Claude Artifact

The size of a Python process can vary significantly depending on several factors. Let me break this down:

A basic Python interpreter process typically starts around 8-15MB of RAM when first launched. However, the actual memory usage can grow substantially based on:

1. Imported libraries/modules

• Basic libraries like numpy can add 30-100MB
• Heavy frameworks like TensorFlow can add hundreds of MB
• GUI frameworks like PyQt can add 50-150MB

1. Data loaded into memory

• Working with large datasets
• Caching operations
• Object creation and retention

1. Operating System

• Windows Python processes tend to use slightly more memory than Linux
• Memory allocation and reporting differs between platforms

1. Python version

• Python 3.x generally uses more memory than Python 2.x
• Different versions have different memory optimization features

For a typical data processing script with common libraries like pandas and numpy, you might expect:

• Minimum: ~50MB