Instructor Notes
Testing this lesson
A lot of the code in this lesson can be tested using Entangled. You may tangle source files by running
entangled tangle -aA set of source files will appear in
<project-root>/src, including a Poetry environment
for running the tests and benchmarks. You may also run
entangled daemon if you want to debug the code, changes
made to the files in src will then be merged back into the
lesson material automatically.
TOML
[tool.poetry]
name = "parallel-python"
version = "0.1.0"
description = "Testing environment for Parallel Python workshop"
authors = ["Johan Hidding <j.hidding@esciencecenter.nl>"]
license = "Apache-2.0"
[tool.poetry.dependencies]
python = ">=3.9, <3.11"
numba = "^0.56.4"
dask = {extras = ["complete"], version = "^2022.12.1"}
richbench = "^1.0.3"
matplotlib = "^3.6.2"
numba-progress = "^0.0.4"
pandas = "^1.5.2"
plotnine = "^0.10.1"
[tool.poetry.dev-dependencies]
[build-system]
requires = ["poetry-core>=1.0.0"]
build-backend = "poetry.core.masonry.api"introductionCommon problemsOverview and rationaleWhy Python?What is parallel computing?
BenchmarkingA first example with DaskMemory profilingUsing many cores
Computing $\pi$Parallelizing a Python applicationUsing Numba to accelerate Python code
Threads and processesThreadingMultiprocessing
Delayed evaluationDask Delayed
Map and reduce
Exercise with FractalsThe Mandelbrot and Julia fractals
AsyncioIntroduction to AsyncioA first programWorking with asyncio outside Jupyter
Instructor Note
This section goes rather in depth on coroutines. This is meant to
grow the correct mental model about what’s going on with
asyncio.
Instructor Note
It may be best to let participants copy paste this snippet from the collaborative document. You may want to explain what a context manager is, but don’t overdo it. This is advanced code and may scare off novices.