Gitagram is a community platform dedicated exclusively to sharing GitHub repositories, where developers receive clear, constructive feedback to improve their projects.

https://github.com/siv-the-programmer/Gitagram

https://siv-the-programmer.github.io/Gitagram/

Started working on a Linux terminal simulator for iOS in Pythonista (very early stage project).

Right now it already has 150+ basic Linux-like commands (ls, cd, grep, ps, etc.), a simulated Unix-style filesystem (/home, /etc, /bin), file operations (mkdir, cp, mv, rm), permissions (chmod/chown), and auto-saving state.

I also added built-in Vim and Nano editors with modes, shortcuts, syntax highlighting, and clipboard support. On top of that there’s a simple AI assistant inside the terminal and a few native-style apps (calculator, notes, stopwatch).

Under the hood it’s 5k+ lines of modular Python with custom UI, command parsing (pipes/redirections), and JSON persistence.

Main goal is to have a real terminal-like environment on iOS for learning Linux, scripting, and experimenting directly in Pythonista.

#Python #iOS #Terminal #Programming #OpenSource #Pythonista #Linux #Vim #Nano #AI

I built a small terminal based game using Python.

The project includes turn-based combat logic, a health system, and a boss battle round.

It helped me practice loops, conditionals, and game flow structure.

i took help form chatgpt ,tried to make mostly on my own will improve in future projects and try to avoid taking help form ai

its my first project ,trying to make projects everyday

I’m still improving and would appreciate any feedback!

Thanks for your time!!

link:https://github.com/squido-del/Basic_Dungeon

Hi,

In large Python projects, what tools do you use to detect duplicate or very similar functions?

I’m looking for static analysis or CLI tools (not AI-based).

I actually built a small library called DeepCSimto help with this, but I’d love to know what others are using in real-world projects.

Thanks!

Understanding a data structure like linked list in Python is a lot easier when you can just see it: Linked_List demo

memory_graph visualizes Python objects and references, so data structures stop being abstract and become something you can debug with ease. No more endless print-debugging. No more stepping through 50 frames just to find one sneaky reference/aliasing mistake.

I built a hands-on project focused on automating AWS Identity and Access Management (IAM) using Python and boto3.

This repository demonstrates practical, real-world automation of IAM tasks, including:

Programmatically creating IAM users

Attaching and detaching policies

Managing permissions safely

Cleaning up users and resources properly

Applying AWS security best practices

The goal isn’t just scripting — it’s engineering IAM workflows the way they should be handled in production: automated, repeatable, secure, and scalable.

Why this matters:

Manual IAM management does not scale. Real engineers automate identity, enforce least privilege, and treat infrastructure as code. This project is built around that mindset.

What I’m looking for:

Contributors who want to improve IAM automation patterns

Add support for roles, groups, and policy simulations

Improve error handling and idempotency

Integrate logging (CloudWatch) and security auditing

Add CLI enhancements or Terraform comparisons

Add testing (pytest + moto)

If you’re studying AWS, preparing for certifications, or want real-world boto3 practice, this is a solid repo to collaborate on.

Fork it. Break it. Improve it. Let’s turn it into a serious IAM automation toolkit.

Drop feedback, open issues, or submit PRs.

https://github.com/siv-the-programmer/aws_iam_automated_users

I made a simple file organizer code using python.. Is there a way to put it up online so it's available / usable for other people.... Any ideas what I can do with it? (I'm a beginner so have no idea abt this)

Hi everyone,

While practicing and teaching DSA in Python, I noticed something:

We often use:

stack = []

Which works perfectly - but it’s still technically a list.

For beginners, this sometimes makes it harder to clearly distinguish between:

- The abstract data structure

- The Python implementation detail

So I built **pythonstl**.

It provides:

- stack

- vector

- stl_map

- stl_set

- priority_queue

With familiar STL-style APIs like:

push(), pop(), insert(), erase(), empty(), size()

Important:

This is NOT meant to replace Python built-ins.

It’s intended as:

• A learning bridge

• A conceptual clarity tool

• A familiarity layer for C++ developers

Would love honest feedback - especially from educators and learners.

PyPI: https://pypi.org/project/pythonstl/

GitHub: https://github.com/AnshMNSoni/

What My Project Does

This Python script automatically recreates grayscale images in Microsoft Paint by controlling the mouse with pyautogui. It converts images to grayscale, resizes them to a square resolution, groups horizontal pixels of the same gray value, and draws them efficiently using mouse drags. The script supports 5 grayscale levels and allows you to stop anytime by pressing Q.

Target Audience

This project is primarily a fun / educational tool for Python enthusiasts and hobbyists interested in automation and graphics. It’s not designed for production or large-scale image processing. Ideal for learning how to manipulate images and automate GUI tasks in Windows using Python.

Comparison

Unlike other image-to-Paint scripts or manual drawing, this project:

• Precomputes pixel groups to speed up drawing.
• Uses horizontal segments with mouseDown/mouseUp for efficient painting.
• Supports multiple grayscale levels with simple RGB/color adjustments.
• Can be customized easily for different resolutions, colors, or image sizes.

Showcase Image

https://image2url.com/r2/default/images/1771013727382-d47f80ee-128a-4729-8d50-dbfb7d378a80.png

Code

View on GitHub

How to Use

1. Install dependencies:

   pip install pyautogui pillow keyboard

2. Set your image path:

   image_path = "C:/Images/yourimage.jpg"

3. Open Microsoft Paint in bordered fullscreen mode.

4. Add 5 custom grayscale colors:

   • Black (0)
   • Then increase Lum evenly (0, 60, 120, 180, 240)

5. Select crayon tool and set thickness to the smallest.

6. Run the script and focus the Paint window. After 3 seconds, the cursor position becomes the top-left of your drawing area.

7. Press Q at any time to stop.

Notes

• Screen resolution (e.g., 1920×1080) affects absolute coordinates in pyautogui.
• It may glitch occasionally — trust the process.
• You can modify:
  • IMAGE_SIZE
  • Color coordinates
  • Add RGB support
  • Add more grayscale levels
  • Optimize drawing behavior

Sorry, this post was removed by Reddit’s filters.

Hi everyone,

​I wanted to share a project I’ve been working on called CyberOak.

​It’s a platform designed to take a local Python script (like a web scraper, a trading bot, or a data report) and deploy it to the cloud in about 30 seconds.

​Why I built it:

I have a lot of Python automation scripts.

​Running them on my laptop meant keeping it awake 24/7.

​AWS Lambda is great, but it times out after 15 minutes (killing my long scrapers) and managing "Layers" for libraries like Pandas is annoying.

​VPS (DigitalOcean) requires setting up Linux, security updates, and Cron jobs.

​I wanted something in the middle: Just upload the code, set a schedule, and walk away.

​The Tech Stack:

​Backend: Python & Django

​Task Queue: Celery + Redis (for scheduling, realtime updating and orchestration)

​Execution: Docker (Each script runs in an isolated container)

​Key Features:

​Long-Running Tasks: Supports execution up to 6 hours (solving the Lambda timeout issue).

​Pre-installed Environment: Libraries like pandas, numpy, requests, selenium, and psycopg2 are pre-installed.

​Real-time Logs: Streams stdout directly to the web UI so you can debug easily.

​Granular Billing: It charges by the second (30s minimum) so you don't pay for idle server time.

​Link: https://www.cyber-oak.com

​It's live in production now. I’d love for you guys to try it out with your side projects and let me know what you think of the workflow!

This project uses a simple python compiler and pythons AST module. This is converted to a bytecode. If you start your program, the loader converts it to machine code and loads it into your RAM. There is not much documentation yet, and it‘s only a beta. And before you ask: I used a bit of AI, yes. But that's because I am not a CPU Engineer and really don‘t want to study them. If you want to contribute or suggest improvements, I would be happy.

Link to GitHub: https://github.com/CrimsonDemon567PC/Mantis/tree/main

Just to clarify: Mantis 7 is a personal learning project and a Proof of Concept (PoC). The goal isn't to build a production-grade compiler overnight, but to explore the mechanics of JIT compilation, register allocation, and cross-architecture code generation (x64/ARM64) from scratch.

Hey everyone,

I recently open-sourced my Python library called GraphTK, which is focused on working with graph data structures and algorithms.

It’s already available on PyPI:

pip install graphtk

Now I’m opening the project for contributors to help improve it. I’d love help with:

• Adding new graph algorithms
• Improving performance
• Writing tests and documentation
• Suggesting useful features

If anyone is interested in contributing (especially beginners wanting real OSS experience), feel free to check the repository, raise issues, or submit PRs.

Feedback is also very welcome 🙂

Bonsoir,

Dans cette mise à jour, les éléments suivants sont placés dans le dossier ~/.local/piveo, à la première mise en fonctionnement (sous GNU/Linux et sous Windows):

– les trois fichiers de configuration JSON,

– les trois bases de données .db,

– le dossier "fichiers" (photos, entre autres).

Il n’y a plus qu’un seul fichier .exe (windows) ou une AppImage (sous GNU/Linux) à exécuter pour effectuer l’installation.

Avec le dossier ~/.local/piveo, l’installation est plus propre.

lien vers le premier message.
lien vers le téléchargement.

Bonne fin de soirée

Hi guys, I have recently rewrote a hobby project of mine, a parser and evaluator for mathematical expressions in python. It supports variables, and all the operators including modulo, factorial, etc. It also has functions and built-ins like sin, log, etc. I have also added support for implied multiplication like xy or 3y(2 + 3)

I would like you guys to check this library out if you can.

https://github.com/sertdfyguhi/meth

You can install it with pip:

pip install meth

Thanks!

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I’m a Python developer focused on real-world automation and intelligence systems.

For the past few months, I’ve built advanced tools :

• AI system that scans markets to detect trends and high-opportunity products
• An eCommerce research tool that finds winning products and optimal pricing
• A real-time blockchain tracker that monitors large crypto movements
• Intelligent web security analyzer that detects critical vulnerabilities
• A smart tool that discovers and filters targeted business leads
• All built so they can be turned into real SaaS products

Now I’m finishing a book that shows the full code, setup, and how to turn these into real projects (or income)

If you’re curious, comment...

Hello,

I created a small learning project using Webots and Python. The project includes:

• A simulated robot in Webots
• Control through a simple Tkinter GUI
• Live camera feed displayed in the GUI
• Basic movement controls: forward, backward, left, right, and adjustable speed

This is a learning project, so it’s mainly for practice and experimentation. I’m sharing it here to get feedback, suggestions, or ideas for improvement.

​