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Version: 3.0.0

Sample Task Creation CRUD App (Flask)

Introduction

🪄 Dive into the world of Student CRUD Apps and see how seamlessly Keploy integrated with Flask and MongoDB Buckle up, it's gonna be a fun ride! 🎢

Clone a simple Student Management API 🧪

git clone https://github.com/keploy/samples-python.git && cd samples-python/flask-mongo

How to run the sample application Using Docker Compose 🐳

Note: Before getting started, make sure Keploy is installed on your machine.

We will be using Docker compose to run the application as well as Mongo on Docker container.

Lights, Camera, Record! 🎥

Capture the test-cases-

keploy record -c "docker compose up" --container-name "flask-app" --buildDelay 50

🔥Make some API calls. Postman, Hoppscotch or even curl - take your pick!

Let's make URLs short and sweet:

Generate testcases

To generate testcases we just need to make some API calls.

  1. Make a POST request:
curl -X POST -H "Content-Type: application/json" -d '{"student_id": "12345", "name": "John Doe", "age": 20}' http://localhost:6000/students
  1. Make a GET request:
curl http://localhost:6000/students
  1. Make a PUT request:
curl -X PUT -H "Content-Type: application/json" -d '{"name": "Jane Smith", "age": 21}' http://localhost:6000/students/12345
  1. Make a DELETE request:
curl -X DELETE http://localhost:6000/students/12345

And once you are done, you can stop the recording and give yourself a pat on the back! With that simple spell, you've conjured up a test case with a mock! Explore the keploy directory and you'll discover your handiwork in tests directory and mocks.yml.

Want to see if everything works as expected?

Run Tests

Time to put things to the test 🧪

keploy test -c "docker compose up" --container-name "flask-app" --buildDelay 50 --delay 10

The --delay flag? Oh, that's just giving your app a little breather (in seconds) before the test cases come knocking.

How to Run the App Locally on Linux/WSL 🐧

Note: Before getting started, make sure Keploy is installed on your machine.

Introduction

🪄 Dive into the world of Student CRUD Apps and see how seamlessly Keploy integrated with Flask and MongoDB Buckle up, it's gonna be a fun ride! 🎢

Clone a simple Student Management API 🧪

git clone https://github.com/keploy/samples-python.git && cd samples-python/flask-mongo

We'll be running our sample application right on Linux, but just to make things a tad more thrilling, we'll have the database (MongoDB) chill on Docker. Ready? Let's get the party started!🎉

Install all dependencies

pip install -r requirements.txt

Start the MongoDB container

docker run -p 27017:27017 -d --network backend --name mongo mongo

Since we are using a MongoDB container, we need to update the client on line 11 in app.py, to localhost.

Lights, Camera, Record! 🎥

To initiate the recording of API calls, execute this command in your terminal:

keploy record -c "python3 app.py"

Now, your app will start running, and you have to make some API calls to generate the test cases!!

  1. Make a POST request:
curl -X POST -H "Content-Type: application/json" -d '{"student_id": "12345", "name": "John Doe", "age": 20}' http://localhost:6000/students
  1. Make a GET request:
curl http://localhost:6000/students
  1. Make a PUT request:
curl -X PUT -H "Content-Type: application/json" -d '{"name": "Jane Smith", "age": 21}' http://localhost:6000/students/12345
  1. Make a DELETE request:
curl -X DELETE http://localhost:6000/students/12345

And once you are done, you can stop the recording and give yourself a pat on the back! With that simple spell, you've conjured up a test case with a mock! Explore the keploy directory and you'll discover your handiwork in tests directory and mocks.yml.

Run the tests

Now, it's time to put things to the test 🧪

keploy test -c "python3 app.py" --delay 10

Now, you can also try different API calls, tweak the DB response in the mocks.yml, or fiddle with the request or response in test-x.yml. Run the tests again and see the magic unfold!

Check Test Coverage

We have a test-app.py where all the unit test cases has been written. Now using Keploy, we can check it's code coverage!! Now to run your unit tests with Keploy, you can run the command given below:

python3 -m coverage run -p --data-file=.coverage.unit -m pytest -s test_keploy.py test_app.py

To combine the coverage from the unit tests, and Keploy's API tests we can use the command below:

python3 -m coverage combine

Finally, to generate the coverage report for the test run, you can run:

python3 -m coverage report

and if you want the coverage in an html file, you can run:

python3 -m coverage html

Wrapping it up 🎉

Congrats on the journey so far! You've seen Keploy's power, flexed your coding muscles, and had a bit of fun too! Now, go out there and keep exploring, innovating, and creating! Remember, with the right tools and a sprinkle of fun, anything's possible.😊🚀

Hope this helps you out, if you still have any questions, reach out to us .

Question? 🤔💭

For any support please join keploy slack community to get help from fellow users, or book a demo if you're exploring enterprise use cases.