taskipy VS requests-html

pdbpp: Improved pdb boltons: assorted python addtions twisted: event driven networking framework sorcery: Dark magic in python, things know where+how they are being called, helps reducing boilerplate sh: Better alternative for subprocess module, much more pythonic taskipy: npm run scipt_name like functionality snoop: pdb lite, record+replay function steps birdseye: graphical debugger remote-pdb: easy pdb from inside containers typer: wrapper around click for simpler code for CLIs arrow: Always TZ aware datetimes, plus more features more-itertools: more functions for iterators pydantic: data validation + dataclasses loguru: better logging notifiers: sending notifications from python

Taskipy

taskipy – complementary task runner for python

I always use Taskipy https://github.com/illBeRoy/taskipy to run tasks in my applications, works really well with Poetry so when I am running my dev Flask/FastAPI server and Celery or running my tests or format my code it's all there.

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In legacy (don't break anything) mode, there's still no reason to not switch. I export `requirements.txt` with poetry just for pip legacy reasons and it works great. If I just update some scripts, I could avoid it. It's running all the time in CI, it's exercised quite a bit.

What's wrong with just using pip and requirements.txt? There's no dev section. In addition, bumping deps is not the same. I have [a blog post](https://squarism.com/2021/09/10/sciencing-out-updates/) explaining semver updates to a python dev.

_my strong assertion:_ Python and Go missed it from the start. That's why it is so confusing. There's no other choice in Rust but Cargo. Rust devs are never confused on how to add a package, semver it. The answer is always Cargo. It's in the tutorial. It's in the book. It's in the culture.

I think I've heard that pip might support the pyproject spec, poetry already does. If you want scripts like npm, you can have that too with [taskipy](https://github.com/illBeRoy/taskipy). You don't have to.

taskipy

requests-html

Ya, thanks for advice. When using requests_html library, I am trying to lower down the speed using response.html.render(timeout=1000), but it raise Runtime error instead on Google Colab: https://github.com/psf/requests-html/issues/517.

For dynamic js, prefer requests-html with xpath selection.

Example: requests-html which has a rather exhaustive README.md, but their dedicated page is not that helpful, if I remember correctly, and currently the domain is suspended.

When it comes to web scraping, the usual people recommend is beautifulsoup, lxml, or selenium. But I highly recommend people check out requests-html also. Its a library that is a happy medium between ease of use as in beautifulsoup and also good enough to be used for dynamic, javascript data where it would be overkill to use a browser emulator like selenium.

Quite possible. If you look at requests-html source code, it is simply one single python file that acts as a wrapper around a bunch of other packages, like requests, chromium, parse, lxml, etc., plus a couple convenience functions. So it could easily be some sort of bad dependency resolution.

What I do is try to see if I can use requests_html first before trying selenium. requests_html is usually enough if I dont need to interact with browser widgets or if the authentication isnt too difficult to reverse engineer.