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README.md

User Data CRUD Application

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

  1. GET /user/ - To get all the data at once.
  2. GET /user/uuid/ - To get the data of any particular user.
  3. POST /user/ - To create a new user.
  4. PUT /user/uuid/ - To update an existing user.
  5. DELETE /user/uuid/ - To delete an existing user.

Installation Setup

git clone https://github.com/keploy/samples-python.git && cd samples-python/django-postgres/django_postgres

Installation Keploy

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 https://raw.githubusercontent.com/keploy/keploy/main/keploy.sh && source keploy.sh
 keploy

Starting the PostgreSQL Instance

# Start the application
docker-compose up -d

Setting Django Application

This is a one time setup of django application.

python3 -m virtualenv venv
source venv/bin/activate
pip3 install -r requirements.txt
python3 manage.py makemigrations
python3 manage.py migrate

Capture the Testcases

This command will start the recording of API calls using ebpf:-

sudo -E keploy record -c "python3 manage.py runserver"

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

Generate testcases

To generate testcases we just need to make some API calls. You can use Postman, Hoppscotch, or simply curl

Make a POST request

curl --location 'http://127.0.0.1:8000/user/' \
--header 'Content-Type: application/json' \
--data-raw '    {
        "name": "Jane Smith",
        "email": "jane.smith@example.com",
        "password": "smith567",
        "website": "www.janesmith.com"
    }'
curl --location 'http://127.0.0.1:8000/user/' \
--header 'Content-Type: application/json' \
--data-raw '    {
        "name": "John Doe",
        "email": "john.doe@example.com",
        "password": "john567",
        "website": "www.johndoe.com"
    }'

Make a GET request to get all the data

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

This will return all the data saved in the database.

Make a GET request to get a specific data

curl --location 'http://127.0.0.1:8000/user/c793c752-ad95-4cff-8cbe-5715a1e8a76e/'

Make a PUT request to update a specific data

curl --location --request PUT 'http://127.0.0.1:8000/user/efbe12df-3cae-4cbc-b045-dc74840aa82b/' \
--header 'Content-Type: application/json' \
--data-raw '    {
        "name": "Jane Smith",
        "email": "smith.jane@example.com",
        "password": "smith567",
        "website": "www.smithjane.com"
    }'

Make a DELETE request to delete a specific data

curl --location --request DELETE 'http://127.0.0.1:8000/user/ee2af3fc-0503-4a6a-a452-b7d8c87a085b/'

Now both 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.

Run the Testcases

Now let's run the application in test mode.

sudo -E keploy test -c "python3 manage.py runserver" --delay 10

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 😄