Python debugging, redefined.
Cyberbrain: Python debugging, redefined.
Cyberbrain1(电子脑) aims to free programmers from debugging. It lets you:
Backtrace variable changes.
See every state of program execution, including variables' values
Debug loops with confidence.
Never spend hours stepping through a program, let Cyberbrain tell you what happened.
I gave a talk at PyCascades 2021 about Cyberbrain, watch it here.
To install Cyberbrain:
pip install cyberbrain code --install-extension laike9m.cyberbrain
How to Use
Suppose you want to trace a function
foo, just decorate it with
from cyberbrain import trace # As of now, you can only have one @trace decorator in the whole program. # We may change this in version 2.0, see https://github.com/laike9m/Cyberbrain/discussions/73 @trace # Disable tracing with `@trace(disabled=True)` def foo(): ...
Cyberbrain keeps your workflow unchanged. You run a program (from vscode or command line, both work), and a new panel will be opened to visualize how your program executed.
The following gif demonstrates the workflow (click to view the full size image):
Read our documentation to learn more about Cyberbrain's features and limitations.
❗Note on use❗
- Cyberbrain may conflict with other debuggers. If you set breakpoints and use VSC's debugger, Cyberbrain may not function normally. Generally speaking, prefer "Run Without Debugging" (like shown in the gif).
- If you have multiple VS Code window opened, the trace graph will always be created in the first one. #72 is tracking this issue.
- When having multiple decorators, you should put
@traceas the innermost one.
@app.route("/") @trace def hello_world(): x = [1, 2, 3] return "Hello, World!"
Cyberbrain is new and under active development, bugs are expected. If you met any, please create an issue. At this point, you should NOT use Cyberbrain in production. We'll release 1.0 when it's ready for production.
Major features planned for future versions are listed below. It may change over time.
|1.0||Code & trace interaction (#7), API specification|
|2.0||Multi-frame tracing (👉 I need your feedback for this feature)|
|4.0||Fine-grained symbol tracing|
Visit the project's kanban to learn more about the current development schedule.
How does it compare to other tools?
PySnooperPySnooper and Cyberbrain share the same goal of reducing programmers' work while debugging, with a fundamental difference: Cyberbrain traces and shows the sources of each variable change, while PySnooper only logs them. The differences should be pretty obvious after you tried both.
Debug VisualizerDebug visualizer and Cyberbrain have different goals. Debug visualizer visualizes data structures, while Cyberbrain visualizes program execution (but also lets you inspect values).
Python TutorPython Tutor is for education purposes, you can't use it to debug your own programs. It's a brilliant tool for its purpose and I do it like it very much.
Static analysisCyberbrain is *NOT* static analyis. It's runtime tracing. Static analysis can't provide enough information for debugging.
- 💬 GitHub Discussions (for general discussions)
- 🤖 Discord (for more instant discussions. I'm happy to chat any time!)
- 🐦 Twitter @PyCyberbrain (for announcements)
Interested in Contributing?
Thanks goes to these wonderful contributors ✨
林玮 (Jade Lin)
Cyberbrain is a huge and complicated project that will last for years, but once finished, it will reshape how people think and do debugging. Your support can help sustain it. Let's make it the best Python debugging tool 🤟!
Cyberization is the process whereby a normal brain is physically integrated with electronic components to produce an augmented organ referred to as a cyberbrain.
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