haxl

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

Version on this page:0.5.1.0
LTS Haskell 12.24:2.0.1.1
Stackage Nightly 2018-12-18:2.0.1.1
Latest on Hackage:2.0.1.1

See all snapshots haxl appears in

Haxl Logo

Haxl

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

Changes in version 2.0.1.1

  • Support for GHC 8.6.1
  • Bugfixes

Changes in version 2.0.1.0

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

Changes in version 2.0.0.0

  • 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 0.5.1.0

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

Changes in version 0.5.0.0

  • Rename ‘Show1’ to ‘ShowP’ (#62)

Changes in version 0.3.0.0

  • 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