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The Real Python Podcast · Yesterday · 1 hr 16 min

Performance Engineering: Profiling and Making Apps Fast by Default

How do you plan for the performance of your Python applications? What does a performance budget entail, and where should you spend your resources? This week on the show, we speak with Den Odell about his new book “Fast by Default: Practical Performance Engineering.” Den has 25 years of experience in building web systems for companies with hundreds of millions of users. Working on public-facing tools has honed his skills in understanding where performance is vital and in guiding decisions based on data from actual users. Den shares details of his performance framework that works across any platform or stack. We discuss the need for budgeting performance during the planning phase, measuring performance through consistent profiling, and keeping systems fast even as your codebase and user base grow. Course Spotlight: Profiling Performance in Python Learn to profile Python programs with built-in and popular third-party tools, and turn performance insights into faster code. Topics: 00:00:00 – Introduction 00:01:39 – Modern systems run across multiple languages 00:03:52 – What lead you toward performance engineering? 00:12:54 – Frameworks and balancing performance against developer experience 00:17:45 – Measuring performance and profiling 00:24:28 – What is Fast by Default? 00:36:34 – Video Course Spotlight 00:38:16 – Breaking into the methodology 00:42:10 – Performance budget 00:48:27 – End user pain points 00:51:21 – Microservices and monoliths 00:54:01 – Performance questionnaire 01:00:31 – What is easier about performance planning upfront? 01:01:50 – Discoveries during the writing process 01:07:01 – Do LLMs write performant code? 01:12:37 – What are you excited about in the world of Python? 01:13:41 – What do you want to learn next? 01:15:02 – How can people follow your work online? 01:15:43 – Thanks and goodbye Show Links: Fast by Default - Den Odell - Manning Discount Link Fast by Default Constraints and the Lost Art of Optimization - Den Odell Python 3.15 Preview: Sampling Profiler Tachyon: High frequency statistical sampling profile Profiling in Python: How to Find Performance Bottlenecks Episode #128: Using a Memory Profiler in Python & What It Can Teach You Episode #172: Measuring Multiple Facets of Python Performance With Scalene Running Python code in a sandbox with MicroPython and WASM Syntorial: The Ultimate Synthesizer Course Den Odell - LinkedIn Den Odell – Author. Staff Web Engineer. Level up your Python skills with our expert-led courses: Speed Up Python With Concurrency Profiling Performance in Python Testing Your Code With Python's unittest Support the podcast & join our community of Pythonistas

0:00-1:16:40

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show notes

How do you plan for the performance of your Python applications? What does a performance budget entail, and where should you spend your resources? This week on the show, we speak with Den Odell about his new book “Fast by Default: Practical Performance Engineering.”

Den has 25 years of experience in building web systems for companies with hundreds of millions of users. Working on public-facing tools has honed his skills in understanding where performance is vital and in guiding decisions based on data from actual users.

Den shares details of his performance framework that works across any platform or stack. We discuss the need for budgeting performance during the planning phase, measuring performance through consistent profiling, and keeping systems fast even as your codebase and user base grow.

Course Spotlight: Profiling Performance in Python

Learn to profile Python programs with built-in and popular third-party tools, and turn performance insights into faster code.

Topics:

  • 00:00:00 – Introduction
  • 00:01:39 – Modern systems run across multiple languages
  • 00:03:52 – What lead you toward performance engineering?
  • 00:12:54 – Frameworks and balancing performance against developer experience
  • 00:17:45 – Measuring performance and profiling
  • 00:24:28 – What is Fast by Default?
  • 00:36:34 – Video Course Spotlight
  • 00:38:16 – Breaking into the methodology
  • 00:42:10 – Performance budget
  • 00:48:27 – End user pain points
  • 00:51:21 – Microservices and monoliths
  • 00:54:01 – Performance questionnaire
  • 01:00:31 – What is easier about performance planning upfront?
  • 01:01:50 – Discoveries during the writing process
  • 01:07:01 – Do LLMs write performant code?
  • 01:12:37 – What are you excited about in the world of Python?
  • 01:13:41 – What do you want to learn next?
  • 01:15:02 – How can people follow your work online?
  • 01:15:43 – Thanks and goodbye

Show Links:

Level up your Python skills with our expert-led courses:

Support the podcast & join our community of Pythonistas

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