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https://github.com/lokeshmohanty/expman-rs

High-performance experiment manager written in Rust, with a Python wrapper for non-blocking logging, a live web dashboard, and a friendly CLI.
https://github.com/lokeshmohanty/expman-rs

experiment-manager interactive-dashboard python rust

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High-performance experiment manager written in Rust, with a Python wrapper for non-blocking logging, a live web dashboard, and a friendly CLI.

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README

          

# Experiment Manager built using Rust

[![Crates.io](https://img.shields.io/crates/v/expman.svg)](https://crates.io/crates/expman)
[![PyPI](https://img.shields.io/pypi/v/expman-rs.svg)](https://pypi.org/project/expman-rs/)
[![GitHub Repo](https://img.shields.io/badge/github-repo-blue.svg?logo=github)](https://github.com/lokeshmohanty/expman-rs)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![Documentation](https://img.shields.io/badge/docs-deploy-blue)](https://lokeshmohanty.github.io/expman-rs)

High-performance experiment manager written in Rust, with a Python wrapper for non-blocking logging, a live web dashboard, and a friendly CLI.

## Features

- **Non-blocking Python logging**: `log_vector()` is a ~100ns channel send — never blocks your training loop
- **Live dashboard**: SSE-powered real-time metric streaming, run comparison charts, artifact browser
- **Scalar metric filtering**: Toggle which metric columns appear in the runs table with one click
- **Single binary**: CLI + web server in one `exp` binary — no Python runtime needed for the server
- **Efficient storage**: Batched Arrow/Parquet writes, not per-step read-concat-write
- **Nix dev environment**: Reproducible with `nix develop`

## Screenshots








## Installation

### From Cargo

```bash
cargo install expman-cli
```

### From PYPI

```bash
pip install expman-rs
```

### Alternatively: Download from GitHub Releases

- **Direct Download**: Download the pre-built standalone `exp` binaries or Python wheels directly from our [GitHub Releases](https://github.com/lokeshmohanty/expman-rs/releases).

## Quick Start

### Python

**Option A: Global Singleton (Easiest)**
```python
import expman as exp

exp.init("resnet_cifar10")
exp.log_params({"lr": 0.001})
exp.log_vector({"loss": 0.5}, step=0)
# Auto-closes on script exit
```

**Option B: Context Manager (Recommended for scope control)**
```python
from expman import Experiment

with Experiment("resnet_cifar10") as exp:
exp.log_vector({"loss": 0.5}, step=0)
```

## For Rust

Basic usage:

```rust
use expman::{ExperimentConfig, LoggingEngine, RunStatus};

fn main() -> anyhow::Result<()> {
let config = ExperimentConfig::new("my_rust_exp", "./experiments");
let engine = LoggingEngine::new(config)?;

engine.log_vector([("loss".to_string(), 0.5.into())].into(), Some(0));

engine.close(RunStatus::Finished);
Ok(())
}
```

### Dashboard

```bash
exp serve ./experiments
# Open http://localhost:8000
```

### CLI

```bash
exp list ./experiments # list all experiments
exp list ./experiments -e resnet # list runs for an experiment
exp inspect ./experiments/resnet/runs/20240101_120000
exp clean resnet --keep 5 --force # delete old runs
exp export ./experiments/resnet/runs/20240101_120000 --format csv
```

## Development

Please see [CONTRIBUTING.md](CONTRIBUTING.md) for detailed instructions on setting up your local environment, building the Python bindings, and important git configuration notes.

```bash
nix develop # enter dev shell
just test # run all tests
just dev-py # build Python extension (uv pip install -e .)
just serve ./experiments # start dashboard
just watch # watch mode for tests
just build-docs # build and open documentation
```

## Documentation

For detailed usage, refer to the standalone documentation files for each component:
- [`expman-cli`](crates/expman-cli/README.md) - Command-line interface definitions and references.
- [`expman`](crates/expman/README.md) - Core high-performance async Rust logging engine.
- [`expman-py`](crates/expman-py/README.md) - Python extension for non-blocking logging.
- [`expman-server`](crates/expman-server/README.md) - Axum web server and SSE live streaming API.

### Dashboard Features
- **Live Metrics**: Real-time SSE streaming of experiment metrics and logs.
- **Live Jupyter Notebooks**: Instantly spawn a live Jupyter instance natively bound to any run's execution environment directly from the UI, with auto-generated analytics boilerplate (Polars).
- **Scalar Filter**: Toggle individual metric columns in the Runs table via chip buttons — no page reload.
- **Deep Inspection**: View detailed run configurations, metadata, and artifacts.
- **Artifact Browser**: Preview `parquet`, `csv`, and other files directly in the browser.
- **Comparison View**: Overlay multiple runs on a shared timeline for analysis.
- **Server-side filtering**: Pass `?metrics=loss,acc` to `/api/experiments/:exp/runs` to limit which scalars are returned.

## Examples

Practical code samples are provided in the [examples/](examples/) directory. The Python example demonstrates logging metrics, alongside generating and storing rich media artifacts (audio, video, plots) directly natively.

- **Python**: [examples/python/basic_training.py](examples/python/basic_training.py)
- **Rust**: [examples/rust/logging.rs](examples/rust/logging.rs)

To run the Python examples, ensure you have built the extension first with `just dev-py` and installed the dev dependencies (`uv pip install -e ".[dev]"`).

To run the Rust example, use:

```bash
cargo run --example logging -p expman
```

## Experiments Layout

```
experiments/
my_experiment/
experiment.yaml # display name, description
20240101_120000/ # run directory
metrics.parquet # all logged metrics (Arrow/Parquet)
config.yaml # logged params/hyperparameters
run.yaml # run metadata (status, duration, timestamps)
run.log # text log
artifacts/ # user-saved files
```