Python-powered Chat Apps with Twilio and SendGrid Transcripts
Chapter: Creating the Flask Python web app
Lecture: Concept: Creating an HTTP JSON API
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We saw how to call an API from Twilio studio. But how do we create one? Well, we're going to use Python and flask,
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and it's really, really straight forward, but we're going to define a Python function called cake_order(). You call it whatever you want.
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This name actually is only needs to be making sense. You it's not used publicly. We're going to add a route. And we used to blueprints this properly,
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separate our code and not just jam it into one giant file. So blueprint.route give it the URL until it accepts posts.
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Remember? That's what we were doing over in studio. We said we're going to post JSON body, so make sure we set it to be post.
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Then we need to get the data submitted. My twilio studio. So we say flask,
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request get JSON. That gives us a Python dictionary equivalent of what we had over
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there Is that JSON document, we used pydantic to convert and validate that model that data
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So we created an order model and it had a cake and a customer and a price and so on. So we just take the data and this double *
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thing means take a dictionary and converted to keyword arguments, passed to the constructor or initializer here that generates the model data,
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which is all validated and verified. We had this user service which recorded the order and created the user if necessary.
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So we passed over things like the cake customer and price. And then finally we create a response because, remember, Twilio Studio wants to say,
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thanks that worked, your order was accepted and your orderid is 700 or whatever it is. So then we're going to pass that back,
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and because we want to have a dictionary and not a pydantic models return, we have to say response.dict And that's all we do.
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This is all of it, except it's not because maybe something goes wrong.
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Maybe they submitted the wrong data and that model validation that order model **data Maybe it says, Whoa,
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the customer part is missing. That's not going to work. That would look like our service crashed. But the problem really is what they submitted right.
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In order to communicate that back, we put this into a try except section, and then we send back some kind of error here.
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We're just saying error code 500. But we could also catch a validation error out of pydantic and say, That's a 400 or 422,
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you know, invalid data was passed in all sorts of things like that. We could have different error exceptions and send those back.
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But the main takeaways come up with their body, come up with the error code. That's the status code. And then we just say,
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flask.response. Give it the JSON has text, set the status code, set the mimetype application, JSON, and send it right back to them.
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That's it. That's the entire order, API implementation. And this is how studio and our Python flask application work
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together to hand of the ordering process.