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Python package manager with uv-like optimizations

Project description

Hermes

Fast Python package manager with uv-like optimizations

Ever thought why uv is fast, most people attribute it to being written in Rust, but there are several other optimisations that uv does, which we have tried to implement here

IMPORTANT : Hermes is currently designed as an educational project (Not a complete dependency manager, while i would definitely like to make it prod grade, there is a long way to go for that)

PyPI version Python Versions

UV-Inspired Features

  • PubGrub Dependency Resolution - Advanced SAT-based resolver (same algorithm as UV)
  • Parallel Async Downloads - HTTP/2 support with configurable concurrency limits
  • Two-Tier Global Cache - Separate wheels and unpacked package caches
  • Zero-Copy Installations - Reflink → hardlink → copy fallback strategy (30% disk savings on APFS)
  • Lock File Support - Reproducible builds with hermes.lock
  • Fast Metadata Fetching - PEP 658 support for direct .metadata access
  • Virtual Environment Management - Lightweight venv creation without pip
  • Parallel Installation - ThreadPoolExecutor with 4 workers for concurrent package installs
  • SHA256 Verification - Automatic integrity checking for all downloads
  • Platform-Aware Wheel Selection - Intelligent matching for OS, architecture, and Python version
  • Security Auditing - Built-in vulnerability scanning via OSV database
  • Rich CLI - Colored output, progress indicators, and performance tracking

Installation

pip install hermes-pm

Initialize a Project

# Create a new project
mkdir my-project
cd my-project

# Initialize (creates .venv, pyproject.toml, hermes.lock)
hermes init

Add Packages

# Add single package
hermes add requests

# Add multiple packages
hermes add httpx rich typer

# Add with version constraints
hermes add "requests>=2.28.0"
hermes add "httpx<1.0"

Sync from Lock File

# Install from hermes.lock (fast!)
hermes sync

List Packages

# Show all installed packages
hermes list

Remove Packages

# Remove package and unused dependencies
hermes remove requests

# Remove package but keep its dependencies
hermes remove requests --keep-deps

Security Audit

# Scan all installed packages for vulnerabilities
hermes audit

Manage Cache

# View cache statistics
hermes cache info

# Clear cache
hermes cache clear

Performance

Comprehensive benchmarks comparing Hermes against pip and Poetry can be found in the benchmarks directory (Tier wise separation, you can add or remove any packages you want for benchmarking):

Warm Cache Performance (vs pip)

Tier Packages Hermes Speedup Disk Savings
Basic Data Science 5 1.78x faster 32.8% smaller
ML Engineering 8 1.26x faster 29.3% smaller
Full ML Stack 12 1.09x faster 30.4% smaller

Key Highlights:

  • 26-78% faster than pip for cached reinstalls
  • ~30% less disk space through reflink copies (APFS/Btrfs)
  • 4-12x cache effectiveness - dramatically faster warm cache installs
  • Parallel installation with ThreadPoolExecutor (4 workers)

Benchmarked on Python 3.13.7, macOS (Darwin 23.5.0), packages: numpy, pandas, matplotlib, scikit-learn, scipy, etc.

📖 Commands

Command Description
hermes init Initialize a new project (venv, pyproject.toml, hermes.lock)
hermes add <packages> Add and install packages with dependency resolution
hermes list Show all installed packages
hermes remove <packages> Remove packages (includes orphaned dependencies by default)
hermes remove <pkg> --keep-deps Remove package but keep its dependencies
hermes sync Install all packages from hermes.lock
hermes audit Scan installed packages for security vulnerabilities (OSV)
hermes cache info Show cache location, size, and statistics
hermes cache clear Clear the global package cache
hermes --version / -V Show Hermes version
hermes --help Show help message

Inspired by: uv - A production-ready, blazing-fast package manager

Testing

We have a shell file test suite that validates all core functionality

./test_core.sh

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