Skip to content

django-postgres

Directory actions

More options

Directory actions

More options

Latest commit

 

History

History
 
 

django-postgres

Folders and files

NameName
Last commit message
Last commit date

parent directory

..
django_postgres
django_postgres
 
 
README.md
README.md
 
 
data.json
data.json
 
 

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

1. AMD Architecture

curl --silent --location "https://github.com/keploy/keploy/releases/latest/download/keploy_linux_amd64.tar.gz" | tar xz -C /tmp

sudo mkdir -p /usr/local/bin && sudo mv /tmp/keploy /usr/local/bin && keploy
2. ARM Architecture 
curl --silent --location "https://github.com/keploy/keploy/releases/latest/download/keploy_linux_arm64.tar.gz" | tar xz -C /tmp

sudo mkdir -p /usr/local/bin && sudo mv /tmp/keploy /usr/local/bin && 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 😄