Intel®️ Tiber™️ App-Level Optimization blogs: Python
Profiling in Python: Top Tools and 5 Tips for Success
Profiling Python code involves modifying the program’s executable binary form or source code and using an analyzer to investigate the code
Understanding PySpark: Features, Ecosystem, and Optimization
PySpark is a Python library for Apache Spark that allows users to interface with Spark using Python
5 PySpark Optimization Techniques You Should Know
Apache PySpark is the Python API for Apache Spark, an open-source, distributed computing system that is designed for high-speed processing of...
Python vs. Java: Performance, Scalability, and Stability
Python is a high-level programming language that abstracts memory management, processes, pointers, and threads. Java is a popular low-level...
Python Performance: Optimization Tips and Faster Python Versions
Python is considered slower than other languages. Learn about ways to optimize Python performance, and new Python versions that offer...
Python Performance Testing: Quick Tutorial and Best Practices
Python offers several tools to identify performance bottlenecks and track important metrics in your code.
3 Ways to Improve Python Application Performance Using Continuous Profiling
This article illustrates the concept of continuous profiling, how to execute it for Python applications, and choosing the right tool for you.
Introduction to the Infamous Python GIL
Learn the function of the Python GIL, its potential performance impacts, and how it can be bypassed when necessary.