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Introduction to web scraping with Python

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Re: Introduction to web scraping with Python

#44

Post by ivansavz »

Loic wrote: post #19

It is making one mistake, it is parsing and scraping in the same loop. You should pull the data, store them and have another process accessing the data store and perform the parsing and understanding of the data. A "quick" parsing can be done to pull the links and build your frontier, but the data should be pulled and stored for the main parsing. This allows you to test your parsing routines independently of the targ…

For a simple caching solution that works well with requests, you can look at cachecontrol:

    from cachecontrol import CacheControl
    
    sess = requests.session()
    cached_sess = CacheControl(sess)
    response = cached_sess.get('http://google.com')
Very good for interactive debugging when you have to make multiple GET requests. First time you'll hit the webserver, after that it's all served from cache.

Re: Introduction to web scraping with Python

#45

Post by jacobush »

jacobush wrote: post #6
drej wrote: post #2

I love requests+lxml, use it fairly regularly, just a few quick notes: 1. lxml is way faster than BeautifulSoup - this may not matter if all you're waiting for is the network. But if you're parsing something on disk, this may be significant. 2. Don't forget to check the status code of r (r.status_code or less generally r.ok) 3. Those with a background in coding might prefer the .cssselect method available in whatever…

I had reason to gather news articles and extract keywords and authors - can't remember why I didn't use BeatifulSoup, because that was my first choice. In the end I used lxml with its html5parser: https://github.com/vonj/scraping Regarding legality - something frowned upon is putting load on servers. You may get blocked, rate limited or worse if you put too much strain on servers. Especially when you as I did, experi…

In that github repo there is an example squid config for caching permanently.

Re: Introduction to web scraping with Python

#46

Post by chinathrow »

I wonder how many folks using this will obey the robots.txt as explained nicely within the article:

"Robots

Web scraping is powerful, but with great power comes great responsibility. When you are scraping somebody’s website, you should be mindful of not sending too many requests. Most websites have a “robots.txt” which shows the rules that your web scraper should obey (which URLs are allowed to be scraped, which ones are not, the rate of requests you can send, etc.)."

Re: Introduction to web scraping with Python

#47

Post by vectorEQ »

lxml is nice. i would as suggested parse and scrape in different threads so you can speed up a bit, but it's not required per se. if you can't get the data you see on the website using lxml there might be ajax or other stuff implemented. to capture these streams / datas use a headless browser like phantomJS or so. Article looks good to me for 'simple' scrapings and is a good base to start playing with the concepts.

The nice thing about making a scraper from scratch like this is that you get to decide it's behaviour and fingerprint ,and you wont get blocked as some known scraperr. that being said, most people would appreiciate if you parse their robots.txt , but depending on your geographical locatin this might be an 'extra' step which isnt needed... (i'd advise to do it anyway if you are a friendly ;) and maybe put in user agent for requests something like 'i don't bite' to let ppl know you are benign...) if you get blocked while trying to scrape you can try to fake site into thinking you are browser just by setting user agent and other headrs appropriately. if you dont know which these are, open nc -nlvp 80 on your local machine and wget or firefox into it to see headers...

Deciding on good xpath or 'markers' to scrape can be automated, but it's often ,. if you need good accurate data from a singlular source, a good idea to manually go through the html and seek some good markers...

an alternate method of scraping is automating wget --recursive + links -dump to render html pages to txt output and grep or w/e these for what data you need... tons of methods can be devised... depending on your needs some will be more practical and stable than others.

saving files is only usefull if you need assurance on data quality and if you want to be able to tweak the results without having to re-request the data from the server. (just point to local data directory instead...). this way you can setup a harvester and parsers fr this datas.

if you want to scrape or harvest LARGE data sets consider a proxy network or something like a tor connection jugling docker instance or so to ensure rate limiting is not killing your hrvesters...

good luck have fun and don't kill peopels servers with your traffic spam, that's a dick move.... (throttle/humanise your scrapings...)

Re: Introduction to web scraping with Python

#48

Post by austincheney »

This is perhaps the fastest way to screenscrape a dynamically executed website.

1. First go get and run this code, which allows immediate gathering of all text nodes from the DOM: https://github.com/prettydiff/getNodesByType/blob/master/get...

2. Extract the text content from the text nodes and ignore nodes that contain only white space:

let text = document.getNodesByType(3), a = 0, b = text.length, output = []; do { if ((/^(\s+)$/).test(text[a].textContent) === false) { output.push(text[a].textContent); } a = a + 1; } while (a That will gather ALL text from the page. Since you are working from the DOM directly you can filter your results by various contextual and stylistic factors. Since this code is small and executes stupid fast it can be executed by bots easily.

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