Metadata-Version: 1.1
Name: graphjoiner
Version: 0.4.0b35
Summary: Implementing GraphQL with joins
Home-page: http://github.com/healx/python-graphjoiner
Author: Michael Williamson
Author-email: mike@zwobble.org
License: UNKNOWN
Description: GraphJoiner: Implementing GraphQL with joins
        ============================================
        
        In the reference GraphQL implementation, resolve functions describe how to
        fulfil some part of the requested data for each instance of an object.
        If implemented naively with a SQL backend, this results in the N+1 problem.
        For instance, given the query:
        
        ::
        
            {
                books(genre: "comedy") {
                    title
                    author {
                        name
                    }
                }
            }
        
        A naive GraphQL implementation would issue one SQL query to get the list of all
        books in the comedy genre, and then N queries to get the author of each book
        (where N is the number of books returned by the first query).
        
        There are various solutions proposed to this problem: GraphJoiner suggests that
        using joins is a natural fit for many use cases. For this specific case, we only
        need to run two queries: one to find the list of all books in the comedy genre,
        and one to get the authors of books in the comedy genre.
        
        Installation
        ------------
        
        ::
        
            pip install graphjoiner
        
        Example
        -------
        
        Let's say we have some models defined by SQLAlchemy. A book has an ID, a title,
        a genre and an author ID. An author has an ID and a name.
        
        .. code-block:: python
        
                from sqlalchemy import Column, Integer, Unicode, ForeignKey
                from sqlalchemy.ext.declarative import declarative_base
        
                Base = declarative_base()
        
                class AuthorRecord(Base):
                    __tablename__ = "author"
        
                    id = Column(Integer, primary_key=True)
                    name = Column(Unicode, nullable=False)
        
                class BookRecord(Base):
                    __tablename__ = "book"
        
                    id = Column(Integer, primary_key=True)
                    title = Column(Unicode, nullable=False)
                    genre = Column(Unicode, nullable=False)
                    author_id = Column(Integer, ForeignKey(AuthorRecord.id))
        
        We then define object types for the root, books and authors:
        
        .. code-block:: python
        
            from graphjoiner.declarative import RootType, single, many, select, String
            from graphjoiner.declarative.sqlalchemy import SqlAlchemyObjectType, column_field, sql_join
        
            class Author(SqlAlchemyObjectType):
                __model__ = AuthorRecord
        
                id = column_field(AuthorRecord.id)
                name = column_field(AuthorRecord.name)
        
            class Book(SqlAlchemyObjectType):
                __model__ = BookRecord
        
                id = column_field(BookRecord.id)
                title = column_field(BookRecord.title)
                genre = column_field(BookRecord.genre)
                author_id = column_field(BookRecord.author_id)
                author = single(lambda: sql_join(Author))
        
            class Root(RootType):
                books = many(lambda: select(Book))
        
                @books.arg("genre", String)
                def books_arg_genre(query, genre):
                    return query.filter(BookRecord.genre == genre)
        
        We create an ``execute()`` function by calling ``executor()`` with our ``Root``:
        
        .. code-block:: python
        
            from graphjoiner.declarative import executor
        
            execute = executor(Root)
        
        ``execute`` can then be used to execute queries:
        
        .. code-block:: python
        
            query = """
                {
                    books(genre: "comedy") {
                        title
                        author {
                            name
                        }
                    }
                }
            """
        
            class Context(object):
                def __init__(self, session):
                    self.session = session
        
            result = execute(root, query, context=Context(session))
        
        
        Where ``result.data`` is:
        
        ::
        
            {
                "books": [
                    {
                        "title": "Leave It to Psmith",
                        "author": {
                            "name": "PG Wodehouse"
                        }
                    },
                    {
                        "title": "Right Ho, Jeeves",
                        "author": {
                            "name": "PG Wodehouse"
                        }
                    },
                    {
                        "title": "Catch-22",
                        "author": {
                            "name": "Joseph Heller"
                        }
                    },
                ]
            }
        
        Let's break things down a little, starting with the definition of ``Author``:
        
        .. code-block:: python
        
            class Author(SqlAlchemyObjectType):
                __model__ = AuthorRecord
        
                id = column_field(AuthorRecord.id)
                name = column_field(AuthorRecord.name)
        
        When defining object types that represent SQLAlchemy models,
        we can inherit from ``SqlAlchemyObjectType``,
        with the ``__model__`` attribute set to the appropriate model.
        
        Fields that can be fetched without further joining can be defined using ``column_field()``.
        GraphJoiner will automatically infer the GraphQL type of the field based on the SQL type of the column.
        
        Next is the definition of ``Book``:
        
        .. code-block:: python
        
            class Book(SqlAlchemyObjectType):
                __model__ = BookRecord
        
                id = column_field(BookRecord.id)
                title = column_field(BookRecord.title)
                genre = column_field(BookRecord.genre)
                author_id = column_field(BookRecord.author_id)
                author = single(lambda: sql_join(Author))
        
        As before, we inherit from ``SqlAlchemyObjectType``,
        set ``__model__`` to the appropriate class,
        and define a number of fields that correspond to columns.
        
        We also define an ``author`` field that allows a book to be joined to an author.
        GraphJoiner will automatically inspect ``BookRecord`` and ``AuthorRecord``
        and use the foreign keys to determine how they should be joined together.
        To override this behaviour, you can pass in an explicit ``join`` argument:
        
        .. code-block:: python
        
            author = single(lambda: sql_join(Author, join={Book.author_id: Author.id}))
        
        This explicitly tells GraphJoiner that authors can be joined to books
        by equality between the fields ``Book.author_id`` and ``Author.id``.
        When defining relationships such as this,
        we call ``single()`` with a lambda to defer evaluation until all of the types and fields have been defined.
        
        Finally, we can create a root object:
        
        .. code-block:: python
        
            class Root(RootType):
                books = many(lambda: select(Book))
        
                @books.arg("genre", String)
                def books_arg_genre(query, genre):
                    return query.filter(BookRecord.genre == genre)
        
        The root has only one field, ``books``, which we define using ``many()``.
        Using ``select`` tells GraphJoiner to select all of the books in the database,
        rather than trying to perform a join.
        
        Using ``books.arg()`` adds an optional argument to the field.
        
        For completeness, we can tweak the definition of ``Author`` so
        we can request the books by an author:
        
        .. code-block:: python
        
            class Author(SqlAlchemyObjectType):
                __model__ = AuthorRecord
        
                id = column_field(AuthorRecord.id)
                name = column_field(AuthorRecord.name)
                books = many(lambda: sql_join(Book))
        
        
        API
        ---
        
        ``graphjoiner.declarative``
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        ObjectType
        ^^^^^^^^^^
        
        Represents a GraphQL object type.
        Fields can be declared as attributes.
        For instance, to create an object type called ``User`` with a ``name`` and ``emailAddress`` field:
        
        .. code-block:: python
        
            from graphqjoiner import NonNull, ObjectType, String
        
            class User(ObjectType):
                name = NonNull(String)
                email_address = NonNull(String)
        
        Field names are inferred from attribute names,
        converting from snake case to camel case.
        In the example above, the attribute name ``email_address`` is converted to the field name ``emailAddress``.
        
        To create a type that can be joined to,
        implement ``__fetch_immediates__`` as a static or class method.
        
        * ``__fetch_immediates__(selections, query, context)``:
          fetch the values for the selected fields that aren't defined as relationships.
        
          Receives the arguments:
        
          * ``selections``: an iterable of the selections,
            where each selection has the attributes:
        
            * ``field``: the field being selected
            * ``args``: the arguments for the selection
            * ``selections``: the sub-selections of that selection
        
          * ``query``: the query for the records to select.
        
          * ``context``: the context as passed into the executor
        
          Should return a list of tuples,
          where each tuple contains the value for each selection in the same order.
        
        Implementing ``__select_all__`` allows the object to be used with ``select()``.
        ``__select_all__()`` takes no arguments,
        and should return a query that represents all instances of the object.
        
        For instance,
        to implement a base type for static data:
        
        .. code-block:: python
        
            import collections
        
            from graphjoiner.declarative import ObjectType, RootType, select, single, String
        
            class StaticDataObjectType(ObjectType):
                @classmethod
                def __select_all__(cls):
                    return cls.__records__
        
                @classmethod
                def __fetch_immediates__(cls, selections, records, context):
                    return [
                        tuple(
                            getattr(record, selection.field.attr_name)
                            for selection in selections
                        )
                        for record in records
                    ]
        
            AuthorRecord = collections.namedtuple("AuthorRecord", ["name"])
        
            class Author(StaticDataObjectType):
                __records__ = [AuthorRecord("PG Wodehouse")]
        
                name = field(type=String)
        
            class Root(RootType):
                author = single(lambda: select(Author))
        
        
        Relationships
        ^^^^^^^^^^^^^
        
        Use ``single``, ``single_or_null``, ``first_or_null`` and ``many`` to create fields that are joined to other types.
        For instance, to select all books from the root type:
        
        .. code-block:: python
        
            from graphjoiner.declarative import many, RootType, select
        
            class Root(RootType):
                ...
                books = many(lambda: select(Book))
        
        Each relationship function accepts a joiner:
        a value that describes how to join the left type to the right type.
        The joiner is always wrapped in a lambda to defer evaluation until all types are defined.
        In this case, the left type is ``Root``, the right type is ``Book``,
        and the joiner is ``select(Book)``.
        Calling ``select()`` with just the right type tells GraphJoiner to select all values,
        in this case all books.
        
        All joiners accept a ``filter`` argument that allow the query to be tweaked.
        For instance,
        supposing books are selected using SQLAlchemy queries,
        and we want the ``books`` field to be sorted by title:
        
        .. code-block:: python
        
            from graphjoiner.declarative import many, RootType, select
            from graphjoiner.declarative.sqlalchemy import SqlAlchemyObjectType
        
            class Book(SqlAlchemyObjectType):
                __model__ = BookRecord
        
                ...
        
                @staticmethod
                def order_by_title(query):
                    # query is an instance of sqlalchemy.orm.Query
                    return query.order_by(BookRecord.title)
        
            class Root(RootType):
                ...
        
                books = many(lambda: select(
                    Book,
                    filter=Book.order_by_title,
                ))
        
        Arguments can be added using the ``arg()`` decorator.
        If the GraphQL selection for that field includes a value for the argument,
        the query is updated using the decorated function.
        For instance, to allow books to be filtered by title:
        
        .. code-block:: python
        
            from graphjoiner.declarative import many, RootType, select, String
            from graphjoiner.declarative.sqlalchemy import SqlAlchemyObjectType
        
            class Book(SqlAlchemyObjectType):
                __model__ = BookRecord
        
                ...
        
                @staticmethod
                def filter_by_title(query, title):
                    # query is an instance of sqlalchemy.orm.Query
                    return query.filter(BookRecord.title == title)
        
            class Root(RootType):
                ...
        
                books = many(lambda: select(Book))
                @books.arg("title", String)
                def books_arg_title(query, title):
                    return Book.filter_by_title(query, title)
        
        
        ``select(target, join_query=None, join_fields=None)``
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
        
        Creates a joiner to the target type.
        When given no additional arguments,
        it will select all values of the target type using ``target.__select_all__()``.
        All left values are joined onto all right values
        i.e. the join is the cartesian product.
        Unless the left type is the root type,
        this probably isn't what you want.
        
        Set ``join_fields`` to describe which fields to use to join together the left and right types.
        Each item in the dictionary should map a field from the left type to a field from the right type.
        For instance, supposing each author has a unique ID,
        and each book has an author ID:
        
        .. code-block:: python
        
            from graphjoiner.declarative import field, Int, ObjectType, select, single
        
            class Book(ObjectType):
                ...
                author_id = field(type=Int)
                author = single(lambda: select(
                    Author,
                    join_fields={Book.author_id: Author.id},
                ))
        
        Set ``join_query`` to describe how to join the left query and the right query.
        This should be a function that accepts a left query and a right query,
        and returns a right query filtered to the values relevant to the left query.
        This avoids the cost of fetching all values of the right type only to discard those that don't join onto any left values.
        For instance, when using the ``sqlalchemy`` module,
        we'd like to fetch the authors for just the requested book,
        rather than all available authors:
        
        .. code-block:: python
        
            from graphjoiner.declarative import select, single
            from graphjoiner.declarative.sqlalchemy import column_field, SqlAlchemyObjectType
        
            class Book(SqlAlchemyObjectType):
                ...
                author_id = column_field(BookRecord.author_id)
        
                def join_authors(book_query, author_query):
                    author_ids = book_query \
                        .add_columns(BookRecord.author_id) \
                        .subquery()
        
                    return author_query.join(
                        author_ids,
                        author_ids.c.author_id == AuthorRecord.id,
                    )
        
                author = single(lambda: select(
                    Author,
                    join_query=join_authors,
                    join_fields={Book.author_id: Author.id},
                ))
        
        In this particular case, using ``sql_join()`` would remove much of the boilerplate:
        
        .. code-block:: python
        
            from graphjoiner.declarative import single
            from graphjoiner.declarative.sqlalchemy import column_field, sql_join, SqlAlchemyObjectType
        
            class Book(SqlAlchemyObjectType):
                ...
                author_id = column_field(BookRecord.author_id)
                author = single(lambda: sql_join(Author, {Book.author_id: Author.id}))
        
        ``extract(field, sub_field)``
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
        
        Create a new field by extracting ``sub_field`` from ``field``.
        The arguments for the new field are the same as the arguments for ``field``.
        
        For instance,
        supposing we have a field ``books`` on the root type,
        each book has a ``title`` field,
        and we want to add a ``bookTitles`` field to the root type:
        
        .. code-block:: python
        
            from graphjoiner.declarative import extract, many, RootType, select
        
            class Root(RootType):
                books = many(lambda: select(Book))
                book_titles = extract(books, lambda: Book.title)
        
        If we want to just have the ``bookTitles`` field without a ``books`` field,
        we can pass the relationship directly into ``extract()``:
        
        .. code-block:: python
        
            from graphjoiner.declarative import extract, many, RootType, select
        
            class Root(RootType):
                book_titles = extract(
                    many(lambda: select(Book)),
                    lambda: Book.title,
                )
        
        ``extract()`` is often useful when modelling many-to-many relationships.
        For instance,
        suppose a book may have many publishers,
        and each publisher may publish many books.
        We define a type that associates books and publishers:
        
        .. code-block:: python
        
            from graphjoiner.declarative import ObjectType, select, single
        
            class BookPublisherAssociation(ObjectType):
                book = single(lambda: select(Book, ...))
                publisher = single(lambda: select(Publisher, ...))
        
        We can then use ``extract`` to define a field for all publishers of a book,
        and a field for books from a publisher:
        
        .. code-block:: python
        
            from graphjoiner.declarative import extract, many, ObjectType, select
        
            class Book(ObjectType):
                ...
                publishers = extract(
                    many(lambda: select(BookPublisherAssociation, ...)),
                    lambda: BookPublisherAssociation.publisher,
                )
        
            class Publisher(ObjectType):
                ...
                books = extract(
                    many(lambda: select(BookPublisherAssociation, ...)),
                    lambda: BookPublisherAssociation.book,
                )
        
        Interfaces
        ^^^^^^^^^^
        
        To define an interface,
        subclass ``InterfaceType`` and specify fields using ``field()``:
        
        .. code-block:: python
        
            from graphjoiner.declarative import InterfaceType, String
        
            class HasName(InterfaceType):
                name = field(type=String)
        
        To set which interfaces an object implements,
        set the ``__interfaces__`` attribute:
        
        .. code-block:: python
        
            from graphjoiner.declarative import ObjectType
        
            class Author(ObjectType):
                __interfaces__ = lambda: [HasName]
                ...
        
        Field sets
        ^^^^^^^^^^
        
        Field sets can be used to define multiple fields using a single attribute.
        For instance, this definition without field sets:
        
        .. code-block:: python
        
            from graphjoiner.declarative import field, Int, ObjectType, String
        
            class Book(ObjectType):
                title = field(type=String)
                author_id = field(type=Int)
        
        is roughly equivalent to this definition using field sets:
        
        .. code-block:: python
        
            from graphjoiner.declarative import field, field_set, ObjectType, String
        
            class Book(ObjectType):
                fields = field_set(
                    title=field(type=String),
                    author_id=field(type=String),
                )
        
        Field sets are useful when a set of fields needs to be generated dynamically.
        
        Input object types
        ^^^^^^^^^^^^^^^^^^
        
        Define input types by inheriting from ``InputObjectType``,
        and defining fields using ``field()``.
        For instance:
        
        .. code-block:: python
        
            from graphjoiner.declarative import InputObjectType, String
        
            class BookSelectionInput(InputObjectType):
                title = field(type=String, default=None)
        
        The fields on input object values are available as attributes.
        For instance:
        
        .. code-block:: python
        
            from graphjoiner.declarative import many, RootType, select, String
            from graphjoiner.declarative.sqlalchemy import SqlAlchemyObjectType
        
            class Book(SqlAlchemyObjectType):
                __model__ = BookRecord
        
                ...
        
                @staticmethod
                def filter_by_title(query, title):
                    # query is an instance of sqlalchemy.orm.Query
                    return query.filter(BookRecord.title == title)
        
            class Root(RootType):
                ...
        
                books = many(lambda: select(Book))
                @books.arg("selection", BookSelectionInput)
                def books_arg_title(query, title):
                    if selection.title is not None:
                        query = Book.filter_by_title(query, title)
        
                    return query
        
        The default value for each field can be set by passing the ``default`` argument to each field.
        To allow the absence of a value to be distinguished from an explicit null value,
        the default value for a field is ``undefined`` if the ``default`` argument is not set.
        For instance,
        to allow books to be filtered by title,
        including null titles:
        
        .. code-block:: python
        
            from graphjoiner.declarative import field, InputObjectType, many, RootType, select, String, undefined
            from graphjoiner.declarative.sqlalchemy import SqlAlchemyObjectType
        
            class BookSelectionInput(InputObjectType):
                title = field(type=String)
        
            class Book(SqlAlchemyObjectType):
                __model__ = BookRecord
        
                ...
        
                @staticmethod
                def filter_by_title(query, title):
                    # query is an instance of sqlalchemy.orm.Query
                    return query.filter(BookRecord.title == title)
        
            class Root(RootType):
                ...
        
                books = many(lambda: select(Book))
                @books.arg("selection", BookSelectionInput)
                def books_arg_title(query, title):
                    if selection.title is not undefined:
                        query = Book.filter_by_title(query, title)
        
                    return query
        
        Core Example
        ------------
        
        The declarative API of GraphJoiner is built on top of a core API.
        The core API exposes the fundamentals of how GraphJoiner works,
        giving greater flexibility at the cost of being rather verbose to use directly.
        The below shows how the original example could be written using the core API.
        In general,
        using the declarative API should be preferred,
        either by using the built-in tools or adding your own.
        
        Let's say we have some models defined by SQLAlchemy. A book has an ID, a title,
        a genre and an author ID. An author has an ID and a name.
        
        .. code-block:: python
        
            from sqlalchemy import Column, Integer, Unicode, ForeignKey
            from sqlalchemy.ext.declarative import declarative_base
        
            Base = declarative_base()
        
            class Author(Base):
                __tablename__ = "author"
        
                id = Column(Integer, primary_key=True)
                name = Column(Unicode, nullable=False)
        
            class Book(Base):
                __tablename__ = "book"
        
                id = Column(Integer, primary_key=True)
                title = Column(Unicode, nullable=False)
                genre = Column(Unicode, nullable=False)
                author_id = Column(Integer, ForeignKey(Author.id))
        
        We then define object types for the root, books and authors:
        
        .. code-block:: python
        
            from graphql import GraphQLInt, GraphQLString, GraphQLArgument
            from graphjoiner import JoinType, RootJoinType, single, many, field
            from sqlalchemy.orm import Query
        
            def create_root():
                def fields():
                    return {
                        "books": many(
                            book_join_type,
                            books_query,
                            args={"genre": GraphQLArgument(type=GraphQLString)}
                        )
                    }
        
                def books_query(args, _):
                    query = Query([]).select_from(Book)
        
                    if "genre" in args:
                        query = query.filter(Book.genre == args["genre"])
        
                    return query
        
                return RootJoinType(name="Root", fields=fields)
        
            root = create_root()
        
            def fetch_immediates_from_database(selections, query, context):
                query = query.with_entities(*(
                    selection.field.column_name
                    for selection in selections
                ))
        
                return query.with_session(context.session).all()
        
            def create_book_join_type():
                def fields():
                    return {
                        "id": field(column_name="id", type=GraphQLInt),
                        "title": field(column_name="title", type=GraphQLString),
                        "genre": field(column_name="genre", type=GraphQLString),
                        "authorId": field(column_name="author_id", type=GraphQLInt),
                        "author": single(author_join_type, author_query, join={"authorId": "id"}),
                    }
        
                def author_query(args, book_query):
                    books = book_query.with_entities(Book.author_id).distinct().subquery()
                    return Query([]) \
                        .select_from(Author) \
                        .join(books, books.c.author_id == Author.id)
        
                return JoinType(
                    name="Book",
                    fields=fields,
                    fetch_immediates=fetch_immediates_from_database,
                )
        
            book_join_type = create_book_join_type()
        
            def create_author_join_type():
                def fields():
                    return {
                        "id": field(column_name="id", type=GraphQLInt),
                        "name": field(column_name="name", type=GraphQLString),
                    }
        
                return JoinType(
                    name="Author",
                    fields=fields,
                    fetch_immediates=fetch_immediates_from_database,
                )
            author_join_type = create_author_join_type()
        
        We can execute the query by calling ``execute``:
        
        .. code-block:: python
        
            from graphjoiner import execute
        
            query = """
                {
                    books(genre: "comedy") {
                        title
                        author {
                            name
                        }
                    }
                }
            """
        
            class Context(object):
                def __init__(self, session):
                    self.session = session
        
            execute(root, query, context=Context(session))
        
        
        Which produces:
        
        ::
        
            {
                "books": [
                    {
                        "title": "Leave It to Psmith",
                        "author": {
                            "name": "PG Wodehouse"
                        }
                    },
                    {
                        "title": "Right Ho, Jeeves",
                        "author": {
                            "name": "PG Wodehouse"
                        }
                    },
                    {
                        "title": "Catch-22",
                        "author": {
                            "name": "Joseph Heller"
                        }
                    },
                ]
            }
        
        Let's break things down a little, starting with the definition of the root object:
        
        .. code-block:: python
        
            def create_root():
                def fields():
                    return {
                        "books": many(
                            book_join_type,
                            books_query,
                            args={"genre": GraphQLArgument(type=GraphQLString)}
                        )
                    }
        
                def books_query(args, _):
                    query = Query([]).select_from(Book)
        
                    if "genre" in args:
                        query = query.filter(Book.genre == args["genre"])
        
                    return query
        
                return RootJoinType(name="Root", fields=fields)
        
            root = create_root()
        
        For each object type, we need to define its fields.
        The root has only one field, ``books``, a one-to-many relationship,
        which we define using ``many()``.
        The first argument, ``book_join_type``,
        is the type we're defining a relationship to.
        The second argument to describes how to create a query representing all of those
        related books: in this case all books, potentially filtered by a genre argument.
        
        This means we need to define ``book_join_type``:
        
        .. code-block:: python
        
            def create_book_join_type():
                def fields():
                    return {
                        "id": field(column_name="id", type=GraphQLInt),
                        "title": field(column_name="title", type=GraphQLString),
                        "genre": field(column_name="genre", type=GraphQLString),
                        "authorId": field(column_name="author_id", type=GraphQLInt),
                        "author": single(author_join_type, author_query, join={"authorId": "id"}),
                    }
        
                def author_query(args, book_query):
                    books = book_query.with_entities(Book.author_id).distinct().subquery()
                    return Query([]) \
                        .select_from(Author) \
                        .join(books, books.c.author_id == Author.id)
        
                return JoinType(
                    name="Book",
                    fields=fields,
                    fetch_immediates=fetch_immediates_from_database,
                )
        
            book_join_type = create_book_join_type()
        
        The ``author`` field is defined as a one-to-one mapping from book to author.
        As before, we define a function that generates a query for the requested authors.
        We also provide a ``join`` argument to ``single()`` so that GraphJoiner knows
        how to join together the results of the author query and the book query:
        in this case, the ``authorId`` field on books corresponds to the ``id`` field
        on authors.
        (If we leave out the ``join`` argument, then GraphJoiner will perform a cross
        join i.e. a cartesian product. Since there's always exactly one root instance,
        this is fine for relationships defined on the root.)
        
        The remaining fields define a mapping from the GraphQL field to the database
        column. This mapping is handled by ``fetch_immediates_from_database``.
        The value of ``selections`` in
        ``fetch_immediates()`` is the selections of fields that aren't defined as relationships
        (using ``single`` or ``many``) that were either explicitly requested in the
        original GraphQL query, or are required as part of the join.
        
        .. code-block:: python
        
            def fetch_immediates_from_database(selections, query, context):
                query = query.with_entities(*(
                    fields[selection.field_name].column_name
                    for selection in selections
                ))
        
                return query.with_session(context.session).all()
        
        For completeness, we can tweak the definition of ``author_join_type`` so
        we can request the books by an author:
        
        .. code-block:: python
        
            def create_author_join_type():
                def fields():
                    return {
                        "id": field(column_name="id", type=GraphQLInt),
                        "name": field(column_name="name", type=GraphQLString),
                        "author": many(book_join_type, book_query, join={"id": "authorId"}),
                    }
        
                def book_query(args, author_query):
                    authors = author_query.with_entities(Author.id).distinct().subquery()
                    return Query([]) \
                        .select_from(Book) \
                        .join(authors, authors.c.id == Book.author_id)
        
                return JoinType(
                    name="Author",
                    fields=fields,
                    fetch_immediates=fetch_immediates_from_database,
                )
        
            author_join_type = create_author_join_type()
        
        
Keywords: graphql graph join
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
