Search
Parsing
Parsing Expressions in Ruby
Edit
#parsing
#regex
#ruby
Summarized using AI

Parsing Expressions in Ruby

Michael Jackson • February 19, 2015 • Earth

In the talk "Parsing Expressions in Ruby," Michael Jackson discusses the advantages of using parsing expressions as a powerful alternative to regular expressions (regex) for text parsing in Ruby. He highlights that while regex is often used for various text manipulation tasks, it can lead to performance issues and maintainability troubles due to its complexity and ambiguity when dealing with diverse text types.

Key points in the talk include:

- Challenges of Using Regex: Michael relates his experience with a particularly complex regex for URL validation that caused significant performance degradation in an application, underlining the dangers of relying on copy-paste regex solutions.

- Diversity of Text: He explains the varied sources of input text in programming and how standardized formats like XML and JSON have reliable parsers, unlike many other informal text inputs that lead developers to rely on regex.

- Introduction to Parsing Expressions: Parsing expressions, introduced at MIT in 2004, offer a structured, declarative alternative with recursive capabilities that allow for more complex and maintainable parsing solutions than regex.

- Citrus Library: Michael discusses the Citrus library, which he developed to facilitate efficient parsing expressions in Ruby. He explains how Citrus enables familiar syntax for defining grammars, thus allowing more readable and maintainable code compared to regex.

- Citrus Features: Features such as defining character classes, handling repetitions, and implementing logical order make Citrus user-friendly, allowing for more intuitive parsing operations. Examples like parsing nested parentheses or arithmetic expressions showcase the library's capabilities.

In conclusion, Michael emphasizes the importance of choosing the right tool for text parsing challenges. By utilizing parsing expressions over traditional regex, developers can achieve greater agility and flexibility, ultimately enhancing their programming practices and application development. He encourages the audience to explore these techniques in their projects.

Parsing Expressions in Ruby
Michael Jackson • February 19, 2015 • Earth

By, Michael Jackson
As a programmer one of your most useful tools is the regular expression. Like a trusty old hammer, Regexp is always ready and willing to parse your random bits of text with brutal precision and accuracy.

But there are some tasks for which regular expressions are not the best tool for the job. Parsing expressions are a relative newcomer in the field of text analysis. Libraries like Treetop and Citrus make it easy to use parsing expressions with Ruby. In this talk, we'll discuss potential applications for parsing expressions and how to use and test them in your Ruby code.

Help us caption & translate this video!

http://amara.org/v/GJRX/

MountainWest RubyConf 2011

00:00:12.160 Hello, Mountains! This has really been an excellent conference so far. We have had some amazing speakers.
00:00:17.279 Some very enlightening topics have been presented. I love how MountainWest always seems to cover a wide range of subjects.
00:00:22.400 We get to explore systems programming, plant programming, and even people's pet projects. This afternoon, we're going to hear about some exciting topics related to different kinds of systems.
00:00:29.199 It's truly awesome being here. I just want to start off by expressing my gratitude for the conference.
00:00:35.440 Today, I'm going to talk about parsing expressions, specifically using them in the Ruby programming language. Can I quickly see how many people are familiar with the concept of parsing expressions?
00:00:41.600 How many of you have heard about or used libraries like Treetop? Okay, excellent! We are speaking to a pretty good audience here.
00:00:58.399 I just want to talk a little bit about myself. I've been using Ruby for about three years professionally. I work for Paf in San Francisco, where we are a small startup working on an iPhone app and social network. I handle all of our website and APIs.
00:01:12.400 So I understand something about the Ruby community, and I also know that many of you have a dirty little secret lurking in the bowels of your apps.
00:01:18.320 How many of you have one of these lurking deep in your applications? Can anyone guess what this expression does? It can be quite confusing.
00:01:35.440 I once worked on an app that had a regex similar to this. It started with 'http' followed by an optional 's' or 'x'. Apparently, this regex supports FTP as well.
00:01:59.600 When I saw this, I was unsure whether the person who created it knew what they were doing. As we developed our app, I hit a bug regarding URL validation, which mostly resulted in a 500 error when users attempted to save accounts with Blogspot addresses.
00:02:19.760 Any guesses on what the performance of this regex was against such URLs? Twelve seconds? Ninety-seven seconds? Yeah, it was terrible.
00:02:39.840 Our Unicorn processes were being slaughtered because after a minute of running on this expression, the master process would terminate due to the excessive runtime.
00:02:54.560 The regex beast was hiding deep in my app with its maddening complexity, leading to inefficiencies and confusion.
00:03:05.040 Be cautious if you’re using a regex like this. Commonly, the tendency is to find a regex for URL validation or email validation by copying and pasting from the internet. You may think you’re done, but you might not realize the potential pitfalls.
00:03:22.000 Let's step back and discuss the problem we're trying to solve with regular expressions. The core of the problem is the diverse text we manipulate in coding.
00:03:36.560 Text comes from various sources, like user input in forms or API responses in formats like XML or JSON. For standardized formats like XML and JSON, we have good parsers, but for everything else, we often resort to regex.
00:03:54.639 Regrettably, this has made regex a common hammer for text parsing, leading us to apply it even when a different tool would be more appropriate.
00:04:07.120 Regular expressions were not designed for all tasks, and we need to consider what alternatives exist. Although regex is useful for certain types of text, other scenarios may require a more efficient solution.
00:04:30.960 For example, many standards are complex and require structured parsing rather than one-off regex solutions. We want tools that allow us to define structured grammar that inherently knows how to parse according to specification.
00:04:57.760 When building our parsers, we want speed, simplicity, modifiability, and flexibility. If the parser’s complexity makes it difficult to maintain, then in practical terms, it becomes useless.
00:05:20.800 Most of us use regex because we are better accustomed to its mechanics than to structured parsing patterns. However, we benefit greatly if we can create flexible parsing systems that allow for better readability and maintainability.
00:05:35.440 Parsing expressions were first discussed at MIT by Brian Ford in 2004, offering a declarative alternative to regex.
00:05:56.800 They provide a recursive mechanism that allows for much more complex parsing in comparison to traditional regex.
00:06:18.640 With parsing expressions, it is easier to read and maintain code compared to regex. This is particularly important, as regex becomes complex with increased size.
00:06:40.240 Additionally, parsing expressions eliminate ambiguity due to their structured decision-making from token streams, while regex tends to backtrack, complicating the parsing process.
00:06:57.100 Most experimental performance shows parsing expressions can outperform regex for specific tasks because they are built to handle structured data better.
00:07:17.400 I was very interested in exploring parsing expressions, so I initially tried the Treetop library. However, I found it to be unmaintained and inefficient for my purposes.
00:07:40.800 This led me to create Citrus, a library designed for efficient parsing expressions in Ruby. You can install it using 'gem install citrus'.
00:08:00.000 Citrus is designed to be user-friendly and allows you to define grammars using familiar syntax that looks like Ruby.
00:08:33.280 The grammar rule names allow you to define relationships easily, and thus references rules within your grammar schema.
00:09:01.440 I prefer the intuitive layout of Citrus and its support for various expressions, enabling complex tasks without cumbersome regex.
00:09:28.480 Let’s quickly review how Citrus works syntactically. You can represent strings, define exact matches, or even use regex as a fallback when necessary.
00:09:52.640 Citrus makes it possible to create character classes or specify repetition with clear syntax. This supports a default of either zero or more matches based on your use case.
00:10:15.440 You can also implement logical ordering in your parsing expressions, ensuring one match follows another in a clear sequence.
00:10:46.000 The trees created during parsing enable efficiently tracking of matches under different paths logically.
00:11:05.760 You can achieve semantic value assignment through the block mechanism where you can convert matched string values into usable integers.
00:11:22.960 In this way, your parsing becomes both straightforward and extensible, allowing for deeper inspection into your match trees.
00:11:47.840 I’d like to demonstrate an example that would otherwise be impossible with regex: parsing nested parentheses structures.
00:12:20.400 I can define a simple grammar to match open parentheses followed by characters and closed parentheses while allowing for recursion in the parsing process.
00:12:55.280 To illustrate how the parsing mechanics work, let's look at matching simple arithmetic operations, using Citrus to parse and handle mathematical expressions effectively.
00:13:11.840 The process of parsing expressions with various objects in Ruby and creating logical operations is tremendous fun and can be done intuitively.
00:13:42.960 You can also develop more complex functionalities within the same framework, using Citrus to parse structured content from external APIs or user-generated data.
00:14:22.320 Considering how seamless it is to integrate such capabilities into your existing codebase allows developers to create dynamic applications efficiently.
00:15:05.120 In conclusion, using parsing expressions equates to increased agility and capability essential for modern application development.
00:15:32.040 Using the right tool for the job is crucial; parsing expressions in Ruby opens doors to better manipulation of data formats while avoiding the common pitfalls of traditional regex.
00:16:03.920 Thank you very much for your attention today! I'm excited to see how you implement parser techniques in your projects. If anyone has any questions, now is the time!
MJ
Michael Jackson
1 talk
Explore all talks recorded at MountainWest RubyConf 2011
+13