text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|> probVal = Decimal(float(probVal*100))
probVal = round(probVal,2)
ac = str(probVal)
if probVal> threshold:
cv2.putText(imgOriginal,str(catagory[i]),(50,70),cv2.FONT_HERSHEY_SIMPLEX,2,(0,0,255),2)
cv2.putText(imgOriginal,"acc = "+ac+'%',(30, 140), cv2.FONT_HERSHEY_COMPLEX, 1,... | code_fim | hard | {
"lang": "python",
"repo": "marci0903/Mechine-Learning-Projects",
"path": "/Image_classifier/Testing.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>API'}
with open('flaskbox.yml', 'w') as file:
yaml.dump(base_app, file, default_flow_style=False)<|fim_prefix|># repo: nik849/Flaskbox path: /tests/conftest.py
import yaml
def create_init_file():
"""Create In<|fim_middle|>it file"""
base_app = {'application': 'My restful | code_fim | easy | {
"lang": "python",
"repo": "nik849/Flaskbox",
"path": "/tests/conftest.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nik849/Flaskbox path: /tests/conftest.py
import yaml
def create_init_file():
"""Create Init file"""
base_app = {'application': 'My restful <|fim_suffix|> yaml.dump(base_app, file, default_flow_style=False)<|fim_middle|>API'}
with open('flaskbox.yml', 'w') as file:
| code_fim | easy | {
"lang": "python",
"repo": "nik849/Flaskbox",
"path": "/tests/conftest.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> @data.setter
def data(self, value):
self._tensor.data = value
def __repr__(self):
return f"{self.__class__.__name__}({self._tensor})"
def __bool__(self):
"""Override bool operator since encrypted tensors cannot evaluate"""
raise RuntimeError("Cannot evalua... | code_fim | hard | {
"lang": "python",
"repo": "facebookresearch/CrypTen",
"path": "/crypten/cryptensor.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: facebookresearch/CrypTen path: /crypten/cryptensor.py
rad_input is None:
if self.nelement() == 1:
grad_input = self.new(torch.ones_like(self.data))
else:
raise RuntimeError(
"grad c... | code_fim | hard | {
"lang": "python",
"repo": "facebookresearch/CrypTen",
"path": "/crypten/cryptensor.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: facebookresearch/CrypTen path: /crypten/cryptensor.py
# in initial backward call, identify all required nodes:
if top_node:
self._identify_required_grads()
# if undefined, set gradient input to one:
if grad_input is ... | code_fim | hard | {
"lang": "python",
"repo": "facebookresearch/CrypTen",
"path": "/crypten/cryptensor.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: DiyanKalaydzhiev23/OOP---Python path: /Polymorphism and Abstraction - Exercise/Groups.py
class Person:
def __init__(self, name, surname):
self.name = name
self.surname = surname
def __repr__(self):
return f"{self.name} {self.surname}"
def __add__(self, other... | code_fim | hard | {
"lang": "python",
"repo": "DiyanKalaydzhiev23/OOP---Python",
"path": "/Polymorphism and Abstraction - Exercise/Groups.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
p0 = Person('Aliko', 'Dangote')
p1 = Person('Bill', 'Gates')
p2 = Person('Warren', 'Buffet')
p3 = Person('Elon', 'Musk')
p4 = p2 + p3
first_group = Group('__VIP__', [p0, p1, p2])
second_group = Group('Special', [p3, p4])
third_group = first_group + second_group
print(len(first_group))
print(second_grou... | code_fim | hard | {
"lang": "python",
"repo": "DiyanKalaydzhiev23/OOP---Python",
"path": "/Polymorphism and Abstraction - Exercise/Groups.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> .. [2] Huber, Peter et al (1964)
Robust Estimation of a Location Parameter
https://projecteuclid.org/euclid.aoms/1177703732
"""
predictions, targets = align_targets(predictions, targets)
abs_diff = abs(targets - predictions)
ift = 0.5 * squared_error(targets, pred... | code_fim | hard | {
"lang": "python",
"repo": "Ram-Aditya/Healthcare-Data-Analytics",
"path": "/env/lib/python2.7/site-packages/lasagne/objectives.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> .. math:: L_i = \\frac{(p - t)^2}{2}, |p - t| \\le \\delta
L_i = \\delta (|p - t| - \\frac{\\delta}{2} ), |p - t| \\gt \\delta
Parameters
----------
predictions : Theano 2D tensor or 1D tensor
Prediction outputs of a neural network.
targets : Theano 2D tensor or 1D ... | code_fim | hard | {
"lang": "python",
"repo": "Ram-Aditya/Healthcare-Data-Analytics",
"path": "/env/lib/python2.7/site-packages/lasagne/objectives.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Ram-Aditya/Healthcare-Data-Analytics path: /env/lib/python2.7/site-packages/lasagne/objectives.py
:nosignatures:
aggregate
Note that these functions only serve to write more readable code, but are
completely optional. Essentially, any differentiable scalar Theano expression
can be used ... | code_fim | hard | {
"lang": "python",
"repo": "Ram-Aditya/Healthcare-Data-Analytics",
"path": "/env/lib/python2.7/site-packages/lasagne/objectives.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: fuvity/mc906project2 path: /graphics.py
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from matplotlib import cm
from matplotlib.ticker import LinearLocator, FormatStrFormatter
import numpy as np
from math import sqrt, ceil
def getChild(A, B):
if crossover_method == ... | code_fim | hard | {
"lang": "python",
"repo": "fuvity/mc906project2",
"path": "/graphics.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if itt == max_iterations-1:
ax = plt.figure()
plt.title('Última geração')
p = plt.imshow(Z, cmap=cm.viridis)
plt.colorbar(p)
childrenx = []
childreny = []
for child in children:
childrenx.append(child[0])
childreny.append(... | code_fim | hard | {
"lang": "python",
"repo": "fuvity/mc906project2",
"path": "/graphics.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: chor-nyan/trimap path: /example.py
# https://github.com/eamid/examples
import numpy as np
import matplotlib.pyplot as plt
from sklearn.datasets import fetch_openml
from utils import plot_results
import matplotlib.cm as cm
from sklearn.decomposition import PCA
from sklearn.manifold import TSNE
# ... | code_fim | hard | {
"lang": "python",
"repo": "chor-nyan/trimap",
"path": "/example.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>plt.scatter(yo_trimap[:, 0], yo_trimap[:, 1], s=0.1, c=cols[L, :])
# plt.scatter(yo_trimap[index,0], yo_trimap[index,1], s=80, c='red', marker='x')
plt.show()
# yo_pca = PCA(n_components = 2).fit_transform(Xo)
# plt.scatter(yo_pca[:,0], yo_pca[:,1], s=0.1, c=cols[L,:])
# plt.scatter(yo_pca[index,0], yo_... | code_fim | hard | {
"lang": "python",
"repo": "chor-nyan/trimap",
"path": "/example.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>scale = False
if scale:
flag1 = yo_trimap[:, 0] > -150
flag2 = yo_trimap[:, 1] < 130
flag = flag1 & flag2
plt.scatter(yo_trimap[flag,0], yo_trimap[flag,1], s=0.1, c=cols[L[flag],:])
plt.show()
# flag = [True] * Xo.shape[0]
# flag[index] = False
# plt.scatter(yo_trimap[flag,0], yo_trima... | code_fim | hard | {
"lang": "python",
"repo": "chor-nyan/trimap",
"path": "/example.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> host, _ = deploy.get_socket()
port = 50001 if not 'KUBE_OPENEO_API_PORT' in os.environ else os.environ['KUBE_OPENEO_API_PORT']
def on_started() -> None:
from openeo_driver.views import app
app.logger.setLevel('DEBUG')
server.run(title="OpenEO API",
descrip... | code_fim | hard | {
"lang": "python",
"repo": "bartjanssens92/openeo-geopyspark-driver",
"path": "/openeogeotrellis/deploy/kubernetes.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bartjanssens92/openeo-geopyspark-driver path: /openeogeotrellis/deploy/kubernetes.py
"""
Script to start a production server on Kubernetes. This script can serve as the mainApplicationFile for the SparkApplication custom resource of the spark-operator
"""
import logging
from logging.config impor... | code_fim | hard | {
"lang": "python",
"repo": "bartjanssens92/openeo-geopyspark-driver",
"path": "/openeogeotrellis/deploy/kubernetes.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|># Calculate one transitive-fraternal-augmentation-step and
# result a tuple (newgraph, transedges, fratedges)
# @memorized(['orig', 'step'])
def truncated_tf_augmentation(orig, g, trans, frat, col, nodes,
step, td, ldoFunc):
fratGraph = Graph()
newTrans = {}
for ... | code_fim | medium | {
"lang": "python",
"repo": "TheoryInPractice/CONCUSS",
"path": "/lib/coloring/basic/truncated_tf_augmentation.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: TheoryInPractice/CONCUSS path: /lib/coloring/basic/truncated_tf_augmentation.py
#!/usr/bin/python
#
# This file is part of CONCUSS, https://github.com/theoryinpractice/concuss/,
# and is Copyright (C) North Carolina State University, 2015. It is licensed
# under the three-clause BSD license; see ... | code_fim | hard | {
"lang": "python",
"repo": "TheoryInPractice/CONCUSS",
"path": "/lib/coloring/basic/truncated_tf_augmentation.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> indegs = []
for v in g:
#Flexible indegs[v] = g.in_degree(v)
if v < len(indegs):
indegs[v] = g.in_degree(v)
else:
indegs.extend([0 for x in range(len(indegs), v)])
indegs.insert( v, g.in_degree(v) )
fratDigraph = ldoFunc(fratGraph, ... | code_fim | hard | {
"lang": "python",
"repo": "TheoryInPractice/CONCUSS",
"path": "/lib/coloring/basic/truncated_tf_augmentation.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mr-sivamareedu/infraform path: /infraform/cli/list/parser.py
# Copyright 2019 Arie Bregman
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://w... | code_fim | medium | {
"lang": "python",
"repo": "mr-sivamareedu/infraform",
"path": "/infraform/cli/list/parser.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """The parser for sub command 'list'."""
list_parser = subparsers.add_parser("list")
list_parser.set_defaults(func=list_cli.main)
list_parser.add_argument('--scenarios', '-s',
dest="scenarios",
action='store_true',
... | code_fim | medium | {
"lang": "python",
"repo": "mr-sivamareedu/infraform",
"path": "/infraform/cli/list/parser.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>class YamlSerializer(Serializer[str]):
@classmethod
def serialize(cls, obj: Any, **opts: Any) -> str:
return yaml.safe_dump(obj, **opts) # type: ignore
class YamlDeserializer(Deserializer[str]):
@classmethod
def deserialize(cls, data: str, **opts: Any) -> Any:
return yam... | code_fim | medium | {
"lang": "python",
"repo": "yukinarit/pyserde",
"path": "/serde/yaml.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yukinarit/pyserde path: /serde/yaml.py
"""
Serialize and Deserialize in YAML format. This module depends on
[pyyaml](https://pypi.org/project/PyYAML/) package.
"""
from typing import Type, Any, overload, Optional
import yaml
from .compat import T
from .de import Deserializer, from_dict
from .se... | code_fim | hard | {
"lang": "python",
"repo": "yukinarit/pyserde",
"path": "/serde/yaml.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> ...
def from_yaml(c: Any, s: str, de: Type[Deserializer[str]] = YamlDeserializer, **opts: Any) -> Any:
"""
`c` is a class obejct and `s` is YAML string. If you supply keyword arguments other than `de`,
they will be passed in `yaml.safe_load` function.
If you want to use the other ya... | code_fim | hard | {
"lang": "python",
"repo": "yukinarit/pyserde",
"path": "/serde/yaml.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: starkbank/sdk-python path: /tests/utils/rule.py
from copy import deepcopy
from random import choice, randint
from starkbank import CorporateRule, MerchantCountry, CardMethod, MerchantCategory
example_rule = CorporateRule(
name="Example Rule",
interval="day",
amount=100000,
curre... | code_fim | medium | {
"lang": "python",
"repo": "starkbank/sdk-python",
"path": "/tests/utils/rule.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def generateExampleRuleJson(n=1):
rules = []
for _ in range(n):
example_rule.interval = choice(["day", "week", "month", "instant"])
example_rule.amount = randint(1000, 100000)
example_rule.currency_code = choice(["BRL", "USD"])
example_rule.countries = [MerchantCoun... | code_fim | medium | {
"lang": "python",
"repo": "starkbank/sdk-python",
"path": "/tests/utils/rule.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: PyreWatch/pyrefinder path: /tests/test_db.py
import datetime
from pyrefinder import db
def test_add_fighter():
DB = db.DatabaseManager()
topic = "dt/fighter/bob"
message = {"latitude": 100, "longitude": 100}
db.add_fighter(topic, message)
result = DB.query_db(
"se... | code_fim | hard | {
"lang": "python",
"repo": "PyreWatch/pyrefinder",
"path": "/tests/test_db.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> fighter_time_result = DB3.query_db(
"select last_time from fighter where id=? and last_time=?",
["sam", now])
DB3.modify_db("delete from fighter_data where client_id=?", ["sam"])
DB3.modify_db("delete from fighter where id=?", ["sam"])
del DB3
assert fighter_time_res... | code_fim | hard | {
"lang": "python",
"repo": "PyreWatch/pyrefinder",
"path": "/tests/test_db.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> assert fighter_time_result != (now, )
def test_update_of_last_status():
DB4 = db.DatabaseManager()
now = datetime.datetime.now()
topic = "dt/fighter/sam"
message = {"status": "NOFIRE", "latitude": 100, "longitude": 100}
db.add_fighter(topic, message)
message = {"status": "... | code_fim | hard | {
"lang": "python",
"repo": "PyreWatch/pyrefinder",
"path": "/tests/test_db.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dorucioclea/posthog path: /posthog/migrations/0220_backfill_primary_dashboards.py
import structlog
from django.db import connection, migrations
def backfill_primary_dashboards(apps, _):
logger = structlog.get_logger(__name__)
logger.info("starting 0220_set_primary_dashboard")
Team ... | code_fim | hard | {
"lang": "python",
"repo": "dorucioclea/posthog",
"path": "/posthog/migrations/0220_backfill_primary_dashboards.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># Because of the nature of this backfill, there's no way to reverse it without potentially destroying customer data
# However, we still need a reverse function, so that we can rollback other migrations
def reverse(apps, _):
pass
class Migration(migrations.Migration):
atomic = False
dependen... | code_fim | hard | {
"lang": "python",
"repo": "dorucioclea/posthog",
"path": "/posthog/migrations/0220_backfill_primary_dashboards.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: RekGRpth/auto-indexing-PostgreSQL path: /test/test1_0.py
import csv
import re
import sys
import subprocess
import psycopg2
import json
import math
import random
import time
# Open Connection to database
conn = psycopg2.connect(database = "test", user = "postgres", password = "", host = "localhos... | code_fim | hard | {
"lang": "python",
"repo": "RekGRpth/auto-indexing-PostgreSQL",
"path": "/test/test1_0.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> cur.execute(stmt21.format(random.randint(0,129)))
result = str(cur.fetchall())
cur.execute(stmt22.format(snames[random.randint(0,len(snames)-1)]))
result = str(cur.fetchall())
cur.execute(stmt3.format(deps[random.randint(0,len(deps)-1)] , random.randint(0,129)))
result = str(cur.fetchall())
conn... | code_fim | hard | {
"lang": "python",
"repo": "RekGRpth/auto-indexing-PostgreSQL",
"path": "/test/test1_0.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>with open('ReleaseStatus.xml') as infile:
soup = BeautifulSoup(infile, 'lxml')
synsets = soup.find_all('synset')
synsets = [synsets[i].attrs['wnid'] for i in range(len(synsets)) if int(synsets[i].attrs['numimages']) > 100]
extra_train = np.random.choice(synsets, 100)
extra_test = np.random.choice(s... | code_fim | hard | {
"lang": "python",
"repo": "JobQiu/PrototypicalNetwork",
"path": "/data/mini-imagenet/demo.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: JobQiu/PrototypicalNetwork path: /data/mini-imagenet/demo.py
import numpy as np
np.random.seed(42)
from bs4 import BeautifulSoup
with open('empty_dir') as f:
content = f.readlines()
# you may also want to remove whitespace characters like `\n` at the end of each line
content = [x.strip() fo... | code_fim | hard | {
"lang": "python",
"repo": "JobQiu/PrototypicalNetwork",
"path": "/data/mini-imagenet/demo.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: inventree/InvenTree path: /InvenTree/plugin/builtin/integration/test_core_notifications.py
"""Tests for core_notifications."""
from django.core import mail
from part.test_part import BaseNotificationIntegrationTest
from plugin import registry
from plugin.builtin.integration.core_notifications i... | code_fim | medium | {
"lang": "python",
"repo": "inventree/InvenTree",
"path": "/InvenTree/plugin/builtin/integration/test_core_notifications.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # enable plugin and set mail setting to true
plugin = registry.plugins.get('inventreecorenotificationsplugin')
plugin.set_setting('ENABLE_NOTIFICATION_EMAILS', True)
NotificationUserSetting.set_setting(
key='NOTIFICATION_METHOD_MAIL',
value=True,
... | code_fim | medium | {
"lang": "python",
"repo": "inventree/InvenTree",
"path": "/InvenTree/plugin/builtin/integration/test_core_notifications.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_email(self):
"""Ensure that the email notifications run."""
# No email should be send
self.assertEqual(len(mail.outbox), 0)
# enable plugin and set mail setting to true
plugin = registry.plugins.get('inventreecorenotificationsplugin')
plugin.se... | code_fim | medium | {
"lang": "python",
"repo": "inventree/InvenTree",
"path": "/InvenTree/plugin/builtin/integration/test_core_notifications.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # only add augmentation to first reader (not validation reader)
self.readers[0].add_preprocessing_layers(
normalisation_layers + augmentation_layers)
for reader in self.readers[1:]:
reader.add_preprocessing_layers(normalisation_layers)
def initialise_s... | code_fim | hard | {
"lang": "python",
"repo": "12SigmaTechnologies/NiftyNet-1",
"path": "/niftynet/application/gan_application.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: 12SigmaTechnologies/NiftyNet-1 path: /niftynet/application/gan_application.py
# -*- coding: utf-8 -*-
from __future__ import absolute_import, print_function
import tensorflow as tf
from niftynet.application.base_application import BaseApplication
from niftynet.engine.application_factory import ... | code_fim | hard | {
"lang": "python",
"repo": "12SigmaTechnologies/NiftyNet-1",
"path": "/niftynet/application/gan_application.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def initialise_sampler(self):
self.sampler = []
if self.is_training:
self.sampler.append([ResizeSampler(
reader=reader,
window_sizes=self.data_param,
batch_size=self.net_param.batch_size,
windows_per_image=1,
... | code_fim | hard | {
"lang": "python",
"repo": "12SigmaTechnologies/NiftyNet-1",
"path": "/niftynet/application/gan_application.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def retain( self, resource ):
if not hasattr( self, '__resources' ):
self.__resources = []
guard = ResRef( resource )
self.__resources.append( guard )
def release( self, resource ):
for i, guard in iter( self.__resources ):
if guard.data is resource:
self.__resources = self.__resource... | code_fim | hard | {
"lang": "python",
"repo": "pixpil/gii",
"path": "/lib/gii/core/res.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pixpil/gii path: /lib/gii/core/res.py
from abc import ABCMeta, abstractmethod
##----------------------------------------------------------------##
_resGuardDictCache = {}
_resGuardDict = {}
def registerResGuard( typeId, guard ):
_resGuardDict[ typeId ] = guard
def findResGuard( typeId ):
g = ... | code_fim | hard | {
"lang": "python",
"repo": "pixpil/gii",
"path": "/lib/gii/core/res.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> pass
##----------------------------------------------------------------##
class ResRef(object):
def __init__(self, data):
self.data = data
def __dealloc__( self ):
self.release( self.data )
def release( self, data ):
typeId = type( data )
guard = findResGuard( typeId )
if guard:
gua... | code_fim | hard | {
"lang": "python",
"repo": "pixpil/gii",
"path": "/lib/gii/core/res.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: marcomusy/vedo path: /examples/advanced/meshquality.py
"""Metrics of quality for
the cells of a triangular mesh
(zoom to see cell label values)"""
from vedo import dataurl, Mesh, show
from vedo.pyplot import histogram
mesh = Mesh(dataurl + "panther.stl").compute_normals().linewidth(0.1).flat()
... | code_fim | hard | {
"lang": "python",
"repo": "marcomusy/vedo",
"path": "/examples/advanced/meshquality.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># create numeric labels of active scalar on top of cells
labs = mesh.labels(on="cells", precision=3, scale=0.4, font="Quikhand", c="black")
cam = dict(
pos=(59.8, -191, 78.9),
focal_point=(27.9, -2.94, 3.33),
viewup=(-0.0170, 0.370, 0.929),
distance=205,
clipping_range=(87.8, 355),
)
... | code_fim | hard | {
"lang": "python",
"repo": "marcomusy/vedo",
"path": "/examples/advanced/meshquality.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>)
equipment_map = {"车锁":"lock","头盔":"helmet","手套":"glove","手机支架":"phoneHolder","水壶架":"kettleHolder","梁包":"bag","后座":"backseat","码表":"stopwatch","手电":"flashlight","尾灯":"backlight","指南针":"compass"}
if order[7]:
temp = order[7].split(',')
for i,equipment in enumerate(t... | code_fim | hard | {
"lang": "python",
"repo": "kinsney/sport",
"path": "/orderConvert.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kinsney/sport path: /orderConvert.py
import pymysql as pm
from django.contrib.auth.hashers import make_password
qike = pm.connect(host='localhost',user='root',passwd='root',db='qike',port=3306,charset='utf8')
sport = pm.connect(host='localhost',user='root',passwd='root',db='sport',port=3306,chars... | code_fim | hard | {
"lang": "python",
"repo": "kinsney/sport",
"path": "/orderConvert.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>odified,scoreRenter,scoreOwner,bike_id,renter_id)
print(sql_order)
sc.execute(sql_order)
print(id)
if order[20].strip():
commentId+=1
rentercontent = order[20]
sql_comment = "INSERT INTO order_comments VALUES({0},'{1}',{2},{3},'{4}')".for... | code_fim | hard | {
"lang": "python",
"repo": "kinsney/sport",
"path": "/orderConvert.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def ROT_Z(theta=0):
return qOp([[np.exp(-1j * theta/2.0), 0],
[0, np.exp(1j * theta/2.0)]])
# Two-qubit gates
SWAP = qOp([[1, 0, 0, 0],
[0, 0, 1, 0],
[0, 1, 0, 0],
[0, 0, 0, 1]])
CNOT = qOp([[1, 0, 0, 0],
[0, 1, 0, 0],
[0, ... | code_fim | hard | {
"lang": "python",
"repo": "jasonelhaderi/pypsqueak",
"path": "/pypsqueak/gates.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jasonelhaderi/pypsqueak path: /pypsqueak/gates.py
'''
Static gates
============
Pre-defined ``qOp`` objects are provided implementing the common static gates
``X``, ``Y``, ``Z``, ``I``, ``H``, ``S`` (phase), and ``T`` (pi/8).
Parametric gates
================
Common parametric gates (such as rot... | code_fim | medium | {
"lang": "python",
"repo": "jasonelhaderi/pypsqueak",
"path": "/pypsqueak/gates.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> client = DataAPIClient(get_api_endpoint_from_stage(arguments['<stage>']), arguments['<data_api_token>'])
user = arguments['<user>'] or getpass.getuser()
framework_slugs = arguments.get("<framework_slugs>") and arguments["<framework_slugs>"].split(",")
dry_run = bool(arguments.get("--dry-ru... | code_fim | hard | {
"lang": "python",
"repo": "alphagov-mirror/digitalmarketplace-scripts",
"path": "/scripts/oneoff/migrate-supplier-data-from-declarations.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: alphagov-mirror/digitalmarketplace-scripts path: /scripts/oneoff/migrate-supplier-data-from-declarations.py
#!/usr/bin/env python
"""Selectively migrate supplier information from a recent framework declaration to new fields on supplier itself
Usage:
scripts/oneoff/migrate-supplier-data-from-... | code_fim | hard | {
"lang": "python",
"repo": "alphagov-mirror/digitalmarketplace-scripts",
"path": "/scripts/oneoff/migrate-supplier-data-from-declarations.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ZhuoZhuoCrayon/AcousticKeyBoard-Web path: /apps/example/serializers.py
# -*- coding: utf-8 -*-
from django.utils.translation import ugettext_lazy as _
from rest_framework import serializers
from apps.example import constants, models
from apps.example.tests import mock_data
from djangocli.utils.d... | code_fim | hard | {
"lang": "python",
"repo": "ZhuoZhuoCrayon/AcousticKeyBoard-Web",
"path": "/apps/example/serializers.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class CommonValidateExceptionRequestSer(filter.PageSerializer):
class Meta:
swagger_schema_fields = {"example": mock_data.API_COMMON_VALIDATE_EXCEPTION.request_data}
class CommonValidateExceptionResponseSer(serializers.Serializer):
class Meta:
swagger_schema_fields = {"example":... | code_fim | hard | {
"lang": "python",
"repo": "ZhuoZhuoCrayon/AcousticKeyBoard-Web",
"path": "/apps/example/serializers.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: huaweicloud/huaweicloud-sdk-python-v3 path: /huaweicloud-sdk-cfw/huaweicloudsdkcfw/v1/model/flavor.py
# coding: utf-8
import six
from huaweicloudsdkcore.utils.http_utils import sanitize_for_serialization
class Flavor:
"""
Attributes:
openapi_types (dict): The key is attribute n... | code_fim | hard | {
"lang": "python",
"repo": "huaweicloud/huaweicloud-sdk-python-v3",
"path": "/huaweicloud-sdk-cfw/huaweicloudsdkcfw/v1/model/flavor.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> 日志存储
:return: The log_storage of this Flavor.
:rtype: int
"""
return self._log_storage
@log_storage.setter
def log_storage(self, log_storage):
"""Sets the log_storage of this Flavor.
日志存储
:param log_storage: The log_storage of thi... | code_fim | hard | {
"lang": "python",
"repo": "huaweicloud/huaweicloud-sdk-python-v3",
"path": "/huaweicloud-sdk-cfw/huaweicloudsdkcfw/v1/model/flavor.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> @log_storage.setter
def log_storage(self, log_storage):
"""Sets the log_storage of this Flavor.
日志存储
:param log_storage: The log_storage of this Flavor.
:type log_storage: int
"""
self._log_storage = log_storage
def to_dict(self):
"""R... | code_fim | hard | {
"lang": "python",
"repo": "huaweicloud/huaweicloud-sdk-python-v3",
"path": "/huaweicloud-sdk-cfw/huaweicloudsdkcfw/v1/model/flavor.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: daisycrego/mercury-telemetry path: /ag_data/tests/test_error_record.py
from django.test import TestCase
from ag_data.error_record import record
from ag_data.models import ErrorLog
class TestErrorRecord(TestCase):
<|fim_suffix|> foo = ErrorLog.objects.first()
self.assertEqual(foo... | code_fim | hard | {
"lang": "python",
"repo": "daisycrego/mercury-telemetry",
"path": "/ag_data/tests/test_error_record.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_save(self):
foo = ErrorLog.objects.first()
self.assertEqual(foo.error_code, self.test_data["error_code"])
self.assertEqual(foo.description, self.test_data["description"])
self.assertEqual(foo.raw_data, self.test_data["raw_data"])<|fim_prefix|># repo: daisycrego... | code_fim | hard | {
"lang": "python",
"repo": "daisycrego/mercury-telemetry",
"path": "/ag_data/tests/test_error_record.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def setUp(self):
record.save_error(
raw_data=self.test_data["raw_data"],
error_code=self.test_data["error_code"],
error_description=self.test_data["description"],
)
def test_save(self):
foo = ErrorLog.objects.first()
self.assertE... | code_fim | hard | {
"lang": "python",
"repo": "daisycrego/mercury-telemetry",
"path": "/ag_data/tests/test_error_record.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: GitHubChengPeng/jMetalPy path: /jmetal/util/ckecking.py
class NoneParameterException(Exception):
def __init__(self, message: str = ""):
self.error_message = message
class InvalidConditionException(Exception):
def __init__(self, message: str):
self.error_message = message... | code_fim | medium | {
"lang": "python",
"repo": "GitHubChengPeng/jMetalPy",
"path": "/jmetal/util/ckecking.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if value < 0.0 or value > 1.0:
raise InvalidProbabilityValueException(value)
@staticmethod
def value_is_in_range(value: float, lowest_value: float, highest_value: float):
if value < lowest_value or value > highest_value:
raise ValueOutOfRangeException(value... | code_fim | medium | {
"lang": "python",
"repo": "GitHubChengPeng/jMetalPy",
"path": "/jmetal/util/ckecking.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> @staticmethod
def probability_is_valid(value: float):
if value < 0.0 or value > 1.0:
raise InvalidProbabilityValueException(value)
@staticmethod
def value_is_in_range(value: float, lowest_value: float, highest_value: float):
if value < lowest_value or value > h... | code_fim | hard | {
"lang": "python",
"repo": "GitHubChengPeng/jMetalPy",
"path": "/jmetal/util/ckecking.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def test_sample_data_set():
"""
"""
(initial_state, rules) = parse_data(TEST_DATA)
pots = Pots(initial_state)
for gen in range(20):
actual = to_string(pots).strip(".")
expected = GENERATIONS[gen].strip(".")
assert actual == expected, f"Failed at gen {gen}"
... | code_fim | hard | {
"lang": "python",
"repo": "xpqz/aoc-18",
"path": "/tests/test_day12.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: xpqz/aoc-18 path: /tests/test_day12.py
from day12 import Pots, parse_data
TEST_DATA = [
"initial state: #..#.#..##......###...###",
"...## => #",
"..#.. => #",
".#... => #",
".#.#. => #",
".#.## => #",
".##.. => #",
".#### => #",
"#.#.# => #",
"#.### => #"... | code_fim | hard | {
"lang": "python",
"repo": "xpqz/aoc-18",
"path": "/tests/test_day12.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: amarsdd/R-NET-Behavioral-Navigation path: /plotter.py
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from numpy import genfromtxt
models = ["0", "1"]
ndim = ["50", "100"]
nlayers = ["1", "3"]
plt.rc('font', family='serif')
plt.rc('xtick', labelsize='medium')
plt.rc('y... | code_fim | hard | {
"lang": "python",
"repo": "amarsdd/R-NET-Behavioral-Navigation",
"path": "/plotter.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> name = csvpath+"model_"+models[i]+"_hdim_"+ndim[n_row]+"_nlayers_"+nlayers[n_col]+"_loss.csv"
loss = genfromtxt(name, delimiter=',')
vname = csvpath+"model_" + models[i] + "_hdim_" + ndim[n_row] + "_nlayers_" + nlayers[n_col]+"_val_loss.csv"
vloss = genfromtxt(vname, delim... | code_fim | hard | {
"lang": "python",
"repo": "amarsdd/R-NET-Behavioral-Navigation",
"path": "/plotter.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> context = {
'preload': {},
'now': arrow.now(),
'url': self.request.url,
}
self.render(self.context)<|fim_prefix|># repo: erichiggins/gae-mixy path: /handlers/main.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import httplib
import logging
import sys
import arrow
import... | code_fim | hard | {
"lang": "python",
"repo": "erichiggins/gae-mixy",
"path": "/handlers/main.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: erichiggins/gae-mixy path: /handlers/main.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import httplib
import logging
import sys
import arrow
import webapp2
from google.appengine.api import memcache
from google.appengine.ext import deferred
from google.appengine.ext import ndb
from google.a... | code_fim | hard | {
"lang": "python",
"repo": "erichiggins/gae-mixy",
"path": "/handlers/main.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>__all__ = [
'Home',
'Admin',
'WarmUp',
#'ExteriorImage',
]
class WarmUp(main.Health, base.BaseHandler):
"""Handler for warmup requests sent to /_ah/warmup."""
def get(self, *args, **kwargs):
"""Print out health status to try and keep the frontend instance up."""
status = htt... | code_fim | medium | {
"lang": "python",
"repo": "erichiggins/gae-mixy",
"path": "/handlers/main.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
import string
import os
import sys
from os.path import join
from org.batfish.util.util import make_sure_path_exists
from org.batfish.util.batfish_exception import BatfishException
# check if this line starts with @param
def isParamAttr(s):
return s.find("@param") == 0 and (len(s) == 6 or s[6] in st... | code_fim | hard | {
"lang": "python",
"repo": "Network-verification/batfish",
"path": "/projects/pybatfish/src/org/batfish/questions_to_html/questions_to_html.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Network-verification/batfish path: /projects/pybatfish/src/org/batfish/questions_to_html/questions_to_html.py
# Author: Todd Millstein
# Copyright 2016
# This script parses Javadoc comments in Batfish question files and produces a documentation page batfish-questions.html.
# If a command-line a... | code_fim | hard | {
"lang": "python",
"repo": "Network-verification/batfish",
"path": "/projects/pybatfish/src/org/batfish/questions_to_html/questions_to_html.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> train_files = [args.train_dir + 'train.bucket' + str(i) + '.txt' for i in range(args.num_buckets)]
if args.combinator == fcm.FORM_ONLY:
args.sample_context_words = 1
elif args.combinator == fcm.CONTEXT_ONLY:
args.nmin = 1
args.nmax = 1
if args.log_file is not Non... | code_fim | hard | {
"lang": "python",
"repo": "timoschick/form-context-model",
"path": "/fcm/train.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> batch_builder = InputProcessor(
word_embeddings_file=args.emb_file,
word_embeddings_format=args.emb_format,
train_files=train_files,
vocab_file=args.vocab,
vector_size=args.emb_dim,
nmin=args.nmin,
nmax=args.nmax,
ngram_dropout=args.dropo... | code_fim | hard | {
"lang": "python",
"repo": "timoschick/form-context-model",
"path": "/fcm/train.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: timoschick/form-context-model path: /fcm/train.py
import argparse
import io
import os
import datetime
import socket
import form_context_model as fcm
import my_log
from batch_builder import InputProcessor
logger = my_log.get_logger('root')
def main():
parser = argparse.ArgumentParser()
... | code_fim | hard | {
"lang": "python",
"repo": "timoschick/form-context-model",
"path": "/fcm/train.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: c1rdan/pytan path: /lib/taniumpy/__init__.py
'''A python package that handles the serialization/deserialization of XML SOAP
requests/responses<|fim_suffix|> import Session
# from .question_asker import QuestionAsker
from .object_types.base import BaseType
from .object_types.result_set import Resu... | code_fim | medium | {
"lang": "python",
"repo": "c1rdan/pytan",
"path": "/lib/taniumpy/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>pe
from .object_types.result_set import ResultSet
from .object_types.result_info import ResultInfo<|fim_prefix|># repo: c1rdan/pytan path: /lib/taniumpy/__init__.py
'''A python package that handles the serialization/deserialization of XML SOAP
requests/responses<|fim_middle|> from Tanium to/from python o... | code_fim | medium | {
"lang": "python",
"repo": "c1rdan/pytan",
"path": "/lib/taniumpy/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Damon8q/geonotebook path: /devops/filter_plugins/groups.py
def cidr_list_to_rules(values):
<|fim_suffix|> return {
'cidr_list_to_rules': cidr_list_to_rules
}<|fim_middle|> return [{'proto': 'all', 'cidr_ip': v} for v in values]
class FilterModule(object):
def fi... | code_fim | medium | {
"lang": "python",
"repo": "Damon8q/geonotebook",
"path": "/devops/filter_plugins/groups.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> return {
'cidr_list_to_rules': cidr_list_to_rules
}<|fim_prefix|># repo: Damon8q/geonotebook path: /devops/filter_plugins/groups.py
def cidr_list_to_rules(values):
return [{'proto': 'all', 'cidr_ip': v} for v in values]
<|fim_middle|>class FilterModule(object):
def fi... | code_fim | easy | {
"lang": "python",
"repo": "Damon8q/geonotebook",
"path": "/devops/filter_plugins/groups.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: slochower/openforcefield path: /openforcefield/tests/test_utils.py
#!/usr/bin/env python
# =============================================================================================
# MODULE DOCSTRING
# ==========================================================================================... | code_fim | hard | {
"lang": "python",
"repo": "slochower/openforcefield",
"path": "/openforcefield/tests/test_utils.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> pass
subclass_names = [cls.__name__ for cls in utils.all_subclasses(Foo)]
assert set(subclass_names) == set(
["FooSubclass1", "FooSubclass2", "FooSubSubclass"]
)
def test_temporary_cd():
"""Test temporary_cd() context manager"""
initial_dir = os.getcwd()
temporar... | code_fim | hard | {
"lang": "python",
"repo": "slochower/openforcefield",
"path": "/openforcefield/tests/test_utils.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: contrun/dotfiles path: /dot_config/sway/scripts/executable_i3session
#!/usr/bin/env python2
import os
import i3
import sys
import pickle
import subprocess
import logging
from time import sleep
from xdg.BaseDirectory import *
class Node:
def __init__(self, data, parent = None):
self.... | code_fim | hard | {
"lang": "python",
"repo": "contrun/dotfiles",
"path": "/dot_config/sway/scripts/executable_i3session",
"mode": "psm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|> pickle.dump(session, open(config_file, "wb"))
print "Session saved to " + config_file
elif sys.argv[1] == 'restore':
nag_bar = nag_bar_process()
print "Restoring..."
# load session from file
try:
session = pickle.load(open(config_file, "rb")... | code_fim | hard | {
"lang": "python",
"repo": "contrun/dotfiles",
"path": "/dot_config/sway/scripts/executable_i3session",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|> assert device.by_id == device.links[0]
assert device.major == 5
assert device.minor == 10<|fim_prefix|># repo: home-assistant/supervisor path: /tests/hardware/test_data.py
"""Test HardwareManager Module."""
from pathlib import Path
from supervisor.hardware.data import Device
# pylint: disab... | code_fim | hard | {
"lang": "python",
"repo": "home-assistant/supervisor",
"path": "/tests/hardware/test_data.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def test_device_property(coresys):
"""Test device cgroup policy."""
device = Device(
"ttyACM0",
Path("/dev/ttyACM0"),
Path("/sys/bus/usb/001"),
"tty",
None,
[Path("/dev/serial/by-id/fixed-device")],
{"MAJOR": "5", "MINOR": "10"},
[],... | code_fim | medium | {
"lang": "python",
"repo": "home-assistant/supervisor",
"path": "/tests/hardware/test_data.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: home-assistant/supervisor path: /tests/hardware/test_data.py
"""Test HardwareManager Module."""
from pathlib import Path
from supervisor.hardware.data import Device
# pylint: disable=protected-access
def test_device_property(coresys):
<|fim_suffix|> assert device.by_id == device.links[0]
... | code_fim | hard | {
"lang": "python",
"repo": "home-assistant/supervisor",
"path": "/tests/hardware/test_data.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> temp = line.split()
norm = 2 * int(temp[0])
inv = 2 * int(temp[1])
tag = str(norm) + ' ' + str(inv) + ' '
smallRel = float(temp[4])
smallErr = float(temp[5])
for inner_line in open(largeFile):
if inner_line.startswith(tag):
temp = inner_line.split()
largeR... | code_fim | hard | {
"lang": "python",
"repo": "daschaich/susy_scripts",
"path": "/analyze_blocked_loops.py",
"mode": "spm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_suffix|> p = float(norm + inv) / 4.0
rescaled = largeLoop * np.power(xi, p) # de(xi^p) = p (xi^{p - 1}) de(x)
err1 = largeErr / largeLoop
err2 = (p * np.power(xi, p - 1.0) * xi_err) / xi
err = rescaled * np.sqrt(err1**2 + err2**2)
# print "%d %d %.4g" % (int(norm) / 2, int(inv) / 2, float(... | code_fim | hard | {
"lang": "python",
"repo": "daschaich/susy_scripts",
"path": "/analyze_blocked_loops.py",
"mode": "spm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: daschaich/susy_scripts path: /analyze_blocked_loops.py
#!/usr/bin/python
import os
import sys
import glob
import numpy as np
# ------------------------------------------------------------------
# Determine xi from small-volume and blocked-large-volume Wilson loops,
# scaling mu \propto 1 / L
# T... | code_fim | hard | {
"lang": "python",
"repo": "daschaich/susy_scripts",
"path": "/analyze_blocked_loops.py",
"mode": "psm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Yelp/task_processing path: /tests/unit/plugins/mesos/constraints_test.py
import pytest
from pyrsistent import m
from task_processing.plugins.mesos.constraints import attributes_match_constraints
from task_processing.plugins.mesos.constraints import Constraint
@pytest.fixture
def fake_dict():
... | code_fim | hard | {
"lang": "python",
"repo": "Yelp/task_processing",
"path": "/tests/unit/plugins/mesos/constraints_test.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>def test_constraints_all_match(fake_dict):
assert attributes_match_constraints(
fake_dict,
[
Constraint(
attribute="region",
operator="==",
value="fake_region_text",
),
Constraint(
attri... | code_fim | hard | {
"lang": "python",
"repo": "Yelp/task_processing",
"path": "/tests/unit/plugins/mesos/constraints_test.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>def test_constraints_LIKE_match(fake_dict):
assert attributes_match_constraints(
fake_dict,
[
Constraint(
attribute="region",
operator="LIKE",
value="fak.*t..t",
),
],
)
assert attributes_match_cons... | code_fim | hard | {
"lang": "python",
"repo": "Yelp/task_processing",
"path": "/tests/unit/plugins/mesos/constraints_test.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: XrosLiang/SymmetryNet path: /tools/prcurve/pr.py
import numpy as np
import matplotlib.pyplot as plt
savedir = './shapenet/'
datadir = './shapenet/data/' # ycb rot
# file1 = datadir+'heavy-new_ins-oursdis=15.txt'
# file2 = datadir+'mid-new_ins-oursdis=15.txt'
# file3 = datadir+'light-new_ins-ours... | code_fim | hard | {
"lang": "python",
"repo": "XrosLiang/SymmetryNet",
"path": "/tools/prcurve/pr.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>plt.plot(recall1, precision1, linewidth = 2, color = 'tab:red', zorder = 10, label='holdout category')
plt.plot(recall2, precision2, linewidth = 2, color = 'tab:green', zorder = 10, label='holdout instance')
plt.plot(recall3, precision3, linewidth = 2, color = 'tab:blue', zorder = 10, label='holdout vi... | code_fim | hard | {
"lang": "python",
"repo": "XrosLiang/SymmetryNet",
"path": "/tools/prcurve/pr.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: atultherajput/doc2text path: /doc2text.py
import convert
import ocr
def getText():
docType=input("1. Aadhaar Card\n2. PAN Card\nEnter Document Type: ")
filename = input("File Name: ")
if docType == "1":
aadhaar=convert.convert(filename)
return {'file': filename, 'aadh... | code_fim | medium | {
"lang": "python",
"repo": "atultherajput/doc2text",
"path": "/doc2text.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>': aadhaar[2]}
elif docType=="2":
name, f_name, dob, pan = ocr.get_pan(filename)
return {'file': filename, 'pan': pan, 'name': name, 'f_name': f_name, 'dob':dob}
else:
print("Wrong Option! Try again.")
if __name__ == '__main__':
result = getText()
print(result)<|fi... | code_fim | medium | {
"lang": "python",
"repo": "atultherajput/doc2text",
"path": "/doc2text.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dmatiasr/django-demo path: /mysite/RentApp/migrations/0001_initial.py
# -*- coding: utf-8 -*-
# Generated by Django 1.11.2 on 2019-01-06 18:55
from __future__ import unicode_literals
from django.conf import settings
import django.contrib.gis.db.models.fields
from django.db import migrations, mod... | code_fim | hard | {
"lang": "python",
"repo": "dmatiasr/django-demo",
"path": "/mysite/RentApp/migrations/0001_initial.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
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