Environments & Deployment

This section covers running py3plex from the command line, in Docker containers, and at scale.

This section covers:

• Docker Usage Guide — Command-line interface and containerized deployment

• Performance and Scalability Best Practices — Memory management, optimization, large networks

When to Use This Section

Read this section when you need to:

• Automate analyses that currently run interactively

• Process networks too large for a single Python session

• Share reproducible environments with collaborators

• Integrate py3plex into a production pipeline

CLI provides a scriptable interface for common operations—no Python required.

Docker ensures identical results everywhere, eliminating environment issues.

Performance chapter covers memory management and optimization for large networks.

Start with Docker Usage Guide for automation, then Performance and Scalability Best Practices for optimization.

Tip

Deployment checklist:

• Version-pin all dependencies

• Add error handling for edge cases

• Verify results on test data

• Set up logging for debugging

• Test on the target environment