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Import (ConnectionString)ĬonnString = 'host=127.0.0.1 port=5432 user=postgres dbname=postgres password=password' Note that this level of Template Haskell requires many compiler extensions. Instead of defining User in the normal Haskell way, we're going to define it within the quasi-quoter. This means it will create all our tables for us!īut before we see this in action, we need to re-define our user type. After this Template Haskell gets compiled, this function will allow us to migrate our DB. More importantly, we also create a migration function, migrateAll. In particular we specify sqlSettings, so everything we do here will focus on an SQL database. We notate certain settings about those types. Within this section, we'll define all the different types our database will use. It then generates the necessary Template Haskell for our data schema. The share function takes a list of settings and then the quasi-quoter itself. The quasi-quoter is the final argument: import qualified as PTH Here's what the Template Haskell call looks like. We delimit a quasi-quoter by a combination of brackets and pipes. It is often used in libraries that do some sort of foreign function interface.

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This is a block of code that follows some syntax designed by the programmer or in a library, rather than normal Haskell syntax.

To generate our code, we'll use a language construct called a 'quasi-quoter'. With Persistent however, the amount of code generated is substantial, so the pros out-weigh the cons. It will also make our code less accessible to inexperienced Haskellers. But it will make our compile times longer as well. It does allow us to avoid writing some boilerplate code. We can get these bonuses from Persistent without all that much extra code! To do this, we're going to use Template Haskell (TH). Persistent helps us solve these problems. There would be a high probability of errors. We could write out these raw commands and execute them, but the same issues apply. And this means writing another error-prone command.įrom our Haskell program, we'll also want to make SQL queries based on the structure of the user.

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If we update the Haskell code, we have to remember to update the database.

When we do this, there's nothing linking our Haskell data type to the table structure. The command would look something like this: create table users ( But regardless, the process will be at least a little error prone.

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We could do this with a manual SQL command or through an editor. We'll first need to define the table to store our users. Imagine we want to store objects of this type in an SQL database. Our Basic TypeĬonsider a simple user type that looks like this: data User = User Let's start our journey by defining the type we'd like to store. You can also make type-safe queries to save yourself the hassle of decoding data. With Persistent, you can link your Haskell types to your database definition. There are many Haskell libraries that allow you to make a quick SQL call.

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If you want a larger listing of the many different libraries available to you, be sure to download our Production Checklist! It'll tell you about other options for databases, APIs and more!Īs a final note, all the code for this series is on Github! For this first part, most of the code lives in the Basic Schema module and the Database module. If you're already familiar with this, feel free to move on to part 2, where we'll look at building an API using Servant. We'll start by looking at how we store our Haskell data in databases. Welcome to our Real World Haskell Series! In these tutorials, we'll explore a bunch of different libraries you can use for some important tasks in backend web development.

Brew install haskell