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ExpOps User Guide

Welcome to the ExpOps user guide! ExpOps is a project-based experiment runner that keeps each experiment isolated under a workspace, runs pipelines, and saves run artifacts with optional tracking/backends.

What is ExpOps?

expops is a comprehensive MLOps platform designed to help you manage machine learning experiments efficiently. It provides:

  • Project-Based Workflow: Each ML project is isolated in its own workspace with independent configurations, dependencies, and artifacts
  • DAG Pipeline Execution: Define complex ML pipelines as directed acyclic graphs (DAGs) using NetworkX
  • Distributed Computing: Execute pipelines on clusters using Dask (with SLURM support) or run locally
  • Environment Isolation: Automatic virtual environment management (venv/conda)
  • Caching & Reproducibility: Intelligent step-level caching with configurable backends
  • Static & Dynamic Reporting: Generate static charts (PNG) and interactive dynamic charts

Quick Start

Get started with ExpOps in minutes:

pip install expops
mkdir -p ~/expops-workspace && cd ~/expops-workspace
expops create sklearn-basic --template sklearn-basic
expops run sklearn-basic --local

Documentation Structure

This guide is organized into the following sections:

Installation

The installed CLI command is expops.

pip install expops