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Version: 3.0.0

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! 🎢

🛠️ Platform-Specific Requirements for Keploy​

Below is a table summarizing the tools needed for both native and Docker installations of Keploy on MacOS, Windows, and Linux:

Operating SystemWithout DockerDocker InstallationPrerequisites
MacOS MacOSGuideGuide- Docker Desktop version must be 4.25.2 or above
Windows WindowsSupportedSupported- Use WSL wsl --install
- Windows 10 version 2004 and higher (Build 19041 and higher) or Windows 11
Linux LinuxSupportedSupportedLinux kernel 5.15 or higher

On MacOS and Windows, additional tools are required for Keploy due to the lack of native eBPF support.

Keploy Installation​

Quick Installation Using CLI​

Let's get started by setting up the Keploy alias with this command:

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

You should see something like this:

       ▓██▓▄
    ▓▓▓▓██▓█▓▄
     ████████▓▒
          ▀▓▓███▄      ▄▄   ▄               ▌
         ▄▌▌▓▓████▄    ██ ▓█▀  ▄▌▀▄  ▓▓▌▄   ▓█  ▄▌▓▓▌▄ ▌▌   ▓
       ▓█████████▌▓▓   ██▓█▄  ▓█▄▓▓ ▐█▌  ██ ▓█  █▌  ██  █▌ █▓
      ▓▓▓▓▀▀▀▀▓▓▓▓▓▓▌  ██  █▓  ▓▌▄▄ ▐█▓▄▓█▀ █▓█ ▀█▄▄█▀   █▓█
       ▓▌                           ▐█▌                   █▌
        ▓

Keploy CLI

Available Commands:
  example           Example to record and test via keploy
  config --generate generate the keploy configuration file
  record            record the keploy testcases from the API calls
  test              run the recorded testcases and execute assertions
  update            Update Keploy

Flags:
      --debug     Run in debug mode
  -h, --help      help for keploy
  -v, --version   version for keploy

Use "keploy [command] --help" for more information about a command.

🎉 Wohoo! You are all set to use Keploy.

Other Installation Methods​

Install using Docker

Downloading and running Keploy in Docker

On macOS​

Note : Keploy is not supported natively on MacOS, so you can follow the below method to run with docker

  1. Open up a terminal window.

  2. Create a bridge network in Docker using the following docker network create command:

docker network create keploy-network
  1. Install Keploy
 curl --silent -O -L https://keploy.io/install.sh && source install.sh

Examples:​

Record:

keploy record -c "docker run -p 8080:8080 --name <containerName> --network keploy-network <applicationImage>" --container-name "<containerName>" --buildDelay 60

Test:

keploy test --c "docker run -p 8080:8080 --name <containerName> --network keploy-network <applicationImage>" --delay 10 --buildDelay 60
Install Natively

Downloading and running Keploy in Native

Prequisites:

  • Linux Kernel version 5.15 or higher
  • Run uname -a to verify the system architecture.
  • In case of Windows, use WSL with Ubuntu 20.04 LTS or higher.
Downloading and running Keploy On WSL/Linux AMD

On WSL/Linux AMD​

  1. Open the terminal Session.
  2. Run the following command to download and install Keploy:
curl --silent --location "https://github.com/keploy/keploy/releases/latest/download/keploy_linux_amd64.tar.gz" | tar xz --overwrite -C /tmp
sudo mkdir -p /usr/local/bin && sudo mv /tmp/keploy /usr/local/bin/keploy

On WSL/Linux ARM​

  1. Open the terminal Session
  2. Run the following command to download and install Keploy:
curl --silent --location "https://github.com/keploy/keploy/releases/latest/download/keploy_linux_arm64.tar.gz" | tar xz --overwrite -C /tmp
sudo mkdir -p /usr/local/bin && sudo mv /tmp/keploy /usr/local/bin/keploy

Note: Keploy is not supported on MacOS natively.

Setting up the Docker Desktop for WSL 2

  1. Install Docker Desktop for Windows from here.

When developing on Windows with Docker Desktop and WSL 2, it's crucial to configure Docker Desktop to allow WSL 2 distributions to access the Docker daemon. This setup enables seamless integration between your Windows environment, WSL 2 Linux distros, and Docker.

By default, Docker Desktop may not be configured to work with all WSL 2 distros out of the box. Proper configuration ensures that you can run Docker commands from within your WSL 2 environment, allowing for a more native Linux development experience while leveraging the power of Windows.

This setup is essential for Keploy to function correctly in a WSL 2 environment, as it needs to interact with the Docker daemon to manage containers and networks effectively. For detailed instructions on how to configure Docker Desktop for WSL 2, please refer to the official Docker documentation.

Get Started! 🎬​

Clone a simple Student Management API 🧪​

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

Installation Keploy​

Depending on your OS, choose your adventure:

There are 2 ways you can run this sample application.

Using Docker Compose 🐳​

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.

# Generated by Keploy (2.4.16)
version: api.keploy.io/v1beta1
kind: Http
name: test-1
spec:
  metadata: {}
  req:
    method: POST
    proto_major: 1
    proto_minor: 1
    url: http://localhost:6000/students
    header:
      Accept: "*/*"
      Content-Length: "54"
      Content-Type: application/json
      Host: localhost:6000
      User-Agent: curl/8.7.1
    body: '{"student_id": "12345", "name": "John Doe", "age": 20}'
    timestamp: 2025-04-02T13:12:05.255523333Z
  resp:
    status_code: 200
    header:
      Content-Length: "48"
      Content-Type: application/json
      Date: Wed, 02 Apr 2025 13:12:05 GMT
      Server: Werkzeug/2.2.2 Python/3.9.21
    body: |
      {
        "message": "Student created successfully"
      }
    status_message: OK
    proto_major: 0
    proto_minor: 0
    timestamp: 2025-04-02T13:12:07.292707847Z
  objects: []
  assertions:
    noise:
      header.Date: []
  created: 1743599527
curl: |-
  curl --request POST \
    --url http://localhost:6000/students \
    --header 'Host: localhost:6000' \
    --header 'User-Agent: curl/8.7.1' \
    --header 'Accept: */*' \
    --header 'Content-Type: application/json' \
    --data "{\"student_id\": \"12345\", \"name\": \"John Doe\", \"age\": 20}"

This is how the mocks.yml looks like:

version: api.keploy.io/v1beta1
kind: Mongo
name: mock-0
spec:
  metadata:
    operation: '{ OpQuery flags: [], fullCollectionName: admin.$cmd, numberToSkip: 0, numberToReturn: -1, query: {"ismaster": {"$numberInt":"1"},"helloOk": true,"client": {"driver": {"name": "PyMongo","version": "4.4.1"},"os": {"type": "Linux","name": "Linux","architecture": "aarch64","version": "6.1.0-32-cloud-arm64"},"platform": "CPython 3.9.21.final.0"}}, returnFieldsSelector:  }'
    type: config
  requests:
    - header:
        length: 269
        requestId: 846930886
        responseTo: 0
        Opcode: 2004
      message:
        flags: 0
        collection_name: admin.$cmd
        number_to_skip: 0
        number_to_return: -1
        query: '{"ismaster":{"$numberInt":"1"},"helloOk":true,"client":{"driver":{"name":"PyMongo","version":"4.4.1"},"os":{"type":"Linux","name":"Linux","architecture":"aarch64","version":"6.1.0-32-cloud-arm64"},"platform":"CPython 3.9.21.final.0"}}'
        return_fields_selector: ""
  responses:
    - header:
        length: 329
        requestId: 3
        responseTo: 846930886
        Opcode: 1
      message:
        response_flags: 8
        cursor_id: 0
        starting_from: 0
        number_returned: 1
        documents:
          - '{"helloOk":true,"ismaster":true,"topologyVersion":{"processId":{"$oid":"67ed3773a2f7dd8385defa99"},"counter":{"$numberLong":"0"}},"maxBsonObjectSize":{"$numberInt":"16777216"},"maxMessageSizeBytes":{"$numberInt":"48000000"},"maxWriteBatchSize":{"$numberInt":"100000"},"localTime":{"$date":{"$numberLong":"1743599485435"}},"logicalSessionTimeoutMinutes":{"$numberInt":"30"},"connectionId":{"$numberInt":"1"},"minWireVersion":{"$numberInt":"0"},"maxWireVersion":{"$numberInt":"25"},"readOnly":false,"ok":{"$numberDouble":"1.0"}}'
      read_delay: 990489
  created: 1743599485
  reqTimestampMock: 2025-04-02T13:11:25.434864042Z
  resTimestampMock: 2025-04-02T13:11:25.436114528Z

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.

Final thoughts? Dive deeper! 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!✨👩‍💻👨‍💻✨

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. 😊🚀

Happy coding! ✨👩‍💻👨‍💻✨

Running App Locally on Linux/WSL 🐧​

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.

version: api.keploy.io/v1beta1
kind: Http
name: test-1
spec:
  metadata: {}
  req:
    method: POST
    proto_major: 1
    proto_minor: 1
    url: http://localhost:6000/students
    header:
      Accept: "*/*"
      Content-Length: "54"
      Content-Type: application/json
      Host: localhost:6000
      User-Agent: curl/8.7.1
    body: '{"student_id": "12345", "name": "John Doe", "age": 20}'
    timestamp: 2025-04-02T13:12:05.255523333Z
  resp:
    status_code: 200
    header:
      Content-Length: "48"
      Content-Type: application/json
      Date: Wed, 02 Apr 2025 13:12:05 GMT
      Server: Werkzeug/2.2.2 Python/3.9.21
    body: |
      {
        "message": "Student created successfully"
      }
    status_message: OK
    proto_major: 0
    proto_minor: 0
    timestamp: 2025-04-02T13:12:07.292707847Z
  objects: []
  assertions:
    noise:
      header.Date: []
  created: 1743599527
curl: |-
  curl --request POST \
    --url http://localhost:6000/students \
    --header 'Host: localhost:6000' \
    --header 'User-Agent: curl/8.7.1' \
    --header 'Accept: */*' \
    --header 'Content-Type: application/json' \
    --data "{\"student_id\": \"12345\", \"name\": \"John Doe\", \"age\": 20}"

This is how the mocks.yml looks like:

version: api.keploy.io/v1beta1
kind: Mongo
name: mock-0
spec:
  metadata:
    operation: '{ OpQuery flags: [], fullCollectionName: admin.$cmd, numberToSkip: 0, numberToReturn: -1, query: {"ismaster": {"$numberInt":"1"},"helloOk": true,"client": {"driver": {"name": "PyMongo","version": "4.4.1"},"os": {"type": "Linux","name": "Linux","architecture": "aarch64","version": "6.1.0-32-cloud-arm64"},"platform": "CPython 3.9.21.final.0"}}, returnFieldsSelector:  }'
    type: config
  requests:
    - header:
        length: 269
        requestId: 846930886
        responseTo: 0
        Opcode: 2004
      message:
        flags: 0
        collection_name: admin.$cmd
        number_to_skip: 0
        number_to_return: -1
        query: '{"ismaster":{"$numberInt":"1"},"helloOk":true,"client":{"driver":{"name":"PyMongo","version":"4.4.1"},"os":{"type":"Linux","name":"Linux","architecture":"aarch64","version":"6.1.0-32-cloud-arm64"},"platform":"CPython 3.9.21.final.0"}}'
        return_fields_selector: ""
  responses:
    - header:
        length: 329
        requestId: 3
        responseTo: 846930886
        Opcode: 1
      message:
        response_flags: 8
        cursor_id: 0
        starting_from: 0
        number_returned: 1
        documents:
          - '{"helloOk":true,"ismaster":true,"topologyVersion":{"processId":{"$oid":"67ed3773a2f7dd8385defa99"},"counter":{"$numberLong":"0"}},"maxBsonObjectSize":{"$numberInt":"16777216"},"maxMessageSizeBytes":{"$numberInt":"48000000"},"maxWriteBatchSize":{"$numberInt":"100000"},"localTime":{"$date":{"$numberLong":"1743599485435"}},"logicalSessionTimeoutMinutes":{"$numberInt":"30"},"connectionId":{"$numberInt":"1"},"minWireVersion":{"$numberInt":"0"},"maxWireVersion":{"$numberInt":"25"},"readOnly":false,"ok":{"$numberDouble":"1.0"}}'
      read_delay: 990489
  created: 1743599485
  reqTimestampMock: 2025-04-02T13:11:25.434864042Z
  resTimestampMock: 2025-04-02T13:11:25.436114528Z

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.