Data Validation

Often, if not always, you want to validate an incoming payload to ensure it is passing the necessary parameters. If parameters are missing, you can fast-fail with an InvalidInput-like exception to quickly let the requester know the payload is malformed. Documented below is a simple way to do such validation.

from flask import Flask 
from flask import request
from flask import jsonify

app = Flask(__name__)

@app.route("/create", methods=["POST"])
def create(): 
    payload = request.get_json()
    person: Person = Person(payload)
    return jsonify({"status": "ok"})


class Person: 
    def __init__(self, args): 
        try: 
            self.name = args["name"]
            self.age = args["age"]
            self.address = args.get("address") 

        except Exception as ex:
            raise InvalidInput()


if __name__ == "__main__": 
    app.run(host="0.0.0.0", debug=True, port=8888)

All it consists of is a class whose __init__ sets the parameters according to what is in the payload. If such a value does not exist, an error is thrown. Also notice that in this model parameters can be required or optional.

Unfortunately, this does not validate against extraneous data - it only checks that the required parameters were provided.

This is a rather rudimentary method of data validation and for more complicated validations (including extraneous data validations) using pydantic is preferred.

Maybe the next blog will cover pydantic.

Until then,

Happy coding! 🛂

P.S. Pydantic extraneous data validation check is here