqrt(2.0)))
def swish(x):
return x * torch.sigmoid(x)
ACT... | MIT License |
genomoncology/related | src/related/validators.py | regex | python | def regex(match_string):
return _RegexValidator(match_string) | A validator that executes each validator passed as arguments. | https://github.com/genomoncology/related/blob/3799cde862b8c9500931706f5f1ce5576028f642/src/related/validators.py#L42-L46 | from attr import attr, attributes
import re
@attributes(repr=False, slots=True)
class _CompositeValidator(object):
validators = attr()
def __call__(self, inst, attr, value):
for validator in self.validators:
validator(inst, attr, value)
def __repr__(self):
return (
"<... | MIT License |
iperdance/ipercore | iPERCore/tools/trainers/lwg_trainer.py | LWGTrainer.optimize_D | python | def optimize_D(self, fake_bg, fake_tsf_imgs):
bs, nt, c, h, w = fake_tsf_imgs.shape
fake_tsf_imgs = fake_tsf_imgs.view(bs * nt, c, h, w)
real_tsf_imgs = self._real_tsf.reshape(bs * nt, c, h, w)
tsf_cond = self._input_G_tsf[:, :, -3:].view(bs * nt, -1, h, w)
fake_input_D = torch.c... | Args:
fake_bg (torch.Tensor):
fake_tsf_imgs (torch.Tensor):
Returns: | https://github.com/iperdance/ipercore/blob/1c15b8208a4313c91ce6bf7a97a15fe43cee4a74/iPERCore/tools/trainers/lwg_trainer.py#L791-L832 | import abc
import torch
import torch.nn.functional as F
from collections import OrderedDict
from iPERCore.models.networks import NetworksFactory
from iPERCore.models.networks.criterions import VGGLoss, FaceLoss, LSGANLoss, TVLoss, TemporalSmoothLoss
from iPERCore.tools.utils.filesio.cv_utils import tensor2im
from .base... | Apache License 2.0 |
demetoir/allgans | util/Stacker.py | Stacker.max_pooling | python | def max_pooling(self, filter_):
return self.add_layer(max_pooling, filter_) | add max pooling layer | https://github.com/demetoir/allgans/blob/2f972db5e9a65f18aee0695d817f4acc221e54da/util/Stacker.py#L104-L106 | from util.tensor_ops import *
class Stacker:
def __init__(self, start_layer=None, reuse=False, name="stacker"):
self.reuse = reuse
self.layer_count = 1
self.last_layer = start_layer
self.layer_seq = [start_layer]
self.name = name
def add_layer(self, func, *args, **kwargs)... | MIT License |
paddlepaddle/paddle | python/paddle/fluid/entry_attr.py | EntryAttr._to_attr | python | def _to_attr(self):
raise NotImplementedError("EntryAttr is base class") | Returns the attributes of this parameter.
Returns:
Parameter attributes(map): The attributes of this parameter. | https://github.com/paddlepaddle/paddle/blob/056b87414880e0520bb4560fc40d5b62db9c5175/python/paddle/fluid/entry_attr.py#L31-L38 | from __future__ import print_function
__all__ = ['ProbabilityEntry', 'CountFilterEntry']
class EntryAttr(object):
def __init__(self):
self._name = None | Apache License 2.0 |
garoe/tf_mvg | mvg_distributions/covariance_representations/covariance_conv.py | PrecisionConvCholFilters.np_off_diag_mask | python | def np_off_diag_mask(self):
assert self.recons_filters_precision.shape[1:3].is_fully_defined()
n = self.recons_filters_precision.shape[1].value
n_width = int(np.sqrt(n))
nb = self.recons_filters_precision.shape[2].value
nf = int(np.sqrt(nb))
kernel = np.zeros((nf, nf), dt... | Returns a ndarray of [n,n] that is 1 of the off-diagonal elements in L | https://github.com/garoe/tf_mvg/blob/01bc681a8b3aac5dcf0837d481b963f4968eb777/mvg_distributions/covariance_representations/covariance_conv.py#L567-L585 | import numpy as np
import tensorflow as tf
from mvg_distributions.covariance_representations.covariance_matrix import Covariance, SampleMethod
from mvg_distributions.utils.variable_filter_functions import conv2d_samples_linear_combination_filters
from mvg_distributions.utils.unpooling import unpooling2d_zero_filled
imp... | MIT License |
redcokedevelopment/teapot.py | teapot/cogs/music.py | Music.queue | python | async def queue(self, ctx, page: int = 1):
player = self.bot.lavalink.player_manager.get(ctx.guild.id)
if not player.queue:
return await ctx.send('Nothing queued.')
items_per_page = 10
pages = math.ceil(len(player.queue) / items_per_page)
start = (page - 1) * items_pe... | Shows the player's queue. | https://github.com/redcokedevelopment/teapot.py/blob/aa4e92d7a1bf6f997051ae3422ba52fc034e317b/teapot/cogs/music.py#L140-L160 | import math
import re
import discord
import lavalink
from discord.ext import commands
import teapot
url_rx = re.compile('https?:\\/\\/(?:www\\.)?.+')
class Music(commands.Cog):
def __init__(self, bot):
self.bot = bot
if not hasattr(bot, 'lavalink'):
bot.lavalink = lavalink.Client(bot... | MIT License |
kirthevasank/nasbot | nn/nn_comparators.py | _get_conv_filter_size_cost | python | def _get_conv_filter_size_cost(labi, labj, conv_scale):
conv_diff = float(abs(int(labi[-1]) - int(labj[-1])))
return conv_scale * np.sqrt(conv_diff) | Returns the cost for comparing two different convolutional filters. | https://github.com/kirthevasank/nasbot/blob/3c745dc986be30e3721087c8fa768099032a0802/nn/nn_comparators.py#L27-L30 | import numpy as np
from gp.kernel import ExpSumOfDistsKernel, SumOfExpSumOfDistsKernel
from nn import neural_network
from utils.oper_utils import opt_transport
DFLT_TRANSPORT_DIST = 'lp'
DFLT_CONN_COST_FUNC = 'linear'
DFLT_KERN_DIST_POWERS = 1
REPLACE_COST_INF_WITH = 7.65432e5
CONV_RES_RAW_COST_FRAC = 0.9
CNN_STRUCTURA... | MIT License |
aws/aws-iot-device-sdk-python | AWSIoTPythonSDK/core/greengrass/discovery/providers.py | DiscoveryInfoProvider.configureCredentials | python | def configureCredentials(self, caPath, certPath, keyPath):
self._ca_path = caPath
self._cert_path = certPath
self._key_path = keyPath | **Description**
Used to configure the credentials for discovery request. Should be called before the discovery request happens.
**Syntax**
.. code:: python
myDiscoveryInfoProvider.configureCredentials("my/ca/path", "my/cert/path", "my/key/path")
**Parameters**
*ca... | https://github.com/aws/aws-iot-device-sdk-python/blob/a67eadfcbf9d229229b18435fb7a109685250854/AWSIoTPythonSDK/core/greengrass/discovery/providers.py#L145-L173 | from AWSIoTPythonSDK.exception.AWSIoTExceptions import DiscoveryInvalidRequestException
from AWSIoTPythonSDK.exception.AWSIoTExceptions import DiscoveryUnauthorizedException
from AWSIoTPythonSDK.exception.AWSIoTExceptions import DiscoveryDataNotFoundException
from AWSIoTPythonSDK.exception.AWSIoTExceptions import Disco... | Apache License 2.0 |
santhisenan/sdn_ddos_simulation | ddpg/replay_buffer.py | ReplayBuffer.sample_batch | python | def sample_batch(self, batch_size=32):
_available_batch_length = self._count if self._count < batch_size else batch_size
batch = random.sample(self._buffer, _available_batch_length)
_states = np.array([_experience[0] for _experience in batch])
_actions = np.array([_experience[... | If the number of elements in the replay memory is less than the required
batch_size, then return only those elements present in the memory, else
return 'batch_size' number of elements. | https://github.com/santhisenan/sdn_ddos_simulation/blob/be0f812de4d2e0668f1266a71172948123e3750c/ddpg/replay_buffer.py#L24-L44 | from collections import deque
import random
import numpy as np
class ReplayBuffer(object):
def __init__(self, buffer_size):
self._buffer_size = buffer_size
self._count = 0
self._buffer = deque()
def insert(self, _experience):
if(self._count <= self._buffer_size):
sel... | MIT License |
hyde/hyde | setup.py | find_package_data | python | def find_package_data(
where='.', package='',
exclude=standard_exclude,
exclude_directories=standard_exclude_directories,
only_in_packages=True,
show_ignored=False):
out = {}
stack = [(convert_path(where), '', package, only_in_packages)]
while stack:
where, pr... | Return a dictionary suitable for use in ``package_data``
in a distutils ``setup.py`` file.
The dictionary looks like::
{'package': [files]}
Where ``files`` is a list of all the files in that package that
don't match anything in ``exclude``.
If ``only_in_packages`` is true, then top-level... | https://github.com/hyde/hyde/blob/7f415402cc3e007a746eb2b5bc102281fdb415bd/setup.py#L26-L104 | from setuptools import setup, find_packages
from hyde.version import __version__
from distutils.util import convert_path
from fnmatch import fnmatchcase
import os
import sys
PROJECT = 'hyde'
try:
long_description = open('README.rst', 'rt').read()
except IOError:
long_description = ''
standard_exclude = ('*.py',... | MIT License |
openfun/marsha | src/backend/marsha/core/serializers/video.py | ThumbnailSerializer.get_urls | python | def get_urls(self, obj):
if obj.uploaded_on:
base = f"{settings.AWS_S3_URL_PROTOCOL}://{settings.CLOUDFRONT_DOMAIN}/{obj.video.pk}"
urls = {}
stamp = time_utils.to_timestamp(obj.uploaded_on)
for resolution in settings.VIDEO_RESOLUTIONS:
urls[resolu... | Urls of the thumbnail.
Parameters
----------
obj : Type[models.Thumbnail]
The thumbnail that we want to serialize
Returns
-------
Dict or None
The urls for the thumbnail.
None if the thumbnail is still not uploaded to S3 with success. | https://github.com/openfun/marsha/blob/550be08d7cad91579cd1cc2548ea95751113f15d/src/backend/marsha/core/serializers/video.py#L250-L272 | from datetime import timedelta
from urllib.parse import quote_plus
from django.conf import settings
from django.shortcuts import get_object_or_404
from django.urls import reverse
from django.utils import timezone
from django.utils.text import slugify
from botocore.signers import CloudFrontSigner
from rest_framework imp... | MIT License |
compas-dev/compas | src/compas/datastructures/network/matrices.py | network_adjacency_matrix | python | def network_adjacency_matrix(network, rtype='array'):
key_index = network.key_index()
adjacency = [[key_index[nbr] for nbr in network.neighbors(key)] for key in network.nodes()]
return adjacency_matrix(adjacency, rtype=rtype) | Creates a node adjacency matrix from a Network datastructure.
Parameters
----------
network : obj
Network datastructure object to get data from.
rtype : {'array', 'csc', 'csr', 'coo', 'list'}
Format of the result.
Returns
-------
array-like
Constructed adjacency mat... | https://github.com/compas-dev/compas/blob/d795a8bfe9f21ffa124d09e37e9c0ed2e3520057/src/compas/datastructures/network/matrices.py#L33-L51 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from compas.numerical import adjacency_matrix
from compas.numerical import degree_matrix
from compas.numerical import connectivity_matrix
from compas.numerical import laplacian_matrix
__all__ = [
'network_ad... | MIT License |
laixintao/pingtop | pingtop/ping.py | checksum | python | def checksum(source_string):
sum = 0
count_to = int((len(source_string) / 2) * 2)
for count in range(0, count_to, 2):
this = source_string[count + 1] * 256 + source_string[count]
sum = sum + this
sum = sum & 0xffffffff
if count_to < len(source_string):
sum = sum + ord(s... | I'm not too confident that this is right but testing seems
to suggest that it gives the same answers as in_cksum in ping.c | https://github.com/laixintao/pingtop/blob/75353119db1af8635fec85a9bf38722e152c426c/pingtop/ping.py#L110-L134 | __version__ = "0.2"
import os
import select
import socket
import struct
import sys
import time
ICMP_ECHO_REQUEST = 8 | MIT License |
zimbra-community/python-zimbra | pythonzimbra/communication.py | Communication.gen_request | python | def gen_request(self, request_type="json", token=None, set_batch=False,
batch_onerror=None):
if request_type == "json":
local_request = RequestJson()
elif request_type == "xml":
local_request = RequestXml()
else:
raise UnknownRequestType()
... | Convenience method to quickly generate a token
:param request_type: Type of request (defaults to json)
:param token: Authentication token
:param set_batch: Also set this request to batch mode?
:param batch_onerror: Onerror-parameter for batch mode
:return: The request | https://github.com/zimbra-community/python-zimbra/blob/1b4b1e0650bfab52f8df402f217ad5873f01d610/pythonzimbra/communication.py#L59-L89 | from __future__ import unicode_literals
import sys
if sys.version < '3':
import urllib2 as ur
import urllib2 as ue
else:
import urllib.request as ur
import urllib.error as ue
from pythonzimbra.request_json import RequestJson
from pythonzimbra.request_xml import RequestXml
from pythonzimbra.respo... | BSD 2-Clause Simplified License |
partho-maple/coding-interview-gym | leetcode.com/python/457_Circular_Array_Loop.py | Solution.circularArrayLoop | python | def circularArrayLoop(self, nums):
for i in range(len(nums)):
is_forward = nums[i] >= 0
slow, fast = i, i
while True:
slow = self.find_next_index(nums, is_forward, slow)
fast = self.find_next_index(nums, is_forward, fast)
if (... | :type nums: List[int]
:rtype: bool | https://github.com/partho-maple/coding-interview-gym/blob/f11c78b6e42d1014296fc0f360aa6fc530600493/leetcode.com/python/457_Circular_Array_Loop.py#L2-L26 | class Solution(object): | MIT License |
mpi4jax/mpi4jax | examples/shallow_water.py | get_initial_conditions | python | def get_initial_conditions():
u0_global = 10 * jnp.exp(
-((yy_global - 0.5 * length_y) ** 2) / (0.02 * length_x) ** 2
)
v0_global = jnp.zeros_like(u0_global)
coriolis_global = CORIOLIS_F + yy_global * CORIOLIS_BETA
h_geostrophy = np.cumsum(-dy * u0_global * coriolis_global / GRAVITY, axis=0)... | For the initial conditions, we use a horizontal jet in geostrophic balance. | https://github.com/mpi4jax/mpi4jax/blob/e3ed6f00a5552099f260c6b1f68588917461403b/examples/shallow_water.py#L139-L170 | import os
import sys
import math
import time
import warnings
from contextlib import ExitStack
from collections import namedtuple
from functools import partial
import numpy as np
from mpi4py import MPI
try:
import tqdm
except ImportError:
warnings.warn("Could not import tqdm, can't show progress bar")
HAS_TQ... | MIT License |
elsonidoq/fito | fito/data_store/base.py | BaseDataStore.get_id | python | def get_id(self, spec):
raise NotImplementedError() | Get's the internal id of a given spec, it should raise KeyError if spec not in self | https://github.com/elsonidoq/fito/blob/e76ab0a9a4eb954b6d88c190cb57d112f94739e1/fito/data_store/base.py#L82-L86 | from fito import config
import warnings
from functools import wraps
from fito import Spec
from fito.data_store.rehash_ui import RehashUI
from fito.operation_runner import FifoCache, OperationRunner
from fito.operations.decorate import as_operation
from fito.specs.base import get_import_path
from fito.specs.fields impor... | MIT License |
dedsecinside/awesome-scripts | APIs/Telegram API/telethon/client/telegrambaseclient.py | TelegramBaseClient._create_exported_sender | python | async def _create_exported_sender(self: 'TelegramClient', dc_id):
dc = await self._get_dc(dc_id)
sender = MTProtoSender(None, loggers=self._log)
await sender.connect(self._connection(
dc.ip_address,
dc.port,
dc.id,
loggers=self._log,
pr... | Creates a new exported `MTProtoSender` for the given `dc_id` and
returns it. This method should be used by `_borrow_exported_sender`. | https://github.com/dedsecinside/awesome-scripts/blob/856835e5ff5f8a6af2d74bb25800c620feb712e3/APIs/Telegram API/telethon/client/telegrambaseclient.py#L666-L693 | import abc
import re
import asyncio
import collections
import logging
import platform
import time
import typing
from .. import version, helpers, __name__ as __base_name__
from ..crypto import rsa
from ..entitycache import EntityCache
from ..extensions import markdown
from ..network import MTProtoSender, Connection, Con... | MIT License |
libcity/bigscity-libcity-datasets | old_backup/nyc_taxi_od.py | convert_to_trajectory | python | def convert_to_trajectory(df):
start = df[['drive_id', 'PULocationID', 'tpep_pickup_datetime']]
end = df[['drive_id', 'DOLocationID', 'tpep_dropoff_datetime']]
start.columns = ['driveid', 'geo_id', 'time_str']
end.columns = ['driveid', 'geo_id', 'time_str']
trajectory_data = pd.concat((start, end), ... | :param df: all data
:return: df['driveid', 'geo_id', 'time', 'timestamp'] | https://github.com/libcity/bigscity-libcity-datasets/blob/9d686af4731d7db821298345734926c0437703e6/old_backup/nyc_taxi_od.py#L95-L107 | import json
import math
import os
from datetime import datetime
import numpy as np
import pandas as pd
old_time_format = '%Y-%m-%d %H:%M:%S'
new_time_format = '%Y-%m-%dT%H:%M:%SZ'
def get_data_url(input_dir_flow, start_year, start_month, end_year, end_month):
pattern = input_dir_flow + "/yellow_tripdata_%d-%02d.csv... | Apache License 2.0 |
ericsson/codechecker | codechecker_common/skiplist_handler.py | SkipListHandler.__call__ | python | def __call__(self, source_file_path: str) -> bool:
return self.should_skip(source_file_path) | Check if the given source should be skipped. | https://github.com/ericsson/codechecker/blob/d2db1b49e8a2b775d41436406b5a2e5d9af76c0f/codechecker_common/skiplist_handler.py#L105-L109 | import fnmatch
import re
import os
from codechecker_common.logger import get_logger
LOG = get_logger('system')
class SkipListHandler:
def __init__(self, skip_file_content=""):
self.__skip = []
if not skip_file_content:
skip_file_content = ""
self.__skip_file_lines = [line.strip()... | Apache License 2.0 |
docusign/docusign-python-client | docusign_esign/models/commission_number.py | CommissionNumber.anchor_x_offset | python | def anchor_x_offset(self):
return self._anchor_x_offset | Gets the anchor_x_offset of this CommissionNumber. # noqa: E501
Specifies the X axis location of the tab, in anchorUnits, relative to the anchorString. # noqa: E501
:return: The anchor_x_offset of this CommissionNumber. # noqa: E501
:rtype: str | https://github.com/docusign/docusign-python-client/blob/c6aeafff0d046fa6c10a398be83ba9e24b05d4ea/docusign_esign/models/commission_number.py#L803-L811 | import pprint
import re
import six
from docusign_esign.client.configuration import Configuration
class CommissionNumber(object):
"""
Attributes:
swagger_types (dict): The key is attribute name
and the value is attribute type.
attribute_map (dict): The key is attribute n... | MIT License |
lsapan/docker-swarm-demo | secrets.py | secret | python | def secret(name, strip=True):
with open(secret_path(name), 'r') as f:
val = f.read()
if strip:
val = val.strip()
return val | Returns the value of a secret from the docker container. | https://github.com/lsapan/docker-swarm-demo/blob/f6b905fbbbe4b74d62a4af664f9a677f3cb03b8e/secrets.py#L18-L26 | import os
class SecretNotFoundError(IOError):
pass
def secret_path(name):
secret_path = f'/run/secrets/{name}'
if not os.path.isfile(secret_path):
raise SecretNotFoundError(name)
return secret_path | MIT License |
uvjustin/alarmdotcom | custom_components/alarmdotcom/alarm_control_panel.py | AlarmDotCom._validate_code | python | def _validate_code(self, code):
check = self._code is None or code == self._code
if not check:
_LOGGER.warning("Wrong code entered")
return check | Validate given code. | https://github.com/uvjustin/alarmdotcom/blob/8b7288bfd1c21a5687cd2359753f0d2efceca726/custom_components/alarmdotcom/alarm_control_panel.py#L215-L220 | import logging
import re
from pyalarmdotcomajax import Alarmdotcom, AlarmdotcomADT, AlarmdotcomProtection1
import voluptuous as vol
import homeassistant.components.alarm_control_panel as alarm
try:
from homeassistant.components.alarm_control_panel import AlarmControlPanelEntity
except ImportError:
from homeassi... | MIT License |
synbiodex/pysbol2 | sbol2/componentdefinition.py | ComponentDefinition.linearize | python | def linearize(self, components=None):
raise NotImplementedError("Not yet implemented") | TODO document
:param components: An optional list of component definitions or URIs.
If None, an empty list of ComponentDefinitions is assumed.
:return: None | https://github.com/synbiodex/pysbol2/blob/127b92d60ecf6f9b6cb8fbf9657bb578bc983090/sbol2/componentdefinition.py#L887-L895 | import os
import posixpath
from typing import Union
from rdflib import URIRef
from .component import Component
from .config import Config, ConfigOptions
from .constants import *
from .toplevel import TopLevel
from .property import OwnedObject, ReferencedObject, URIProperty
from .sbolerror import SBOLError, SBOLErrorCod... | Apache License 2.0 |
flyteorg/flytekit | flytekit/models/literals.py | RetryStrategy.__init__ | python | def __init__(self, retries):
self._retries = retries | :param int retries: Number of retries to attempt on recoverable failures. If retries is 0, then
only one attempt will be made. | https://github.com/flyteorg/flytekit/blob/6c032035563ae645b0b93558b3fe3362080057ea/flytekit/models/literals.py#L15-L20 | from datetime import datetime as _datetime
import pytz as _pytz
from flyteidl.core import literals_pb2 as _literals_pb2
from google.protobuf.struct_pb2 import Struct
from flytekit.common.exceptions import user as _user_exceptions
from flytekit.models import common as _common
from flytekit.models.core import types as _c... | Apache License 2.0 |
practical-data-science/ecommercetools | ecommercetools/utilities/metrics.py | average_tickets_to_resolve | python | def average_tickets_to_resolve(total_tickets, total_resolutions):
return total_tickets / total_resolutions | Returns the average number of tickets required to resolve an issue.
Args:
total_tickets (int): Total chats, emails, or tickets in the period.
total_resolutions (int): Total chats, emails, or tickets resolved in the period.
Returns:
Average number of tickets it takes to resolve an issue... | https://github.com/practical-data-science/ecommercetools/blob/b00175d7775dc4f6ad57b52702a0b2acce3425fc/ecommercetools/utilities/metrics.py#L732-L743 | import math
from datetime import datetime
def tax(gross_revenue, tax_rate=0.2):
return gross_revenue * tax_rate
def net_revenue(gross_revenue, tax_rate=0.2):
total_tax = tax(gross_revenue, tax_rate)
return gross_revenue - total_tax
def aov(total_revenue, total_orders):
return total_revenue / total_order... | MIT License |
rapid7/vm-console-client-python | rapid7vmconsole/models/review.py | Review.to_dict | python | def to_dict(self):
result = {}
for attr, _ in six.iteritems(self.swagger_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map(
lambda x: x.to_dict() if hasattr(x, "to_dict") else x,
value
... | Returns the model properties as a dict | https://github.com/rapid7/vm-console-client-python/blob/55e1f573967bce27cc9a2d10c12a949b1142c2b3/rapid7vmconsole/models/review.py#L181-L206 | import pprint
import re
import six
class Review(object):
"""
Attributes:
swagger_types (dict): The key is attribute name
and the value is attribute type.
attribute_map (dict): The key is attribute name
and the value is json key in definition.... | MIT License |
googlecloudplatform/tensorflow-recommendation-wals | airflow/plugins/gae_admin_plugin.py | AppEngineAdminHook.get_version_identifiers | python | def get_version_identifiers(self, project_id, service_id):
request = self._gaeadmin.apps().services().versions().list(appsId=project_id,
servicesId=service_id)
versions = []
while request is not None:
versions_doc = request.execute()
... | Get list of versions of a service on App Engine Engine.
Args:
project_id: project id
service_id: service id
Returns:
the list of version identifiers if successful and raises an error otherwise. | https://github.com/googlecloudplatform/tensorflow-recommendation-wals/blob/2116cd21e4cc77b7380cccc9fee6f2ed606119db/airflow/plugins/gae_admin_plugin.py#L121-L140 | from airflow.contrib.hooks.gcp_api_base_hook import GoogleCloudBaseHook
from airflow.exceptions import AirflowException
from airflow.models import BaseOperator
from airflow.plugins_manager import AirflowPlugin
from airflow.utils.decorators import apply_defaults
from apiclient.discovery import build
from datetime import... | Apache License 2.0 |
ebagdasa/federated_adaptation | utils/text_load.py | Corpus.tokenize_train | python | def tokenize_train(self, path):
files = os.listdir(path)
per_participant_ids = list()
per_participant_ids_test = list()
per_participant_different_words = list()
per_participant_voc_size = list()
for file in tqdm(files[:self.authors_no]):
if 'checkpoint' in fil... | We return a list of ids per each participant.
:param path:
:return: | https://github.com/ebagdasa/federated_adaptation/blob/0c0ae97445fddc635c427ae100854bc70a00a11c/utils/text_load.py#L49-L82 | import os
import torch
import json
import re
from tqdm import tqdm
import random
filter_symbols = re.compile('[a-zA-Z]*')
class Dictionary(object):
def __init__(self):
self.word2idx = {}
self.idx2word = []
def add_word(self, word):
raise ValueError("Please don't call this method, so we w... | MIT License |
laszukdawid/pyemd | PyEMD/EEMD.py | EEMD.eemd | python | def eemd(self, S: np.ndarray, T: Optional[np.ndarray] = None, max_imf: int = -1) -> np.ndarray:
if T is None:
T = get_timeline(len(S), S.dtype)
scale = self.noise_width*np.abs(np.max(S)-np.min(S))
self._S = S
self._T = T
self._N = len(S)
self._scale = scale
... | Performs EEMD on provided signal.
For a large number of iterations defined by `trials` attr
the method performs :py:meth:`emd` on a signal with added white noise.
Parameters
----------
S : numpy array,
Input signal on which EEMD is performed.
T : numpy array... | https://github.com/laszukdawid/pyemd/blob/3d8ec292cd2ba8cba327d3e0ad576366a8ead6ff/PyEMD/EEMD.py#L141-L212 | from __future__ import print_function
import logging
import numpy as np
from collections import defaultdict
from multiprocessing import Pool
from typing import Dict, List, Optional, Sequence, Tuple, Union
from PyEMD.utils import get_timeline
class EEMD:
logger = logging.getLogger(__name__)
noise_kinds_all = ["n... | Apache License 2.0 |
biolink/kgx | kgx/utils/kgx_utils.py | expand | python | def expand(
curie: str, prefix_maps: Optional[List[dict]] = None, fallback: bool = True
) -> str:
default_curie_maps = [
get_jsonld_context("monarch_context"),
get_jsonld_context("obo_context"),
]
if prefix_maps:
uri = expand_uri(curie, prefix_maps)
if uri == curie and fa... | Expand a given CURIE to an URI, based on mappings from `prefix_map`.
This method will return the CURIE as the IRI if there is no mapping found.
Parameters
----------
curie: str
A CURIE
prefix_maps: Optional[List[dict]]
A list of prefix maps to use for mapping
fallback: bool
... | https://github.com/biolink/kgx/blob/247d113d5b593f078afce1951c63eee2a8cc1248/kgx/utils/kgx_utils.py#L264-L299 | import importlib
import re
import time
import uuid
from enum import Enum
from typing import List, Dict, Set, Optional, Any, Union
import stringcase
from linkml_runtime.linkml_model.meta import (
TypeDefinitionName,
ElementName,
SlotDefinition,
ClassDefinition,
TypeDefinition,
Element,
)
from bmt... | BSD 3-Clause New or Revised License |
nok/sklearn-porter | sklearn_porter/utils/Shell.py | Shell._run | python | def _run(method, cmd, cwd=None, shell=True, universal_newlines=True,
stderr=STDOUT):
if not cmd:
error_msg = 'Passed empty text or list'
raise AttributeError(error_msg)
if isinstance(cmd, six.string_types):
cmd = str(cmd)
if shell:
if ... | Internal wrapper for `call` amd `check_output` | https://github.com/nok/sklearn-porter/blob/8658c6567e28c570d96ab2e858c510f84b1d94dc/sklearn_porter/utils/Shell.py#L13-L31 | import six
from subprocess import call
from subprocess import check_output
from subprocess import STDOUT
class Shell(object):
@staticmethod | MIT License |
chuckus/chromewhip | chromewhip/protocol/emulation.py | Emulation.setDefaultBackgroundColorOverride | python | def setDefaultBackgroundColorOverride(cls,
color: Optional['DOM.RGBA'] = None,
):
return (
cls.build_send_payload("setDefaultBackgroundColorOverride", {
"color": color,
}),
Non... | Sets or clears an override of the default background color of the frame. This override is used
if the content does not specify one.
:param color: RGBA of the default background color. If not specified, any existing override will be
cleared.
:type color: DOM.RGBA | https://github.com/chuckus/chromewhip/blob/7249f64f96df3c6ca0859a3da06ce7ddcebbfded/chromewhip/protocol/emulation.py#L112-L126 | import logging
from typing import Any, Optional, Union
from chromewhip.helpers import PayloadMixin, BaseEvent, ChromeTypeBase
log = logging.getLogger(__name__)
from chromewhip.protocol import dom as DOM
from chromewhip.protocol import page as Page
from chromewhip.protocol import runtime as Runtime
class ScreenOrientati... | MIT License |
facelessuser/subclrschm | subclrschm/lib/gui/custom_statusbar.py | CustomStatusBar.__init__ | python | def __init__(self, parent, name, fields=None):
field_array = [-1] if not fields else fields[:]
super(CustomStatusBar, self).__init__(
parent,
id=wx.ID_ANY,
style=wx.STB_DEFAULT_STYLE,
name=name
)
self.sb_setup(field_array) | Init the CustomStatusBar object. | https://github.com/facelessuser/subclrschm/blob/52cf5bc39bac6e3dd6d44061cd0c005cdc9a41d1/subclrschm/lib/gui/custom_statusbar.py#L259-L269 | from __future__ import unicode_literals
from collections import OrderedDict
import wx
import wx.lib.agw.supertooltip
from .. import util
if wx.VERSION > (2, 9, 4):
def monkey_patch():
import inspect
import re
target_line = re.compile(r'([ ]{8})(maxWidth = max\(bmpWidth\+\(textWidth\+self._... | MIT License |
nlesc/yeap16-ai-3d-printing | deepy3d/util.py | get_closest_factors | python | def get_closest_factors(number):
a = int(np.sqrt(number))
while number % a != 0:
a -= 1
b = number/a
if a == 1 or b == 1:
a, b = get_closest_factors(number + 1)
return a, b | Find the 2 factors of a number that are closest together. | https://github.com/nlesc/yeap16-ai-3d-printing/blob/4f15c1851d819290dc7a922c9470a76ff458945c/deepy3d/util.py#L40-L53 | import numpy as np
def block_index(num_blocks, len_list):
if num_blocks < 1:
ValueError('Number of blocks must be larger or equal to 1')
if len_list < num_blocks:
ValueError('Length of list must be larger than number of blocks.')
lin_list = np.linspace(0, num_blocks, len_list, endpoint=False... | Apache License 2.0 |
tonyfischetti/sake | sakelib/build.py | write_shas_to_shastore | python | def write_shas_to_shastore(sha_dict):
if sys.version_info[0] < 3:
fn_open = open
else:
fn_open = io.open
with fn_open(".shastore", "w") as fh:
fh.write("---\n")
fh.write('sake version: {}\n'.format(constants.VERSION))
if sha_dict:
fh.write(yaml.dump(sha_di... | Writes a sha1 dictionary stored in memory to
the .shastore file | https://github.com/tonyfischetti/sake/blob/818f1b1ad97a0d7bcf2c9e0082affb2865b25f26/sakelib/build.py#L116-L130 | from __future__ import unicode_literals
from __future__ import print_function
import glob
import hashlib
import io
import locale
from multiprocessing import Pool
import networkx as nx
import os.path
import shlex
from subprocess import Popen, PIPE
import sys
import yaml
from . import acts
from . import constants
ERROR_F... | MIT License |
flow-dev/robustvideomatting | inference.py | auto_downsample_ratio | python | def auto_downsample_ratio(h, w):
return min(512 / max(h, w), 1) | Automatically find a downsample ratio so that the largest side of the resolution be 512px. | https://github.com/flow-dev/robustvideomatting/blob/b8848d58188fcc1e56edc7c8636aabdae1971284/inference.py#L154-L158 | import torch
import os
from torch.utils.data import DataLoader
from torchvision import transforms
from typing import Optional, Tuple
from tqdm.auto import tqdm
from inference_utils import VideoReader, VideoWriter, ImageSequenceReader, ImageSequenceWriter
def convert_video(model,
input_source: str,
... | Apache License 2.0 |
avast/retdec-regression-tests-framework | tests/parsers/c_parser/stmts/statement_tests.py | StatementTests.get_return_stmt | python | def get_return_stmt(self, code):
func = self.insert_into_function_body(code)
return func.return_stmts[0] | Returns the first return stmt in the given code. | https://github.com/avast/retdec-regression-tests-framework/blob/a8d024475bf76cd6acdee3c9df3a3d38a2ec63df/tests/parsers/c_parser/stmts/statement_tests.py#L52-L55 | from unittest import mock
from regression_tests.parsers.c_parser.stmts.break_stmt import BreakStmt
from regression_tests.parsers.c_parser.stmts.continue_stmt import ContinueStmt
from regression_tests.parsers.c_parser.stmts.do_while_loop import DoWhileLoop
from regression_tests.parsers.c_parser.stmts.empty_stmt import E... | MIT License |
openshift/kuryr-kubernetes | kuryr_kubernetes/controller/drivers/base.py | PodSubnetsDriver.get_subnets | python | def get_subnets(self, pod, project_id):
raise NotImplementedError() | Get subnets for Pod.
:param pod: dict containing Kubernetes Pod object
:param project_id: OpenStack project ID
:return: dict containing the mapping 'subnet_id' -> 'network' for all
the subnets we want to create ports on, where 'network' is an
`os_vif.network.Ne... | https://github.com/openshift/kuryr-kubernetes/blob/7b2e7f83b91fa711d1a506c451be8f1143cdcd86/kuryr_kubernetes/controller/drivers/base.py#L148-L158 | import abc
from kuryr.lib._i18n import _
from stevedore import driver as stv_driver
from kuryr_kubernetes import config
_DRIVER_NAMESPACE_BASE = 'kuryr_kubernetes.controller.drivers'
_DRIVER_MANAGERS = {}
_MULTI_VIF_DRIVERS = []
class DriverBase(object):
@classmethod
def get_instance(cls, specific_driver=None, ... | Apache License 2.0 |
kcyu2014/eval-nas | search_policies/cnn/random_policy/nasbench_weight_sharing_policy.py | NasBenchWeightSharingPolicy.run | python | def run(self):
train_queue, valid_queue, test_queue, criterion = self.initialize_run()
args = self.args
model, optimizer, scheduler = self.initialize_model()
fitness_dict = {}
self.optimizer = optimizer
self.scheduler = scheduler
logging.info(">> Begin the search ... | Procedure of training. This run describes the entire training procedure.
:return: | https://github.com/kcyu2014/eval-nas/blob/385376a3ef96336b54ee7e696af1d02b97aa5c32/search_policies/cnn/random_policy/nasbench_weight_sharing_policy.py#L141-L177 | import os
import gc
import logging
import operator
import IPython
import shutil
import numpy as np
import torch
from functools import partial
from collections import namedtuple, OrderedDict, deque
import utils
from search_policies.cnn.cnn_general_search_policies import CNNSearchPolicy
from search_policies.cnn.enas_poli... | MIT License |
virgesmith/ukcensusapi | ukcensusapi/Nomisweb.py | _get_api_key | python | def _get_api_key(cache_dir):
filename = cache_dir / "NOMIS_API_KEY"
if os.path.isfile(str(filename)):
with open(str(filename), "r") as file:
content = file.readlines()
return None if len(content) == 0 else content[0].replace("\n","")
return os.environ.get("NOMIS_API_KEY") | Look for key in file NOMIS_API_KEY in cache dir, falling back to env var | https://github.com/virgesmith/ukcensusapi/blob/b78a753375665d1aa05c0d30813d7e533834d015/ukcensusapi/Nomisweb.py#L21-L31 | import os
import json
import hashlib
import warnings
from pathlib import Path
from collections import OrderedDict
from urllib import request
from urllib.error import HTTPError
from urllib.error import URLError
from urllib.parse import urlencode
from socket import timeout
import pandas as pd
import ukcensusapi.utils as ... | MIT License |
clericpy/torequests | torequests/dummy.py | Loop.wait_all_tasks_done | python | def wait_all_tasks_done(self,
timeout=NotSet,
delay: float = 0.5,
interval: float = 0.1):
timeout = self._timeout if timeout is NotSet else timeout
timeout = timeout or float("inf")
start_time = time_time()
... | Block, only be used while loop running in a single non-main thread. Not SMART! | https://github.com/clericpy/torequests/blob/e57ce331aa850db45c198dc90b9d01e437384b61/torequests/dummy.py#L302-L316 | from asyncio import (Future, Queue, Task, TimeoutError, as_completed, gather,
get_event_loop, iscoroutine, new_event_loop, sleep, wait,
wait_for)
from asyncio.futures import _chain_future
from concurrent.futures import ALL_COMPLETED
from functools import wraps
from time import ... | MIT License |
ying-wen/malib_deprecated | malib/utils/tf_utils.py | soft_variables_update | python | def soft_variables_update(
source_variables, target_variables, tau=1.0, sort_variables_by_name=False, name=None
):
if tau < 0 or tau > 1:
raise ValueError("Input `tau` should be in [0, 1].")
updates = []
op_name = "soft_variables_update"
if name is not None:
op_name = "{}_{}".format(... | Performs a soft/hard update of variables from the source to the target.
For each variable v_t in target variables and its corresponding variable v_s
in source variables, a soft update is:
v_t = (1 - tau) * v_t + tau * v_s
When tau is 1.0 (the default), then it does a hard update:
v_t = v_s
Args:... | https://github.com/ying-wen/malib_deprecated/blob/875338b81c4d87064ad31201f461ef742db05f25/malib/utils/tf_utils.py#L7-L48 | import tensorflow as tf
EPS = 1e-6 | MIT License |
dedsecinside/awesome-scripts | Machine Learning & AI/Linear_Regression_with_Gradient_Descent.py | r2_alpha | python | def r2_alpha(r2, alphas):
plt.plot(alphas, r2)
plt.title('R^2 vs. Learning Rate')
print(max(r2))
print(np.linspace(0.001,1,10)[r2.index(max(r2))]) | Plot r2 alpha
Args:
r2: (todo): write your description
alphas: (array): write your description | https://github.com/dedsecinside/awesome-scripts/blob/856835e5ff5f8a6af2d74bb25800c620feb712e3/Machine Learning & AI/Linear_Regression_with_Gradient_Descent.py#L150-L165 | import random
import matplotlib.pyplot as plt
import numpy as np
def sse(n,a0,a1,x,y):
s=0
mean=np.mean(y)
for i in range(n):
s+=(a0+a1*x[i]-mean)**2
return s/(2*n)
def cost(n,a0,a1,x,y,ch,p=2):
s=0;
if ch=='sum-of-squares':
for i in range(n):
s+=(a0+a1*x[i]-y[i])**2
... | MIT License |
ing-bank/skorecard | skorecard/features_bucket_mapping.py | merge_features_bucket_mapping | python | def merge_features_bucket_mapping(a: FeaturesBucketMapping, b: FeaturesBucketMapping) -> FeaturesBucketMapping:
assert isinstance(a, FeaturesBucketMapping)
assert isinstance(b, FeaturesBucketMapping)
cols_in_both = [col for col in a.columns if col in b.columns]
cols_in_a = [col for col in a.columns if c... | Merge two sets of sequentual FeatureBucketMapping.
If there are unique features, we'll add them as-in. | https://github.com/ing-bank/skorecard/blob/8ab8d38db9385aab049a7a8bef4d5f235d3f46ce/skorecard/features_bucket_mapping.py#L161-L186 | import yaml
import dataclasses
from skorecard.bucket_mapping import BucketMapping, merge_bucket_mapping
class FeaturesBucketMapping:
def __init__(self, maps=[]):
self.maps = {}
if isinstance(maps, list):
for bucketmap in maps:
self.append(bucketmap)
if isinstance(... | MIT License |
awslabs/aws-data-api | vendor/tornado/template.py | BaseLoader.__init__ | python | def __init__(self, autoescape=_DEFAULT_AUTOESCAPE, namespace=None,
whitespace=None):
self.autoescape = autoescape
self.namespace = namespace or {}
self.whitespace = whitespace
self.templates = {}
self.lock = threading.RLock() | Construct a template loader.
:arg str autoescape: The name of a function in the template
namespace, such as "xhtml_escape", or ``None`` to disable
autoescaping by default.
:arg dict namespace: A dictionary to be added to the default template
namespace, or ``None``.
... | https://github.com/awslabs/aws-data-api/blob/81f6ad1fd89935fcec600ced2b404f37d87254fe/vendor/tornado/template.py#L385-L411 | from __future__ import absolute_import, division, print_function
import datetime
import linecache
import os.path
import posixpath
import re
import threading
from tornado import escape
from tornado.log import app_log
from tornado.util import ObjectDict, exec_in, unicode_type, PY3
if PY3:
from io import StringIO
else... | Apache License 2.0 |
purestorage-openconnect/py-pure-client | pypureclient/flasharray/FA_2_1/models/volume_response.py | VolumeResponse.__init__ | python | def __init__(
self,
items=None,
):
if items is not None:
self.items = items | Keyword args:
items (list[Volume]): Returns a list of all items after filtering. The values are displayed for each name where meaningful. If `total_only=true`, the `items` list will be empty. | https://github.com/purestorage-openconnect/py-pure-client/blob/2d9fdef0b73321cea9613e7d1eb881b42845099b/pypureclient/flasharray/FA_2_1/models/volume_response.py#L43-L52 | import pprint
import re
import six
import typing
from ....properties import Property
if typing.TYPE_CHECKING:
from pypureclient.flasharray.FA_2_1 import models
class VolumeResponse(object):
swagger_types = {
'items': 'list[Volume]'
}
attribute_map = {
'items': 'items'
}
required_... | BSD 2-Clause Simplified License |
docusign/docusign-python-client | docusign_esign/models/login_account.py | LoginAccount.is_default | python | def is_default(self):
return self._is_default | Gets the is_default of this LoginAccount. # noqa: E501
This value is true if this is the default account for the user, otherwise false is returned. # noqa: E501
:return: The is_default of this LoginAccount. # noqa: E501
:rtype: str | https://github.com/docusign/docusign-python-client/blob/c6aeafff0d046fa6c10a398be83ba9e24b05d4ea/docusign_esign/models/login_account.py#L187-L195 | import pprint
import re
import six
from docusign_esign.client.configuration import Configuration
class LoginAccount(object):
"""
Attributes:
swagger_types (dict): The key is attribute name
and the value is attribute type.
attribute_map (dict): The key is attribute name
... | MIT License |
rikonor/vanguard-api | seleniumapis/browser/browser.py | Browser.find_element_by_any | python | def find_element_by_any(self, search_term):
return self.find_element_by_id(search_term) or self.find_element_by_name(search_term) | Find an element by a search term
Try ID, then fallback to Name | https://github.com/rikonor/vanguard-api/blob/5462b2327cacad68bedb945dc323d534ebbdfeee/seleniumapis/browser/browser.py#L37-L43 | from selenium import webdriver
from selenium.webdriver.common.desired_capabilities import DesiredCapabilities
from selenium.common.exceptions import *
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
clas... | MIT License |
tamasgal/km3pipe | km3pipe/io/daq.py | DAQPump.seek_to_frame | python | def seek_to_frame(self, index):
pointer_position = self.frame_positions[index]
self.blob_file.seek(pointer_position, 0) | Move file pointer to the frame with given index. | https://github.com/tamasgal/km3pipe/blob/c10fa39f72f3a8e384025712344378012fae5115/km3pipe/io/daq.py#L231-L234 | from collections import namedtuple
from io import BytesIO
import json
import math
import struct
from struct import unpack
import time
import pprint
from urllib.request import urlopen, URLError
import numpy as np
from thepipe import Module, Blob
from km3pipe.dataclasses import Table
from km3pipe.sys import ignored
from ... | MIT License |
vitrioil/speech-separation | src/loader/data.py | Signal.augment_audio | python | def augment_audio(self, augmenter: Callable, *args, **kwargs):
self.audio = augmenter(self.audio, *args, **kwargs) | Change the audio via the augmenter method. | https://github.com/vitrioil/speech-separation/blob/65a532d36cf0725d622f18ef058cf5a537c01070/src/loader/data.py#L65-L69 | import os
import cv2
import librosa
import numpy as np
from pathlib import Path
from typing import Callable, Tuple, List
EMBED_DIR = [Path("../data/train/embed")]
SPEC_DIR = [Path("../data/train/spec")]
def get_frames(video):
frame_count = int(video.get(cv2.CAP_PROP_FRAME_COUNT))
frame_width = int(video.get(cv2... | MIT License |
jakecover/distest | distest/TestInterface/_reply.py | assert_reply_contains | python | async def assert_reply_contains(self, contents, substring):
response = await self.wait_for_reply(contents)
return await self.assert_message_contains(response, substring) | Send a message and wait for a response. If the response does not contain
the given substring, fail the test.
:param str contents: The content of the trigger message. (A command)
:param str substring: The string to test against.
:returns: The reply.
:rtype: discord.Message
:raises: ResponseDidNo... | https://github.com/jakecover/distest/blob/8810c884546a37a67881ddf3fbeed03b6eccebe5/distest/TestInterface/_reply.py#L22-L33 | from asyncio import sleep
from inspect import signature, _ParameterKind
from typing import Dict
from discord import Embed, Message
async def assert_reply_equals(self, contents, matches):
response = await self.wait_for_reply(contents)
return await self.assert_message_equals(response, matches) | MIT License |
thingsboard/python_tb_rest_client | tb_rest_client/models/models_pe/report_config.py | ReportConfig.to_dict | python | def to_dict(self):
result = {}
for attr, _ in six.iteritems(self.swagger_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map(
lambda x: x.to_dict() if hasattr(x, "to_dict") else x,
value
... | Returns the model properties as a dict | https://github.com/thingsboard/python_tb_rest_client/blob/87c6a3703974fc8a86e4c72c444168ee2b758ecb/tb_rest_client/models/models_pe/report_config.py#L300-L325 | import pprint
import re
import six
class ReportConfig(object):
swagger_types = {
'base_url': 'str',
'dashboard_id': 'str',
'name_pattern': 'str',
'state': 'str',
'timewindow': 'str',
'timezone': 'str',
'type': 'str',
'use_current_user_credentials': '... | Apache License 2.0 |
xilinx/pyxir | python/pyxir/contrib/dpuv1/dpuv1_op_support.py | mean_op_support | python | def mean_op_support(X, bXs, tXs):
axes = X.attrs['axes']
keepdims = X.attrs['keepdims']
return len(axes) == 2 and keepdims | Check whether we can execute the provided Mean operator
on the dpuv1 target | https://github.com/xilinx/pyxir/blob/bef661d6d77adcdbd2cf4163f2cf3a1d31d40406/python/pyxir/contrib/dpuv1/dpuv1_op_support.py#L212-L220 | import math
import pyxir
import logging
logger = logging.getLogger('pyxir')
@pyxir.register_op_support_check('dpuv1', 'BatchNorm')
def batchnorm_op_support(X, bXs, tXs):
axis = X.attrs['axis']
channels = X.shapes[axis]
return channels >= 1 and channels <= 4096
@pyxir.register_op_support_check('dpuv1', 'Bias... | Apache License 2.0 |
kriaga/health-checker | HealthChecker/venv/Lib/site-packages/nltk/data.py | normalize_resource_name | python | def normalize_resource_name(resource_name, allow_relative=True, relative_path=None):
is_dir = bool(re.search(r'[\\/.]$', resource_name)) or resource_name.endswith(os.path.sep)
if sys.platform.startswith('win'):
resource_name = resource_name.lstrip('/')
else:
resource_name = re.sub(r'^/+', '/... | :type resource_name: str or unicode
:param resource_name: The name of the resource to search for.
Resource names are posix-style relative path names, such as
``corpora/brown``. Directory names will automatically
be converted to a platform-appropriate path separator.
Directory traili... | https://github.com/kriaga/health-checker/blob/3d9ce933f131bcbb897103b0f509cc45393cae4a/HealthChecker/venv/Lib/site-packages/nltk/data.py#L210-L254 | from __future__ import print_function, unicode_literals
from __future__ import division
from abc import ABCMeta, abstractmethod
from six import add_metaclass
import functools
import textwrap
import io
import os
import re
import sys
import zipfile
import codecs
from gzip import GzipFile, READ as GZ_READ, WRITE as GZ_WRI... | MIT License |
bigmlcom/bigmler | bigmler/resourcesapi/batch_anomaly_scores.py | create_batch_anomaly_score | python | def create_batch_anomaly_score(anomaly, test_dataset,
batch_anomaly_score_args, args,
api=None, session_file=None,
path=None, log=None):
if api is None:
api = bigml.api.BigML()
message = dated("Creating batch an... | Creates remote batch anomaly score | https://github.com/bigmlcom/bigmler/blob/91973ca1e752954302bf26bb22aa6874dc34ce69/bigmler/resourcesapi/batch_anomaly_scores.py#L74-L106 | import sys
import bigml.api
from bigmler.utils import (dated, get_url, log_message, check_resource,
check_resource_error, log_created_resources)
from bigmler.reports import report
from bigmler.resourcesapi.common import set_basic_batch_args, map_fields, update_json_args
from bigmler.resour... | Apache License 2.0 |
loudnate/openaps-predict | openapscontrib/predict/predict.py | ceil_datetime_at_minute_interval | python | def ceil_datetime_at_minute_interval(timestamp, minute):
nsecs = timestamp.minute * 60 + timestamp.second + timestamp.microsecond * 1e-6
seconds = minute * 60
delta = (nsecs // seconds) * seconds + seconds - nsecs
if delta < seconds:
return timestamp + datetime.timedelta(seconds=delta)
else:... | From http://stackoverflow.com/questions/13071384/python-ceil-a-datetime-to-next-quarter-of-an-hour
:param timestamp:
:type timestamp: datetime.datetime
:param minute:
:type minute: int
:return:
:rtype: datetime.datetime | https://github.com/loudnate/openaps-predict/blob/a2da82148318d86b0935a1fca596477d84dd8247/openapscontrib/predict/predict.py#L50-L71 | from collections import defaultdict
import datetime
from dateutil.parser import parse
from functools32 import lru_cache
import math
from numpy import arange
from scipy.stats import linregress
from models import Unit
class Schedule(object):
def __init__(self, entries):
self.entries = entries
@lru_cache()... | MIT License |
edx-unsupported/edx-load-tests | loadtests/student_notes/locustfile.py | BaseNotesTask._create_many_notes | python | def _create_many_notes(self, num_notes):
for _ in xrange(num_notes):
self._create_note() | Create many notes within the course for the current user. | https://github.com/edx-unsupported/edx-load-tests/blob/1a6dc891d2fb72575f354521988a531489f30032/loadtests/student_notes/locustfile.py#L202-L207 | import os
import sys
sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
from contextlib import contextmanager
from copy import copy
import json
from locust import HttpLocust, task, TaskSet
import logging
import random
from helpers import settings
settings.init(__name__, required_data=[
'co... | Apache License 2.0 |
bobotig/thermalprinter | thermalprinter/thermalprinter.py | ThermalPrinter.upside_down | python | def upside_down(self, state=False):
state = bool(state)
if state is not self._upside_down:
self._upside_down = state
self.send_command(Command.ESC, 123, int(state)) | Turns on/off upside-down printing mode. | https://github.com/bobotig/thermalprinter/blob/4cf697049d6c4fbad31ba8ea6842e0a4bc1b35ad/thermalprinter/thermalprinter.py#L624-L630 | from atexit import register
from time import sleep
from serial import Serial
from .constants import (BarCodePosition, CharSet, Chinese, CodePage,
CodePageConverted, Command)
from .exceptions import (ThermalPrinterValueError,
ThermalPrinterCommunicationError)
from .valida... | MIT License |
flask-admin/flask-admin | flask_admin/contrib/appengine/form.py | AdminModelConverter.convert_GeoPtProperty | python | def convert_GeoPtProperty(self, model, prop, kwargs):
return GeoPtPropertyField(**kwargs) | Returns a form field for a ``ndb.GeoPtProperty``. | https://github.com/flask-admin/flask-admin/blob/e39f786374ce0e60db93f583efacb4672de0025c/flask_admin/contrib/appengine/form.py#L8-L10 | from wtforms_appengine.ndb import ModelConverter
from .fields import GeoPtPropertyField
from flask_admin.model.form import converts
class AdminModelConverter(ModelConverter):
@converts('GeoPt') | BSD 3-Clause New or Revised License |
chrklemm/sesmg | program_files/create_objects.py | Sinks.create_sink | python | def create_sink(self, de: dict, timeseries_args: dict):
self.nodes_sinks.append(
solph.Sink(label=de['label'],
inputs={
self.busd[de['input']]:
solph.Flow(**timeseries_args)})) | Creates an oemof sink with fixed or unfixed timeseries.
:param de: dictionary containing all information for the
creation of an oemof sink. At least the
following key-value-pairs have to be included:
- 'label'
... | https://github.com/chrklemm/sesmg/blob/382ffd600b98d3cc6df53abed0cb3526187cb1cf/program_files/create_objects.py#L693-L718 | from oemof import solph
import logging
import os
import pandas as pd
from feedinlib import *
import demandlib.bdew as bdew
import datetime
import numpy
def buses(nodes_data: dict, nodes: list) -> dict:
busd = {}
for i, b in nodes_data['buses'].iterrows():
if b['active']:
bus = solph.Bus(labe... | MIT License |
facebookresearch/nevergrad | nevergrad/parametrization/core.py | as_parameter | python | def as_parameter(param: tp.Any) -> Parameter:
if isinstance(param, Parameter):
return param
else:
return Constant(param) | Returns a Parameter from anything:
either the input if it is already a parameter, or a Constant if not
This is convenient for iterating over Parameter and other objects alike | https://github.com/facebookresearch/nevergrad/blob/1981997603e361b1fd5b5e2aeb8173c4eae6aef0/nevergrad/parametrization/core.py#L469-L477 | import uuid
import warnings
import numpy as np
import nevergrad.common.typing as tp
from nevergrad.common import errors
from . import utils
from ._layering import ValueProperty as ValueProperty
from ._layering import Layered as Layered
from ._layering import Level as Level
P = tp.TypeVar("P", bound="Parameter")
class P... | MIT License |
cainmagi/mdnt | data/deprecated/h5py.py | H5SupSaver.dump | python | def dump(self, keyword, data):
if self.f is None:
raise OSError('Should not dump data before opening a file.')
self.f.create_dataset(keyword, data=data, **self.__kwargs)
if self.logver > 0:
print('Dump {0} into the file. The data shape is {1}.'.format(keyword, data.shape)... | Dump the dataset with a keyword into the file.
Arguments:
keyword: the keyword of the dumped dataset.
data: dataset, should be a numpy array. | https://github.com/cainmagi/mdnt/blob/4affd8a83698ce6786c04dddacdcf7415f8c5f90/data/deprecated/h5py.py#L73-L84 | import h5py
import numpy as np
import tensorflow as tf
import os
REMOVE_DEPRECATION = False
def depcatedInfo():
try:
raise DeprecationWarning('This library has been deprecated.')
except Exception as e:
if not REMOVE_DEPRECATION:
raise e
class H5SupSaver:
def __init__(self, fileNa... | MIT License |
tektoncd/experimental | sdk/python/tekton_pipeline/models/v1beta1_pipeline_list.py | V1beta1PipelineList.api_version | python | def api_version(self, api_version):
self._api_version = api_version | Sets the api_version of this V1beta1PipelineList.
APIVersion defines the versioned schema of this representation of an object. Servers should convert recognized schemas to the latest internal value, and may reject unrecognized values. More info: https://git.k8s.io/community/contributors/devel/sig-architecture/... | https://github.com/tektoncd/experimental/blob/0ba4e7a2b9d45ed4accaecbb34dac006d665796a/sdk/python/tekton_pipeline/models/v1beta1_pipeline_list.py#L95-L104 | import pprint
import re
import six
from tekton_pipeline.configuration import Configuration
class V1beta1PipelineList(object):
"""
Attributes:
openapi_types (dict): The key is attribute name
and the value is attribute type.
attribute_map (dict): The key is attribute name... | Apache License 2.0 |
qkaiser/cottontail | cottontail/rabbitmq_management.py | RabbitMQManagementClient.get_request | python | def get_request(self, path):
response = requests.get(
"{}://{}:{}/api/{}".format(self._scheme, self._host, self._port, path),
auth=(self._username, self._password),
verify=False,
timeout=5
)
if response.status_code == 200:
return respon... | Wrapper for GET requests to the API.
Args:
path (str): REST path appended to /api
Returns:
HTTP response JSON object.
Raises:
UnauthorizedException | https://github.com/qkaiser/cottontail/blob/b7f5222959cf6229ef33d7369e5e8881e6181727/cottontail/rabbitmq_management.py#L60-L87 | try:
from urllib.parse import quote
except ImportError:
from urllib import quote
import requests
from requests.packages.urllib3.exceptions import InsecureRequestWarning
requests.packages.urllib3.disable_warnings(InsecureRequestWarning)
class UnauthorizedAccessException(Exception):
pass
class RabbitMQManagem... | BSD 3-Clause New or Revised License |
nsls-ii/pyxrf | pyxrf/core/tests/test_quant_analysis.py | _create_file_with_ref_standards | python | def _create_file_with_ref_standards(*, wd):
sd = _standard_data_sample[0]
file_path = os.path.join(wd, ".pyxrf", "quantitative_standards.yaml")
standard_data = []
for n in range(2):
sd_copy = copy.deepcopy(sd)
sd_copy["serial"] += f"{n}"
sd_copy["name"] = f"Test reference standar... | r"""
Create a file with user-defined standards based on ``_standard_data_sample[0]``.
The file contains the descriptions of 2 standards with identical sets of elements/compounds
with slightly different densities.
The created file is placed at the standard default location ``<wd>/.pyxrf/quantiative_stan... | https://github.com/nsls-ii/pyxrf/blob/0aa4e175f541edfaa8f71daf54b54a07e4ab2b04/pyxrf/core/tests/test_quant_analysis.py#L727-L767 | import os
import pytest
import jsonschema
import copy
import numpy as np
import numpy.testing as npt
import time as ttime
import re
from pyxrf.core.utils import convert_time_from_nexus_string
from pyxrf.core.xrf_utils import validate_element_str, generate_eline_list, split_compound_mass
from pyxrf.core.quant_analysis i... | BSD 3-Clause New or Revised License |
pyconll/pyconll | pyconll/tree/_treebuilder.py | TreeBuilder._assert_initialization_status | python | def _assert_initialization_status(self) -> None:
if self.root is None:
raise ValueError(
'The TreeBuilder has not created a root for the Tree yet') | Asserts the initialization invariant on the root of this builder.
Raises:
ValueError: If the TreeBuilder's root has not been initialized. | https://github.com/pyconll/pyconll/blob/a69b1bfb884aab7b449e19a7cc8850dcf7e985c0/pyconll/tree/_treebuilder.py#L203-L212 | from typing import Any, Generic, TypeVar
from pyconll.tree.tree import Tree
T = TypeVar('T')
class TreeBuilder(Generic[T]):
def __init__(self) -> None:
self.root: Any = None
self.current: Any = None
self.constructed: bool = False
def create_root(self, data: T) -> None:
self.root ... | MIT License |
merll/docker-map | dockermap/map/client.py | MappingDockerClient.restart | python | def restart(self, container, instances=None, map_name=None, **kwargs):
return self.run_actions('restart', container, instances=instances, map_name=map_name, **kwargs) | Restarts instances for a container configuration.
:param container: Container name.
:type container: unicode | str
:param instances: Instance names to stop. If not specified, will restart all instances as specified in the
configuration (or just one default instance).
:type inst... | https://github.com/merll/docker-map/blob/54e325595fc0b6b9d154dacc790a222f957895da/dockermap/map/client.py#L284-L300 | from __future__ import unicode_literals
import logging
import sys
from ..exceptions import PartialResultsError
from .action import simple, script, update
from .config.client import ClientConfiguration
from .config.main import ContainerMap
from .config.utils import get_map_config_ids
from .exceptions import ActionExcept... | MIT License |
pyannote/pyannote-database | pyannote/database/protocol/speaker_recognition.py | SpeakerRecognitionProtocol.train | python | def train(self, yield_name=False):
generator = self.trn_iter()
for name, item in generator:
if yield_name:
yield name, self.preprocess(item)
else:
yield self.preprocess(item) | Iterate over the training set
This will yield dictionaries with the followings keys:
* database: str
unique database identifier
* uri: str
unique recording identifier
* channel: int
index of resource channel to use
* speaker: str
unique speaker identifier
as well as keys coming from the provided preprocessor... | https://github.com/pyannote/pyannote-database/blob/7391b48e70f087dd963776d37257321bed1e313a/pyannote/database/protocol/speaker_recognition.py#L95-L125 | from .protocol import Protocol
class SpeakerRecognitionProtocol(Protocol):
def trn_iter(self):
raise NotImplementedError(
"Custom speaker recognition protocol " 'should implement "trn_iter".'
)
def trn_enroll_iter(self):
raise NotImplementedError(
"Custom speaker ... | MIT License |
chaffelson/whoville | whoville/cloudbreak/models/rds_config_response.py | RDSConfigResponse.cluster_names | python | def cluster_names(self, cluster_names):
self._cluster_names = cluster_names | Sets the cluster_names of this RDSConfigResponse.
list of clusters which use config
:param cluster_names: The cluster_names of this RDSConfigResponse.
:type: list[str] | https://github.com/chaffelson/whoville/blob/f71fda629c9fd50d0a482120165ea5abcc754522/whoville/cloudbreak/models/rds_config_response.py#L284-L293 | from pprint import pformat
from six import iteritems
import re
class RDSConfigResponse(object):
"""
Attributes:
swagger_types (dict): The key is attribute name
and the value is attribute type.
attribute_map (dict): The key is attribute name
and... | Apache License 2.0 |
smartelect/smartelect | civil_registry/tests/factories.py | CitizenFactory._setup_next_sequence | python | def _setup_next_sequence(cls):
return 1 | Set up an initial sequence value for Sequence attributes.
Returns:
int: the first available ID to use for instances of this factory.
Note: If we don't override this, then DjangoModelFactory bases
the initial value on the max PK of the corresponding model,
which in my case i... | https://github.com/smartelect/smartelect/blob/d6d35f2fa8f60e756ad5247f8f0a5f05830e92f8/civil_registry/tests/factories.py#L52-L63 | from datetime import date
import random
import string
import factory
import factory.fuzzy
from civil_registry.models import Citizen, TempCitizen
from libya_elections.constants import MALE
def get_nid(stub):
from register.tests.factories import get_unused_gender_appropriate_national_id
return get_unused_gender_a... | Apache License 2.0 |
http-apis/hydra-python-agent | hydra_agent/tests/test_redis.py | Tests.collection_endpoints | python | def collection_endpoints(self):
print("testing collection endpoints with db=0 ...")
query = ('GRAPH.QUERY','apigraph', "MATCH (p:collection) RETURN p")
redis_db = redis.StrictRedis(host='localhost', port=6379, db=0)
redis_reply = [[[b'p.id', b'p.operations', b'p.type'], [b'vocab:EntryPoi... | Test for testing the data stored in collection endpoints
`redis_reply` is data which will get from redis_db_0 on `query` execution. | https://github.com/http-apis/hydra-python-agent/blob/e2bcd51f3cbf0700cd44e5e392e3c21af2cbd2a3/hydra_agent/tests/test_redis.py#L26-L43 | import unittest
import redis
from unittest.mock import MagicMock
class Tests:
def entry_point(self):
print("testing entrypoint with db=0 ...")
query = ('GRAPH.QUERY','apigraph', "MATCH (p:id) RETURN p")
redis_db = redis.StrictRedis(host='localhost', port=6379, db=0)
redis_reply = [[[... | MIT License |
ollo69/ha_tuya_custom | custom_components/tuya_custom/__init__.py | TuyaDevice.object_id | python | def object_id(self):
return self._tuya.object_id() | Return Tuya device id. | https://github.com/ollo69/ha_tuya_custom/blob/66b8722afc9c771318b8c67865907e5ac0aac602/custom_components/tuya_custom/__init__.py#L380-L382 | import asyncio
from datetime import timedelta
import logging
from .tuyaha.tuyaapi import (
DEFAULTREGION,
TuyaApi,
TuyaAPIException,
TuyaAPIRateLimitException,
TuyaFrequentlyInvokeException,
TuyaNetException,
TuyaServerException,
)
import voluptuous as vol
from homeassistant.config_entries i... | Apache License 2.0 |
erigones/esdc-ce | api/serializers.py | BaseSerializer.get_field_key | python | def get_field_key(self, field_name):
return field_name | Return the key that should be used for a given field. | https://github.com/erigones/esdc-ce/blob/f83a62d0d430e3c8f9aac23d958583b0efce4312/api/serializers.py#L356-L360 | from __future__ import unicode_literals
import copy
import datetime
import inspect
import types
from collections import OrderedDict
from decimal import Decimal
from django.apps import apps
from django.core.paginator import Page
from django.db import models
from django.forms import widgets
from django.utils import six
f... | Apache License 2.0 |
hathornetwork/hathor-core | hathor/stratum/stratum.py | StratumProtocol.create_job_tx | python | def create_job_tx(self, jobid: UUID) -> BaseTransaction:
if self.mine_txs and self.factory.tx_queue:
funds_hash = self.factory.tx_queue[0]
tx = self.factory.mining_tx_pool[funds_hash]
tx.timestamp = self.factory.get_current_timestamp()
tx.parents = self.manager.ge... | Creates a BaseTransaction for the designated miner job.
:return: created BaseTransaction
:rtype: BaseTransaction | https://github.com/hathornetwork/hathor-core/blob/b8bd2428b9fab4f53dfc4d92de230ffae48fbf46/hathor/stratum/stratum.py#L640-L667 | from abc import ABC, abstractmethod
from hashlib import sha256
from itertools import count
from json import JSONDecodeError
from math import log
from multiprocessing import Process, Queue as MQueue
from multiprocessing.sharedctypes import Array, Value
from os import cpu_count
from string import hexdigits
from time impo... | Apache License 2.0 |
jasonmcintosh/rabbitmq-zabbix | scripts/rabbitmq/api.py | RabbitMQAPI.check_aliveness | python | def check_aliveness(self):
return self.call_api('aliveness-test/%2f')['status'] | Check the aliveness status of a given vhost. | https://github.com/jasonmcintosh/rabbitmq-zabbix/blob/8ecadfdd2cab6154eb7ab73ce4e7bb39b21b61c1/scripts/rabbitmq/api.py#L209-L211 | from __future__ import unicode_literals
import io
import json
import optparse
import socket
import urllib2
import subprocess
import os
import logging
class RabbitMQAPI(object):
def __init__(self, user_name='guest', password='guest', host_name='',
port=15672, conf='/etc/zabbix/zabbix_agentd.conf', s... | Apache License 2.0 |
bennylope/django-organizations | src/organizations/utils.py | model_field_attr | python | def model_field_attr(model, model_field, attr):
fields = dict([(field.name, field) for field in model._meta.fields])
return getattr(fields[model_field], attr) | Returns the specified attribute for the specified field on the model class. | https://github.com/bennylope/django-organizations/blob/55808ad7e4b23ef4612c9226cadce46d514c9a79/src/organizations/utils.py#L89-L94 | from itertools import chain
def default_org_model():
from organizations.models import Organization
return Organization
def model_field_names(model):
return list(
set(
chain.from_iterable(
(field.name, field.attname)
if hasattr(field, "attname")
... | BSD 2-Clause Simplified License |
westpa/westpa | lib/west_tools/westtools/wipi.py | __get_data_for_iteration__.successful_trajectories | python | def successful_trajectories(self):
state_changes = np.where(self.raw['states'][:,:-1] != self.raw['states'][:,1:])
walkers = state_changes[0]
new_states = state_changes[1] + 1
old_states = state_changes[1]
walker = {}
for z, (i, j) in enumerate(zip(old_states, new_states)... | Returns which trajectories are successful. | https://github.com/westpa/westpa/blob/cda177c5dea2cee571d71c4b04fcc625dc5f689c/lib/west_tools/westtools/wipi.py#L427-L450 | import numpy as np
import os, sys
import scipy.sparse as sp
from westtools import Plotter
import itertools
class WIPIDataset(object):
def __init__(self, raw, key):
self.__dict__ = {}
self.raw = raw
self.name = key
def __repr__(self):
if isinstance(self.__dict__['raw'], dict):
... | MIT License |
hszhao/pointweb | lib/pointops/functions/pointops.py | pairwise_distances | python | def pairwise_distances(x, y=None):
x_norm = (x ** 2).sum(1).view(-1, 1)
if y is not None:
y_t = torch.transpose(y, 0, 1)
y_norm = (y ** 2).sum(1).view(1, -1)
else:
y_t = torch.transpose(x, 0, 1)
y_norm = x_norm.view(1, -1)
dist = x_norm + y_norm - 2.0 * torch.mm(x, y_t)
... | Input: x is a Nxd matrix
y is an optional Mxd matirx
Output: dist is a NxM matrix where dist[i,j] is the square norm between x[i,:] and y[j,:]
if y is not given then use 'y=x'.
i.e. dist[i,j] = ||x[i,:]-y[j,:]||^2 | https://github.com/hszhao/pointweb/blob/f31fe05616c3c068f6c1870170a3caaf1f7d8abb/lib/pointops/functions/pointops.py#L346-L363 | from typing import Tuple
import torch
from torch.autograd import Function
import torch.nn as nn
import pointops_cuda
class FurthestSampling(Function):
@staticmethod
def forward(ctx, xyz, m):
assert xyz.is_contiguous()
b, n, _ = xyz.size()
idx = torch.cuda.IntTensor(b, m)
temp = t... | MIT License |
probcomp/bayeslite | src/core.py | bayesdb_table_has_column | python | def bayesdb_table_has_column(bdb, table, name):
bayesdb_table_guarantee_columns(bdb, table)
sql = 'SELECT COUNT(*) FROM bayesdb_column WHERE tabname = ? AND name = ?'
return cursor_value(bdb.sql_execute(sql, (table, name))) | True if the table named `table` has a column named `name`.
`bdb` must have a table named `table`. If you're not sure, call
:func:`bayesdb_has_table` first.
WARNING: This may modify the database by populating the
``bayesdb_column`` table if it has not yet been populated. | https://github.com/probcomp/bayeslite/blob/211e5eb3821a464a2fffeb9d35e3097e1b7a99ba/src/core.py#L82-L93 | from bayeslite.exception import BQLError
from bayeslite.sqlite3_util import sqlite3_quote_name
from bayeslite.util import casefold
from bayeslite.util import cursor_value
def bayesdb_has_table(bdb, name):
qt = sqlite3_quote_name(name)
cursor = bdb.sql_execute('PRAGMA table_info(%s)' % (qt,))
try:
cu... | Apache License 2.0 |
zagaran/mongolia | mongolia/database_collection.py | DatabaseCollection.__init__ | python | def __init__(self, path=None, objtype=None, query=None, sort_by=ID_KEY, ascending=True,
page=0, page_size=None, read_only=False, projection=None, field=None,
**kwargs):
if objtype:
self.OBJTYPE = objtype
if path:
self.PATH = path
if not q... | Loads a list of DatabaseObjects from path matching query. If nothing
matches the query (possibly because there is nothing in the specified
mongo collection), the created DatabaseCollection will be an empty
list and have bool(returned object) == False
NOTE: The path and objtype ... | https://github.com/zagaran/mongolia/blob/18d921017123b9edb7b70b01d8cfb3eb491b4cb6/mongolia/database_collection.py#L67-L161 | import json
from pymongo import ASCENDING, DESCENDING
from mongolia.constants import ID_KEY, GT
from mongolia.database_object import DatabaseObject
from mongolia.json_codecs import MongoliaJSONEncoder
class DatabaseCollection(list):
OBJTYPE = DatabaseObject
PATH = None | MIT License |
diofant/diofant | diofant/simplify/radsimp.py | rcollect | python | def rcollect(expr, *vars):
if expr.is_Atom or not expr.has(*vars):
return expr
else:
expr = expr.__class__(*[rcollect(arg, *vars) for arg in expr.args])
if expr.is_Add:
return collect(expr, vars)
else:
return expr | Recursively collect sums in an expression.
Examples
========
>>> expr = (x**2*y + x*y + x + y)/(x + y)
>>> rcollect(expr, y)
(x + y*(x**2 + x + 1))/(x + y)
See Also
========
collect, collect_const, collect_sqrt | https://github.com/diofant/diofant/blob/05c50552b0e0533f1dbf2ec05e65b6c45b7e2c11/diofant/simplify/radsimp.py#L387-L412 | from collections import defaultdict
from ..core import (Add, Derivative, I, Integer, Mul, Pow, Rational,
expand_mul, expand_power_base, gcd_terms, symbols)
from ..core.compatibility import iterable
from ..core.exprtools import Factors
from ..core.function import _mexpand
from ..core.mul import _keep... | BSD 3-Clause New or Revised License |
cityofsantamonica/mds-provider | mds/db/loaders.py | Records.load | python | def load(self, source, **kwargs):
if isinstance(source, dict):
source = [source]
df = pd.DataFrame.from_records(source)
super().load(df, **kwargs) | Load data from one or more MDS Provider records.
Parameters:
source: dict, list
One or more dicts of type record_type.
record_type: str
The type of MDS data.
table: str
The name of the database table to insert this data into.... | https://github.com/cityofsantamonica/mds-provider/blob/02abcb227c35cdfe78a39e35b3157f7c2916c028/mds/db/loaders.py#L193-L216 | import string
import pandas as pd
from ..db import sql
from ..fake import util
from ..files import DataFile
from ..schemas import STATUS_CHANGES, TRIPS, EVENTS, VEHICLES, Schema
from ..versions import UnexpectedVersionError, Version
class DataFrame():
def load(self, source, **kwargs):
record_type = kwargs.p... | MIT License |
google/cauliflowervest | cauliflowervest/server/handlers/maintenance.py | _update_schema | python | def _update_schema(model, cursor=None, num_updated=0):
query = model.all()
if cursor:
query.with_cursor(cursor)
updated = 0
for p in query.fetch(limit=_BATCH_SIZE):
_reinsert_entity(model, p.key())
updated += 1
if updated > 0:
num_updated += updated
logging.info(
'Put %d %s entitie... | Add tag field. | https://github.com/google/cauliflowervest/blob/d3f52501ebed8b9a392350c8e177bbc602a6a09d/cauliflowervest/server/handlers/maintenance.py#L41-L63 | import httplib
import logging
from google.appengine.api import users
from google.appengine.ext import db
from google.appengine.ext import deferred
from cauliflowervest import settings as base_settings
from cauliflowervest.server.handlers import base_handler
from cauliflowervest.server.models import base
from cauliflowe... | Apache License 2.0 |
jmchilton/galaxy-central | galaxy/datatypes/sniff.py | is_bed | python | def is_bed(headers, skip=0):
try:
if not headers:
return False
for hdr in headers[skip:]:
try:
map(int, [ hdr[1], hdr[2] ])
except:
return False
return True
except:
return False | Checks for 'bedness'
>>> fname = get_test_fname('test_tab.bed')
>>> headers = get_headers(fname, sep='\\t')
>>> is_bed(headers)
True
>>> fname = get_test_fname('interval.bed')
>>> headers = get_headers(fname, sep='\\t')
>>> is_bed(headers)
False | https://github.com/jmchilton/galaxy-central/blob/31e2fd3a32b06ddfba06ae5b044efdce1d93f08c/galaxy/datatypes/sniff.py#L221-L246 | import logging, sys, os, csv, tempfile, shutil, re
log = logging.getLogger(__name__)
def get_test_fname(fname):
path, name = os.path.split(__file__)
full_path = os.path.join(path, 'test', fname)
return full_path
def stream_to_file(stream):
fd, temp_name = tempfile.mkstemp()
while 1:
chunk = ... | MIT License |
smartbgp/yabgp | yabgp/message/open.py | Open.construct | python | def construct(self, my_capability):
capas = b''
if 'afi_safi' in my_capability:
capas += Capability(capa_code=1, capa_length=4).construct(my_capability)
if my_capability.get('cisco_route_refresh'):
capas += Capability(capa_code=128, capa_length=0).construct(my_capability)... | Construct a BGP Open message | https://github.com/smartbgp/yabgp/blob/f073633a813899cd9b413bc28ea2f7737deee141/yabgp/message/open.py#L232-L265 | import struct
import netaddr
from yabgp.common import exception as excp
from yabgp.common import constants as bgp_cons
class Open(object):
def __init__(self, version=None, asn=None, hold_time=None,
bgp_id=None, opt_para_len=None, opt_paras=None):
self.version = version
self.asn = as... | Apache License 2.0 |
pbattaglia/scenesim | scenesim/physics/bulletbase.py | BulletBase.add_ghostnode | python | def add_ghostnode(node):
name = "%s-ghost" % node.getName()
ghost = NodePath(BulletGhostNode(name))
ghost.reparentTo(node)
return ghost | Adds a child ghostnode to a node as a workaround for the
ghost-static node collision detection problem. | https://github.com/pbattaglia/scenesim/blob/2633c63bc5cb97ea99017b2e25fc9b4f66d72605/scenesim/physics/bulletbase.py#L582-L588 | from collections import Iterable
from contextlib import contextmanager
from functools import update_wrapper
from itertools import combinations, izip
from math import isnan, sqrt
from warnings import warn
import numpy as np
from panda3d.bullet import (BulletBaseCharacterControllerNode, BulletBodyNode,
... | MIT License |
onshape-public/onshape-clients | python/onshape_client/oas/models/bt_microversion_info.py | BTMicroversionInfo.openapi_types | python | def openapi_types():
return {
"microversion": (str,),
} | This must be a class method so a model may have properties that are
of type self, this ensures that we don't create a cyclic import
Returns
openapi_types (dict): The key is attribute name
and the value is attribute type. | https://github.com/onshape-public/onshape-clients/blob/20843a00c628e516e7219e17a23ec4ef2bf9f16f/python/onshape_client/oas/models/bt_microversion_info.py#L66-L77 | from __future__ import absolute_import
import re
import sys
import six
import nulltype
from onshape_client.oas.model_utils import (
ModelComposed,
ModelNormal,
ModelSimple,
date,
datetime,
file_type,
int,
none_type,
str,
validate_get_composed_info,
)
class BTMicroversio... | MIT License |
decred/tinydecred | decred/decred/dcr/blockchain.py | LocalNode.header | python | def header(self, blockHash):
try:
return self.headerDB[blockHash]
except database.NoValueError:
header = self.rpc.getBlockHeader(blockHash, verbose=False)
self.headerDB[header.cachedHash()] = header
return header | Get the header, from the headerDB if possible, otherwise fetch from RPC.
Args:
blockHash (ByteArray): The block header hash.
Returns:
BlockHeader: The block header. | https://github.com/decred/tinydecred/blob/f7f7d9f7da8d49d9ae9a72e5579b07a3b8572267/decred/decred/dcr/blockchain.py#L66-L81 | import time
from decred.dcr import addrlib, rpc
from decred.dcr.wire.msgblock import BlockHeader
from decred.util import database, helpers
from decred.util.encode import ByteArray
log = helpers.getLogger("blockchain")
class LocalNode:
def __init__(self, netParams, dbPath, url, user, pw, certPath=None):
self... | ISC License |
muneebalam/scrapenhl2 | scrapenhl2/plot/app/player_page.py | generate_table | python | def generate_table(dataframe):
return html.Table(
[html.Tr([html.Th(col) for col in dataframe.columns])] +
[html.Tr([html.Td(dataframe.iloc[i][col]) for col in dataframe.columns]) for i in range(len(dataframe))]) | Transforms a pandas dataframe into an HTML table | https://github.com/muneebalam/scrapenhl2/blob/a9867f03d002773da852fc150f2976adc2ba8c25/scrapenhl2/plot/app/player_page.py#L24-L31 | import pandas as pd
import datetime
import dash
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output
import plotly.graph_objs as go
import scrapenhl2.scrape.schedules as schedules
import scrapenhl2.scrape.players as players
import scrapenhl2.plot.rolling_cf_... | MIT License |
seldonio/alibi | alibi/explainers/cfrl_tabular.py | CounterfactualRLTabular._diversity | python | def _diversity(self,
X: np.ndarray,
Y_t: np.ndarray,
C: Optional[List[Dict[str, List[Union[str, float]]]]],
num_samples: int = 1,
batch_size: int = 100,
patience: int = 1000,
tolerance: f... | Generates a set of diverse counterfactuals given a single instance, target and conditioning.
Parameters
----------
X
Input instance.
Y_t
Target label.
C
List of conditional dictionaries. If `None`, it means that no conditioning was used during... | https://github.com/seldonio/alibi/blob/ef757b9579f85ef2e3dfc7088211969616ee3fdb/alibi/explainers/cfrl_tabular.py#L377-L497 | from alibi.api.interfaces import Explainer, Explanation
from alibi.utils.frameworks import has_pytorch, has_tensorflow
from alibi.explainers.cfrl_base import CounterfactualRL, Postprocessing, _PARAM_TYPES
from alibi.explainers.backends.cfrl_tabular import sample, get_conditional_vector, get_statistics
import numpy as n... | Apache License 2.0 |
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