Python Bytes
Python Bytes
Aug 26, 2021
#247 Do you dare to press "."?
Play • 46 min

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About the show

Special guest: Dan Taylor

Michael #1: Keep your computer awake during long processing

  • For now, use Michael’s fork when on macOS. Until this PR is merged.
  • Do you have work that will take a long time?
  • Keeping your OS working away is just a context block
    from wakepy import keepawake

    with keepawake(keep_screen_awake=False):
      ... # do stuff that takes long time

Brian #2: How to write a great Stack Overflow question

  • via Kevin Markham
  • The punchline (but it’s not enough)
    • Write a brief introduction
    • Provide a self-contained code example
    • Detail the expected results and why I expect those results
    • Add any important notes
    • Link to any relevant questions
    • Write a title that summarizes the question
  • Kevin starts with a question about pandas dataframes and filling in missing values.
    • The question is really application specific
  • The rewrite of the question is awesome
    • Simplifies the problem into a toy example, literally, and out of the domain specific context.
    • Includes example code that can copied, pasted, and run that sets up the problem
    • Uses short and simple variable names
    • Talks about expected results. And why he expects those results.
    • Includes a dataset in the sample code that covers cases the solution needs to provide
    • Includes non-obvious requirements or non-requirements
    • Links to related questions and why they don’t solve your problem.
  • I don’t think I’ve ever seen this, but I think it’d be cool to add test code that will pass when the problem is solved. But that might make the question unnecessarily long.

Dan #3: Github.dev - press ‘.’ to edit code in any GitHub repo

  • Fun bonus feature released at the same time as GitHub Codespaces
  • Runs VS Code entirely in your browser - supercharged “edit button”
    • Nothing to install
    • There’s no server to pay for, though functionality is limited
    • The file system is your browser’s local storage and GitHub repo
    • You can add files and commit changes directly to your repo
  • You can install extensions that support running in “VS Code Web”
  • Added basic web support to the Python Extension just yesterday
    • Syntax checking, auto-complete, go-to-definition
    • Uses type hints for packages (no python interpreter in the browser)
  • You can also install vscode-pyiodide to run Python code using Jupyter+Pyiodide
  • Overall means you can do more powerful code editing quickly in GitHub.com, I’m looking forward to seeing how this evolves

Michael #4: Log analyzer (minus google analytics)

  • GoAccess is an open source real-time web log analyzer and interactive viewer that runs in a terminal in *nix systems or through your browser.
  • Features
    • Fast, real-time, millisecond/second updates, written in C
    • Only ncurses as a dependency
    • Nearly all web log formats (Apache, Nginx, Amazon S3, Elastic Load Balancing, CloudFront, Caddy, etc)
    • Simply set the log format and run it against your log
    • Beautiful terminal and bootstrap dashboards (Tailor GoAccess to suit your own color taste/schemes)

Brian #5: KMK: Clackety Keyboards Powered by Python

  • recommended by Blaise
  • “firmware for computer keyboards written and configured in CircuitPython.”
  • Cool list of features
    • Fully configured through a single, easy to understand Python file.
    • Single-piece or two-piece split keyboards are supported
    • Chainable keys such as KC.LWIN(KC.L) to lock the screen on a Windows PC
    • Built-in unicode macros, including emojis
    • RGB underglow and LED backlights
    • One key can turn into many more based on how many times you tap it
  • One writeup I found of someone using it for a 10-key
  • Seems like limited hardware so far, and although the coding might not be too difficult, you still gotta swap out of the circuitboard.
  • I’m bringing this topic up because I’m hoping some keyboard kit people will put together something that just starts with the ability to run CircuitPython so I can just skip to the coding part.

Dan #6: SQLModel - use the same models for SQL and FastAPI

  • via Sebastián Ramírez (creator of SQLModel and FastAPI)
  • Write a schema once and use everywhere, reduces a lot of repetitive code
    • Traditionally have to manage several layers of code to pass your data from database queries, to the backend code, expose to your API and consume from the client
    • Code-first ORMs (SQLAlchemy, Django ORM) make it easy to write code that generates SQL
    • FastAPI makes it easy to expose objects to your API using Pydantic models
    • Before you would need to create both models and convert from ORM to Pydantic using .from_orm
  • SQLModel unifies those: a SQLModel is both a SQLAlchemy model and a Pydantic model
    • You can use SQLModel to interact with the database (via wrapping SQLAlchemy)
    • You can use that same model as a Pydantic model in FastAPI requests and responses
    • FastAPI also uses the Pydantic models to generate an openapi.json, meaning you could generate a client library in any language using OpenAPI Generator
  • Some other cool things:
    • Designed using type annotations so that editors like VS Code, PyCharm give great auto-complete out of the box, uses the proposed dataclass_transforms spec for dynamic typing
    • Supports async database sessions, alembic migrations because it’s based on SQLAlchemy (not yet documented)
    • Should be possible to integrate with postgis, ts_vectors

Extras

Brian

  • pip install ./local_directory is pretty interesting. Test & Code 163
    • The way pip installs from a local directory is about to change. Stéphane Bidoul joins the show to talk about it.

Dan

  • type4py - using ML to add type annotations to your codebase
    • retrofitting codebases with types is a pain — static type checkers can only infer so much
    • type4py research paper outlines a state of the art ML model for inferring types, adopting some techniques used in computer vision
    • Open sourced training code, data set, VS Code extension, and inferencing server
    • If you have a need to add type annotations to a large code base, worth giving this a try!
    • WARNING the VS Code extension sends code tokens to their API on type4py.com (they do have a privacy policy) — if this is a concern be sure to host the inferencing server yourself!

Joke: Continuous Deployment

Also:

“If a programmer gets an interview because of a recommendation from a friend, are they being passed by reference?” From @CarlaNotarobot, via @bluefiddleguy

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