onecrayon · July 25, 2021 09:32 · prostomarkeloff · Sep 17, 2020 · onecrayon · Sep 17, 2020
diff --git a/main.py b/main.py
 #!/usr/bin/env python3
 """
 1. Install Python 3.7 and `pipenv`: https://docs.pipenv.org/en/latest/
 2. `pipenv install`
 3. `pipenv shell`
 4. `./main.py`
 5. In your browser, visit http://localhost:8000/parents

 See comments in lines 92-108 for details on where I'm struggling.
 """

 import logging
 from typing import List
 from pprint import pprint

 import uvicorn
 from databases import Database
 from fastapi import FastAPI
 from pydantic import BaseModel
 import sqlalchemy as sa
 from sqlalchemy.engine import Engine
 from sqlalchemy.orm import relationship, joinedload
 from sqlalchemy.orm.query import Query
 from sqlalchemy.ext.declarative import declarative_base

 logger = logging.getLogger()
 logger.setLevel(logging.DEBUG)

 AlchemyBase = declarative_base()

 DATABASE_URL = "sqlite:///./test.db"
 db = Database(DATABASE_URL)


 """SQLAlchemy model classes"""
 class Parent(AlchemyBase):
    __tablename__ = 'parents'

    id = sa.Column(sa.Integer, primary_key=True)
    name = sa.Column(sa.String)

    children = relationship('Child', back_populates='parent')

 class Child(AlchemyBase):
    __tablename__ = 'children'

    id = sa.Column(sa.Integer, primary_key=True)
    name = sa.Column(sa.String)
    parent_id = sa.Column(sa.Integer, sa.ForeignKey('parents.id'))

    parent = relationship('Parent', back_populates='children')


 """Pydantic FastAPI type classes"""
 class ChildOut(BaseModel):
    id: int
    name: str

 class ParentOut(BaseModel):
    id: int
    name: str
    children: List[ChildOut] = []


 """Load app and initialize database"""
 app = FastAPI()

 ### Bootstrap the database; this is only necessary to create the tables and data for this example
 # I would manage the database with migrations rather than creating an engine normally
 engine: Engine = sa.create_engine(
    DATABASE_URL, connect_args={"check_same_thread": False}
 )
 AlchemyBase.metadata.create_all(bind=engine)
 engine.execute("INSERT OR REPLACE INTO parents (id, name) VALUES (1, 'First Parent'), (2, 'Second Parent'), (3, 'Third Parent')")
 engine.execute("INSERT OR REPLACE INTO children (id, name, parent_id) VALUES (1, 'Child A', 1), (2, 'Child B', 1), (3, 'Child C', 2)")
 ### End example bootstrapping code


 """Define app events for managing database lifecycle"""
 @app.on_event("startup")
 async def startup():
    await db.database.connect()

 @app.on_event("shutdown")
 async def shutdown():
    await db.database.disconnect()


 """Define app routes for fetching data"""
 @app.get('/parents', response_model=List[ParentOut])
 async def read_parents():
    query = Query(Parent).options(joinedload('children'))
    # This logic is how SQLAlchemy handles things internally; similarly, I could just do this:
    #     statement = query.with_labels().statement
    #     results = await db.fetch_all(statement)
    # Best I can tell, I'll need access to the context to correctly map stuff (hence this code)
    query_context = query._compile_context()
    query_context.statement.use_labels = True
    logger.info(f'QUERY: {query_context.statement}')
    results = await db.fetch_all(statement)
    # For logging purposes...
    results_as_dicts = [
        {column: value for column, value in rowproxy.items()} for rowproxy in results
    ]
    logger.info(f'RESULTS: {pprint(results_as_dicts)}')
    # At this point I have a query, a context, and a result set, and I need to use those things to
    # map the results into a dict that I can return (at which point Pydantic will convert the dict
    # into a list of ParentOut objects)
    return []


 """Easy server running for debugging"""
 if __name__ == "__main__":
    uvicorn.run(app, host="localhost", port=8000)
diff --git a/Pipfile b/Pipfile
 [[source]]
 name = "pypi"
 url = "https://pypi.org/simple"
 verify_ssl = true

 [dev-packages]
 pylint = "*"

 [packages]
 sqlalchemy = "*"
 databases = {extras = ["sqlite"],version = "*"}
 fastapi = "*"
 uvicorn = "*"

 [requires]
 python_version = "3.7"
diff --git a/Pipfile.lock b/Pipfile.lock
 {
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 }
	#!/usr/bin/env python3
	"""
	1. Install Python 3.7 and `pipenv`: https://docs.pipenv.org/en/latest/
	2. `pipenv install`
	3. `pipenv shell`
	4. `./main.py`
	5. In your browser, visit http://localhost:8000/parents

	See comments in lines 92-108 for details on where I'm struggling.
	"""

	import logging
	from typing import List
	from pprint import pprint

	import uvicorn
	from databases import Database
	from fastapi import FastAPI
	from pydantic import BaseModel
	import sqlalchemy as sa
	from sqlalchemy.engine import Engine
	from sqlalchemy.orm import relationship, joinedload
	from sqlalchemy.orm.query import Query
	from sqlalchemy.ext.declarative import declarative_base

	logger = logging.getLogger()
	logger.setLevel(logging.DEBUG)

	AlchemyBase = declarative_base()

	DATABASE_URL = "sqlite:///./test.db"
	db = Database(DATABASE_URL)


	"""SQLAlchemy model classes"""
	class Parent(AlchemyBase):
	__tablename__ = 'parents'

	id = sa.Column(sa.Integer, primary_key=True)
	name = sa.Column(sa.String)

	children = relationship('Child', back_populates='parent')

	class Child(AlchemyBase):
	__tablename__ = 'children'

	id = sa.Column(sa.Integer, primary_key=True)
	name = sa.Column(sa.String)
	parent_id = sa.Column(sa.Integer, sa.ForeignKey('parents.id'))

	parent = relationship('Parent', back_populates='children')


	"""Pydantic FastAPI type classes"""
	class ChildOut(BaseModel):
	id: int
	name: str

	class ParentOut(BaseModel):
	id: int
	name: str
	children: List[ChildOut] = []


	"""Load app and initialize database"""
	app = FastAPI()

	### Bootstrap the database; this is only necessary to create the tables and data for this example
	# I would manage the database with migrations rather than creating an engine normally
	engine: Engine = sa.create_engine(
	DATABASE_URL, connect_args={"check_same_thread": False}
	)
	AlchemyBase.metadata.create_all(bind=engine)
	engine.execute("INSERT OR REPLACE INTO parents (id, name) VALUES (1, 'First Parent'), (2, 'Second Parent'), (3, 'Third Parent')")
	engine.execute("INSERT OR REPLACE INTO children (id, name, parent_id) VALUES (1, 'Child A', 1), (2, 'Child B', 1), (3, 'Child C', 2)")
	### End example bootstrapping code


	"""Define app events for managing database lifecycle"""
	@app.on_event("startup")
	async def startup():
	await db.database.connect()

	@app.on_event("shutdown")
	async def shutdown():
	await db.database.disconnect()


	"""Define app routes for fetching data"""
	@app.get('/parents', response_model=List[ParentOut])
	async def read_parents():
	query = Query(Parent).options(joinedload('children'))
	# This logic is how SQLAlchemy handles things internally; similarly, I could just do this:
	# statement = query.with_labels().statement
	# results = await db.fetch_all(statement)
	# Best I can tell, I'll need access to the context to correctly map stuff (hence this code)
	query_context = query._compile_context()
	query_context.statement.use_labels = True
	logger.info(f'QUERY: {query_context.statement}')
	results = await db.fetch_all(statement)
	# For logging purposes...
	results_as_dicts = [
	{column: value for column, value in rowproxy.items()} for rowproxy in results
	]
	logger.info(f'RESULTS: {pprint(results_as_dicts)}')
	# At this point I have a query, a context, and a result set, and I need to use those things to
	# map the results into a dict that I can return (at which point Pydantic will convert the dict
	# into a list of ParentOut objects)
	return []


	"""Easy server running for debugging"""
	if __name__ == "__main__":
	uvicorn.run(app, host="localhost", port=8000)
	[[source]]
	name = "pypi"
	url = "https://pypi.org/simple"
	verify_ssl = true

	[dev-packages]
	pylint = "*"

	[packages]
	sqlalchemy = "*"
	databases = {extras = ["sqlite"],version = "*"}
	fastapi = "*"
	uvicorn = "*"

	[requires]
	python_version = "3.7"
	{
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