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This or that? Similar methods & classes in Ruby && Rails

Andy Andrea • May 07, 2024 • Detroit, MI

In the session titled "This or that? Similar methods & classes in Ruby && Rails," speaker Andy Andrea discusses the intricacies of methods and classes in Ruby and Rails that may seem similar yet differ significantly in functionality and performance. This informative talk aims to clarify these distinctions to help developers make more informed decisions in their coding practices.

Key Points Discussed:
- Performance Considerations:
- Methods and classes in Ruby may have different performance implications, including error handling and direct database operations versus in-memory processing.
- Andy emphasizes the need to evaluate whether work should be done in memory or in the database based on the context of data operations.

  • Method Types:

    • Differences between bang and non-bang methods affect garbage collection and object mutation.
    • Noteworthy is the comparison between cover and include methods in the Range class. While both check if values fall within a range, cover performs better due to its less extensive evaluation process.

  • Benchmarking Examples:

    • The performance of range.cover is about twice that of range.include for large ranges, highlighting how certain methods perform better under different conditions.
    • For instance, performance metrics for small ranges may not be significant, but larger ranges such as A..ZZ demonstrate the profound impact on efficiency, with include drastically slowing down under stress.

  • Regular Expressions:

    • Various regular expression methods (match, scan, and match?) show different performance effects and return values, with match? introduced in Ruby 2.4 providing a simple boolean without impacting global variables, unlike other methods.
    • Understanding side effects from global variable settings in regex methods is essential for maintaining code stability.

  • Error Handling Nuances:

    • Andy distinguishes between no method error and not implemented error, noting their different implications and how they can guide code structuring and error handling.

  • Monkey Patching and Performance:

    • The concept of monkey patching to enhance classes without altering their original structures is discussed alongside alternative methods like defining methods with class variables, showcasing performance impacts.

  • Method Calls and Clean Code:

    • Andy concludes with the idea that clarity and simplicity in method calls lead not only to better performance but also to maintainable code. Complex syntax can obscure intention, making it pivotal to prioritize readability in coding practices.

Overall, Andy Andrea's session at RailsConf 2024 provides valuable insights into Ruby's methods and classes, emphasizing the importance of understanding subtle differences to optimize performance and maintainability in Rails applications.

This or that? Similar methods & classes in Ruby && Rails
Andy Andrea • May 07, 2024 • Detroit, MI

Working with Ruby and Rails affords access to a wealth of convenience, power and productivity. It also gives us a bunch of similar but distinct ways for checking objects' equality, modeling datetimes, checking strings against regular expressions and accomplishing other common tasks. Sometimes, this leads to confusion; other times, we simply pick one option that works and might miss out something that handles a particular use case better.

In this talk, we'll take a look at groups of patterns, classes and methods often seen in Rails code that might seem similar or equivalent at first glance. We’ll see how they differ and look at any pros, cons or edge cases worth considering for each group so that we can make more informed decisions when writing our code.

RailsConf 2024

00:00:10.480 Hello everyone! My name is Andy Andrea, and I have considerable experience working as a Ruby developer.
00:03:58.920 In Ruby and Rails development, we often face challenges where methods or classes may differ slightly in terms of functionality.
00:04:04.040 For instance, different methods may raise various errors or warnings, leading to side effects that can impact performance. Some functions operate fully in the database, while others work entirely in memory. It's essential to understand their performance implications when deciding on the approach.
00:04:30.759 This often comes down to performance considerations. Sometimes, offloading work to the database is beneficial, but if you've already loaded data, it might be more efficient to operate in memory.
00:04:41.400 When looking at methods, the difference between bang and non-bang methods, or place allocation versus object allocation, can be significant. These differences can affect garbage collection or result in unintended modifications.
00:05:06.080 The aspects covered so far have focused on performance, but there are many additional factors that can differentiate methods. I also want to touch upon general usage semantics, which often guide how we choose to implement these methods.
00:05:17.560 Of course, linter rules play a role, but I won't delve into those due to their complexity and variability.
00:05:32.400 This talk will specifically focus on methods and classes that might seem similar at first glance, and we'll explore their distinctions.
00:05:50.960 We'll begin with a relatively simple example compared to the later ones. This involves the `cover` and `include` methods that we can apply to the Range class.
00:06:05.520 These two methods serve similar functions, but they have differences worth noting for our discussion. `include` is older, and while it might not have a significant effect on our day-to-day decisions, it’s important to recognize some Ruby applications are still using older versions.
00:06:31.319 In this talk, we'll benchmark these methods using Ruby 3.3.0. Different environments may yield different results, so keep that in mind.
00:06:51.000 Comparing the performance of `range.cover` versus `range.include`, using the range of letters from A through Z, we notice that `cover` operates about twice as fast as `include`. This performance metric is less critical with small ranges but becomes significant with larger ranges.
00:07:36.319 For example, a range like A..ZZ would drastically affect performance, with `include` dropping to just 27.7 iterations per second compared to `cover`.
00:08:08.920 On the general usage side, both methods return true for values within the range but false outside. This makes them appear quite similar.
00:08:36.360 The difference becomes notable when we call these methods on non-numeric ranges. When we test strings, we can see that `cover` may indicate that certain values are technically covered by the range even if they aren't within it.
00:09:05.200 Understanding when `include` raises errors for endless or beginningless ranges is essential as it could lead to unexpected behaviors. In contrast, `cover` will return a boolean without raising exceptions in these cases.
00:09:24.640 Another differentiation is in how `include` fully evaluates the range while `cover` only checks the endpoints, which contributes to its performance advantage.
00:09:47.640 This helps to illustrate how different methods can serve similar purposes while exhibiting unique behaviors that can affect performance and usability.
00:10:08.880 Next, we'll move to regular expression matching, which provides several options for pattern matching in Ruby.
00:10:30.000 Initially, I found the need for a method that returns a simple boolean rather than a numeric value, and I was delighted when Ruby 2.4 introduced the `match?` method.
00:10:54.320 As we analyze the performance of regular expression methods, we identify the varying return values across methods like `match`, `scan`, and others.
00:11:10.640 It's important to understand how these methods can affect our code, especially when we consider side effects from global variable settings.
00:11:48.320 For instance, every regular expression call (except for `match?`) sets a range of global variables that can lead to issues, particularly if developers are unaware of them.
00:12:07.560 Designing code that’s readable involves recognizing the implications of using these global variables and finding ways to mitigate their effects.
00:12:27.000 Now let's touch on the nuances of the `method` and `not implemented error` in Ruby.
00:12:42.120 A `no method error` typically arises when invoking a method on a nil object, whereas a `not implemented error` occurs with unsupported system calls. Their different behaviors are crucial to understanding error handling in Ruby.
00:13:05.360 An interesting aspect of `not implemented error` is its use among developers to mock interfaces without actual implementations, indicating where future code should go.
00:13:36.360 When rescuing these errors, note that a typical rescue will catch all standard errors but will not catch every instance of `not implemented error`.
00:14:03.160 Moving on, let's talk about monkey patching with defined method classes.
00:14:24.960 This technique enables developers to inject additional methods into classes or modules, enhancing functionality without needing to alter their original structure.
00:14:42.960 While you might be used to monkey patching as the conventional approach, there are also alternatives like defining methods through class variables.
00:15:01.440 The subsequent part of our dialog will explore performance differences with these methods; surprisingly, monkey patching proved to be one of the seemly fastest solutions.
00:15:21.040 With options available to delegate methods, we can also delve into Active Support’s delegate method.
00:15:42.200 Active Support's functionality can be beneficial, but it demands having the Active Support library, which might not always be accessible in a standard Ruby script.
00:16:09.160 The distinctions between global and targeted delegation highlight the differences in these approaches. Depending on how they are structured and used, performance can vary.
00:16:30.000 For example, when using `define_method`, you are given more control and flexibility, enabling specific outcomes while still leveraging Ruby's dynamic nature.
00:17:00.000 This brings us to the comparison of delegation methods; there are various options that serve similar purposes but can have distinctly different performance impacts.
00:17:27.960 Another area of exploration includes defining methods within the context of Ruby, indicating the need to thoroughly evaluate the efficiency of the chosen approach.
00:17:51.480 Finally, let’s discuss how method calls using different expressions perform under various conditions.
00:18:18.040 Watching the performance metrics in action can paint a clearer picture of how seemingly subtle differences can create significant performance variations.
00:18:43.360 The exploration of method calls leads us to consider other inventive ways of invoking methods, even including the 'smearing' of method calls—an artistically humorous notion.
00:19:06.720 As we wrap up our exploration of Ruby methods and classes, it’s essential to understand the importance of clarity and maintainability while writing code.
00:19:31.920 Invoking methods through unusual syntax or employing complicated mechanisms may lead to confusion, and the code's intention can become obscured.
00:19:56.320 This serves as a reminder—when coding, simple and clear function calls often lead to better performance and ultimately, increased maintainability.
00:20:18.480 I hope this analysis has provided insights into the ways Ruby and Rails allow us to navigate various methods and classes. Thank you all for being a part of this session!
00:20:43.920 If you have questions or wish to dive deeper, I will be hanging out here. Thank you once more!
00:20:57.400 As I wrap things up, if you're interested in similar topics, feel free to reach out or check my resources, including links to various Ruby materials.
Andy Andrea
@andycandrea
Explore all talks recorded at RailsConf 2024
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