ReactJS

State Management with React: Client State and Beyond

Jun 28, 2023

6 min read

Introduction

State management has long been a hotly debated subject in the React world. Best practices have continued to evolve, and there’s still a lot of confusion around the subject. In this article, we are going to dive into what tools we might want to use for solving common problems we face in modern web application development. There are different types of state and different types of ways to store and manage your application state. For example, you might have some local client state in a component that controls a dropdown, and you might also have a global store that contains authenticated user state. Aside from those typical examples, on some pages of your website, you might store some state in the URL.

For quite a while, we’ve been leaning into global client state in single-page app land. This is what state management tools like Redux and other similar libraries help us out with. In this post, we will cover these different strategies in more detail so that we can try to make the best decisions going forward regarding state management in our applications.

Local and global client state

In this section, we'll discuss the differences between local and global client state, when to use each, and some popular libraries that can help you manage them effectively.

When to use local client state

Local client state is best suited for managing state that is specific to a single component or a small group of related components. Examples of local state include form inputs, component visibility, and UI element states like button toggles. Using local state keeps the component self-contained, making it easier to understand and maintain. In general, it's a good idea to start with local state and only use global state when you have a clear need for it. This can help keep your code simple and easy to understand.

When to use global client state

Global client state is useful when you have state that needs to be accessed by multiple unrelated components, or when the state is complex and would benefit from a more carefully designed API. Common examples of global state include user authentication, theme preferences, and application-wide settings. By centralizing this state, you can easily share it across the entire application, making it more efficient and consistent.

If you’re building out a feature that has some very complex state requirements, this could also be a good case for using a “global” state management library. Truth is, you can still use one of these libraries to manage state that is actually localized to your feature. Most of these libraries support creating multiple stores. For example, if I was building a video chat client like Google Meets with a lot of different state values that are constantly changing, it might be a good idea to create a store to manage the state for a video call. Most state management libraries support more features than what you get out of the box with React, which can help design a clean and easy to reason about modules and APIs for scenarios where the state is complex.

Popular libraries for global state management

There are a lot of great libraries for managing state in React out there these days. I think deciding which might be best for you or your project is mostly a matter of preference.

Redux and MobX are a couple of options that have been around for quite a long time. Redux has gained a reputation for being overly complex and requiring a lot of boilerplate code. The experience is actually much improved these days thanks to the Redux Toolkit library. MobX provides an easy-to-use API that revolves around reactive data/variables. These are both mature and battle-tested options that are always worth considering.

Meta also has a state management named Recoil that provides a pretty easy-to-use API that revolves around the concept of atoms and selectors. I don’t see this library being used a ton in the wild, but I think it’s worth mentioning.

A couple of the more popular new players on the block are named jotai and zustand. I think after the Redux hangover, these libraries showed up as a refreshing oasis of simplicity. Both of these libraries have grown a ton in popularity due to their small byte footprints and simple, straightforward APIs.

Context is not evil

The React Context API, like Redux, has also been stigmatized over the years to the point where many developers have their pitchforks out, declaring that you should never use it. We leaned on it for state management a bit too much for a while, and now it is a forbidden fruit. I really dislike these hard all-or-nothing stances though. We just need to be a little bit more considerate about when and where we choose to use it.

Typically, React Context is best for storing, and making available global state that doesn’t change much. Some of the most common use cases are things like themes, authentication, localization, and user preferences. Contrary to popular belief, only components (and their children) that use that context (const context = useContext(someContext);) are re-rendered in the event of a state change, not all of the children below the context provider.

Storing state in the URL

The most underused and underrated tool in the web app state management tool belt is using the URL to store state. Storing state in the URL can be beneficial for several reasons, such as enabling users to bookmark and share application state, improving SEO, and simplifying navigation. The classic example for this is filters on an e-commerce website. A good user experience would be that the user can select some filters to show only the products that they are looking for and then be able to share that URL with a friend and them see the same exact results. Before you add some state to a page, I think it’s always worth considering the question: “Should I be able to set this state from the URL?”.

Tools for managing URL state

We typically have a couple of different tools available to use for managing URL state. Built-in browser APIs like the URL class and URLSearchParams. Both of these APIs allow you to easily parse out parts of a URL. Most often, you will store URL state in the parameters.

In most React applications, you will typically have a routing library available to help with URL and route state management as well. React Router has multiple hooks and other APIs for managing URL state like useLocation that returns a parsed object of the current URL state.

Keeping URL and application state in sync

The tricky part of storing state in the URL is when you need to keep local application state in sync with the URL values. Let’s look at an example component with a simple name component that stores a piece of state called name.

import React, { useState, useEffect } from 'react';
import { useLocation, useHistory } from 'react-router-dom';

function MyComponent() {
	const location = useLocation();
	const history = useHistory();
	const [name, setName] = useState('');

	useEffect(() => {
		// Update the name state when the URL changes
		const searchParams = new URLSearchParams(location.search);
		setName(searchParams.get('name') || '');
	}, [location]);

	function handleNameChange(event) {
		setName(event.target.value);
		// Update the URL when the name changes
		history.push(`/my-component?name=${event.target.value}`);
	}

	return (
		<div>
			<input type="text" value={name} onChange={handleNameChange} />
		</div>
	);
}

The general idea is to pull the initial value off of the URL when the component mounts and set the state value. After that, in our event handler, we make sure to update the URL state as well as our local React state.

Moving state to the server

Moving web application state to the server can be beneficial in several scenarios. For example, when you have a complex state that is difficult to manage on the client-side. By moving the state to the server, you can simplify the client-side code and reduce the amount of data that needs to be transferred between the client and server. This can be useful for applications that have a lot of business logic or complex data structures. In most cases if there’s some logic or other work that you can move off of your client web application and onto the server that is a win.

Conclusion

State management is a crucial aspect of building modern web applications with React. By understanding the different types of state and the tools available for managing them, you can make informed decisions about the best approach for your specific use case. Remember to consider local and global client state, URL-based state, and server-side state when designing your application's state management strategy.

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How to test React custom hooks and components with Vitest

Introduction In this guide, we'll navigate through the process of testing React hooks and components using Vitest—a powerful JavaScript unit testing framework. Discover how Vitest simplifies testing setups, providing an optimal solution for both Vite-powered projects and beyond. Vitest is a javascript unit testing framework that aims to position itself as the Test Runner of choice for Vite projects and as a solid alternative even for projects not using Vite. Vitest was built primarily for Vite-powered projects, to help reduce the complexity of setting up testing with other testing frameworks like Jest. Vitest uses the same configuration of your App (through vite.config.js), sharing a common transformation pipeline during dev, build, and test time. Prerequisites This article assumes a solid understanding of React and frontend unit testing. Familiarity with tools like React Testing Library and JSDOM will enhance your grasp of the testing process with Vitest. Installation and configuration Let’s see how we can use Vitest for testing React custom hooks and components. But first, we will need to create a new project with Vite! If you already have an existing project, you can skip this step. ` Follow the prompts to create a new React project successfully. For testing, we need the following dependencies installed: Vitest as the unit testing framework JSDOM as the DOM environment for running our tests React Testing Library as the React testing utilities. To do so, we run the following command: ` Once we have those packages installed, we need to configure the vite.config.js file to run tests. By default, some of the extra configs we need to set up Vitest are not available in the Vite config types, so we will need the vite.config.ts file to reference Vitest types by adding /// reference types=”vitest” /> at the top of the file. Add the following code to the vite.config.ts ` We set globals to true because, by default, Vitest does not provide global APIs for explicitness. So with this set to true, we can use keywords like describe, test and it without needing to import them. To get TypeScript working with the global APIs, add vitest/globals to the types field in your tsconfig.json. ` The environment property tells Vitest which environment to run the test. We are using jsdom as the environment. The root property tells Vitest the root folder from where it should start looking for test files. We should add a script for running the test in package.json ` With all that configured, we can now start writing unit tests for customs hooks and React components. Writing test for custom hooks Let’s write a test for a simple useCounter hook that takes an initial value and returns the value, an increment function and a decrement function. ` We can write a test to check the default return values of the hook for value as below: ` To test if the hook works when we increment the value, we can use the act() method from @testing-library/react to simulate the increment function, as shown in the below test case: ` Kindly Note that you can't destructure the reactive properties of the result.current instance, or they will lose their reactivity. Testing hooks with asynchronous logic Now let’s test a more complex logic that contains asynchronous logic. Let’s write a useProducts hook that fetches data from an external api and return that value ` Now, let’s see what the test looks like: ` In the above example, we had to spy on the global fetch API, so that we can mock its return value. We wrapped that inside a beforeAll so that this runs before any test in this file. Then we added an afterAll method and called the mockRestore() to run after all test cases have been completed and return all mock implementations to their original function. We can also use the mockClear() method to clear all the mock's information, such as the number of calls and the mock's results. This method is handy when mocking the same function with different return values for different tests. We usually use mockClear() in beforeEach() or afterEach() methods to ensure our test is isolated completely. Then in our test case, we used a waitFor(), to wait for the return value to be resolved. Writing test for components Like Jest, Vitest provides assertion methods (matchers) to use with the expect methods for asserting values, but to test DOM elements easily, we will need to make use of custom matchers such as toBeInTheDocument() or toHaveTextContent(). Luckily the Vitest API is mostly compatible with the Jest API, making it possible to reuse many tools originally built for Jest. For such methods, we can install the @testing-library/jest-dom package and extend the expect method from Vitest to include the assertion methods in matchers from this package. ` After installing the jest-dom testing library package, create a file named vitest-setup.ts on the root of the project and import the following into the project to extend js-dom custom matchers: ` Since we are using typescript, we also need to include our setup file in our tsconfig.json: ` In vite.config.ts, we need to add the vitest-setup.ts file to the test.setupFiles field: ` Now let’s test the Products.tsx component: ` We start by spying and mocking the useProducts hook with vi.spyOn() method from Vitest: ` Now, we render the Products component using the render method from @testing-library/react and assert that the component renders the list of products as expected and also the product has the title as follows: ` In the above code, we use the render method from @testing-library/react to render the component and this returns some useful methods we can use to extract information from the component like getByTestId and getByText. The getByTestId method will retrieve the element whose data-testid attribute value equals product-list, and we can then assert its children to equal the length of our mocked items array. Using data-testid attribute values is a good practice for identifying a DOM element for testing purposes and avoiding affecting the component's implementation in production and tests. We also used the getByText method to find a text in the rendered component. We were able to call the toBeInTheDocument() because we extended the matchers to work with Vitest earlier. Here is what the full test looks like: ` Conclusion In this article, we delved into the world of testing React hooks and components using Vitest, a versatile JavaScript unit testing framework. We walked through the installation and configuration process, ensuring compatibility with React, JSDOM, and React Testing Library. The comprehensive guide covered writing tests for custom hooks, including handling asynchronous logic, and testing React components, leveraging custom matchers for DOM assertions. By adopting Vitest, developers can streamline the testing process for their React applications, whether powered by Vite or not. The framework's seamless integration with Vite projects simplifies the setup, reducing the complexities associated with other testing tools like Jest....

Mar 15, 2024

5 mins

ViteReactTesting

AI (Probably) Won’t Ruin Your Engineering Career with Ben Lesh, Adam Rackis, & Tracy Lee

In this episode of the Modern Web Podcast, hosts Tracy Lee, Ben Lesh, and Adam Rackis kick things off by discussing the progress of observables landing in the browser and the potential impact it could have on the use of RXJS. As developers, we're always on the lookout for new tools and technologies that can make our lives easier, and observables in the browser certainly have the potential to do just that. They talk about whether or not you should listen to your “customers” or have a strong vision that you want to push forward, like Ryan Carniato and his approach with Solid and Signals. The three also talk about AI tools, such as GPT and Co-Pilot, and how they are shaping the future of coding and ideation. Finally, Ben, Adam, and Tracy briefly touch on the potential impact of automation on job roles and the outsourcing of tech jobs. While automation can streamline certain tasks, it's important to remember that human creativity and problem-solving skills are irreplaceable. Download this episode here!...

Feb 16, 2024

1 min

ReactRxJSArtificial Intelligence

Level up your REST API's with JSON Schema

JSON Schema isn’t a hot topic that gets a lot of attention compared to GraphQL or other similar tools. I discovered the power of JSON Schema while I was building a REST API with Fastify. What is it exactly? The website describes it as “the vocabulary that enables JSON data consistency, validity, and interoperability at scale”. Or more simply, it’s a schema specification for JSON data. This article is going to highlight some of the benefits gained by defining a JSON Schema for a REST API. JSON Schema Basics Here’s an example of a simple schema representing a user: ` If you’re familiar with JSON already, you can probably understand most of this at a glance. This schema represents a JSON object with some properties that define a User in our system, for example. Along with the object’s properties, we can define additional metadata about the object. We can describe which fields are required and whether or not the schema can accept any additional properties that aren’t defined on the properties list. Types We covered a lot of types in our example schema. The root type of our JSON schema is an object with various properties defined on it. The base types available to define in your JSON Schema map to valid JSON types: object, array, string, number, integer, boolean. Check the type reference page to learn more. Formats The email property in our example has an additional field named format next to its type. The format property allows us to define a semantic identification for string values. This allows our schema definition to be more specific about the type of values allowed for a given field. “hello” is not a valid string value for our email type. Another common example is for date or timestamp values that get serialized. Validation implementations can use the format definition to make sure a value matches the expected type and format defined. There’s a section on the website that lists the various formats available for the string type. Schema Structuring JSON Schema supports referencing schemas from within a schema. This is a very important feature that helps us keep our schemas DRY. Looking back to our initial example we might want to define a schema for a list of users. We defined an id on our user schema of “user”, we can use this to reference that schema from another schema. ` In this example we have a simple schema that is just an array whose items definition references our user schema. This schema is exactly the same as if we defined our initial schema inside of "items": { }. The JSON Schema website has a page dedicated to structuring schemas. JSON Schema Benefits Validation One of the main benefits of defining a schema for your API is being able to validate inputs, outputs. Inputs include things like the request body, URL parameters, and search parameters. The output is your response JSON data or headers. There are some different libraries available to handle schema validation. A popular choice and the one used by Fastify is called Ajv. Security Validating inputs has some security advantages. It can prevent bad or malicious data from being accepted by your API. For instance, you can specify that a certain field must be an integer, or that a string must match a certain regex pattern. This can help prevent SQL injection, cross-site scripting (XSS). Defining a schema for your response types can help to prevent leaking sensitive data from your database. Your web server can be configured to not include any data that is not defined in the schema from your responses. Performance By validating data at the schema level, you can reject invalid requests early, before they reach more resource-intensive parts of your application. This can help protect against Denial of Service (DoS) attacks. fast-json-stringify is a library that creates optimized stringify functions from JSON schemas that can help improve response times and throughput for JSON API’s. Documentation JSON Schema also greatly aids in API documentation. Tools like OpenAPI and Swagger use JSON Schema to automatically generate human-readable API documentation. This documentation provides developers with clear, precise information about your API’s endpoints, request parameters, and response formats. This not only helps to maintain consistent and clear communication within your development team, but also makes your API more accessible to outside developers. Type-safety I plan to cover this in more detail in an upcoming post but there are tools available that can help achieve type-safety both on your server and client-side by pairing JSON Schema with TypeScript. In Fastify for example, you can infer types in your request handlers based on your JSON Schema specifications. Schema Examples I’ve taken some example schemas from the Fastify website to walk through how they would work in practice. ` ` We would use this schema to define, validate, and parse the query string of an incoming request in our API. Given a query string like: ?name=Dane&excitement=10&other=additional - we can expect to receive an object that looks like this: ` Since additionalProperties are not allowed, the other property that wasn’t defined on our schema gets parsed out. ` Imagining we had a route in our API defined like /users/:userId/posts/:slug ` Given this url: /users/1/posts/hello-world - we can expect to get an object in our handler that looks like this: ` We can be sure about this since the schema doesn’t allow for additional properties and both properties are required. If either field was missing or not matching its type, our API can automatically return a proper error response code. Just to highlight what we are getting here again. We are able to provide fine-grained schema definitions for all the inputs and outputs of our API. Aside from serving as documentation and specification, it powers validation, parsing, and sanitizing values. I’ve found this to be a very simple and powerful tool in my toolbox. Summary In this post, we've explored the power and functionality of JSON Schema, a tool that often doesn't get the spotlight it deserves. We've seen how it provides a robust structure for JSON data, ensuring consistency, validity, and interoperability on a large scale. Through our user schema example, we've delved into key features like types, formats, and the ability to structure schemas using references, keeping our code DRY. We've also discussed the substantial benefits of using JSON Schema, such as validation, enhanced security, improved performance, and the potential for type-safety. We've touched on useful libraries like Ajv for validation and fast-json-stringify for performance optimization. In a future post we will explore how we can utilize JSON Schema to achieve end-to-end type-safety in our applications....

Feb 16, 2024

5 mins

JSON

Intro to EdgeDB - The 10x ORM

Intro to EdgeDB - The 10x ORM I’ve written a couple of posts recently covering different TypeScript ORMs. One about Prisma, and another about Drizzle. ORM’s are a controversial topic in their own right - some people think they are evil, and others think they are great. I enjoy them quite a bit. They make it easy to interact with your databases. What is more important and magical for an application than data? SQL without an ORM is amazing as well, but there are some pain points with that approach. Today I’m excited to write about EdgeDB, which isn’t _exactly_ an ORM or a database from my perspective (although they call themselves one). It is, however an incredibly impressive piece of technology that solves these common pain points in a pretty novel way. So if it’s not an ORM or a database, what exactly is it? I don’t think I can answer that in one or two sentences, so we will explore the various pieces that make up EdgeDB in this article. From a high-level standpoint, though, an interface/query language that sits in front of PostgreSQL. This may seem like some less important implementation detail, but in my eyes, it’s a feature and one of the most compelling selling points. Data Modeling EdgeDB advertises itself as a “graph-relational database”. The core components of EdgeDB data modeling are the schema, type system, and relationship definitions. A schema will consist of objects that contain various typed attributes and links that connect the objects. In SQL, a table is analogous to an Object, and a foreign-key is associated with a link. Here’s what a simple schema in EdgeDB looks like ` There’s a few things to highlight here * We defined two different objects (tables) User and Post * Each object contains properties with their types defined * str is one of several scalar types (bool, int, float, json, datetime, etc) * the author property is a required link to the User object Defining relations / associations In our example above we defined a one-to-many relationship between a user and posts. All the relation types that you can define in traditional SQL are available. One interesting feature though is called backward links. These can be defined in your schema and it allows you to access related data from both sides of a relationship. ` likes are a many-to-many relationship between Tweet and User. With a backlink defined multi link likers := Tweet.<likes[is User]; - we can access likes from a User and likers from a Tweet. ` That's how we can access these relations in our queries. You might be looking at these queries and thinking it looks a lot like GraphQL. This is why they call it a ‘Graph-relational’ database. We’ve only scratched the surface of EdgeDB schema’s. Hopefully, I’ve at least managed to pique your interest. Computed properties Computed properties are a super powerful feature that can be added to your schema or queries. This example user schema creates a computed discriminator and username property. The discriminator uses an EdgeDB standard library function to generate a discriminator number and the username property is a combination between the name and discriminator properties. ` Globals and Access Policies EdgeDB allows you to define global variables as part of your schema. The most common use case I’ve seen for this is to power the access policy feature. You can define a global variable as part of your schema: global current_user: uuid; With a global variable defined, you can provide the value as a sort of context from your application by providing it into your EdgeDB driver/client. ` You can then add access policies directly to your schema, for example, to provide fine-grained access control to blog posts in your blogging application. ` Aside from access policies, you can use your global variables in your queries as well. For example, if you wanted a query to select the current user. ` Types and Sets EdgeDB is very type-centric. All of your data is strongly typed. We’ve touched on some of the types already. * Scalars - There are a lot of scalar types available out of the box * Custom scalars - Custom scalar types are user-defined extensions of existing types * Enums - Are supported out of the box - enum<Admin, Moderator, Member> * Arrays - Defined by passing the singular value type - array<str>; * Tuples - In EdgeD, tuples can contain more than 2 elements and come in named and unnamed varieties - <str, number>; tuple<name: str, jersey_number: float64, active: bool>; All queries return a Set which is a collection of values of a given type. In the query language, all values are Sets. Sets are a collection of values of a given type. A comma-separated list of values inside a set of {curly braces}. A query with no results will return an empty or singleton set. If we have no User values stored yet - select User returns {}. Paired with the query language types and set provides an incredibly powerful and expressive system for interacting with your data. If you thought TypeScript was cool, wait until you start writing EdgeQL! 🙂 EdgeQL Now to the fun stuff: the query language. We’ll use a schema from the docs and start by looking at some of those queries and build on those. The example schema has an abstract type Person with two sub-types based on it Hero and Villian. This is known as a polymorphic type in EdgeDB. The Movie type includes a 1:m association with Person ` Selecting properties / data Before we dig into some real queries we should just touch on how we select actual data from a query. It’s pretty obvious and GraphQL-like but worth mentioning. To specify properties to select, you attach a shape. This works for getting nested link / association data as well. Based on our schema, here’s how we could select fields from Movie, including data from the collection of related characters. ` There is also a feature called a splats that allows you to select all fields and/or all linked fields without specifying them individually. ` If you don’t specify any properties or splats, only id’s get returned select Movie; . Adding some objects with insert To get started, we can use insert to add objects to our database. We’ll start big by looking at the nested insert example. This example is interesting because it shows the creation of two objects in a single query. You’ll notice the simplicity of the syntax. Even though this is the first EdgeQL query we’re looking at, in my experience, it’s like this across the board. I’ve found EdgeQL queries to be simple and intuitive to the point where I’ve been able to intuit how to accomplish things in my head without having to reference the docs or ask the AI. This example adds a new Villian and a new Hero which gets assigned as a link or association to the nemesis field on our Villian. To accomplish this we see that we can nest queries by wrapping them in (). ` The next example is pretty similar, but instead of creating the linked property, we are select ing and adding several potential objects to the characters list of Movie since it is a multi link. This is a pretty complex query that is doing a lot of different things. It’s deceivingly succinct. To accomplish the same thing with SQL this would probably be about 3 different queries. This query finds the objects to add to the characters multi link by filtering on a collection of different strings to match against the name property. ` The last thing we’ll cover for insert is bulk inserts. This is particularly useful for things like seed scripts. In this example, you can just imagine that you have a JSON array of objects with hero names that gets passed in as an argument to your query ` Querying data with select We’ve already seen subqueries and a select in the last section where we found a collection of Person records with a filter. We’ll build on that and see what tools are available to us when it comes to querying data. This one covers a lot of ground. Very similar to SQL we have order and limit, and offset operators to support sorting and pagination. Also there is a whole standard library of functions and operators like count that can be used in our queries. This example returns a collection of villian names, excluding the first and last result. ` Most commonly, you will want to filter by an id ` Here’s another common example filtering by datetime. Since we’re using a string value here we need to cast it to the EdgeDB datetime type. ` You get a pretty similar toolbox to SQL when it comes to filtering with your common operators and things. Combined with all the tools in the standard library, you can get pretty creative with it. Changing values and links with update The update..filter..set statement is how we can update existing data with EdgeQL. set is followed by a shape with assignments of properties to be updated. ` You can replace links for an object ` or add additional ones ` An even more interesting example is removing links matched on a type. Since Villian is a sub-type of Person , this query will remove all characters linked of the Villian type. ` Deleting objects with delete Deleting is pretty straight forward. Using the delete command you can just filter for the objects that you would like to remove. ` When the EdgeQL pieces fall into place As you become more familiar with the EdgeQL query language chances are you’ll start writing very complex queries fluently because everything just makes sense once you’ve learned the building blocks. Domain and business concerns I don’t think they explicitly mention this as a goal anywhere but it’s something that I picked up on pretty quickly. EdgeDB nudges you to move more of what might have traditionally been application logic into your database layer. This is a topic that can bring a lot of division since even things like foreign keys and constraints in SQL are frowned upon in some circles. EdgeDB goes as far as providing constraints, global variables, contexts, and authorization support built into the database. I think that the ability to bake some of these concerns into your EdgeDB Schema is great. The way you model your schema and database in EdgeDB map to your domain in a much more intuitive way where domain concerns don’t really feel out of place there. Database Clients and Query Builders and Generators We’ve covered a lot so far to highlight what EdgeDB is and how to handle common use cases with the query language. To use it in your project though, you will need a client/driver library. There are clients available in several different languages. The one that they clearly have put the most investment into is the TypeScript query builder. We’ll briefly look at both options: simple driver/client and query builder. Whichever you end up choosing you will need to instantiate a driver and make sure you have a connection to your database instance configured. Basic client Although the TS query builder is very popular and pretty amazing, I couldn’t get away from just writing EdgeQL queries. In my application, I composed queries using template strings, and it worked great. The clients all have a set of methods available for passing in EdgeQL queries and parameters. querySingle is a method for queries where you are only expecting a single result. If your query will have multiple results you would use query instead. There is also a queryRequiredSingle which will throw an error if no results are found. There are some other methods available as well including one for running queries in a transaction ` The first argument is the query, and the second is a map of parameters. In this example we include the title parameter and it is accessed in our query via $title. TypeScript query builder If you have a TypeScript app and type-safety is important, you might prefer using the query builder. It is a pretty incredible feat of TypeScript magic initially developed by the same developer behind the popular library Zod. We can’t cover it in very much depth here but we’ll look at an example just to have an idea of what the query builder looks like in an application. ` The query builder is able to infer the result type automatically. It knows which fields you’ve selected, it knows that the result will be a single item. Query generator There are generators for queries and types. So even if you opt out of using the query builder you can still have queries that are strongly typed. It’s nice to have this option if you want to just write your queries as EdgeQL in .edgeql files. ` We end up with an exported function named getUser that is strongly typed. ` Tools and Utilities The team at EdgeDB puts a big emphasis on developer experience. It shows up all over the place. We’ve already seen some utilities with the generators that are available. There are some other tools available as well that help complete the entire experience. EdgeDB CLI The first and most important tool to mention is the CLI. If you’ve started using EdgeDB then you’ve most likely already installed and used it. The CLI is pretty extensive. It includes commands for things like migrations, managing EdgeDB versions and installations, managing projects and local/cloud database instances, dumps and restores, a repl, and more. The CLI makes managing EdgeDB a breeze. Admin UI The CLI includes a command to launch an admin UI for any project or database. The Admin UI includes a awesome interactive diagram of your database schema, a repl for running queries, and a table to inspect and make changes to the data stored in your database. Summary Adopting newer database technology is a tough sales pitch. Replacing your application’s database technology at any point in its lifecycle is not a problem that anyone wants to have. This is one of the reasons why EdgeDB being a superset of PostgreSQL is a huge feature in my opinion. The underlying database technology is tried and true, and EdgeDB is open-source. Based on this, I would feel confident using EdgeDB if it aligned well from a technical and business perspective. We’ve covered a lot of ground in this post. EdgeDB is feature-packed and powerful. Databases is a tough nut to crack, and I commend the team for all their hard work to help continue pushing forward one of the most important components of almost any application. I’m typically pretty conservative when it comes to databases, but EdgeDB took a great approach, in my opinion. I recommend at least giving it a try. You might catch the EdgeDB bug like I did!...

Apr 26, 2024

11 mins

JavaScriptEdgeDB

State Management with React: Client State and Beyond

Introduction

Local and global client state

When to use local client state

When to use global client state

Popular libraries for global state management

Context is not evil

Storing state in the URL

Tools for managing URL state

Keeping URL and application state in sync

Moving state to the server

Conclusion

Dane Grant

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