A lightweight async-compatible experiment framework for safely comparing candidate code paths to control logic.
Project description
Scientist-Py
A lightweight, async-compatible Python port of GitHub's Scientist for testing candidate code paths against a control in production without affecting users.
Features
- 🧪 Run control and candidate functions safely
- ⏱️ Measure execution time of each path
- ⚠️ Compare results and log mismatches
- ✅ Support for
asyncfunctions - 🎯 Sampling to control experiment frequency
- 🛡️ Ignore known exceptions
- 📊 Metric logging out-of-the-box
What are Control and Candidate in Scientist?
Control = The current, trusted, production logic.
Candidate = The new or experimental logic you're testing against the control.
Why use this?
It’s the safest way to test new implementations without breaking stuff. You can:
Rewrite a function (e.g., old regex → new parser)
Replace a service call (e.g., REST → GraphQL)
Try a new algorithm or optimization
All while continuing to serve the real user with the proven control.
Installation
Simply copy the Experiment class into your project. No external dependencies required.
Usage
Basic Example
from experiment import Experiment
exp = Experiment("add-function")
@exp.control
def control():
return 2 + 2
@exp.candidate
def candidate():
return 2 + 2 # or some experimental logic
result = await exp.run()
With async functions
@exp.control
async def control():
await asyncio.sleep(0.1)
return 2 + 2
@exp.candidate
async def candidate():
await asyncio.sleep(0.1)
return 4
Add a custom comparator
exp.compare_with(lambda a, b: round(a, 2) == round(b, 2))
Ignore known exceptions
exp.ignore_exceptions(ValueError)
Enable sampling (e.g. 10% of the time)
exp.sample(0.1)
Logging Output
When a mismatch is found, logs look like:
[Experiment: add-function] Mismatch detected!
- Control result: 4
- Candidate result: 5
[Experiment: add-function] Metrics:
- Control duration: 0.000120 sec
- Candidate duration: 0.000150 sec
- Match: False
License
MIT (or adapt as needed for internal tools)
Inspired By
TODO
- Persistent result storage (e.g., file/DB)
- Dashboard or reporting
- Integration with Prometheus or StatsD
Project details
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