MonkeyType with Carl Meyer and Matt Page

The podcast about Python and the people who make it great

MonkeyType with Carl Meyer and Matt Page

January 27, 2018 00:48:25 32.95 MB Downloads: 0

Summary

One of the draws of Python is how dynamic and flexible the language can be. Sometimes, that flexibility can be problematic if the format of variables at various parts of your program is unclear or the descriptions are inaccurate. The growing middle ground is to use type annotations as a way of providing some verification of the format of data as it flows through your application and enforcing gradual typing. To make it simpler to get started with type hinting, Carl Meyer and Matt Page, along with other engineers at Instagram, created MonkeyType to analyze your code as it runs and generate the type annotations. In this episode they explain how that process works, how it has helped them reduce bugs in their code, and how you can start using it today.

Preface

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Your host as usual is Tobias Macey and today I’m interviewing Carl Meyer and Matt Page about MonkeyType, a system to collect type information at runtime for your Python 3 code

Interview

Introductions
How did you get introduced to Python?
What is MonkeyType and how did the project get started?
How much overhead does the MonkeyType tracing add to the running system, and what techniques have you used to minimize the impact on production systems?
Given that the type information is collected from call traces at runtime, and some functions may accept multiple different types for the same arguments (e.g. add), do you have any logic that will allow for combining that information into a higher-order type that gets set as the annotation?
How does MonkeyType function internally and how has the implementation evolved over the time that you have been working on it?
Once the type annotations are present in your code base, what other tooling are you using to take advantage of that information?
It seems as though using MonkeyType to trace your running production systems could be a way to inadvertantly identify dead sections of code that aren’t being executed. Have you investigated ways to use the collected type information perform that analysis?
What have been some of the most challenging aspects of building, using, and maintaining MonkeyType?
What have been some of the most interesting or noteworthy things that you have learned in the process of working on and with MonkeyType?
What have you found to be the most useful and most problematic aspects of the typing capabilities provided in recent versions of Python?
For someone who wants to start using MonkeyType today, what is involved in getting it set up and using it in a new or existing codebase?
What features or improvements do you have planned for future releases of MonkeyType?

Keep In Touch

Carl
- Email
- @carljm on Twitter
Matt
- Email
- @void_star on Twitter