text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_prefix|># repo: libinjungle/LeetCode_Python path: /String/17.py
class solution(object):
'''
Given a digit string, return all possible letter combinations that the number could represent.
'''
def letterCombinations(self, digits):
'''
each element in the returned list represents the input digits.
... | code_fim | medium | {
"lang": "python",
"repo": "libinjungle/LeetCode_Python",
"path": "/String/17.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>if __name__ == '__main__':
sol = solution()
digits = '234'
print sol.letterCombinations(digits)<|fim_prefix|># repo: libinjungle/LeetCode_Python path: /String/17.py
class solution(object):
'''
Given a digit string, return all possible letter combinations that the number could represent.
'''
... | code_fim | hard | {
"lang": "python",
"repo": "libinjungle/LeetCode_Python",
"path": "/String/17.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Subhash8969/bobby path: /classes.py
'''class Computer:
def _init_(self,cpu,ram):
self.cpu=cpu
self.ram=ram
def config(self,cpu,ram):
print("config is", cpu, ram)
<|fim_suffix|>
b = Bankaccount("subbu")
print(b.name)
b.deposit()
b.withdra... | code_fim | hard | {
"lang": "python",
"repo": "Subhash8969/bobby",
"path": "/classes.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
b = Bankaccount("subbu")
print(b.name)
b.deposit()
b.withdraw()
b.balance()
print("Thankyou sir/madam,Have a nice day:")
#********************************************************
#class vendingmachine:<|fim_prefix|># repo: Subhash8969/bobby path: /classes.py
'''class Computer:
def _init_(se... | code_fim | hard | {
"lang": "python",
"repo": "Subhash8969/bobby",
"path": "/classes.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
data.nNodes = ask_number("Number of nodes ?")
data.nColors = ask_number("Number of colors ?")
nEdges = ask_number("Number of edges ?")
data.edges = [random_edge() for _ in range(nEdges)]
Compilation.string_data = "-" + "-".join(str(v) for v in (data.nNodes, data.nColors, nEdges))<|fim_prefix|># repo: xc... | code_fim | medium | {
"lang": "python",
"repo": "xcsp3team/pycsp3",
"path": "/problems/data/parsers/Coloring_Random.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>data.nNodes = ask_number("Number of nodes ?")
data.nColors = ask_number("Number of colors ?")
nEdges = ask_number("Number of edges ?")
data.edges = [random_edge() for _ in range(nEdges)]
Compilation.string_data = "-" + "-".join(str(v) for v in (data.nNodes, data.nColors, nEdges))<|fim_prefix|># repo: xcs... | code_fim | medium | {
"lang": "python",
"repo": "xcsp3team/pycsp3",
"path": "/problems/data/parsers/Coloring_Random.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: xcsp3team/pycsp3 path: /problems/data/parsers/Coloring_Random.py
from pycsp3.problems.data.parsing import *
from pycsp3.compiler import Compilation
import random
def random_edge():
x, y = random.randint(0, data.nNodes - 1), random.randint(0, data.nNodes - 1)
return (x, y) if x != y else... | code_fim | medium | {
"lang": "python",
"repo": "xcsp3team/pycsp3",
"path": "/problems/data/parsers/Coloring_Random.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> uploadedImage = models.FileField(upload_to=settings.MEDIA_ROOT)<|fim_prefix|># repo: GustavoMonardez/python-django-cd-file-upload path: /apps/fileupload_app/models.py
from django.db import models
from django.conf import settings
<|fim_middle|>class ModelWithFileField(models.Model):
| code_fim | easy | {
"lang": "python",
"repo": "GustavoMonardez/python-django-cd-file-upload",
"path": "/apps/fileupload_app/models.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: GustavoMonardez/python-django-cd-file-upload path: /apps/fileupload_app/models.py
from django.db import models
from django.conf import settings
<|fim_suffix|> uploadedImage = models.FileField(upload_to=settings.MEDIA_ROOT)<|fim_middle|>class ModelWithFileField(models.Model):
| code_fim | easy | {
"lang": "python",
"repo": "GustavoMonardez/python-django-cd-file-upload",
"path": "/apps/fileupload_app/models.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Pharce/jax-suite path: /chex/intro-chex.py
import chex
import jax
import jax.numpy as jnp
from chex import assert_shape, assert_rank, assert_type, assert_equal_shape, assert_tree_all_close, assert_tree_all_finite, assert_numerical_grads, assert_devices_available, assert_tpu_available
from absl.te... | code_fim | hard | {
"lang": "python",
"repo": "Pharce/jax-suite",
"path": "/chex/intro-chex.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def fn_sub(x, y):
return x - y
# can be used with jax.pmap
fn_sub_pmapped = jax.pmap(chex.assert_max_retraces(fn_sub), n = 10)
### Test Variants with and without jax
def fn(x, y):
return x + y
class ExampleTest(chex.TestCase):
@chex.variants(with_jit=True, without_jit=True)... | code_fim | hard | {
"lang": "python",
"repo": "Pharce/jax-suite",
"path": "/chex/intro-chex.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> z = fn_sum_jitted(jnp.zeros(3), jnp.zeros(3))
t = fn_sum_jitted(jnp.zeros(6,7), jnp.zeros(6, 7)) # assertion error
def fn_sub(x, y):
return x - y
# can be used with jax.pmap
fn_sub_pmapped = jax.pmap(chex.assert_max_retraces(fn_sub), n = 10)
### Test Variants with and withou... | code_fim | hard | {
"lang": "python",
"repo": "Pharce/jax-suite",
"path": "/chex/intro-chex.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> sitelist = []
dburl = "http://chien.neuro.utah.edu/tol2kitwiki/index.php/Att_site_sequences"
http = urllib2.urlopen(dburl).read()
src = re.findall(r'gt;.*?([\w\d]+).*?([A-Z]{3,}.*?)[&<]', http,flags=re.DOTALL)
for n in range (0,len(src),1):
if '_' in... | code_fim | hard | {
"lang": "python",
"repo": "hashemd/Advanced-Virtual-Digest",
"path": "/libs/db/builder.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: hashemd/Advanced-Virtual-Digest path: /libs/db/builder.py
from bs4 import BeautifulSoup
import urllib2
import sys
import re
import os
sys.path.insert(0,'libs')
from google.appengine.ext import ndb, deferred
class VectorDatabase():
def __init__(self, database):
self.database = databa... | code_fim | hard | {
"lang": "python",
"repo": "hashemd/Advanced-Virtual-Digest",
"path": "/libs/db/builder.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def db_check(self):
test_enz = self.database.query(self.database.name=='EcoRV').get()
if test_enz is None:
deferred.defer(self.dl_enzymes, _target='builder')
def dl_enzymes(self):
enzlist = []
dburl = "http://www.addgene.org/mol_bio_reference/rest... | code_fim | hard | {
"lang": "python",
"repo": "hashemd/Advanced-Virtual-Digest",
"path": "/libs/db/builder.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # add handlers to logger
logger.addHandler(ch)
return logger<|fim_prefix|># repo: JohnSnowLabs/spark-nlp-workshop path: /tutorials/academic/LLMs_in_Healthcare/benchmarks/workbench/modules/log_module.py
import logging
def setup_logger(logger_name, level=logging.INFO):
# create logger obj... | code_fim | medium | {
"lang": "python",
"repo": "JohnSnowLabs/spark-nlp-workshop",
"path": "/tutorials/academic/LLMs_in_Healthcare/benchmarks/workbench/modules/log_module.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # create formatter
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
# add formatter to handlers
ch.setFormatter(formatter)
# add handlers to logger
logger.addHandler(ch)
return logger<|fim_prefix|># repo: JohnSnowLabs/spark-nlp-workshop ... | code_fim | medium | {
"lang": "python",
"repo": "JohnSnowLabs/spark-nlp-workshop",
"path": "/tutorials/academic/LLMs_in_Healthcare/benchmarks/workbench/modules/log_module.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: JohnSnowLabs/spark-nlp-workshop path: /tutorials/academic/LLMs_in_Healthcare/benchmarks/workbench/modules/log_module.py
import logging
def setup_logger(logger_name, level=logging.INFO):
<|fim_suffix|> # create formatter
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s... | code_fim | hard | {
"lang": "python",
"repo": "JohnSnowLabs/spark-nlp-workshop",
"path": "/tutorials/academic/LLMs_in_Healthcare/benchmarks/workbench/modules/log_module.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jkootsher/LunarMission path: /lib/gnc/control/frames.py
import numpy
from lib.tools.conversions import unit_vector
class Frames(object):
''' Local Navigation Frames '''
def inertial_to_lvlh(self, state_vector=None):
''' A genertic inertial frame to the LVLH (Hill) frame '''
... | code_fim | hard | {
"lang": "python",
"repo": "jkootsher/LunarMission",
"path": "/lib/gnc/control/frames.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> def lvlh_to_inertial(self, state_vector=None):
''' LVLH (Hill) frame to a generic inertial frame '''
BYI2LVH = self.lvlh_to_inertial(state_vector)
return BYI2LVH.T<|fim_prefix|># repo: jkootsher/LunarMission path: /lib/gnc/control/frames.py
import numpy
from lib.tools.convers... | code_fim | hard | {
"lang": "python",
"repo": "jkootsher/LunarMission",
"path": "/lib/gnc/control/frames.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> BYI2LVH = numpy.zeros((3,3))
BYI2LVH[2,:] = unit_vector(r_vector.T)
BYI2LVH[1,:] = unit_vector(w_vector.T)
BYI2LVH[0,:] = numpy.cross(BYI2LVH[2,:], BYI2LVH[0,:])
return BYI2LVH
def lvlh_to_inertial(self, state_vector=None):
''' LVLH (Hill) frame to a ge... | code_fim | hard | {
"lang": "python",
"repo": "jkootsher/LunarMission",
"path": "/lib/gnc/control/frames.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def main():
start_sec = timeTransform(opt.starttime)
end_sec = timeTransform(opt.endtime)
if start_sec > end_sec:
print('出错:开始时间大于结束时间')
return
file_name = os.path.basename(opt.path)
name, ext = file_name.split('.')
print("开始剪辑：{}-{}，共{}秒".format(opt.starttime,opt.endtime,end_sec-start... | code_fim | hard | {
"lang": "python",
"repo": "kevincao91/Tools",
"path": "/clip_video.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kevincao91/Tools path: /clip_video.py
from moviepy.editor import *
import argparse
import datetime
import os
parser = argparse.ArgumentParser(description='Clip video')
parser.add_argument('--starttime',type=str,default='00:00:00')
parser.add_argument('--endtime',type=str,default='00... | code_fim | hard | {
"lang": "python",
"repo": "kevincao91/Tools",
"path": "/clip_video.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if not os.path.exists(out_full) or force:
print("Loading {}".format(out_full))
era = proc.GrbData(grb_file=f, site="gold_coast")
print("Formatting {}".format(out_full))
era.format()
print("Saving {}".format(out_full))
era.create_df()
era.df.to_cs... | code_fim | medium | {
"lang": "python",
"repo": "robjameswall/global_metocean_data",
"path": "/proc_gc_gwes.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: robjameswall/global_metocean_data path: /proc_gc_gwes.py
import grb_processing as proc
import reanalysis as re
import os
site = "gold_coast"
fn = re.get_all_filenames(directory="data")
<|fim_suffix|> if not os.path.exists(out_full) or force:
print("Loading {}".format(out_full))
... | code_fim | hard | {
"lang": "python",
"repo": "robjameswall/global_metocean_data",
"path": "/proc_gc_gwes.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> form = SubscribeForm(request.POST)
data = {
'success': False,
}
if form.is_valid():
email = form.cleaned_data['email']
deleted_count = SubscribedEmail.objects.filter(email=email).delete()[0]
data['success'] = True
data['deleted'] = bool(deleted_count... | code_fim | hard | {
"lang": "python",
"repo": "wtl0442/bwg_real",
"path": "/beautiful/main/views.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: thoas/django-metadata path: /metadata/mixins.py
from .models import MetadataContainer
from . import settings
from .connection import client
<|fim_suffix|> metadata = MetadataContainer(connection=client,
key=lambda instance: instance.metadata_key)
@proper... | code_fim | hard | {
"lang": "python",
"repo": "thoas/django-metadata",
"path": "/metadata/mixins.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> @property
def metadata_key(self):
key = getattr(self, 'METADATA_KEY', settings.METADATA_KEY)
if key:
return key % {
'identifier': self.__class__.__name__.lower(),
'id': self.pk
}
return None<|fim_prefix|># repo: thoa... | code_fim | hard | {
"lang": "python",
"repo": "thoas/django-metadata",
"path": "/metadata/mixins.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>luster_centers_[2,1])
km_clf.predict(X)
lable_hash = {
1:1,
2:2,
0:3
}
lable_map = np.array([3,1,2])
predict = km_clf.predict(X)
predict
_y = lable_map[predict]
_y
np.sum(y == _y)/y.size<|fim_prefix|># repo: 280942919/gitTest path: /KMeans_System.py
#jupyter-notebook
%matplotlib inline
import matplotl... | code_fim | medium | {
"lang": "python",
"repo": "280942919/gitTest",
"path": "/KMeans_System.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: 280942919/gitTest path: /KMeans_System.py
#jupyter-notebook
%matplotlib inline
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
data = pd.read_csv('./data.csv',usecols=['F1','F2','Target‘])
data[:10]
data_arr<|fim_suffix|>luster_centers_[2,1])
km_clf.predict(X)
lable_hash = ... | code_fim | hard | {
"lang": "python",
"repo": "280942919/gitTest",
"path": "/KMeans_System.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> Only extract the most important features, which are PVT data and
7-Param data for machine learning algorithm.
Computational data for machine learning:
type: ndarray.
format: rows(instances) x columns(features), 2-D array.
Return... | code_fim | hard | {
"lang": "python",
"repo": "EMUNES/hust-mdb",
"path": "/backend/ml/views.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: EMUNES/hust-mdb path: /backend/ml/views.py
from django.http import JsonResponse
from django.http.response import Http404
from django.views import View
from django.core.serializers.json import DjangoJSONEncoder
from django.core.serializers import serialize
import numpy as np
from sklearn.preproces... | code_fim | hard | {
"lang": "python",
"repo": "EMUNES/hust-mdb",
"path": "/backend/ml/views.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> mat_arrays = []
for mat in mats: # django queryset -> python list
mat_features = []
# Add data
# Some data are missing here.
#TODO: Delete those if sentences after cleaning the data.
mat_features.append(mat.pvt_b5 if ... | code_fim | hard | {
"lang": "python",
"repo": "EMUNES/hust-mdb",
"path": "/backend/ml/views.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.asm.pass_one()
self.asm.pass_two()
print("=======LITERALS========")
for i, val in self.asm.LITERAL.items():
print(" {:7}\t{:04X}".format(i, val))
def test_record(self):
self.asm.pass_one()
self.asm.pass_two()
print("======Object... | code_fim | hard | {
"lang": "python",
"repo": "hane1818/SIC-XE-Assembler",
"path": "/test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: hane1818/SIC-XE-Assembler path: /test.py
from SICXE import Assembler
import unittest
class TestAssembler(unittest.TestCase):
def setUp(self):
self.asm = Assembler()
self.asm.load_file("SICXE.txt")
def test_read_source(self):
self.assertIsNotNone(self.asm.source,... | code_fim | hard | {
"lang": "python",
"repo": "hane1818/SIC-XE-Assembler",
"path": "/test.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.asm.pass_one()
self.asm.pass_two()
print("======Object Program=====")
print(self.asm.object_program)
if __name__ == "__main__":
unittest.main()<|fim_prefix|># repo: hane1818/SIC-XE-Assembler path: /test.py
from SICXE import Assembler
import unittest
class TestA... | code_fim | hard | {
"lang": "python",
"repo": "hane1818/SIC-XE-Assembler",
"path": "/test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> list_display = ["id", "area", "name", "byte", "bit", "tipo_dato",]
# def get_value(self, obj: Fila):
# return obj.read_value(obj.area.datos.first().dato)
# get_value.short_description = "Last value"
@admin.register(DatoProcesado)
class DatoProcesadoAdmin(admin.ModelAdmin):
list_... | code_fim | medium | {
"lang": "python",
"repo": "lautarodapin/webserver-snap7",
"path": "/app/admin.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lautarodapin/webserver-snap7 path: /app/admin.py
from django.contrib import admin
from .models import *
@admin.register(Plc)
class PlcAdmin(admin.ModelAdmin):
pass
@admin.register(Area)
class AreaAdmin(admin.ModelAdmin):
pass
<|fim_suffix|>@admin.register(DatoProcesado)
class DatoProce... | code_fim | hard | {
"lang": "python",
"repo": "lautarodapin/webserver-snap7",
"path": "/app/admin.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> if not os.path.isfile(simplified_path):
extractor = IconExtractor(app_path)
extractor.export_icon(download_path)
icon = Image.open(download_path).resize((ICON_SIZE, ICON_SIZE), Image.Resampling.LANCZOS)
icon.quantize(MAX_COLOURS).save(simplified_path)
return simpli... | code_fim | medium | {
"lang": "python",
"repo": "BenAAndrew/VolumeController",
"path": "/volume_controller/fetch_icon.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def get_icon(app_path: str, name: str) -> str:
download_path = os.path.join(ICONS_FOLDER, name + ".png")
simplified_path = os.path.join(ICONS_FOLDER, name + "-simple.png")
if not os.path.isfile(simplified_path):
extractor = IconExtractor(app_path)
extractor.export_icon(downloa... | code_fim | medium | {
"lang": "python",
"repo": "BenAAndrew/VolumeController",
"path": "/volume_controller/fetch_icon.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: BenAAndrew/VolumeController path: /volume_controller/fetch_icon.py
import os
from PIL import Image
from icoextract import IconExtractor
ICONS_FOLDER = "icons"
os.makedirs(ICONS_FOLDER, exist_ok=True)
ICON_SIZE = 60
MAX_COLOURS = 30
<|fim_suffix|> if not os.path.isfile(simplified_path):
... | code_fim | medium | {
"lang": "python",
"repo": "BenAAndrew/VolumeController",
"path": "/volume_controller/fetch_icon.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>gits + string.punctuation
password = []
for x in range(password_length):
password.append(random.choice(password_characters))
print(''.join(password))<|fim_prefix|># repo: KJ-18/PythonProjects path: /Random_PG.py
import random, string
password_length = int(input("How long would does your p<|fim_m... | code_fim | medium | {
"lang": "python",
"repo": "KJ-18/PythonProjects",
"path": "/Random_PG.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: KJ-18/PythonProjects path: /Random_PG.py
import random, string
password_length = int(input("How long would does your password need to be?"))
password_characters =string.ascii_uppercase + string.di<|fim_suffix|> password.append(random.choice(password_characters))
print(''.join(password))<|fim_... | code_fim | medium | {
"lang": "python",
"repo": "KJ-18/PythonProjects",
"path": "/Random_PG.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> password.append(random.choice(password_characters))
print(''.join(password))<|fim_prefix|># repo: KJ-18/PythonProjects path: /Random_PG.py
import random, string
password_length = int(input("How long would does your p<|fim_middle|>assword need to be?"))
password_characters =string.ascii_uppercase + s... | code_fim | medium | {
"lang": "python",
"repo": "KJ-18/PythonProjects",
"path": "/Random_PG.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sfu-cl-lab/our-papers path: /frequency-paper/table1.py
"""
Compute joint probabilities and pseudo-likelihood estimate for a Bayes Net according to
random selection semantics from a database.
Written in haste---bugs likely remain! It's also been eight months since I wrote real
py... | code_fim | hard | {
"lang": "python",
"repo": "sfu-cl-lab/our-papers",
"path": "/frequency-paper/table1.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>def functorOtherValue(functor, val):
""" For functors with a binary range, return the other element """
range = functorRange(functor)
assert len(range) == 2
if val == range[0]:
return range[1]
else:
return range[0]
def atomList(joints):
""" Return the atoms, derive... | code_fim | hard | {
"lang": "python",
"repo": "sfu-cl-lab/our-papers",
"path": "/frequency-paper/table1.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> return self._fail_total
def compute_stats(self):
self._good_diff = list()
self._good_duration = list()
self._failed_diff = list()
self._failed_duration = list()
self._good_total = 0
self._fail_total = 0
for es in... | code_fim | hard | {
"lang": "python",
"repo": "JBlaschke/cctbx_profiling",
"path": "/debug/directory.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: JBlaschke/cctbx_profiling path: /debug/directory.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
#TODO: change name => "stream" is not appropriate
class DirectoryStream(object):
def __init__ (self, root):
self._root = root
self._event_streams = list()
# g... | code_fim | hard | {
"lang": "python",
"repo": "JBlaschke/cctbx_profiling",
"path": "/debug/directory.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sevenler/hey path: /www/views/group/mine.py
#!/usr/bin/env python
# encoding=utf8
from views.base import BaseView
from core.logic import Group
<|fim_suffix|> my_group_list = Group.filter(created_user_id=me.id)
group_map_list = []
for group in my_group_list:
gr... | code_fim | medium | {
"lang": "python",
"repo": "sevenler/hey",
"path": "/www/views/group/mine.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> me = self.get_current_user()
my_group_list = Group.filter(created_user_id=me.id)
group_map_list = []
for group in my_group_list:
group_map_list.append(group.info())
self.render("group/mine.html", groups=group_map_list)<|fim_prefix|># repo: sevenler/hey ... | code_fim | easy | {
"lang": "python",
"repo": "sevenler/hey",
"path": "/www/views/group/mine.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> if sname is not None:
nx.write_edgelist(g, sname)
if __name__ == '__main__':
"""
sname = sys.argv[1]
d = int(sys.argv[2])
n = int(sys.argv[3])
randomRegularGraph(n, d, sname)
"""
sname = sys.argv[1]
n1 = int(sys.argv[2])
n2 = int(sys.argv[3])
n3 = int(... | code_fim | hard | {
"lang": "python",
"repo": "jakir-sust/CoreProject",
"path": "/src/data/generate_graph.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jakir-sust/CoreProject path: /src/data/generate_graph.py
import networkx as nx
import sys
import random
from pprint import pprint
def randomRegularGraph(n, d, sname=None):
g = nx.random_regular_graph(d,n)
if sname is not None:
nx.write_edgelist(g, sname)
def corePeriphery(n1, n2... | code_fim | hard | {
"lang": "python",
"repo": "jakir-sust/CoreProject",
"path": "/src/data/generate_graph.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: KIT-CMS/shape-producer path: /shape_producer/channel.py
ss EE(Channel):
def __init__(self):
self._name = "ee"
self._cuts = Cuts(
Cut("extraelec_veto<0.5", "extraelec_veto"),
Cut("extramuon_veto<0.5", "extramuon_veto"),
Cut("iso_1<0.1 && iso_... | code_fim | hard | {
"lang": "python",
"repo": "KIT-CMS/shape-producer",
"path": "/shape_producer/channel.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __init__(self, **kvargs):
super(EMSM2017, self).__init__(**kvargs)
self._cuts.add(
Cut("nbtag==0 && mTdileptonMET_puppi<60", "bveto_mTdileptonMET"),
)
class MMSM2017(MM2017):
def __init__(self, **kvargs):
super(MMSM2017, self).__init__(**kvargs)
... | code_fim | hard | {
"lang": "python",
"repo": "KIT-CMS/shape-producer",
"path": "/shape_producer/channel.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> super(TTSM2016, self).__init__(**kvargs)
class EMSM2016(EM2016):
def __init__(self, **kvargs):
super(EMSM2016, self).__init__(**kvargs)
self._cuts.add(
Cut("nbtag==0 && mTdileptonMET_puppi<60", "bveto_mTdileptonMET"),
)
class MMSM2016(MM2016):
def __... | code_fim | hard | {
"lang": "python",
"repo": "KIT-CMS/shape-producer",
"path": "/shape_producer/channel.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>def get_score(cuisine_file, menu):
return float(count_same_words(cuisine_file, menu))/len(menu)
def to_JSON(meal, list_of_cuisines, list_of_menus):
"""
Writes a dictionary of cuisines, scores per dining hall menu to a JSON file
meal: string describing name of meal - "breakfast", "lunch... | code_fim | hard | {
"lang": "python",
"repo": "rracheva/Dine-squad",
"path": "/menu_analysis.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rracheva/Dine-squad path: /menu_analysis.py
"""
MENU ANALYSIS PROGRAM
get_score(cuisine_file, menu): returns the score for a given
cuisine and menu
to_JSON(meal, list_of_cuisines, list_of_menus): writes all of the cuisine
and menu score dictionaries to a JSON file, entitled meal+"data.json"
... | code_fim | hard | {
"lang": "python",
"repo": "rracheva/Dine-squad",
"path": "/menu_analysis.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> all_words = []
new_word_list = []
for line in file:
for char in line:
if char.isalpha():
new_word_list.append(str(char).lower())
elif not char.isalpha() and len(new_word_list) > 0:
... | code_fim | hard | {
"lang": "python",
"repo": "rracheva/Dine-squad",
"path": "/menu_analysis.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: HaydenInEdinburgh/LintCode path: /828_word_pattern.py
class Solution:
"""
@param pattern: a string, denote pattern string
@param teststr: a string, denote matching string
@return: an boolean, denote whether the pattern string and the matching string match or not
"""
def wo... | code_fim | hard | {
"lang": "python",
"repo": "HaydenInEdinburgh/LintCode",
"path": "/828_word_pattern.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>if __name__ == '__main__':
s = Solution()
word = "a dog dog a"
pattern = "abba"
print(s.wordPattern(pattern, word))<|fim_prefix|># repo: HaydenInEdinburgh/LintCode path: /828_word_pattern.py
class Solution:
"""
@param pattern: a string, denote pattern string
@param teststr: a ... | code_fim | hard | {
"lang": "python",
"repo": "HaydenInEdinburgh/LintCode",
"path": "/828_word_pattern.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jonathanjaimes/python path: /6.1_contarVector.py
"""
while True:
num1 = int(input("Ingrese un número: "))
if num1 >= 10 and num1 <= 20:
break
while True:
num2 = int(input("Ingrese un número: "))
if num2 >= 10 and num2 <= 20:
break
while True:
num3 = int(input("Ingres... | code_fim | hard | {
"lang": "python",
"repo": "jonathanjaimes/python",
"path": "/6.1_contarVector.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>"""
lista = []
while True:
num1 = int(input("Ingrese un número: "))
if num1 >= 10 and num1 <= 20:
break
lista.append(num1)
while True:
num2 = int(input("Ingrese un número: "))
if num2 >= 10 and num2 <= 20:
break
lista.append(num2)
while True:
num3 = int(input("Ingrese un ... | code_fim | medium | {
"lang": "python",
"repo": "jonathanjaimes/python",
"path": "/6.1_contarVector.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> name = models.CharField(verbose_name=_('Name'), max_length=190)
def __str__(self):
return self.name
class Book(models.Model):
title = I18nCharField(verbose_name='Book title', max_length=190)
abstract = I18nTextField(verbose_name='Abstract')
author = models.ForeignKey('Author... | code_fim | medium | {
"lang": "python",
"repo": "raphaelm/django-i18nfield",
"path": "/tests/testapp/models.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: raphaelm/django-i18nfield path: /tests/testapp/models.py
from django.db import models
from django.utils.translation import gettext_lazy as _
from i18nfield.fields import I18nCharField, I18nTextField
<|fim_suffix|> return self.name
class Book(models.Model):
title = I18nCharField(ve... | code_fim | medium | {
"lang": "python",
"repo": "raphaelm/django-i18nfield",
"path": "/tests/testapp/models.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> return self.name
class Book(models.Model):
title = I18nCharField(verbose_name='Book title', max_length=190)
abstract = I18nTextField(verbose_name='Abstract')
author = models.ForeignKey('Author', verbose_name='Author', on_delete=models.CASCADE)
def __str__(self):
return s... | code_fim | medium | {
"lang": "python",
"repo": "raphaelm/django-i18nfield",
"path": "/tests/testapp/models.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dfischer/ActorForth path: /src/tests/test_repl.py
import unittest
from repl import *
class TestRepl(unittest.TestCase):
<|fim_suffix|> code = afc("1 int 2 int +")
assert do_repl("test", code) == 3<|fim_middle|>
def test_simple_code(self) -> None:
| code_fim | easy | {
"lang": "python",
"repo": "dfischer/ActorForth",
"path": "/src/tests/test_repl.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: HaThiMyChi/Django path: /djangoRestFramework/demoapi/course/serializers.py
from rest_framework import serializers
from .models import Course
class GetAllCourseSerializer(serializers.ModelSerializer):
<|fim_suffix|> title = serializers.CharField(max_length=12)
content = serializers.CharField(max... | code_fim | medium | {
"lang": "python",
"repo": "HaThiMyChi/Django",
"path": "/djangoRestFramework/demoapi/course/serializers.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> title = serializers.CharField(max_length=12)
content = serializers.CharField(max_length=12)
price = serializers.IntegerField()<|fim_prefix|># repo: HaThiMyChi/Django path: /djangoRestFramework/demoapi/course/serializers.py
from rest_framework import serializers
from .models import Course
class GetAll... | code_fim | medium | {
"lang": "python",
"repo": "HaThiMyChi/Django",
"path": "/djangoRestFramework/demoapi/course/serializers.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: abijithmg/kraya path: /api/admin.py
from django.contrib import admin
from api.models import Item, Preference, \
Supplier, SupplierRating
# @admin.register(Movie)
# class MovieAdmin(admin.ModelAdmin):
# fields = ('title', 'description')
# list_display = ['title', 'description']
# ... | code_fim | hard | {
"lang": "python",
"repo": "abijithmg/kraya",
"path": "/api/admin.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
@admin.register(Preference)
class PreferenceAdmin(admin.ModelAdmin):
fields = ('item', 'delivery_address', 'note_to_buyer', 'emergency_contact')
list_display = ['item', 'delivery_address', 'note_to_buyer', 'emergency_contact']
# search_fields = ('')
@admin.register(Supplier)
class SupplierA... | code_fim | hard | {
"lang": "python",
"repo": "abijithmg/kraya",
"path": "/api/admin.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> if (alphabet not in vowels):
return True
else:
return False
# Filter Vowels
filtered_vowels = filter(filter_vowels, alphabets)
print(filtered_vowels)
print(list(filtered_vowels))
# Filter Consonants
filtered_consonants = filter(filter_consonants, alphabets)
print(filtered_consona... | code_fim | medium | {
"lang": "python",
"repo": "vikash-india/DeveloperNotes2Myself",
"path": "/languages/python/src/concepts/P064_FilterFunction_Alphabets.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: vikash-india/DeveloperNotes2Myself path: /languages/python/src/concepts/P064_FilterFunction_Alphabets.py
# Description: Filter Vowels and Consonants Using Vowels
# Note
# 1. If a function is already define, use it over a list using a map function.
# List of alphabets
alphabets = ['a', 'b', 'c',... | code_fim | medium | {
"lang": "python",
"repo": "vikash-india/DeveloperNotes2Myself",
"path": "/languages/python/src/concepts/P064_FilterFunction_Alphabets.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: 0ne4rif/plotly-scatter-plots path: /demo.py
import plotly
import plotly.graph_objects as go
import pandas as pd
<|fim_suffix|>fig = go.Figure()
fig.add_trace(go.Scatter(x=df['date'], y=df['confirmed'], mode='line+markers', name='Positive'))
fig.add_trace(go.Scatter(x=df['date'], y=df['rele... | code_fim | medium | {
"lang": "python",
"repo": "0ne4rif/plotly-scatter-plots",
"path": "/demo.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>fig = go.Figure()
fig.add_trace(go.Scatter(x=df['date'], y=df['confirmed'], mode='line+markers', name='Positive'))
fig.add_trace(go.Scatter(x=df['date'], y=df['released'], mode='markers', name='Released'))
fig.add_trace(go.Scatter(x=df['date'], y=df['deceased'], mode='line', name='Deceased'))
fig.upda... | code_fim | medium | {
"lang": "python",
"repo": "0ne4rif/plotly-scatter-plots",
"path": "/demo.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: NguyenHaiPhong/NguyenHaiHa---Fundamentals---C4E19 path: /WebModules/Web03/serious_exercises_8_9.py
from flask import *
river_app = Flask(__name__)
import mlab
from river import river
<|fim_suffix|> all_rivers = river.objects(continent = "Africa")
return render_template("ex-8.html", all_ri... | code_fim | medium | {
"lang": "python",
"repo": "NguyenHaiPhong/NguyenHaiHa---Fundamentals---C4E19",
"path": "/WebModules/Web03/serious_exercises_8_9.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>@river_app.route("/ex-9")
def all_rivers_in_south_america_continent_length_lt_1000():
all_rivers = river.objects(continent = "S. America", length__lt = 1000)
return render_template("ex-9.html", all_rivers = all_rivers)
if __name__ == '__main__':
river_app.run(debug=True)<|fim_prefix|># repo: Ng... | code_fim | medium | {
"lang": "python",
"repo": "NguyenHaiPhong/NguyenHaiHa---Fundamentals---C4E19",
"path": "/WebModules/Web03/serious_exercises_8_9.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: LoganHentschel/csp_python path: /CSP_Sem1/TURTLE/1.1 Unit/Bug Fix Assignment/FIXED_VARIABLES_a115_buggy_image.py
# a115_buggy_image.py
import turtle as trtl
##############
trtl_spider = trtl.Turtle()
#
trtl_spider.pensize(40)
trtl_spider.circle(20)
# # #
<|fim_suffix|>trtl_spider.hideturtle()
... | code_fim | hard | {
"lang": "python",
"repo": "LoganHentschel/csp_python",
"path": "/CSP_Sem1/TURTLE/1.1 Unit/Bug Fix Assignment/FIXED_VARIABLES_a115_buggy_image.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>trtl_spider.hideturtle()
# # # #
wn = trtl.Screen()
wn.mainloop()<|fim_prefix|># repo: LoganHentschel/csp_python path: /CSP_Sem1/TURTLE/1.1 Unit/Bug Fix Assignment/FIXED_VARIABLES_a115_buggy_image.py
# a115_buggy_image.py
import turtle as trtl
##############
trtl_spider = trtl.Turtle()
#
trtl_spider.... | code_fim | hard | {
"lang": "python",
"repo": "LoganHentschel/csp_python",
"path": "/CSP_Sem1/TURTLE/1.1 Unit/Bug Fix Assignment/FIXED_VARIABLES_a115_buggy_image.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|># # #
trtl_spider.hideturtle()
# # # #
wn = trtl.Screen()
wn.mainloop()<|fim_prefix|># repo: LoganHentschel/csp_python path: /CSP_Sem1/TURTLE/1.1 Unit/Bug Fix Assignment/FIXED_VARIABLES_a115_buggy_image.py
# a115_buggy_image.py
import turtle as trtl
##############
trtl_spider = trtl.Turtle()
#
trtl_... | code_fim | hard | {
"lang": "python",
"repo": "LoganHentschel/csp_python",
"path": "/CSP_Sem1/TURTLE/1.1 Unit/Bug Fix Assignment/FIXED_VARIABLES_a115_buggy_image.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> for _ in string:
str_1 = re.sub('[^A-Za-z0-9]', '', string.lower())
# str_1 = string.lower()
# str_1 = string.strip(" !@#$%^&*()-_+={}[]|\:;'<>?,./\"")
return str_1
def main():
'''main function'''
string = input()
print(clean_string(string))
if __name__ == '__main__':... | code_fim | medium | {
"lang": "python",
"repo": "swapnika-20186045/CSPP1",
"path": "/CSPP1-Practice/M22 (final exam)/assignment2/clean_input.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: swapnika-20186045/CSPP1 path: /CSPP1-Practice/M22 (final exam)/assignment2/clean_input.py
'''
Write a function to clean up a given string by removing the special characters and retain
alphabets in both upper and lower case and numbers.
<|fim_suffix|>def main():
'''main function'''
string... | code_fim | hard | {
"lang": "python",
"repo": "swapnika-20186045/CSPP1",
"path": "/CSPP1-Practice/M22 (final exam)/assignment2/clean_input.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>def main():
'''main function'''
string = input()
print(clean_string(string))
if __name__ == '__main__':
main()<|fim_prefix|># repo: swapnika-20186045/CSPP1 path: /CSPP1-Practice/M22 (final exam)/assignment2/clean_input.py
'''
Write a function to clean up a given string by removing the sp... | code_fim | hard | {
"lang": "python",
"repo": "swapnika-20186045/CSPP1",
"path": "/CSPP1-Practice/M22 (final exam)/assignment2/clean_input.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kirjur/fotoforte path: /services/models.py
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models
from django.utils.encoding import python_2_unicode_compatible
@python_2_unicode_compatible
class ServiceType(models.Model):
class Meta():
db_tabl... | code_fim | medium | {
"lang": "python",
"repo": "kirjur/fotoforte",
"path": "/services/models.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class Meta():
db_table = 'service'
verbose_name = "Услуга"
name = models.CharField(max_length=200, verbose_name="Наименование")
description = models.TextField(verbose_name="Описание")
created_date = models.DateTimeField(verbose_name="Дата создания")
service_type = mod... | code_fim | hard | {
"lang": "python",
"repo": "kirjur/fotoforte",
"path": "/services/models.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: margueriteblair/Python-Algorithms path: /LoopsReview.py
N = int(input())
for j in range(N):
S = input()
<|fim_suffix|>se:
odd += S[i]
print(even + " " + odd)<|fim_middle|> even = ""
odd = ""
for i in range(len(S)):
if (i%2 == 0):
even += S[i]
... | code_fim | medium | {
"lang": "python",
"repo": "margueriteblair/Python-Algorithms",
"path": "/LoopsReview.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>se:
odd += S[i]
print(even + " " + odd)<|fim_prefix|># repo: margueriteblair/Python-Algorithms path: /LoopsReview.py
N = int(input())
for j in range(N):
S = input()
<|fim_middle|> even = ""
odd = ""
for i in range(len(S)):
if (i%2 == 0):
even += S[i]
... | code_fim | medium | {
"lang": "python",
"repo": "margueriteblair/Python-Algorithms",
"path": "/LoopsReview.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>#Visulaizing the regression results
X_grid = np.arange(min(X), max(X), 0.1)
X_grid = X_grid.reshape(len(X_grid), 1)
plt.scatter(X, y, color='red')
plt.plot(X_grid, regressor.predict(X_grid), color='blue')
plt.title('Random Forest Regression')
plt.xlabel('Position Label')
plt.ylabel('Salary')
plt.show()<|f... | code_fim | medium | {
"lang": "python",
"repo": "Joseorina/machine_learning_regression",
"path": "/RFR/random_forest_regression.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>#Predicting a new result
y_pred = regressor.predict([[6.5]])
#Visulaizing the regression results
X_grid = np.arange(min(X), max(X), 0.1)
X_grid = X_grid.reshape(len(X_grid), 1)
plt.scatter(X, y, color='red')
plt.plot(X_grid, regressor.predict(X_grid), color='blue')
plt.title('Random Forest Regression')
p... | code_fim | hard | {
"lang": "python",
"repo": "Joseorina/machine_learning_regression",
"path": "/RFR/random_forest_regression.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Joseorina/machine_learning_regression path: /RFR/random_forest_regression.py
#Random Forest Regression
#Importing libraries
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
#Importing the dataset
dataset = pd.read_csv('Position_Salaries.csv')
X = dataset.iloc[:, 1:2].value... | code_fim | medium | {
"lang": "python",
"repo": "Joseorina/machine_learning_regression",
"path": "/RFR/random_forest_regression.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Shivani2006/Number-Guessing-Game path: /c97Project.py
import random
print('The Number Guessing Game')
<|fim_suffix|>print ('guess a number between 1 to 10')
chances=0
while(chances<3):
guess=int(input('enter your guess '))
if(guess==no):
print('Congratulations! You won'... | code_fim | easy | {
"lang": "python",
"repo": "Shivani2006/Number-Guessing-Game",
"path": "/c97Project.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>print ('guess a number between 1 to 10')
chances=0
while(chances<3):
guess=int(input('enter your guess '))
if(guess==no):
print('Congratulations! You won')
break
elif(guess<no):
print('Please guess a higher number! ', guess)
else:
print('Please g... | code_fim | easy | {
"lang": "python",
"repo": "Shivani2006/Number-Guessing-Game",
"path": "/c97Project.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>chances=0
while(chances<3):
guess=int(input('enter your guess '))
if(guess==no):
print('Congratulations! You won')
break
elif(guess<no):
print('Please guess a higher number! ', guess)
else:
print('Please guess a lower number! ',guess)
chances=c... | code_fim | easy | {
"lang": "python",
"repo": "Shivani2006/Number-Guessing-Game",
"path": "/c97Project.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>name = f'{employee.last_name} {employee.first_name} {employee.patronymic}'
manager_post = employee.post
manager = f'{manager_name}<div style="color:red; font-style:italic">{manager_post}</div><br>'
base_string = (base_string + manager)
if employ... | code_fim | hard | {
"lang": "python",
"repo": "MrGreeny12/employee_tree",
"path": "/company/services.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MrGreeny12/employee_tree path: /company/services.py
from company.models import Company, DepartmentRelations
from employee.models import Employee
def get_correct_format_department_list():
'''
Возвращает список формата:
list = [
['Название отдела, руководитель, сотрудники', 'К... | code_fim | hard | {
"lang": "python",
"repo": "MrGreeny12/employee_tree",
"path": "/company/services.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> if self.batch_norm:
conv_out = (conv_out - conv_out.mean(axis = (0,2,3), keepdims = True)) / (1.0 + conv_out.std(axis = (0,2,3), keepdims = True))
conv_out = conv_out + self.b.dimshuffle('x', 0, 'x', 'x')
if self.activation == "relu":
out = T.maximum(0.0, ... | code_fim | hard | {
"lang": "python",
"repo": "alexmlamb/JSA",
"path": "/lib/DeConvLayer.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: alexmlamb/JSA path: /lib/DeConvLayer.py
import theano
import theano.tensor as T
from theano.sandbox.cuda.basic_ops import (as_cuda_ndarray_variable,
host_from_gpu,
gpu_contiguous, HostFromGpu,
... | code_fim | hard | {
"lang": "python",
"repo": "alexmlamb/JSA",
"path": "/lib/DeConvLayer.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> # find which character the RHS belongs to
cha_index = []
for j in range(RHS_len + 1):
cha_index.append(min(np.where(points_cumsum > start + j)[0]))
for j in range(RHS_len):
x1_base = (cha_index[j] - 10 * int(cha_index[j] / 10)) * 550
y1_base = (9 - int(cha_index[j... | code_fim | hard | {
"lang": "python",
"repo": "HELL-TO-HEAVEN/WriteId",
"path": "/Code/data_process/visualize_attn.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> x2 = sample_points[j + 1][0] + x2_base
y2 = 500 - sample_points[j + 1][1] + y2_base
if attn[j] >= thres:
if delta_S[start + j][2] == 1:
line = 'r-'
else:
line = 'r--'
else:
if delta_S[start + j][2] == 1:
... | code_fim | hard | {
"lang": "python",
"repo": "HELL-TO-HEAVEN/WriteId",
"path": "/Code/data_process/visualize_attn.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: HELL-TO-HEAVEN/WriteId path: /Code/data_process/visualize_attn.py
import matplotlib.pyplot as plt
import numpy as np
import glob
import os
import re
def flag(i, x, p):
t = data[i][x][p][:]
t.append(0) if p == 0 else t.append(1)
return t
def trans(d1, d2):
return [d2[0] - d1[0]... | code_fim | hard | {
"lang": "python",
"repo": "HELL-TO-HEAVEN/WriteId",
"path": "/Code/data_process/visualize_attn.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: levuhachi/levuhachi-web-c4e23 path: /Web1/homework/EX1-bmi-calculator-master/upgraded_ex1_bmi.py
from flask import Flask, render_template, request
app = Flask(__name__)
@app.route('/', methods=['GET', 'POST'])
def index():
bmi = ''
if request.method == 'POST' and 'weight' in request.for... | code_fim | hard | {
"lang": "python",
"repo": "levuhachi/levuhachi-web-c4e23",
"path": "/Web1/homework/EX1-bmi-calculator-master/upgraded_ex1_bmi.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
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