#240 This is GitHub, your pilot speaking...
Watch the live stream: Watch on YouTube About the show Sponsored by us: Check out the courses over at Talk Python And Brian’s book too! Special guest: Chris Moffit Brain #1: Subclassing in Python Redux Hynek Schlawack Prefer composition over inheritance, But if you must subclass, there are 3 types subclassing for code sharing bad. don’t do it. read the article and included linked articles if you aren’t convinced Interfaces / Abstract Data Types Can be useful, but Python has tools that make this work without subclassing Specialization Exception hierarchies There’s also an interesting discussion of structuring data classes with common elements This is the only type of subclassing that Hynek deems worthy This is a well written, useful, and long-ish article that I cannot summarize and do it justice. My summary: If you even consider sublcassing other than for exceptions, read this article first. Michael #2: Extra, Extra, Extra*7, Hear all about it! New course! Python-powered chat apps with Twilio and SendGrid Pyodide is now an independent project Wow textual from Nick Mouh #NoFLOC for real! Need to protect your Python source? SourceDefender **(commercial product, but neat) I was a guest on A Day in a Life of a WFH Pythonista. Full episode starts here, and the studio/office tour here. Python 3.9.6 is out Python Web Conf 2021 videos are out, including mine on memory. pip install pythonbytes via pythonbytes package. Chris #3: klib Perform automated cleaning and analyzing of data in a pandas DataFrame Missing value plot and correlation data plots are similar to other tools but the visualizations are nicely done and useful. The data cleaning functions are really nice. In some testing, the automated data type conversion can save a meaningful amount of data. For large data sets, you can drop columns with lots of null values or highly correlated values. The clean_column_names function also performs several cleanups on column names such as removing spaces, standardizing CamelCase, etc. You have control to use as much or as little of the automated process as possible. Brian #4: Don’t forget about functools “functools — Higher-order functions and operations on callable objects” in English: cool decorators and other functions that act on functions A recent article by Martin Heinz reminded me to review functools We’ve talked about singledispatch recently, and I’m sure we’ve talked about lru_cache before. These are in functools. functools is an interesting library in that you kind of use it more and more as you increase your Python experience. As a new Python dev, I would have been rather lost looking at this, but as you work through different projects, come back to this and have a look, it’ll have stuff you probably could have used, and will use in the future. What’s in there? Here’s a few: @singledispatch & @singledispatchmethod - function/method overloading @wraps - A must for creating your own decorators that makes the decorated function act just like the original function (attributes, docstring, and all, with just the added behavior you are adding. @lru_cache - memoization made easy LRU = least recently used. It’s what it throws away when it’s full @cache - like @lru_cache but with no max size. New in 3.9 @cached_property - only run the read code once. New in 3.8 del(obj.property) to clear it. Yes this is weird, but also cool. @total_ordering - Define __eq__() and one other ordering function and get the other ordering functions for “free”. not free. cost is slower execution and confusing stack traces if things go wrong. but still, when prototyping something, or when comparisons are very rare, this is cool partial / partialmethod - create a new function with some of the arguments of the old function already filled in. super cool for callbacks or defining convenience functions Michael #5: GitHub Copilot Get suggestions for whole lines or entire functions right inside your editor. Available today as a Visual Studio Code extension. The technical preview does especially well for Python, JavaScript, TypeScript, Ruby, and Go, but it understands dozens of languages and can help you find your way around almost anything. You can cycle through alternative suggestions Powered by Codex, the new AI system created by OpenAI Based on gpt3. Chris #6: Kats New tool from facebook for Time Series analysis Can use Facebook’s Prophet as well as other algorithms such as Sarima and Holt-Winters for prediction. Here’s my old post on prophet. Some controversy about how well prophet performs in real life. Very detailed article here. Provides utilities for analyzing time series including outlier and seasonality detection Offers advanced ensemble methods and access to deep learning algorithms Extras Chris Unyt - library for working with units of measure. Pint is another similar one with a different API. Jokes Italian Aysnc (from Dean Langsam) Q: Why aren't cryptocurrency engineers allowed to vote? A: Because they're miners!