🚀 How I Built & Published My First Python Package: LogMate

Three weeks ago, I embarked on an ambitious journey—Project52—where, as a marketer with zero prior coding experience, I committed to publishing one new project every week for 52 weeks. My goal? To push myself into the world of programming, covering Python, C, AI, Neural Networks, Deep Learning, and Web Development while building real-world applications.

In the first three weeks of Project52, I:
✅ Built a self-driving 2D AI car using convolutional neural networks and reinforcement learning.
✅ Created a billionaire wealth calculator (HTML, JavaScript, CSS) to visualize wealth growth over time.
✅ Developed a Reddit scraping bot that analyzed 300,000+ comments to identify which countries talk most about AI, politics, and religion.

Each of these projects relied on powerful third-party dependencies—PyTorch, TensorFlow, BeautifulSoup, Matplotlib, Flask, and more. I was fascinated by how seamlessly these packages integrated into my workflow.

But while working on my projects, I encountered a recurring frustration:

➡ Debugging was difficult because of poorly structured log outputs.
➡ Many logs lacked clear timestamps, error classifications, or filtering options.
➡ If an error occurred, I often found myself sifting through long, unstructured error messages just to figure out what went wrong.

That’s when the idea struck:
💡 What if I built a logging tool that made debugging easier, cleaner, and more insightful?

🛠 The Development Journey: Building LogMate

What LogMate Does

LogMate is a smart log management tool that improves traditional logging by:

✔ Enhanced readability – Rich-text output with color-coded levels (INFO, WARNING, ERROR)
✔ Filtered log extraction – Easily find logs based on error type, time range, or keywords
✔ Exporting logs – Save logs as JSON and CSV for deeper analysis
✔ Rotating log files – Prevent bloated log files by managing file size

Structuring the Project Properly

When building LogMate, I had to learn how to structure a Python package properly. The final structure looked like this:

📂 logmate/ → The main package directory
📄 logmate/logmate.py → Core logging logic, including filters, exports, and formatting
📄 setup.py → The packaging script that defines dependencies, metadata, and entry points
📄 README.md → Installation & usage documentation
📄 .gitignore → Prevents unnecessary files from being pushed to GitHub
📂 tests/ → Unit tests to ensure LogMate functions properly

For logging, I used Python’s built-in logging module and integrated Rich for visually enhanced output. The result? A clean, structured, and highly readable logging system that simplifies debugging.

📦 Publishing LogMate to PyPI: The Challenges

One of my main goals was to make LogMate installable via pip install logmate, which meant publishing it to PyPI (Python Package Index). This wasn’t as easy as I expected. Here’s what I learned:

1️⃣ Packaging the Project Correctly

To distribute LogMate, I needed a setup.py file that included:

• The package name, version, and author details

• Dependencies (like rich)

• Entry points for using LogMate as a CLI tool

2️⃣ Creating a GitHub Repository

Uploading to GitHub was straightforward, but I ran into authentication errors because GitHub removed password-based authentication. The fix? Using personal access tokens instead.

3️⃣ Uploading LogMate to PyPI

This was one of the most frustrating steps. I made several mistakes before successfully uploading LogMate to PyPI:

✔ Wrong API token scope – I initially generated an API token without "publish" permissions, which led to upload failures.
✔ Incorrect .pypirc configuration – The authentication details in my config file were wrong.
✔ Fixing authentication – Once I updated the API token, I was able to successfully run:

twine upload dist/*

And finally… LogMate was LIVE on PyPI! 🎉

💡 Try it out now:

pip install logmate
logmate --help

🔥Lessons Learned

Lessons I Learned From This Journey

✅ Understanding Python packaging – Structuring, packaging, and distributing Python modules is an essential skill.
✅ Git & GitHub workflows – Handling authentication, versioning, and releases taught me real-world software engineering.
✅ Importance of documentation – Writing a clear README and usage instructions makes or breaks a project.

Final Thoughts: From a Marketer to a Developer 🚀

This week’s Project52 challenge was a game-changer. I didn’t just build LogMate—I created a dependency that I will actively use in future projects.

More importantly, I proved to myself that:
🔹 Even without a background in coding, I can build and publish real-world software.
🔹 If I can do it, anyone can.

Want to give LogMate a try?

pip install logmate
logmate --help

Here’s LogMate in action 🫡:

Would love to hear your feedback! Let’s make debugging smarter and easier together. 🚀

Want More?

📩 Subscribe to my Project52 journey—where I build and release one new project every week for 52 weeks!

This is just Week 4. 48 more projects to go.
Follow along for AI, Python, Web Dev, and more!

📢 Share Your Thoughts!

🔹 Have you built your own Python package before?
🔹 What are the biggest challenges you faced while publishing to PyPI?
🔹 What feature should I add next to LogMate?

Share your thoughts in the comments! 👇