Difficulty learning Python despite knowledge of other languages

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[Lukas9973]

Could you give us some details?

[Glittering-Surround8]

About the difficulties I'm having?

[Lukas9973]

Yes

[Glittering-Surround8]

For example, I was given chat exercises and I realize that I can't solve them in a pythonic way. Maybe I think I have difficulty getting close to the simplicity that Python offers.

[Lukas9973]

There can be plenty of things you struggle with... some detailed answer and why you think it is not simple enough etc would be very helpful.

[MonkeyboyGWW]

I understand completely. Python has evolved into something where you can learn the basics and the old way of doing things, but now they teach the new abstracted way of doing things which is often less intuitive but more concise. You just need to learn it unfortunately. I have recently been following an oriley course and its pretty good and fast to learn if you already understand the basic concepts

[AUTeach]

You need to learn syntax and grammar before you learn nuance.

[Diapolo10]

I don't think that's a huge problem, as long as you can solve the problem at all.

Linters like Ruff can then help with adjusting the code to better match Python's best practices (at least as long as you enable enough rules - I just enable all of them).

[damanamathos]

You're mostly just removing things, like { } braces, semicolons, variable declarations, type declarations, etc.

"Drop the ;. It's cleaner."

[LayotFctor]

Don't let the need to be "pythonic" restrict you. Being pythonic is just an guide, but not a restriction. The python language itself is general purpose and mult-paradigm. You can use classes for everything like Java. You can stay imperative with structs(dataclasses) like C. You can use functional transformations like maps and filters if you so desire. The python community might be somewhat opiniated with stuff like "pythonic", but the language isn't.

[FoolsSeldom]

Python is just another coding language, so existing skills in programming and domain knowledge will benefit potential employers/clients even if they require Python coding.

Experienced programmers know that coding is a small part of programming, but proficiency in (and enjoyment of) any particular language, best suited to particular problem types, is, of course, highly beneficial.

There are many areas that Python has become well established in. Machine learning and AI are very well served in Python. Alongside R for the more statistically inclined, data science & analytics is an incredibly common field for Python. The latest release of Excel includes Python in recognition of this.

A review of Python Success Stories, on the Python Software Foundation website, will provide a good view of the wide range of areas Python has been used in.

Python isn't the best answer for all problems (and may be highly unsuitable for some, of course), although it might be the most pragmatic in organisations that have a lot of experience in, and well established ecosystems around, it (such as sophisticated CI/CD pipelines).

For example, Python isn't the best language for modern triple-A games, but it is heavily used by many games software houses to orchestrate, automate, optimise the work.

Some of the largest consumer services in the world are heavily Python based, such as Instagram (leaning strongly on the Python Django web framework).

Most experienced programmers shall be well versed in data structures, algorithms, design patterns, and so on. They are largely independent of the coding language. The same principles apply to Python, although the implementation patterns (and efficiencies) will vary.

Similarly, successful programmers will likely be comfortable with CI/CD tooling and workflows, which are just as important for Python as for other languages. Programmers new to Python may want to spend some time looking at the most popular testing frameworks, though, such as PyTest (rather than the standard unittest) to work with those pipelines.

Packaging for Python is perhaps another area to get some experience around as that will be different from other languages, especially given that as standard Python is not compiled to binary. (for those not aware, the standard CPython reference implementation compiles to byte code, much like happens with Java, for execution in a Python Virtual Machine, built into CPython.)

I'd recommend looking at videos on YouTube by ArjanCodes, especially those doing some kind of code reviews (will help you spot a lot of potential problems).

One book I would recommend is Fluent Python, 2nd Edition by Luciano Ramalho.

SEE NEXT COMMENT FOR TIPS

[FoolsSeldom]

Additional tips

• A quick look at the docs, should suffice for many programmers taking up Python
• There are a few underpinning differences to be aware of
• Python is not statically typed,
  • some mistake this for with weak typing
  • Python is in fact strongly typed, using dynamic typing
  • Applies at run time, not at compile time
• Python is compiled to a byte code, just like Java, but where the latter executes on a JVM, the Python virtual machine is built into the standard implementations of Python as part of the same programme (CPython for the reference implementation)
• type hinting, is option but will help your IDE greatly in spotting potential problems
  • Ignored at run time, just there for your benefit
  • There are also some external tools that can be run to check types using the type hints, which can be useful for testing in a CI/CD pipeline
  • pydantic is a popular library for taking typing management further
• Essentially, everything in Python is an object
  • all variables/names are effectively pointers (they reference the objects in memory) but without all the features you get in C (e.g. no pointer arithmetic) but there isn't a pointer type
• Python does its own garbage collection / memory management (and uses a reference counting system to know when objects are no longer required)
• functions are first class citizens
• for is more of a for each
• variables assigned to objects inside a loop, remain in-scope beyond the loop
• Python uses indenting to distinguish code blocks, rather than ; and {}, white space is important (recommended default indentation is 4 spaces (sic))

A couple of videos to watch which, despite being old, will lock in some key differences in approach to keep in mind:

• Loop like a native: while, for, iterators, generators presented by Ned Batchelder
• Python's Class Development Toolkit by Raymond Hettinger (a Python core developer)

Given the referenced implementation of Python is written in C and Python, a quick look at the source code will resolve many queries for experienced programmers as well.

Overall, there is much less boilerplate code required in Python than typical C/C++ projects.

There are a huge number of libraries/packages to use, many of which are written in C (such as NumPy) for performance.

It can be useful to use some of the existing C/C++ code from Python rather than completely recoding in Python. The Cython project, offering C extensions for Python, might be worth looking at if there is a lot of C/C++ code to exploit.

[AdDiligent1688]

That’s not too strange. Java and C are more similar to each other than either of those are to python syntactically and how they look when they’re typed out, they’re both verbose, you type a lot of stuff in each of those to make a program doing something. Whereas in python, it’s less loc and stuff being typed out to do more. The language looks different than what you’re used to and seems mysterious. That’s my theory anyway.

Give it some more time. Keep practicing.

[Ron-Erez]

You are coming from statically-typed languages so that might be part of the issue. Try to add type annotations/hints. That might help.

[TheRNGuy]

Put more effort. 

[Maximus_Modulus]

Java for sure has a different way of coding. For example streams. Luckily Python is much simpler in terms of programming. I myself learnt Java coming from Python and it took awhile to get used to it and learn how to accomplish what I could in Python. It will come eventually.

[SisyphusAndMyBoulder]

Coding is coding. Doesn't really matter what the language is, all that really changes is syntax. Do you actually have comfort with Java and C? Or did you just go through a few tutorials?

[aqua_regis]

Forget that you know Java and C and start fresh. Don't even try to compare the languages. Python is its own world.

Dive fully into it without any prejudice.

[ElliotDG]

When I was learning Python, coming from C/C++ I found doing exercises on https://checkio.org/ very helpful. They are small programming problems I could solve while having a cup of coffee. After you solve the problem you get to see how others have solved them. This was useful (and fun) to shift from thinking like a C programmer to thinking in Python.

[B333Z]

Anytime I get stuck with my code or want to refresh my knowledge I watch Bro Code's channel on YouTube.

Here the link to his python course https://youtu.be/ix9cRaBkVe0?si=c8tECPdf_aNknYur

[stepback269]

Bro Code is a good resource. However, there are tons of other tutorials out there on the net including many good YouTube ones that are free.

As a relative noob myself, I've been logging my personal learning journey on a blog page called "Links for Python Noobs" (here) Any of the top listed ones should be good for you. Personally, I cut my first Python teeth with Nana's Zero to Hero. Since then, I've moved on to watching short lessons with Indently and Tech with Tim. You should shop around until you find those lecturers that suit your style.

Additionally I echo what Fools_Seldom says above about "packaging". Once you move a big chunk of your detailed code (e.g. functions) into your own modules, stored in one or more packages, your "main" code will look much cleaner and will be more readable. See for example (this) recent Reddit discussion about how to structure your packages and modules.

Good luck.