text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|> rows = []
for s, o, data in self.graph.edges(data=True):
row = self.build_export_row(data.copy())
row['subject'] = s
row['object'] = o
rows.append(row)
df = pd.DataFrame.from_dict(rows)
cols = df.columns.tolist()
cols ... | code_fim | hard | {
"lang": "python",
"repo": "justaddcoffee/kgx",
"path": "/kgx/pandas_transformer.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: justaddcoffee/kgx path: /kgx/pandas_transformer.py
import pandas as pd
import numpy as np
import logging
import os
import tarfile
from tempfile import TemporaryFile
from kgx.utils import make_path
from .transformer import Transformer
from typing import Dict, List, Optional
LIST_DELIMITER = '|... | code_fim | hard | {
"lang": "python",
"repo": "justaddcoffee/kgx",
"path": "/kgx/pandas_transformer.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> logging.info('Test Dice Coeff: {}'.format(test_score_dice))
print('Test Dice Coeff: {}'.format(test_score_dice))
writer.add_scalar(f'Phase_{phase}_Dice_{dropout_flag}/test', test_score_dice, epoch)
logging.info('Test IOU : {}'.format(test_score_iou))
print('Test IO... | code_fim | hard | {
"lang": "python",
"repo": "ConstantSun/active_learning_1",
"path": "/trainer/train.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ConstantSun/active_learning_1 path: /trainer/train.py
from tqdm import tqdm
import torch
import torch.nn as nn
from trainer.eval import eval_net
from pathlib import Path
import os
# trong mỗi phase, lưu lại best model để làm training cho phase tiếp theo.
def train(net: torch.nn, data_train, tra... | code_fim | hard | {
"lang": "python",
"repo": "ConstantSun/active_learning_1",
"path": "/trainer/train.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> # writer.add_scalar('Loss/train', loss.item(), global_step)
pbar.set_postfix(**{'loss (batch)': loss.item()})
optimizer.zero_grad()
loss.backward()
nn.utils.clip_grad_value_(net.parameters(), 0.1)
optimizer.ste... | code_fim | hard | {
"lang": "python",
"repo": "ConstantSun/active_learning_1",
"path": "/trainer/train.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: productiveware-xhacks/productiveware path: /py-app/launch.py
import sys
from PySide6 import QtWidgets
<|fim_suffix|>if __name__ == '__main__':
app = QtWidgets.QApplication()
main_window = MainWidget()
sys.exit(app.exec())<|fim_middle|>from productiveware.widgets.main_window import Ma... | code_fim | medium | {
"lang": "python",
"repo": "productiveware-xhacks/productiveware",
"path": "/py-app/launch.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>if __name__ == '__main__':
app = QtWidgets.QApplication()
main_window = MainWidget()
sys.exit(app.exec())<|fim_prefix|># repo: productiveware-xhacks/productiveware path: /py-app/launch.py
import sys
from PySide6 import QtWidgets
<|fim_middle|>from productiveware.widgets.main_window import Ma... | code_fim | medium | {
"lang": "python",
"repo": "productiveware-xhacks/productiveware",
"path": "/py-app/launch.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gcfyouthlive/youthlive_web path: /api/models.py
from django.db import models
from django.contrib.auth.models import AbstractUser
from django.utils.translation import ugettext_lazy as _
from django.conf import settings
import datetime, uuid
# Create your models here.
#Custom User
class User(Abst... | code_fim | hard | {
"lang": "python",
"repo": "gcfyouthlive/youthlive_web",
"path": "/api/models.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|># Events System
class Events(models.Model):
eventname = models.CharField(max_length=60, blank=False)
datetime = models.DateTimeField()
attendees = models.ManyToManyField('User',blank=True)
def __str__(self):
return self.eventname
# Reimbursment System
class Transaction(models.Mod... | code_fim | medium | {
"lang": "python",
"repo": "gcfyouthlive/youthlive_web",
"path": "/api/models.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jayhebe/w3resource_exercises path: /Basic - Part1/ex123.py
import sys
print("Float value informati<|fim_suffix|>aximum size of an integer: ", sys.maxsize)<|fim_middle|>on: ", sys.float_info)
print("Integer value information: ", sys.int_info)
print("M | code_fim | medium | {
"lang": "python",
"repo": "jayhebe/w3resource_exercises",
"path": "/Basic - Part1/ex123.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>aximum size of an integer: ", sys.maxsize)<|fim_prefix|># repo: jayhebe/w3resource_exercises path: /Basic - Part1/ex123.py
import sys
print("Float value information: ", sys.float_info)
print("Integer val<|fim_middle|>ue information: ", sys.int_info)
print("M | code_fim | easy | {
"lang": "python",
"repo": "jayhebe/w3resource_exercises",
"path": "/Basic - Part1/ex123.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: 131250208/IPGeolocation path: /Experiments/data_preprocessor.py
import requests
from Tools import requests_tools as rt, geoloc_commercial_db, web_mapping_services, network_measurer, geo_distance_calculator
import re
from bs4 import BeautifulSoup
import socket
import pyprind
import settings,... | code_fim | hard | {
"lang": "python",
"repo": "131250208/IPGeolocation",
"path": "/Experiments/data_preprocessor.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> try:
ip = socket.gethostbyname(name)
lm["ip"] = ip
# print(("getaddrinfo succeed, domain_name: %s, org: %s" % (name, lm["university_name"])))
except Exception as e:
count_fail += 1
# print("getaddrinfo failed, domain_name: %... | code_fim | hard | {
"lang": "python",
"repo": "131250208/IPGeolocation",
"path": "/Experiments/data_preprocessor.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Return list of HTML theme paths."""
cur_dir = path.abspath(path.dirname(path.dirname(__file__)))
return cur_dir
# See http://www.sphinx-doc.org/en/stable/theming.html#distribute-your-theme-as-a-python-package
def setup(app):
app.add_html_theme(
"pt_lightning_sphinx_theme", pat... | code_fim | medium | {
"lang": "python",
"repo": "FedML-AI/FedML",
"path": "/doc/theme/lightning_sphinx_theme/pt_lightning_sphinx_theme/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> dependencies = [
]
operations = [
migrations.CreateModel(
name='Book',
fields=[
('id', models.AutoField(primary_key=True, serialize=False)),
('title', models.CharField(max_length=64, unique=True)),
],
... | code_fim | hard | {
"lang": "python",
"repo": "bagaki/Python",
"path": "/Full Stack/day63Django/day63Mysite/MyApp/migrations/0001_initial.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bagaki/Python path: /Full Stack/day63Django/day63Mysite/MyApp/migrations/0001_initial.py
# Generated by Django 2.1 on 2018-09-04 08:02
from django.db import migrations, models
class Migration(migrations.Migration):
<|fim_suffix|> operations = [
migrations.CreateModel(
... | code_fim | hard | {
"lang": "python",
"repo": "bagaki/Python",
"path": "/Full Stack/day63Django/day63Mysite/MyApp/migrations/0001_initial.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> operations = [
migrations.CreateModel(
name='Book',
fields=[
('id', models.AutoField(primary_key=True, serialize=False)),
('title', models.CharField(max_length=64, unique=True)),
],
),
migrations.Create... | code_fim | hard | {
"lang": "python",
"repo": "bagaki/Python",
"path": "/Full Stack/day63Django/day63Mysite/MyApp/migrations/0001_initial.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>if __name__ == '__main__':
# Log http requests
logging.basicConfig(filename= cwd + '/logs/webapp.log', level=logging.DEBUG)
# Run the webserver
app.run(host='0.0.0.0', port=8080, debug=True)<|fim_prefix|># repo: paib/docker_apps path: /file_vault/app/vault_app.py
import os
from flask import Flas... | code_fim | medium | {
"lang": "python",
"repo": "paib/docker_apps",
"path": "/file_vault/app/vault_app.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: paib/docker_apps path: /file_vault/app/vault_app.py
import os
from flask import Flask, render_template
import logging
from logging.handlers import RotatingFileHandler
app = Flask(__name__)
app.debug = True
<|fim_suffix|>if __name__ == '__main__':
# Log http requests
logging.basicConfig(file... | code_fim | medium | {
"lang": "python",
"repo": "paib/docker_apps",
"path": "/file_vault/app/vault_app.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cartoonist/poodledo path: /poodledo/toodledodata.py
import six
import time
from datetime import datetime, timedelta
def _local_date(string):
dt = datetime.strptime(string[0:25], '%a, %d %b %Y %H:%M:%S')
return dt + timedelta(hours=6) + timedelta(seconds=_local_time_offset())
def _local_... | code_fim | hard | {
"lang": "python",
"repo": "cartoonist/poodledo",
"path": "/poodledo/toodledodata.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> _typemap = {
'server': {
'unixtime': int,
'date': _local_date,
'tokenexpires': float
},
'folder': {
'id': int,
'name': str,
'archived': _boolstr,
'pri... | code_fim | hard | {
"lang": "python",
"repo": "cartoonist/poodledo",
"path": "/poodledo/toodledodata.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: reefsource/core path: /test/integration_tests/python/test_rules.py
import json
import logging
log = logging.getLogger(__name__)
sh = logging.StreamHandler()
log.addHandler(sh)
<|fim_suffix|> r = as_user.get('/rules')
assert r.status_code == 403
r = as_user.post('/rules', json={'tes... | code_fim | easy | {
"lang": "python",
"repo": "reefsource/core",
"path": "/test/integration_tests/python/test_rules.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> r = as_user.post('/rules', json={'test': 'rule'})
assert r.status_code == 403<|fim_prefix|># repo: reefsource/core path: /test/integration_tests/python/test_rules.py
import json
import logging
log = logging.getLogger(__name__)
sh = logging.StreamHandler()
log.addHandler(sh)
def test_rule_acces... | code_fim | medium | {
"lang": "python",
"repo": "reefsource/core",
"path": "/test/integration_tests/python/test_rules.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # get_state(): Accepts an array of actions and performs the action on the Dino
# Returns the new state, the reward, and if the game ended
def get_state(self, actions):
score = self._game.get_score()
reward = 0.1 * score / 10
is_over = False
if actio... | code_fim | medium | {
"lang": "python",
"repo": "ajmadrid3/DinoRun_ML",
"path": "/Game_state.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ajmadrid3/DinoRun_ML path: /Game_state.py
# Used by the network to perform actions and getting new states
from Grab_screen import grab_screen
class Game_state:
def __init__(self, agent, game):
self._agent = agent
self._game = game
<|fim_suffix|> if self._agent.is_cras... | code_fim | hard | {
"lang": "python",
"repo": "ajmadrid3/DinoRun_ML",
"path": "/Game_state.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> self._agent = agent
self._game = game
# get_state(): Accepts an array of actions and performs the action on the Dino
# Returns the new state, the reward, and if the game ended
def get_state(self, actions):
score = self._game.get_score()
reward = 0.... | code_fim | medium | {
"lang": "python",
"repo": "ajmadrid3/DinoRun_ML",
"path": "/Game_state.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: smallstateinstitute/ssi-site path: /tools/mnis/__init__.py
from mnis.mnislib import \
getCurrentCommonsMembers, \
getCommonsMembersOn, \
getCommonsMembersBetwe<|fim_suffix|>getServiceDataForMember, \
getSummaryDataForMembers, \
saveSummaryDataForMembers, \
downloadMembers \<|fim_middle|>en,... | code_fim | hard | {
"lang": "python",
"repo": "smallstateinstitute/ssi-site",
"path": "/tools/mnis/__init__.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> getGenderForMember, \
getDateOfBirthForMember, \
getConstituencyForMember, \
getPartyForMember, \
getServiceDataForMember, \
getSummaryDataForMembers, \
saveSummaryDataForMembers, \
downloadMembers \<|fim_prefix|># repo: smallstateinstitute/ssi-site path: /tools/mnis/__init__.py
from mnis.mnislib... | code_fim | medium | {
"lang": "python",
"repo": "smallstateinstitute/ssi-site",
"path": "/tools/mnis/__init__.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>getServiceDataForMember, \
getSummaryDataForMembers, \
saveSummaryDataForMembers, \
downloadMembers \<|fim_prefix|># repo: smallstateinstitute/ssi-site path: /tools/mnis/__init__.py
from mnis.mnislib import \
getCurrentCommonsMembers, \
getCommonsMembersOn, \
getCommonsMembersBetween, \
getCommons... | code_fim | medium | {
"lang": "python",
"repo": "smallstateinstitute/ssi-site",
"path": "/tools/mnis/__init__.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> print("downloading " + entry + "...")
# Login to Kaggle and retrieve the data.
r = requests.post(r.url, data = kaggle_info)
# Writes the data to a local file one chunk at a time.
f = open(data_path + files[entry], 'w')
for chunk in r.iter_content(ch... | code_fim | hard | {
"lang": "python",
"repo": "jakewalker56/ml-lab",
"path": "/kaggle/dstl_satellite/download.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jakewalker56/ml-lab path: /kaggle/dstl_satellite/download.py
import requests
import zipfile
import os
data_url = 'https://www.kaggle.com/c/dstl-satellite-imagery-feature-detection/download/'
data_path = "/Volumes/external/data/"
files = {
"sample_submission.csv.zip" : "sample_submission.csv.... | code_fim | hard | {
"lang": "python",
"repo": "jakewalker56/ml-lab",
"path": "/kaggle/dstl_satellite/download.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> #delte the zip file
#print("deleting zip file...")
#os.remove(data_path + files[entry])
else:
print("already unzipped")
for folder in delete_folders:
print("removing " + folder + "...")
try:
os.rmdir(data_path + folder)
except (OSError):
pr... | code_fim | hard | {
"lang": "python",
"repo": "jakewalker56/ml-lab",
"path": "/kaggle/dstl_satellite/download.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: milvus-io/pymilvus path: /pymilvus/client/types.py
t as ok
:attribute message: str (optional) current status message
"""
SUCCESS = common_pb2.Success
UNEXPECTED_ERROR = common_pb2.UnexpectedError
CONNECT_FAILED = 2
PERMISSION_DENIED = 3
COLLECTION_NOT_EXISTS = 4
... | code_fim | hard | {
"lang": "python",
"repo": "milvus-io/pymilvus",
"path": "/pymilvus/client/types.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: milvus-io/pymilvus path: /pymilvus/client/types.py
HNSW = 11
ANNOY = 12
# alternative name
IVF_FLAT = IVFLAT
IVF_SQ8_H = IVF_SQ8H
def __repr__(self) -> str:
return f"<{self.__class__.__name__}: {self._name_}>"
def __str__(self) -> str:
return self._name... | code_fim | hard | {
"lang": "python",
"repo": "milvus-io/pymilvus",
"path": "/pymilvus/client/types.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __repr__(self) -> str:
s = "Replica groups:"
for g in self.groups:
s += f"\n- {g}"
return s
@property
def groups(self):
return self._groups
class BulkInsertState:
"""enum states of bulk insert task"""
ImportPending = 0
ImportFaile... | code_fim | hard | {
"lang": "python",
"repo": "milvus-io/pymilvus",
"path": "/pymilvus/client/types.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> for slot,v in t.items():
v=str(v)
for n,x in enumerate(sys.argv):
if x=="-" + slot[0] or x=="--" + slot:
if v == "false":
v = "true"
elif v == "true":
v = "false"
else:
... | code_fim | hard | {
"lang": "python",
"repo": "Mansimran7/ASE_Group12_Hws",
"path": "/src/Hw1-script/misc.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Mansimran7/ASE_Group12_Hws path: /src/Hw1-script/misc.py
from help import *
import math
import re
import sys
def settings(str):
return dict(re.findall("\n[\s]+[-][\S]+[\s]+[-][-]([\S]+)[^\n]+= ([\S]+)",str))
def coerce(s1):
"""
Converts value to Boolean, if value is not a boolea... | code_fim | hard | {
"lang": "python",
"repo": "Mansimran7/ASE_Group12_Hws",
"path": "/src/Hw1-script/misc.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> @property
def commandResult(self) -> global___SendCommandResult: ...
def __init__(self,
*,
sendError : typing.Optional[global___SendError.Enum.V] = ...,
handlerReturnStatus : typing.Optional[global___HandlerReturnStatus.Enum.V] = ...,
handlerReturnStatusDatas : ... | code_fim | hard | {
"lang": "python",
"repo": "cchampignon/pyatv",
"path": "/pyatv/protocols/mrp/protobuf/SendCommandResultMessage_pb2.pyi",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cchampignon/pyatv path: /pyatv/protocols/mrp/protobuf/SendCommandResultMessage_pb2.pyi
"""
@generated by mypy-protobuf. Do not edit manually!
isort:skip_file
"""
import builtins
import google.protobuf.descriptor
import google.protobuf.internal.containers
import google.protobuf.internal.enum_type... | code_fim | hard | {
"lang": "python",
"repo": "cchampignon/pyatv",
"path": "/pyatv/protocols/mrp/protobuf/SendCommandResultMessage_pb2.pyi",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mayi/start path: /WebStarter/main.py
# coding: utf-8
import sys
import web
import url
<|fim_suffix|>if __name__ == "__main__":
app = web.application(urls, globals())
app.run()<|fim_middle|>sys.path.append('./controllers')
urls = url.urls
| code_fim | easy | {
"lang": "python",
"repo": "mayi/start",
"path": "/WebStarter/main.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>if __name__ == "__main__":
app = web.application(urls, globals())
app.run()<|fim_prefix|># repo: mayi/start path: /WebStarter/main.py
# coding: utf-8
import sys
import web
import url
<|fim_middle|>sys.path.append('./controllers')
urls = url.urls
| code_fim | easy | {
"lang": "python",
"repo": "mayi/start",
"path": "/WebStarter/main.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: stevesan/dero path: /play.py
#!/usr/bin/env python3
"""
Given a WAD, it'll detect if it's for DOOM1 or 2 (based on map names) and
run GZDoom with the right iwad arg
"""
import argparse
import os
import wad
import subprocess
import dero_config
<|fim_suffix|> # Find all WADs and PK3's in this f... | code_fim | hard | {
"lang": "python",
"repo": "stevesan/dero",
"path": "/play.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Find all WADs and PK3's in this folder and load them.
wadpaths = []
for file in os.listdir(pwad_dir):
if file.lower().endswith('.wad') or file.lower().endswith('.pk3'):
wadpaths.append(os.path.join(pwad_dir, file))
if args.voxels:
wadpaths.append('/Users/stevenan/dooming/wads/chee... | code_fim | hard | {
"lang": "python",
"repo": "stevesan/dero",
"path": "/play.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: thisgirlangie/Tipsy path: /tipsy.py
"""
tipsy.py -- This is a Flask-based to-do list
"""
from flask import Flask, render_template, request
import model
<|fim_suffix|>@app.route("/add-task")
def add_task():
return render_template("add_task.html", user_id="user_id")
@app.route("/add-task-crea... | code_fim | medium | {
"lang": "python",
"repo": "thisgirlangie/Tipsy",
"path": "/tipsy.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> model.connect_to_db()
title = request.args.get("title")
user_id = request.args.get("user_id")
created_at = request.args.get("datestamp")
row = model.new_task(title, created_at, user_id)
html = render_template("added_task.html")
return html
if __name__ == "__main__":
app.ru... | code_fim | hard | {
"lang": "python",
"repo": "thisgirlangie/Tipsy",
"path": "/tipsy.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> """ A subscriber to the ``pyramid.events.BeforeRender`` events. Updates
the :term:`renderer globals` with values that are familiar to Pylons
users."""
request = event.get('request')
if request is None:
request = get_current_request()
globs = {
'url': route_url,
... | code_fim | medium | {
"lang": "python",
"repo": "SEL-Columbia/gateway",
"path": "/gateway/subscribers.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SEL-Columbia/gateway path: /gateway/subscribers.py
from pyramid.threadlocal import get_current_request
from pyramid.exceptions import ConfigurationError
from pyramid.security import authenticated_userid
from pyramid.url import route_url
from git import Repo
<|fim_suffix|> """ A subscriber to ... | code_fim | medium | {
"lang": "python",
"repo": "SEL-Columbia/gateway",
"path": "/gateway/subscribers.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> def visit_arguments(self, node):
if type(self.current_node) is not FunctionNode:
ast_error("Argument should be found in a function", node)
for arg in node.args:
var_type = ast_to_call_graph_type(self.stack, arg.annotation)
var_node = VariableNode(arg... | code_fim | hard | {
"lang": "python",
"repo": "prg-titech/Sanajeh",
"path": "/new-src/call_graph.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: prg-titech/Sanajeh path: /new-src/call_graph.py
return self.name + "*"
def to_field_type(self):
return self.name + "*"
def declared_functions(self):
return self.class_node.declared_functions
class RefTypeNode(TypeNode):
def __init__(self, type_node):
... | code_fim | hard | {
"lang": "python",
"repo": "prg-titech/Sanajeh",
"path": "/new-src/call_graph.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: prg-titech/Sanajeh path: /new-src/call_graph.py
names = set()
self.has_device_data = False
def get_ClassNode(self, class_name):
for class_node in self.declared_classes:
if class_node.name == class_name:
return class_node
return None
... | code_fim | hard | {
"lang": "python",
"repo": "prg-titech/Sanajeh",
"path": "/new-src/call_graph.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: PayamDiba/CycleGAN path: /generator.py
"""
@author: Payam Dibaeinia
"""
import torch
import torch.nn as nn
from collections import OrderedDict
from ResidualBlock import ResNetBlock
class generator(nn.Module):
"""
According to the cycleGAN paper, reflection padding and instance normaliz... | code_fim | hard | {
"lang": "python",
"repo": "PayamDiba/CycleGAN",
"path": "/generator.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> layers += [nn.ReflectionPad2d(3)]
layers += [nn.Conv2d(in_channels = nChanFirstConv, out_channels = out_channels, kernel_size = 7)]
layers += [nn.Tanh()]
self.all_layers_ = nn.Sequential(*layers)
def forward(self,x):
return self.all_layers_(x)<|fim_prefix|># r... | code_fim | hard | {
"lang": "python",
"repo": "PayamDiba/CycleGAN",
"path": "/generator.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: johnclarke96/6867-final-project path: /scripts/useful_constants.py
atomic_weights = {
'C': 12,
'O': 16,
'H': 1,
'N': 14,
'S': 32,
}
<|fim_suffix|>amino_acids_index = {
'A': 0,
'R': 1,
'N': 2,
'D': 3,
'Y': 4,
'C': 5,
'E': 6,
'Q': 7,
'V': 8,
'G': 9,
'H': 10,
'I': ... | code_fim | hard | {
"lang": "python",
"repo": "johnclarke96/6867-final-project",
"path": "/scripts/useful_constants.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>amino_acids_index = {
'A': 0,
'R': 1,
'N': 2,
'D': 3,
'Y': 4,
'C': 5,
'E': 6,
'Q': 7,
'V': 8,
'G': 9,
'H': 10,
'I': 11,
'L': 12,
'K': 13,
'M': 14,
'F': 15,
'P': 16,
'S': 17,
'T': 18,
'W': 19,
}
atom_codes = {
'H': 1,
'C': 2,
'O': 3,
'N': 4,
'S': 5,
}<|fim... | code_fim | hard | {
"lang": "python",
"repo": "johnclarke96/6867-final-project",
"path": "/scripts/useful_constants.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> context = super(HomeView, self).get_context_data(**kwargs)
context['featured_products'] = Product.objects \
.prefetch_related('photos').featured()
return context<|fim_prefix|># repo: ular/toko path: /toko/apps/pages/views.py
from django.views.generic import TemplateVie... | code_fim | medium | {
"lang": "python",
"repo": "ular/toko",
"path": "/toko/apps/pages/views.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ular/toko path: /toko/apps/pages/views.py
from django.views.generic import TemplateView
from toko.apps.products.models import Product
<|fim_suffix|> def get_context_data(self, **kwargs):
context = super(HomeView, self).get_context_data(**kwargs)
context['featured_products'] = ... | code_fim | medium | {
"lang": "python",
"repo": "ular/toko",
"path": "/toko/apps/pages/views.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rhinstaller/kickstart-tests path: /scripts/weekly-summary
hen using pycurl.NOSIGNAL - see
# the libcurl tutorial for more info.
try:
import signal
from signal import SIGPIPE, SIG_IGN
except ImportError:
pass
else:
signal.signal(SIGPIPE, SIG_IGN)
def get_artifacts(token, artifact... | code_fim | hard | {
"lang": "python",
"repo": "rhinstaller/kickstart-tests",
"path": "/scripts/weekly-summary",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> for n in flakes:
top_flakes[n] = top_flakes.get(n, 0) + 1
# Summary of tests per scenario
print("Weekly summary", file=buf)
print("==============", file=buf)
for scenario in sorted(all_days.keys()):
success = all_days[scenario]["success"]
missi... | code_fim | hard | {
"lang": "python",
"repo": "rhinstaller/kickstart-tests",
"path": "/scripts/weekly-summary",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rhinstaller/kickstart-tests path: /scripts/weekly-summary
int(f"Fetching {filename}")
ok = run_curl(token, a["archive_download_url"], filename)
if not ok:
continue
zipfiles.append((a["name"], datename, filename))
return zipfiles
def extract_logs(f):
... | code_fim | hard | {
"lang": "python",
"repo": "rhinstaller/kickstart-tests",
"path": "/scripts/weekly-summary",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> elif method=="XGBOOST":
print("Training model Xgboost ...")
output_path = "model_output/saved_xgboost_model.joblib"
xgboost = train_model_xgboost(X_train, y_train, output_path)
return xgboost
if __name__ == "__main__":
df = pd.read_csv("NSE-TATA.csv")
feature... | code_fim | hard | {
"lang": "python",
"repo": "minhtrihcmus/stock-price-prediction",
"path": "/train.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: minhtrihcmus/stock-price-prediction path: /train.py
# Base on stock_pred.py
from datetime import time
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.pylab import rcParams
from sklearn.model_selection import train_test_split
from sklearn.preprocessing imp... | code_fim | hard | {
"lang": "python",
"repo": "minhtrihcmus/stock-price-prediction",
"path": "/train.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Jonny-Riggs/Studio-Manager-API path: /studio_app/views/user_view.py
from django.contrib.auth.models import User
from rest_framework import viewsets
from django.core import serializers
from studio_app.models import *
from studio_app.serializers import *
<|fim_suffix|>
queryset = User.objects... | code_fim | easy | {
"lang": "python",
"repo": "Jonny-Riggs/Studio-Manager-API",
"path": "/studio_app/views/user_view.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>class UserViewSet(viewsets.ModelViewSet):
queryset = User.objects.all()
serializer_class = UserSerializer<|fim_prefix|># repo: Jonny-Riggs/Studio-Manager-API path: /studio_app/views/user_view.py
from django.contrib.auth.models import User
from rest_framework import viewsets
from django.core impo... | code_fim | medium | {
"lang": "python",
"repo": "Jonny-Riggs/Studio-Manager-API",
"path": "/studio_app/views/user_view.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> elif si+1 == ei: # If we searched the entire array and can't find the target
print(f"{target} could not be found")
searching = False
# Else continue searching
else:
if arr[mi] > target: # What we're searching for is a smaller number
... | code_fim | hard | {
"lang": "python",
"repo": "Victorli888/Python-Tutorial-Workbook",
"path": "/Algorithms/LinearBinarySearch.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Victorli888/Python-Tutorial-Workbook path: /Algorithms/LinearBinarySearch.py
# Linear Search - going through each and every element in a list.
# Binary Search - splitting the list in half and searching through the half before moving on
print("Example 1: Linear Search")
# find if 0 is present in... | code_fim | hard | {
"lang": "python",
"repo": "Victorli888/Python-Tutorial-Workbook",
"path": "/Algorithms/LinearBinarySearch.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> total = sum(nums)
if total % 4:
return False
nums.sort(reverse=True)
return self.dfs(nums, [0]*4, 0, total//4)
def dfs(self, nums: List[int], sums: List[int], pos: int, target: int) -> bool:
if pos == len(nums):
... | code_fim | medium | {
"lang": "python",
"repo": "eric496/leetcode.py",
"path": "/backtracking/473.matchsticks_to_square.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> if total % 4:
return False
nums.sort(reverse=True)
return self.dfs(nums, [0]*4, 0, total//4)
def dfs(self, nums: List[int], sums: List[int], pos: int, target: int) -> bool:
if pos == len(nums):
return True
... | code_fim | hard | {
"lang": "python",
"repo": "eric496/leetcode.py",
"path": "/backtracking/473.matchsticks_to_square.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: eric496/leetcode.py path: /backtracking/473.matchsticks_to_square.py
"""
Remember the story of Little Match Girl? By now, you know exactly what matchsticks the little match girl has, please find out a way you can make one square by using up all those matchsticks. You should not break any stick, b... | code_fim | hard | {
"lang": "python",
"repo": "eric496/leetcode.py",
"path": "/backtracking/473.matchsticks_to_square.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: JackNeus/lampPost path: /app/mod_api/views.py
from datetime import datetime
from flask import jsonify, make_response, request, render_template
from flask_httpauth import HTTPTokenAuth
from flask_login import login_required
import json
from app.mod_user.models import AuthorizationError, User, User... | code_fim | hard | {
"lang": "python",
"repo": "JackNeus/lampPost",
"path": "/app/mod_api/views.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if updated_event is None:
return gen_error_response(event_dne_text)
return gen_data_response(get_raw_event(updated_event))
@mod_api.route("/event/delete/<id>", methods=["DELETE"])
@auth.login_required
def delete_event(id):
try:
event = controller.get_event(id)
if event is None:
return gen_er... | code_fim | hard | {
"lang": "python",
"repo": "JackNeus/lampPost",
"path": "/app/mod_api/views.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Make sure creator matches authorized user.
try:
event = controller.get_event(id)
if event is None:
return gen_error_response(event_dne_text)
user = User.get_user_in_token(request)
if user is None:
return gen_error_response("Invalid authorization.")
if user.netid != event.creator:
r... | code_fim | hard | {
"lang": "python",
"repo": "JackNeus/lampPost",
"path": "/app/mod_api/views.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: claudiasofiaC/Facial_Recognition_Attendance path: /basics.py
import cv2
import numpy as np
import face_recognition
# Load and encode images
imgElon = face_recognition.load_image_file('ImageBasic/Elon Musk.jpg')
imgElon = cv2.cvtColor(imgElon, cv2.COLOR_BGR2RGB)
imgTest = face_recognition.load_im... | code_fim | hard | {
"lang": "python",
"repo": "claudiasofiaC/Facial_Recognition_Attendance",
"path": "/basics.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|># compare
results = face_recognition.compare_faces([encodeElon], encodeTest)
faceDis = face_recognition.face_distance([encodeElon], encodeTest)
print(results, faceDis)
cv2.putText(imgTest, f'{results} {round(faceDis[0], 2)}', (50, 50), cv2.FONT_HERSHEY_DUPLEX, 1, (0, 0, 255), 2)
cv2.imshow('Elon Muskrat'... | code_fim | hard | {
"lang": "python",
"repo": "claudiasofiaC/Facial_Recognition_Attendance",
"path": "/basics.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rcrowther/dancer path: /pdf/modern.py
#!/usr/bin/python3
from dancerPDF import DancerPDF
class Modern(DancerPDF):
def __init__(self):
DancerPDF.__init__(self)
self.titleFontFamily = "Helvetica-Bold"
self.titleFontSize = 32
self.sectionFontFamily = "Helvetica-Bold"
self... | code_fim | medium | {
"lang": "python",
"repo": "rcrowther/dancer",
"path": "/pdf/modern.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.c.setFont(self.creditsFontFamily, self.creditsFontSize)
#48
self.c.drawRightString(self.rightStockAbs, self.rawToAbsY(self._titleHeightRaw + self.creditsTopSkip), performers)
self._titleHeightRaw += self.creditsTopSkip + self.creditsFontSize
#68
self.c.drawRightString(self.rig... | code_fim | medium | {
"lang": "python",
"repo": "rcrowther/dancer",
"path": "/pdf/modern.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: vladimir-efimov/text-classification path: /term_stat_labeled.py
# Copyright (c) 2020, Vladimir Efimov
# All rights reserved.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import sys
import modules.text_processor_norm... | code_fim | hard | {
"lang": "python",
"repo": "vladimir-efimov/text-classification",
"path": "/term_stat_labeled.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> sorted_items = sorted(term_score.items(), reverse=True, key=lambda key_value: (key_value[1], key_value[0]))
topic_list = topics_words.keys()
header = ["Term", "Score", "Count", "Document count", "Labeled ratio"]
header.extend(topic_list)
print("\t".join(header))
for (term, score)... | code_fim | hard | {
"lang": "python",
"repo": "vladimir-efimov/text-classification",
"path": "/term_stat_labeled.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Elbadri0/mundiapolis-math path: /math/0x00-linear_algebra/7-gettin_cozy.py
#!/usr/bin/env python3
"""
concatenating of two matrices with specific axis
"""
<|fim_suffix|> """
enter a matrix
and Returns a list of concatenated matrices
"""
if (len(mat1[0]) == len(mat2[0])) and (... | code_fim | medium | {
"lang": "python",
"repo": "Elbadri0/mundiapolis-math",
"path": "/math/0x00-linear_algebra/7-gettin_cozy.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
enter a matrix
and Returns a list of concatenated matrices
"""
if (len(mat1[0]) == len(mat2[0])) and (axis == 0):
concat = [ele.copy() for ele in mat1]
concat += [ele.copy() for ele in mat2]
return concat
elif (len(mat1) == len(mat2)) and (axis == 1):
... | code_fim | medium | {
"lang": "python",
"repo": "Elbadri0/mundiapolis-math",
"path": "/math/0x00-linear_algebra/7-gettin_cozy.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sarauwu/summerimmersion path: /menu.py
import random
desserts = ["red velvet cake", "souffle", "ice cream", "macaron", "sundae", "flan", "tarimisu"]
desertaa = random.choice(desserts)
<|fim_suffix|>
#2 months on SL! Thank ya'll!
import random
first = ("Super", "Retarded", "Great", "Sexy",... | code_fim | medium | {
"lang": "python",
"repo": "sarauwu/summerimmersion",
"path": "/menu.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>#2 months on SL! Thank ya'll!
import random
first = ("Super", "Retarded", "Great", "Sexy", "Vegan", "Brave", "Shy", "Cool", "Poor", "Rich", "Fast", "Gummy", "Yummy", "Masked", "Unusual", "American", "Bisexual", "MLG", "Mlg", "lil", "Lil")
second = ("Coder", "Vegan", "Man", "Hacker", "Horse", "Bear", "G... | code_fim | medium | {
"lang": "python",
"repo": "sarauwu/summerimmersion",
"path": "/menu.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> n = 10000
exponential_samples = np.random.exponential(1,n)
plt.hist(exponential_samples)
plt.show()
uniform_samples = np.random.uniform(0,1,n)
plt.hist(uniform_samples)
plt.show()
transformed_exponential_samples = quantile_exponential_distribution(lambda_param=1, y=unifor... | code_fim | medium | {
"lang": "python",
"repo": "agdenadel/agdenadel.github.io",
"path": "/_posts/code/inverse-transform-sampling/inverse-transform-sampling.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ToHanwei/Bioinformatics path: /3-Which_DNA_Ptterns_Serve_as_molecular/task3/ProfileMostProbable.py
import sys
infile = sys.argv[1]
with open(infile) as inputf:
lines = inputf.readlines()
dna = lines[0].strip()
k = int(lines[1].strip())
matrix = []
for line in lines[2:]:
values = line.str... | code_fim | medium | {
"lang": "python",
"repo": "ToHanwei/Bioinformatics",
"path": "/3-Which_DNA_Ptterns_Serve_as_molecular/task3/ProfileMostProbable.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>mostPr = float('-inf')
mostKmer = ''
for i in range(len(dna)-k):
kmer = dna[i:i+k]
Pr = 1
for jj, w in enumerate(kmer):
ii = trans[w]
Pr *= matrix[ii][jj]
if Pr > mostPr:
mostPr = Pr
mostKmer = kmer
print(mostKmer)<|fim_prefix|># repo: ToHanwei/Bioinformatics path: /3-Which_DNA_Ptterns_Serve... | code_fim | medium | {
"lang": "python",
"repo": "ToHanwei/Bioinformatics",
"path": "/3-Which_DNA_Ptterns_Serve_as_molecular/task3/ProfileMostProbable.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> transformed_data = pca.transform(X)
print transformed_data
for ii,jj in zip(transformed_data,X):
print (first_pc[0]*ii[0],first_pc[1]*ii[0])
plt.scatter(first_pc[0]*ii[0],first_pc[1]*ii[0],color='r') # 第一主成分上映射的点 (主成分与需要映射的点的点积)
plt.scatter(second_pc[0]*ii[1],second_p... | code_fim | hard | {
"lang": "python",
"repo": "lj72808up/Mechine_Learning",
"path": "/PCA/TestPCA.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lj72808up/Mechine_Learning path: /PCA/TestPCA.py
# encoding:utf-8
import matplotlib.pyplot as plt
import numpy as np
from sklearn.decomposition import PCA
def doPCA(data):
<|fim_suffix|> transformed_data = pca.transform(X)
print transformed_data
for ii,jj in zip(transformed_data,X):
... | code_fim | hard | {
"lang": "python",
"repo": "lj72808up/Mechine_Learning",
"path": "/PCA/TestPCA.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>def write_meat(input, output):
with open(input, 'r', encoding='utf-8') as f:
for line in f:
if line[0] == '>':
line = '//' + line
output.write('\t' + line)
def write_opener(file):
opener = '"lang"\n{\n\t"Language"\t"English"\n\t"Tokens"\n\t{\n'
... | code_fim | hard | {
"lang": "python",
"repo": "operation-waifu-omelette/pathfinders",
"path": "/game/dota_addons/pathfinder/scripts/compile_localization.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: operation-waifu-omelette/pathfinders path: /game/dota_addons/pathfinder/scripts/compile_localization.py
import glob
def doTheThing(lang):
path = 'D:\\SteamLibrary\\steamapps\\common\\dota 2 beta\\game\\dota_addons\\pathfinder\\pf_localizations\\' + lang
output = open(
'D:\\Ste... | code_fim | hard | {
"lang": "python",
"repo": "operation-waifu-omelette/pathfinders",
"path": "/game/dota_addons/pathfinder/scripts/compile_localization.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> # enable primary network and wpa2 and disable wpa
network_page = NetworkPage(self.firefox)
network_page.enable(network_page.get_primary_network())
network_page.enable(network_page.get_wpa2())
network_page.disable(network_page.get_wpa())
network_page.apply_c... | code_fim | hard | {
"lang": "python",
"repo": "JulioMagnani/autobot-files",
"path": "/autobot/autobot/tests/wifi24/test_wpa2_to_wpa.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Preview the resulting DataFrame
dumping_df = dumping_df[
['service_request_id', 'original_lang', 'translated_desc']]
dumping_df.head()
######################################################################<|fim_prefix|># repo: patsess/aws-practice path: /awspractice/example_cod... | code_fim | hard | {
"lang": "python",
"repo": "patsess/aws-practice",
"path": "/awspractice/example_code_translate.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> ######################################################################
translated_text = translate.translate_text(
Text='Hello, how are you?',
SourceLanguageCode='auto', # note: should conclude English ('en')
TargetLanguageCode='es')['TranslatedText']
################... | code_fim | hard | {
"lang": "python",
"repo": "patsess/aws-practice",
"path": "/awspractice/example_code_translate.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: patsess/aws-practice path: /awspractice/example_code_translate.py
import boto3
"""
Note: code is for reference only (taken from an online course)
"""
if __name__ == '__main__':
# Generate the boto3 client for interacting with translate (for
# translation of text into another language)... | code_fim | hard | {
"lang": "python",
"repo": "patsess/aws-practice",
"path": "/awspractice/example_code_translate.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>if __name__ == '__main__':
logging.basicConfig(format='[%(filename)s:%(lineno)d] %(message)s', level=logging.DEBUG)
main()<|fim_prefix|># repo: FredWe/touch_project path: /data/open_image_by_uttid.py
import io_helper
import logging
import sys
import subprocess
import os
<|fim_middle|>IMAGEDIR = ... | code_fim | hard | {
"lang": "python",
"repo": "FredWe/touch_project",
"path": "/data/open_image_by_uttid.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: FredWe/touch_project path: /data/open_image_by_uttid.py
import io_helper
import logging
import sys
import subprocess
import os
<|fim_suffix|>if __name__ == '__main__':
logging.basicConfig(format='[%(filename)s:%(lineno)d] %(message)s', level=logging.DEBUG)
main()<|fim_middle|>IMAGEDIR = ... | code_fim | hard | {
"lang": "python",
"repo": "FredWe/touch_project",
"path": "/data/open_image_by_uttid.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> utt2recpath = io_helper.parse_dictfile(SCPPATH)
recpath = utt2recpath[UTTID]
imagename = io_helper.path2uttid(recpath)
imagepath = os.path.join(IMAGEDIR, '%s.png' % imagename)
subprocess.run('eog %s' % imagepath, shell=True)
if __name__ == '__main__':
logging.basicConfig(format='[... | code_fim | medium | {
"lang": "python",
"repo": "FredWe/touch_project",
"path": "/data/open_image_by_uttid.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: JeeVeeVee/SnackBar path: /python_parts/database_setup/database.py
import sqlite3
conn = sqlite3.connect("SnackBar.db")
def initiate_leiding_table(conn):
cursor = conn.cursor()
cursor.execute("""CREATE TABLE leiding (
first text,
last text,
schuld fl... | code_fim | hard | {
"lang": "python",
"repo": "JeeVeeVee/SnackBar",
"path": "/python_parts/database_setup/database.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> cursor = connection.cursor()
statement = "INSERT INTO leiding VALUES ('{}', '{}', {})".format(leider[0], leider[1], leider[2])
cursor.execute(statement)
connection.commit()
def fill_leiding_table():
file = open("src/python_parts/database_setup/leiding.csv", "r")
for line in file:
... | code_fim | hard | {
"lang": "python",
"repo": "JeeVeeVee/SnackBar",
"path": "/python_parts/database_setup/database.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ckt22/coach-ai path: /backend/main.py
from flask import Flask, request, jsonify
import tensorflow as tf
app = Flask(__name__)
available_fps = [3, 4, 5]
models = {fps: tf.keras.models.load_model(f'model/fps_{fps}') for fps in available_fps}
class_labels = ['push-up-arms-not-bent-enough', 'push-u... | code_fim | hard | {
"lang": "python",
"repo": "ckt22/coach-ai",
"path": "/backend/main.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> return 'Exercise classifier running'
@app.route('/classify', methods=['POST'])
def classify():
data = request.json
timeseries = tf.convert_to_tensor(data['timeseries'])
fps = data['fps']
model = models[fps]
probabilities = model.predict(timeseries)
print(probabilities)
ind... | code_fim | medium | {
"lang": "python",
"repo": "ckt22/coach-ai",
"path": "/backend/main.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>if __name__ == '__main__':
# This is used when running locally only.
app.run(host='0.0.0.0', port=8080, debug=True)<|fim_prefix|># repo: ckt22/coach-ai path: /backend/main.py
from flask import Flask, request, jsonify
import tensorflow as tf
app = Flask(__name__)
available_fps = [3, 4, 5]
models... | code_fim | hard | {
"lang": "python",
"repo": "ckt22/coach-ai",
"path": "/backend/main.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
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