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81 lines
1.8 KiB
ReStructuredText
81 lines
1.8 KiB
ReStructuredText
Schema
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======
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A Schema is created by supplying the root types of each type of operation, query and mutation (optional).
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A schema definition is then supplied to the validator and executor.
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.. code:: python
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my_schema = Schema(
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query=MyRootQuery,
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mutation=MyRootMutation,
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)
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Types
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-----
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There are some cases where the schema cannot access all of the types that we plan to have.
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For example, when a field returns an ``Interface``, the schema doesn't know about any of the
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implementations.
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In this case, we need to use the ``types`` argument when creating the Schema.
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.. code:: python
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my_schema = Schema(
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query=MyRootQuery,
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types=[SomeExtraObjectType, ]
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)
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Querying
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--------
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To query a schema, call the ``execute`` method on it.
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.. code:: python
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my_schema.execute('{ lastName }')
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Auto CamelCase field names
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--------------------------
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By default all field and argument names (that are not
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explicitly set with the ``name`` arg) will be converted from
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``snake_case`` to ``camelCase`` (as the API is usually being consumed by a js/mobile client)
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For example with the ObjectType
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.. code:: python
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class Person(graphene.ObjectType):
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last_name = graphene.String()
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other_name = graphene.String(name='_other_Name')
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the ``last_name`` field name is converted to ``lastName``.
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In case you don't want to apply this transformation, provide a ``name`` argument to the field constructor.
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``other_name`` converts to ``_other_Name`` (without further transformations).
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Your query should look like
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.. code::
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{
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lastName
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_other_Name
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}
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To disable this behavior, set the ``auto_camelcase`` to ``False`` upon schema instantiation.
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.. code:: python
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my_schema = Schema(
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query=MyRootQuery,
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auto_camelcase=False,
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)
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