Python is a slow language---but there are many ways to squeeze performance out of it. This hands-on course looks at techniques and tools for speeding up your Python apps.
Introduction to Python Training • course 1905
This is an advanced course that assumes familiarity with Python programming. However, it is applicable to all Python communities (e.g., web development, data science, automation).
This course is for experience Python programmers looking to expand on their Python experience.
Enhancing Python Performance Training Delivery Methods
- Hands-on labs for enhancing practical skills
- After-course instructor coaching benefit
Enhancing Python Performance Training Course Benefits
Identify bottlenecks in your appsUse concurrent execution to make better use of your computer's resourcesSpeed up numerical apps using NumPyGain performance improvements using JIT compilation
Advanced Python Training Outline
- Measuring execution time
- cProfile
- py-spy
- Concurrency in Python
- threading
- asyncio
- multiprocessing
- Basic optimisations
- NumPy
- Numba
- JAX
- PyPy
- Cython