A sample user data CRUD app to test Keploy integration capabilities using FastAPI and PostgreSQL.
Make the following requests to the respective endpoints -

1. GET students/ - Get all students.
2. GET students/{id} - Get a student by id.
3. POST students/ - Create a student.
4. PUT students/{id} - Update a student by id.
5. DELETE students/{id} - Delete a student by id.

git clone https://github.com/keploy/samples-python.git && cd samples-python/fastapi-postgres
pip3 install coverage
pip3 install -r requirements.txt

Keploy can be installed on Linux directly and on Windows with the help of WSL. Based on your system architecture, install the keploy latest binary release

curl -O -L https:///keploy.io/install.sh && source install.sh

# Start the application
docker-compose up -d postgres

If we have setup our sample-app with docker, we need to update the container name to postgres on line 6, in application/database.py, from postgresql://postgres:postgres@localhost:5432/studentdb to postgresql://postgres:postgres@postgres:5432/studentdb.

Also, we need to update the container name to postgres on line 11, of application/main.py, from postgresql://postgres:postgres@localhost:5432/studentdb to postgresql://postgres:postgres@postgres:5432/studentdb.

This command will start the recording of API calls :

sudo -E PATH=$PATH keploy record -c "uvicorn application.main:app --reload"

Make API Calls using Hoppscotch, Postman or cURL command. Keploy with capture those calls to generate the test-suites containing testcases and data mocks.

curl --location 'http://127.0.0.1:8000/students/' \
--header 'Content-Type: application/json' \
--data-raw '{
      "name": "Eva White",
      "email": "[email protected]",
      "password": "evawhite111"
    }'

curl --location 'http://127.0.0.1:8000/students/' \
--header 'Content-Type: application/json' \
--data-raw '    {
      "name": "John Doe",
      "email": "[email protected]",
      "password": "johndoe123"
    }'

curl --location 'http://127.0.0.1:8000/students/'

This will return all the data saved in the database.

curl --location 'http://127.0.0.1:8000/students/1'

curl --location --request PUT 'http://127.0.0.1:8000/students/2' \
--header 'Content-Type: application/json' \
--data-raw '    {
        "name": "John Dow",
        "email": "[email protected]",
        "password": "johndoe123",
        "stream": "Arts"
    }'

curl --location --request DELETE 'http://127.0.0.1:8000/students/1'

Now all these API calls were captured as editable testcases and written to keploy/tests folder. The keploy directory would also have mocks file that contains all the outputs of postgres operations.

Now let's run the application in test mode.

sudo -E PATH=$PATH keploy test -c "python3 -m uvicorn application.main:app" --delay 10

We will get output something like below -

By making just 2 api call, we have generated a complete test suite for our application and acheived 72% coverage.

So, no need to setup fake database/apis like Postgres or write mocks for them. Keploy automatically mocks them and, The application thinks it's talking to Postgres 😄