Local-first, git-aware ML experiment tracking.
Project description
Trackle
Trackle is a lightweight, local-first, git-aware ML experiment tracker.
Goals
- Local filesystem storage only
- No servers or networking
- Simple Python API and CLI
- Git-based reproducibility
Installation
pip install trackle-ml # from PyPI
# or for development
pip install -e .
# optional extras
# pip install trackle-ml[viz] # matplotlib plots
# pip install trackle-ml[rich] # richer CLI output (if extended)
Quick start
import trackle_ml as trackle
trackle.init(run_name="demo")
trackle.log_params({"lr": 0.01})
trackle.log_metric("loss", 0.5, step=1)
trackle.finish()
Storage layout
Runs are stored locally (default ./trackle_experiments):
trackle_experiments/
runs/
<run_id>/
run.json # metadata: name, created_at, finished_at, duration_s, tags
params.json # merged params
metrics.csv # step,key,value,timestamp
context.json # env info (python/os/hw/torch)
git.json # git commit/branch/dirty/remote
artifacts/ # copied artifacts
notes.md # optional note
CLI
trackle-ml list-runs [--base DIR] [--limit N]
trackle-ml diff-runs <run_a> <run_b> [--base DIR]
trackle-ml plot-metrics <run_id> [--key metric] [--base DIR]
Project details
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