Emre Aydin aydinemre

## multi_process.py
import multiprocessing
from functools import partial

# Manager to create shared object.
manager = multiprocessing.Manager()

# Create a global variable.
dictionary = manager.dict()


## read_json_from_sql.py
# -*- coding: utf-8 -*-

import json

import pandas as pd

from db.oracle_client import get_oracle_conn

file_name = "data.csv"

## scraper.py
# -*- coding: utf-8 -*-

"""

pip install scrapy
pip install pandas
scrapy runspider scraper/scraper.py -s LOG_ENABLED=False

"""
import scrapy

## pandas_to_datetime.py
import pandas as pd

df = pd.DataFrame({"purchase_time": ["19-09-1995 12:14:00.000","12/09/2018 15:34"]})

df['Timestamp'] = pd.to_datetime(df.purchase_time, format='%d/%m/%Y %H:%M', errors='coerce')

mask = df.Timestamp.isnull()

df.loc[mask, 'Timestamp'] = pd.to_datetime(df[mask]['purchase_time'], format='%d-%m-%Y %H:%M:%S.%f', errors='coerce')

## clean-up-boot-partition-ubuntu.md

      
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                aydinemre
                / clean-up-boot-partition-ubuntu.md
            
            
              Created
              August 31, 2019 06:09
                — forked from ipbastola/clean-up-boot-partition-ubuntu.md
            
              
                Safest way to clean up boot partition - Ubuntu 14.04LTS-x64, Ubuntu 16.04LTS-x64
              
          
    Safest way to clean up boot partition - Ubuntu 14.04LTS-x64, Ubuntu 16.04LTS-x64

Reference
Case I: if /boot is not 100% full and apt is working

1. Check the current kernel version

$ uname -r 


## connection.py
#
# A higher level module for using sockets (or Windows named pipes)
#
# multiprocessing/connection.py
#
# Copyright (c) 2006-2008, R Oudkerk
# Licensed to PSF under a Contributor Agreement.
#

__all__ = [ 'Client', 'Listener', 'Pipe', 'wait' ]

## connection.py
#
# A higher level module for using sockets (or Windows named pipes)
#
# multiprocessing/connection.py
#
# Copyright (c) 2006-2008, R Oudkerk
# Licensed to PSF under a Contributor Agreement.
#

__all__ = [ 'Client', 'Listener', 'Pipe', 'wait' ]

## clarifamp.py
#!/usr/bin/env python
# coding: utf-8
import json
import os
from datetime import datetime
from multiprocessing import Pool, cpu_count
from pathlib import Path

import pandas as pd
from PIL import Image

## arsa_rayic_bedelleri.py
import itertools

import pandas as pd
from selenium import webdriver

from selenium.webdriver.support.select import Select

driver = webdriver.Chrome(executable_path='./chromedriver')

belediyeler = ['basaksehir-belediyesi-arsa-rayic']

## hoppy_project.py
import os
from urllib.request import urlretrieve

import pandas as pd
import requests
from bs4 import BeautifulSoup
from selenium import webdriver
from selenium.common.exceptions import NoSuchElementException
from webdriver_manager.chrome import ChromeDriverManager
	import multiprocessing
	from functools import partial

	# Manager to create shared object.
	manager = multiprocessing.Manager()

	# Create a global variable.
	dictionary = manager.dict()
	# -- coding: utf-8 --

	import json

	import pandas as pd

	from db.oracle_client import get_oracle_conn

	file_name = "data.csv"
	# -- coding: utf-8 --

	"""

	pip install scrapy
	pip install pandas
	scrapy runspider scraper/scraper.py -s LOG_ENABLED=False

	"""
	import scrapy
	import pandas as pd

	df = pd.DataFrame({"purchase_time": ["19-09-1995 12:14:00.000","12/09/2018 15:34"]})

	df['Timestamp'] = pd.to_datetime(df.purchase_time, format='%d/%m/%Y %H:%M', errors='coerce')

	mask = df.Timestamp.isnull()

	df.loc[mask, 'Timestamp'] = pd.to_datetime(df[mask]['purchase_time'], format='%d-%m-%Y %H:%M:%S.%f', errors='coerce')
	#
	# A higher level module for using sockets (or Windows named pipes)
	#
	# multiprocessing/connection.py
	#
	# Copyright (c) 2006-2008, R Oudkerk
	# Licensed to PSF under a Contributor Agreement.
	#

	__all__ = [ 'Client', 'Listener', 'Pipe', 'wait' ]
	#!/usr/bin/env python
	# coding: utf-8
	import json
	import os
	from datetime import datetime
	from multiprocessing import Pool, cpu_count
	from pathlib import Path

	import pandas as pd
	from PIL import Image
	import itertools

	import pandas as pd
	from selenium import webdriver

	from selenium.webdriver.support.select import Select

	driver = webdriver.Chrome(executable_path='./chromedriver')

	belediyeler = ['basaksehir-belediyesi-arsa-rayic']
	import os
	from urllib.request import urlretrieve

	import pandas as pd
	import requests
	from bs4 import BeautifulSoup
	from selenium import webdriver
	from selenium.common.exceptions import NoSuchElementException
	from webdriver_manager.chrome import ChromeDriverManager