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 0.6.1
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-0.6.1.tar.gz | 9.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| mllogs-0.6.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 21.7 kB
Release files / mllogs-0.6.1.tar.gz
| Download URL | mllogs-0.6.1.tar.gz |
|---|---|
| Size | 9.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
b1e4f60fddf0a12a7edf79ee4786f988ffb7a7a15f830e9d874519f86125361d
|
|
BLAKE2b-256 checksum How to use checksums |
1924923b207b88a81cced3206790de93aba1e983f52bd938acd0b761bcf92104
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 30, 2026.
Transparency logRelease files / mllogs-0.6.1-py3-none-any.whl
| Download URL | mllogs-0.6.1-py3-none-any.whl |
|---|---|
| Size | 12.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
775f6965b0edb9d0236d52297667f3f7c1409d671457bbb9e00b00fd7cb7ae23
|
|
BLAKE2b-256 checksum How to use checksums |
c83974027b5d01b6c8513fbc409efaada0c7da7d817e09cc3c7bf1e648c6d618
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 30, 2026.
Transparency log
