0.8.0.2

• Fix ToJSON instance for 15-tuples (see #223).

0.8.0.1

• Support time-1.5.

0.8.0.0

• Add ToJSON and FromJSON instances for tuples of up to 15 elements.

0.7.1.0

• Major compiler and library compatibility changes: we have dropped support for GHC older than 7.4, text older than 1.1, and bytestring older than 0.10.4.0. Supporting the older versions had become increasingly difficult, to the point where it was no longer worth it.

0.7.0.0

• The performance of encoding to and decoding of bytestrings have both improved by up to 2x, while also using less memory.

• New dependency: the scientific package lets us parse floating point numbers more quickly and accurately.

• eitherDecode, decodeStrictWith: fixed bugs.

• Added FromJSON and ToJSON instances for Tree and Scientific.

• Fixed the ToJSON instances for UTCTime and ZonedTime.

0.6 series

• Much improved documentation.

• Angle brackets are now escaped in JSON strings, to help avoid XSS attacks.

• Fixed up handling of nullary constructors when using generic encoding.

• Added ToJSON/FromJSON instances for:

  • The Fixed class
  • ISO-8601 dates: UTCTime, ZonedTime, and TimeZone

• Added accessor functions for inspecting Values.

• Added eitherDecode function that returns an error message if decoding fails.

0.5 to 0.6

• This release introduces a slightly obscure, but backwards-incompatible, change.

  In the generic APIs of versions 0.4 and 0.5, fields whose names began with a “_” character would have this character removed. This no longer occurs, as it was both buggy and surprising (https://github.com/bos/aeson/issues/53).

• Fixed a bug in generic decoding of nullary constructors (https://github.com/bos/aeson/issues/62).

0.4 to 0.5

• When used with the UTF-8 encoding performance improvements introduced in version 0.11.1.12 of the text package, this release improves aeson’s JSON encoding performance by 33% relative to aeson 0.4.

  As part of achieving this improvement, an API change was necessary. The fromValue function in the Data.Aeson.Encode module now uses the text package’s Builder type instead of the blaze-builder package’s Builder type.

0.3 to 0.4

• The new decode function complements the longstanding encode function, and makes the API simpler.

• New examples make it easier to learn to use the package (https://github.com/bos/aeson/tree/master/examples).

• Generics support

  aeson’s support for data-type generic programming makes it possible to use JSON encodings of most data types without writing any boilerplate instances.

  Thanks to Bas Van Dijk, aeson now supports the two major schemes for doing datatype-generic programming:

  • the modern mechanism, built into GHC itself (http://www.haskell.org/ghc/docs/latest/html/users_guide/generic-programming.html)

  • the older mechanism, based on SYB (aka “scrap your boilerplate”)

  The modern GHC-based generic mechanism is fast and terse: in fact, its performance is generally comparable in performance to hand-written and TH-derived ToJSON and FromJSON instances. To see how to use GHC generics, refer to examples/Generic.hs.

  The SYB-based generics support lives in Data.Aeson.Generic and is provided mainly for users of GHC older than 7.2. SYB is far slower (by about 10x) than the more modern generic mechanism. To see how to use SYB generics, refer to examples/GenericSYB.hs.

• We switched the intermediate representation of JSON objects from Data.Map to Data.HashMap which has improved type conversion performance.

• Instances of ToJSON and FromJSON for tuples are between 45% and 70% faster than in 0.3.

• Evaluation control

  This version of aeson makes explicit the decoupling between identifying an element of a JSON document and converting it to Haskell. See the Data.Aeson.Parser documentation for details.

  The normal aeson decode function performs identification strictly, but defers conversion until needed. This can result in improved performance (e.g. if the results of some conversions are never needed), but at a cost in increased memory consumption.

  The new decode’ function performs identification and conversion immediately. This incurs an up-front cost in CPU cycles, but reduces reduce memory consumption.