Fast PostgreSQL driver for Haskell with a flexible mapping API

Hasql is a highly efficient PostgreSQL driver for Haskell with a typesafe yet flexible mapping API. It targets both the users, who need maximum control, and the users who face the typical tasks of DB-powered applications, providing them with higher-level APIs. Currently it is known to be the fastest driver in the Haskell ecosystem.

[!IMPORTANT] Hasql is one of the supported targets of the pGenie code generator, which empowers it with schema and query validation, and relieves you from boilerplate.

Status

Hasql is production-ready, actively maintained and the API is pretty stable. It’s used by many companies and most notably by the Postgrest project.

Ecosystem

Hasql is not just a single library, it is a granular ecosystem of composable libraries, each isolated to perform its own task and stay simple.

• “hasql” - the root of the ecosystem, which provides the essential abstraction over the PostgreSQL client functionality and mapping of values. Everything else revolves around that library.

• “hasql-th” - Template Haskell utilities, providing compile-time syntax checking and easy statement declaration.

• “hasql-transaction” - an STM-inspired composable abstraction over database transactions providing automated conflict resolution.

• “hasql-dynamic-statements” - a toolkit for generating statements based on the parameters.

• “hasql-cursor-query” - a declarative abstraction over cursors.

• “hasql-cursor-transaction” - a lower-level abstraction over cursors, which however allows to fetch from multiple cursors simultaneously. Generally though “hasql-cursor-query” is the recommended alternative.

• “hasql-pool” - a Hasql-specialized abstraction over the connection pool.

• “hasql-migration” - A port of postgresql-simple-migration for use with hasql.

• “hasql-listen-notify” / “hasql-notifications” - Support for PostgreSQL asynchronous notifications.

• “hasql-optparse-applicative” - “optparse-applicative” parsers for Hasql.

• “hasql-implicits” - implicit definitions, such as default codecs for standard types.

• “hasql-interpolate” - a QuasiQuoter that supports interpolating Haskell expressions into Hasql queries.

Benefits of being an ecosystem

• Simplicity. Each library in isolation provides a simple API, which is hopefully easier to comprehend.

• Flexibility and composability. The user picks and chooses the features, thus precisely matching the level of abstraction that he needs for his task.

• Much more stable and more descriptive semantic versioning. E.g., a change in the API of the “hasql-transaction” library won’t affect any of the other libraries and it gives the user a more precise information about which part of his application he needs to update to conform.

• Interchangeability and competition of the ecosystem components. E.g., not everyone will agree with the restrictive design decisions made in the “hasql-transaction” library. However those decisions are not imposed on the user, and instead of having endless debates about how to abstract over transactions, another extension library can simply be released, which will provide a different interpretation of what the abstraction over transactions should be.

• Horizontal scalability of the ecosystem. Instead of posting feature- or pull-requests, the users are encouraged to release their own small extension-libraries, with themselves becoming the copyright owners and taking on the maintenance responsibilities. Compare this model to the classical one, where some core-team is responsible for everything. One is scalable, the other is not.

Tutorials

Videos

There’s several videos on Hasql done as part of a nice intro-level series of live Haskell+Bazel coding by the “Ants Are Everywhere” YouTube channel:

• Coding Day 20: Switching from postgresql-simple to Hasql
• Coding Day 21: Refactoring the Hasql code

Articles

• Organization of Hasql code in a dedicated library

Short Example

Following is a complete application, which performs some arithmetic in Postgres using Hasql.

{-# LANGUAGE OverloadedStrings, QuasiQuotes #-}
import Prelude
import Data.Int
import Data.Functor.Contravariant
import Hasql.Session (Session)
import Hasql.Statement (Statement(..))
import qualified Hasql.Session as Session
import qualified Hasql.Decoders as Decoders
import qualified Hasql.Encoders as Encoders
import qualified Hasql.Connection as Connection


main :: IO ()
main = do
  Right connection <- Connection.acquire connectionSettings
  result <- Session.run (sumAndDivModSession 3 8 3) connection
  print result
  where
    connectionSettings = Connection.settings "localhost" 5432 "postgres" "" "postgres"


-- * Sessions
-- 
-- Session is an abstraction over the database connection and all possible errors.
-- It is used to execute statements.
-- It is composable and has a Monad instance.
-- 
-- It's recommended to define sessions in a dedicated 'Sessions'
-- submodule of your project.
-------------------------

sumAndDivModSession :: Int64 -> Int64 -> Int64 -> Session (Int64, Int64)
sumAndDivModSession a b c = do
  -- Get the sum of a and b
  sumOfAAndB <- Session.statement (a, b) sumStatement
  -- Divide the sum by c and get the modulo as well
  Session.statement (sumOfAAndB, c) divModStatement


-- * Statements
-- 
-- Statement is a definition of an individual SQL-statement,
-- accompanied by a specification of how to encode its parameters and
-- decode its result.
-- 
-- It's recommended to define statements in a dedicated 'Statements'
-- submodule of your project.
-------------------------

sumStatement :: Statement (Int64, Int64) Int64
sumStatement = Statement sql encoder decoder True where
  sql = "select $1 + $2"
  encoder =
    (fst >$< Encoders.param (Encoders.nonNullable Encoders.int8)) <>
    (snd >$< Encoders.param (Encoders.nonNullable Encoders.int8))
  decoder = Decoders.singleRow (Decoders.column (Decoders.nonNullable Decoders.int8))

divModStatement :: Statement (Int64, Int64) (Int64, Int64)
divModStatement = Statement sql encoder decoder True where
  sql = "select $1 / $2, $1 % $2"
  encoder =
    (fst >$< Encoders.param (Encoders.nonNullable Encoders.int8)) <>
    (snd >$< Encoders.param (Encoders.nonNullable Encoders.int8))
  decoder = Decoders.singleRow row where
    row =
      (,) <$>
      Decoders.column (Decoders.nonNullable Decoders.int8) <*>
      Decoders.column (Decoders.nonNullable Decoders.int8)

For the general use-case it is advised to prefer declaring statements using the “hasql-th” library, which validates the statements at compile-time and generates codecs automatically. So the above two statements could be implemented the following way:

import qualified Hasql.TH as TH -- from "hasql-th"

sumStatement :: Statement (Int64, Int64) Int64
sumStatement =
  [TH.singletonStatement|
    select ($1 :: int8 + $2 :: int8) :: int8
    |]

divModStatement :: Statement (Int64, Int64) (Int64, Int64)
divModStatement =
  [TH.singletonStatement|
    select
      (($1 :: int8) / ($2 :: int8)) :: int8,
      (($1 :: int8) % ($2 :: int8)) :: int8
    |]