Summary

If you have ever found yourself frustrated by a complicated regular expression or wondered how you can build your own dialect of Python then you need a parser. Dave Beazley and Erik Rose talk about what parsers are, how some of them work, and what you can do with them in this episode.

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Preface

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Your host as usual is Tobias Macey and today I’m interviewing Erik Rose and Dave Beazley about what parsing is, why you might want to use it, and how their respective libraries Parsimonious and PLY make it easy.

Interview

Introductions

How did you get introduced to Python?

Can you each start by talking a bit about your respective libraries and what problem you were trying to solve when they were first created?

In what ways does a full-fledged parser differ from what a regular expression engine is capable of?

What are some of the different high-level approaches to building a parser and when might you want to choose one over the others?

I’m sure that when most people hear the term parsing they associate it with reading in a data interchange format such as JSON or CSV. What are some of the more interesting or broadly applicable uses of parsing that might not be as obvious?

One term that kept coming up while I was doing research for this interview was “Grammars”. How would you explain that concept for someone who is unfamiliar with it?

Once an input has been parsed, what does the resulting data look like and how would a developer interact with it to do something useful?

For someone who wants to build their own domain specific language (DSL) what are some of the considerations that they should be aware of to create the grammar?

What are some of the most interesting or innovative uses of parsers that you have seen?

Keep In Touch

Dave Beazley @dabeaz on Twitter Website

Erik Rose @ErikRose on Twitter Website



Picks

Links

The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA