DynamoDB layer for Haskell

This library intends to simplify working with DynamoDB AWS database. It uses Generics code (generics-sop) on top of your structures and just by adding a few instances allows you to easily generate AWS commands.

data Test = Test {
    category :: T.Text
  , user     :: T.Text
  , subject  :: T.Text
  , replies  :: Int
} deriving (Show)
-- Generate instances and category', user' etc. variables for queries/updates
mkTableDefs "migrate" (tableConfig "" (''Test, WithRange) [] [])

test :: IO ()
test = do
  lgr  <- newLogger Info stdout
  setEnv "AWS_ACCESS_KEY_ID" "XXXXXXXXXXXXXX"
  setEnv "AWS_SECRET_ACCESS_KEY" "XXXXXXXXXXXXXXfdjdsfjdsfjdskldfs+kl"
  env  <- newEnv Discover
  let dynamo = setEndpoint False "localhost" 8000 dynamoDB
  let newenv = env & configure dynamo & set envLogger lgr
  runResourceT $ runAWS newenv $ do
      migrate mempty Nothing -- Create tables, indices etc.
      --
      putItem (Test "news" "john" "test" 20)
      --
      item <- getItem Eventually tTest ("news", "john")
      liftIO $ print item
      --
      items <- scanCond tTest (replies' >. 15) 10
      liftIO $ print items

Features

• Global secondary indexes.
• Local secondary indexes.
• Tables with only hash keys as well as tables with combined hash and sort key.
• Sparse indexes (define the column as Maybe in a table, omit the Maybe in index definition).
• Automatically generate polymorphic lenses to access fields in main table and index records.
• Standard datatypes including Tagged and basic default instances for data types supporting Show/Read.
• New types can be added easily.
• High-level, easy-to-use API - hides intricacies of both DynamoDB and amazonka library.
• Type-safe conditions, including nested structures.
• Type-safe update actions.
• Template-haskell macro to easily create all relevant instances.
• 'Schema migration' - upon startup checks if the database schema matches the definition and, if possible, adjusts the database. If it is impossible, it fails.
• Automatic handling of invalid values (empty strings, empty sets). Automatic rewriting of queries when searching for these empty values.
• Compatible with GHC8 DuplicateRecordFields
• Customizable table and index names. Custom translation of field names to attribute names.
• AWS Dynamo streaming settings.
• Utilities to help with simulated joins or retriving original data from index.
• Both conduit and page-based API.

What is planned

• Support for automatic versioning of fields.

Limitations

• Projections are not supported. Using some generic programming on tuples it should be possible.
• You cannot compare attributes between themselves (i.e. currentAccount' >=. averageAccount'). I'm not sure this would be currently technically possible. Does anybody need it?

Handling of NULLs

DynamoDB does not accept empty strings/sets. It accepts NULL, but that is not acceptable in fields that are used for sparse indexing.

Empty string and empty set are represented by omitting the value.

• Just Nothing :: Maybe (Maybe a) will become Nothing on retrieval.
• [Just 1, Nothing, Just 3] will become [Just 1, Just 3] on retrieval.
• HashMap Text (Maybe a) is not a good idea; missing values will disappear.
• Maybe (Set a) will become Nothing on empty set
• Don't try to use inequality comparisons (>., <.) on empty strings.
• If you use maybeCol' == Nothing, it gets internally replaced by attr_missing(maybeCol), so it will behave as expected. The same with empty String or Set. Keep that in mind when traversing nested structures.
• In case of schema change, Maybe columns are considered Nothing.
• In case of schema change, String columns are decoded as empty strings, Set columns as empty sets, [a] columns as empty lists.
• Condition for == "", == [] etc. is automatically enhanced to account for non-existent attributes (i.e. after schema change).
• Empty list/empty hashmap is represented as empty list/hashmap; however it is allowed to be decoded even when the attribute is missing in order to allow better schema migrations.