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Enhancing Python Performance Training

Course 4655

  • Duration: 1 day
  • Language: English
  • Level: Advanced
Get This Course 4.950 kr
  • 1-day instructor-led training course
  • One-on-one after-course instructor coaching
  • Tuition fee can be paid later by invoice -OR- at the time of checkout by credit card
#4655
  • Guaranteed to Run - you can rest assured that the class will not be cancelled.
    sep 28 15:00 - 22:30 CEST
    Virtual
  • nov 22 10:00 - 17:30 CET
    London or Virtual
  • nov 28 15:00 - 22:30 CET
    Virtual
  • jan 18 15:00 - 22:30 CET
    Virtual
  • feb 21 10:00 - 17:30 CET
    London or Virtual
  • apr 13 15:00 - 22:30 CEST
    Virtual
  • maj 16 10:00 - 17:30 CEST
    London or Virtual
  • jul 25 15:00 - 22:30 CEST
    Virtual

Scroll to view additional course dates

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.