PG-Entity Book

Welcome to pg-entity's documentation.

Read the Tutorial to learn how to use the library.

Read the Guides to learn more about specific usecases and patterns.

See also these resources to understand the library's underlying mechanisms:

• postgresql-simple: The library that provies the Query primitives and the database connection

• pg-transact: The library that provides the transaction monad transformer in which our queries run

• Oliver Charles' 24 Days of GHC Extensions series if you want to understand the underlying derivation mechanisms that enable us to write less code:

  • Deriving
  • DeriveGeneric

• Richard Eisenberg's Avoid boilerplate instances with -XDerivingVia is most helpful to understand how the GenericEntity mechanism works, as well as a showcase for other deriving strategies.

pg-entity tutorial

In this tutorial, you will learn how to implement the Entity typeclass for your business logic data-types, and run queries against the database.

Setting up

Language Extensions

• OverloadedLists allow us to use the [list] syntax for datatypes other than List, like Vector.
• QuasiQuotes enable us to write plain SQL and field names in a [|quasi-quoter block|].
• The Deriving extensions give us more powerful typeclass derivation.

{-# LANGUAGE DeriveAnyClass #-}
{-# LANGUAGE DerivingVia #-}
{-# LANGUAGE GeneralizedNewtypeDeriving #-}
{-# LANGUAGE OverloadedLists #-}
{-# LANGUAGE OverloadedStrings #-}
{-# LANGUAGE QuasiQuotes #-}

module Tutorial where

Then, let's import some data-types and modules:

import Data.Pool (Pool)
import Data.Text (Text)
import Data.Time (UTCTime)
import Data.UUID (UUID)
import Database.PostgreSQL.Simple
import Database.PostgreSQL.Simple.FromField
import Database.PostgreSQL.Simple.ToField
import Database.PostgreSQL.Transact (DBT)
import GHC.Generics

import Control.Monad.Error
import qualified Data.Time as Time
import qualified Data.UUID.V4 as UUID
import Database.PostgreSQL.Entity
import Database.PostgreSQL.Entity.DBT
import Database.PostgreSQL.Entity.Types

And let's write down our initial data models for a blog. Author, and BlogPost.

It is good practice to wrap your primary key in a newtype to gain more type-safety, but without losing access to typeclass instances of the underlying type, with deriving newtype.

newtype AuthorId = AuthorId {getAuthorId :: UUID}
  deriving newtype (Eq, Show, FromField, ToField)

data Author = Author
  { authorId :: AuthorId
  -- ^ Primary key
  , name :: Text
  , createdAt :: UTCTime
  }
  deriving stock (Eq, Generic, Show)
  deriving anyclass (FromRow, ToRow)

and

newtype BlogPostId = BlogPostId {getBlogPostId :: UUID}
  deriving newtype (Eq, FromField, Show, ToField)

data BlogPost = BlogPost
  { blogPostId :: BlogPostId
  -- ^ Primary key
  , authorId :: AuthorId
  -- ^ Foreign key
  , title :: Text
  , content :: Text
  , createdAt :: UTCTime
  }
  deriving stock (Eq, Generic, Show)
  deriving anyclass (FromRow, ToRow)

Let us write the Entity instances now:

instance Entity Author where
  tableName = "authors"
  primaryKey = [field| author_id |]
  fields =
    [ [field| author_id |]
    , [field| name |]
    , [field| created_at |]
    ]

The above instance declaration reads as:

My table's name is authors, its primary key is author_id, and the fields are author_id, name, and created_at.

The order matters for the declarations, so make sure that each field is at the correct position.

Let's do the same for BlogPost:

instance Entity BlogPost where
  tableName = "blogposts"
  primaryKey = [field| blogpost_id |]
  fields =
    [ [field| blogpost_id |]
    , [field| author_id |]
    , [field| title |]
    , [field| content |]
    , [field| created_at |]
    ]

And these instances will give you access to the Entity functions to query your tables

Using Generics

But all these manual instances are a tad tedious. Fortunately, there is a derivation mechanism available that allows you to automate the generation of the Entity instance. This mechanism is called DerivingVia. It allows you to use a wrapper, called GenericEntity, and a list of options at the type-level to generate the instance

deriving via
  (GenericEntity
    '[ TableName "authors"
     , PrimaryKey "author_id"
     ] Author
  ) instance Entity Author

Those two options, TableName and PrimaryKey are optional, and the library will adopt the following defaults:

• tableName will be the snake_case version of the record's name. No pluralisation will be done.

• primaryKey will be the snake_case version of the first field of the record.

• field names will be the snake_case version of the record fields.

The advantages brought by this technique are that the error surface is reduced when implementing the Entity typeclass.

⚠️ While all these deriving parameters are optional, I advise you to write down the table name (with the TableName option). In the PostgreSQL world, it is customary to pluralise the name of the table containing your data, and pg-entity does not automatically do this.

⚠️ For performance reasons, you are advised to write the primary key in the options. If you do not, the generic deriving mechanism will have to do a linear search in the fields list (of complexity 𝛰(n) whereas the lookup will take 𝛰(1) if the primary key is given in your code. Do this especially if you have long tables.

Do it if you have long tables.

Writing the SQL migrations

In a separate file, we will translate our Haskell data models into SQL migrations.

create table authors (
    author_id uuid primary key,
    name text not null,
    created_at timestamptz not null
    );

create table blogposts (
    blogpost_id uuid primary key,
    author_id uuid not null,
    title text not null,
    content text not null,
    created_at timestamptz not null,
    constraint fk_author
      foreign key(author_id)
        references authors(author_id)
    );

Making queries

By implementing the Entity Typeclass, your data-type has access to a variety of functions, combinators and helpers that serve the one true purpose of this library:

Provide a safe mechanism to expand the fields of a table while writing a query.

Let us define our insertion function for the Author model:

insertAuthor :: Author -> DBT IO ()
insertAuthor = insert @Author

The result of this function, which we call a “DBT action”,* is then passed to withPool.

You can then build a higher-level API endpoint or route controller like that:

data AuthorInfo = AuthorInfo
  { name :: Text
  }
  deriving stock (Eq, Show)

mkAuthor :: MonadIO m => AuthorInfo -> m Author
mkAuthor AuthorInfo{name = authorName} = do
  authorId <- liftIO $ AuthorId <$> UUID.nextRandom
  createdAt <- liftIO Time.getCurrentTime
  pure Author{name = authorName, authorId, createdAt}

addAuthor
  :: MonadIO m
  => Pool Connection
  -> AuthorInfo
  -> m ()
addAuthor pool info = do
  newAuthor <- mkAuthor info
  withPool pool $ insertAuthor newAuthor

And if you want to later select an Author based on its AuthorId:

getAuthor
  :: MonadIO m
  => Pool Connection
  -> AuthorId
  -> m (Maybe Author)
getAuthor pool authorId =
  withPool pool $ selectOneByField [field| author_id |] (Only authorId)

This is the end of this tutorial. There are many more functions to discover that will help you write your queries. While you shouldn't have to explore the source code to gain understanding of how to use the library, feel free to navigate it to see how the underlying mechanisms work. :)

Next, you can consult our Guides section to see how to do error handling.

module ErrorsGuide where

import Control.Monad.Except (MonadError (..))
import Control.Monad.Trans
import Data.Text (Text)
import Database.PostgreSQL.Entity (Entity, selectById)
import Database.PostgreSQL.Entity.Types (GenericEntity)
import Database.PostgreSQL.Simple
import Database.PostgreSQL.Transact (DBT)
import GHC.Generics (Generic)

Error Handling

Error handling is a tricky subject, and most often you will have to provide translation layers between your different components to express how a request has failed and what is the relevant information to be reported.

For example, inserting twice the same entity with the same primary key will raise an error in the database engine that you have violated the uniqueness constraint of a primary key. This is of little use for consumers of the system, who simply need to be told that their chosen email address or username is already used.

Building a top-down error datatype can be a very good or very bad idea, and should sometimes be replaced with a more extensible mechanism like Haskell Exceptions (whose datatypes can be used outside of this mechanism, fortunately).

Let us consider a simple usecase, where we wish to express the following error modes:

• Entity was not found

• Entity is in a Bad State™

• Entity processing is running

data EntityError
  = EntityNotFound
  | EntityBadState
  | EntityProcessingIsRunning
  deriving (Eq, Show)

A MonadError stack can be used to handle errors with your data-type.

Here are the functions that we will be using:

This function allows great control over the way we report errors, and allows us to plug a MonadError for reporting.

withPool :: (MonadBaseControl IO m)
         => Pool Connection
         -> DBT m a
         -> m a

Those two functions show that we do not have to put a MonadError everywhere, and if a lower-level error happens, we can let it bubble up to create a higher-level error (like status code 500 in an http server).

data E = E
  { eId :: Text
  }
  deriving stock (Eq, Show, Generic)
  deriving
    (Entity)
    via (GenericEntity '[]) E
  deriving anyclass (FromRow)

insertEntity :: (MonadIO m)
             => E
             -> DBT m ()

getEntity
  :: (MonadError EntityError m, MonadIO m)
  => Int
  -> DBT m E
getEntity key = do
  result <- selectById (Only key)
  case result of
    Just e -> pure e
    Nothing -> lift $ throwError EntityNotFound

↑ Here, we convert a valid database response into a more precise business logic component.