5 ms·

Scrapism

121 points by cjlm 4y ago

niharikajoshi 4y ago
[dead]
niharikajoshi 4y ago
quyleanh 4y ago
I usually create some small scraping script for my daily life. - Getting all comic's image and converting to e-book for my Kindle. - Surveying info for buying new house. - Helping my wife in collecting data for her new writing. - Transferring all my Facebook fanpage post to my personal blog And I did enjoyed my journey in scraping thing to make my life easier and full of joy.
- gtsnexp 4y ago
  Wonderful, are you also sharing your scripts with everyone?
  - quyleanh 4y ago
    Not yet. But I have plan about writing a blog about these scripts.
fjallstrom 4y ago
Was happy to find that the person behind it Sam Lavigne, one of the people behind Stupid Hackathon.
simonw 4y ago
A trick I think would be useful to include here is running scrapers in GitHub Actions that write their results back to the repository. This is free(!) to host, and the commit log gives an enormous amount of detail about how the scraped resource changed over time. I wrote more about this trick here: https://simonwillison.net/2020/Oct/9/git-scraping/ https://simonwillison.net/2020/Oct/9/git-scraping/ Here are 267 repos that are using it: https://github.com/topics/git-scraping?o=desc&s=updated https://github.com/topics/git-scraping?o=desc&s=updated
- ornornor 4y ago
  There is a repo on GH that basically does this and can be used as a currency conversion API (with historical rates). It scrapes all values once a day with actions, commits it, and you can then query it with a cdn. https://github.com/fawazahmed0/currency-api https://github.com/fawazahmed0/currency-api
- sackerhews 4y ago
  Honorable mention even if he doesn't use Actions: https://github.com/elsamuko/Shirt-without-Stripes https://github.com/elsamuko/Shirt-without-Stripes
- Labo333 4y ago
  Interesting! Any idea of how likely Github ips are to be blocked?
- electroly 4y ago
  I feel like this is bad manners. The runners are a shared resource and you risk getting their IPs blacklisted by the sites you're scraping. I think a strict reading of the GitHub Actions TOS may prohibit this sort of usage, too. > ... for example, don't use Actions as a content delivery network or as part of a serverless application ... > Actions should not be used for: ... any other activity unrelated to the production, testing, deployment, or publication of the software project associated with the repository where GitHub Actions are used. > You may only access and use GitHub Actions to develop and test your application(s). https://docs.github.com/en/site-policy/github-terms/github-terms-for-additional-products-and-features https://docs.github.com/en/site-policy/github-terms/github-t...
  - jamessb 4y ago
    I initially had similar concerns, but the idea seems to be endorsed by the GitHub Developer Experience team: https://githubnext.com/projects/flat-data/ https://githubnext.com/projects/flat-data/
- saaaam 4y ago
  Hi Simon! I'll definitely consider adding that in. Also, I love Datasette!
rpastuszak 4y ago
Tangentially related question: Is Python still the most common tool used for web scraping and if so, what's the advantage over jsdom/cheerio or, say a headless browser based tool like puppeteer? I've been using these tools for years, but I grew up in the JS world, so I'd be curious to hear people with different backgrounds/biases than mine:)
- marban 4y ago
  For low-level stuff where you don't need the overhead of puppeteer, I doubt that there's a better solution. I do pretty much anything with https://www.python-httpx.org https://www.python-httpx.org these days.
- dec0dedab0de 4y ago
  Is Python still the most common tool used for web scraping and if so, what's the advantage over jsdom/cheerio or, say a headless browser based tool like puppeteer? I'm a bit of a Python zealot, but if you prefer JS then use JS. The best tool is the one you know. I think Python became the scraping language because many people thought it was significantly easier to use than Perl, and Perl was on top because it was significantly easier than shell scripting. Any language that is incrementally easier, or better in other aspects wont inspire people to learn something new. If we had node 15 years ago, maybe it would have been JS. As far as headless browsers, selenium has official Python bindings. Though I kind of consider that cheating. For my personal taste, I choose Python because I can write it off the top of my head without making syntax errors, or leaning on an IDE. It's the only language I can do that with, and I've been able to do it since about a month into using it.
1vuio0pswjnm7 4y ago
This is from 2020. Besides a small change to the "Introduction to the Command Line" section, it has not been updated. Back in 2015, the author reported using CasperJS to scrape public LinkedIn profiles. The author reported this was a PITA. Here the author recommends using WebDriver implementations, e.g., chromedriver or geckodriver, in addition to scripting language frameworks such as Puppeteer and Selenium. Is scraping LinkedIn still a PITA. Because the examples given are always relatively simple, i.e., not LinkedIn, I am skeptical when I see "web scraping" tutorials using Python frameworks and cURL as the only recommended option for automated public data/information retrieval from the www.[FN1,2] I use none of the above. For small tasks like the examples given in these tutorials, the approaches I use are not nearly as sophisticated/complicated and yet they are faster and use fewer resources than using Python and/or cURL. They are also easier to update if something changes. That is in part because (1) the binaries I use are smaller, (2) I do not rely on scripting languages[FN3] and third party libraries (and so much less code involved), (3) the programs I use start working immediately whereas Python takes seconds to start up and (4) compared to the programs I use, cURL as a means of sending HTTP requests is inflexible, e.g., one is limited to what "options" cURL provides and cURL has no option for HTTP/1.1 pipelining. 1. LinkedIn's so-called "technological measures" to prevent retrieval of public information have failed. Similarly, its attempts to prevent retrieval of public information through intimidation, e.g., cease-and-desist letters and threats of CFAA claims, have failed. Tutorials on "web scraping" that extol Python frameworks should use LinkedIn as an example instead of trivial examples for which using Python is, IMHO, overkill. 2. What would be more interesting is a Rosetta Code for "web scraping" tasks. There are many, many ways to do public data/information retrieval from the www. Using scripting languages such as Python, Ruby, NodeJS, etc. and frameworks are one way. That approach may be ideally suited for large scale jobs, like those undertaken by what the author calls "internet companies". But for smaller tasks undertaken by individual www users for noncommercial purposes, e.g., this author's concept of "scrapism", there are also faster, less complicated and more efficient options. 3. Other than the Almquist shell
- saaaam 4y ago
  Hi - I'd be interested to hear more details about what approaches you suggest!
Labo333 4y ago
Good guide! The "Scraping XHR" [1] explains how to inspect network requests and reproduce them with Python. I actually built har2requests [2] to automate that process! [1]: https://scrapism.lav.io/scraping-xhr/ https://scrapism.lav.io/scraping-xhr/ [2]: https://github.com/louisabraham/har2requests https://github.com/louisabraham/har2requests
- saaaam 4y ago
  Thanks for sharing this - I'll check it out!
saaaam 4y ago
Hi! This is a guide that I started during the pandemic but never quite finished. I’m in the process of re-writing/re-recording some parts of it to bring it back up to date, and adding in the bits that are still missing.
CWuestefeld 4y ago
I'm bothered that this doesn't mention any of the ethics involved, such as checking the robots.txt file and so forth. More than half of my traffic is from bots, so I'm paying something like half my operational expenses to support them. And we've had to do a lot of work to mitigate what would otherwise be DoS attacks from badly written (or badly intended!) bots. I think that at least a tip of the hat to avoiding damage would be appropriate in a piece like this.
helsinki 4y ago
Hi Sam, It might be worth adding a section on distributed anonymous scrapers that use some form of messaging middleware to distribute the URLs to scrape. Regarding the anonymous aspect (independent of job distribution, of course), you could walk them through using https://github.com/aaronsw/pytorctl https://github.com/aaronsw/pytorctl or even a rotating tor proxy. This is how I scraped all those Instagram locations + metadata we discussed about five years ago. Hope you’re doing well!

Scrapism

121 points by cjlm 4y ago

niharikajoshi 4y ago

[dead]

niharikajoshi 4y ago

quyleanh 4y ago

I usually create some small scraping script for my daily life. - Getting all comic's image and converting to e-book for my Kindle. - Surveying info for buying new house. - Helping my wife in collecting data for her new writing. - Transferring all my Facebook fanpage post to my personal blog And I did enjoyed my journey in scraping thing to make my life easier and full of joy.

gtsnexp 4y ago
Wonderful, are you also sharing your scripts with everyone?
- quyleanh 4y ago
  Not yet. But I have plan about writing a blog about these scripts.

fjallstrom 4y ago

Was happy to find that the person behind it Sam Lavigne, one of the people behind Stupid Hackathon.

simonw 4y ago

A trick I think would be useful to include here is running scrapers in GitHub Actions that write their results back to the repository. This is free(!) to host, and the commit log gives an enormous amount of detail about how the scraped resource changed over time. I wrote more about this trick here: https://simonwillison.net/2020/Oct/9/git-scraping/ https://simonwillison.net/2020/Oct/9/git-scraping/ Here are 267 repos that are using it: https://github.com/topics/git-scraping?o=desc&s=updated https://github.com/topics/git-scraping?o=desc&s=updated

ornornor 4y ago
There is a repo on GH that basically does this and can be used as a currency conversion API (with historical rates). It scrapes all values once a day with actions, commits it, and you can then query it with a cdn. https://github.com/fawazahmed0/currency-api https://github.com/fawazahmed0/currency-api
sackerhews 4y ago
Honorable mention even if he doesn't use Actions: https://github.com/elsamuko/Shirt-without-Stripes https://github.com/elsamuko/Shirt-without-Stripes
Labo333 4y ago
Interesting! Any idea of how likely Github ips are to be blocked?
electroly 4y ago
I feel like this is bad manners. The runners are a shared resource and you risk getting their IPs blacklisted by the sites you're scraping. I think a strict reading of the GitHub Actions TOS may prohibit this sort of usage, too. > ... for example, don't use Actions as a content delivery network or as part of a serverless application ... > Actions should not be used for: ... any other activity unrelated to the production, testing, deployment, or publication of the software project associated with the repository where GitHub Actions are used. > You may only access and use GitHub Actions to develop and test your application(s). https://docs.github.com/en/site-policy/github-terms/github-terms-for-additional-products-and-features https://docs.github.com/en/site-policy/github-terms/github-t...
- jamessb 4y ago
  I initially had similar concerns, but the idea seems to be endorsed by the GitHub Developer Experience team: https://githubnext.com/projects/flat-data/ https://githubnext.com/projects/flat-data/
saaaam 4y ago
Hi Simon! I'll definitely consider adding that in. Also, I love Datasette!

rpastuszak 4y ago

Tangentially related question: Is Python still the most common tool used for web scraping and if so, what's the advantage over jsdom/cheerio or, say a headless browser based tool like puppeteer? I've been using these tools for years, but I grew up in the JS world, so I'd be curious to hear people with different backgrounds/biases than mine:)

marban 4y ago
For low-level stuff where you don't need the overhead of puppeteer, I doubt that there's a better solution. I do pretty much anything with https://www.python-httpx.org https://www.python-httpx.org these days.
dec0dedab0de 4y ago
Is Python still the most common tool used for web scraping and if so, what's the advantage over jsdom/cheerio or, say a headless browser based tool like puppeteer? I'm a bit of a Python zealot, but if you prefer JS then use JS. The best tool is the one you know. I think Python became the scraping language because many people thought it was significantly easier to use than Perl, and Perl was on top because it was significantly easier than shell scripting. Any language that is incrementally easier, or better in other aspects wont inspire people to learn something new. If we had node 15 years ago, maybe it would have been JS. As far as headless browsers, selenium has official Python bindings. Though I kind of consider that cheating. For my personal taste, I choose Python because I can write it off the top of my head without making syntax errors, or leaning on an IDE. It's the only language I can do that with, and I've been able to do it since about a month into using it.

1vuio0pswjnm7 4y ago

This is from 2020. Besides a small change to the "Introduction to the Command Line" section, it has not been updated. Back in 2015, the author reported using CasperJS to scrape public LinkedIn profiles. The author reported this was a PITA. Here the author recommends using WebDriver implementations, e.g., chromedriver or geckodriver, in addition to scripting language frameworks such as Puppeteer and Selenium. Is scraping LinkedIn still a PITA. Because the examples given are always relatively simple, i.e., not LinkedIn, I am skeptical when I see "web scraping" tutorials using Python frameworks and cURL as the only recommended option for automated public data/information retrieval from the www.[FN1,2] I use none of the above. For small tasks like the examples given in these tutorials, the approaches I use are not nearly as sophisticated/complicated and yet they are faster and use fewer resources than using Python and/or cURL. They are also easier to update if something changes. That is in part because (1) the binaries I use are smaller, (2) I do not rely on scripting languages[FN3] and third party libraries (and so much less code involved), (3) the programs I use start working immediately whereas Python takes seconds to start up and (4) compared to the programs I use, cURL as a means of sending HTTP requests is inflexible, e.g., one is limited to what "options" cURL provides and cURL has no option for HTTP/1.1 pipelining. 1. LinkedIn's so-called "technological measures" to prevent retrieval of public information have failed. Similarly, its attempts to prevent retrieval of public information through intimidation, e.g., cease-and-desist letters and threats of CFAA claims, have failed. Tutorials on "web scraping" that extol Python frameworks should use LinkedIn as an example instead of trivial examples for which using Python is, IMHO, overkill. 2. What would be more interesting is a Rosetta Code for "web scraping" tasks. There are many, many ways to do public data/information retrieval from the www. Using scripting languages such as Python, Ruby, NodeJS, etc. and frameworks are one way. That approach may be ideally suited for large scale jobs, like those undertaken by what the author calls "internet companies". But for smaller tasks undertaken by individual www users for noncommercial purposes, e.g., this author's concept of "scrapism", there are also faster, less complicated and more efficient options. 3. Other than the Almquist shell

saaaam 4y ago
Hi - I'd be interested to hear more details about what approaches you suggest!

Labo333 4y ago

Good guide! The "Scraping XHR" [1] explains how to inspect network requests and reproduce them with Python. I actually built har2requests [2] to automate that process! [1]: https://scrapism.lav.io/scraping-xhr/ https://scrapism.lav.io/scraping-xhr/ [2]: https://github.com/louisabraham/har2requests https://github.com/louisabraham/har2requests

saaaam 4y ago
Thanks for sharing this - I'll check it out!

saaaam 4y ago

Hi! This is a guide that I started during the pandemic but never quite finished. I’m in the process of re-writing/re-recording some parts of it to bring it back up to date, and adding in the bits that are still missing.

CWuestefeld 4y ago

I'm bothered that this doesn't mention any of the ethics involved, such as checking the robots.txt file and so forth. More than half of my traffic is from bots, so I'm paying something like half my operational expenses to support them. And we've had to do a lot of work to mitigate what would otherwise be DoS attacks from badly written (or badly intended!) bots. I think that at least a tip of the hat to avoiding damage would be appropriate in a piece like this.

helsinki 4y ago

Hi Sam, It might be worth adding a section on distributed anonymous scrapers that use some form of messaging middleware to distribute the URLs to scrape. Regarding the anonymous aspect (independent of job distribution, of course), you could walk them through using https://github.com/aaronsw/pytorctl https://github.com/aaronsw/pytorctl or even a rotating tor proxy. This is how I scraped all those Instagram locations + metadata we discussed about five years ago. Hope you’re doing well!