Summary
Writing code that is easy to read and understand will have a lasting impact on you and your teammates over the life of a project. Sometimes it can be difficult to identify opportunities for simplifying a block of code, especially if you are early in your journey as a developer. If you work with senior engineers they can help by pointing out ways to refactor your code to be more readable, but they aren’t always available. Brendan Maginnis and Nick Thapen created Sourcery to act as a full time pair programmer sitting in your editor of choice, offering suggestions and automatically refactoring your Python code. In this episode they share their journey of building a tool to automatically find opportunities for refactoring in your code, including how it works under the hood, the types of refactoring that it supports currently, and how you can start using it in your own work today. It always pays to keep your tool box organized and your tools sharp and Sourcery is definitely worth adding to your repertoire.
Announcements
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- Your host as usual is Tobias Macey and today I’m interviewing Nick Thapen and Brendan Maginnis about Sourcery, an advanced refactoring engine that cleans up your code as you work
Interview
- Introductions
- How did you get introduced to Python?
- Can you start by giving an overview of what Sourcery is?
- What was your motivation for building a system for performing automated refactoring?
- What are your goals and priorities with Sourcery?
- There are a number of services that aim to automate portions of the developer workflow, such as code completions, quality checks, refactoring, etc. What was lacking in the existing tooling that made Sourcery a necessary project?
- How does Sourcery compare with some of the other services that offer AI or ML powered assistance? (e.g. Kite, Tab9, Codata(?))
- What was your reasoning for focusing solely on Python for your refactoring, rather than trying to support multiple language targets?
- Can you give some examples of the types of refactoring that you are able to automate?
- Can you describe how Sourcery is implemented?
- What are some of the ways that the system has changed or evolved in design and/or scope?
- What are some examples of the types of refactorings that Sourcery is ill-suited for and which still require manual intervention?
- What is involved in adding support for a new editor?
- How much variation is there in terms of implementation or available functionality across editors?
- How has the introduction of the Language Server Protocol influenced your approach to editor integration?
- What are some of the most interesting, unexpected, or challenging lessons that you have learned while working on Sourcery?
- When is Sourcery the wrong choice?
- What do you have planned for the future of Sourcery
Keep In Touch
- Nick
- Brendan
- @brendan_m6s on Twitter
- brendanator on GitHub
Picks
- Tobias
- Nick
- The Magicians TV Series
- Brendan
- David Copperfield by Charles Dickens
Closing Announcements
- Thank you for listening! Don’t forget to check out our other show, the Data Engineering Podcast for the latest on modern data management.
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Links
- Sourcery
- IBM RPG
- Delphi
- Java
- Scala
- PyTorch
- NLP == Natural Language Processing
- Tensorflow
- Language Server Protocol
- Kent Beck
- Martin Fowler
- MyPy
- Clojure
- Lisp
- Abstract Syntax Tree
- ASTroid
- Rope
- Sans I/O
- pre-commit framework
The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA
from Planet Python
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