{"id":25546263,"date":"2022-11-06T15:00:57","date_gmt":"2022-11-06T09:30:57","guid":{"rendered":"https:\/\/entri.app\/blog\/?p=25546263"},"modified":"2023-11-28T12:34:59","modified_gmt":"2023-11-28T07:04:59","slug":"memory-management-in-python","status":"publish","type":"post","link":"https:\/\/entri.app\/blog\/memory-management-in-python\/","title":{"rendered":"How is Memory Managed in Python"},"content":{"rendered":"

Technology is a delicate and sensitive product, just like human skin. If something happens to technology, whether good or bad, it affects the entire system. And, in this ever-changing world, we must be more cautious in our use of technology. Nobody could have predicted in the 1980s that a programming language inspired by ABC (an abandoned programming language) would become one of the most popular languages of the twenty-first century. Python is now responsible for the vast majority of software applications used by people all over the world. Whether it’s machine learning, banking, scientific computing, video games, engineering, or any other imaginable field, chances are you’ll hear the term Python used by the majority of the developers working on the software. Everyone has used it or is using it, from Google, Facebook, Microsoft, NASA, IBM, and various small businesses. If you ask a programmer what the importance of a language is in programming, don’t be surprised if they say that a language is everything that goes into building a program and bringing what is imagined to life. Numerous languages are used for various purposes. However, some languages are universal and have a wide range of applications. Python is one such language that is widely understood and preferred for development all over the world. It is a general-purpose, high-level OOPs-based interpreted language widely used for dynamic applications worldwide. Python is extremely popular due to its versatility and breadth of application. The memory management in python is automatic as the Python developers creates a garbage collector so that the user does not have to do manual garbage collection.<\/p>\n

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Memory Allocation in Python<\/h2>\n

Memory management is the process by which applications read and write data to and from memory. A memory manager decides where to store data from an application. Because memory is limited, like the pages in our book analogy, the manager must find some free space and make it available to the application. Memory allocation refers to the process of providing memory. Python memory management consists of a private heap containing all Python objects and data structures. The Python memory manager is in charge of managing this private heap. The Python memory manager is made up of various components that deal with various aspects of dynamic storage management, such as sharing, segmentation, preallocation, and caching. At the most basic level, a raw memory allocator ensures that there is enough space in the private heap for all Python-related data by interacting with the operating system’s memory manager. In addition to the raw memory allocator, several object-specific allocators operate on the same heap and implement distinct memory management policies tailored to the unique characteristics of each object type.<\/p>\n

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Memory allocation is a critical component of memory management for a developer. This process essentially allows free space in the computer’s virtual memory, and two types of virtual memory work while programs are being executed.<\/p>\n

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  1. Static Memory Allocation<\/li>\n
  2. Dynamic Memory Allocation<\/li>\n<\/ol>\n

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