mllogs
Local experiment logging for machine learning.
Installation
pip install mllogs
Usage
from mllogs import MLLogsClient
client = MLLogsClient()
client.start_run(
name="baseline",
run_type="training",
)
client.log_param("learning_rate", 0.01)
client.log_metric("accuracy", 0.92)
client.set_tag("model", "logistic_regression")
client.end_run()
Features
- Start and end experiment runs
- Log parameters, metrics, and tags
- Save runs to local storage
- Load, list, and delete saved runs
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 0.1.3
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-0.1.3.tar.gz | 5.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| mllogs-0.1.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 9.9 kB
Release files / mllogs-0.1.3.tar.gz
| Download URL | mllogs-0.1.3.tar.gz |
|---|---|
| Size | 5.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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| Download URL | mllogs-0.1.3-py3-none-any.whl |
|---|---|
| Size | 4.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
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