Recursive crawling with BeautifulSoup really slow - python

I'm building a crawler that downloads all .pdf Files of a given website and its subpages. For this, I've used built-in functionalities around the below simplified recursive function that retrieves all links of a given URL.
However this becomes quite slow, the longer it crawls a given website (may take 2 minutes or longer per URL).
I can't quite figure out what's causing this and would really appreciate suggestions on what needs to be changed in order to increase the speed.
import re
import requests
from bs4 import BeautifulSoup
pages = set()
def get_links(page_url):
global pages
pattern = re.compile("^(/)")
html = requests.get(f"https://www.srs-stahl.de/{page_url}").text
soup = BeautifulSoup(html, "html.parser")
for link in soup.find_all("a", href=pattern):
if "href" in link.attrs:
if link.attrs["href"] not in pages:
new_page = link.attrs["href"]
print(new_page)
pages.add(new_page)
get_links(new_page)
get_links("")

It is not that easy to figure out what activly slow down your crawling - It is maybe the way you crawl, server of the website, ...
In your code, you request a URL, grab the links and call the functions itself in the first iteration, so you only append requested urls.
You may want to work with "queues" to keep the processes more transparent.
One advantage is that if the script aborts, you have this information stored and can access it to start from the urls you already have collected to visit. Quite the opposite of your for loop, which may have to start at an earlier point to ensure it get all urls.
Another point is, you request the PDF files, but without using the response in any way. Wouldn't it make more sense to either download and save them directly or skip the request and at least keep the links in separate "queue" for post processing?
Collected information in comparison - Based on iterations
Code in question:
pages --> 24
Example code (without delay):
urlsVisited --> 24
urlsToVisit --> 87
urlsToDownload --> 67
Example
Just to demonstrate, feel free to create defs, classes and structure to your needs. Note added some delay, but you can skip it if you like. "Queues" to demonstrate the process are lists but should be files, database,... to store your data safely.
import requests, time
from bs4 import BeautifulSoup
baseUrl = 'https://www.srs-stahl.de'
urlsToDownload = []
urlsToVisit = ["https://www.srs-stahl.de/"]
urlsVisited = []
def crawl(url):
html = requests.get(url).text
soup = BeautifulSoup(html, "html.parser")
for a in soup.select('a[href^="/"]'):
url = f"{baseUrl}{a['href']}"
if '.pdf' in url and url not in urlsToDownload:
urlsToDownload.append(url)
else:
if url not in urlsToVisit and url not in urlsVisited:
urlsToVisit.append(url)
while urlsToVisit:
url = urlsToVisit.pop(0)
try:
crawl(url)
except Exception as e:
print(f'Failed to crawl: {url} -> error {e}')
finally:
urlsVisited.append(url)
time.sleep(2)

Related

How to increase the speed of my program in Python?

I am working on a web scraping project, and I have to get links from 19062 facilities. If I use a for loop, it will take almost 3 hours to complete. I tried making a generator but failed to make any logic, and I am not sure that it can be done using a generator. So, is there any Python expert who has an idea to get what I want faster? In my code, I execute it for just 20 ids. Thanks
import requests, json
from bs4 import BeautifulSoup as bs
url = 'https://hilfe.diakonie.de/hilfe-vor-ort/marker-json.php?ersteller=&kategorie=0&text=& n=55.0815&e=15.0418321&s=47.270127&w=5.8662579&zoom=20000'
res = requests.get(url).json()
url_1 = 'https://hilfe.diakonie.de/hilfe-vor-ort/info-window-html.php?id='
# extracting all the id= from .json res object
id = []
for item in res['items'][0]["elements"]:
id.append(item["id"])
# opening a .json file and making a dict for links
file = open('links.json', 'a')
links = {'links': []}
def link_parser(url, id):
resp = requests.get(url + id).content
soup = bs(resp, "html.parser")
link = soup.select_one('p > a').attrs['href']
links['links'].append(link)
# dumping the dict into links.json file
for item in id[:20]:
link_parser(url_1, item)
json.dump(links, file)
file.close()
In web scraping, speed is not a good idea! You will be hitting the server numerous times a second and will most likely get blocked if you use a For Loop. A generator will not make this quicker. Ideally, you want to hit the server once and process the data locally.
If it were me, I would want to use a framework like Scrapy that encourages good practice and various Spider classes to support standard techniques.

Error while scraping image with beautifulsoup

The original code is here : https://github.com/amitabhadey/Web-Scraping-Images-using-Python-via-BeautifulSoup-/blob/master/code.py
So i am trying to adapt a Python script to collect pictures from a website to get better at web scraping.
I tried to get images from "https://500px.com/editors"
The first error was
The code that caused this warning is on line 12 of the file/Bureau/scrapper.py. To get rid of this warning, pass the additional argument
'features="lxml"' to the BeautifulSoup constructor.
So I did :
soup = BeautifulSoup(plain_text, features="lxml")
I also adapted the class to reflect the tag in 500px.
But now the script stopped running and nothing happened.
In the end it looks like this :
import requests
from bs4 import BeautifulSoup
import urllib.request
import random
url = "https://500px.com/editors"
source_code = requests.get(url)
plain_text = source_code.text
soup = BeautifulSoup(plain_text, features="lxml")
for link in soup.find_all("a",{"class":"photo_link "}):
href = link.get('href')
print(href)
img_name = random.randrange(1,500)
full_name = str(img_name) + ".jpg"
urllib.request.urlretrieve(href, full_name)
print("loop break")
What did I do wrong?
Actually the website is loaded via JavaScript using XHR request to the following API
So you can reach it directly via API.
Note that you can increase parameter rpp=50 to any number as you want for getting more than 50 result.
import requests
r = requests.get("https://api.500px.com/v1/photos?rpp=50&feature=editors&image_size%5B%5D=1&image_size%5B%5D=2&image_size%5B%5D=32&image_size%5B%5D=31&image_size%5B%5D=33&image_size%5B%5D=34&image_size%5B%5D=35&image_size%5B%5D=36&image_size%5B%5D=2048&image_size%5B%5D=4&image_size%5B%5D=14&sort=&include_states=true&include_licensing=true&formats=jpeg%2Clytro&only=&exclude=&personalized_categories=&page=1&rpp=50").json()
for item in r['photos']:
print(item['url'])
also you can access the image url itself in order to write it directly!
import requests
r = requests.get("https://api.500px.com/v1/photos?rpp=50&feature=editors&image_size%5B%5D=1&image_size%5B%5D=2&image_size%5B%5D=32&image_size%5B%5D=31&image_size%5B%5D=33&image_size%5B%5D=34&image_size%5B%5D=35&image_size%5B%5D=36&image_size%5B%5D=2048&image_size%5B%5D=4&image_size%5B%5D=14&sort=&include_states=true&include_licensing=true&formats=jpeg%2Clytro&only=&exclude=&personalized_categories=&page=1&rpp=50").json()
for item in r['photos']:
print(item['image_url'][-1])
Note that image_url key hold different img size. so you can choose your preferred one and save it. here I've taken the big one.
Saving directly:
import requests
with requests.Session() as req:
r = req.get("https://api.500px.com/v1/photos?rpp=50&feature=editors&image_size%5B%5D=1&image_size%5B%5D=2&image_size%5B%5D=32&image_size%5B%5D=31&image_size%5B%5D=33&image_size%5B%5D=34&image_size%5B%5D=35&image_size%5B%5D=36&image_size%5B%5D=2048&image_size%5B%5D=4&image_size%5B%5D=14&sort=&include_states=true&include_licensing=true&formats=jpeg%2Clytro&only=&exclude=&personalized_categories=&page=1&rpp=50").json()
result = []
for item in r['photos']:
print(f"Downloading {item['name']}")
save = req.get(item['image_url'][-1])
name = save.headers.get("Content-Disposition")[9:]
with open(name, 'wb') as f:
f.write(save.content)
Looking at the page you're trying to scrape I noticed something. The data doesn't appear to load until a few moments after the page finishes loading. This tells me that they're using a JS framework to load the images after page load.
Your scraper will not work with this page due to the fact that it does not run JS on the pages it's pulling. Running your script and printing out what plain_text contains proves this:
<a class='photo_link {{#if hasDetailsTooltip}}px_tooltip{{/if}}' href='{{photoUrl}}'>
If you look at the href attribute on that tag you'll see it's actually a templating tag used by JS UI frameworks.
Your options now are to either see what APIs they're calling to get this data (check the inspector in your web browser for network calls, if you're lucky they may not require authentication) or to use a tool that runs JS on pages. One tool I've seen recommended for this is selenium, though I've never used it so I'm not fully aware of its capabilities; I imagine the tooling around this would drastically increase the complexity of what you're trying to do.

Displaying all search results in Python web scraper

I am quite new to Python and am building a web scraper, which will scrape the following page and links in them: https://www.nalpcanada.com/Page.cfm?PageID=33
The problem is the page's default is to display the first 10 search results, however, I want to scrape all 150 search results (when 'All' is selected, there are 150 links).
I have tried messing around with the URL, but the URL remains static no matter what display results option is selected. I have also tried to look at the Network section of the Developer Tools on Chrome, but can't seem to figure out what to use to display all results.
Here is my code so far:
import bs4
import requests
import csv
import re
response = requests.get('https://www.nalpcanada.com/Page.cfm?PageID=33')
soup = bs4.BeautifulSoup(response.content, "html.parser")
urls = []
for a in soup.findAll('a', href=True, class_="employerProfileLink", text="Vancouver, British Columbia"):
urls.append(a['href'])
pagesToCrawl = ['https://www.nalpcanada.com/' + url + '&QuestionTabID=47' for url in urls]
for pages in pagesToCrawl:
html = requests.get(pages)
soupObjs = bs4.BeautifulSoup(html.content, "html.parser")
nameOfFirm = soupObjs.find('div', class_="ip-left").find('h2').next_element
tbody = soupObjs.find('div', {"id":"collapse8"}).find('tbody')
offers = tbody.find('td').next_sibling.next_sibling.next_element
seeking = tbody.find('tr').next_sibling.next_sibling.find('td').next_sibling.next_sibling.next_element
print('Firm name:', nameOfFirm)
print('Offers:', offers)
print('Seeking:', seeking)
print('Hireback Rate:', int(offers) / int(seeking))
Replacing your response call with this code seems to work. The reason is that you weren't passing in the cookie properly.
response = requests.get(
'https://www.nalpcanada.com/Page.cfm',
params={'PageID': 33},
cookies={'DISPLAYNUM': '100000000'}
)
The only other issue I came across was that a ValueError was being raised by this line when certain links (like YLaw Group) don't seem to have "offers" and/or "seeking".
print('Hireback Rate:', int(offers) / int(seeking))
I just commented out the line since you will have to decide what to do in those cases.

crawler (of my own design) cannot fetch more than 10 urls

I wrote a simple Python crawler to fetch urls from a website. Here is the code:
from bs4 import BeautifulSoup
import requests as req
def get_soup(url):
content = req.get(url).content
return BeautifulSoup(content,'lxml')
def extract_links(url):
soup = get_soup(url)
a_tags = soup.find_all('a', class_="kkyou true-load-invoker")
links = set(a_tag.get('href') for a_tag in a_tags)
return links
def set_of_links(url, size):
'''
breadth-first search for article hyperlinks
'''
seen = set()
active = extract_links(start_url)
while active:
next_active = set()
for item in active:
for result in extract_links(item):
if result not in seen:
if len(seen) >= size:
break
else:
seen.add(result)
next_active.add(result)
active = next_active
return seen
Essentially, I get a soup from a start url I specify, extract all urls within the start url that have class kkyou true-load-invoker and then I repeat the process in a breadth-first fashion for all urls I have collected. I stop this process when I have seen a certain number of urls.
Until a couple of weeks ago, I had no problem running this. I could specify any number of urls and it would fetch them for me. I just tried the exact same code today, and it only returns a maximum of 14 urls. For example, if I ask it to fetch me 50 urls, it will only fetch 10 and stop. Clearly, this cannot be a problem with the code because I changed nothing! I am wondering whether the page I am trying to crawl is using some mechanism to stop me from crawling an "excessive" number of pages. The page I am trying to crawl is this (choose any article as a start url).
Any insights on this will be greatly appreciated! I am a complete novice in web crawling.

Scrape title by only downloading relevant part of webpage

I would like to scrape just the title of a webpage using Python. I need to do this for thousands of sites so it has to be fast. I've seen previous questions like retrieving just the title of a webpage in python, but all of the ones I've found download the entire page before retrieving the title, which seems highly inefficient as most often the title is contained within the first few lines of HTML.
Is it possible to download only the parts of the webpage until the title has been found?
I've tried the following, but page.readline() downloads the entire page.
import urllib2
print("Looking up {}".format(link))
hdr = {'User-Agent': 'Mozilla/5.0',
'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
'Accept-Charset': 'ISO-8859-1,utf-8;q=0.7,*;q=0.3',
'Accept-Encoding': 'none',
'Accept-Language': 'en-US,en;q=0.8',
'Connection': 'keep-alive'}
req = urllib2.Request(link, headers=hdr)
page = urllib2.urlopen(req, timeout=10)
content = ''
while '</title>' not in content:
content = content + page.readline()
-- Edit --
Note that my current solution makes use of BeautifulSoup constrained to only process the title so the only place I can optimize is likely to not read in the entire page.
title_selector = SoupStrainer('title')
soup = BeautifulSoup(page, "lxml", parse_only=title_selector)
title = soup.title.string.strip()
-- Edit 2 --
I've found that BeautifulSoup itself splits the content into multiple strings in the self.current_data
variable (see this function in bs4), but I'm unsure how to modify the code to basically stop reading all remaining content after the title has been found. One issue could be that redirects should still work.
-- Edit 3 --
So here's an example. I have a link www.xyz.com/abc and I have to follow this through any redirects (almost all of my links use a bit.ly kind of link shortening). I'm interested in both the title and domain that occurs after any redirections.
-- Edit 4 --
Thanks a lot for all of your assistance! The answer by Kul-Tigin works very well and has been accepted. I'll keep the bounty until it runs out though to see if a better answer comes up (as shown by e.g. a time measurement comparison).
-- Edit 5 --
For anyone interested: I've timed the accepted answer to be roughly twice as fast as my existing solution using BeautifulSoup4.
You can defer downloading the entire response body by enabling stream mode of requests.
Requests 2.14.2 documentation - Advanced Usage
By default, when you make a request, the body of the response is
downloaded immediately. You can override this behaviour and defer
downloading the response body until you access the Response.content
attribute with the stream parameter:
...
If you set stream to True when making a request, Requests cannot release the connection back to the pool unless you consume all the data or call Response.close.
This can lead to inefficiency with connections. If you find yourself partially reading request bodies (or not reading them at all) while using stream=True, you should consider using contextlib.closing (documented here)
So, with this method, you can read the response chunk by chunk until you encounter the title tag. Since the redirects will be handled by the library you'll be ready to go.
Here's an error-prone code tested with Python 2.7.10 and 3.6.0:
try:
from HTMLParser import HTMLParser
except ImportError:
from html.parser import HTMLParser
import requests, re
from contextlib import closing
CHUNKSIZE = 1024
retitle = re.compile("<title[^>]*>(.*?)</title>", re.IGNORECASE | re.DOTALL)
buffer = ""
htmlp = HTMLParser()
with closing(requests.get("http://example.com/abc", stream=True)) as res:
for chunk in res.iter_content(chunk_size=CHUNKSIZE, decode_unicode=True):
buffer = "".join([buffer, chunk])
match = retitle.search(buffer)
if match:
print(htmlp.unescape(match.group(1)))
break
Question: ... the only place I can optimize is likely to not read in the entire page.
This does not read the entire page.
Note: Unicode .decode() will raise Exception if you cut a Unicode sequence in the middle. Using .decode(errors='ignore') remove those sequences.
For instance:
import re
try:
# PY3
from urllib import request
except:
import urllib2 as request
for url in ['http://www.python.org/', 'http://www.google.com', 'http://www.bit.ly']:
f = request.urlopen(url)
re_obj = re.compile(r'.*(<head.*<title.*?>(.*)</title>.*</head>)',re.DOTALL)
Found = False
data = ''
while True:
b_data = f.read(4096)
if not b_data: break
data += b_data.decode(errors='ignore')
match = re_obj.match(data)
if match:
Found = True
title = match.groups()[1]
print('title={}'.format(title))
break
f.close()
Output:
title=Welcome to Python.org
title=Google
title=Bitly | URL Shortener and Link Management Platform
Tested with Python: 3.4.2 and 2.7.9
You're scraping webpages using standard REST requests and I'm not aware of any request that only returns the title, so I don't think it's possible.
I know this doesn't necessarily help get the title only, but I usually use BeautifulSoup for any web scraping. It's much easier. Here's an example.
Code:
import requests
from bs4 import BeautifulSoup
urls = ["http://www.google.com", "http://www.msn.com"]
for url in urls:
r = requests.get(url)
soup = BeautifulSoup(r.text, "html.parser")
print "Title with tags: %s" % soup.title
print "Title: %s" % soup.title.text
print
Output:
Title with tags: <title>Google</title>
Title: Google
Title with tags: <title>MSN.com - Hotmail, Outlook, Skype, Bing, Latest News, Photos & Videos</title>
Title: MSN.com - Hotmail, Outlook, Skype, Bing, Latest News, Photos & Videos
the kind of thing you want i don't think can be done, since the way the web is set up, you get the response for a request before anything is parsed. there isn't usually a streaming "if encounter <title> then stop giving me data" flag. if there is id love to see it, but there is something that may be able to help you. keep in mind, not all sites respect this. so some sites will force you to download the entire page source before you can act on it. but a lot of them will allow you to specify a range header. so in a requests example:
import requests
targeturl = "http://www.urbandictionary.com/define.php?term=Blarg&page=2"
rangeheader = {"Range": "bytes=0-150"}
response = requests.get(targeturl, headers=rangeheader)
response.text
and you get
'<!DOCTYPE html>\n<html lang="en-US" prefix="og: http://ogp.me/ns#'
now of course here's the problems with this
what if you specify a range that is too short to get the title of the page?
whats a good range to aim for? (combination of speed and assurance of accuracy)
what happens if the page doesn't respect Range? (most of the time you just get the whole response you would have without it.)
i don't know if this might help you? i hope so. but i've done similar things to only get file headers for download checking.
EDIT4:
so i thought of another kind of hacky thing that might help. nearly every page has a 404 page not found page. we might be able to use this to our advantage. instead of requesting the regular page. request something like this.
http://www.urbandictionary.com/nothing.php
the general page will have tons of information, links, data. but the 404 page is nothing more than a message, and (in this case) a video. and usually there is no video. just some text.
but you also notice that the title still appears here. so perhaps we can just request something we know does not exist on any page like.
X5ijsuUJSoisjHJFk948.php
and get a 404 for each page. that way you only download a very small and minimalistic page. nothing more. which will significantly reduce the amount of information you download. thus increasing speed and efficiency.
heres the problem with this method: you need to check somehow if the page does not supply its own version of the 404. most pages have it because it looks good with the site. and its standard practice to include one. but not all of them do. make sure to handle this case.
but i think that could be something worth trying out. over the course of thousands of sites, it would save many ms of download time for each html.
EDIT5:
so as we talked about, since you are interested in urls that redirect. we might make use of an http head reqeust. which wont get the site content. just the headers. so in this case:
response = requests.head('http://myshortenedurl.com/5b2su2')
replace my shortenedurl with tunyurl to follow along.
>>>response
<Response [301]>
nice so we know this redirects to something.
>>>response.headers['Location']
'http://stackoverflow.com'
now we know where the url redirects to without actually following it or downloading any page source. now we can apply any of the other techniques previously discussed.
Heres an example, using requests and lxml modules and using the 404 page idea. (be aware, i have to replace bit.ly with bit'ly so stack overflow doesnt get mad.)
#!/usr/bin/python3
import requests
from lxml.html import fromstring
links = ['http://bit'ly/MW2qgH',
'http://bit'ly/1x0885j',
'http://bit'ly/IFHzvO',
'http://bit'ly/1PwR9xM']
for link in links:
response = '<Response [301]>'
redirect = ''
while response == '<Response [301]>':
response = requests.head(link)
try:
redirect = response.headers['Location']
except Exception as e:
pass
fakepage = redirect + 'X5ijsuUJSoisjHJFk948.php'
scrapetarget = requests.get(fakepage)
tree = fromstring(scrapetarget.text)
print(tree.findtext('.//title'))
so here we get the 404 pages, and it will follow any number of redirects. now heres the output from this:
Urban Dictionary error
Page Not Found - Stack Overflow
Error 404 (Not Found)!!1
Kijiji: Page Not Found
so as you can see we did indeed get out titles. but we see some problems with the method. namely some titles add things, and some just dont have a good title at all. and thats the issue with that method. we could however try the range method too. benefits of that would be the title would be correct, but sometimes we might miss it, and sometimes we have to download the whole pagesource to get it. increasing required time.
Also credit to alecxe for this part of my quick and dirty script
tree = fromstring(scrapetarget.text)
print(tree.findtext('.//title'))
for an example with the range method. in the loop for link in links: change the code after the try catch statement to this:
rangeheader = {"Range": "bytes=0-500"}
scrapetargetsection = requests.get(redirect, headers=rangeheader)
tree = fromstring(scrapetargetsection.text)
print(tree.findtext('.//title'))
output is:
None
Stack Overflow
Google
Kijiji: Free Classifieds in...
here we see urban dictionary has no title or ive missed it in the bytes returned. in any of these methods there are tradeoffs. the only way to get close to total accuracy would be to download the entire source for each page i think.
using urllib you can set the Range header to request a certain range of bytes, but there are some consequences:
it depends on the server to honor the request
you assume that data you're looking for is within desired range (however you can make another request using different range header to get next bytes - i.e. download first 300 bytes and get another 300 only if you can't find title within first result - 2 requests of 300 bytes are still much cheaper than whole document)
(edit) - to avoid situations when title tag splits between two ranged requests, make your ranges overlapped, see 'range_header_overlapped' function in my example code
import urllib
req = urllib.request.Request('http://www.python.org/')
req.headers['Range']='bytes=%s-%s' % (0, 300)
f = urllib.request.urlopen(req)
just to verify if server accepted our range:
content_range=f.headers.get('Content-Range')
print(content_range)
my code also solves cases when title tag is splitted between chunks.
#!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Tue May 30 04:21:26 2017
====================
#author: s
"""
import requests
from string import lower
from html.parser import HTMLParser
#proxies = { 'http': 'http://127.0.0.1:8080' }
urls = ['http://opencvexamples.blogspot.com/p/learning-opencv-functions-step-by-step.html',
'http://www.robindavid.fr/opencv-tutorial/chapter2-filters-and-arithmetic.html',
'http://blog.iank.org/playing-capitals-with-opencv-and-python.html',
'http://docs.opencv.org/3.2.0/df/d9d/tutorial_py_colorspaces.html',
'http://scikit-image.org/docs/dev/api/skimage.exposure.html',
'http://apprize.info/programming/opencv/8.html',
'http://opencvexamples.blogspot.com/2013/09/find-contour.html',
'http://docs.opencv.org/2.4/modules/imgproc/doc/geometric_transformations.html',
'https://github.com/ArunJayan/OpenCV-Python/blob/master/resize.py']
class TitleParser(HTMLParser):
def __init__(self):
HTMLParser.__init__(self)
self.match = False
self.title = ''
def handle_starttag(self, tag, attributes):
self.match = True if tag == 'title' else False
def handle_data(self, data):
if self.match:
self.title = data
self.match = False
def valid_content( url, proxies=None ):
valid = [ 'text/html; charset=utf-8',
'text/html',
'application/xhtml+xml',
'application/xhtml',
'application/xml',
'text/xml' ]
r = requests.head(url, proxies=proxies)
our_type = lower(r.headers.get('Content-Type'))
if not our_type in valid:
print('unknown content-type: {} at URL:{}'.format(our_type, url))
return False
return our_type in valid
def range_header_overlapped( chunksize, seg_num=0, overlap=50 ):
"""
generate overlapping ranges
(to solve cases when title tag splits between them)
seg_num: segment number we want, 0 based
overlap: number of overlaping bytes, defaults to 50
"""
start = chunksize * seg_num
end = chunksize * (seg_num + 1)
if seg_num:
overlap = overlap * seg_num
start -= overlap
end -= overlap
return {'Range': 'bytes={}-{}'.format( start, end )}
def get_title_from_url(url, proxies=None, chunksize=300, max_chunks=5):
if not valid_content(url, proxies=proxies):
return False
current_chunk = 0
myparser = TitleParser()
while current_chunk <= max_chunks:
headers = range_header_overlapped( chunksize, current_chunk )
headers['Accept-Encoding'] = 'deflate'
# quick fix, as my locally hosted Apache/2.4.25 kept raising
# ContentDecodingError when using "Content-Encoding: gzip"
# ContentDecodingError: ('Received response with content-encoding: gzip, but failed to decode it.',
# error('Error -3 while decompressing: incorrect header check',))
r = requests.get( url, headers=headers, proxies=proxies )
myparser.feed(r.content)
if myparser.title:
return myparser.title
current_chunk += 1
print('title tag not found within {} chunks ({}b each) at {}'.format(current_chunk-1, chunksize, url))
return False

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