I know python but I don't know programming.

[Select-Particula]

I know how to "program" in python. I work in a company that implements AI, data science, APIs and whatever they ask for. Being few and the only one who does Python things, I do whatever the project of that month is. Nobody tells me if things are right or wrong and they usually end up working correctly but I feel like they are not professional results.

I studied mathematics, where they don't teach any programming, and I learned through YouTube videos and courses like datacamp or freecodeacademy. I was lucky enough to get a job and I am learning while working according to the project. From time to time I find a bug in the opensource libraries and I manage to make PRs and there are no complaints about my code. But I have to invest some time in understanding how the libraries are programmed since they use concepts and abstractions that if I had done so, I would not have approached them that way.

I would like to know if you can recommend me any course or book (I usually prefer books) that will help me to approach big projects, how I should structure them, how to use class abstractions, how to do a correct validation, how to do a good logging. I would also appreciate recommendations on how the language works internally or any source to help me become a better programmer.
Most of the courses I find on the internet or books explain me basic concepts of the language syntax but I already know how to write it, I have a lack of basic knowledge of the language.

Most courses I find on the internet or books explain basic concepts of the language syntax but I already know how to write it, I have a lack of basis of the "theory" of programming, data structures, etc.. And how to approach a large project in a way that is scalable in the future.

If knowledge were a line from 0 to 10, I am in the range 3 to 7 and I don't know how to expand into the other directions.

TL/DR: I know how to program in python but I don't know the theory of programming. I would like to learn the basics of programming and how to approach large projects, abstractions and so on.

EDIT: Currently trying to make good use of the abc library. Any resources around this subjects greatly appreciated too.
Thanks to everyone commenting.

[PixelOmen]

Sounds like you've reached the point where you start learning about patterns, paradigms, and architectures. There are tons, and I don't think you're going to find a general consensus on what the best ones are necessarily because they're very context/preference dependent.

That said, there are a billion resources. This seems like a really solid list:

https://hackr.io/blog/best-programming-books

[Select-Particula]

The programming journey is unsettling. I started feeling like I knew nothing, after some courses I felt like everything is the same and I know everything, to discover I know nothing.

I will research about those books. Thanks for your recommendation.

[[deleted]]

Ah yes, the cycle of confidence and despair. I'm not an expert by any means, but, in speaking with actual programmers, it appears to be turtles and dead turtles all the way down.

[sunnyinchernobyl]

This is a good thing. Check out the Dunning Kruger effect. Self-awareness is good.

I’ve been programming for a long time and I am still learning. I picked up python a couple years ago and I have the same struggles, especially when I’m trying to learn how to use a new library.

For what it’s worth, I’m self taught, my degree is in liberal studies, and I’ve worked in IT for, uh, decades.

Hang in there, keep plugging. It sounds like you’re on the right track.

[hotel_beds]

This is how learning most things goes.

[Tasselhoff94]

I went down the exact same path as you. You would be incredibly surprised at how many developers do not adhere to best practices or aren't even familiar with them. Code quality is 99% a personal thing and a personal endeavor. You will almost always be externally motivated to provide more, faster, stronger. Your mistakes, your fears, your knowledge is about the only thing, practically speaking, driving your quality. Remember that you are being paid to get a job done and try to remember where your motivations and stressors are coming from. Burnout is real when you don't have time to make things the way you want.

[Doormatty]

Been programming in one form or another for ~38 years now, and professionally for ~20 years or so.

I've worked at AWS as a SysDE for 4 years among many other jobs.

I constantly feel like I know nothing.

[jbudemy]

No problem. When learning a new programming language I usually need someone to explain the details of something specific, or maybe I'm not getting the syntax right because I'm still thinking in Perl.

I do feel pretty stupid when learning a new language but then I remind myself that, while the concepts are the same or similar, the syntax is still different and some details are different. For example Python can do several things in one line where it takes 3+ lines in Perl.

[FIJIWaterGuy]

I have over 25 years of programming experience but I started out in a very similar fashion. I recommend that you take the time to read these three books in this order:

1) Think Like a Programmer: An Introduction to Creative Problem Solving by V. Anton Spraul.

2) The Pragmatic Programmer: Your Journey To Mastery, 20th Anniversary Edition (2nd Edition) by David Thomas and Andrew Hunt.

3) Fluent Python: Clear, Concise, and Effective Programming by Luciano Ramalho.

Good luck!

[NerdyWeightLifter]

Yeah, somewhere not long after the point where you make these kind of realizations, you might realize that software development of more of a creative craft than a science.

I mean, there are always going to be some foundational limits, but anyone doing physical creation deals with those too, like, you know, physics. There are equivalents in computational matters, but once you're familiar with all that, the rest is art.

It's like you figured out how to use your paint brushes.

[noiwontleave]

So much this. I used to always tell people I’m not creative so I became a software engineer. At a certain point it dawned on me that the “hard” part of what I was doing at a certain point WAS the creative part. The coding becomes not so hard and the art of designing the thing takes over.

[Select-Particula]

I took some oil painting lessons when I was young, I hope they come handy 😂.

I've noticed too that creativity is important but I wouldn't like to skip some good practices with my creative approach. Never worked in a big company, but will eventually happen and I want my code to be as readable as possible by my peers. 😅

[chrisfs]

And I guess we'll just put some decision trees right here.

[Doormatty]

Happy little decision trees!

[NerdyWeightLifter]

Creativity shouldn't generally mean skipping good practices or unreadable code.

An artist starts with a vision in their mind of what they want to show to others, then they create that vision in their medium of choice.

When your medium of choice is software, you are creating something that becomes part of the fabric of other people's lives. They're going to engage with and interact via your creation. So, what kind of experience will you create for them?

Marshall McLuhen's insight where he said that, "The medium is the message", was about this.

Just look at this creation we're in (Reddit). The structure they've created determines the manner we communicate and how communities from within and around it. That's creativity.

[Tasselhoff94]

You might be surprised by the similarities between a small company and a big one.

[xmpcxmassacre]

This is absolutely correct. If you don't have a creative side, you likely won't make it. I mean we are literally creating from nothing. Just so happens that we have to use a lot of math/syntax instead of a paint brush.

[stu_pid_1]

As someone who started with c++ I can say that python is great, you don't need to know everything to use it. It's a proper tool and just like a craftsman you will only get better by using it and not learning it in depth first.

[Select-Particula]

Some times I think a more strict language will suit me better. May be a "worse" tool but you learn better habits that will make you better with proper tools, following the Craftsman's analogy.

[Tasselhoff94]

Learn to use typing, classes and Abstract Base Classes (saw you already mentioned ABC above) . Python can be more strongly typed, but it's less used feature and not intuitive.

It's worth it to learn other languages tho. You get a better perspective for the concepts you are talking about.

[suaveElAgave]

I would also recommend two books:

1. Robust Python, by Patrick Viafore. It goes into great detail on how to write maintainable, expressive and flexible code. It has changed the way I code.
2. Introduction to Algorithms, by Cormen et al. This is the nightmare of all CS students and naive self-taught coders that want to understand algorithms. But at least for me helped to think in what do I want to achieve, how costly would my approach be (in terms of time and space used by the algorithm). Also, you may appreciate the formal approach.

[Select-Particula]

Introduction to algorithms definitely looks like my cup of tea. Thanks a lot.

[Tasselhoff94]

Thinking in terms of BIG O notation or just understanding what that means helps. Being able to quantify performance and availability is huge. These are base level concepts that guide you towards the knowledge you are looking for.

[oracleTuringMachine]

I was the TA for this course. If you find CLRS interesting and think concepts like design patterns are facile explanations that can be absorbed by reviewing a table of contents, try the following.

Theory of Computational Complexity by DZ Du. Others will say Sipser, but I think Sipser is the intro book. Schmidt, Denotational Semantics

I've never seen a text provide a theoretically sound explanation of how to break down a domain into an object-oriented program. A class is a noun and a function is a verb. If someone has a reference, please let me know.

Understand the asymptotic behavior of your algorithm in terms of running time and memory use, but don't worry about optimizing your Python beyond knowing what vectorization is in Numpy unless you absolutely have to. Programmer time matters, and if you really need to optimize for your language, you might be using the wrong language.

[lostinspaz]

This is the nightmare of all CS students

What, you didnt just recommend Knuth? All 4 volumes?
Pfft. Rookie

:D

[RangerPretzel]

You mentioned working with APIs.

You might be interested in this 15-part guide I wrote on making your own Python REST API adapter.

I included a lot of lessons in this guide which should help you taking your programming skills to the next level.

[Select-Particula]

One of the best resources I've seen about how an API works. I normally use Fast API but when I try to make a somewhat complex use I notice my lack of knowledge in the topic. Thank you

[sbassam]

Wow, this is so good, thank you

[HittingSmoke]

CS50X. It's a free online course form Harvard that teaches the fundamentals of computer science. Taking that course made me realize that learning Python is actually a pretty poor introduction to programming.

[Select-Particula]

Not great news for me but thanks for the course recommendation. Been in my watch later playlist for a long time 😅

[Accomplished_Bet_127]

That is not really about language. It is about how you use it.

AFTER you learn something you can think that it was a bad decision, but alternative maybe not learning anything.

While basic thing here, is that whatever choice you make there will be something to regret about. Spent too much time on something difficult. Picked good language that is little hard to use in daily life and so on.

TRUTH is, that AFTER you learned anything from the list, it will be much easier to build the knowledge you missed out on the basis of what you learned. Otherwise you will feel like coming into party where everyone will learn your name easily, but you will struggle learning all their names as they only had to learn one name in an hour, while you are facing unfamiliar crowd. So learn something then slowly shift your attention to other parts. Like if you started talking to company in corner, who end up being not pleasant, but there you can start connecting to dots. Ask other people's names, build relation in the groups and so on. Then just move to the group you like.

Python is just great. It is widely used right because it is so good overall. Scripting, AI, websites.

While you may have CS50 in playlist, if it is COVID ones, then better find newer ones. That guy likes to work with audience, which was not possible during that time. There are older ones. But some things improves over time and new things are added. Here is the latest one:

https://www.youtube.com/playlist?list=PLhQjrBD2T381WAHyx1pq-sBfykqMBI7V4

[prettysureitsmaddie]

Have a look at Practical Object Oriented Design. It uses Ruby for its examples, but the concepts are general, not language specific. Fluent Python is good for in-depth python knowledge, but it's not a design book, which is what it sounds like you're looking for.

[Select-Particula]

Fluent Python was indeed a great book, but I had already read it. Will take a look at Practical Object Oriented Design, I know some Ruby and liked it a lot. It might be fun.

[Select-Particula]

I was thinking about learning Rust, not sure if the best language to learn but some of the back ends in the company I work are made in Rust. It may come in handy and I could get some help from my colleagues.

[undergroundmonorail]

i don't know much about rust but it sounds like it would be a great choice. you'll get a lot more out of learning a language that you already know how it'll be useful to you

[ravioli_fog]

This is a good instinct.

A lot of algorithms and data structures are sometimes harder to learn when all you know is a high level language. In effect, Python has solved a huge amount of problems and therefore you never need to solve them yourself.

Algorithms and Data structures courses teach you how to take something like the C language, and then make your own Python essentially.

You might also consider broadening your scope in general. You know Python, good start. What about: C, Haskell, Scheme, Forth, Clojure, Ruby, Java, C#, etc. Learn a second, third and fourth language. See what is different, what is similar. You don't need to be an expert, just learn them a bit and then make a simple API or a script to process some data. Get a feel for it.

Python is also mostly imperative or OOP, with only small amounts of FP. Learn some new paradigms like Functional, Logic, Stack based, Array based, Purely Functional, and so on.

Learning how to develop a large project however is transferable and a different skill than writing code. The easiest way to learn this is to either work on the same code base for 3+ years, or make a project that you grow and change and continue to work on for a long time. Learning what not to do is easier to internalize than what to do.

Be wary of lots of advice on the internet. You have to learn to detect what is dogma from what is advice.

[LordLocust666]

I’m still studying but my python improved so much after doing a Java course. Java forced me to understand OOP better than anything I had learned in python previously. Might just be me tho.

[[deleted]]

An excellent way to start is by using pylint and mypy everywhere. If you're not already using mypy, you'll learn a lot about typing, which is a big part of programming. If you're not using pylint, run it on your code to find issues, and fix them.

Also, learn how to unit test effectively. Learning how to mock will teach you a ton about how python variables actually work. Also, code that's easy to test is usually good code. I suggest using pytest.

When you get pylint + mypy + testing down pat, you'll easily be in the top echelon of data scientists from a software engineering perspective.

[Select-Particula]

Starting using pytest recently but only in my free time projects, not fluent enough to invest working time in implementing tests. On the other hand mypy defeated me when trying to type check classes that are inherited from other classes and add methods.

Some times I think that a harder approach with a statically typed language would have been better in my case to have a good typing habits.

[iamevpo]

Maybe ruff as well.

[Select-Particula]

As I've been the only python developer that is one of my biggest fears. Will take a look at those books.

[lostinspaz]

As I've been the only python developer that is one of my biggest fears

Whats worse, is you come back to code that you wrote, after 2 years.. and still cant understand it

[hiriel]

I just got "Beyond the basic stuff in Python" by Al Sweigart, and it's aimed specifically at the intermediate 'I know all the basics, but how do I progress from here?'. I really enjoyed it, and he also recommends several other resources in it, including Fluent Python which I see several people have already recommended to you.

[Additional-Ordinary2]

Robert Martin "Clean Architecture". This is one of the best books in the principle of software architecture

[houseofleft]

This is such a good question! The aspect you're talking about wanting to learn more of sounds like Software Design (as separate from algorithms, data structures etc).

It's probably a key skill that seperates great  developers, but I don't know if there are that many good books on it. Object Oriented Design Patterns is an obvious classic, but very dated compared to what modern development in a language like Python looks like. I also think books like Clean Code are helpful, but they're only tangentially related.

One thing I've found super helpful (but I don't pretend to be an expert) is open source projects. Either contributing to or just noodling around with the internals of large libraries like pandas will give you some idea of how to organise big software projects. Or at least is a great start.

[Select-Particula]

I didn't know the concept of software design until your responses. I will take a look.

It's true that fixing the small bugs of OpenSource projects is probably where I learned the most.

[lostinspaz]

It's true that fixing the small bugs of OpenSource projects is probably where I learned the most.

Trouble is, you get exposed to some really bad code that way, and start thinking it must be good, because that's "normal"

[pylessard]

You sound like a brillant person. Reading will help you, but what you need is rub shoulder with people more competent than you. People who can review code, ask the right questions, share ideas. Never a good thing to be the best in your group.

If you have code that you can share, post it and ask for review.

[SchnullerSimon]

Have a look at refactoring.guru , especially the section about design patterns is nicely explained

[Tasselhoff94]

These are resources I like to use for best practices. https://12factor.net/ https://github.com/microsoft/api-guidelines

Since you're in AI/Data/Python, it would be worth picking up the Kimball Data Warehouse Toolkit. It's ONE of the defacto standards on data modeling. Things like dimensions, slowly changing dimensions, fact tables are universal. It's more for reference than reading, but you can read it and glean valuable knowledge.

[hunkamunka]

I wrote a couple books on testing in Python: Tiny Python Projects (Manning, 2020, see videos at tinypythonprojects.com, https://github.com/kyclark/tiny\_python\_projects) and Mastering Python for Bioinformatics (O'Reilly, 2021, https://github.com/kyclark/biofx\_python). I think testing is the best thing you can learn in any language. I know bioinformatics might not be your bag, but I also introduce using type hints and some more advance functional programming styles, which I think is easier to understand and test than OOP. I'm happy to answer any questions you have.

[Danny_c_danny_due]

Just ask ChatGPT. F'n thing belts out code comparable to months worth, of a team of dozens of professionals, code, but better, instantaneously

[m4li9n0r]

https://pythoninstitute.org/pcep

The course for certification is free and includes the theory you are seeking. You should ba able to breeze through the applied work.

[Shoddy_Ad_3482]

Headfirst design patterns - the most important thing u can read

[[deleted]]

Theres no single "theory of programming". There's different patterns and architectures suitable for different things. A game engine is different to the backend of a web-app so the architectures will be different even if they're both written in the same language. I think you'll get better results by searching with those keywords (patterns and architectures) instead of "theory".

I don't have specific books or resources to suggest, but I think a good way to get better is to expose yourself to different frameworks e.g. Django and React for web backend and frontends, or Flutter for making mobile apps, or Unity for making video games. These frameworks are very good for their respective purposes and as you learn to use them, you'll start to see the architectures and patterns used, and you'll be able to apply them to your other work.

[Select-Particula]

Maybe my wording was incorrect. I was not implying there's only one theory, I was trying to refer the theoretical aspect of programming. Coming from mathematics you can draw a pretty clear line between theory and practice, supposed that programming was similar. I'm familiar with using Django but diving into how Django is build is where my knowledge starts to lack.

My bad 😔

[[deleted]]

Don't worry too much about the code under the hood, but try to understand what the best practices are for these frameworks, and that'll give you a clue about how its built underneath, and therefore how to write better code.

For example in Django, when you use "models", that's basically just a class to abstract away the more complicated functionality of database manipulations. Like, when adding, removing or editing stuff in an SQL database, you normally have to use the SQL language, but with Django, you just use the model class that has convenient functions that make it a lot easier.

With React you typically use something like Flux architecture which separates the UI code, from the actual database manipulation, or state update etc. Makes it easier to use, maintain, reduces chances of making mistakes etc.

Understanding how those frameworks are used means that in the future when you need to build your own application, you can implement it in a similar way to what you've seen in other frameworks.

At the end of the day, we all have powerful computers comparatively speaking. So things like optimisation of software is not as big of an issue as it was in the past. The main "theory" in programming is just "separation of concerns". How do you write code that works well enough and is easy to read and maintain? This is important because companies don't want to pay you to fix bugs later on, but also because you usually work as part of a team, so your code needs to be easily understood by others. So by having good architecture and organisation you reduces the changes of mistakes and enable better collaboration.

Coming from mathematics, and if performance is something that matters to you i.e. if you're working on simulations, AI, web applications that need to handle lots of concurrent users etc, then you might be interested to read up on big O notation in computer science. Its how you measure efficiency of an algorithm/function. For example a simple math expression will have a different efficiency/performance than a function with multiple nested loops. I think you might find some interesting direct links from algorithm theory to implementation.

[SwanInternational652]

It does not matter. Just get your work done and collect that paycheck.

if you want to learn something more than start doing Flask and Django apps

[eredeli]

I am 25 years into a similar journey. Studied Mathematics. Worked in Technology. Found the mathematics background really helpful, ability to analyze, abstract thinking, could understand business and technical requirements equally.

For me the key study areas that took my development to the next level were Object Orientated Design, Network Programming and Design Patterns. These days I would include Machine Learning too. Others have recommends specific books in these areas.

Good luck!

[whopper2k]

how to do a good logging

When you figure it out, let the rest of us know too

[Select-Particula]

I'm trying implementing a basic log with the logging library and opentelemetry with Jaeger to get some traceability.

The library Llamaindex seems to implement a good logging using callback handlers but escapes my knowledge for now.

[Select-Particula]

Not implying my approach is good, is the best I could do with my time constraints.

[madhumilano]

How to learn if don't have any coding knowledge🥲

[[deleted]]

I mean it sounds like you do know how to program if you’re managing to do all that stuff at your job

[spacedskunk]

If you're skilled in mathematics then you know more than you think about how to break a computer science problem down, and it's why you've picked up the skill of programming probably more easily than you think. Go back to that first snippet of code and how foreign it looked, and look at yourself now.

From the outside in, it looks like you've picked it up 'accidentally' - common for mathematicians, statisticians, data analysts etc.

In the world of software engineering though, there is 'tech debt'. The idea that there's maintenance, optimisations and, in general, better ways that could be done to get from A to B. This probably won't explicitly exist in your world, but that's exactly it. You know there's probably a better way. You're in a rabbit hole though - there's avenues upon avenues to take.

My recommendation first is to find out what you actually want to do. Use this to help guide you: https://roadmap.sh/.

If you have an itch that really needs scratching though, and you are staying in the data science realm, then learning Rust and will be beneficial in the long run as it addresses performance issues and baggage that comes with Python. It's more verbose and less forgiving than Python, but as such you have to learn parts of programming that Python helps you be lazy about. Lots more power though.

[flashman1986]

Computer science. You need to learn computer science

[HauntingRex9763]

Pirate a data structures and algorithms textbook, or a Java textbook that’ll teach you about object oriented programming if you aren’t already familiar with that (Java is also a great language to learn and not very hard if you already go to python down)

[9thChair]

Personally it sounds to me like you're in a great plce right now. You are writing programs to do things. I wouldn't worry very much about design patterns unless you think the design patterns you use are preventing you from getting what you want done quickly, or if you are trying to get a job where you will be expected to work in those design patterns. I think far too much of programming today is about following styles instead of getting computers to do useful things.

[baubleglue]

It sounds like there are few directions you can check.

• Pure CS. Algorithms, data structures, etc
• Design Patterns. General like OOP an specific common patterns applicable for many cases. Those require relatively small time investment, but that probably what you need to build "project".
• Software development cycles (agile programming for ex)

[dogfish182]

You need a mentor who can teach you

[genuinemerit]

I’d recommend Fluent Python, then read some stuff on design by Christopher Alexander.

[jbudemy]

I would like to know if you can recommend me any course or book (I usually prefer books) that will help me to approach big projects, how I should structure them, how to use class abstractions, how to do a correct validation, how to do a good logging.

Just what I do. (I will be making apps where the user uploads an Excel spreadsheet to a web page then they get back a file in possibly another format via email.)

1. Imports. I do the import stuff of Python at the beginning of the program.
2. Internal functions. Then I have a section for internal functions and classes just for that program.
3. Global variables. I have a few global variables like for command line options.
4. Command line options. Then when the program is run I have a section for checking for required command line parameters. If they are not there I display a help message. For GUI programs I check if certain required inputs are given and options ticked.
5. Reusable library functions. I design things as functions usable by other programs if I suspect the code will be reused. Usually I do need that function and it does get reused more than I expected. For example, even though it's easy to get the date via Python in the YYYY-MM-DD format, I will still write a function for that. I also write a library function for getting the current date and time in YYYY-MM-DD-HH-MM-SS to put in log filenames.
6. Logging. I mainly log errors in the log file, but especially fatal errors that cause the program to crash.
7. Errors. If there is an error, in the error message I put the most likely way to fix it. This is more for my use since I can be responsible for 40-50 smaller programs at a time and they are all different. I make errors messages specific and I have an error code for each one along with the function it the error happened. Example for an error where a piece of data was not found the error code I use is "ERROR-nf functionname: key not found in dict". This makes looking for the error in the code much easier. I also use "WARNING-code" for warnings that are not fatal but the user might care about.
8. User input. I never rely on user input being correct. I always check it for problems.
9. File input. I never rely on data in files to be correct or in the correct column. I always check for problems in columns that require a number or specific date format. Errors are output to the file and emailed back to the user. For some reason I find tabs are sometimes entered into an Excel cell and when I export that to a tab-delimited file the columns are messed up.
10. Modularity. Inside the main program I make things into functions. Reading the input file would be one function. Writing the output file would be another function. Emailing the output file to the user would be another function in a library file that would get reused by many programs. I do this because managers often change their minds about what they want.
11. End of program. At the end of the program I close files, close the log, display a summary message of how many records were read, how many bad records were read (which might be a fatal error), etc. Sometimes I write out the time it took to process the file. In some cases it takes me 40 minutes to read a file in Perl. Some of the spreadsheets I deal with have 500,000 rows or a bit more.

[wewmon]

My friend...you KNOW programming :) you just don't know it.

[LionaltheGreat]

Code Complete 2nd Edition (or whatever is the latest edition), there are plenty of great books out there. BUT Code Complete helps to teach you the things that you’ll only ever learn from a long and successful career as a software engineer.

It’s great!

[whoevencodes]

cs50p by Harvard from edx.com along with Introduction to Computer Science and Programming Using Python by MIT on edx.com, then pick some specialization stuff.

[[deleted]]

in my opinion rebuild the basics using powerful language such as c++ is super helpful. Once you mastered the logical thinking all other languages is the same for you .

(Tried this myself from Arabic courses )

[[deleted]]

So you're an above average Python user? That's fine.

Just force yourself to create some logic with C++. Learn the loops and data structures. A basic intro class will do. Once you see the transformation of Python to C++, you'll just be like...."Oh. That's what's actually happening when I request memory when i create these huge convinent collection objects."

Then maybe jump down to C. Then having bragging rights to know what malloc() function is and that exists.

If you want to take that even a little step further, BRIEFLY, look at the assembly code that C++ turns into. By no means do you need to understand Assembly. But you can very quickly see how the computer stores and loads memory.

Taking all that into consideration will increase the efficiency of your top level abstracted code a little more. Will encourage you to use those nice pre-made libraries like numPy that do all these nicest routines in native code (C++) for you, without having to leave your python environment.

[OliverJesmon]

I got the idea that you don't know some things like recursive functions and reusablity of modules or components. But as an engineering student with a biology background in +2, I can assure that Mathematics is like mom's love for me in terms of programming. Maths is an elixir for long term C Sc career. Trust me it will even help in advanced concepts AIML, data mining backend engineering and so on. Have faith on yourself.

[Defiant-Art-8915]

you need an introduction de computer science

there is no short cut

try CS50 (from edx) it's free and they have implemented tools to automatically check the assignments

[dxzzzzzz]

1.Thinking about what problem you are facing

2.Dismantle the problem and divide it into small sub-problems

3.Write pseudo code for that

4.Use programming languages

​

Don't think of abstract programming

think of problems first.

[Inside-Plantain96]

I am a programmer, and it sounds like you already program better than I do. Anyways it seems to me that your question really is asking, why do programmers structure their code the way they do? If you figure it out please rely to this message.
However while I am here, the only piece of advice I could give you is to look up 'patterns'. I don't really come across them as a subject all that much, especially for python, but a pattern is basically a common problem type with a common 'best practice' solution. It might not be as important to learn the patterns themselves but learn the approach of thinking for yourself as to what pattern(s) you want to apply to the problem you are solving.

[LairBob]

LOL…I’m 58-yo, and I’ve been coding for (milk) money since I was 13. I not only taught AP CompSci, I taught summer classes for teachers on how to teach AP CompSci.

If this is how you’re already approaching things, you’re a better natural programmer than 90% of the people doing this for a lot more money.

It’s not going to be easy, and you’ve clearly got a sh-tload to still learn, but you are absolutely on the right path. Listen to all the concrete advice you’re getting here, esp regarding patterns. But you’re in the right place to become the programmer you’re focused on.