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<|fim_suffix|> LOGGERS.clear() def test_bad_log_dir(): """ test bad log dir warning and converstion to stream logger """ with pytest.warns(LoggerWarning): log_file = '/abc/log.log' logger = init_logger(__name__, log_file=log_file) assert len(logger.handlers) == 1 ...
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{ "lang": "python", "repo": "NREL/rex", "path": "/tests/test_logging.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: NREL/rex path: /tests/test_logging.py # -*- coding: utf-8 -*- """ pytests for logging methodology """ import os import pytest import tempfile from rex.utilities.exceptions import LoggerWarning from rex.utilities.loggers import (init_logger, LOGGERS, add_handlers, ...
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{ "lang": "python", "repo": "NREL/rex", "path": "/tests/test_logging.py", "mode": "psm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: avast/retdec path: /scripts/type_extractor/type_extractor/lti_types.py """Dictionary of types used in headers and types for lti.""" LTI_TYPES = { # default C types and some typedefs '__int64': 'i64', 'bool': 'i1', 'double': 'double', 'long double': 'double', 'float': 'flo...
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{ "lang": "python", "repo": "avast/retdec", "path": "/scripts/type_extractor/type_extractor/lti_types.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> # modifiers '*': '*', 'const': '', 'signed': '', 'unsigned': '', # specials '_In_': '', '_In_opt_': '', '_Inout_': 'OUT ', '_Inout_opt_': 'OUT ', '_Out_': 'OUT ', '_Out_opt_': 'OUT ', '_Reserved_': '', # structs 'struct': '%struct.', }<|fim_prefi...
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{ "lang": "python", "repo": "avast/retdec", "path": "/scripts/type_extractor/type_extractor/lti_types.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: numpy/numpy path: /numpy/matrixlib/defmatrix.pyi from collections.abc import Sequence, Mapping from typing import Any from numpy import matrix as matrix from numpy._typing import ArrayLike, DTypeLike, NDArray <|fim_suffix|>def bmat( obj: str | Sequence[ArrayLike] | NDArray[Any], ldict: N...
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{ "lang": "python", "repo": "numpy/numpy", "path": "/numpy/matrixlib/defmatrix.pyi", "mode": "psm", "license": "Zlib", "source": "the-stack-v2" }
<|fim_suffix|>def asmatrix(data: ArrayLike, dtype: DTypeLike = ...) -> matrix[Any, Any]: ... mat = asmatrix<|fim_prefix|># repo: numpy/numpy path: /numpy/matrixlib/defmatrix.pyi from collections.abc import Sequence, Mapping from typing import Any from numpy import matrix as matrix from numpy._typing import ArrayLike,...
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{ "lang": "python", "repo": "numpy/numpy", "path": "/numpy/matrixlib/defmatrix.pyi", "mode": "spm", "license": "Zlib", "source": "the-stack-v2" }
<|fim_prefix|># repo: adafruit/Adafruit_CircuitPython_CircuitPlayground path: /examples/circuitplayground_advanced_examples/circuitplayground_gravity_pulls_pixel.py # SPDX-FileCopyrightText: 2021 ladyada for Adafruit Industries # SPDX-License-Identifier: MIT """Gravity Pulls Pixel This program uses the Circuit Playg...
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{ "lang": "python", "repo": "adafruit/Adafruit_CircuitPython_CircuitPlayground", "path": "/examples/circuitplayground_advanced_examples/circuitplayground_gravity_pulls_pixel.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> cp.pixels.brightness = 0.1 # Adjust overall brightness as desired, between 0 and 1 pixel_positions = compute_pixel_angles() while True: debug = cp.switch # True is toward the left accel_x, accel_y = cp.acceleration[:2] # Ignore z down_angle = positive_degrees(angle_in_degrees(accel_x, acc...
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{ "lang": "python", "repo": "adafruit/Adafruit_CircuitPython_CircuitPlayground", "path": "/examples/circuitplayground_advanced_examples/circuitplayground_gravity_pulls_pixel.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> list_attr_celeba_txt = os.path.join(cfg['root'], 'CelebA', 'Anno', 'list_attr_celeba.txt') df = pd.read_csv(list_attr_celeba_txt, delim_whitespace=True, header=None) df.columns = ["File", "5_o_Clock_Shadow", "Arched_Eyebrows", "Attractive", "Bags_Under_Eyes", "Bald", "Bangs", ...
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{ "lang": "python", "repo": "lucasxlu/MMNet", "path": "/data/datasets.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: lucasxlu/MMNet path: /data/datasets.py from skimage.color import gray2rgb import torch from torch.utils.data.sampler import SubsetRandomSampler from torch.utils.data import Dataset, DataLoader from torchvision import transforms, utils sys.path.append('../') from config.cfg import cfg class Ra...
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{ "lang": "python", "repo": "lucasxlu/MMNet", "path": "/data/datasets.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> return sample class UTKFaceDataset(Dataset): """ UTKFace dataset """ def __init__(self, train=True, transform=None): files = os.listdir(os.path.join(cfg['root'], 'UTKFace')) ages = [int(fname.split("_")[0]) for fname in files] train_files, test_files, tr...
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{ "lang": "python", "repo": "lucasxlu/MMNet", "path": "/data/datasets.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>system("ccx element") os.system("cgx -b post-n.fbd") os.system("cgx -b post-e.fbd")<|fim_prefix|># repo: larsmei/CalculiX-Examples path: /Linear/Separate/test.py #!/usr/bin/python import os os.system("c<|fim_middle|>gx -b pre.fbd") os.system("ccx nodal") os.
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{ "lang": "python", "repo": "larsmei/CalculiX-Examples", "path": "/Linear/Separate/test.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: larsmei/CalculiX-Examples path: /Linear/Separate/test.py #!/usr/bin/python import os os.system("c<|fim_suffix|>ost-n.fbd") os.system("cgx -b post-e.fbd")<|fim_middle|>gx -b pre.fbd") os.system("ccx nodal") os.system("ccx element") os.system("cgx -b p
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{ "lang": "python", "repo": "larsmei/CalculiX-Examples", "path": "/Linear/Separate/test.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> operations = [ migrations.RemoveField( model_name='queue', name='value', ), migrations.RemoveField( model_name='ticketpriority', name='value', ), ]<|fim_prefix|># repo: KerkhoffTechnologies/django-autotask path: /djau...
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{ "lang": "python", "repo": "KerkhoffTechnologies/django-autotask", "path": "/djautotask/migrations/0009_auto_20190920_1648.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: KerkhoffTechnologies/django-autotask path: /djautotask/migrations/0009_auto_20190920_1648.py # Generated by Django 2.1.11 on 2019-09-20 16:48 from django.db import migrations <|fim_suffix|> operations = [ migrations.RemoveField( model_name='queue', name='valu...
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{ "lang": "python", "repo": "KerkhoffTechnologies/django-autotask", "path": "/djautotask/migrations/0009_auto_20190920_1648.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> dependencies = [ ('lw2', '0003_auto_20180909_0727'), ] operations = [ migrations.AddField( model_name='post', name='slug', field=models.CharField(default='test', max_length=60), preserve_default=False, ), migrati...
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{ "lang": "python", "repo": "JD-P/accordius", "path": "/lw2/migrations/0004_auto_20180909_2314.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> dependencies = [ ('lw2', '0003_auto_20180909_0727'), ] operations = [ migrations.AddField( model_name='post', name='slug', field=models.CharField(default='test', max_length=60), preserve_default=False, ), migratio...
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{ "lang": "python", "repo": "JD-P/accordius", "path": "/lw2/migrations/0004_auto_20180909_2314.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: JD-P/accordius path: /lw2/migrations/0004_auto_20180909_2314.py # Generated by Django 2.1.1 on 2018-09-09 23:14 from django.conf import settings from django.db import migrations, models import django.db.models.deletion <|fim_suffix|> operations = [ migrations.AddField( mo...
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{ "lang": "python", "repo": "JD-P/accordius", "path": "/lw2/migrations/0004_auto_20180909_2314.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: MovElb/Ann path: /src/model/bertynet/BatchGen.py import random class BatchGen: """Batch generator class which can be used either for training or inference. """ def __init__(self, data, batch_size, evaluation=False): """ Args: data (list of lists): raw p...
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{ "lang": "python", "repo": "MovElb/Ann", "path": "/src/model/bertynet/BatchGen.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def __len__(self): return len(self.data) // self.batch_size def __iter__(self): """ Yields: batch (list of lists): len(batch) <= batch_size (may be less for last batch). Contains following data: [0] - context_ids [1] - context_t...
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{ "lang": "python", "repo": "MovElb/Ann", "path": "/src/model/bertynet/BatchGen.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: Jeromeyoung/wLogger path: /webServer/divers/mysql.py # coding=UTF-8 from flask import Response,current_app,request,session from sqlalchemy import text from webServer.customer import Func,ApiCorsResponse import json,time,datetime # 自定义mysql 数据获取class class MysqlDb(): today = time.strftime(...
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{ "lang": "python", "repo": "Jeromeyoung/wLogger", "path": "/webServer/divers/mysql.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> @classmethod def get_request_num_by_status(cls): with current_app.db.connect() as cursor: sql = text(""" select count(*) as total_num,`status_code` from {0} where `timestamp` >= UNIX_TIMESTAMP(:today) and `status_code` != 200 ...
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{ "lang": "python", "repo": "Jeromeyoung/wLogger", "path": "/webServer/divers/mysql.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> if not request.args.get('code'): return ApiCorsResponse.response('缺少code参数', False) with current_app.db.connect() as cursor: sql = text(""" select count(*) as total_num,`request_url` from {0} where FROM_UNIXTIME(`times...
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{ "lang": "python", "repo": "Jeromeyoung/wLogger", "path": "/webServer/divers/mysql.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: cash2one/xai path: /xai/brain/wordbase/nouns/_sulphur.py #calss header class _SULPHUR(): def __init__(self,): <|fim_suffix|> self.specie = 'nouns' def run(self, obj1 = [], obj2 = []): return self.jsondata<|fim_middle|> self.name = "SULPHUR" self.definitions = [u'a pale yellow chemic...
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{ "lang": "python", "repo": "cash2one/xai", "path": "/xai/brain/wordbase/nouns/_sulphur.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: tomway777/datalineage path: /parsing.py from database import connection import re # import parser from tools import spliters sql_query = '''SELECT ROUTINE_SCHEMA as sch, SPECIFIC_NAME as sp_name, ROUTINE_TYPE, ROUTINE_BODY, ROUTINE_DEFINITION as `sql`, SQL_DATA...
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{ "lang": "python", "repo": "tomway777/datalineage", "path": "/parsing.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|># Splitting comment and cleaning data for k,v in ndict.items(): if k == 'sp_body': nls = [] for i in v: nls.append(spt.reformat(i)) ndict[k] = nls ## Split data using space and dot print(ndict['sp_body'][1])<|fim_prefix|># repo: tomway777/datalineage path: /parsin...
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{ "lang": "python", "repo": "tomway777/datalineage", "path": "/parsing.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: cxdcxd/chainer-gqn path: /experiments/shepard_metzler/predictions.py import argparse import math import os import random import sys import time import chainer import chainer.functions as cf import cupy as cp import matplotlib.pyplot as plt import numpy as np from chainer.backends import cuda sy...
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{ "lang": "python", "repo": "cxdcxd/chainer-gqn", "path": "/experiments/shepard_metzler/predictions.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> query_viewpoints = xp.array( ( camera_direction[0], camera_direction[1], camera_direction[2], math.cos(yaw), ...
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{ "lang": "python", "repo": "cxdcxd/chainer-gqn", "path": "/experiments/shepard_metzler/predictions.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> generated_images = model.generate_image( query_viewpoints, representation)[0] yi_start = pitch_loop * image_height yi_end = (pitch_loop + 1) * image_height xi_start = yaw_loop * ima...
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{ "lang": "python", "repo": "cxdcxd/chainer-gqn", "path": "/experiments/shepard_metzler/predictions.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> #we can use for loops to iterate through a variable for i in range(n): #i in range [0,n-1] y[i] = 2.0 * float(i) + 1.0 #set y = 2i+1 #we can iterate through the y elements one by one for y_element in y: print(y_element) #execute the main function if __name__ == "__main__": main()<|fim_prefix|...
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{ "lang": "python", "repo": "Merlin1908/astr-119-hw-1", "path": "/astr-119-hw-1/variables_and_loops.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> #we can use nu,py to quickly make arrays y= np.zeros(n,dtype=float) #declares 10 zeros #we can use for loops to iterate through a variable for i in range(n): #i in range [0,n-1] y[i] = 2.0 * float(i) + 1.0 #set y = 2i+1 #we can iterate through the y elements one by one for y_element in y: ...
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{ "lang": "python", "repo": "Merlin1908/astr-119-hw-1", "path": "/astr-119-hw-1/variables_and_loops.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: Merlin1908/astr-119-hw-1 path: /astr-119-hw-1/variables_and_loops.py import numpy as np #we use numpy for lots of things def main(): i = 0 #declare i equal to 0 n = 10 #declare n equal to 10 x = 119.0 #float x, these have a . #we can use nu,py to quickly make arrays y= np.zeros(n,dtype=...
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{ "lang": "python", "repo": "Merlin1908/astr-119-hw-1", "path": "/astr-119-hw-1/variables_and_loops.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: DeachSword/LINE-DemoS-Bot path: /createLineAtAndVerify.py from DeachSword.linepy import * from DeachSword.LINEBASE import ttypes import requests, json, time, os, string, random def randstr(n): random_str = ''.join([random.choice(string.ascii_letters + string.digits) for i in range(n)]) r...
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{ "lang": "python", "repo": "DeachSword/LINE-DemoS-Bot", "path": "/createLineAtAndVerify.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> res = requests.post(host + endpoint, data=json.dumps(payload), headers=header) accessPermissions(channelId, AuthToken) return accessToken createOA() def accessPermissions(channelId, AuthToken): url = 'https://access.line.me/dialog/api/permissions' payload = { "on": [ ...
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{ "lang": "python", "repo": "DeachSword/LINE-DemoS-Bot", "path": "/createLineAtAndVerify.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> description = self.get_snapshot_description() snapshot = self._raw.create_snapshot( Description=description, TagSpecifications=[ { 'ResourceType': 'snapshot', 'Tags': [ {'Key': 'Name', '...
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{ "lang": "python", "repo": "guenbakku/ebsant", "path": "/core/volume.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: guenbakku/ebsant path: /core/volume.py # coding: utf-8 import utils from snapshot import Snapshot class Volume(object): ''' Represent Volume class ''' _config = { 'target_tag': 'ebsant', } def __init__(self, ec2, raw): ''' Instance constructor Agrs: ...
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{ "lang": "python", "repo": "guenbakku/ebsant", "path": "/core/volume.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: uva-slp/pico path: /docker/pico/secrets.py # Database info DB_NAME = 'pico' DB_USER = 'pico' DB_PASS = 'password' # Server email inf<|fim_suffix|>RT = 0 EMAIL_HOST_PASSWORD = '' # secret key<|fim_middle|>o SERVER_EMAIL = '' EMAIL_HOST = '' EMAIL_PO
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{ "lang": "python", "repo": "uva-slp/pico", "path": "/docker/pico/secrets.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>RT = 0 EMAIL_HOST_PASSWORD = '' # secret key<|fim_prefix|># repo: uva-slp/pico path: /docker/pico/secrets.py # Database info DB_NAME = 'pico' DB_USER = 'p<|fim_middle|>ico' DB_PASS = 'password' # Server email info SERVER_EMAIL = '' EMAIL_HOST = '' EMAIL_PO
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{ "lang": "python", "repo": "uva-slp/pico", "path": "/docker/pico/secrets.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: uva-slp/pico path: /docker/pico/secrets.py # Database info DB_NAME = 'pico' DB_USER = 'p<|fim_suffix|>RT = 0 EMAIL_HOST_PASSWORD = '' # secret key<|fim_middle|>ico' DB_PASS = 'password' # Server email info SERVER_EMAIL = '' EMAIL_HOST = '' EMAIL_PO
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{ "lang": "python", "repo": "uva-slp/pico", "path": "/docker/pico/secrets.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> @staticmethod def from_dict(dict): """ A convenience method that directly creates a new instance from a passed dictionary (that probably came from a JSON response from the server. """ return SIO_SDC(**dict)<|fim_prefix|># repo: keerthanabs1/scaleio-py path:...
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{ "lang": "python", "repo": "keerthanabs1/scaleio-py", "path": "/scaleiopy/api/scaleio/mapping/sdc.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: keerthanabs1/scaleio-py path: /scaleiopy/api/scaleio/mapping/sdc.py # Imports # Project imports from scaleiopy.api.scaleio.mapping.sio_generic_object import SIO_Generic_Object from scaleiopy.api.scaleio.mapping.link import SIO_Link <|fim_suffix|> def __init__(self, id=None, ...
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{ "lang": "python", "repo": "keerthanabs1/scaleio-py", "path": "/scaleiopy/api/scaleio/mapping/sdc.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> self.id = id self.name = name self.mdmConnectionState = mdmConnectionState self.sdcIp = sdcIp self.guid = sdcGuid self.links = [] for link in links: self.links.append(SIO_Link(link['href'], link['rel'])) @staticmethod def from_di...
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{ "lang": "python", "repo": "keerthanabs1/scaleio-py", "path": "/scaleiopy/api/scaleio/mapping/sdc.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> for i, pf in enumerate(plotfiles): ds = CastroDataset(pf) ds.add_field(("gas", "ash"), function=_ash, display_name="ash", units="(dimensionless)", sampling_type="cell") field = "ash" sp = yt.SlicePlot(ds, "theta", field, center=[xctr, yctr, 0.0*cm], width=[L_x, L_y, ...
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{ "lang": "python", "repo": "AMReX-Astro/Castro", "path": "/Exec/science/flame_wave/analysis/ash_timeseries.py", "mode": "spm", "license": "BSD-3-Clause-LBNL", "source": "the-stack-v2" }
<|fim_prefix|># repo: AMReX-Astro/Castro path: /Exec/science/flame_wave/analysis/ash_timeseries.py #!/usr/bin/env python3 import argparse import os import re import sys from functools import reduce import matplotlib import matplotlib.pyplot as plt import numpy as np from mpl_toolkits.axes_grid1 import ImageGrid imp...
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{ "lang": "python", "repo": "AMReX-Astro/Castro", "path": "/Exec/science/flame_wave/analysis/ash_timeseries.py", "mode": "psm", "license": "BSD-3-Clause-LBNL", "source": "the-stack-v2" }
<|fim_suffix|> self.logger.debug('Calling cavities') traceback = None cavities_list = [] tf_health, traceback = self._tf_health(force=False) cavities = tf_health.get('cavities', {}) for cavity_name, cavity in cavities.items(): cavity['name'] = cavity_name ...
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{ "lang": "python", "repo": "davidvoler/ate_meteor", "path": "/xmlrpc/server_process_base.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: davidvoler/ate_meteor path: /xmlrpc/server_process_base.py import xmlrpclib from tornado.options import options from ate_logger import AteLogger class BaseXmlRpcProcess(object): def __init__(self): self.logger = AteLogger('XmlRpcProcess') self._tf_status = False def st...
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{ "lang": "python", "repo": "davidvoler/ate_meteor", "path": "/xmlrpc/server_process_base.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def cavities(self): self.logger.debug('Calling cavities') traceback = None cavities_list = [] tf_health, traceback = self._tf_health(force=False) cavities = tf_health.get('cavities', {}) for cavity_name, cavity in cavities.items(): cavity['na...
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{ "lang": "python", "repo": "davidvoler/ate_meteor", "path": "/xmlrpc/server_process_base.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> for i in range(0,len(cls.indexes)): if function<=cls.indexes[i]: return cls.classes[i].execute(function-last,connection0,connection1,parameter0,parameter1,parameter2,gabor_filter_frequency,gabor_filter_orientation) last = cls.indexes[i]<|fim_prefix|># repo: ...
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{ "lang": "python", "repo": "julienbiau/CGP-IP", "path": "/cgpip/functions.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: julienbiau/CGP-IP path: /cgpip/functions.py import random class Functions: # Function Int # Connection 0 Int # Connection 1 Int # Parameter 0 Real no limitation # Parameter 1 Int [−16, +16] # Parameter 2 Int [−16, +16] # Gabor Filter Frequ. Int [0, 16] # Gabor Fi...
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{ "lang": "python", "repo": "julienbiau/CGP-IP", "path": "/cgpip/functions.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> last = 0 function -= cls.outside_nb_functions for i in range(0,len(cls.indexes)): if function<=cls.indexes[i]: return cls.classes[i].execute(function-last,connection0,connection1,parameter0,parameter1,parameter2,gabor_filter_frequency,gabor_filter_orien...
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{ "lang": "python", "repo": "julienbiau/CGP-IP", "path": "/cgpip/functions.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def write_to_csv(data: List[dict], filepath: Path): header = data[0].keys() with filepath.open('w') as fp: writer = csv.DictWriter(fp, header, quoting=csv.QUOTE_MINIMAL) writer.writeheader() writer.writerows(data) def main(): parser = argparse.ArgumentParser(descr...
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{ "lang": "python", "repo": "pddg/gnu-make-exercise", "path": "/ex03/gen_data.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: pddg/gnu-make-exercise path: /ex03/gen_data.py import argparse import csv from pathlib import Path from typing import List from mimesis import schema def generate_data_set(num: int) -> List[dict]: <|fim_suffix|>def main(): parser = argparse.ArgumentParser(description="Test data generator")...
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{ "lang": "python", "repo": "pddg/gnu-make-exercise", "path": "/ex03/gen_data.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>def main(): parser = argparse.ArgumentParser(description="Test data generator") parser.add_argument("filename", type=Path, help="Path to output file name") parser.add_argument("-n", "--number", type...
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{ "lang": "python", "repo": "pddg/gnu-make-exercise", "path": "/ex03/gen_data.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: qw85639229/Car_License_SVM path: /OCR_For_Car_License/chinese_template_generate.py import cv2 import os import numpy as np template_path = './data/Chinese_Template' templates = os.listdir(template_path) chinese_chars = [x.split('.')[0] for x in templates] template_imgs = [] for c in templates: ...
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{ "lang": "python", "repo": "qw85639229/Car_License_SVM", "path": "/OCR_For_Car_License/chinese_template_generate.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> # cv2.imshow('otsu', cropped_otsu_img) # cv2.waitKey(0) cropped_otsu_img = cv2.resize(cropped_otsu_img, (100, 100)) cv2.imwrite('./data/chinese_template_process/%s.jpg' % chinese_chars[j], cropped_otsu_img)<|fim_prefix|># repo: qw85639229/Car_License_SVM path: /OCR_For_Car_License/chines...
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{ "lang": "python", "repo": "qw85639229/Car_License_SVM", "path": "/OCR_For_Car_License/chinese_template_generate.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> # calculates the mean correlations for all images in the img_folders into a list corrs_means = [] corrs_quantiles = [] corrs_vars = [] for img_folder in img_folders: img_dir = os.path.join(dir, img_folder) corrs_folder = os.path.join(img_dir, 'corrs', method) ...
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{ "lang": "python", "repo": "heysoos/cppn-tensorflow", "path": "/visualize_natimg_correlations.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: heysoos/cppn-tensorflow path: /visualize_natimg_correlations.py import numpy as np import os import sampler import pickle from operator import itemgetter import matplotlib.pyplot as plt from matplotlib import colors from orderedset import OrderedSet import scipy.stats from p_tqdm import p_map de...
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{ "lang": "python", "repo": "heysoos/cppn-tensorflow", "path": "/visualize_natimg_correlations.py", "mode": "psm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|> # calculate correlation means corrs = np.nan_to_num(corrs) # set nan correlations to 0 folder_corrs_means.append(np.mean(corrs, axis=0)) folder_corrs_quantiles.append( (np.quantile(corrs, 0.25, axis=0), np.quantile(corrs, ...
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{ "lang": "python", "repo": "heysoos/cppn-tensorflow", "path": "/visualize_natimg_correlations.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|> _version_prefix = "rbac.authorization.k8s.io/" class Storage(KubernetesBaseObject): _version_prefix = "storage.k8s.io/" class Authentication(KubernetesBaseObject): _version_prefix = "authentication.k8s.io/" class Authorization(KubernetesBaseObject): _version_prefix = "authorizatio...
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{ "lang": "python", "repo": "Maxiimeeb/avionix", "path": "/avionix/kube/base_objects.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: Maxiimeeb/avionix path: /avionix/kube/base_objects.py """ Classes making up the main interfaces for other Kubernetes classes """ from typing import Optional from avionix.options import DEFAULTS from avionix.yaml.yaml_handling import HelmYaml class KubernetesBaseObject(HelmYaml): """ B...
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{ "lang": "python", "repo": "Maxiimeeb/avionix", "path": "/avionix/kube/base_objects.py", "mode": "psm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|>Agent.train(max_step=1500000, render=False, verbose=0,record_ep_inter=100) Agent.test(max_step=10000, render=True, verbose=2)<|fim_prefix|># repo: maccoyhaha/Torch-rl path: /Torch_rl/example/RUN_Pendulum_with_batch_PPO.py import gym import time from Torch_rl import Batch_PPO from Torch_rl.model.Network i...
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{ "lang": "python", "repo": "maccoyhaha/Torch-rl", "path": "/Torch_rl/example/RUN_Pendulum_with_batch_PPO.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: maccoyhaha/Torch-rl path: /Torch_rl/example/RUN_Pendulum_with_batch_PPO.py import gym import time from Torch_rl import Batch_PPO from Torch_rl.model.Network import DenseNet from torch import nn #%% envID ="Pendulum-v0" env = gym.make(envID) <|fim_suffix|>Agent = Batch_PPO(env, policy_model, val...
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{ "lang": "python", "repo": "maccoyhaha/Torch-rl", "path": "/Torch_rl/example/RUN_Pendulum_with_batch_PPO.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> return "Hello, World!"<|fim_prefix|># repo: petriashev/Abstract-Rest-Service-Benchmark path: /python-flask/app.py import logging from flask import Flask app = Flask(__name__) app.logger.disabled = True log = logging.getLogger('werkzeug') log.disabled = True <|fim_middle|>@app.route("/api/test")...
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{ "lang": "python", "repo": "petriashev/Abstract-Rest-Service-Benchmark", "path": "/python-flask/app.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: petriashev/Abstract-Rest-Service-Benchmark path: /python-flask/app.py import logging from flask import Flask <|fim_suffix|>@app.route("/api/test") def hello(): return "Hello, World!"<|fim_middle|>app = Flask(__name__) app.logger.disabled = True log = logging.getLogger('werkzeug') log.disa...
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{ "lang": "python", "repo": "petriashev/Abstract-Rest-Service-Benchmark", "path": "/python-flask/app.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>#This method queries all puppies by ascending weight def selectFatPuppies(): s = select([Puppy]).\ order_by("Puppy.weight") results = session.execute(s) print 'selectFatPuppies:' print '-----------------' print str(s) for result in results: print 'Weight: ',result.weight,\ 'Name: ',res...
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{ "lang": "python", "repo": "robertkohl125/PuppyShelter", "path": "/puppyExpressionLanguage.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> #This method queries all puppies grouped by the shelter in which they are staying def selectPuppiesByShelter(): j = join(Puppy, Shelter, Puppy.shelter_id == Shelter.shelter_id) s = select([Shelter.name, Puppy.puppy_id, Puppy.name]).select_from(j).\ order_by("shelter.name") results = session.execu...
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{ "lang": "python", "repo": "robertkohl125/PuppyShelter", "path": "/puppyExpressionLanguage.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: robertkohl125/PuppyShelter path: /puppyExpressionLanguage.py from sqlalchemy import * from sqlalchemy.orm import * from puppy_shelter_database_setup import Base, Puppy, Shelter from sqlalchemy.sql import * import datetime engine = create_engine('sqlite:///puppyshelter.db') Base.metadata.bind = e...
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{ "lang": "python", "repo": "robertkohl125/PuppyShelter", "path": "/puppyExpressionLanguage.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: zjsyj/JiashengBlog path: /JiashengBlog/article/forms.py from django import forms from .models import ArticlePost class ArticlePostForm(forms.ModelForm): <|fim_suffix|> model = ArticlePost fields = ('title', 'body')<|fim_middle|> class Meta:
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{ "lang": "python", "repo": "zjsyj/JiashengBlog", "path": "/JiashengBlog/article/forms.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> model = ArticlePost fields = ('title', 'body')<|fim_prefix|># repo: zjsyj/JiashengBlog path: /JiashengBlog/article/forms.py from django import forms from .models import ArticlePost <|fim_middle|>class ArticlePostForm(forms.ModelForm): class Meta:
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{ "lang": "python", "repo": "zjsyj/JiashengBlog", "path": "/JiashengBlog/article/forms.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: LennyPhoenix/Mini-Jam-56-Sky path: /source/__init__.py from .button import Button from .chunk import CHUNKS, Chunk from .player import Player from .tap_ba<|fim_suffix|>rt BucketBalloon from .water_drop import WaterDrop<|fim_middle|>lloon import TapBalloon from .bucket_balloon impo
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{ "lang": "python", "repo": "LennyPhoenix/Mini-Jam-56-Sky", "path": "/source/__init__.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>rt BucketBalloon from .water_drop import WaterDrop<|fim_prefix|># repo: LennyPhoenix/Mini-Jam-56-Sky path: /source/__init__.py from .button import Button from .chunk import CHU<|fim_middle|>NKS, Chunk from .player import Player from .tap_balloon import TapBalloon from .bucket_balloon impo
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{ "lang": "python", "repo": "LennyPhoenix/Mini-Jam-56-Sky", "path": "/source/__init__.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>lloon import TapBalloon from .bucket_balloon import BucketBalloon from .water_drop import WaterDrop<|fim_prefix|># repo: LennyPhoenix/Mini-Jam-56-Sky path: /source/__init__.py from .button import Button from .chunk import CHU<|fim_middle|>NKS, Chunk from .player import Player from .tap_ba
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{ "lang": "python", "repo": "LennyPhoenix/Mini-Jam-56-Sky", "path": "/source/__init__.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: aadeshnpn/swarm path: /test/test_evolution.py """Test case for convergence of evolution algorithm.""" from swarms.lib.agent import Agent from swarms.lib.model import Model from swarms.lib.time import SimultaneousActivation from swarms.lib.space import Grid from unittest import TestCase import nu...
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{ "lang": "python", "repo": "aadeshnpn/swarm", "path": "/test/test_evolution.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> self.direction = model.random.rand() * (2 * np.pi) self.speed = 2 self.radius = 3 # self.exchange_time = model.random.randint(2, 4) # This doesn't help. Maybe only perform genetic operations when # an agents meet 10% of its total population # """ ...
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{ "lang": "python", "repo": "aadeshnpn/swarm", "path": "/test/test_evolution.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: dtienq/crawl-shop path: /examples/service/ShopeeCrawler.py from .CrawService import CrawService from requests_html import HTML from ..base.base import session_factory from selenium.webdriver.support.ui import WebDriverWait from selenium.webdriver.support import expected_conditions as EC from sele...
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{ "lang": "python", "repo": "dtienq/crawl-shop", "path": "/examples/service/ShopeeCrawler.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> html_has_category = HTML(html=browser.page_source) categories = html_has_category.find('._2o2XQg') for category in categories: # save category to database category_url = url + category.links.pop() browser_category = craw_service.craw_html(categor...
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{ "lang": "python", "repo": "dtienq/crawl-shop", "path": "/examples/service/ShopeeCrawler.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: steinitzu/jotbox path: /jotbox/whitelist/base.py from abc import abstractmethod, ABC from typing import Optional, Generic from jotbox.types import TPayload, DateTimeStamp, TSub, TSession class Whitelist(ABC, Generic[TPayload]): @abstractmethod async def add(self, payload: TPayload, unt...
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{ "lang": "python", "repo": "steinitzu/jotbox", "path": "/jotbox/whitelist/base.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> @abstractmethod async def delete(self, delete: TPayload) -> None: """ Immediately revoke the token from the whitelist """ class SessionWhitelist(Whitelist[TSession], Generic[TSession, TSub]): @abstractmethod async def delete_sub(self, sub: TSub) -> None: "...
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{ "lang": "python", "repo": "steinitzu/jotbox", "path": "/jotbox/whitelist/base.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: umr-ds/pyserval path: /pyserval/lowlevel/client.py """ pyserval.lowlevel.client ~~~~~~~~~~~~~~~ Collection of API-objects """ from pyserval.lowlevel.connection import RestfulConnection from pyserval.lowlevel.keyring import LowLevelKeyring from pyserval.lowlevel.rhizome import LowLevelRhizome fr...
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{ "lang": "python", "repo": "umr-ds/pyserval", "path": "/pyserval/lowlevel/client.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> @staticmethod def new( host: str = "localhost", port: int = 4110, user: str = "pyserval", passwd: str = "pyserval", ): """Utility-method that creates a connection-object and then a lient from it Args: host (str): Hostname to connect ...
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{ "lang": "python", "repo": "umr-ds/pyserval", "path": "/pyserval/lowlevel/client.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> Args: host (str): Hostname to connect to port (int): Port to connect to user (str): Username for HTTP basic auth passwd (str): Password for HTTP basic auth Returns: LowLevelClient: Fully instantiated client """ co...
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{ "lang": "python", "repo": "umr-ds/pyserval", "path": "/pyserval/lowlevel/client.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: ma1co/fwtool.py path: /fwtool/util/__init__.py """Some utility functions to unpack integers""" import binascii import struct from collections import namedtuple def parse64be(data): return struct.unpack('>Q', data)[0] def dump64be(value): return struct.pack('>Q', value) def parse64le(data):...
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{ "lang": "python", "repo": "ma1co/fwtool.py", "path": "/fwtool/util/__init__.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> LITTLE_ENDIAN = '<' BIG_ENDIAN = '>' PADDING = '%dx' CHAR = 'c' STR = '%ds' INT64 = 'Q' INT32 = 'I' INT16 = 'H' INT8 = 'B' def __init__(self, name, fields, byteorder=LITTLE_ENDIAN): self.tuple = namedtuple(name, (n for n, fmt in fields if not isinstance(fmt, int))) self.format = byteorder +...
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{ "lang": "python", "repo": "ma1co/fwtool.py", "path": "/fwtool/util/__init__.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> reProj.change_projection(inShapefile, outShapefile, outEPSG)<|fim_prefix|># repo: HotMaps/Hotmaps-building_h-c path: /app/modules/common/CM/CM_TUW24/run_cm.py import os import sys path = os.path.dirname(os.path.dirname(os.path.dirname(os.path. ab...
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{ "lang": "python", "repo": "HotMaps/Hotmaps-building_h-c", "path": "/app/modules/common/CM/CM_TUW24/run_cm.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: HotMaps/Hotmaps-building_h-c path: /app/modules/common/CM/CM_TUW24/run_cm.py import os import sys path = os.path.dirname(os.path.dirname(os.path.dirname(os.path. abspath(__file__)))) if path not in sys.path: sys.path.append(path) import C...
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{ "lang": "python", "repo": "HotMaps/Hotmaps-building_h-c", "path": "/app/modules/common/CM/CM_TUW24/run_cm.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> return super(Firmware,self).comms_ok() def external_event(self, event_name, arg): super(Firmware,self).external_event(event_name, arg) if event_name=="upgradeFirmware": logging.info("Upgrading firmware on device "+self.properties["$id"]+" to "+str(arg)) ...
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{ "lang": "python", "repo": "pervasivesolutions/synth", "path": "/synth/devices/firmware.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def external_event(self, event_name, arg): super(Firmware,self).external_event(event_name, arg) if event_name=="upgradeFirmware": logging.info("Upgrading firmware on device "+self.properties["$id"]+" to "+str(arg)) self.set_property("firmware", arg) if e...
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{ "lang": "python", "repo": "pervasivesolutions/synth", "path": "/synth/devices/firmware.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: pervasivesolutions/synth path: /synth/devices/firmware.py """ firmware ======== Provides a device firmware revision, which can be change by incoming "upgradeFirmware" events, and rolled-back to factory firmware by incoming "factoryReset" events. Configurable parameters:: <|fim_suffix|> s...
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{ "lang": "python", "repo": "pervasivesolutions/synth", "path": "/synth/devices/firmware.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: cmuparlay/pbbsbench path: /benchmarks/nearestNeighbors/bench/testInputs #!/usr/bin/env python3 bnchmrk="neighbors" benchmark="Nearest Neighbors" checkProgram="../bench/neighborsCheck" dataDir = "../geometryData/data" <|fim_suffix|> [1, "3DinCube_10M","-d 3 -k 10", "-d 3 -k 10"], [1, "3Dp...
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{ "lang": "python", "repo": "cmuparlay/pbbsbench", "path": "/benchmarks/nearestNeighbors/bench/testInputs", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>import sys sys.path.insert(0, 'common') import runTests runTests.timeAllArgs(bnchmrk, benchmark, checkProgram, dataDir, tests)<|fim_prefix|># repo: cmuparlay/pbbsbench path: /benchmarks/nearestNeighbors/bench/testInputs #!/usr/bin/env python3 bnchmrk="neighbors" benchmark="Nearest Neighbors" checkProgra...
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{ "lang": "python", "repo": "cmuparlay/pbbsbench", "path": "/benchmarks/nearestNeighbors/bench/testInputs", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> if clustermeta['incl_mstar'] == 1: c_mcmc, rs_mcmc, normsersic_mcmc \ = map(lambda v: (v[1], v[2]-v[1], v[1]-v[0]), zip(*np.percentile(samples, [16, 50, 84], axis=0))) elif clustermeta['incl_mstar'] == ...
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{ "lang": "python", "repo": "hainest/bmpmod", "path": "/bmpmod/posterior_mcmc.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: hainest/bmpmod path: /bmpmod/posterior_mcmc.py import defaultparams.params as params from joblib import Parallel, delayed from mod_mass import * from gen import * import scipy import scipy.integrate import numpy as np def calc_rdelta_p(row, nemodel, clustermeta): ''' Radius corresp...
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{ "lang": "python", "repo": "hainest/bmpmod", "path": "/bmpmod/posterior_mcmc.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: PeterJCLaw/poltergeist path: /src/matches_for.py from datetime import datetime import sys import talk from display_utils import get_delayed_time <|fim_suffix|> num = ident[6:] # print "| {0} | {1} | {2} |".format(dt.time(), num, ' | '.join(team_ids)) print ident<|fim_middle|>req_team...
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{ "lang": "python", "repo": "PeterJCLaw/poltergeist", "path": "/src/matches_for.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> num = ident[6:] # print "| {0} | {1} | {2} |".format(dt.time(), num, ' | '.join(team_ids)) print ident<|fim_prefix|># repo: PeterJCLaw/poltergeist path: /src/matches_for.py from datetime import datetime import sys import talk from display_utils import get_delayed_time <|fim_middle|>req_team...
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{ "lang": "python", "repo": "PeterJCLaw/poltergeist", "path": "/src/matches_for.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>for ident, stamp in match_data: dt = datetime.fromtimestamp(stamp) dt = get_delayed_time(dt) teams_data = talk.command_yaml('get-match-teams {0}'.format(ident)) #print teams_data team_ids = teams_data['teams'] if not req_team in team_ids: continue num = ident[6:] # ...
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medium
{ "lang": "python", "repo": "PeterJCLaw/poltergeist", "path": "/src/matches_for.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>30): print('Time: '+str(i)) time.sleep(1) n = lora_proc('this is working')<|fim_prefix|># repo: CityofEdmonton/lora-ttn-messager path: /src/thethingsnetwork-send-v1/test.py from lora import lora_proc import time <|fim_middle|> n = lora_proc('testing') for i in range(
code_fim
easy
{ "lang": "python", "repo": "CityofEdmonton/lora-ttn-messager", "path": "/src/thethingsnetwork-send-v1/test.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: CityofEdmonton/lora-ttn-messager path: /src/thethingsnetwork-send-v1/test.py from lora import lora_proc import time <|fim_suffix|>sleep(1) n = lora_proc('this is working')<|fim_middle|> n = lora_proc('testing') for i in range(30): print('Time: '+str(i)) time.
code_fim
medium
{ "lang": "python", "repo": "CityofEdmonton/lora-ttn-messager", "path": "/src/thethingsnetwork-send-v1/test.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>sleep(1) n = lora_proc('this is working')<|fim_prefix|># repo: CityofEdmonton/lora-ttn-messager path: /src/thethingsnetwork-send-v1/test.py from lora import lora_proc import time <|fim_middle|> n = lora_proc('testing') for i in range(30): print('Time: '+str(i)) time.
code_fim
medium
{ "lang": "python", "repo": "CityofEdmonton/lora-ttn-messager", "path": "/src/thethingsnetwork-send-v1/test.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: christoffer/pycharm-pyxl path: /testdata/Comments.py # coding: pyxl def stuff_with_comments(): return ( <|fim_suffix|>]> <!-- Comment --> </html> </frag> )<|fim_middle|><frag> <!DOCTYPE html> <html><![CDATA[ <!-- I...
code_fim
hard
{ "lang": "python", "repo": "christoffer/pycharm-pyxl", "path": "/testdata/Comments.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> <!-- Inner comment --> ]]> <!-- Comment --> </html> </frag> )<|fim_prefix|># repo: christoffer/pycharm-pyxl path: /testdata/Comments.py # coding: pyxl def stuff_with_comments(): return ( <|fim_middle|><frag> <!DOCTYPE html...
code_fim
hard
{ "lang": "python", "repo": "christoffer/pycharm-pyxl", "path": "/testdata/Comments.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }