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Enhancing Python Performance Training

Course 4655

  • Duration: 1 day
  • Language: English
  • Level: Advanced
Get This Course $690
  • 1-day instructor-led training course
  • Earn 7 NASBA credits (live, in-class training only)
  • One-on-one after-course instructor coaching
  • Tuition can be paid later by invoice -OR- at the time of checkout by credit card
#4655
  • Aug 1 9:00 AM - 4:30 PM EDT
    AnyWare
  • Sep 28 9:00 AM - 4:30 PM EDT
    AnyWare
  • Nov 28 9:00 AM - 4:30 PM EST
    AnyWare
  • Jan 18 9:00 AM - 4:30 PM EST
    AnyWare
  • Mar 13 9:00 AM - 4:30 PM EDT
    AnyWare
  • May 31 9:00 AM - 4:30 PM EDT
    AnyWare

Questions about this course?

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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 apps
  • Use concurrent execution to make better use of your computer's resources
  • Speed up numerical apps using NumPy
  • Gain 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

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Course FAQs

Yes. 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).

The course is focused on gaining performance through the use of _Python_ code. While languages such as C/C++ and Rust are important in the development of high-performance Python applications, they are beyond the scope of this course.

The course doesn't focus on any particular IDE. Both Visual Studio Code and PyCharm are provided for use in exercises.

Yes. There are various opportunities to apply the ideas presented to sample Python apps.
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