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<|fim_prefix|># repo: brainmorsel/python-dhcp-sprout path: /ds/dhcp/bench.py import logging import socket import threading import time from .proto.packet import Packet from .proto.opttypes import OptionType from .proto.dhcpmsg import MessageType def sync_worker(address, on_success, on_fail, oneshot=False, macaddr=...
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{ "lang": "python", "repo": "brainmorsel/python-dhcp-sprout", "path": "/ds/dhcp/bench.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> for _ in range(threads): t = threading.Thread(target=sync_worker, args=((host, port), inc_success, inc_fail, False, macaddr, relay_ip), daemon=True) t.start() while True: time.sleep(1.0) print('requests success: %s fail: %s' % (success_count, fail_count)) s...
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{ "lang": "python", "repo": "brainmorsel/python-dhcp-sprout", "path": "/ds/dhcp/bench.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: jgrss/geowombat path: /tests/test_coreg.py import unittest import tempfile from pathlib import Path import geowombat as gw from geowombat.data import l8_224077_20200518_B2 from geowombat.data import l8_224077_20200518_B4 import numpy as np import xarray as xr def shift(data: xr.Data...
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{ "lang": "python", "repo": "jgrss/geowombat", "path": "/tests/test_coreg.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> """Tests a 1-pixel shift.""" with gw.open(l8_224077_20200518_B2) as target, gw.open( l8_224077_20200518_B4 ) as reference: with tempfile.TemporaryDirectory() as tmp: # Shift by 1 pixel in each direction target_shifted = ...
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{ "lang": "python", "repo": "jgrss/geowombat", "path": "/tests/test_coreg.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: akleber/mqtt-connectors path: /tankstellen-connector.py #!/usr/bin/env python """Fetches diesel prices""" import paho.mqtt.client as paho # pip install paho-mqtt import time import logging import sys import requests from pathlib import Path from config import * from secrets import * FREQUEN...
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{ "lang": "python", "repo": "akleber/mqtt-connectors", "path": "/tankstellen-connector.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> try: tankstellenlist = ','.join(tankstellen) url = f"https://creativecommons.tankerkoenig.de/json/prices.php?ids={tankstellenlist}&apikey={TANKERKOENIG_API_KEY}" # noqa E501 r = requests.get(url, timeout=TIMEOUT) r.raise_for_status() data = r.json() if...
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{ "lang": "python", "repo": "akleber/mqtt-connectors", "path": "/tankstellen-connector.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: thanhtd91/proso-apps path: /proso_user/apps.py from django.apps import AppConfig as OAppConfig from proso.django.enrichment import register_object_type_enricher class AppConfig(OAppConfig): <|fim_suffix|> def ready(self): register_object_type_enricher(['user_question'], 'proso_user.j...
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{ "lang": "python", "repo": "thanhtd91/proso-apps", "path": "/proso_user/apps.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def ready(self): register_object_type_enricher(['user_question'], 'proso_user.json_enrich.user_answers')<|fim_prefix|># repo: thanhtd91/proso-apps path: /proso_user/apps.py from django.apps import AppConfig as OAppConfig from proso.django.enrichment import register_object_type_enricher clas...
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{ "lang": "python", "repo": "thanhtd91/proso-apps", "path": "/proso_user/apps.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: gumo-py/gumo-core path: /tests/core/domain/entity_key_test.py import pytest from gumo.core.domain.entity_key import KeyPair from gumo.core.domain.entity_key import NoneKey from gumo.core.domain.entity_key import EntityKey from gumo.core.domain.entity_key import EntityKeyFactory from gumo.core.do...
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{ "lang": "python", "repo": "gumo-py/gumo-core", "path": "/tests/core/domain/entity_key_test.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> class TestEntityKeyWithStringName: factory = EntityKeyFactory() sample_key_pairs = [ ('Book', 'name'), ('BookComment', 'comment'), ] def test_zero_length_pairs(self): with pytest.raises(ValueError): self.factory.build_from_pairs(pairs=[]) def test...
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{ "lang": "python", "repo": "gumo-py/gumo-core", "path": "/tests/core/domain/entity_key_test.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> """Returns the maximum allowed debug file size for this organization.""" if features.has('organizations:large-debug-files', organization): return MAX_FILE_SIZE else: return options.get('system.maximum-file-size')<|fim_prefix|># repo: honorarac/sentry path: /src/sentry/utils/fi...
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{ "lang": "python", "repo": "honorarac/sentry", "path": "/src/sentry/utils/files.py", "mode": "spm", "license": "BSD-2-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: honorarac/sentry path: /src/sentry/utils/files.py """ sentry.utils.files ~~~~~~~~~~~~~~~~~~ :copyright: (c) 2010-2014 by the Sentry Team, see AUTHORS for more details. :license: BSD, see LICENSE for more details. """ from __future__ import absolute_import import zlib <|fim_suffix|>def get_max_...
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{ "lang": "python", "repo": "honorarac/sentry", "path": "/src/sentry/utils/files.py", "mode": "psm", "license": "BSD-2-Clause", "source": "the-stack-v2" }
<|fim_suffix|> global showoldlines gAddMenu(self, "FA Demo", \ [["Init", self.initDemo], \ ['button', "Show Old Line", showoldlines, 1, 0, None], \ ["Resolution Higher", self.setResolutionHigher], \ ["Resolution Lower", self.setResolu...
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{ "lang": "python", "repo": "ideaOwl/rltoolkit", "path": "/RLtoolkit/fa/demo.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: ideaOwl/rltoolkit path: /RLtoolkit/fa/demo.py ### Routines for demonstrating 1D function learning programs. from RLtoolkit.G.g import * from RLtoolkit.Quickgraph.graph import * from math import * from .fa import * from .tilecoder import * window = None black = gColorBlack(True) flip = gColorFli...
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{ "lang": "python", "repo": "ideaOwl/rltoolkit", "path": "/RLtoolkit/fa/demo.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def check_for_protoproj(self): items=os.listdir( self.path ); for item in items: if item.endswith(".project-proto"): self.has_project_proto=True; self.proto_file=os.path.join(self.path,item); break;<|fim_prefix|># repo: SherrodJmsGitHub/packages path: /Fancy Projects/fancyproje...
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{ "lang": "python", "repo": "SherrodJmsGitHub/packages", "path": "/Fancy Projects/fancyprojects/project_structure.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> return self.name def check_for_protoproj(self): items=os.listdir( self.path ); for item in items: if item.endswith(".project-proto"): self.has_project_proto=True; self.proto_file=os.path.join(self.path,item); break;<|fim_prefix|># repo: SherrodJmsGitHub/packages path: /Fanc...
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{ "lang": "python", "repo": "SherrodJmsGitHub/packages", "path": "/Fancy Projects/fancyprojects/project_structure.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: SherrodJmsGitHub/packages path: /Fancy Projects/fancyprojects/project_structure.py # Copyright (C) 2013 Christopher "Kasoki" Kaster # # This file is part of "FancyProjects". <http://github.com/Kasoki/FancyProjects> # # Permission is hereby granted, free of charge, to any person obtaining a copy ...
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{ "lang": "python", "repo": "SherrodJmsGitHub/packages", "path": "/Fancy Projects/fancyprojects/project_structure.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> if self.serial != None: if self.serial.is_open: self.configure_device() else: raise IOError("Could not open serial port") elif self.bt_manager != None: if self.bt_manager.connected: ...
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{ "lang": "python", "repo": "markqvist/Reticulum", "path": "/RNS/Interfaces/Android/RNodeInterface.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> RNS.log("Configuring RNode interface...", RNS.LOG_VERBOSE) self.initRadio() if (self.validateRadioState()): self.interface_ready = True RNS.log(str(self)+" is configured and powered up") sleep(0.3) self.online = True else: ...
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{ "lang": "python", "repo": "markqvist/Reticulum", "path": "/RNS/Interfaces/Android/RNodeInterface.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: markqvist/Reticulum path: /RNS/Interfaces/Android/RNodeInterface.py serial.is_open: self.configure_device() else: raise IOError("Could not open serial port") elif self.bt_manager != None: if self.bt_manager.connec...
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{ "lang": "python", "repo": "markqvist/Reticulum", "path": "/RNS/Interfaces/Android/RNodeInterface.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: MFry/pyAlgoDataStructures path: /Top_Coder/Greedy/SRM169_GoldMine.py """ https://community.topcoder.com/stat?c=problem_statement&pm=2235&rd=5070 https://www.topcoder.com/community/data-science/data-science-tutorials/greedy-is-good/ """ def GoldMine(mines, miners): # sanitize input ...
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{ "lang": "python", "repo": "MFry/pyAlgoDataStructures", "path": "/Top_Coder/Greedy/SRM169_GoldMine.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> test_mines = ["000, 030, 030, 040, 000, 000, 000", "020, 020, 020, 010, 010, 010, 010"] test_miners = 4 result = GoldMine(test_mines, test_miners) solution = [2, 2] print('Test case result: ', result == solution) test_mines = ["026, 012, 005, 013, 038, 002, 004", "026, 012, 00...
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{ "lang": "python", "repo": "MFry/pyAlgoDataStructures", "path": "/Top_Coder/Greedy/SRM169_GoldMine.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: xalien10/pyfortnox path: /fortnox/services/voucher_services.py class VoucherService(object): """ :class:`fortnox.VoucherService` is used by :class:`fortnox.Client` to make actions related to Voucher resource. Normally you won't instantiate this class directly. """ """ ...
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{ "lang": "python", "repo": "xalien10/pyfortnox", "path": "/fortnox/services/voucher_services.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> Returns a single Voucher according to the unique Voucher ID provided If the specified Voucher does not exist, this query returns an error :calls: ``get /vouchers/sublist/{voucher_series}`` :param int id: Unique identifier of a Voucher. :return: Dictionary that supp...
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{ "lang": "python", "repo": "xalien10/pyfortnox", "path": "/fortnox/services/voucher_services.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: murageh/Formation path: /formation/tests/test_json.py import unittest from formation.formats import JSONFormat class EqualityTestCase(unittest.TestCase): def test_child_equality(self): json1 = """ { "type":"tag1", "children": [ {"typ...
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{ "lang": "python", "repo": "murageh/Formation", "path": "/formation/tests/test_json.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> json2 = """ { "type":"tag1", "attrib": { "name": "tag1" }, "children": [ { "type": "tag2", "attrib": { "attr": { "heig...
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{ "lang": "python", "repo": "murageh/Formation", "path": "/formation/tests/test_json.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def setUp(self) -> None: self.node = JSONFormat( data=""" { "type": "tag1", "attrib": { "name": "tag1", "attr": { "background": "#ffffff", "font": "A...
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{ "lang": "python", "repo": "murageh/Formation", "path": "/formation/tests/test_json.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: maxprofs-llcio/basilisk_mag path: /dist/Basilisk/fswAlgorithms/ephem_nav_converter/ephem_nav_converter.py # This file was automatically generated by SWIG (http://www.swig.org). # Version 3.0.12 # # Do not make changes to this file unless you know what you are doing--modify # the SWIG interface fi...
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{ "lang": "python", "repo": "maxprofs-llcio/basilisk_mag", "path": "/dist/Basilisk/fswAlgorithms/ephem_nav_converter/ephem_nav_converter.py", "mode": "psm", "license": "ISC", "source": "the-stack-v2" }
<|fim_suffix|> def __init__(self): this = _ephem_nav_converter.new_EphemNavConverterData() try: self.this.append(this) except __builtin__.Exception: self.this = this __swig_destroy__ = _ephem_nav_converter.delete_EphemNavConverterData __del__ = lambda self: Non...
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{ "lang": "python", "repo": "maxprofs-llcio/basilisk_mag", "path": "/dist/Basilisk/fswAlgorithms/ephem_nav_converter/ephem_nav_converter.py", "mode": "spm", "license": "ISC", "source": "the-stack-v2" }
<|fim_suffix|> def protectSetAttr(self, name, value): if(hasattr(self, name) or name == 'this'): object.__setattr__(self, name, value) else: raise ValueError('You tried to add this variable: ' + name + '\n' + 'To this class: ' + str(self)) def protectAllClasses(moduleType): imp...
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{ "lang": "python", "repo": "maxprofs-llcio/basilisk_mag", "path": "/dist/Basilisk/fswAlgorithms/ephem_nav_converter/ephem_nav_converter.py", "mode": "spm", "license": "ISC", "source": "the-stack-v2" }
<|fim_suffix|> dataloader = DataLoader(seq_dataset, batch_size=batch_size, shuffle=True, pin_memory=True, num_workers=8) log = 'dataset='+ str(args.dataset) log = log + '_window_size=' + str(window_size) if args.slide == 0 else log + '_slide=' + str(args.slide) log = log + '_hidden_size=' + str(hi...
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{ "lang": "python", "repo": "HankKung/LogPred", "path": "/train_ae.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: HankKung/LogPred path: /train_ae.py import time import torch import torch.nn as nn import torch.nn.functional as F import torch.optim as optim from torch.utils.tensorboard import SummaryWriter from torch.utils.data import TensorDataset, DataLoader import argparse from tqdm import tqdm import os ...
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{ "lang": "python", "repo": "HankKung/LogPred", "path": "/train_ae.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> label = torch.tensor(label).to(device) if args.model =='vae': loss, rec, kl = model.compute_loss(seq) else: output = model(seq) if args.dataset == 'bgl_loss' or args.dataset == 'bgl_loss_full': ...
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{ "lang": "python", "repo": "HankKung/LogPred", "path": "/train_ae.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> """ Generates the given node. If node is invalid, empty or non-existent, generates the entire website. """ if not node or not self.generated_once and not incremental: return self.generate_all() self.load_template_if_needed() self.initial...
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{ "lang": "python", "repo": "vosskuhle/hyde", "path": "/hyde/generator.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> self.refresh_config() if not resource.is_processable: logger.debug("Skipping [%s]", resource) return if incremental and not self.has_resource_changed(resource): logger.debug("No changes found. Skipping resource [%s]", resource) return...
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{ "lang": "python", "repo": "vosskuhle/hyde", "path": "/hyde/generator.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: vosskuhle/hyde path: /hyde/generator.py # -*- coding: utf-8 -*- """ The generator class and related utility functions. """ from commando.util import getLoggerWithNullHandler from fswrap import File, Folder from hyde.exceptions import HydeException from hyde.model import Context, Dependents from ...
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{ "lang": "python", "repo": "vosskuhle/hyde", "path": "/hyde/generator.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>#divide into validation data val_prec = 0.2 val_limits = int(val_prec * y.size) x_val = data_features[:val_limits, :] x_train = data_features[val_limits: , :] y_val = y[:val_limits] y_train = y[val_limits:] # #test data x_test = x_test/ 255.0 x_test = GetPredictedFeaturesFromMNIST(x_test, ...
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{ "lang": "python", "repo": "amirbawab/image_recognition", "path": "/tools/python/CNN_second_portion_segregated_image_28.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> np.save('x_train',x_train) np.save('y_train',y_train) np.save('x_val',x_val) np.save('y_val',y_val) np.save('x_test',x_test) def GetMappingTo40(mapping, labels): y=[] for i in labels: y.append(mapping[i]) y_mappedto_40 = np.array(y).astype('int32') return y_mappedto_40 de...
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{ "lang": "python", "repo": "amirbawab/image_recognition", "path": "/tools/python/CNN_second_portion_segregated_image_28.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: amirbawab/image_recognition path: /tools/python/CNN_second_portion_segregated_image_28.py ''' Using 12X3 vectors from forst portion of CNN architecture gets output 40 class classification Input: 3 images with same labels (segregated image with 2 digits and 1 alphabet) Output: 40 class class...
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{ "lang": "python", "repo": "amirbawab/image_recognition", "path": "/tools/python/CNN_second_portion_segregated_image_28.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>lothes[-1] <= rack_capacity: curr_sum += clothes.pop() else: racks_count += 1 curr_sum = 0 print(racks_count)<|fim_prefix|># repo: elenaborisova/Python-Advanced path: /02. Lists as Stacks and Queues - Exercise/04_fashion_boutique.py clothes = [int(x) for x in input().split()]...
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{ "lang": "python", "repo": "elenaborisova/Python-Advanced", "path": "/02. Lists as Stacks and Queues - Exercise/04_fashion_boutique.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: elenaborisova/Python-Advanced path: /02. Lists as Stacks and Queues - Exercise/04_fashion_boutique.py clothes = [int(x) for x in input().split()] rack_capacity = int(inpu<|fim_suffix|>se: racks_count += 1 curr_sum = 0 print(racks_count)<|fim_middle|>t()) racks_count = 1 curr_sum...
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{ "lang": "python", "repo": "elenaborisova/Python-Advanced", "path": "/02. Lists as Stacks and Queues - Exercise/04_fashion_boutique.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> width, height = video_dimensions(filename) video_stream, _ = ( ffmpeg .input(filename) .output('pipe:', format='rawvideo', pix_fmt='rgb24') .run(capture_stdout=True) ) video = ( np .frombuffer(video_stream, np.uint8) .reshape([-1, h...
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{ "lang": "python", "repo": "saulocatharino/pyfx", "path": "/pyfx/util/video.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>while True: in_bytes = process1.stdout.read(width * height * 3) if not in_bytes: break in_frame = ( np .frombuffer(in_bytes, np.uint8) .reshape([height, width, 3]) ) out_frame = in_frame * 0.3 process2.stdin.write( frame .astype(np.ui...
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{ "lang": "python", "repo": "saulocatharino/pyfx", "path": "/pyfx/util/video.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: saulocatharino/pyfx path: /pyfx/util/video.py import pyfx import numpy as np import ffmpeg def video_dimensions(filename): """ Get dimensions of frames in a video file. """ probe = ffmpeg.probe(filename) video_stream = next((stream for stream in probe['streams'] ...
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{ "lang": "python", "repo": "saulocatharino/pyfx", "path": "/pyfx/util/video.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: mit-aera/pyFlightGoggles path: /flightgoggles/controller.py #!/usr/bin/env python # coding: utf-8 import numpy as np import os, sys, time, copy, yaml from .utils import * # Controller base class UAV_pid(): def __init__(self, *args, **kwargs): # PID Controller Vehicle Parameters ...
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{ "lang": "python", "repo": "mit-aera/pyFlightGoggles", "path": "/flightgoggles/controller.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) # PID Controller Gains (roll / pitch / yaw) if 'propGain' in kwargs: self.propGain_ = kwargs['propGain'] else: if self.flag_debug: print("Did not get the PID ...
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{ "lang": "python", "repo": "mit-aera/pyFlightGoggles", "path": "/flightgoggles/controller.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>## Reduced COCOMO def prune_cocomo(model, rows, row_count, column_ratio): pruned_rows = shuffle(rows[:])[:row_count] loc_column, rest = model.decisions[-1], model.decisions[:-1] entropies = [] for decision in rest: effort_map = get_column_vals(model, pruned_rows, decision) entropy = 0 ...
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{ "lang": "python", "repo": "ai-se/george", "path": "/Technix/CoCoMo.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: ai-se/george path: /Technix/CoCoMo.py from __future__ import division,print_function import sys sys.dont_write_bytecode = True from lib import * import numpy as np _ = 0 Coc2tunings = { # vl l nom h vh xh # Scale Factors 'Flex' : [5.07, 4.05, 3.04, 2.03, 1.01, ...
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{ "lang": "python", "repo": "ai-se/george", "path": "/Technix/CoCoMo.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: openalto/alto-swagger path: /unicorn_server/models/__init__.py # coding: utf-8 from __future__ import absolute_import # import models into model package from .an<|fim_suffix|>or_meta import ErrorMeta from .flow_spec import FlowSpec from .path_query_response import PathQueryResponse from .query_d...
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{ "lang": "python", "repo": "openalto/alto-swagger", "path": "/unicorn_server/models/__init__.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>esponse from .query_desc import QueryDesc from .resource_query_response import ResourceQueryResponse<|fim_prefix|># repo: openalto/alto-swagger path: /unicorn_server/models/__init__.py # coding: utf-8 from __future__ import absolute_import # import models into model package from .an<|fim_middle|>e impor...
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{ "lang": "python", "repo": "openalto/alto-swagger", "path": "/unicorn_server/models/__init__.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> """Verbosity level to logging level.""" logLevels = {0: logging.WARNING, 1: logging.INFO} if verbosity > 1: return logging.DEBUG else: return logLevels.get(verbosity, logging.ERROR)<|fim_prefix|># repo: inetAnt/telegramtogo path: /telegramtogo/utils.py """ Utils """ import...
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{ "lang": "python", "repo": "inetAnt/telegramtogo", "path": "/telegramtogo/utils.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: inetAnt/telegramtogo path: /telegramtogo/utils.py """ Utils """ import logging <|fim_suffix|> """Verbosity level to logging level.""" logLevels = {0: logging.WARNING, 1: logging.INFO} if verbosity > 1: return logging.DEBUG else: return logLevels.get(verbosity, logg...
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{ "lang": "python", "repo": "inetAnt/telegramtogo", "path": "/telegramtogo/utils.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> EFIDTrackingCuts = ConfiguredNewTrackingTrigCuts("Offline") EFIDTrackingCutsCosmics = ConfiguredNewTrackingTrigCuts("Cosmics") EFIDTrackingCutsBeamGas = ConfiguredNewTrackingTrigCuts("BeamGas") EFIDTrackingCutsLowPt = ConfiguredNewTrackingTrigCuts("LowPt") EFIDTrackingCutsTRT = ConfiguredNewTrackingTrigC...
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{ "lang": "python", "repo": "strigazi/athena", "path": "/InnerDetector/InDetExample/InDetTrigRecExample/python/ConfiguredNewTrackingTrigCuts.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> from InDetTrigRecExample.InDetTrigFlags import InDetTrigFlags self.__indetflags = InDetTrigFlags EFIDTrackingCuts = ConfiguredNewTrackingTrigCuts("Offline") EFIDTrackingCutsCosmics = ConfiguredNewTrackingTrigCuts("Cosmics") EFIDTrackingCutsBeamGas = ConfiguredNewTrackingTrigCuts("BeamGas") EFID...
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{ "lang": "python", "repo": "strigazi/athena", "path": "/InnerDetector/InDetExample/InDetTrigRecExample/python/ConfiguredNewTrackingTrigCuts.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: strigazi/athena path: /InnerDetector/InDetExample/InDetTrigRecExample/python/ConfiguredNewTrackingTrigCuts.py # Copyright (C) 2002-2017 CERN for the benefit of the ATLAS collaboration """ Derive from the offline class and override InDetFlags """ __author__ = "J. Masik" __version__= "$Revision: ...
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{ "lang": "python", "repo": "strigazi/athena", "path": "/InnerDetector/InDetExample/InDetTrigRecExample/python/ConfiguredNewTrackingTrigCuts.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> transition.add_predicate(lambda t: not self._reserved_predicate(t)) super(Cycle, self).add_outgoing_transition(transition)<|fim_prefix|># repo: gosion/pyPvm path: /pvm/activities/cycle.py from uuid import UUID from pvm.activities.activity import Activity from pvm.transition import Transi...
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{ "lang": "python", "repo": "gosion/pyPvm", "path": "/pvm/activities/cycle.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: gosion/pyPvm path: /pvm/activities/cycle.py from uuid import UUID from pvm.activities.activity import Activity from pvm.transition import Transition <|fim_suffix|> """设置自循环出口条件 """ self._reserved_predicate = predicate self._reserved_transition.add_predicate(pred...
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{ "lang": "python", "repo": "gosion/pyPvm", "path": "/pvm/activities/cycle.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: jrepifano/xai_is_fragile path: /IRIS/loo_synthetic.py import os import shap import torch import numpy as np import simple_influence from scipy.stats import pearsonr, spearmanr from sklearn.datasets import make_classification from sklearn.model_selection import train_test_split from sklearn.prepro...
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{ "lang": "python", "repo": "jrepifano/xai_is_fragile", "path": "/IRIS/loo_synthetic.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def main(): n_datasets = 10000 nodes = [100, 500, 1000, 2000, 5000] epochs = [300, 300, 350, 350, 350] accuracy_results = np.empty((n_datasets, len(nodes), 5)) spearman_stats = np.empty((n_datasets, len(nodes), 3)) spearman_pvalues = np.empty((n_datasets, len(nodes), 3)) pears...
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{ "lang": "python", "repo": "jrepifano/xai_is_fragile", "path": "/IRIS/loo_synthetic.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: mruprich/leapp-repository path: /repos/system_upgrade/el7toel8/actors/initrdinclude/tests/test_initrdinclude.py import pytest from leapp.exceptions import StopActorExecutionError from leapp.libraries.actor import initrdinclude from leapp.libraries.stdlib import api, CalledProcessError from leapp...
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{ "lang": "python", "repo": "mruprich/leapp-repository", "path": "/repos/system_upgrade/el7toel8/actors/initrdinclude/tests/test_initrdinclude.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> self.called += 1 self.args = args if self.raise_err: raise_call_error(args) def test_no_includes(monkeypatch): run_mocked = RunMocked() monkeypatch.setattr(api, 'current_actor', CurrentActorMocked(msgs=[])) monkeypatch.setattr(api, 'current_logger', logger...
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{ "lang": "python", "repo": "mruprich/leapp-repository", "path": "/repos/system_upgrade/el7toel8/actors/initrdinclude/tests/test_initrdinclude.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: johnsonm325/drift-backend path: /tests/test_inventory_service_interface.py import requests import responses import string import unittest import mock from drift import app, inventory_service_interface from drift.exceptions import InventoryServiceError, SystemNotReturned from . import fixtures ...
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{ "lang": "python", "repo": "johnsonm325/drift-backend", "path": "/tests/test_inventory_service_interface.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> def _create_500_response_for_systems(self, service_hostname, system_uuids): url_template = "http://%s/api/inventory/v1/hosts/%s" responses.add(responses.GET, url_template % (service_hostname, system_uuids), body="I am error", status=requests.codes.INTERNAL_SERVER_...
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{ "lang": "python", "repo": "johnsonm325/drift-backend", "path": "/tests/test_inventory_service_interface.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> systems = inventory_service_interface.fetch_systems_with_profiles(systems_to_fetch, "my-auth-key", self.mock_logger) found_system_ids = {syste...
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{ "lang": "python", "repo": "johnsonm325/drift-backend", "path": "/tests/test_inventory_service_interface.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> } } model_params = { 'func' : train.get_latent_models, 'cfg' : model_cfg, 'action_model_desc' : 'uncertainty_model' } one_obj_scene_info = [ { 'type' : 'SHAPENET', 'scale' : args['objsize'], 'mass' : 1., ...
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{ "lang": "python", "repo": "neuroailab/curiosity_deprecated", "path": "/scripts/uncertainty_scripts/train_um_morechoked.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: neuroailab/curiosity_deprecated path: /scripts/uncertainty_scripts/train_um_morechoked.py ''' A script for searching through various possibilities with uncertainty model online learning, assuming that we are modeling the uncertainty of the action model. ''' import sys sys.path.append('curios...
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{ "lang": "python", "repo": "neuroailab/curiosity_deprecated", "path": "/scripts/uncertainty_scripts/train_um_morechoked.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|>train_params = { 'updater_func' : train.get_latent_updater, 'updater_kwargs' : { 'state_desc' : 'depths1' } } model_params = { 'func' : train.get_latent_models, 'cfg' : model_cfg, 'action_model_desc' : 'uncertainty_model' } one_obj_scene_i...
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{ "lang": "python", "repo": "neuroailab/curiosity_deprecated", "path": "/scripts/uncertainty_scripts/train_um_morechoked.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> 100)) print('O produto com desconto saiu de R${:.2f} por R${:.2f}.'.format(valor, desconto))<|fim_prefix|># repo: dudulacerdadl/prototipos path: /Curso Python/Exercícios/ex012.py valor = float(input('Digite o valor do produto<|fim_middle|> desejado: ')) desconto = valor - (valor * (5 /
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{ "lang": "python", "repo": "dudulacerdadl/prototipos", "path": "/Curso Python/Exercícios/ex012.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>${:.2f} por R${:.2f}.'.format(valor, desconto))<|fim_prefix|># repo: dudulacerdadl/prototipos path: /Curso Python/Exercícios/ex012.py valor = float(input('Digite o valor do produto<|fim_middle|> desejado: ')) desconto = valor - (valor * (5 / 100)) print('O produto com desconto saiu de R
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{ "lang": "python", "repo": "dudulacerdadl/prototipos", "path": "/Curso Python/Exercícios/ex012.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: dudulacerdadl/prototipos path: /Curso Python/Exercícios/ex012.py valor = float(input('Digite o valor do produto desejado: ')) desconto = valor - (valor * (5 /<|fim_suffix|>${:.2f} por R${:.2f}.'.format(valor, desconto))<|fim_middle|> 100)) print('O produto com desconto saiu de R
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{ "lang": "python", "repo": "dudulacerdadl/prototipos", "path": "/Curso Python/Exercícios/ex012.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: macbury/SmartHouse path: /home-assistant/custom_components/smartthinq_sensors/wideq/dehumidifier.py """------------------for Dehumidifier""" import enum import logging from typing import Optional from .const import ( FEAT_HUMIDITY, FEAT_TARGET_HUMIDITY, FEAT_WATER_TANK_FULL, ) from ....
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{ "lang": "python", "repo": "macbury/SmartHouse", "path": "/home-assistant/custom_components/smartthinq_sensors/wideq/dehumidifier.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> @property def operation(self): op = self._get_operation() if not op: return None return op.name @property def operation_mode(self): key = self._get_state_key(STATE_OPERATION_MODE) if (value := self.lookup_enum(key, True)) is None: ...
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{ "lang": "python", "repo": "macbury/SmartHouse", "path": "/home-assistant/custom_components/smartthinq_sensors/wideq/dehumidifier.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> async def power(self, turn_on): """Turn on or off the device (according to a boolean).""" op = DHumOp.ON if turn_on else DHumOp.OFF keys = self._get_cmd_keys(CMD_STATE_OPERATION) op_value = self.model_info.enum_value(keys[2], op.value) if self._should_poll: ...
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{ "lang": "python", "repo": "macbury/SmartHouse", "path": "/home-assistant/custom_components/smartthinq_sensors/wideq/dehumidifier.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>Q = q_init(env) print(Q.shape) desc = [['S', 'F', 'F'], ['F', 'H', 'H'], ['F', 'F', 'G']] env = load_frozen_lake(desc=desc) Q = q_init(env) print(Q.shape) env = load_frozen_lake(map_name='4x4') Q = q_init(env) print(Q.shape)<|fim_prefix|># repo: ledbagholberton/holbertonschool-machine_learning pa...
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{ "lang": "python", "repo": "ledbagholberton/holbertonschool-machine_learning", "path": "/reinforcement_learning/0x00-q_learning/1-main.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: ledbagholberton/holbertonschool-machine_learning path: /reinforcement_learning/0x00-q_learning/1-main.py #!/usr/bin/env python3 load_frozen_lake = __import__('0-load_env').load_frozen_lake q_init = __import__('1-q_in<|fim_suffix|>desc=desc) Q = q_init(env) print(Q.shape) env = load_frozen_...
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{ "lang": "python", "repo": "ledbagholberton/holbertonschool-machine_learning", "path": "/reinforcement_learning/0x00-q_learning/1-main.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> q = cls.query.filter(cls.object_id == obj.id, cls.object_type == obj.__tablename__) if access_type: q = q.filter(AccessPermission.access_type == access_type) if grantee: q = q.filter(AccessPermission.grantee == grantee) if grantor: q =...
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{ "lang": "python", "repo": "getredash/redash", "path": "/redash/models/users.py", "mode": "spm", "license": "BSD-2-Clause", "source": "the-stack-v2" }
<|fim_suffix|> def to_dict(self): return { "id": self.id, "name": self.name, "permissions": self.permissions, "type": self.type, "created_at": self.created_at, } @classmethod def all(cls, org): return cls.query.filter(cls.or...
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{ "lang": "python", "repo": "getredash/redash", "path": "/redash/models/users.py", "mode": "spm", "license": "BSD-2-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: getredash/redash path: /redash/models/users.py import hashlib import itertools import logging import time from functools import reduce from operator import or_ from flask import current_app as app from flask import request_started, url_for from flask_login import AnonymousUserMixin, UserMixin, c...
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{ "lang": "python", "repo": "getredash/redash", "path": "/redash/models/users.py", "mode": "psm", "license": "BSD-2-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: ppujol76/Lucas_Transformers path: /evaluate.py import torch import random from nltk.translate.bleu_score import corpus_bleu from model.visualization import Visualization def evaluate(model, test_loader, vocab, device, epoch): model.eval() <|fim_suffix|> if idx % 10 == 0: num_img=random....
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{ "lang": "python", "repo": "ppujol76/Lucas_Transformers", "path": "/evaluate.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> total_loss += corpus_bleu(target_s,sentences,(1.0/1.0,)) if idx % 10 == 0: num_img=random.randint(0,img.shape[0]-1) example=' '.join(sentences[num_img]) reference=vocab.generate_caption(target[num_img,1:]) print(f'Evaluating batch {idx} / {len(test_loader)}...') print(f'Gen ...
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{ "lang": "python", "repo": "ppujol76/Lucas_Transformers", "path": "/evaluate.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> if idx % 10 == 0: num_img=random.randint(0,img.shape[0]-1) example=' '.join(sentences[num_img]) reference=vocab.generate_caption(target[num_img,1:]) print(f'Evaluating batch {idx} / {len(test_loader)}...') print(f'Gen example: {example}') print(f'Exp example: {reference}') s...
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{ "lang": "python", "repo": "ppujol76/Lucas_Transformers", "path": "/evaluate.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>if not is_model_registered('accessgroup', 'AccessGroup'): class AccessGroup(AbstractAccessGroup): pass __all__.append('AccessGroup')<|fim_prefix|># repo: lyoniionly/django-cobra path: /src/cobra/apps/accessgroup/models.py # -*- coding: utf-8 -*- from cobra.core.loading import is_model_re...
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{ "lang": "python", "repo": "lyoniionly/django-cobra", "path": "/src/cobra/apps/accessgroup/models.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: lyoniionly/django-cobra path: /src/cobra/apps/accessgroup/models.py # -*- coding: utf-8 -*- from cobra.core.loading import is_model_registered from .abstract_models import * # noqa <|fim_suffix|> if not is_model_registered('accessgroup', 'AccessGroup'): class AccessGroup(AbstractAccessGrou...
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{ "lang": "python", "repo": "lyoniionly/django-cobra", "path": "/src/cobra/apps/accessgroup/models.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> pass __all__.append('AccessGroup')<|fim_prefix|># repo: lyoniionly/django-cobra path: /src/cobra/apps/accessgroup/models.py # -*- coding: utf-8 -*- from cobra.core.loading import is_model_registered from .abstract_models import * # noqa __all__ = [] <|fim_middle|> if not is_model_registe...
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{ "lang": "python", "repo": "lyoniionly/django-cobra", "path": "/src/cobra/apps/accessgroup/models.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> as0 = np.array(ps.vectorDataAt(a0)) for val in as0: assert val.tolist() == [2.0, 4.0, -1.0] as1 = np.array(ps.vectorDataAt(a1)) for val in as1: assert val.tolist() == [9.0, -2.0, 5.0] def test_add_particles3(): ps = pyjet.ParticleSystemData3() ps.resize(12) ...
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{ "lang": "python", "repo": "doyubkim/fluid-engine-dev", "path": "/src/tests/python_tests/test_particle_system_data.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: doyubkim/fluid-engine-dev path: /src/tests/python_tests/test_particle_system_data.py """ Copyright (c) 2018 Doyub Kim I am making my contributions/submissions to this project solely in my personal capacity and am not conveying any rights to any intellectual property of any third parties. """ im...
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{ "lang": "python", "repo": "doyubkim/fluid-engine-dev", "path": "/src/tests/python_tests/test_particle_system_data.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>metadict_class_proficiency = { # Ключ словаря -- кортеж (класс, уровень). ('Any',1):{'proficiency_bonus':2}, ('Any',2):{'proficiency_bonus':2}, ('Any',3):{'proficiency_bonus':2}, ('Any',4):{'proficiency_bonus':2}, ('Any',5):{'proficiency_bonus':3}, (...
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{ "lang": "python", "repo": "wizard-of-void/dnd-mass-combat-simulation", "path": "/data/classes.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: wizard-of-void/dnd-mass-combat-simulation path: /data/classes.py ('Wizard',15):{'1_lvl':4,'2_lvl':3,'3_lvl':3,'4_lvl':3,'5_lvl':2, '6_lvl':1,'7_lvl':1,'8_lvl':1,'9_lvl':0}, ('Wizard',16):{'1_lvl':4,'2_lvl':3,'3_lvl':3,'4_lvl':3,'5_lvl':2, '6_lvl':1,'7_lvl...
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{ "lang": "python", "repo": "wizard-of-void/dnd-mass-combat-simulation", "path": "/data/classes.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>metadict_class_spells = { # Слоты заклинаний по уровням: # https://www.dandwiki.com/wiki/5e_SRD:Bard#Table:_The_bard # Барды, клерики, друиды, волшебники и чародеи -- по слотам одинаковы: # TODO: сделай уже "any", если подходящего нет. ('Any',1):{}, ('Any',2...
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{ "lang": "python", "repo": "wizard-of-void/dnd-mass-combat-simulation", "path": "/data/classes.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> parsed = request.urlparts url = "%s://%s%s" % (parsed.scheme, parsed.netloc, request.script_name) return url @app.error(500) def error(e): response.content_type = "application/json" return json.dumps({ "status": e.status, "url": repr(request.url), "exception":...
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{ "lang": "python", "repo": "cloud-custodian/cloud-custodian", "path": "/tools/sandbox/c7n_sphere11/c7n_sphere11/app.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: cloud-custodian/cloud-custodian path: /tools/sandbox/c7n_sphere11/c7n_sphere11/app.py # Copyright The Cloud Custodian Authors. # SPDX-License-Identifier: Apache-2.0 from bottle import Bottle, request, response, abort import json import logging import os from audit import init_audit from control...
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{ "lang": "python", "repo": "cloud-custodian/cloud-custodian", "path": "/tools/sandbox/c7n_sphere11/c7n_sphere11/app.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> @app.error(500) def error(e): response.content_type = "application/json" return json.dumps({ "status": e.status, "url": repr(request.url), "exception": repr(e.exception), # "traceback": e.traceback and e.traceback.split('\n') or '', "body": repr(e.body) ...
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{ "lang": "python", "repo": "cloud-custodian/cloud-custodian", "path": "/tools/sandbox/c7n_sphere11/c7n_sphere11/app.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: alanlujan91/DemARK path: /notebooks/DiamondOLG.py # equation: Ctrl-E # itemize: Ctrl-I # labels_anchors: false # latex_user_defs: false # report_style_numbering: false # user_envs_cfg: false # widgets: # application/vnd.jupyter.widget-state+json: # state: ...
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{ "lang": "python", "repo": "alanlujan91/DemARK", "path": "/notebooks/DiamondOLG.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: alanlujan91/DemARK path: /notebooks/DiamondOLG.py xjnf9HxMR/Ps2fPMnLkSPr27Rtp+Rw5cvDxxx+zdu1avvzyS6pWrcquXbt4+PAh7dq1I1OmTPHehxcdV3t7e0uyOnLkSGxsbFi3bl2c1m3uZ3Lu3DnSpk0b6XPUokULxowZw6JFi6hUqRLbt2/Hw8Mj0rC4IiIiKd3t27f55ptvWL16NQBly5bFzc2NsmXLWjewJKAO2K+xxo0b4+bmxjvvvMOmTZtYsGAB6dOnp3///pb+A59++imN...
code_fim
hard
{ "lang": "python", "repo": "alanlujan91/DemARK", "path": "/notebooks/DiamondOLG.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|>TptBtSA8wG8vuR1Tt06RQaHDHzZ5Es+qPsBDpa0eVn2mjVr6NmzJ+fPnwegX79+jBkzJlGvYRYRERERSQoKqUJ4OCxYYN7u3du+tSQ2m2Fjwo4JDPtrGLG2WNxzuLOw7UJqF65t79KSxM2bNxk4cCA//PADAKVKlWLevHk0aNDAzpWJiIiIiDwehVRh6VK4fdvsoDZubO9qEs/NiJt0Xt6ZNcfWANCuQjvmvDKHHJly2LewJLJq1Sp69erFxYsXsVgsDBgwgNGjRyfYwkhEREREJKVTSBXmzTO/e3ub16SmBXsv7aX...
code_fim
hard
{ "lang": "python", "repo": "alanlujan91/DemARK", "path": "/notebooks/DiamondOLG.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> if date not in session_start_dict: return time elif last_time == None: return time else: hour_minute = time[0:5] last_hour_minute = last_time[0:5] if hour_minute < last_hour_minute: hour = int(time[0:2]) hour += 1 new...
code_fim
hard
{ "lang": "python", "repo": "emg/syllog", "path": "/backend/Django/logsyllogsite/logapp/views.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: emg/syllog path: /backend/Django/logsyllogsite/logapp/views.py %s' % mydict['term_M']) next_row.append('%s' % mydict['term_P']) next_row.append('%s' % mydict['correctness']) next_row.append('%s' % mydict['conclusion_truth_value']) ne...
code_fim
hard
{ "lang": "python", "repo": "emg/syllog", "path": "/backend/Django/logsyllogsite/logapp/views.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: emg/syllog path: /backend/Django/logsyllogsite/logapp/views.py answercount += 1 next_row = [] next_row.append(date) next_row.append('%d' % mydict['usernumber']) usernumber = mydict['usernumber'] next_row.append...
code_fim
hard
{ "lang": "python", "repo": "emg/syllog", "path": "/backend/Django/logsyllogsite/logapp/views.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: urutva/mbed-tools-ci-scripts path: /mbed_tools_ci_scripts/license_files.py # # Copyright (C) 2020 Arm Mbed. All rights reserved. # SPDX-License-Identifier: Apache-2.0 # """Apply copyright and licensing to all source files present in a project. This is to comply with OpenChain certification; http...
code_fim
hard
{ "lang": "python", "repo": "urutva/mbed-tools-ci-scripts", "path": "/mbed_tools_ci_scripts/license_files.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> return f"{current}" if current == start else f"{start}-{current}" def get_tool_config(template_file: Path) -> dict: """Gets the configuration for licenseheaders.""" copyright_dates = _determines_copyright_dates() return { "owner": configuration.get_value(ConfigurationVariable.ORG...
code_fim
hard
{ "lang": "python", "repo": "urutva/mbed-tools-ci-scripts", "path": "/mbed_tools_ci_scripts/license_files.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }