A few months ago, I published some code as open source with minimal unit tests and without much of an announcement. This is an attempt to describe what the code does with some pointers to other similar projects.
These projects present an object graph as asynchrounous generators with a friendly method chaining API. All you do is a mostly framework free plain-old objects with some decorators thrown in. Typegraphql uses
@Field decorators for example.
Like Kotlin async flow, this package implements a bunch of operators, which can be combined with python dataclasses and some decorators to express queries. The generators themselves are lazy/cold. No work is done unless requested. Like Kotlin’s
collect, we have
as_dict() as terminal operators.
What Does fquery do?
fquery is built on top of
aioitertools and python’s async generators. It provides a few intermediate and terminal operators so you can create a type safe query builder in python. It provides a few decorators that you can use to annotate your dataclasses. Lastly, it can serialize the query to SQL (experimental feature) or you can serialize to an expression that can be transported on the wire to a backend for remote execution.
@dataclass class MockUser(ViewModel): name: str age: int @edge async def friends(self) -> List["MockUser"]: yield [MockUser.get(m) for m in range(3 * self.id, 3 * self.id + 3)] @edge async def reviews(self) -> List["MockReview"]: yield [ MockReview.get(m) for m in range(3 * self.id + 300, 3 * self.id + 300 + 5) ] @staticmethod def get(id: int) -> "MockUser": ... @dataclass class MockReview(ViewModel): business: str rating: int author: MockUser @edge async def author(self) -> MockUser: yield self.author @staticmethod def get(id: int) -> "MockReview": ...
Super simple isn’t it? For each of the types, you’ll need to implement a
Resolver object. These objects are typically named as
MockReviewQuery and provide a
resolve_obj() method. This way, all the details of how to fetch an object given it’s ID and how to resolve an edge is abstracted out from the actual query execution mechanism.
To understand the internals, you can look at
materialize_walk_obj() are key interfaces. They’re described by included unit tests.
The supported operators are documented in
test_operators.py. Sample query:
@async_test async def test_edge_project_other_kind(self): resp = ( await UserQuery(range(1, 5)) .edge("reviews") .project(["business", "rating", ":id"]) .take(3) .to_json() ) ...
MockUserclass inherits from
ViewModelclass. We can move that into decorators.
- Support more complex SQL queries
- Serialization to other like minded query languages
- Support for
graphqlon top of this infra
- Tighter integration into Django and Flask