mllogs
Local experiment logging for machine learning.
Installation
pip install mllogs
Usage
Track a run:
from mllogs import MLLogs
mll = MLLogs()
mll.start_run()
mll.log_param("learning_rate", 0.01)
mll.log_metric("accuracy", 0.92)
mll.set_tag("model", "logistic_regression")
mll.save_artifact("model", model, "joblib")
run = mll.complete_run()
Query run data:
mll.query.get_run(run.id)
mll.query.get_params(run.id)
mll.query.get_metrics(run.id)
mll.query.get_tags(run.id)
Load saved artifacts:
mll.query.list_artifacts(run.id)
model = mll.query.load_artifact(run.id, "model")
Features
- Start, complete, and fail experiment runs
- Log parameters, metrics, and tags
- Persist run data to a local SQLite database
- Persist artifacts to local file storage
- Query saved runs and their logged data
Development
Install from source with development dependencies:
pip install -e ".[dev]"
Run the test suite:
pytest
License
MIT
1 maintainer
Metadata
1 maintainer
Release files for mllogs 0.6.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| mllogs-0.6.0.tar.gz | 9.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| mllogs-0.6.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 21.5 kB
Release files / mllogs-0.6.0.tar.gz
| Download URL | mllogs-0.6.0.tar.gz |
|---|---|
| Size | 9.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Transparency logRelease files / mllogs-0.6.0-py3-none-any.whl
| Download URL | mllogs-0.6.0-py3-none-any.whl |
|---|---|
| Size | 12.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
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