ud-resolver 1.1.6

A universal dependency resolver supporting multiple package ecosystems

Universal Dependency Resolver

Resolve dependencies across PyPI (pip), npm, Cargo, Go, and more — detect conflicts, check system compatibility, and export to any format.

udr resolve numpy@pypi torch@pypi
  → numpy 1.26.2, torch 2.1.2+cu121 (CUDA 12.1)

The Problem

Your project pulls in packages from everywhere — Python scripts call Node services, Docker images need both pip and apt packages, and your CI pipeline has to pin every transitive dependency across all of them.

Existing tools only work within one ecosystem. pip-compile handles Python. npm ls handles JavaScript. But cross-ecosystem conflicts go undetected until something breaks at runtime. And system compatibility — GPU drivers, CUDA versions, OS patches — is never checked at all.

This tool fixes that.

Quick Start

pip install ud-resolver

Install with extras for additional features:

pip install "ud-resolver[system]"       # GPU & system scanning
pip install "ud-resolver[monitoring]"   # OpenTelemetry & Sentry
pip install "ud-resolver[security]"     # Auth & JWT support
pip install "ud-resolver[postgres]"     # PostgreSQL + Redis + Celery
pip install "ud-resolver[all]"          # Everything

CLI Usage

# Start the API server
udr serve --port 8000

# Check system compatibility
udr check

# Resolve dependencies
udr resolve numpy pandas scikit-learn

# Resolve from other ecosystems
udr resolve react vue -e npm
udr resolve serde tokio -e crates

# Show system info
udr info

# Auto-detect manifests in project dir and lock all deps
udr lock

# Lock with explicit manifest
udr lock --manifest requirements.txt --manifest package.json

# Dry-run lock (no files written)
udr lock --dry-run

# Resolve with JSON output
udr resolve torch torchvision --format json

Python Library Usage

import asyncio
from backend.core.data_aggregator import DataAggregator
from backend.core.conflict_resolver import ConflictResolver
from backend.core.system_scanner import SystemScanner
from backend.manifest_detector import ManifestDetector

async def main():
    scanner = SystemScanner()
    system_info = await scanner.scan_all()
    print(system_info["platform"]["system"], system_info["cpu"]["brand"])

    aggregator = DataAggregator()
    data = await aggregator.get_package_info("torch", ecosystem="pypi",
                                              include_dependencies=True,
                                              include_versions=True)
    print(data["name"], data["versions"])

    detector = ManifestDetector("./my-project")
    manifests = detector.detect()
    packages = detector.normalize(detector.parse_all(manifests))
    print(f"{len(packages)} packages found")

asyncio.run(main())

Features

Feature	What it does
Multi-ecosystem	PyPI (pip), npm, Cargo, Go, Conda, Maven, NuGet, RubyGems, Linux packages, Homebrew
GPU-aware resolution	Scans CUDA, cuDNN, GPU memory — resolves CUDA variants automatically
System scan	Detects OS, CPU, GPU, Python, Node.js, GCC, Java
12 export formats	Dockerfile, requirements.txt, package.json, docker-compose.yml, install.sh, CMakeLists.txt, pyproject.toml, environment.yml, Cargo.toml, build.gradle, pom.xml, Gemfile
CI/CD ready	CLI for pipelines, health check endpoint, structured logging

API Quick Reference

Endpoint	Method	Purpose
/api/v1/packages/search	GET	Search across ecosystems
/api/v1/packages/{ecosystem}/{name}	GET	Get package info
/api/v1/packages/versions	GET	List versions
/api/v1/packages/resolve	POST	Resolve dependencies
/api/v1/packages/export	POST	Export to any format
/api/v1/packages/export-formats	GET	Available export formats
/api/v1/system/info	GET	System information
/api/v1/system/check-compatibility	POST	Check dependency-system fit
/api/v1/scan/github	POST	Scan a GitHub repo
/api/v1/scan/upload	POST	Scan an uploaded archive
/api/v1/scan/local	POST	Scan a local directory
/api/v1/health	GET	Health check

How It Works

Your request → Fetch metadata from ecosystem registries
                   ↓
            Scan target system (OS, GPU, Python, CUDA)
                   ↓
            Resolve conflicts with SAT solver
                   ↓
            Export to 12 formats

The system runs as a FastAPI service with optional PostgreSQL and Redis.

Also available

This package is the backend component. The project also ships:

• Web UI — a browser-based GUI (Vue.js), available as a Docker image or bundled in the desktop app
• Desktop app — standalone cross-platform application (Windows, macOS, Linux) with backend + frontend bundled, no Python or Node.js required

See the full documentation for details.