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Mastering Git Rerere: Solving Repetitive Merge Conflicts with Ease

Mattia Magi

Published Jan 5, 2024

Updated Jan 8, 2024

4 min read

Mastering Git Rerere: Solving Repetitive Merge Conflicts with Ease

Introduction:

Git, the popular version control system, has revolutionized how developers collaborate on projects. However, one common pain point in Git is repetitive merge conflicts. Fortunately, Git provides a powerful and not-so-well-known solution called git rerere (reuse recorded resolution) that can save you time and effort when resolving conflicts. In this blog post, we will explore how to configure and use git rerere, and demonstrate its effectiveness in solving merge conflicts.

Understanding Git Rerere:

Git rerere is a feature that allows Git to remember how you resolved a particular merge conflict in a particular file and automatically apply the same resolution in the future. It works by recording the conflict resolution in a hidden directory called .git/rr-cache. This way, when Git encounters the same conflict in the same file in the future, it can reuse the recorded resolution, saving you from manually resolving the conflict again.

Configuring Git Rerere:

Before using git rerere, you need to enable it in your Git configuration; only once git rerere has been enabled, Git will start recording and remembering resolved conflicts.Open your terminal and run the following command:

git config --global rerere.enabled true

This command enables git rerere globally, making it available for all your repositories. You can also enable it per-repository by omitting the --global flag.

How to use it:

Let's start with a really easy example, then describe a couple of use cases.

We have merged a branch (branch-one) into our main, and we are working on two different features in two different branches (branch-two and branch-three). We need to rebase our branches with main, so we start with

git checkout branch-two
git rebase main

It turns out that there are some conflicts on App.tsx file:

We solve all the conflicts and finish with the rebase and push. As you can see, there are an extra line in the rebase output message that says:

This means that thanks to rerere option enabled, we have saved in our project's .git/rr-cache this resolution for this particular conflict.

Now let's switch branches into branch-three cause we want to rebase on main also this one:

git checkout branch-three
git rebase main

It seems that we have the same conflicts here too, but this time, on the rebase output message, we can read:

The conflict has been resolved automatically; if we check our IDE, we can see the change (and check if it works for us) ready to be committed and pushed with the same resolution we manually used in the past rebase.

The example above focuses on a rebase, but of course, git rerere also works for conflicts that came out from a merge command.

Here are a couple of real-life scenarios where git rerere can save the day:

Frequent Integration of Feature Branches: Imagine you're working on a feature branch that frequently needs to be merged into the main development branch. Each time you merge, you encounter the same merge conflicts. With git rerere, you only need to resolve these conflicts once. After that, Git remembers the resolutions and automatically applies them in future merges, saving you from resolving the same conflicts repeatedly.

Reapplying Patches or Fixes: Let's say you have a situation where you need to apply the same set of changes or fixes to multiple branches. When you encounter conflicts during this process, git rerere can remember how you resolved them the first time. Then, when you apply the changes to other branches, Git can automatically reuse the recorded resolutions, sparing you from manually resolving the same conflicts repeatedly.

Benefits of Git Rerere:

Git rerere offers several benefits that make it a valuable tool for developers, regardless of whether you prefer git merge or git rebase:

Time-saving: By reusing recorded resolutions, git rerere eliminates the need to manually resolve repetitive merge conflicts, saving you valuable time and effort.
Consistency: Git rerere ensures consistent conflict resolutions across multiple merges or rebases, reducing the chances of introducing errors or inconsistencies.
Improved productivity: With git rerere, you can focus on more critical tasks instead of getting stuck in repetitive conflict resolutions.

Conclusion:

Git rerere is a powerful feature that simplifies resolving repetitive merge conflicts. By enabling git rerere and recording conflict resolutions, you can save time, improve productivity, and ensure consistent conflict resolutions across your projects. Incorporate git rerere into your Git workflow, and say goodbye to the frustration of repetitive merge conflicts.

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About the author(s)

Mattia Magi

Ensuring Accurate Workflow Status in GitHub for Enhanced Visibility

Introduction In the world of software development, GitHub workflows are crucial for automating CI/CD processes. However, a key challenge emerges when these workflows report a 'success' despite underlying issues, like failed tests. This is especially common in scenarios involving tests (e.g., Cypress) and notifications (e.g., Slack) within the same workflow. This blog post aims to highlight the importance of accurate GitHub workflow statuses for better visibility and team response, and how to ensure your workflows reflect the true outcome of their runs. The Problem with Misleading Workflow Statuses Consider a scenario in a GitHub workflow where end-to-end tests are run using Cypress. ` If these tests fail, but the workflow proceeds to a subsequent step, like sending a notification via Slack, which completes successfully, the entire workflow might still show a green checkmark. This misleading success status suggests everything is functioning as intended, when in fact, there could be significant underlying issues. The core issue is the determination of workflow success. Even if critical steps like testing fail, later steps without errors can override this, resulting in a false sense of security. This not only delays bug detection but can also lead to faulty code advancing in the CI/CD pipeline. It's crucial for the overall workflow status to accurately reflect failures in critical steps to ensure prompt and appropriate responses to issues. Crafting a Solution and Best Practices Ensuring Accurate Status Reporting To address the issue of misleading workflow statuses, it’s essential to configure your GitHub Actions properly. The goal is to ensure that the workflow accurately reflects the success or failure of critical tasks, such as running tests, regardless of the success of subsequent steps. Adjusting the Workflow Conditional Notifications: First, set up notifications to execute conditionally based on the outcome of critical steps. This ensures you're alerted of the workflow status without altering the overall result. For example, sending a Slack message if a Cypress test fails: ` Explicit Failure Handling: After configuring conditional notifications, explicitly handle failure scenarios. If a critical step like a Cypress test fails, force the workflow to exit with a failure status. This step is crucial to ensure that the overall workflow reflects the true status: ` Best Practices: Clear Step Separation: Clearly separate and label each step in your workflow for easier readability and troubleshooting. Regular Reviews: Periodically review your workflows to ensure they are aligned with the latest project requirements and best practices. Document Workflow Logic: Maintain documentation for your workflows, especially for complex ones, to aid in understanding and future modifications. By first setting up conditional notifications and then enforcing explicit failure handling, you maintain both alertness to issues and accuracy in workflow status. This approach ensures that failures in critical steps like tests are not overshadowed by subsequent successful steps, keeping the reported status of your workflow true to its actual state. Conclusion Accurate GitHub workflow statuses are vital for a transparent and efficient CI/CD process. By implementing conditional notifications and explicit failure handling, we ensure that our workflows truthfully represent the success or failure of critical tasks. This not only fosters better issue awareness and response but also upholds the integrity of our development practices. Embrace these steps as part of your commitment to maintaining clear and reliable automation processes in your projects. Happy coding!...

Mar 22, 2024

3 mins

GitHubGit

Git Strategies For Teams, Another Take

Recently we published an article about a pragmatic approach to using Git in teams. It outlines a strategy which is easy to implement while safeguarding against common issues when using git. It is, however, in my opinion, a compromise. Allowing some issues with edge cases as a trade-off for ease of use. Status Quo Before jumping into another strategy, let us establish the pros and cons of what we’re up against. This will give us a reference for determining whether we did better, or not. Pro: Squash Merging One of the stronger arguments is the squash merge. It offers freedom to all developers within the team to develop as they see fit. One might prefer to develop all at the same time, and push a big commit in the end. Others might like to play it safe and simply commit every 5 minutes, allowing them to roll back or backup changes. The only rule is that at the end of the work, all changes get squashed into a single commit that has to adhere to the team's standards. Con: You Get A Single Commit Each piece of work gets a single commit. To circumvent this, one could create multiple PRs and break-up the work into bite-size chunks. This is, undeniably, a good practice. But it can be cumbersome and distributive when trying to keep pace. In addition, you put the team at risk of getting git conflicts. Say you’re in the middle of building your feature and uncover a bug which requires fixing. As a good scout, you implement the fix and create a separate PR to deliver the fix to the team. At the same time, you keep the fix in your branch as you need it for your feature. At the point of squashing, your newly squashed commit conflicts with the stand-alone fix you’ve delivered to your team. This is nothing that git can’t fix, but it is a nuisance nonetheless. Con: Review Potential A good PR shouldn’t have too many changes, making it easy to review. In the real world however, things get messy. Commits can give us some insight into how the complete changeset came to be. This requires the team to write well-curated commits though. This conflicts with the strength we’re getting from allowing freedom to commit as one sees fit. The History Rewriting Controversy It is good to know that what I’m about to suggest is considered blasphemy by many. Rewriting history is not without its dangers. Changes can go missing, and others who have based their work on now-changed history need to deal with conflicts. However, when applied prudently, rewriting history can yield benefits as well. In this context, some advanced git knowledge is required. The Alternative There was a soft hint towards using conventional commits in Dustin’s article. Let's go ahead and fully endorse adopting it. The convention is simple enough, and the documentation is exhaustive. Now I hear you think, “but we just concluded that allowing us to commit as we like was a good thing”. And you are not wrong. This is where history rewriting comes into play. As you’re working, commit as you like. Then, when it’s time to put your changes up for review, start editing your branch to ensure each change is nicely wrapped and documented in a proper commit. Finally, after getting a thumbs-up on the PR, rebase your changes on top of the branch you’re merging into, and finally do a normal merge. Most git hosting services offer this workflow for you. While I endorse rewriting history in your own branch, restrain from altering shared branches like “main” or “develop”. By sticking to this small rule, you’ve already negated most disadvantages of rewriting history. Shared Changes If we look back at our scenario where both the main and our feature branch include a fix, we get to the same point where we want to merge. However in this case, given that you’ve made the same commit in both branches, git is clever enough to fix the flow of history and remove the fix from your new changes. The following flow... ... will look like this after merging: Fixes On Your Own Features Although this is part of the conventional commit strategy, I feel it deserves some special attention. If you have introduced a new feature in your branch, and committed the changes. It can happen that you introduced a bug. Your first intuition might be to create a “fix” commit. Instead, consider going back to your feature commit and amending the fix to it. This has two advantages. First of all, the history will be less cluttered. Looking back at what changed, it's easy to see which features got introduced and what bugs we found along the way. On top of that, it will prevent confusion for your reviewers. Now, the code presented to others is fixed code. At no time in its history does it ever contain the bug. Your co-workers are not going to have any comments on it. How To Rewrite Your Branch Now we know why to clean-up, let's look at strategies to actually do the orchestration. The most obvious route is to keep the changeset you want to present in mind. Doing so, one prevents having to go back and rewrite everything from scratch. As an added bonus, I’ve found that it helps me better separate concerns. Complete Wipe If you like making periodic commits (or some other strategy that results in you creating arbitrary commits) chances are you are going to completely wipe all commits (not the changes) in your branch. The simplest way to accomplish this is by doing a soft reset to where you forked from the main branch. This can be achieved by rebasing and resetting to main (given main is where you want to merge into). This is a good approach as you also prepare your branch for being merged back. ` This can also be accomplished by counting the amount of commits and making that amount of steps back from HEAD. For example, if you have made 4 commits in your branch. ` And lastly, you can do this by knowing where you started off. One can find this by looking at the logs: ` Using either of these methods will leave you with no commits in your branch, and all your changes in your workspace. From this point, you can start cherry-picking your changes, and making well-curated commits. Interactive Rebase If you already have somewhat of a structure, interactive rebasing might be a better solution for you. This will allow you to go over each commit, and decide on how to alter them. The most interesting options being: s, squash - this will add the changes from this commit to its parent, followed by allowing you to change the commit message, and thus appending the message with the squashed changes. e, edit - using this option, the rebase will stop right before the commit gets added to the branch as if you went back in time and just did the development work. From this point, you can add files, split the commit in multiple different commits, change the commit message, or do whatever you’d like to do. d, drop - in the rare occasion you simply don’t want this commit anymore. r, reword - like edit, but you’re only offered the option to change the commit message. To start an interactive rebase, simply run ` Conclusion By embracing history rewriting and dropping squash merging. A team could produce an even cleaner git history. This option might not be for everyone, as it requires a little work and git knowledge. But if done well, it will circumvent some of the drawbacks of our pragmatic approach....

Oct 17, 2022

6 mins

Git

Next.js Route Groups

Starting from Next.js 13.4, Vercel introduced the App Router with a whole set of new and exciting features. The way we organize the routing in our application has changed radically compared to previous versions of Next.js, as well as the definition and usage of Layouts for our pages. In this article, we will focus on what is called Route Groups, their use cases, and how they can help us in our developer experience. Basic introduction to the new App Router In version 13, Next.js introduced a new App Router built on React Server Components, which supports shared layouts, nested routing, loading states, error handling, and more. The App Router works in a new directory named app Creating a page.tsx file inside the app/test-page folder allows you to define what users are going to see when they navigate to /test-page. So folder’s names inside app directory define your app routes. You can also have nested routes like this: In this case, the URL of your page will be /test-page/nested-page By default, components inside app are React Server Components. This is a performance optimization and allows you to easily adopt them, and you can also use Client Components. Layouts In Next.js, a Layout file is a special component that is used to define the common structure and layout of multiple pages in your application. It acts as a wrapper around the content of each page, providing consistent styling, structure, and functionality. The purpose of a Layout file is to encapsulate shared elements such as headers, footers, navigation menus, sidebars, or any other components that should be present on multiple pages. By using a Layout file, you can avoid duplicating code across multiple pages and ensure a consistent user experience throughout your application. To create a Layout file in Next.js, you typically create a separate component file, such as Layout.tsx, and define the desired layout structure within it. This component can then be imported and used on individual pages where you want to apply the shared layout. By wrapping your page content with the Layout component, Next.js will render the shared layout around each page, providing a consistent look and feel. This approach simplifies the management of common elements and allows for easy updates or modifications to the layout across multiple pages. Here is an example of how to use a Layout file with the new App Router Route Groups In Next.js, the folders in your app directory usually correspond to URL paths. But if you mark a folder as a Route Group, it won't be included in the URL path of the route. This means you can organize your routes and project files into groups without changing the URL structure. Route groups are helpful for: 1. Organizing routes into groups based on site sections, intent, or teams. 2. Creating nested layouts within the same route segment level: - You can have multiple nested layouts in the same segment, even multiple root layouts. - You can add a layout to only a subset of routes within a common segment. To create a route group inside your app folder you just need to wrap the folder’s name in parenthesis: (folderName) Since route groups won’t change the URL structure your page.tsx content will be shown under the/inside-route-group path. Use cases Route groups are amazing when you want to create multiple layouts inside your page: Or if you want to specify a layout for a specific group of pages You need to be careful because all the examples above can lead you to some misunderstanding. *What is root layout? The top-most layout is called the Root Layout. This required layout is shared across all pages in an application.* As you can see, the route folder in the two examples above always has a well-defined root layout. This means that the specific layouts we have defined for the various groups will not replace the root layout, but will be added to it. However, Route Groups also allow us to redefine the root layout. Specifically, they allow us to define different root layouts for different segments of pages. All we have to do is remove the common Root Layout file, create some Route groups, and re-define the different Root layout files for every group in the route folder: In this way, we will have pages with different root layouts, and our paths will once again not be affected by the folder name used in parentheses. Conclusion In conclusion, Next.js route groups offer a powerful and flexible solution for organizing and managing routes in your Next.js applications. By grouping related routes together, you can improve code organization, enhance maintainability, and promote code reusability. Route groups allow for the use of shared layout components, and the customization of root layouts for different segments of pages. With Next.js route groups, you can streamline your development process, create a more intuitive routing structure, and ultimately deliver a better user experience....

Feb 7, 2024

6 mins

NextJSReact

Introduction to Zod for Data Validation

As web developers, we're often working with data from external sources like APIs we don't control or user inputs submitted to our backends. We can't always rely on this data to take the form we expect, and we can encounter unexpected errors when it deviates from expectations. But with the Zod library, we can define what our data ought to look like and parse the incoming data against those defined schemas. This lets us work with that data confidently, or to quickly throw an error when it isn't correct. Why use Zod? TypeScript is great for letting us define the shape of our data in our code. It helps us write more correct code the first time around by warning us if we are doing something we shouldn't. But TypeScript can't do everything for us. For example, we can define a variable as a string or a number, but we can't say "a string that starts with user_id_ and is 20 characters long" or "an integer between 1 and 5". There are limits to how much TypeScript can narrow down our data for us. Also, TypeScript is a tool for us developers. When we compile our code, our types are not available to the vanilla JavaScript. JavaScript can't validate that the data we actually use in our code matches what we thought we'd get when we wrote our TypeScript types unless you're willing to manually write code to perform those checks. This is where we can reach for a tool like Zod. With Zod, we can write data schemas. These schemas, in the simplest scenarios, look very much like TypeScript types. But we can do more with Zod than we can with TypeScript alone. Zod schemas let us create additional rules for data parsing and validation. A 20-character string that starts with user_id_? It's z.string().startsWith('user_id_').length(20). An integer between 1 and 5 inclusive? It's z.number().int().gte(1).lte(5). Zod's primitives give us many extra functions to be more specific about *exactly* what data we expect. Unlike TypeScript, Zod schemas aren't removed on compilation to JavaScript—we still have access to them! If our app receives some data, we can verify that it matches the expected shape by passing it to your Zod schema's parse function. You'll either get back your data in exactly the shape you defined in your schema, or Zod will give you an error to tell you what was wrong. Zod schemas aren't a replacement for TypeScript; rather, they are an excellent complement. Once we've defined our Zod schema, it's simple to derive a TypeScript type from it and to use that type as we normally would. But when we really need to be sure our data conforms to the schema, we can always parse the data with our schema for that extra confidence. Defining Data Schemas Zod schemas are the variables that define our expectations for the shape of our data, validate those expectations, and transform the data if necessary to match our desired shape. It's easy to start with simple schemas, and to add complexity as required. Zod provides different functions that represent data structures and related validation options, which can be combined to create larger schemas. In many cases, you'll probably be building a schema for a data object with properties of some primitive type. For example, here's a schema that would validate a JavaScript object representing an order for a pizza: ` Zod provides a number of primitives for defining schemas that line up with JavaScript primitives: string, number, bigint, boolean, date, symbol, undefined, and null. It also includes primitives void, any, unknown, and never for additional typing information. In addition to basic primitives, Zod can define object, array, and other native data structure schemas, as well as schemas for data structures not natively part of JavaScript like tuple and enum. The documentation contains considerable detail on the available data structures and how to use them. Parsing and Validating Data with Schemas With Zod schemas, you're not only telling your program what data should look like; you're also creating the tools to easily verify that the incoming data matches the schema definitions. This is where Zod really shines, as it greatly simplifies the process of validating data like user inputs or third party API responses. Let's say you're writing a website form to register new users. At a minimum, you'll need to make sure the new user's email address is a valid email address. For a password, we'll ask for something at least 8 characters long and including one letter, one number, and one special character. (Yes, this is not really the best way to write strong passwords; but for the sake of showing off how Zod works, we're going with it.) We'll also ask the user to confirm their password by typing it twice. First, let's create a Zod schema to model these inputs: ` So far, this schema is pretty basic. It's only making sure that whatever the user types as an email is an email, and it's checking that the password is at least 8 characters long. But it is *not* checking if password and confirmPassword match, nor checking for the complexity requirements. Let's enhance our schema to fix that! ` By adding refine with a custom validation function, we have been able to verify that the passwords match. If they don't, parsing will give us an error to let us know that the data was invalid. We can also chain refine functions to add checks for our password complexity rules: ` Here we've chained multiple refine functions. You could alternatively use superRefine, which gives you even more fine grained control. Now that we've built out our schema and added refinements for extra validation, we can parse some user inputs. Let's see two test cases: one that's bound to fail, and one that will succeed. ` There are two main ways we can use our schema to validate our data: parse and safeParse. The main difference is that parse will throw an error if validation fails, while safeParse will return an object with a success property of either true or false, and either a data property with your parsed data or an error property with the details of a ZodError explaining why the parsing failed. In the case of our example data, userInput2 will parse just fine and return the data for you to use. But userInput1 will create a ZodError listing all of the ways it has failed validation. ` ` We can use these error messages to communicate to the user how they need to fix their form inputs if validation fails. Each error in the list describes the validation failure and gives us a human readable message to go with it. You'll notice that the validation errors for checking for a valid email and for checking password length have a lot of details, but we've got three items at the end of the error list that don't really tell us anything useful: just a custom error of Invalid input. The first is from our refine checking if the passwords match, and the second two are from our refine functions checking for password complexity (numbers and special characters). Let's modify our refine functions so that these errors are useful! We'll add our own error parameters to customize the message we get back and the path to the data that failed validation. ` Now, our error messages from failures in refine are informative! You can figure out which form fields aren't validating from the path, and then display the messages next to form fields to let the user know how to remedy the error. ` By giving our refine checks a custom path and message, we can make better use of the returned errors. In this case, we can highlight specific problem form fields for the user and give them the message about what is wrong. Integrating with TypeScript Integrating Zod with TypeScript is very easy. Using z.infer<typeof YourSchema> will allow you to avoid writing extra TypeScript types that merely reflect the intent of your Zod schemas. You can create a type from any Zod schema like so: ` Using a TypeScript type derived from a Zod schema does *not* give you any extra level of data validation at the type level beyond what TypeScript is capable of. If you create a type from z.string.min(3).max(20), the TypeScript type will still just be string. And when compiled to JavaScript, even that will be gone! That's why you still need to use parse/safeParse on incoming data to validate it before proceeding as if it really does match your requirements. A common pattern with inferring types from Zod schemas is to use the same name for both. Because the schema is a variable, there's no name conflict if the type uses the same name. However, I find that this can lead to confusing situations when trying to import one or the other—my personal preference is to name the Zod schema with Schema at the end to make it clear which is which. Conclusion Zod is an excellent tool for easily and confidently asserting that the data you're working with is exactly the sort of data you were expecting. It gives us the ability to assert at runtime that we've got what we wanted, and allows us to then craft strategies to handle what happens if that data is wrong. Combined with the ability to infer TypeScript types from Zod schemas, it lets us write and run more reliable code with greater confidence....

Nov 15, 2024

7 mins

JavaScriptZod

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Mastering Git Rerere: Solving Repetitive Merge Conflicts with Ease

Mastering Git Rerere: Solving Repetitive Merge Conflicts with Ease

Introduction:

Understanding Git Rerere:

Configuring Git Rerere:

How to use it:

Benefits of Git Rerere:

Conclusion:

Mattia Magi

You might also like

Ensuring Accurate Workflow Status in GitHub for Enhanced Visibility

Git Strategies For Teams, Another Take

Next.js Route Groups

Introduction to Zod for Data Validation

Let's innovate together!

You might also like

Ensuring Accurate Workflow Status in GitHub for Enhanced Visibility

Git Strategies For Teams, Another Take

Next.js Route Groups

Introduction to Zod for Data Validation