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Keep shoppingHigh Performance Python: Master Speed, Scale, and Efficiency
2,256 students
High Performance Python: Master Speed, Scale, and Efficiency
Unlock the full power of Python. Master Profiling, Memory Management, NumPy, Cython, and Parallel Processing.
Created byEduero Academy, Inc.
Last updated 1/2026
English
What you'll learn
- Master Profiling: Identify bottlenecks using cProfile and line_profiler to see exactly where your code is slow.
- Write Efficient Data Structures: Understand the memory impact of Lists vs. Tuples vs. Sets to write memory-efficient code.
- Supercharge with Compiled Code: Use Cython and Nuitka to compile Python into C-speed applications.
- Numerical Computing: Leverage NumPy and Pandas for massive speed gains in data analysis and math operations.
- Concurrency & Parallelism: Bypass the GIL (Global Interpreter Lock) using Multiprocessing and Concurrent Futures.
- Optimize Loops & Logic: Replace slow loops with list comprehensions, map(), generators, and vectorization.
- Advanced Object-Oriented Python: Write robust classes and manage object overhead for scalable applications.
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Course content
9 sections • 44 lectures • 5h 42m total length
Requirements
- Basic understanding of Python syntax (variables, loops, functions).
- A computer (Windows, Mac, or Linux) with Python installed.
- No prior experience with C or low-level memory management is required.
Description
Python is easy to write, but can you make it fast?
Python is the language of choice for data science, web development, and automation. But its simplicity often comes with a cost: speed. As data grows and applications scale, "code that just works" isn't enough. You need code that is efficient, robust, and high-performance.
Welcome to Writing High Performance Python. This course is designed to take you from a functional Python programmer to a true software engineer capable of architecting professional-grade solutions.
We don't just cover the syntax; we look "under the hood" to understand how Python manages memory and CPU resources. You will learn to spot inefficiencies in your code and fix them using professional profiling tools and advanced libraries.
What will you master in this course?
1. The Foundations of Efficiency We revisit Python basics through the lens of performance. You won't just learn what a dictionary is; you’ll learn why it’s faster than a list for lookups. We cover advanced slicing, string interning, and selecting the right data structure for the job to save RAM.
2. Profiling & Diagnosis Stop guessing why your code is slow. You will learn to use cProfile and line_profiler to pinpoint bottlenecks with laser accuracy, ensuring you only optimize the parts that matter.
3. Speed Tools & Libraries We dive deep into the ecosystem of high-performance libraries. You will learn:
NumPy & Pandas: For lightning-fast numerical and data processing.
Cython: To bridge the gap between Python and C, offering massive speed improvements.
Generators: To process huge datasets without crashing your memory.
4. Concurrency & Parallelism Unlock the full power of your CPU. We will cover concurrent.futures and the multiprocessing module to run tasks in parallel, drastically reducing execution time for heavy workloads.
5. Compilation Push Python to its limits by exploring compilation tools like Nuitka and PyPy to run your code faster than standard interpreters ever could.
Who is this course for? This course is perfect for Python developers who know the basics but feel limited by slow scripts or memory errors. Whether you are a Data Scientist processing millions of rows or a Backend Engineer building scalable APIs, these skills are essential for your career growth.
Don't let slow code hold you back. Enroll today and start writing Python that performs as well as it reads.
Who this course is for:
- Python Developers looking to move from Junior to Senior levels.
- Data Scientists dealing with large datasets and slow processing times.
- Self-taught programmers who want to understand Computer Science concepts like memory management and complexity.