Metadata-Version: 2.4
Name: structured-ml-logging
Version: 0.1.0
Summary: Structured logging for ML experiments with schema validation and pluggable sinks.
Author: arec1b0
License: MIT License
        
        Copyright (c) arec1b0 2025
        
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License-File: LICENSE
Requires-Python: >=3.10
Requires-Dist: pydantic>=2.6
Requires-Dist: requests>=2.31
Provides-Extra: dev
Requires-Dist: mypy>=1.10; extra == 'dev'
Requires-Dist: pytest>=8; extra == 'dev'
Requires-Dist: ruff>=0.5; extra == 'dev'
Requires-Dist: types-requests>=2.31; extra == 'dev'
Provides-Extra: gcp
Requires-Dist: google-cloud-logging>=3.10; extra == 'gcp'
Description-Content-Type: text/markdown

# Structured ML Logging

Structured (JSON) logging for ML experiments with schema validation and pluggable sinks.

## Installation (dev)

```bash
pip install -e ".[dev]"
````

## Quickstart

```python
from mlog import get_logger, run_context

log = get_logger(project="demo", experiment="baseline", sink="stdout", validation="strict")

with run_context(run_id="run_001", tags={"team": "ml"}):
    log.param("lr", 0.01)
    log.metric("train.loss", 0.123, step=1)
    log.event("done")
```