This document discusses profiling Python performance. It begins by acknowledging that Python can be slow due to the Global Interpreter Lock (GIL) and lack of a just-in-time (JIT) compiler. It then demonstrates how to profile a Python program using the pyflame tool to collect stack samples and convert them to a flamegraph for analysis. The document shows pyflame being used to profile a simple Sanic web application under load testing. It finds that pyflame has surprisingly little overhead and concludes that while Python has limitations, it is not inherently slow when profiled and optimized properly.

1. Python performance
engineering in 2017
Alex Chistyakov, an engineer @ some company

2. Agenda
- Is Python slow?
- How to profile a Python program?
- We are not going to talk about blockchain, sorry
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3. Is Python slow?
- Definitely, because of GIL and lack of proper JIT
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4. Is Python slow?
- Definitely, because of GIL and a lack of a proper JIT
compiler
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5. Is Python slow?
- Seriously, how do you define “to be slow”?
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6. Okay, let’s do our homework finally
- Vagrant + https://github.com/alexclear/piterpy2017
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7. Okay, let’s do our homework finally
- Vagrant + https://github.com/alexclear/piterpy2017
- 2-cores VirtualBox VM
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8. Okay, let’s do our homework finally
- Vagrant + https://github.com/alexclear/piterpy2017
- 2-cores VirtualBox VM
- Something called Sanic:
https://github.com/channelcat/sanic because it’s 2017
and 2.x era should have ended years ago
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9. Okay, let’s do our homework finally
- Vagrant + https://github.com/alexclear/piterpy2017
- 2-cores VirtualBox VM
- Something called Sanic:
https://github.com/channelcat/sanic because it’s 2017
and 2.x era should have ended years ago
- A load testing tool called ab because we love classics
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10. What is a typical Python program?
- https://goo.gl/Abz8LX (Please note that this link will
produce different results in 5 years)
- Something not too server-side (or a framework)
- Something scientifical
- Some utility
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11. What is a typical Python program?
- https://goo.gl/Abz8LX (Please note that this link will
produce different results in 5 years)
- Something not too server-side
- Something scientifical
- Some utility
- An async web application!
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12. A crash course in modern profiling
- Collect stack samples at all costs
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13. A crash course in modern profiling
- Collect stack samples at all costs
- Convert collected samples to Brendan Gregg’s
flamegraph.pl format
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14. A crash course in modern profiling
- Collect stack samples at all costs
- Convert collected samples to Brendan Gregg’s
flamegraph.pl format
- Create a flamegraph
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15. Collecting samples
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16. Collecting samples
- Uber’s pyflame: https://github.com/uber/pyflame
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17. A bit of internal dark magic
- pyflame uses ptrace(2) system call
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18. A bit of internal dark magic
- pyflame uses ptrace(2) system call
- It attaches to a running process and traverses its memory
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19. Limitations
- Linux only
- CPython only
- Should have enough privileges
- Can be slow (again, what is “to be slow”? I honestly have
no idea)
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20. Enough on that, let’s get real
- Starting the server:
python3 ./sanic-app.py 1>/dev/null 2>/dev/null
- (It does basically nothing, just “hello world” stuff)
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21. Enough on that, let’s get real
- Stressing the server:
ab -n 300000 -c 300 http://127.0.0.1:8000/
- Please note that using ab for real world simulations is
totally insane, but this is exactly what we want now
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22. How slow is pyflame?
- We run tests with and without pyflame
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23. Interactive demo time!
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24. Conclusions
- Pyflame is surprisingly fast!
- Python is not slow, it’s just drawn that way
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25. Questions, please?
- alexclear@gmail.com
- Skype, Telegram: demeliorator
- Shameless advertising: http://t.me/lhommequipleure
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