A Haskell library for efficient, concurrent, and concise data access. https://github.com/facebook/Haxl

Version on this page:
LTS Haskell 12.22:
Stackage Nightly 2018-12-10:
Latest on Hackage:

See all snapshots haxl appears in

BSD3 licensed by Facebook, Inc.
Maintained by The Haxl Team

Module documentation for

There are no documented modules for this package.

Haxl Logo


Haxl is a Haskell library that simplifies access to remote data, such as databases or web-based services. Haxl can automatically

  • batch multiple requests to the same data source,
  • request data from multiple data sources concurrently,
  • cache previous requests,
  • memoize computations.

Having all this handled for you behind the scenes means that your data-fetching code can be much cleaner and clearer than it would otherwise be if it had to worry about optimizing data-fetching. We’ll give some examples of how this works in the pages linked below.

There are two Haskell packages here:

To use Haxl in your own application, you will likely need to build one or more data sources: the thin layer between Haxl and the data that you want to fetch, be it a database, a web API, a cloud service, or whatever.

There is a generic datasource in “Haxl.DataSource.ConcurrentIO” that can be used for performing arbitrary IO operations concurrently, given a bit of boilerplate to define the IO operations you want to perform.

The haxl-facebook package shows how we might build a Haxl data source based on the existing fb package for talking to the Facebook Graph API.

Where to go next?

Build Status


Changes in version

  • Support for GHC 8.6.1
  • Bugfixes

Changes in version

  • Exported MemoVar from Haxl.Core.Memo
  • Updated the facebook example
  • Fixed some links in the documentation
  • Bump some version bounds

Changes in version

  • Completely rewritten internals to support arbitrarily overlapping I/O and computation. Haxl no longer runs batches of I/O in “rounds”, waiting for all the I/O to complete before resuming the computation. In Haxl 2, we can spawn I/O that returns results in the background and computation fragments are resumed when the values they depend on are available. See tests/FullyAsyncTest.hs for an example.

  • A new PerformFetch constructor supports the new concurrency features: BackgroundFetch. The data source is expected to call putResult in the background on each BlockedFetch when its result is ready.

  • There is a generic DataSource implementation in Haxl.DataSource.ConcurrentIO for performing each I/O operation in a separate thread.

  • Lots of cleanup and refactoring of the APIs.

  • License changed from BSD+PATENTS to plain BSD3.

Changes in version

  • ‘pAnd’ and ‘pOr’ were added
  • ‘asyncFetchAcquireRelease’ was added
  • ‘cacheResultWithShow’ was exposed
  • GHC 8.2.1 compatibility

Changes in version

  • Rename ‘Show1’ to ‘ShowP’ (#62)

Changes in version

  • Some performance improvements, including avoiding quadratic slowdown with left-associated binds.

  • Documentation cleanup; Haxl.Core is the single entry point for the core and engine docs.

  • (>>) is now defined to be (*>), and therefore no longer forces sequencing. This can have surprising consequences if you are using Haxl with side-effecting data sources, so watch out!

  • New function withEnv, for running a sub-computation in a local Env

  • Add a higher-level memoization API, see ‘memo’

  • Show is no longer required for keys in cachedComputation

  • Exceptions now have Eq instances

comments powered byDisqus