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Memory Management

Python Memory Management Reference

Python Memory Management Reference

Cheatsheets & Reference Guides

Python uses automatic memory management with garbage collection via reference counting and generational cycles for efficiency. Key concepts include object allocation, reference tracking, and performance optimization for large datasets.

Python Performance Optimization for Classes

Python Performance Optimization for Classes

Object-Oriented Programming in Python

Learn effective strategies to optimize Python classes for better performance and memory efficiency in applications.

Python slots Explained

Python slots Explained

Object-Oriented Programming in Python

Optimize memory and performance in Python classes using slots, which replaces the default attribute dictionary, reducing overhead and speeding up access.

Reading Large Files Efficiently in Python

Reading Large Files Efficiently in Python

File Handling in Python

Learn efficient methods to read large files in Python without memory issues, handling logs, CSV, and text datasets effectively.

Removing Items from Dictionaries

Removing Items from Dictionaries

Basics of Python

Learn various methods to remove items from dictionaries in Python, including del, pop(), and popitem(), to efficiently manage data and optimize memory usage.

Using slots for Memory Optimization

Using slots for Memory Optimization

Best Practices & Optimization

Using __slots__ in Python reduces memory by preventing dynamic attribute storage in __dict__, optimizing performance for classes with many instances.