FastAPI

FastAPI is the 3rd most popular Python web framework. The factors like asynchronous views, easy-to-learn, and fast setup have contributed to its quick adoption.

SQLAlchemy

SQLAlchemy is the Python SQL toolkit and Object Relational Mapper that gives application developers the full power and flexibility of SQL.

It provides a full suite of well-known enterprise-level persistence patterns, designed for efficient and high-performing database access, adapted into a simple and Pythonic domain language. - from official docs

It is the most popular ORM for Python, primarily used with Flask.

ormar is a mini async ORM for Python. It uses sqlalchemy for building queries, databases for asynchronous execution of queries, and pydantic for data validation. You can create an ormar model and generate pydantic models from it.

If you have read my post, Pydantic for FastAPI, you will understand how pydantic is very useful for your FastAPI application.

SQLAlchemy uses alembic for migrations. Since ormar is built on top of sqlalchemy, we can use the same for migrations.

Setup the project

$ mkdir fastapi-ormar-alembic && cd $_
$ mkdir .venv
$ pipenv install fastapi uvicorn ormar alembic aiosqlite

Setup the database and models

Create a new file db.py in the root of the project. This file will contain the database setup and an example table.

import databases
import ormar
import sqlalchemy

database = databases.Database("sqlite:///db.sqlite")
metadata = sqlalchemy.MetaData()


class BaseMeta(ormar.ModelMeta):
    database = database
    metadata = metadata


class Users(ormar.Model):
    class Meta(BaseMeta):
        tablename = "users"

    id: int = ormar.Integer(primary_key=True)
    email: str = ormar.String(max_length=64, unique=True)
    password: str = ormar.String(max_length=128)

Creating a BaseMeta lets you add the database and metadata variables to all your models.

We created a simple model with three basic fields; now, let's set up migrations with alembic.

The migrations

(fastapi-ormar-alembic) $ alembic init migrations

Your project structure should look like this:

├── Pipfile
├── Pipfile.lock
├── alembic.ini
├── db.py
├── db.sqlite
├── main.py
└── migrations

Add the database URL to the alembic.ini file. You're modifying a single line:

sqlalchemy.url = sqlite:///db.sqlite

Now, tell the migration environment where our metadata is stored. Add(modify) the following in migrations/env.py:

...
from db import BaseMeta
...


target_metadata = BaseMeta.metadata

Finally, create the migration script. You can use the --autogenerate option to generate migrations based on the metadata automatically:

(fastapi-ormar-alembic) $ alembic revision --autogenerate -m "Added users table"
INFO  [alembic.runtime.migration] Context impl SQLiteImpl.
INFO  [alembic.runtime.migration] Will assume non-transactional DDL.
INFO  [alembic.autogenerate.compare] Detected added table 'users'
  Generating /home/amalshaji/Workspace/Python/blog-code-repository/fastapi-ormar-
  alembic/migrations/versions/c07fe5d55962_added_users_table.py ...  done

Now, run migrations:

(fastapi-ormar-alembic) $ alembic upgrade head

This produced a new file, migrations/versions/c07fe5d55962_added_users_table.py

File name inferred from the migration output.

"""Added users table

Revision ID: c07fe5d55962
Revises: 
Create Date: 2021-08-14 11:55:46.845709

"""
from alembic import op
import sqlalchemy as sa


# revision identifiers, used by Alembic.
revision = 'c07fe5d55962'
down_revision = None
branch_labels = None
depends_on = None


def upgrade():
    # ### commands auto generated by Alembic - please adjust! ###
    op.create_table('users',
    sa.Column('id', sa.Integer(), nullable=False),
    sa.Column('email', sa.String(length=64), nullable=False),
    sa.Column('password', sa.String(length=128), nullable=False),
    sa.PrimaryKeyConstraint('id'),
    sa.UniqueConstraint('email')
    )
    # ### end Alembic commands ###


def downgrade():
    # ### commands auto generated by Alembic - please adjust! ###
    op.drop_table('users')
    # ### end Alembic commands ###

It worked as expected. Now let's modify our table to add a new field and run the migration.

# db.py

class Users(ormar.Model):
    class Meta(BaseMeta):
        tablename = "users"

    id: int = ormar.Integer(primary_key=True)
    email: str = ormar.String(max_length=64, unique=True)
    password: str = ormar.String(max_length=128)
    is_active: bool = ormar.Boolean(default=True) # new

Run the migration:

(fastapi-ormar-alembic) $ alembic revision --autogenerate -m "Added is_active to users table"
INFO  [alembic.runtime.migration] Context impl SQLiteImpl.
INFO  [alembic.runtime.migration] Will assume non-transactional DDL.
INFO  [alembic.autogenerate.compare] Detected added column 'users.is_active'
  Generating /home/amalshaji/Workspace/Python/blog-code-repository/fastapi-ormar-
  alembic/migrations/versions/026a9a23ebbe_added_is_active_to_users_table.py ...  done

(fastapi-ormar-alembic) $ alembic upgrade head

This created a new file, migrations/versions/026a9a23ebbe_added_is_active_to_users_table.py:

"""Added is_active to users table

Revision ID: 026a9a23ebbe
Revises: c07fe5d55962
Create Date: 2021-08-14 12:20:36.817128

"""
from alembic import op
import sqlalchemy as sa


# revision identifiers, used by Alembic.
revision = '026a9a23ebbe'
down_revision = 'c07fe5d55962'
branch_labels = None
depends_on = None


def upgrade():
    # ### commands auto generated by Alembic - please adjust! ###
    op.add_column('users', sa.Column('is_active', sa.Boolean(), nullable=True))
    # ### end Alembic commands ###


def downgrade():
    # ### commands auto generated by Alembic - please adjust! ###
    op.drop_column('users', 'is_active')
    # ### end Alembic commands ###

Let's verify the same by checking the database schema:

$ sqlite3 db.sqlite
SQLite version 3.31.1 2020-01-27 19:55:54
Enter ".help" for usage hints.
sqlite> .schema users
CREATE TABLE users (
        id INTEGER NOT NULL,
        email VARCHAR(64) NOT NULL,
        password VARCHAR(128) NOT NULL, is_active BOOLEAN,
        PRIMARY KEY (id),
        UNIQUE (email)
);
sqlite> .quit

Now that we have seen how to set up ormar + alembic let's see how to initialize our database connection in the fastapi application.

FastAPI application

from fastapi import FastAPI

from db import database

app = FastAPI()


@app.on_event("startup")
async def startup():
    if not database.is_connected:
        await database.connect()


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

We used the FastAPI's(Starlette's) startup and shutdown events to create/close the database connection. We are creating a connection pool. Whenever a database connection is created, it is added to the pool so that the connection can later use for another request—essentially removing the time taken to create a new connection.

Conclusion

We have successfully setup up our FastAPI + ormar + alembic project. With pydantic support, ormar can generate pydantic models from ormar models. The generated pydantic models can be used by FastAPI during request/response data validation. ormar + alembic is an excellent duo for writing database code.

Source Code: fastapi-ormar-alembic