PyCon US 2024 Talk Notes

pycon2024.md

PyCon US 2024 Talk Notes - Unlocking the Parallel Universe: Sub Interpreters and Free-Threading in Python 3.13

Prerequisites

1. PyCon 2023 – Eric Snow talk on sub interpreters
2. EuroPython 2022 – Sam Gross talk on free-threading
3. PyCon 2024 - “Sync vs Async in Python” happening right now
4. PyCon 2024 - Building a JIT compiler for Cpython
5. PyCon 2024 – Overcoming GIL with sub interpreters and immutability
6. “Parallelism and Concurrency” chapter from CPython Internals
7. My Masters Thesis doi.org/10.25949/23974764.v1

Section 1 - Parallel Execution in Python

Parallel Execution

Model	Execution	Start-up time	Data Exchange	Best for…
threads	Parallel *	small	Any	Small, IO-bound tasks that don’t require multiple CPU cores
coroutines	Concurrent	smallest	Any	Small, IO-bound tasks that don’t require multiple CPU cores
multiprocessing	Parallel	large	Serialization	Larger, CPU or IO-bound tasks that require multiple CPU cores
Sub Interpreters	Parallel	medium**	Serialization or Shared Memory	Larger, CPU or IO-bound tasks that require multiple CPU cores

Threading Benchmark

Crude sample:

import numpy

# Create a random array of 100,000 integers
a = numpy.random.randint(0, 100, 100_000)
for x in a:
  abs(x - 50)

Benchmark code to get the "2x slower" figure:

import numpy
import threading
# Create a random array of 100,000 integers between 0 and 100
a = numpy.random.randint(0, 100, 100_000)
def simple_abs_range(vec):
  for x in vec:
    abs(x - 50)
def f_linear():
  # Calculate the distance for each value to 50
  simple_abs_range(a)
def f_threaded():
  threads = []
  # Split array into blocks of 100 and start a thread for each
  for ar in numpy.split(a, 100):
    t = threading.Thread(target=simple_abs_range, args=(ar,))
    t.start()
    threads.append(t)
  for t in threads:
    t.join()

Sub Interpreter vs Thread vs multiprocessing benchmark

The Jupyter Notebook for this sample is here.

Demo

The demo code is here

Terms and Conditions

1. Specializations are not enabled in free threading (yet)
2. GitHub Actions does not have a free-threaded build 1
3. Packaging does not detect the ABI for free-threading correctly 1
4. Some benchmarks are slower with free threading
5. The datetime module is not thread safe 1
6. C Extensions need to support multi-phase-init to be supported with sub interpreters 1
7. Most of your 3rd party C extensions aren’t supported yet 1
8. Cython is not supported 1 2
9. Django does not work in sub interpreters because of (5)
10. Did I mention the datetime module is not thread safe
11. Most PyPi C extensions are not thread safe
12. Orjson, pydantic-core, httptools and uvloop don’t compile
13. Nothing using PY03 is supported 1