Service restrictions from February 12-22, 2026—more information on the University Library website

Result: THE POSSIBILITIES OF USING PARALLEL PROGRAMMING USING PYTHON

Title:
THE POSSIBILITIES OF USING PARALLEL PROGRAMMING USING PYTHON
Source:
Q A Iasaýı atyndaǵy Halyqaralyq qazaq-túrіk ýnıversıtetіnіń habarlary (fızıka matematıka ınformatıka serııasy). 28:105-114
Publisher Information:
Khoja Ahmed Yasawi International Kazakh-Turkish University, 2024.
Publication Year:
2024
Document Type:
Academic journal Article
ISSN:
2524-0080
DOI:
10.47526/2024-1/2524-0080.09
Accession Number:
edsair.doi...........b0d9aae821356b79cf564b4e73e29b09
Database:
OpenAIRE

Further Information

This article explores the development of parallel software applications using the Python programming language. Parallel programming is becoming increasingly important in the information technology world as multi-core processors and distributed computing become more common. Python provides developers with a variety of tools and libraries for creating parallel applications, including threads, processes, and asynchronous programming. This topic covers the basics of parallel programming in Python, including the principles of thread and process management, error handling, synchronization mechanisms, and resource management. He also considers asynchronous programming using the asyncio library, which allows you to efficiently handle asynchronous tasks. In addition, this topic raises issues of optimization and profiling of parallel applications, as well as explores distributed parallel programming using third-party libraries and frameworks. He also emphasizes the importance of testing and debugging in the context of parallel programming. Research and experiments in parallel programming using Python help developers create high-performance and efficient applications that can effectively use multi-core systems and distributed computing. This article offers an in-depth study that examines how Python is suitable for teaching parallel programming to inexperienced students. The results show that there are obstacles that prevent Python from maintaining its advantages in the transition from sequential programming to parallel.