21. Memory Leaks

This chapter describes some techniques for detecting and fixing memory leaks. Much of this is taken from the pymemtrace project

• 21.1. Introduction
  • 21.1.1. Is it a Leak?
  • 21.1.2. Sources of Leaks
  • 21.1.3. A Bit About (C)Python Memory Management
    • 21.1.3.1. Reference Counts
    • 21.1.3.2. Garbage Collection
    • 21.1.3.3. The Big Picture
    • 21.1.3.4. CPython’s Object Allocator (pymalloc)
• 21.2. Tools for Detecting Memory Leaks
  • 21.2.1. Platform Tools
    • 21.2.1.1. Windows
    • 21.2.1.2. Linux
    • 21.2.1.3. Mac OS X
  • 21.2.2. Python Tools
    • 21.2.2.1. Modules from the Standard Library
    • 21.2.2.2. Third Party Modules
  • 21.2.3. Debugging Tools
  • 21.2.4. Building a Debug Version of Python
• 21.3. Techniques
  • 21.3.1. High Level
    • 21.3.1.1. Using Platform Tools
    • 21.3.1.2. Specific Tricks
• 21.4. pymemtrace
  • 21.4.1. pymemtrace Tools
  • 21.4.2. Tool Characteristics
    • 21.4.2.1. Licence
    • 21.4.2.2. Credits
  • 21.4.3. pymemtrace Process
  • 21.4.4. pymemtrace cPyMemTrace
    • 21.4.4.1. Logging Changes in RSS
    • 21.4.4.2. Logging Every Event
  • 21.4.5. pymemtrace and DTrace
  • 21.4.6. pymemtrace trace_malloc
    • 21.4.6.1. Using trace_malloc Directly
    • 21.4.6.2. Using trace_malloc as a Decorator
  • 21.4.7. pymemtrace Debug Malloc Stats