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flask-mongo

README.md

Flask-Mongo Sample Application

This application is a simple student management API built using Python's Flask framework and MongoDB for data storage. It allows you to perform basic CRUD (Create, Read, Update, Delete) operations on student records. The API supports CORS (Cross-Origin Resource Sharing) to facilitate cross-domain requests.

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! 🎢

Pre-Requisite 🛠️

  • Install WSL (wsl --install) for Windows Windows.

Optional 🛠️

  • Install Colima( brew install colima && colima start ) for MacOS MacOs.

Install Keploy

  • Install Keploy CLI using the following command:
curl -O -L https://keploy.io/install.sh && source install.sh

Get Started! 🎬

Setup the MongoDB Database 📦

Create a docker network, run -

docker network create backend

Start the MongoDB instance-

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

Clone a simple Student Management API 🧪

git clone https://github.com/keploy/samples-python.git && cd samples-python/flask-mongo
pip3 install -r requirements.txt

Installation 📥

With Docker 🎥

Build the app image:

docker build -t flask-app:1.0 .

Capture the test-cases-

keploy record -c "docker run -p 6000:6000 --name flask-app --network backend flask-app:1.0"

🔥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

Let's add one more student:

curl -X POST -H "Content-Type: application/json" -d '{"student_id": "12346", "name": "Alice Green", "age": 22}' http://localhost:6000/students

2. Make a GET request

curl http://localhost:6000/students

3. Make a PUT request

curl -X PUT -H "Content-Type: application/json" -d '{"name": "Jane Smith", "age": 21}' http://localhost:6000/students/12345

4. Make a GET request

curl http://localhost:6000/students/12345

5. Make a DELETE request

curl -X DELETE http://localhost:6000/students/12345

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 test-1.yml and mocks.yml.

version: api.keploy.io/v1beta2
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: "56"
      Content-Type: application/json
      Host: localhost:6000
      User-Agent: curl/7.81.0
    body: '{"student_id": "12344", "name": "John Doeww", "age": 10}'
    body_type: ""
    timestamp: 2023-11-13T13:02:32.241333562Z
  resp:
    status_code: 200
    header:
      Content-Length: "48"
      Content-Type: application/json
      Date: Mon, 13 Nov 2023 13:02:32 GMT
      Server: Werkzeug/2.2.2 Python/3.9.18
    body: |
      {
        "message": "Student created successfully"
      }
    body_type: ""
    status_message: ""
    proto_major: 0
    proto_minor: 0
    timestamp: 2023-11-13T13:02:34.752123715Z
  objects: []
  assertions:
    noise:
      - header.Date
  created: 1699880554
curl: |-
  curl --request POST \
    --url http://localhost:6000/students \
    --header 'Host: localhost:6000' \
    --header 'User-Agent: curl/7.81.0' \
    --header 'Accept: */*' \
    --header 'Content-Type: application/json' \
    --data '{"student_id": "12344", "name": "John Doeww", "age": 10}'

This is how mocks.yml generated would look like:-

version: api.keploy.io/v1beta2
kind: Mongo
name: mocks
spec:
  metadata:
    operation: '{ OpMsg flags: 0, sections: [{ SectionSingle msg: {"find":"students","filter":{"student_id":"12345"},"projection":{"_id":{"$numberInt":"0"}},"limit":{"$numberInt":"1"},"singleBatch":true,"lsid":{"id":{"$binary":{"base64":"vPKsEFRdTLytlbnyVimqIA==","subType":"04"}}},"$db":"studentsdb"} }], checksum: 0 }'
  requests:
    - header:
        length: 187
        requestId: 2127584089
        responseTo: 0
        Opcode: 2013
      message:
        flagBits: 0
        sections:
          - '{ SectionSingle msg: {"find":"students","filter":{"student_id":"12345"},"projection":{"_id":{"$numberInt":"0"}},"limit":{"$numberInt":"1"},"singleBatch":true,"lsid":{"id":{"$binary":{"base64":"vPKsEFRdTLytlbnyVimqIA==","subType":"04"}}},"$db":"studentsdb"} }'
        checksum: 0
      read_delay: 3469848802
  responses:
    - header:
        length: 166
        requestId: 154
        responseTo: 2127584089
        Opcode: 2013
      message:
        flagBits: 0
        sections:
          - '{ SectionSingle msg: {"cursor":{"firstBatch":[{"student_id":"12345","name":"John Doe","age":{"$numberInt":"20"}}],"id":{"$numberLong":"0"},"ns":"studentsdb.students"},"ok":{"$numberDouble":"1.0"}} }'
        checksum: 0
      read_delay: 869555
  created: 1699880576
  reqTimestampMock: 2023-11-13T13:02:56.385067848Z
  resTimestampMock: 2023-11-13T13:02:56.386374941Z

Want to see if everything works as expected?

Run Tests

Time to put things to the test 🧪

keploy test -c "sudo docker run -p 6000:6000 --rm --network backend --name flask-app flask-app:1.0" --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 In 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 (PostgreSQL) chill on Docker. Ready? Let's get the party started!🎉

📼 Roll the Tape - Recording Time!

Install the dependencies:

pip install -r requirements.txt

Now, let's Capture the test-cases-

In app.py, replace the MongoDB connection URL with - mongodb://0.0.0.0:27017/

Ready, set, record! Here's how:

keploy record -c "python3 app.py"

Keep an eye out for the -c flag! It's the command charm to run the app.

Alright, magician! With the app alive and kicking, let's weave some test cases. The spell? Making some API calls! Postman, Hoppscotch, or the classic curl - pick your wand.

Generate testcases

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

1. Make a POST request

```bash

curl -X POST -H "Content-Type: application/json" -d '{"student_id": "12345", "name": "John Doe", "age": 20}' http://localhost:6000/students


Let's add one more student: 

```sh
curl -X POST -H "Content-Type: application/json" -d '{"student_id": "12346", "name": "Alice Green", "age": 22}' http://localhost:6000/students

2. Make a GET request

curl http://localhost:6000/students

3. Make a PUT request

curl -X PUT -H "Content-Type: application/json" -d '{"name": "Jane Smith", "age": 21}' http://localhost:6000/students/12345

4. Make a GET request

curl http://localhost:6000/students/12345

5. Make a DELETE request

curl -X DELETE http://localhost:6000/students/12345

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 test-1.yml and mocks.yml.

version: api.keploy.io/v1beta2
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: "56"
      Content-Type: application/json
      Host: localhost:6000
      User-Agent: curl/7.81.0
    body: '{"student_id": "12344", "name": "John Doeww", "age": 10}'
    body_type: ""
    timestamp: 2023-11-13T13:02:32.241333562Z
  resp:
    status_code: 200
    header:
      Content-Length: "48"
      Content-Type: application/json
      Date: Mon, 13 Nov 2023 13:02:32 GMT
      Server: Werkzeug/2.2.2 Python/3.9.18
    body: |
      {
        "message": "Student created successfully"
      }
    body_type: ""
    status_message: ""
    proto_major: 0
    proto_minor: 0
    timestamp: 2023-11-13T13:02:34.752123715Z
  objects: []
  assertions:
    noise:
      - header.Date
  created: 1699880554
curl: |-
  curl --request POST \
    --url http://localhost:6000/students \
    --header 'Host: localhost:6000' \
    --header 'User-Agent: curl/7.81.0' \
    --header 'Accept: */*' \
    --header 'Content-Type: application/json' \
    --data '{"student_id": "12344", "name": "John Doeww", "age": 10}'

This is how mocks.yml generated would look like:-

version: api.keploy.io/v1beta2
kind: Mongo
name: mocks
spec:
  metadata:
    operation: '{ OpMsg flags: 0, sections: [{ SectionSingle msg: {"find":"students","filter":{"student_id":"12345"},"projection":{"_id":{"$numberInt":"0"}},"limit":{"$numberInt":"1"},"singleBatch":true,"lsid":{"id":{"$binary":{"base64":"vPKsEFRdTLytlbnyVimqIA==","subType":"04"}}},"$db":"studentsdb"} }], checksum: 0 }'
  requests:
    - header:
        length: 187
        requestId: 2127584089
        responseTo: 0
        Opcode: 2013
      message:
        flagBits: 0
        sections:
          - '{ SectionSingle msg: {"find":"students","filter":{"student_id":"12345"},"projection":{"_id":{"$numberInt":"0"}},"limit":{"$numberInt":"1"},"singleBatch":true,"lsid":{"id":{"$binary":{"base64":"vPKsEFRdTLytlbnyVimqIA==","subType":"04"}}},"$db":"studentsdb"} }'
        checksum: 0
      read_delay: 3469848802
  responses:
    - header:
        length: 166
        requestId: 154
        responseTo: 2127584089
        Opcode: 2013
      message:
        flagBits: 0
        sections:
          - '{ SectionSingle msg: {"cursor":{"firstBatch":[{"student_id":"12345","name":"John Doe","age":{"$numberInt":"20"}}],"id":{"$numberLong":"0"},"ns":"studentsdb.students"},"ok":{"$numberDouble":"1.0"}} }'
        checksum: 0
      read_delay: 869555
  created: 1699880576
  reqTimestampMock: 2023-11-13T13:02:56.385067848Z
  resTimestampMock: 2023-11-13T13:02:56.386374941Z

On terminal we can see the testcases generated -

keploy testcases

Run Tests

Time to put things to the test 🧪

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

keploy testrun

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! ✨👩‍💻👨‍💻✨