-- | Classes for monads used during schema construction and query parsing. module Hasura.GraphQL.Parser.Class ( MonadParse (..), parseError, module Hasura.GraphQL.Parser.Class, ) where import Data.Has import Data.HashMap.Strict qualified as Map import Data.Text.Extended import GHC.Stack (HasCallStack) import Hasura.Base.Error import Hasura.GraphQL.Parser.Class.Parse import Hasura.GraphQL.Parser.Internal.Types import Hasura.Prelude import Hasura.RQL.Types.Backend import Hasura.RQL.Types.Common import Hasura.RQL.Types.Source import Hasura.RQL.Types.Table import Hasura.Session (RoleName) import Language.Haskell.TH qualified as TH import Type.Reflection (Typeable) {- Note [Tying the knot] ~~~~~~~~~~~~~~~~~~~~~~~~ GraphQL type definitions can be mutually recursive, and indeed, they quite often are! For example, two tables that reference one another will be represented by types such as the following: type author { id: Int! name: String! articles: [article!]! } type article { id: Int! title: String! content: String! author: author! } This doesn’t cause any trouble if the schema is represented by a mapping from type names to type definitions, but the Parser abstraction is all about avoiding that kind of indirection to improve type safety — parsers refer to their sub-parsers directly. This presents two problems during schema generation: 1. Schema generation needs to terminate in finite time, so we need to ensure we don’t try to eagerly construct an infinitely-large schema due to the mutually-recursive structure. 2. To serve introspection queries, we do eventually need to construct a mapping from names to types (a TypeMap), so we need to be able to recursively walk the entire schema in finite time. Solving point number 1 could be done with either laziness or sharing, but neither of those are enough to solve point number 2, which requires /observable/ sharing. We need to construct a Parser graph that contains enough information to detect cycles during traversal. It may seem appealing to just use type names to detect cycles, which would allow us to get away with using laziness rather than true sharing. Unfortunately, that leads to two further problems: * It’s possible to end up with two different types with the same name, which is an error and should be reported as such. Using names to break cycles prevents us from doing that, since we have no way to check that two types with the same name are actually the same. * Some Parser constructors can fail — the `column` parser checks that the type name is a valid GraphQL name, for example. This extra validation means lazy schema construction isn’t viable, since we need to eagerly build the schema to ensure all the validation checks hold. So we’re forced to use sharing. But how do we do it? Somehow, we have to /tie the knot/ — we have to build a cyclic data structure — and some of the cycles may be quite large. Doing all this knot-tying by hand would be incredibly tricky, and it would require a lot of inversion of control to thread the shared parsers around. To avoid contorting the program, we instead implement a form of memoization. The MonadSchema class provides a mechanism to memoize a parser constructor function, which allows us to get sharing mostly for free. The memoization strategy also annotates cached parsers with a Unique that can be used to break cycles while traversing the graph, so we get observable sharing as well. -} -- | A class that provides functionality used when building the GraphQL schema, -- i.e. constructing the 'Parser' graph. class (Monad m, MonadParse n) => MonadSchema n m | m -> n where -- | Memoizes a parser constructor function for the extent of a single schema -- construction process. This is mostly useful for recursive parsers; -- see Note [Tying the knot] for more details. -- -- The generality of the type here allows us to use this with multiple concrete -- parser types: -- -- @ -- 'memoizeOn' :: 'MonadSchema' n m => 'TH.Name' -> a -> m (Parser n b) -> m (Parser n b) -- 'memoizeOn' :: 'MonadSchema' n m => 'TH.Name' -> a -> m (FieldParser n b) -> m (FieldParser n b) -- @ memoizeOn :: forall p a b. (HasCallStack, Ord a, Typeable p, Typeable a, Typeable b) => -- | A unique name used to identify the function being memoized. There isn’t -- really any metaprogramming going on here, we just use a Template Haskell -- 'TH.Name' as a convenient source for a static, unique identifier. TH.Name -> -- | The value to use as the memoization key. It’s the caller’s -- responsibility to ensure multiple calls to the same function don’t use -- the same key. a -> m (p n b) -> m (p n b) type MonadRole r m = (MonadReader r m, Has RoleName r) -- | Gets the current role the schema is being built for. askRoleName :: MonadRole r m => m RoleName askRoleName = asks getter type MonadTableInfo r m = (MonadReader r m, Has SourceCache r, MonadError QErr m) -- | Looks up table information for the given table name. This function -- should never fail, since the schema cache construction process is -- supposed to ensure all dependencies are resolved. askTableInfo :: forall b r m. (Backend b, MonadTableInfo r m) => SourceName -> TableName b -> m (TableInfo b) askTableInfo sourceName tableName = do tableInfo <- asks $ getTableInfo . getter -- This should never fail, since the schema cache construction process is -- supposed to ensure that all dependencies are resolved. tableInfo `onNothing` throw500 ("askTableInfo: no info for table " <> dquote tableName <> " in source " <> dquote sourceName) where getTableInfo :: SourceCache -> Maybe (TableInfo b) getTableInfo = Map.lookup tableName <=< unsafeSourceTables <=< Map.lookup sourceName -- | A wrapper around 'memoizeOn' that memoizes a function by using its argument -- as the key. memoize :: (HasCallStack, MonadSchema n m, Ord a, Typeable a, Typeable b, Typeable k) => TH.Name -> (a -> m (Parser k n b)) -> (a -> m (Parser k n b)) memoize name f a = memoizeOn name a (f a)