Python manages memory allocation using a combination of private heap space, garbage collection, and dynamic typing. The memory management process in Python is automatic, meaning developers don’t have to allocate or deallocate memory manually as in languages like C or C++.

Memory Allocation in Python
Python uses a private heap to store objects and data structures. This heap is not accessible to the programmer directly but is managed internally by Python’s memory manager. The manager handles memory requests and ensures efficient memory usage.

There are three main types of memory allocation in Python:

Static Memory Allocation – Used for fixed-size objects like built-in types (integers, floats, etc.).
Stack Memory Allocation – Used for function calls and local variables, following a Last-In-First-Out (LIFO) approach.
Heap Memory Allocation – Used for dynamically allocated objects, such as lists, dictionaries, and user-defined objects.
Garbage Collection
Python has an inbuilt garbage collector (GC) that automatically removes unused objects from memory. It uses reference counting and a cyclic garbage collection mechanism to detect and free memory occupied by objects that are no longer needed. When an object's reference count drops to zero, it is automatically deallocated.

Memory Optimization Techniques
Using generators instead of lists to reduce memory overhead.
Using slots in classes to prevent memory waste.
Avoiding unnecessary variable references.
Using built-in modules like sys to check memory usage.
Efficient memory management is crucial for developing optimized Python applications. To master these concepts and enhance your coding skills, consider enrolling in a Python training in Noida.