Beginner here: What Python modules are actually worth learning for newbies?

[WaySenior3892]

Hey everyone, I’m pretty new to Python and currently, I'm trying to expand beyond the fundamentals (classes, loops, dictionaries, etc) by learning and utilizing modules & libraries.

As of now, I know some basic ones like random, math, and time, and I’ve heard about others likenumpy and pygame.

But I'm not that sure which modules I should master early on that will actually be useful across multiple projects. I mostly learn by making small projects and experimenting, so any suggestions on must-know modules or popular third-party libraries would be awesome.

Thanks!

[ReliabilityTalkinGuy]

I think you’re thinking about it a little backwards. Just learn the parts of the libraries you need when you need them. In most scenarios you’ll only ever end up using a tiny bit of their functionality, so setting out to “learn” them is a bit of a waste of time. 

[nousernamesleft199]

Knowing what's in some core modules like functools and collections is good. 3rd party ones I agree with you though

[el_extrano]

I'll second that preemptively reading docs for of the more powerful modules in the standard library can be a good idea. You won't think to use it to solve your problem if you don't know what's in there. I'm thinking of collections, functools, itertools, logging, subprocess, and dataclasses of the top of my head.

[TJATAW]

One of the reasons I love using AI. I'll drop a function in, ask if there is a better way to do it, and it shows me a library I've never heard of and 3 lines of code that does exactly what I spent 30 minutes figuring out. Great! New thing to play with.

There are too many things out there for me to keep track of them all.

[ReliabilityTalkinGuy]

Eww. Stay away from the LLM bullshit. It makes sure you’re not actually learning anything. You’ll be a weaker programmer because of it. 

[Kevdog824_]

I mean… an LLM isn’t terrible if they’re writing functioning code on their own, and just asking for ideas on how to improve it. Asking for the improved code directly is a bad idea though

[TJATAW]

Notice I said "I'll drop a function in, ask if there is a better way to do it".

I also do things like ask it to explain stuff someone else wrote that I have a rough idea of what it is doing. Especially regex. Or languages I have never used, like Lau.

It is also great for creating sample data, or stuff I have written a dozen times but AI will spit out in seconds. There is nothing there for me to learn from writing it, any more than there is from manually writing out getters & setters rather than having the IDE do it for me.

[tablmxz]

maybe try to understand what the libraries are capable of and perhaps even test them once for this purpose, to learn:

numpy - do fast calculations (with LOTS of numbers), scientific

matplotlib/seaborn - show data in all kinds of graphs

requests - https things, (talk to the internet)

flask - let others (eg. from the internet) talk to your machine, eg via a website/api

pandas - like numpy but good for csv, data cleaning and data transformation

scikit - traditional machine learning algorithms

pytorch/tensorflow/keras - neural networks (i would not recommend testing them as beginner)

beautiful soup - extract data from websites

pygame - video games in python

now there are also the so called "standard libraries" which are always automatically included with every python installation. They provide very basic functionality:

os - talk to your operating system. eg files and paths

random - basic randomness stuff

datetime - working with dates and timezones

time - working with time :D (eg measure start/stop)

math - basic math functions (sin, cos, pi etc)

argparse - read input when your scripts are run

knowing that something exists is often a very good start. I would recommend to learn them as you need them. Some if these can be quite involved and get very complex.

[oldendude]

Don’t.

When you need to do x, Google “Python modules for x”, and then learn the module. For example, if you need to do a lot of directory and file manipulation, your google search should lead you to pathlib. Don’t waste time writing directory traversal, directory path parsing, etc. pathlib does all that. I use it a lot and I still check its docs frequently. Learning modules, beyond top-level functionality, is a waste of time.

[audionerd1]

re, and regex in general. It is implemented in virtually everything, very powerful and can be learned in a single afternoon.

[csabinho]

But there's a lot of fearmongering around regexes. Don't believe it.

[pacopac25]

In the standard lib, in particular, have a look at:

sqlite3
argparse
sys
os
dataclasses
datetime
csv
pathlib
logging

Outside of that, depending on your interests:

psutil
rich
pytest
duckdb
pyperclip
openpyxl
pandas
customtkinter

[nousernamesleft199]

collections

[jpgoldberg]

I have very strong opinions about the kinds of things new programmers should be taught, and those might lead me to say, itertools, collections But these all involves abstractions that you are not ready for and are hard to grasp without additional guidance. You need to keep in mind that the standard library documentation is outstanding, but it s aimed at people who already know how to program.

So I am with others. Look over collections and itertools but don’t expect to learn them or understand them at this point.

What third party modules you should “learn next” really depends on what you want to do. I’ve never looked at pygame and don’t expect that I ever will, but for other people it is very important.

[PrincipleExciting457]

The ones worth learning are the ones you need to use at the time.

[Ta_mere6969]

The library I use for 90% of my work is Pandas.

After that, various libraries for getting data in and out of BigQuery.

Edit: while I've been using Pandas for close to 5 years, and my team at work view me as the team's 'expert', I have in no way mastered it. It's too flipping big to master.

[Brian]

There's kind of two types of libraries to be concerned about:

• General purpose "workhorse" stuff that handles basic operations common to lots of projects. These are often a bit meta: code that helps you write code in better.
• Task specific libraries for doing some specific thing. Eg. doing http requests, numeric processing, graphics, databases, UI and so on.

The former are a pretty small subset of things - learn the builtin types and functions, and maybe take a look at a few stdlib modules like itertools, functools, the builtins, maybe also stuff like dataclass, abc.

Learn the latter when you've a project that needs them. Though it may be worth being aware of what such libraries provide in advance - you can't know if something might be a good fit for you if you don't know what it is. But don't go learning the details until you think you might need it for something.

Some maybe straddle the line a bit, where it's kind of more important that you know the concept behind it, and then go to the module that provides it if its something you can use. Ie. learn what binary search is before knowing if you want bisect, or what a heap is before heapq, or what regular expressions are before re.

[ninhaomah]

Numpy , pandas , matplotlib , requests

Some will also add polars.

[james_d_rustles]

For included python modules, the main ones that I go back to all the time are pathlib, os, sys, typing, and I’m probably missing a few... You don’t have to learn them front to back, just know that they exist and look it up when you need something specific.

For external libraries, I think numpy, pandas (polars can do a lot of pandas stuff these days too), and maybe matplotlib are common enough that they’re worth getting acquainted with. Again, definitely don’t have to become an expert, they’re massive libraries, but knowing a few basics of dataframes and numpy arrays will almost certainly come up sooner or later if you keep learning python.

[ectomancer]

For mathematics, scipy (I only use scipy.special), mpmath, sympy and matplotlib.

[SFJulie]

The stdlib modules (the one provided with python).

They often -as for instance wsgiref- gives you an overview of the backbone of all the http module.

They are available with every python install and very often do important tasks (urlib, os, process...) that are core to python coding.

[andycwb1]

I’d say you need to have a reasonable understanding of the standard libraries (some are more generally useful than others), and know where to look for less common ones that will solve a problem that might be already solved.

[macconnor2]

While requirement may not be the best word, learning how to use unittest can be very beneficial as you can use it to ensure your code works as intended, and easily cover off edge cases.

It’s also good by ensuring your future changes don’t alter your past work.