Skip to main content

mllogs

Lightweight experiment tracking and model registry 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")

Register and version persisted model artifacts:

model_ref = mll.save_artifact("model", model, "joblib")
mll.registry.create_version("credit-risk", model_ref)

latest = mll.registry.get_latest_version("credit-risk")

create_version automatically registers the model if it does not alreadt exist.

You can also register a model explicitly:

mll.registry.register_model("credit-risk")

And load a specific model version:

version = mll.registry.get_version(
    model_name="credit-risk",
    version=1,
)

Model version reference persisted artifacts, while artifact storage and model registration remain separate parts of the ML lifecycle.

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
  • Register models and create versioned references to persisted model artifacts

Development

Install from source with development dependencies:

pip install -e ".[dev]"

Run the test suite:

pytest

License

MIT

Metadata

Release files for mllogs 0.7.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for mllogs 0.7.1
File Size Uploaded
mllogs-0.7.1.tar.gz 11.2 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for mllogs 0.7.1
File Interpreter ABI Platform
mllogs-0.7.1-py3-none-any.whl Python 3 none any Details

Total release size: 25.9 kB

Release files / mllogs-0.7.1.tar.gz

Download URL mllogs-0.7.1.tar.gz
Size 11.2 kB
Tags Source
SHA-256 checksum
How to use checksums
08e1d43fcc2a27737f849e019fa540998301423f0b0ed94a6a24e55e7a509e04
BLAKE2b-256 checksum
How to use checksums
ce630a1d22e63a4ef08b31450853f173704699bb82a83410993d3e9b1dfac26a
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 Oct 1, 2026.

Transparency log

Release files / mllogs-0.7.1-py3-none-any.whl

Download URL mllogs-0.7.1-py3-none-any.whl
Size 14.7 kB
Tags Python 3
SHA-256 checksum
How to use checksums
52977a8b1acc7c1ae4104c2901358c2bd00e730578b729eccc912c6d2a22e3ae
BLAKE2b-256 checksum
How to use checksums
064547da00e367a1c39cc70aeeea67933da1ca592db8012445f8df36bc5e6e9a
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 Oct 1, 2026.

Transparency log

Release history Release notifications | RSS feed

0.10.0

2 release files

0.9.0

2 release files

0.8.1

2 release files

0.8.0

2 release files

This release

0.7.1 This release

2 release files

0.7.0

2 release files

0.6.1

2 release files

0.6.0

2 release files

0.5.0

2 release files

0.4.0

2 release files

0.3.1

2 release files

0.3.0

2 release files

0.2.1

2 release files

0.2.0

2 release files

0.1.4

2 release files

0.1.3

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page