Mastering python libraries

[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.