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Brian #1: pyscript

• Python in the browser, from Anaconda. repo here
• Announced at PyConUS
• “During a keynote speech at PyCon US 2022, Anaconda’s CEO Peter Wang unveiled quite a surprising project — PyScript. It is a JavaScript framework that allows users to create Python applications in the browser using a mix of Python and standard HTML. The project’s ultimate goal is to allow a much wider audience (for example, front-end developers) to benefit from the power of Python and its various libraries (statistical, ML/DL, etc.).” from a nice article on it, PyScript — unleash the power of Python in your browser
• PyScript is built on Pyodide, which is a port of CPython based on WebAssembly.
• Demos are cool.
• Note included in README: “This is an extremely experimental project, so expect things to break!”

Michael #2: Memray from Bloomberg

• Memray is a memory profiler for Python.
• It can track memory allocations in
  • Python code
  • native extension modules
  • the Python interpreter itself
• Works both via CLI and focused app calls
• Memray can help with the following problems:
  • Analyze allocations in applications to help discover the cause of high memory usage.
  • Find memory leaks.
  • Find hotspots in code which cause a lot of allocations.
• Notable features:
  • 🕵️‍♀️ Traces every function call so it can accurately represent the call stack, unlike sampling profilers.
  • ℭ Also handles native calls in C/C++ libraries so the entire call stack is present in the results.
  • 🏎 Blazing fast! Profiling causes minimal slowdown in the application. Tracking native code is somewhat slower, but this can be enabled or disabled on demand.
  • 📈 It can generate various reports about the collected memory usage data, like flame graphs.
  • 🧵 Works with Python threads.
  • 👽🧵 Works with native-threads (e.g. C++ threads in native extensions)
• Has a live view in the terminal.
• Linux only

Brian #3: pytest-parallel

• I’ve often sped up tests that can be run in parallel by using -n from pytest-xdist.
• I was recommending this to someone on Twitter, and Bruno Oliviera suggested a couple of alternatives. One was pytest-parallel, so I gave it a try.
• pytest-xdist runs using multiprocessing
• pytest-parallel uses both multiprocessing and multithreading.
• This is especially useful for test suites containing threadsafe tests. That is, mostly, pure software tests.
• Lots of unit tests are like this. System tests are often not.
• Use --workers flag for multiple processors, --workers auto works great.
• Use --tests-per-worker for multi-threading. --tesst-per-worker auto let’s it pick.
• Very cool alternative to xdist.
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Michael #4: Pooch: A friend for data files

• via via Matthew Fieckert
• Just want to download a file without messing with requests and urllib?
• Who is it for? Scientists/researchers/developers looking to simply download a file.
• Pooch makes it easy to download a file (one function call). On top of that, it also comes with some bonus features:
  • Download and cache your data files locally (so it’s only downloaded once).
  • Make sure everyone running the code has the same version of the data files by verifying cryptographic hashes.
  • Multiple download protocols HTTP/FTP/SFTP and basic authentication.
  • Download from Digital Object Identifiers (DOIs) issued by repositories like figshare and Zenodo.
  • Built-in utilities to unzip/decompress files upon download
• file_path = pooch.retrieve(url)

Extras

Michael:

• New course! Up and Running with Git - A Pragmatic, UI-based Introduction.

Joke:

• Don’t embarrass me in front of the wizards
• Michael’s crashing github is embarrassing him in front of the wizards!