I am building a python based webscraper that scrapes price and specification data for products from multiple sites. I want to be respectful and follow the robots.txt as much as I can.
Lets say the crawl delay defined in the robots.txt file is 10 seconds. How is this interpreted? I built my scraper to go to each product category page and then take the list of all products from each category and then go into each individual product page and scrape price and specifications.
Does each page request need to be delayed by 10 seconds? Or is the act of running my script once considered one action and I just need to wait 10s each time I run it?
If it is the former then how does anyone scrape large amounts of data from a site? If there are 5000 product pages and I delay each one by 10 seconds then my script will take 14hrs for a single run.
What if I split the work between multiple scripts? Does each separate script need to follow the rule by itself or do all requests from a certain IP need to follow the rule collectively?
I don't want to get my IP banned or accidentally take down anyone's site. Thanks in advance for any answers.
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It means that you should put a delay of 10 seconds between each of the requests to that particular site. For more information, you can read this article
https://www.contentkingapp.com/academy/robotstxt/#crawl-delay
Preferably, you should use some framework to crawl the sites, like scrapy. They provide you a download delay option and make sure that the crawling engine delays each request by that much amount of time.
Related
I have a list from approx. 36,000 URLs, ranging from https://www.fff.fr/la-vie-des-clubs/1/infos-cles to https://www.fff.fr/la-vie-des-clubs/36179/infos-cles (a few of those pages return 404 erros).
Each of those pages contains a number (the number of teams the soccer club contains). In the HTML file, the number appears as <p class="number">5</p>.
Is there a reasonably simple way to compile an excel or csv file with the URL and the associated number of teams as a field ?
I've tried looking into phantomJS but my method took 10 seconds to open a single webpage and I don't really want to spend 100 hours doing this. I was not able to figure out how (or whether it was at all possible) to use scraping tools such as import.io to do this.
Thanks !
For the goal you want to achieve, I can see two solutions:
Code it in Java: Jsoup + any CSV library
In a few minutes, the 36000+ urls can be downloaded easily.
Use a tool like Portia from scrapinghub.com
Portia is a WYSIWYG tool quickly helping you create your project and run it. They offer a free plan which can take in charge the 36000+ links.
This question relates to WordPress's wp-cron function but is general enough to apply to any DB-intensive calculation.
I'm creating a site theme that needs to calculate a time-decaying rating for all content in the system at regular intervals. This rating determines the order of posts on the homepage, which is paged to allow visitors to potentially view all content. This rating value needs to be calculated frequently to make sure the site has fresh content listed in the proper order.
The rating calculation is not heavy but the rating needs to be calculated for, potentially, 1,000s of items and doing that hourly via wp-cron will start to cause problems for sites with lots of content. Ignoring the impact on page load (wp-cron processes requests on page loads once a certain interval has been reached), at some point the script will reach a time limit. Setting up the site to use "plain ol' cron" will solve the page loading issue but not the timeout one.
Assuming that I have no control over the sites that this will run on, what's the best way to handle this rating calculation on a regular basis? A few things that came to mind:
Only calculate the rating for the most recent 1,000 posts, assuming that the rest won't be seen much. I don't like the idea of ignoring all old content, though.
Calculate the first, say, 100 or so, then only calculate the rating for older groups if those pages are loaded. This might be hard to get right, though, and lead to incorrect listing and ratings (which isn't a huge problem for older content but something I'd like to avoid)
Batch process 100 or so at regular intervals, keeping track of the last one processed. This would cycle through the whole body of content eventually.
Any other ideas? Thanks in advance!
Depending on the host, you're in for a potentially sticky situation. Let me outline a couple of ideal cases and you can pick/choose where you need to.
Option 1
Mirror the database first and use a secondary app (WordPress or otherwise) to do the calculations asynchronously against that DB mirror. When they're done, they can update a static file in the project root, write data to a shared Memcached instance, trigger a POST to WordPress' admin_post endpoint to write some internal state, whatever.
The idea here is that you're removing your active site from the equation. The last thing you want to do is have a costly cron job lock the live site's database or cause queries to slow down as it does its indexing.
Option 2
Offload the calculation entirely to a separate application. Tracking ratings in real time with WordPress is a poor idea as it bypasses page caching and triggers an uncachable request every time a new rating comes in. Pushing this off to a second server means your WordPress site is super fast, and it also means you can have the second server do the calculations for you in the first place.
If you're already using something like Elastic Search on the site, you can add ratings as an added indexing facet. Then just update posts as ratings change, and use the ES API to query most popular posts later.
Alternatively, you can use a hosted service like Keen IO to record and aggregate ratings.
Option 3
Still use cron, but don't schedule it as a cron job in WordPress. Instead, write a WP CLI routine that does the reindexing for you. Then, schedule real cron jobs to process the job.
This has the advantage of using PHP's command line version, which can be configured to skip the timeouts and memory limits imposed on the FPM/CGI/whatever version used to serve the site. It also means you don't have to wait for site traffic to trigger the job - and a long-running job won't block other cron events within WordPress from firing.
If using this process, I would set the job to run hourly and, each hour, run a batch of 1/24th of the total posts in the database. You can keep track of offsets or even processed post IDs in the database, the point is just that you're silently re-indexing posts throughout the day.
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I'd like to fetch results from Google using curl to detect potential duplicate content.
Is there a high risk of being banned by Google?
Google disallows automated access in their TOS, so if you accept their terms you would break them.
That said, I know of no lawsuit from Google against a scraper.
Even Microsoft scraped Google, they powered their search engine Bing with it. They got caught in 2011 red handed :)
There are two options to scrape Google results:
1) Use their API
UPDATE 2020: Google has reprecated previous APIs (again) and has new
prices and new limits. Now
(https://developers.google.com/custom-search/v1/overview) you can
query up to 10k results per day at 1,500 USD per month, more than that
is not permitted and the results are not what they display in normal
searches.
You can issue around 40 requests per hour You are limited to what
they give you, it's not really useful if you want to track ranking
positions or what a real user would see. That's something you are not
allowed to gather.
If you want a higher amount of API requests you need to pay.
60 requests per hour cost 2000 USD per year, more queries require a
custom deal.
2) Scrape the normal result pages
Here comes the tricky part. It is possible to scrape the normal result pages.
Google does not allow it.
If you scrape at a rate higher than 8 (updated from 15) keyword requests per hour you risk detection, higher than 10/h (updated from 20) will get you blocked from my experience.
By using multiple IPs you can up the rate, so with 100 IP addresses you can scrape up to 1000 requests per hour. (24k a day) (updated)
There is an open source search engine scraper written in PHP at http://scraping.compunect.com
It allows to reliable scrape Google, parses the results properly and manages IP addresses, delays, etc.
So if you can use PHP it's a nice kickstart, otherwise the code will still be useful to learn how it is done.
3) Alternatively use a scraping service (updated)
Recently a customer of mine had a huge search engine scraping requirement but it was not 'ongoing', it's more like one huge refresh per month.
In this case I could not find a self-made solution that's 'economic'.
I used the service at http://scraping.services instead.
They also provide open source code and so far it's running well (several thousand resultpages per hour during the refreshes)
The downside is that such a service means that your solution is "bound" to one professional supplier, the upside is that it was a lot cheaper than the other options I evaluated (and faster in our case)
One option to reduce the dependency on one company is to make two approaches at the same time. Using the scraping service as primary source of data and falling back to a proxy based solution like described at 2) when required.
Google will eventually block your IP when you exceed a certain amount of requests.
Google thrives on scraping websites of the world...so if it was "so illegal" then even Google won't survive ..of course other answers mention ways of mitigating IP blocks by Google. One more way to explore avoiding captcha could be scraping at random times (dint try) ..Moreover, I have a feeling, that if we provide novelty or some significant processing of data then it sounds fine at least to me...if we are simply copying a website.. or hampering its business/brand in some way...then it is bad and should be avoided..on top of it all...if you are a startup then no one will fight you as there is no benefit.. but if your entire premise is on scraping even when you are funded then you should think of more sophisticated ways...alternative APIs..eventually..Also Google keeps releasing (or depricating) fields for its API so what you want to scrap now may be in roadmap of new Google API releases..
Being lazy, I'm trying to use scrapy instead of implementing my own scraping service using celery+requests (been there, done that). Let's say I have a list of N pages that I like to monitor. After retrieving page X and reading its content, I want to tell the system to rescan it sometime later (depending on its content), say once two hours have passed.
Is such a thing possible with Scrapy?
Considering that most languages have webscraping functionality either built in, or made by others, this is more of a general web-scraping question.
I have a site in which I would like to pull information from about 6 different pages. This normally would not be that bad; unfortunately though, the information on these pages changes roughly every ten seconds, which could mean over 2000 queries an hour (which is simply not okay). There is no api to the website I have in mind either. Is there any possible efficient way to get the amount of information I need without flooding them with requests, or am I out of luck?
At best, the site might return you an HTTP 304 Not Modified in its header when you make a request - indicating that you need not download the page, as nothing has changed. If the site is set up to do so, this might help decrease bandwidth, but would still require the same number of requests.
If there's a consistent update schedule, then at least you know when to make the requests - but you'll still have to ask (i.e.: make a request) to find out what information has changed.