graphical application for downloading videos and audio from YouTube and other platforms (Facebook, Instagram, X.com , TikTok ... ) and more using yt-dlp, with quality control, subtitle support, language switching, and dark/light themes.

build with python3

https://github.com/hmidani-abdelilah/Media_Downloader

Hi. If I offered to write pipelines for github (or maybe gitlab) here for FREE, how many people would be interested in this? Answer if you would be interested in comments.

Reason: I am learning to automate CI/CD as Python AQA.

I'm just collecting info for now, but you can text me in DM for the future.

Focus on CI/CD automation for python projects, testing projects. I am Python AQA with 4 years of experience but haven't worked much with CI/CD and want to practice on real projects (that aren't mine) even if your project is for learning, portfolio and so on. So don't expect that I will be able to finish your task.

Hi everyone,

Please give me some advice on my current Python learning workflow using AI.

I finished a Udemy course covering Python basics. To improve my practical skills, I found a site of practice projects, picked one that interested me, and started coding.

After finishing my first project, I realized I had no idea if I was writing clean, idiomatic code. So, I decided to use Claude as a code reviewer.

Here is how I set up my workflow:
1. I asked Claude strictly not to write code for me, but only to provide hints, point out flaws, and tell me which concepts or topics I needed to read about to understand why a different approach was better.
2. I requested code reviews tailored to production-ready standards, following modern Python best practices.
3. I completely turned off all AI auto-completion in VS Code. I wrote every single line of code myself

The AI would review my draft, essentially tell me "this code is shit =) (joke)" and give me targeted feedback. For example - "Disconnect your internet and see what happens to your API request. Go read about try/except."

From there, I would search Google for each point in the review, study the topic, rewrite my code, and repeat the loop until the reviewer was satisfied. Spent couple weeks to get last verion of program

From my perspective, this feels like solid progress, but I’d love to hear from experienced developers: Is this a good, effective way to learn Python alongside AI, or are there hidden pitfalls?

I've attached screenshots of my first code review alongside the final version. Thanks in advance for your feedback!

Hey everyone,

Chapter 3 is finally done. This chapter took way more time than I originally expected because it grew into a much deeper and larger chapter than planned.

Current Progress:
✅ Chapter 1 - Variables & Memory
✅ Chapter 2 - Expressions & Operators
✅ Chapter 3 - Conditional Statements & Control Flow

I'd love to hear your thoughts on the new chapter and any suggestions for future improvements.

With this, I’m taking a break from Python Under the Hood. I’ll be stepping away from the project for a while and will return to it before July 2027.

When I come back, we’ll continue with even deeper explanations, more advanced topics, and an even better approach to understanding what happens under the hood of Python.

For now, Chapter 3 marks the end of this phase. 🐍⚙️

GitHub: python-under-the-hood

See you in the next chapter.

- David Vael

I’m currently learning Python and preparing for entry-level IT/data-related roles. I’m trying to avoid spending too much time learning advanced topics that aren’t necessary for getting my first job.

What Python topics would you consider must-know for a fresher, and what level of DSA/problem-solving should I aim for?

Also, for people who recently got their first job, what Python skills were actually tested in your interviews?

When I started learning Python, I used the old percent style for string formatting, mostly because that's what the tutorial I followed used. Then I moved to .format() because it looked cleaner to me. These days I use f-strings for almost everything. But I still run into cases where I'm not sure f-strings are the best choice. For logging, for example, I've read that people prefer the older style so the string only gets built if the log actually fires. I'm not sure how much that matters in practice.

What do you reach for now when you format strings? Did you change your habit over time or did you settle on one approach early and stick with it? Are there cases where you still use .format() or the percent style on purpose?

So I’ve spent the last 2 weeks learning Python basics - loops, conditionals, functions, OOP, etc. - and I’m pretty confident with those concepts now. I’ve also built a few small projects along the way.
But now I’m seeing everyone talk about DSA, APIs, Pandas, NumPy, and honestly I’m confused:

1. What even are these? Are they libraries? Frameworks? Concepts?
   
2. Do I have to learn all of them? Or can I pick and choose based on what I want to build?
   
3. In what order should I learn them? Is there a logical sequence?
   
4. Where should I learn from? YouTube, courses, documentation?

I haven’t joined college yet (starting soon), and I want to build a strong foundation before I do. I’m unsure whether I’ll specialize in data science, cybersecurity, AI/ML, or something else—I’ll figure that out during college. So ideally I need skills that give me a good base for any direction.

Anyone been through this? What would you recommend for someone at my stage?

Most of my automation is bash held together by hope. It works fine until a filename has a space in it and suddenly I’m debugging quoting for half the day.

Trying to move the bigger scripts over to python now. The problem is every python course I find seems to spend forever on basic stuff before getting anywhere near a file or an api.

Boot dev, Automate the Boring Stuff and real python are the three I have bookmarked so far.

Anyone here actually used one of these for devops python course stuff? Just looking for something that gets into useful scripts pretty quickly.

I’m fairly experienced with Python and researching how to solve issues on my own. However, I have found that AI can help in some cases. For instance, giving me specific information on debugging and helping me research solutions for specific problems.

I was using Copilot in VS Code for a while, until I ran out of usage. Now, I’ve been messing around with locally-hosted AI, trying to find a good model for coding that runs well on my computer. My challenge is that I only have 4 GB of VRAM, though I also have 16GB of system RAM. If someone could help me find either a good, intelligent, and accurate local model that runs on that, or at least a free cloud model that’s good, I’d appreciate it.

Hi everyone,

I'm building a multi-page CustomTkinter desktop app where I swap pages inside a main container. I want my text and CTkImage sizes to automatically adjust whenever the user resizes the main window. So far, my widgets automatically adjust because I use .place() with relative sizes and placements. But even if the widget itself grows, the text/image stays the same size, which doesn't look appealing in the slightest.

Basic info:

ghost_pic is the label that houses my CTkImage; this automatically changes size already.

ghost_mid_image is the CTkImage

First try:

I thought that I could try to make the image change its size to match its label every time the window changed size. This is because I made sure that the image is approximately the same size as the label on the default window size, but this didn't do anything; the code didn't work at all.

Second try:

I then decided to just size the image with reference to the window, and this kinda worked? When I go to the page that houses this image and resize my window, it works ( very sloppily, but that's an issue for another day). My problem now is that if I enter that page, say, on full screen, the image just goes haywire; sometimes it's too small or too big. I don't know what to do now. I uploaded my indicator function, which is how I change the page; if there is a problem there, let me know.

TLDR:

I want my images to size automatically in reference to the size of the window, but most of the time it just goes haywire.

Hi everyone,

I'm building a multi-page CustomTkinter desktop app where I swap pages inside a main container. I want my text and CTkImage sizes to automatically adjust whenever the user resizes the main window. So far, my widgets automatically adjust because I use .place() with relative sizes and placements. But even if the widget itself grows, the text/image stays the same size, which doesn't look appealing in the slightest.

Basic info:

ghost_pic is the label that houses my CTkImage; this automatically changes size already.

ghost_mid_image is the CTkImage

First try:

I thought that I could try to make the image change its size to match its label every time the window changed size. This is because I made sure that the image is approximately the same size as the label on the default window size, but this didn't do anything; the code didn't work at all.

Second try:

I then decided to just size the image with reference to the window, and this kinda worked? When I go to the page that houses this image and resize my window, it works ( very sloppily, but that's an issue for another day). My problem now is that if I enter that page, say, on full screen, the image just goes haywire; sometimes it's too small or too big. I don't know what to do now. I uploaded my indicator function, which is how I change the page; if there is a problem there, let me know.

TLDR:

I want my images to size automatically in reference to the size of the window, but most of the time it just goes haywire.

I’m a 2nd-year B.Tech CSE student from a Tier-3 college in India, and I’m confused about which backend path to focus on:
Java + Spring Boot
Python backend (FastAPI/Django) + AI
I’ll graduate in 2029, so I want to choose something with good fresher job opportunities.
If you had to choose between these two in my situation, which one would you pick and why? Also, which one do you think will have better demand by 2029?
Would really appreciate honest opinions from people already working in the industry.

Hi, so I tasked myself on making tiny projects daily to refresh my memory on python patterns since I've found it difficult to be consistently learning for a while now.

I'd really appreciate your review of this small and simple beginner level project I did.

Images are attached, should you feel understandably lazy to visit the GitHub page through the link😅.

im 16 indian and i wanna start python from scratch and i know nothing about coding please help me to find resources and guide me 🙏

My first Python project: Postman Clone

I’ve been working on a small project called postman_clone to practice Python and learn more about how APIs and HTTP requests actually work.

I didn’t start with all these features at once. I started with the basics, then kept adding things as I learned. I worked with functions, conditions, user input, JSON, error handling, and HTTP requests, and little by little the project started becoming more complete.

Right now, my project can handle:

• GET
• POST
• PUT
• DELETE
• JSON request bodies
• An optional header
• An optional query parameter
• Basic error handling for requests and JSON

There’s still a lot I want to improve. I want to make the code cleaner, add support for multiple headers and query parameters, improve the error handling, and make the whole thing feel more like an actual API testing tool.

I’m still learning, so I’m posting the code here to get some feedback from people who have more experience with Python.

If you see something I could improve, or if there’s something you think I should add next, I’d really appreciate the advice 🙌

This is still a work in progress, but I’m happy with how far I’ve gotten so far.

if you wanna see the code its in comments

Hi, I have some large data objects that need to be freed. Should I do my_object.clear() and then gc.collect()? Or del my_object then gc.collect()? I'm not sure on the pros/cons of each.

It's a linked list type data object and my_object = [] does not work to free memory for certain.

CLint need a list of 40,000+ members from the ACR directory. Need Name, City, State, Zip, Specialty, Email, and Phone.
The directory/search results give me some of this information, but email, phone, address, Member Since, etc. appear to be available only on the individual member profile.

So I'm trying to figure out the best way to approach this in Python.

If I literally open/request every profile, that's 43k+ profile requests, which obviously makes me concerned about rate limits, blocking, or getting the account/IP banned.

I'm considering Python requests/BeautifulSoup or Playwright, but before attempting something this large I'd like some advice.

This is what I call: little cyka

I just published this open source project to extract contact names and emails from any imap4 compatible mail server.

It let you extract the name, when available, and the associated email address from all the mails sitting in your mailboxes.

Results are persisted in a sqlite file (Turso is actually the engine under the hood) and searchable via the same TUI.

Enjoy Fork and do not hesitate to participate or learn from it.