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Utility for web scraping.

Project description

ScrapingHelper

This library intends to make parsing HTML with using request_html. So, When using this library you automatically get (same as request_html):

  • Full JavaScript support!
  • CSS Selectors (a.k.a jQuery-style, thanks to PyQuery).
  • XPath Selectors, for the faint of heart.
  • Mocked user-agent (like a real web browser).
  • Automatic following of redirects.
  • Connection– pooling and cookie persistence.
  • The Requests experience you know and love, with magical parsing abilities.
  • Async Support

And new features.

  • URL / PROXY parser with validator.
  • UserAgent manager using collected real user-agents.
  • proxy rotation suppport.
  • access with random wait time
  • shell environment options.
  • logging support.

Tutorial and Usage

class URL

  • validator()
  • unquote() / decode()
  • enquote() / encode()
In [1]: from scrapinghelper import URL

In [2]: u = URL()

In [3]: u.validator('http://sample.om')
Out[3]: True

In [4]: u.validator('http://sample.')
Out[4]: False

In [5]: url = URL('http://www.example.com/sample?src=git&encode=jp')

In [6]: url.is_valid
Out[6]: True

In [7]: url.attrs
Out[7]:
{'url': 'http://www.example.com/sample?src=git&encode=jp',
 'is_valid': True,
 'scheme': 'http',
 'netloc': 'www.example.com',
 'username': None,
 'password': None,
 'hostname': 'www.example.com',
 'port': None,
 'path': '/sample',
 'params': '',
 'query': 'src=git&encode=jp',
 'fragment': '',
 'basename': 'sample'}

In [8]: url = URL('http://www.example.com/データ.txt')

In [9]: url.attrs
Out[9]:
{'url': 'http://www.example.com/%E3%83%87%E3%83%BC%E3%82%BF.txt',
 'is_valid': True,
 'scheme': 'http',
 'netloc': 'www.example.com',
 'username': None,
 'password': None,
 'hostname': 'www.example.com',
 'port': None,
 'path': '/%E3%83%87%E3%83%BC%E3%82%BF.txt',
 'params': '',
 'query': '',
 'fragment': '',
 'basename': 'データ.txt'}

In [10]: url.query
Out[10]: 'src=git&encode=jp'

In [11]: url.get_query_val('src')
Out[11]: 'git'

In [12]: url.set_query_val('src', 'csv')
Out[12]: 'http://www.example.com/sample?src=csv&encode=jp'

In [13]: url
Out[13]: http://www.example.com/sample?src=git&encode=jp

In [14]: url.set_query_val('src', 'csv',update=True)
Out[14]: 'http://www.example.com/sample?src=csv&encode=jp'

In [15]: url
Out[15]: http://www.example.com/sample?src=csv&encode=jp

In [16]: url.get_root_address()
Out[16]: 'http://www.example.com'

In [17]: url.strip_query()
Out[17]: 'http://www.example.com/sample'

In [18]: url = URL('https://ja.wikipedia.org/wiki/日本語')

In [19]: url
Out[19]: https://ja.wikipedia.org/wiki/%E6%97%A5%E6%9C%AC%E8%AA%9E

In [20]: url.unquote()
Out[20]: 'https://ja.wikipedia.org/wiki/日本語'

In [21]: url.decode()
Out[21]: 'https://ja.wikipedia.org/wiki/日本語'

class UserAgent

  • load_datafile(keep_user_agents: int=50, datapath: Optional[str]=None)
  • get_random_user_agent()
  • get_next_user_agent()

attributes

  • first_user_agent

class Scraper

  • get_random_user_agent() pass to UserAgent.get_random_user_agent()
  • get_random_ipv4()
  • get_random_ipv6()
  • request()
  • request_async()
  • get_filename()
  • get_links()
  • get_texts()
  • download_file()
n [1]: from scrapinghelper import Scraper

In [2]: sc = Scraper()

In [3]: sc.get_random_user_agent()
Out[3]: 'Mozilla/5.0 (CrKey armv7l 1.5.16041) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/31.0.1650.0 Safari/537.36'

In [4]: sc.get_random_user_agent()
Out[4]: 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_2) AppleWebKit/601.3.9 (KHTML, like Gecko) Version/'

In [5]: sc.get_random_user_agent()
Out[5]: 'Mozilla/5.0 (CrKey armv7l 1.5.16041) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/31.0.1650.0 Safari/537.36'

In [6]: sc.get_random_user_agent()
Out[6]: 'Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:15.0) Gecko/20100101 Firefox/15.0.1'

In [7]: sc.get_random_user_agent()
Out[7]: 'Mozilla/5.0 (CrKey armv7l 1.5.16041) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/31.0.1650.0 Safari/537.36'

In [8]: sc.get_random_user_agent()
Out[8]: 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/'

In [9]: sc.get_random_user_agent()
Out[9]: 'Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:15.0) Gecko/20100101 Firefox/15.0.1'

In [10]: sc.get_random_ipv4()
Out[10]: '121.162.233.190'

In [11]: sc.get_random_ipv4()
Out[11]: '178.172.98.169'

In [12]: sc.get_random_ipv6()
Out[12]: '3d18:cb77:5387:3ee9:1e60:d5f3:d987:283a'

In [13]: sc.get_random_ipv6()
Out[13]: 'cfc1:a00d:9013:37a0:ed94:5e92:7fe7:e356'

In [14]:

the request headers with user agents will be automatically created.

In [1]: # %load examples/check_headers.py
   ...: import scrapinghelper as sch
   ...: from pprint import pprint
   ...:
   ...: scraper = sch.Scraper()
   ...: response = scraper.request('http://httpbin.org/headers')
   ...:
   ...: pprint(response.json())
{'headers': {'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.9',
             'Accept-Encoding': 'gzip, deflate, br',
             'Accept-Language': 'en',
             'Host': 'httpbin.org',
             'Upgrade-Insecure-Requests': '1',
             'User-Agent': 'Mozilla/5.0 (iPad; CPU OS 8_1_2 like Mac OS X) '
                           'AppleWebKit/600.1.4 (KHTML, like Gecko) '
                           'Mobile/12B440',
             'X-Amzn-Trace-Id': 'Root=1-62de3626-07daf491262b96356486884d'}}

In [2]:

**[Important note regardings trie]

the datasets of UserAgents from 51Degrees/DeviceDetection. data file '20000 User Agents.csv' is licenced under the European Union Public Licence V.1.2.

from scrapinghelper import Scraper

scrapper = Scraper(datapath="path_to_new_user_agent_csvfile")
  # ...

or set shell Environmnet "SCRAPINGHELPER_USERAGENT_PATH".

export SCRAPINGHELPER_USERAGENT_PATH="/path/to/new_user_agent_csvfile"
In [2]: from scrapinghelper import URL, Scraper, LogConfig
   ...:
   ...: logconfig = LogConfig()
   ...: logconfig.level = 'INFO'
   ...: sc = Scraper(logconfig=logconfig)
   ...:
   ...: url = URL('https://www.houjin-bangou.nta.go.jp/download/zenken/#csv-unic
   ...: ode')
   ...: response = sc.request(url)
   ...:
   ...: content = response.content
   ...: print(f'code: {response.status_code}')
   ...:
code: 200
In [2]: # %load examples/yahoo_finance.py
   ...: from typing import Any
   ...: import numpy as np
   ...: from scrapinghelper import Scraper, URL
   ...:
   ...: MARKET_SUMMARY = (
   ...:     '#market-summary > div > div.D\(ib\).Fl\(start\).W\(100\%\) '
   ...:     '> div.Carousel-Mask.Pos\(r\).Ov\(h\).market-summary'
   ...:     '.M\(0\).Pos\(r\).Ov\(h\).D\(ib\).Va\(t\) > ul'
   ...: )
   ...:
   ...: class YHFinance(Scraper):
   ...:     Finance = URL('https://finance.yahoo.com/')
   ...:
   ...:     def __init__(self, **kwargs: Any):
   ...:         super().__init__(browser_args='--incognito', **kwargs)
   ...:         self.response = self.request(self.Finance.url)
   ...:
   ...:     def get_market_summary(self)->list:
   ...:         contents = self.get_texts(MARKET_SUMMARY)[0]
   ...:         return contents
   ...:
   ...: if __name__ == '__main__':
   ...:     from scrapinghelper.utils import split_chunks
   ...:
   ...:     yahoo = YHFinance()
   ...:     summary = yahoo.get_market_summary()
   ...:     for data in split_chunks(summary, 5):
   ...:         print(data)
   ...:
['S&P Futures', '', '4,215.50', '-16.00', '(-0.38%)']
['Dow Futures', '', '33,583.00', '-123.00', '(-0.36%)']
['Nasdaq Futures', '', '13,207.00', '-61.50', '(-0.46%)']
['Russell 2000 Futures', '', '1,952.70', '-6.40', '(-0.33%)']
['Crude Oil', '', '89.87', '-0.90', '(-0.99%)']
['Gold', '', '1,759.70', '-3.20', '(-0.18%)']

In [3]:
In [3]: from scrapinghelper import Scraper, LogConfig
   ...:
   ...: logconfig = LogConfig()
   ...: logconfig.level = 'DEBUG'
   ...: sc = Scraper(logconfig=logconfig)
   ...:
   ...: url = URL('https://www.houjin-bangou.nta.go.jp/download/zenken/#csv-unic
   ...: ode')
   ...: response = sc.request(url)
   ...:
   ...: content = response.content
   ...: print(f'code: {response.status_code}')
2022-06-02T19:34:31.885790+0900 LOG configure: {'handlers': [{'sink': <_io.TextIOWrapper name='<stdout>' mode='w' encoding='utf-8'>, 'level': 'DEBUG', 'format': '<green>{time}</green> <level>{message}</level>', 'colorize': True, 'serialize': False}]}
2022-06-02T19:34:31.886414+0900 URL: https://www.houjin-bangou.nta.go.jp/download/zenken/#csv-unicode
2022-06-02T14:34:32.092599+0900 response status_code: 200
code: 200

In [4]: logconfig
Out[4]: LogConfig(sink=None, level=DEBUG, format=<green>{time}</green> <level>{message}</level>, colorize=True, serialize=False

In [5]:

render() and PROXY

if passed render=False, request() skip call render(). render() of requests-html does not work with proxy. scrapinghelper support render() with proxy.

In [2]: # %load examples/check_ipaddress.py
   ...: from scrapinghelper import Scraper, ProxyManager, ProxyRotate
   ...:
   ...: # tiny socks5 proxy
   ...: proxies = [ 'socks5://127.0.0.1:9050']
   ...: url = 'https://httpbin.org/ip'
   ...:
   ...: scraper = Scraper(proxies=proxies)
   ...:
   ...: # default proxy_rotate is ProxyRotate.NO_PROXY
   ...: # does not call render()
   ...: response = scraper.request(url, render=False)
   ...: print(response.html.text)
   ...:
   ...: # using next proxy server.
   ...: response = scraper.request(url, proxy_rotate=ProxyRotate.NEXT, render=Fa
   ...: lse)
   ...: print(response.html.text)
   ...:
   ...: # using current proxy server.
   ...: response = scraper.request(url, proxy_rotate=ProxyRotate.KEEP, render=Fa
   ...: lse)
   ...: print(response.html.text)
   ...:
   ...: # using random proxy server.
   ...: response = scraper.request(url, proxy_rotate=ProxyRotate.RANDOM)
   ...: print(response.html.text)
   ...:

{ "origin": "221.186.103.38" }
{ "origin": "185.220.101.182" }
{ "origin": "185.220.101.182" }
{ "origin": "185.220.101.182" }

In [3]:

PROXY

Get public proxies list from url. default is github.com/hookzof. Please keep in mind, there proxies are ABSOLUTELY NO WARRANTY.

In [1]: from scrapinghelper import ProxyManager, PROXY

In [2]: pm = ProxyManager()

In [3]: pm.load_proxies('https://raw.githubusercontent.com/hookzof/socks5_list/m
   ...: aster/proxy.txt', proxy_type='socks5')

In [4]: pm.proxies[:5]
Out[4]:
['101.67.215.147:44844',
 '103.110.84.199:7497',
 '103.108.228.185:7497',
 '103.74.121.46:27102',
 '1.57.21.59:7302']

In [5]: pm.proxy_pool
Out[5]: <itertools.cycle at 0x11bdd1b80>

In [6]: pm.next_proxy()
Out[6]: 101.67.215.147:44844

In [7]: pm.next_proxy()
Out[7]: 103.110.84.199:7497

In [8]: pm.random_proxy()
Out[8]: 72.210.252.134:46164

In [9]: pm.random_proxy().proxy_map
Out[9]: {'http': 'socks5://1.57.21.59:7302', 'https': 'socks5://1.57.21.59:7302'}

In [10]: pm.current_proxy
Out[10]: 1.57.21.59:7302

In [11]: pm.current_proxy.attrs
Out[11]:
{'proxy_url': '1.57.21.59:7302',
 'is_valid': True,
 'scheme': 'socks5',
 'netloc': '1.57.21.59:7302',
 'username': None,
 'password': None,
 'hostname': '1.57.21.59',
 'port': 7302,
 'proxy_map': {'http': 'socks5://1.57.21.59:7302',
  'https': 'socks5://1.57.21.59:7302'}}

In [12]:

you can filename as url. i.e.:

p = ProxyManager('file://./myproxy_list.txt')

there uri expand as follows.

        if proxies_url.startswith('file://.'):
            proxies_url = proxies_url.replace('file://.','')
            this_directory = Path(__file__).parent
            proxies_url = 'file://{}/{}'.format(this_directory, proxies_url)

CAUTION if you use a free proxy to login to something or enter personal information and POST it, you must be assured that it will be leaked. Keep in mind, it is like writing your credit card number and security code on a postcard.

KNOWN PROBLEM

if you want to use this module(and/or requests_html, selenium) on ubuntu, you should add system libraries. try folloings.

sudo apt install -y gconf-service libasound2 libatk1.0-0 libc6 libcairo2 libcups2 libdbus-1-3 libexpat1 libfontconfig1 libgcc1 libgconf-2-4 libgdk-pixbuf2.0-0 libglib2.0-0 libgtk-3-0 libnspr4 libpango-1.0-0 libpangocairo-1.0-0 libstdc++6 libx11-6 libx11-xcb1 libxcb1 libxcomposite1 libxcursor1 libxdamage1 libxext6 libxfixes3 libxi6 libxrandr2 libxrender1 libxss1 libxtst6 ca-certificates fonts-liberation libappindicator1 libnss3 lsb-release xdg-utils wget

See Also: https://techoverflow.net/2020/09/29/how-to-fix-pyppeteer-pyppeteer-errors-browsererror-browser-closed-unexpectedly/

Utility class and Helper Functions

  • class StrCase Convert case for object(s).
  • class uDict allow to change key for Dict.
  • class iDict Immutable Dict. iDict object hashable.

utilities for string manupulate helper functions.

  • is_alpha() - Check word is alphabet.
  • is_alnum() - Check word is alphabet and digits.
  • ordereddict_to_dict() - convert object from OrderedDict to Dict.
  • change_dict_keys() - Change keys of Dict.
  • replace_values() - Replace objects for object(s).
  • omit_values() - Omit values for object(s).
  • add_df() - Add data into DataFrame.
  • df_compare() - Check DataFrame is equals.
  • split_chunks() - Split iterable object into chunks.
  • urange() - Return an object that produces a sequence of integes.

class StrCase

strCase class support convert case.

In [1]: from scrapinghelper.utils import StrCase

In [2]: c = StrCase()

In [3]: c.show_supported_case()
Out[3]:
{'case': 'sample',
 'snake': 'convert_case',
 'kebab': 'convert-case',
 'camel': 'convertCase',
 'pascal': 'ConvertCase',
 'const': 'CONVERT_CASE',
 'sentence': 'Convert case',
 'title': 'Convert Case',
 'lower': 'convert case',
 'upper': 'CONVERT CASE'}

In [4]: c.convert_case('sentence', 'The sky is the limits')
Out[4]: 'The sky is the limits'

In [5]: c.convert_case('The sky is the limits')
Out[5]: 'the_sky_is_the_limits'

In [6]: c.convert_case('const', 'The sky is the limits')
Out[6]: 'THE_SKY_IS_THE_LIMITS'

In [7]: c.convert_case('camel', ['Good Morning','Thank you'])
Out[7]: ['goodMorning', 'thankYou']

In [8]:

StrCase class support str, list, dict.

data = "The sky is the limit"
expect = 'the-sky-is-the-limit'
s = StrCase(data)
assert s.convert_case('kebab') == expect

data = "The sky is the limit"
expect = 'theSkyIsTheLimit'
s = StrCase(data)
assert s.convert_case(case='camel') == expect

data = ["Good luck", "The sky is the limit" ]
expect = ["good_luck", "the_sky_is_the_limit"]
s = StrCase(data)
assert s.convert_case() == expect

data = {1: "Good luck", 2: "The sky is the limit" }
expect = {1: "good_luck", 2: "the_sky_is_the_limit" }
s = StrCase(data)
assert s.convert_case() == expect

data = {"Good luck": 1, "The sky is the limit": 2 }
expect = {"good_luck": 1, "the_sky_is_the_limit": 2 }
s = StrCase(data)
assert s.convert_case(replace_for='key') == expect

StrCase class support nested objects.

data = ["Good luck", "The sky is the limit",
        {1: "Good luck", 2: "The sky is the limit" } ]
expect = ["good_luck", "the_sky_is_the_limit",
        {1: "good_luck", 2: "the_sky_is_the_limit" } ]
s = StrCase(data)
assert s.convert_case() == expect

class uDict

support change keys for dict.

from scrapinghelerp.utils import uDict

data = uDict({ 'January': 1, 'February': 2, 'March': 3, 'April': 4 })
expect = { 'January': 1, 'February': 2, 'March': 3, 'Apr': 4 }
saved = data.copy()
result = data.replace_key('April', 'Apr')
assert ( result == expect and data == saved )

data = uDict({ 'January': 1, 'February': 2, 'March': 3, 'April': 4 })
replace = {'January': 'Jan', 'February': 'Feb' }
expect = { 'Jan': 1, 'Feb': 2, 'March': 3, 'April': 4 }
saved = data.copy()
result = data.replace_key_map(replace)
assert ( result == expect
         and data == saved )

data = uDict({ 'January': 1, 'February': 2, 'March': 3, 'April': 4 })
replace = {'January': 'Jan', 'February': 'Feb' }
expect = { 'Jan': 1, 'Feb': 2, 'March': 3, 'April': 4 }
saved = data.copy()
result = data.replace_key_map(replace)
assert ( result == expect and data == saved )

data = uDict({ 'January': 1, 'February': 2, 'March': 3, 'April': 4 })
replace = {'January': 'Jan', 'February': 'Feb' }
expect = { 'Jan': 1, 'Feb': 2, 'March': 3, 'April': 4 }
saved = data.copy()
data.replace_key_map(replace, inplace=True)
assert ( data == expect and data != saved )

class iDict

Immutable Dict. iDict is hashable object.

In [1] from scrapinghelerp.utils import uDict

In [2]: data = iDict({ 'January': 1, 'February': 2, 'March': 3, 'April': 4 })

In [3]: try:
   ...:     data['March']='Mar'
   ...: except TypeError as e:
   ...:     print(e)
   ...:
iDict object does not support item assignment

In [4]: hasattr(data, '__hash__')
Out[4]: True

In [5]: d = dict({data: 2})

In [6]: type(d)
Out[6]: dict

In [7]: d
Out[7]: {{'January': 1, 'February': 2, 'March': 3, 'April': 4}: 2}

In [8]: d[data]
Out[8]: 2

In [9]:

chnage_dict_keys()

Change keys for dict objects.

data = { 'January': 1, 'February': 2, 'March': 3, 'April': 4 }
replace = {'March': 3, 'April': 4 }
expect = { 'January': 1, 'February': 2, 3: 3, 4: 4 }
result = change_dict_keys(data, replace)
assert result == expect

data = { 'January': 1, 'February': 2, 'March': 3, 'April': 4 }
replace = {'April': 4, 'September': 9 }
expect = { 'January': 1, 'February': 2, 3: 3, 4: 4 }
saved = data.copy()
change_dict_keys(data, replace, inplace=True)
assert ( data == expect and data != saved )

split_chunks()

Return split into even chunk_size elements.

data = [11,12,13,14, 21,22,23,31,32,33]
expect = [[11,12,13, 14], [21,22,23,31], [32,33, None, None ]]
result = list(split_chunks(data,4))
assert result == expect

data = [11,12,13,14, 21,22,23,31,32,33]
expect = [[11,12,13, 14], [21,22,23,31], [32,33] ]
result = list(split_chunks(data,4, fill_na=False))
assert result == expect

data = [11,12,13,14, 21,22,23,31,32,33]
expect = [[11,12,13, 14], [21,22,23,31], [32,33, -1, -1] ]
result = list(split_chunks(data,4, na_value=-1))
assert result == expect

if pass tuple as input. return list of tuple for chunk data.

data = (11,12,13,21,22,23,31,32,33)
expect = [(11,12,13), (21,22,23), (31,32,33)]
result = list(split_chunks(data,3))
assert result == expect

if pass dict objects as input. return list of dict for chunk data. fill_na and na_value is always ignored.

data = { 'January': 1, 'February': 2, 'March': 3, 'April': 4 }
expect = [{ 'January': 1, 'February': 2, 'March': 3},
          { 'April': 4 } ]
result = list(split_chunks(data,3))
assert result == expect

data = { 'January': 1, 'February': 2, 'March': 3, 'April': 4 }
expect = [{ 'January': 1, 'February': 2, 'March': 3},
          { 'April': 4 } ]
result = list(split_chunks(data,3, fill_na=True))
assert result == expect

data = { 'January': 1, 'February': 2, 'March': 3, 'April': 4 }
expect = [{ 'January': 1, 'February': 2, 'March': 3},
          { 'April': 4 } ]
result = list(split_chunks(data,3, na_value=None))

if pass str objects as input. return list of str for chunk data. fill_na and na_value is always ignored.

data = "Peter Piper picked a peck of pickled peppers."
expect = [ "Peter Piper picked a",
           " peck of pickled pep",
           "pers." ]
result = list(split_chunks(data,20))
assert result == expect

data = "Peter Piper picked a peck of pickled peppers."
expect = [ "Peter Piper picked a",
           " peck of pickled pep",
           "pers." ]
result = list(split_chunks(data,20, fill_na=True, na_value=None))
assert result == expect

urange()

urange() is almost same as range()

expect = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
result = list(urange(10))
assert result == expect

expect = [1, 2, 3, 4, 5, 6, 7, 8, 9]
result = list(urange(1, 10))
assert result == expect

expect = [1, 3, 5, 7, 9]
result = list(urange(1, 10, 2))
assert result == expect

expect = [10, 8, 6, 4, 2]
result = list(urange(10, 1, -2))
assert result == expect

expect = [10, 9, 8, 7, 6, 5, 4, 3, 2]
result = list(urange(10, 1))
assert result == expect

urange() support callable as step.

def  gen_step(val):
    return (val * 3)

expect = [1, 4, 16]
result = list(urange(1, 20, gen_step))
assert result == expect

rename_duplicate()

Rename duplicate string for list or values of dict.

data = ["Apple", "Apple", "Banana", "Maple" ]
expect = ["Apple", "Apple_01", "Banana", "Maple" ]
result = rename_duplicates(data)
assert result == expect

data = ["Apple", "Apple", "Banana", "Maple" ]
expect = ["Apple", "Apple__01", "Banana", "Maple" ]
result = rename_duplicates(data, separator='__')
assert result == expect

data = ["Apple", "Apple", "Banana", "Maple" ]
expect = ["Apple", "Apple_001", "Banana", "Maple" ]
result = rename_duplicates(data, format="{:03}")
assert result == expect

data = ["Apple", ["Apple", "Apple", "Banana", "Maple" ]]
expect = ["Apple", ["Apple", "Apple_01", "Banana", "Maple" ]]
result = rename_duplicates(data)
assert result == expect

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