MattFor

MattFor / LogEye

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Frictionless logging/tracing for Python! No debugger needed.

pypi.orgprojectlogeye ast beginner-friendly introspection logging logging-framework
13
1
100% credibility
Found Mar 29, 2026 at 13 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

LogEye is a Python library that provides automated, real-time logging of variable changes, function calls, and data mutations to visualize code execution without needing a debugger.

How It Works

1
🔍 Discover LogEye

You hear about a simple way to peek inside your running code and see exactly what happens step by step, like magic print statements that do all the work.

2
📦 Add it to your code

You sprinkle a special marker called @log on top of your functions or variables, taking just seconds.

3
▶️ Run your program

You hit run, and instantly colorful logs appear showing function calls, variable updates, and results as they happen.

4
✨ Watch it come alive

Everything lights up: you see numbers changing, lists growing, and logic flowing right before your eyes, making tricky code crystal clear.

5
📚 Switch to story mode

For learning, you flip on educational mode and the logs turn into a friendly narrative, perfect for students or teaching.

6
⚙️ Tweak the details

You choose what to focus on, like certain variables or save logs to a file, keeping it simple and tailored.

🎉 Master your code

Now you understand every twist and turn without frustration, debugging feels effortless, and you confidently build better programs.

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AI-Generated Review

What is LogEye?

LogEye is a frictionless Python logging/tracing library on GitHub that lets you understand code execution in real time without a debugger. Drop `@log` on functions to trace calls, variable changes, and returns, or wrap values with `log()` for automatic assignment logging—think print debugging, but structured and automated. It tracks object mutations and supports file output, making it dead simple for Python devs ditching manual prints.

Why is it gaining traction?

It stands out with "educational mode" that turns raw traces into readable stories, like clean recursion flows or algorithm steps, without args/kwargs noise. Filters, verbosity levels (call/state/full), and mutation tracking for lists/dicts/sets beat basic logging libs—no setup, instant drop-in. Devs love the zero-overhead feel for quick insights, especially over clunky debuggers.

Who should use this?

Python beginners tracing algorithms, students debugging recursion or sorts, and teachers demoing data structures. Ideal for solo devs prototyping without IDE debuggers, or anyone tired of scattered prints in scripts—perfect for educational factorial, Dijkstra, or radix sort examples.

Verdict

Try it for teaching or quick traces; demos shine, docs are solid with PyPI install. At 13 stars and 1.0% credibility, it's early—test thoroughly for edge cases like deep recursion—but promising frictionless py GitHub gem for no-debugger-needed logging.

(178 words)

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