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GraphQL types can refer to each other in a circular way. The PDV framework used to use values of type `Unique` to recognize two fragments of GraphQL schema as being the same instance. Internally, this is based on `Data.Unique` from the `base` package, which simply increases a counter on every creation of a `Unique` object. **NB**: The `Unique` values are _not_ used for knot tying the schema combinators themselves (i.e. `Parser`s). The knot tying for `Parser`s is purely based on keys provided to `memoizeOn`. The `Unique` values are _only_ used to recognize two pieces of GraphQL _schema_ as being identical. Originally, the idea was that this would help us with a perfectly correct identification of GraphQL types. But this fully correct equality checking of GraphQL types was never implemented, and does not seem to be necessary to prevent bugs. Specifically, these `Unique` values are stored as part of `data Definition a`, which specifies a part of our internal abstract syntax tree for the GraphQL types that we expose. The `Unique` values get initialized by the `SchemaT` effect. In #2894 and #2895, we are experimenting with how (parts of) the GraphQL types can be hidden behind certain permission predicates. This would allow a single GraphQL schema in memory to serve all roles, implementing #2711. The permission predicates get evaluated at query parsing time when we know what role is doing a certain request, thus outputting the correct GraphQL types for that role. If the approach of #2895 is followed, then the `Definition` objects, and thus the `Unique` values, would be hidden behind the permission predicates. Since the permission predicates are evaluated only after the schema is already supposed to be built, this means that the permission predicates would prevent us from initializing the `Unique` values, rendering them useless. The simplest remedy to this is to remove our usage of `Unique` altogether from the GraphQL schema and schema combinators. It doesn't serve a functional purpose, doesn't prevent bugs, and requires extra bookkeeping. PR-URL: https://github.com/hasura/graphql-engine-mono/pull/2980 GitOrigin-RevId: 50d3f9e0b9fbf578ac49c8fc773ba64a94b1f43d
152 lines
6.1 KiB
Haskell
152 lines
6.1 KiB
Haskell
-- | Classes for monads used during schema construction and query parsing.
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module Hasura.GraphQL.Parser.Class
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( MonadParse (..),
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parseError,
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module Hasura.GraphQL.Parser.Class,
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)
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where
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import Data.Has
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import Data.HashMap.Strict qualified as Map
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import Data.Text.Extended
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import GHC.Stack (HasCallStack)
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import Hasura.Base.Error
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import Hasura.GraphQL.Parser.Class.Parse
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import Hasura.GraphQL.Parser.Internal.Types
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import Hasura.Prelude
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import Hasura.RQL.Types.Backend
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import Hasura.RQL.Types.Common
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import Hasura.RQL.Types.Source
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import Hasura.RQL.Types.Table
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import Hasura.Session (RoleName)
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import Language.Haskell.TH qualified as TH
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import Type.Reflection (Typeable)
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{- Note [Tying the knot]
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~~~~~~~~~~~~~~~~~~~~~~~~
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GraphQL type definitions can be mutually recursive, and indeed, they quite often
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are! For example, two tables that reference one another will be represented by
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types such as the following:
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type author {
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id: Int!
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name: String!
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articles: [article!]!
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}
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type article {
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id: Int!
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title: String!
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content: String!
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author: author!
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}
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This doesn’t cause any trouble if the schema is represented by a mapping from
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type names to type definitions, but the Parser abstraction is all about avoiding
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that kind of indirection to improve type safety — parsers refer to their
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sub-parsers directly. This presents two problems during schema generation:
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1. Schema generation needs to terminate in finite time, so we need to ensure
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we don’t try to eagerly construct an infinitely-large schema due to the
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mutually-recursive structure.
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2. To serve introspection queries, we do eventually need to construct a
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mapping from names to types (a TypeMap), so we need to be able to
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recursively walk the entire schema in finite time.
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Solving point number 1 could be done with either laziness or sharing, but
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neither of those are enough to solve point number 2, which requires /observable/
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sharing. We need to construct a Parser graph that contains enough information to
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detect cycles during traversal.
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It may seem appealing to just use type names to detect cycles, which would allow
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us to get away with using laziness rather than true sharing. Unfortunately, that
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leads to two further problems:
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* It’s possible to end up with two different types with the same name, which
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is an error and should be reported as such. Using names to break cycles
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prevents us from doing that, since we have no way to check that two types
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with the same name are actually the same.
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* Some Parser constructors can fail — the `column` parser checks that the type
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name is a valid GraphQL name, for example. This extra validation means lazy
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schema construction isn’t viable, since we need to eagerly build the schema
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to ensure all the validation checks hold.
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So we’re forced to use sharing. But how do we do it? Somehow, we have to /tie
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the knot/ — we have to build a cyclic data structure — and some of the cycles
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may be quite large. Doing all this knot-tying by hand would be incredibly
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tricky, and it would require a lot of inversion of control to thread the shared
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parsers around.
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To avoid contorting the program, we instead implement a form of memoization. The
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MonadSchema class provides a mechanism to memoize a parser constructor function,
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which allows us to get sharing mostly for free. The memoization strategy also
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annotates cached parsers with a Unique that can be used to break cycles while
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traversing the graph, so we get observable sharing as well. -}
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-- | A class that provides functionality used when building the GraphQL schema,
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-- i.e. constructing the 'Parser' graph.
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class (Monad m, MonadParse n) => MonadSchema n m | m -> n where
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-- | Memoizes a parser constructor function for the extent of a single schema
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-- construction process. This is mostly useful for recursive parsers;
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-- see Note [Tying the knot] for more details.
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--
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-- The generality of the type here allows us to use this with multiple concrete
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-- parser types:
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--
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-- @
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-- 'memoizeOn' :: 'MonadSchema' n m => 'TH.Name' -> a -> m (Parser n b) -> m (Parser n b)
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-- 'memoizeOn' :: 'MonadSchema' n m => 'TH.Name' -> a -> m (FieldParser n b) -> m (FieldParser n b)
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-- @
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memoizeOn ::
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forall p a b.
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(HasCallStack, Ord a, Typeable p, Typeable a, Typeable b) =>
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-- | A unique name used to identify the function being memoized. There isn’t
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-- really any metaprogramming going on here, we just use a Template Haskell
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-- 'TH.Name' as a convenient source for a static, unique identifier.
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TH.Name ->
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-- | The value to use as the memoization key. It’s the caller’s
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-- responsibility to ensure multiple calls to the same function don’t use
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-- the same key.
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a ->
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m (p n b) ->
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m (p n b)
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type MonadRole r m = (MonadReader r m, Has RoleName r)
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-- | Gets the current role the schema is being built for.
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askRoleName ::
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MonadRole r m =>
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m RoleName
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askRoleName = asks getter
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type MonadTableInfo r m = (MonadReader r m, Has SourceCache r, MonadError QErr m)
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-- | Looks up table information for the given table name. This function
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-- should never fail, since the schema cache construction process is
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-- supposed to ensure all dependencies are resolved.
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askTableInfo ::
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forall b r m.
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(Backend b, MonadTableInfo r m) =>
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SourceName ->
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TableName b ->
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m (TableInfo b)
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askTableInfo sourceName tableName = do
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tableInfo <- asks $ getTableInfo . getter
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-- This should never fail, since the schema cache construction process is
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-- supposed to ensure that all dependencies are resolved.
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tableInfo `onNothing` throw500 ("askTableInfo: no info for table " <> dquote tableName <> " in source " <> dquote sourceName)
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where
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getTableInfo :: SourceCache -> Maybe (TableInfo b)
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getTableInfo = Map.lookup tableName <=< unsafeSourceTables <=< Map.lookup sourceName
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-- | A wrapper around 'memoizeOn' that memoizes a function by using its argument
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-- as the key.
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memoize ::
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(HasCallStack, MonadSchema n m, Ord a, Typeable a, Typeable b, Typeable k) =>
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TH.Name ->
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(a -> m (Parser k n b)) ->
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(a -> m (Parser k n b))
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memoize name f a = memoizeOn name a (f a)
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