Python uses automatic memory management through a combination of manual control and garbage collection. Here's a breakdown of key concepts:
1. Memory Allocation
Python's memory allocator (e.g., malloc in CPython) handles object creation and deallocation.
- Objects are stored in heap memory
id()function shows memory address 📌sys.getsizeof()checks object size in bytes 📏
2. Garbage Collection
Python automatically recycles unused memory via reference counting and cycle detection.
- Objects with zero references are deleted ⚡
gc.collect()triggers manual cleanup 🧹__del__method is deprecated (use context managers instead) 🚫
3. Memory Leaks
Common causes:
- Unreleased resources (e.g., file handles, database connections) 📁
- Circular references in objects 🔄
- Caching large data without proper cleanup 🗑️
Use tracemalloc module to trace memory usage 📊
Learn more about memory profiling
4. Optimization Tips
- Prefer generators over lists for large data streams 🔄
- Use slots in classes to reduce memory footprint 🏗️
- Avoid unnecessary object creation in loops 🚀
- Leverage built-in data types (e.g.,
int,str) for efficiency 🧠
For deeper insights, explore our Python Programming Guide or Performance Tuning section. 📚