lilly 0.0.1

This package provides an opinionated SOA-layered fastapi-based web-framework.

Lilly

Lilly is fast service-oriented and layered Python 3.6+ web framework built on top of FastAPI It is enforces a certain way of creating FastApi applications that is much easier to reason about. Since it is based on FastAPI, it is modern, fast (high performance), and works well with Python type hints.

Purpose

Lilly signifies peaceful beauty. Lilly is thus an opinionated framework that ensures clean beautiful code structure that scales well for large projects and large teams.

• It just adds more opinionated structure to the already beautiful FastAPI.
• It ensures that when someone is building a web application basing on Lilly, they don't need to think about the structure.
• The developer should just know that it is a service-oriented architecture with each service having a layered architecture that ensures layers don't know what the other layer is doing.

Key Features

On top of the key features of FastAPI which include:

• Fast. It is based on FastApi
• Intuitive: Great editor support. Completion everywhere. Less time debugging.
• Easy: Designed to be easy to use and learn. Less time reading docs.
• Short: Minimize code duplication. Multiple features from each parameter declaration. Fewer bugs.
• Robust: Get production-ready code. With automatic interactive documentation.
• Standards-based: Based on (and fully compatible with) the open standards for APIs: OpenAPI (previously known as Swagger) and JSON Schema.

It also:

• Enforces a separation of concerns between service to service
• Enforces a separation of concerns within the service between presentation, business, persistence, and data_source layers

Quick Start

• Ensure you have Python 3.7 or +3.7 installed
• Create a new folder for your application

mkdir lilly_sample && cd lilly_sample

• Create the virtual environment and activate it

python3 -m venv env
source env/bin/activate

• Install lilly

pip install lilly

• Create your first application based off the framework

python -m lilly create-app

This will create the following folder structure with some fully functional sample code

.
  ├── main.py
  ├──  settings.py
  └── services
      ├──  __init__.py
      └── hello
          ├── __init__.py
          ├── actions.py
          ├── datasources.py
          ├── dtos.py
          ├── repositories.py
          └── routes.py

• Install uvicorn and run the app

pip install uvicorn
uvicorn main:app --reload

• For you to add another service in the services folder, run the command:

python -m lilly create-service <service-name>

e.g.

python -m lilly create-service blog

• For more information about the commands, just run the help commands

python -m lilly --help
python -m lilly create-app --help
python -m lilly create-service --help

Design

Requirements

The following features are required.

Configuration

• All services are put in the services folder whose import path is passed as a parameter to the Lilly instance during initialization. (Default: folder called services on root of project)
• All settings are put as constants in the settings python module whose import path is passed to Lilly instance at initialization. (Default: settings.py on the root of project)

Base Structures

• All services must have the following modules or packages:
  • routes (if a package is used, all RouteSet subclasses must be imported into the routes.__init__ module)
  • actions
  • repositories
  • datasources
  • dtos
• Just like FastAPI Class-based views (CBV) routes, Lilly routes (which are technically methods of the Service subclass) should have the post,get,put,patch... decorators. The format is exactly as it is in FastAPI. In addition, dependencies can be shared across multiple endpoints of the same service thanks to FastApi CBV.
• RouteSet is the base class of all Routes. It should have the following methods overridden:
  • _do(self, actionCls: Type[Action], *args, **kwargs) which internally initializes the actionCls and calls run() on it
• Action subclasses should have an overridden run(self) -> Any method
  • The run(self) method should be able to access any repositories by directly importing any it needs
• Repository subclasses should have public:
  • get_one(self, record_id: Any, **kwargs) -> Any method to get one record of id record_id
  • get_many(self, skip: int, limit: int, filters: Dict[Any, Any], **kwargs) -> List[Any] method to get many records that fulfil the filters
  • create_one(self, record: Any, **kwargs) -> Any method to create one record
  • create_many(self, record: List[Any], **kwargs) -> List[Any] method to create many records
  • update_one(self, record_id: Any, new_record: Any, **kwargs) -> Any method to update one record of id record_id
  • update_many(self, new_record: Any, filters: Dict[Any, Any], **kwargs) -> Any method to update many records that fulfil the filters
  • remove_one(self, record_id: Any, **kwargs) -> Any method to remove one record of id record_id
  • remove_many(self, filters: Dict[Any, Any], **kwargs) -> Any method to remove many records that fulfil the filters
• Repository subclasses should also have the following methods overridden:
  • _get_one(self, datasource_connection: Any, record_id: Any, **kwargs) -> Any method to get one record of id record_id
  • _get_many(self, datasource_connection: Any, skip: int, limit: int, filters: Dict[Any, Any], **kwargs) -> List[Any] method to get many records that fulfil the filters
  • _create_one(self, datasource_connection: Any, record: Any, **kwargs) -> Any method to create one record
  • _create_many(self, datasource_connection: Any, record: List[Any], **kwargs) -> List[Any] method to create many records
  • _update_one(self, datasource_connection: Any, record_id: Any, new_record: Any, **kwargs) -> Any method to update one record of id record_id
  • _update_many(self, datasource_connection: Any, new_record: Any, filters: Dict[Any, Any], **kwargs) -> Any method to update many records that fulfil the filters
  • _remove_one(self, datasource_connection: Any, record_id: Any, **kwargs) -> Any method to remove one record of id record_id
  • _remove_many(self, datasource_connection: Any, filters: Dict[Any, Any], **kwargs) -> Any method to remove many records that fulfil the filters
  • _datasource(self) -> DataSource an @property-decorated method to return the DataSource whose connect() method is to be called in any of the other methods to get its instance.
  • _to_output_dto(self, record: Any) -> BaseModel method which converts any record from the data source raw to DTO for the public methods
• DataSource subclasses should have an overridden connect(self) method
• dtos (Data Transfer Object classes) are subclasses of the pydantic.BaseModel which are to be used to move data across the layers
• Any setting added to the gazetted settings file can be accessed via lilly.conf.settings.<setting_name> e.g. lilly.conf.settings.APP_SETTING

Running

• The Lilly instance should be run the same way as FastAPI instances are run e.g.

uvicorn main:app # for app defined in the main.py module

Implementation Ideas

• Create a Lilly class as a subclass of FastAPI.
  • Lilly class should have the following properties set during initialization or else the defaults are applied
    • services_path (an import path as string)
    • settings_path (an import path as string)
  • All routes, actions, repositories and datasources are automatically imported using importlib.import_module by concatenating the services import path to the respective module e.g. actions, routes etc.
• in order to make route definition solely dependent on folder structure, we change @app.get decorators to @get
• app.get, app.post etc. should throw NotImplemented errors (unless this effectively breaks the code. In this case, check the difference between when app.get is used and when router.get is used)
• we will have an attribute in a different module from that where Lilly is defined. It is called router: APIRouter. Let the module be called routing
• in that same module, there will be functions called get, postetc) that are just returning router.get, router.post etc.
• When initializing in init of Lilly, we will fetch all services and call self.include_router(router).
• router will be imported dynamically after all the routes in all services are imported.
• app.mount should throw an NotImplemented error because it will complicate the app structure if used
• Use CBV, but with one with router as one common router for all services as:
  • we will have an attribute in a different module from that where Lilly is defined. It is called router: APIRouter. Let the module be called routing
  • @cbv(router) will be wrapped to become @routeset
  • The class based views themselves will be subclasses of RouteSet
  • The RouteSet class will have a protected method _do(self, action_cls: Action, *args, **kwargs) to make a call to any action
  • The @router.post or @router.get etc. on the class based views methods will all be aliased to their post, get etc counterparts

ToDo

• Set up the abstract methods structure
• Set up the CLI to generate an app
• Set up the CLI to generate a service
• Make repository public
• Package it and publish it
• Add some out-of-the-box base data sources e.g.
  • SqlAlchemy
  • Redis
  • Memcached
  • RESTAPI
  • GraphQL
  • RabbitMQ
  • ActiveMQ
  • Websockets
  • Kafka
  • Mongodb
  • Couchbase
  • DiskCache
• Add some out-of-the-box base repositories e.g.
  • SqlAlchemyRepo (RDBM e.g. PostgreSQL, MySQL etc.)
  • RedisRepo
  • MemcachedRepo
  • RESTAPIRepo
  • GraphQLRepo
  • RabbitMQRepo
  • ActiveMQRepo
  • WebsocketsRepo
  • KafkaRepo
  • MongodbRepo
  • CouchbaseRepo
  • DiskCacheRepo
• Add some out-of-the-box base actions e.g.
  • CreateOneAction
  • CreateManyAction
  • UpdateOneAction
  • UpdateManyAction
  • ReadOneAction
  • ReadManyAction
  • DeleteOneAction
  • DeleteManyAction
• Add some out-of-the-box base route sets
  • CRUDRouteSet
  • WebsocketRouteSet
  • GraphQLRoute
• Add example code in examples folder
  • Todolist (CRUDRouteSet, SqlAlchemyRepo)
  • RandomQuotes (WebsocketRouteSet, MongodbRepo) (quotes got from the Bible)
  • Clock (WebsocketRouteSet, WebsocketsRepo)
• Set up automatic documentation
• Set up CI via Github actions
• Set up CD via Github actions
• Write about it in hashnode or Medium or both

Inspiration

• The idea to create lilly came after looking at what the Loopback team did with Loopback4

License

Copyright (c) 2022 Martin Ahindura Licensed under the MIT License