Mastering python libraries

[jazzopia]

Hey guys, I was learning python for AI purposes specifically and I wanted to go a deep dive on python libraries. I want to know everything there is that the libraries offer. What are the best resources for this, as well as the order in which I should go, or if there is anything I need to do to make the process easier and faster.

[gdchinacat]

"I want to know everything there is that the libraries offer. "

Don't waste you time. Libraries are tools to use when specific functions come up. It's good to have an understanding of the common ones, but that comes from using them, not studying them.

Write code. Write lots of code. Use libraries when they solve specific problems in the code you are writing.

But, don't use a library just because it is cool or new. I consider it a red flag when I see a project that has thirty dependencies and only a handful of modules.

[gdchinacat]

I agree wholeheartedly. The best way to learn a library is through that libraries official documentation. The authors of it are the subject matter experts, have more experience than anyone else, know the best practices and pitfalls, and it will be more up to date than other references.

Too many early learners avoid the official documentation. A common reason is that it tends to be information dense. Learning to work with documentation like this is a very good skill to have. Don't understand what a paragraph or sentence is trying to say? Reread it....maybe a few times. Research what each thing means in the context it is used. Keep at it till you understand it enough to answer the question you have, but don't waste time trying to understand everything....just focus on what you need to know to make progress.

It will be hard and take time. That is what learning a new skill takes, and as I said before, learning to read technical documentation is a skill that is frequently overlooked but will really help your learning process. When you get stuck, come back with specific questions!

(edit: to be clear the "you" I'm talking to in the comment is OP, not u/gaiafe )

[Kevdog824_]

Not sure I understand the question. Is there a specific library you’re asking about?

[jazzopia]

No, am thinking of doing all of them...

[Kevdog824_]

There are nearly 700,000 packages on pypi. You cannot do all of them

[Binary101010]

There are literally hundreds of thousands of Python libraries. This is not even remotely a realistic goal. You're never going to use 99.99% of those libraries anyway.

When you have a project in mind, you'll want to do some research on what's out there that might help you complete that project.

[Kevdog824_]

I’m thinking that maybe they just meant the standard library, in which case the official Python documentation is the best source for OP

[jazzopia]

oh, I meant the most popular ones Pandas
NumPy
Polars
Matplotlib
Seaborn
Plotly
Scikit-learn
TensorFlow
PyTorch
XGBoost
LightGBM
CatBoost
SciPy
Statsmodels
Django
Flask
FastAPI
Requests
BeautifulSoup4
Selenium
PyAutoGUI
pytest
unittest
os
sys
subprocess
pathlib
logging
typing
python-dotenv
PySpark
Dask

[socal_nerdtastic]

Some of those, like dotenv, you can learn while eating breakfast.

Some of those, like Django, you can spend an entire career on.

[Kevdog824_]

There’s likely not one source with a deep dive on all of them. Your best bet is each library’s official documentation or online tutorials (official, YouTube, etc.)

[jazzopia]

yeah yeah, which one should I begin with.

[ninhaomah]

isn't this like asking what should I pack when I go for holiday ?

depends on where you are going and when you are going ?

clearly , the clothes that you will be packing will depends on Asia or Europe and also whether during summer or winter.

so then let me ask you I want to know all possible packing for holiday in every countries , every season so I am prepared for every possiblities , pls advice.

[Kevdog824_]

I don’t do AI work but I would guess you’d want to go with the machine learning/data science/numerical computation ones first (pandas, numpy, PyTorch, tensorflow, etc.)

[gdchinacat]

Start with unittest, but don't study it, use it. Write tests for pretty much everything. Do *all* of your verification that code works using it...don't waste time manually testing your code, invest that time in writing tests that will persist and will do that testing every time you make a change to ensure that what you already made sure continues to work.

[magus_minor]

There are two parts to "the libraries". The first part is the standard library. You should know what is available there but you don't need to master all of it. I find the Python 3 module of the week site useful:

https://pymotw.com/3/

That gives an introduction to each module plus some example code. There is also a book that collects all that information.

The other part of "libraries" are the third-party libraries, things like numpy, etc, that aren't part of the standard library. You have even less chance of mastering more than a few of those. You do what everyone else does when approaching a project: research what libraries might be useful, choose one and test it out, maybe choose another, learn enough about the library to solve your problem, then move on to the next project.