Python Memory Model Explained | Stack, Heap, Objects | 8

In this video, we take a deep dive into the Python Memory Model to understand how Python stores variables, objects, and function calls in memory. This topic is extremely important for writing efficient code, avoiding memory leaks, and understanding performance behavior in Data Engineering pipelines.

We will clearly explain how stack and heap memory are used, how objects are created, and how garbage collection works internally.

🔥 What You Will Learn

• What is Python memory model
• Difference between stack and heap in Python
• How variables are stored as references to objects
• How objects are created in heap memory
• Role of stack frames in function execution
• Mutable vs immutable objects and memory behavior
• Reference counting mechanism
• Python garbage collection explained
• How circular references are handled
• Memory issues in long-running ETL and batch jobs
• Best practices to manage memory in Data Engineering scripts
• Interview-ready explanation of Python memory model

This session is part of the Python for Data Engineering Playlist, designed for Data Engineers who want strong Python internals before working with Spark, Airflow, and large-scale data pipelines.

🔗 Playlists

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