A repository to facilitate API developers, thus it integrate reputable libraries, cover their functional aspects and follows good engineering practices.
These libraries are,
- Flask SqlAlchemy (Wrapper on SqlAlchemy)
- Flask Migrate (Wrapper on Alembic)
- Flask Manager (Wrapper on Flask Scripts)
- Gunicorn (Web Server)
- Psycopg2 to interact with Postgres instance
- PyTest integrated for APIs functionality tests
- PyTest-cov integrated for test coverage report
- PyLint integrated to test code quality
- Tox integrated to test different app on different environments
- Docker integratef to dockerize the flask app
- End to end CRUD implementation on a model.
- For rapid application development, each layer has a Base Class and CRUD functionality is already there.
- Supports environment specific configuration using .env file.
- Logging of web request and exceptions.
- PyTest, PyTestCov, PyLint and Tox complete integration.
- Code is self explanatory; and comments added where needed.
Application is divided in 6 layers.
- Root
- Holds infrastructure files, that runs whole application.
- APIs
- Provides routing to API
- Responsible to serialize request
- Direct request to service layer
- Deserialize service response
- Send it back to the API client.
- Services
- Responsible to drive business logic
- Use repository layer to interact with database
- Repositories
- Responsible to make queries to database
- Models
- It holds definition of database models
- Migrations
- Responsible for database migrations.
- Postgresql instance is up and running
- Python 3.7+ is installed
Clone repository,
git clone https://github.com/uinvent/flask_boilerplate.git
Create a copy of .env.sample and name it as .env. Fill it with your machine configurations.
APP_DB_* configurations are must as they lead to your database.
Install libraries used in project,
virtualenv --python=python3 venv --no-site-packages
source venv/bin/activate
pip install -r requirements.txt
python manage.py init
It will create database on the server configured in .env file.
Then run,
python manage.py init
It will create database on the server configured in .env file.
Then run,
python manage.py db upgrade
This will run two migrations,
- First will create two sample tables person and address. Where each person can have multiple addresses.
- Second will insert records in these tables.
python manage.py runserver -d
This will start your app server and now APIs are ready to be consumed for debugging.
To start a production ready server (gunicorn server) python manage.py runserver
Now APIs are ready to be consumed on default URL http://0.0.0.0:8088
pytest
Above command will find all test cases and runs them. Tests are available in /tests/ folder
pytest --cov=./src/ tests/
Above command will show the test coverage report.
pylint src --errors-only
Above command will run pylint on src folder and will check errors only. It is using .pylintrc for linting rules.
tox -e py37
Above command will run test cases using tox library.
tox -e pylint
Above command will run pylint on all py files including files manage.py, infra.py and conf.py
Install docker package on your machine. Once installed, execute below command.
`bash docker-startup.sh`
You might need to make some changes at your database; to make it accessible over network.
Above will start application instance on docker and it should be accessible at port 8000.
-
Get all persons entities.
http://0.0.0.0:8088/person/ -
Get person entity with id 1.
http://0.0.0.0:8088/person/1 -
Get person entity with its address entities.
http://0.0.0.0:8088/person/1/address/
Save person entity.
http://0.0.0.0:8088/person/
Input
{ "date_of_birth": "1996-05-20 00:00:00+05:00", "first_name": "umair", "gender": "M", "last_name": "", "middle_name": "", "national_identifier": "1110-22-1" }
Update person entity.
http://0.0.0.0:8088/person/1/
Input
{ "date_of_birth": "1996-05-20 00:00:00+05:00", "first_name": "umair", "gender": "M", "last_name": "khan", "middle_name": "", "national_identifier": "1110-22-1" }
To delete a person entity.
http://0.0.0.0:8088/person/1/