FastAPI CRUD using Async, Alembic & Postgresql

Example Async CRUD API using FastAPI

This repository is the result of wading through how to use async CRUD operations using the backend core from the excellent generator template by Sebastián Ramírez, Full Stack FastAPI and PostgreSQL - Base Project Generator.

In reviewing the FastAPI docs, the encode/databases docs on queries, and the gitter channels, there seemed to be only the basic information on using databases with SQL Alchemy and data table definitions that would not work well with Alembic autogenerate - as least in my case using the generator template. This repository is the working result of my tests and learning to use FastAPU with async, asycnpg, databases, and Alembic autogenerated migrations with declarative base model. Hopefully it will be useful to others looking for some examples of using databases, asyncpg and Alembic with FastAPI.

Updates

Version 0.3.0 Dockerfiles & Docker-Compose ready containing two services, PSQL & APP.

PSQL - Postgresql 12-alpine image.
APP - ClearLinux/Python3.8 image with custom build.
Auto Migrations - Migrations including creation of stored procedures in APP image.
.env Sample - Change to .env and provide desired values.

Details

Uses version 0.4.0 of the Fullstack generator: before current changes in structure of the project were made.
encode/databases: To simplify managing connections, pooling, etc.
asyncpg with Posgresql: Built using a Postgresql 12 database, but can be altered to use SQLite.
Alembic: Using autogenerate to create migrations.
Version 0.1.0: Uses raw SQL in CRUD functions. See tag v0.1.0.
Version 0.2.0: Uses functions (reads) and procedures (write). Procedures require Posgresql Version 11 or higher.
Version 0.3.0: Uses Docker-Compose to spin up services and run migrations.

Critical Notes

PyCharm (or other IDE) may complain about the PSQL Procedures using "CALL" - I just injected SQL lanuage on the query text to eliminate the errors.
Some CRUD functions utilize databases.fetch_val() and require using the latest master branch of databases from the repo. The version on PyPi is not correct, and is missing the April 30 commit with the required changes to use this. See this commit.
Clone the [encode/databases] repo into the "backend" folder before running docker-compose up --build.
If not patching or using the current repo from PyPi (says 0.3.2 but really is <=0.3.1)- databases.fetch_one() needs to be used or the get by ID and create routes will fail.

Installation Instructions

Clone the repo.
Clone the [encode/databases] repo into the "backend" folder.
Change the sample.env file to .env and enter your preferred values.
Run Docker Compose (with -d for detached, or omit to run in foreground):

$ docker-compose up --build

In the browser, go to localhost:8000/docs
Login using the super user email and password supplied in the .env file.
Test routes.
When done:

$ docker-compose down

You can rerun the docker-compose up and the datbase data will be persistent.

You can also remove the named volume where the database data resides by adding the -v flag:

$ docker-compoise down -v

To Do

Tests, deployment via docker, and other changes to come, time permitting. Want to see these sooner - see below in Contributing.

Contributing

Contributions, issues and feature requests are welcome!
Feel free to check issues page.

Fork the Project
Create your Feature Branch (git checkout -b feature/YourFeature)
Commit your Changes (git commit -m 'Add My Feature')
Push to the Branch (git push origin feature/YourFeature)
Open a Pull Request

wedwardbeck/lrnfast