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Getting Started with MongoDB and Sanic

Aaron Bassett5 min read • Published Feb 05, 2022 • Updated Sep 23, 2022
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Sanic is a Python 3.6+ async web server and web framework that's written to go fast. The project's goal is to provide a simple way to get up and running a highly performant HTTP server that is easy to build, to expand, and ultimately to scale.
Unfortunately, because of its name and dubious choices in ASCII art, Sanic wasn't seen by some as a serious framework, but it has matured. It is worth considering if you need a fast, async, Python framework.
In this quick start, we will create a CRUD (Create, Read, Update, Delete) app showing how you can integrate MongoDB with your Sanic projects.


  • Python 3.9.0
  • A MongoDB Atlas cluster. Follow the "Get Started with Atlas" guide to create your account and MongoDB cluster. Keep a note of your username, password, and connection string as you will need those later.

Running the Example

You will need to install a few dependencies: Sanic, Motor, etc. I always recommend that you install all Python dependencies in a virtualenv for the project. Before running pip, ensure your virtualenv is active.
It may take a few moments to download and install your dependencies. This is normal, especially if you have not installed a particular package before.
Once you have installed the dependencies, you need to create an environment variable for your MongoDB connection string.
Remember, anytime you start a new terminal session, you will need to set this environment variable again. I use direnv to make this process easier.
The final step is to start your Sanic server.
Screenshot of terminal running Sanic
Once the application has started, you can view it in your browser at There won't be much to see at the moment as you do not have any data! We'll look at each of the end-points a little later in the tutorial, but if you would like to create some data now to test, you need to send a POST request with a JSON body to the local URL.
Try creating a few students via these POST requests, and then refresh your browser.

Creating the Application

All the code for the example application is within I'll break it down into sections and walk through what each is doing.

Setting Up Our App and MongoDB Connection

We're going to use the sanic-motor package to wrap our motor client for ease of use. So, we need to provide a couple of settings when creating our Sanic app.
Sanic-motor's models are unlikely to be very similar to any other database models you have used before. They do not describe the schema, for example. Instead, we only specify the collection name.

Application Routes

Our application has five routes:
  • POST / - creates a new student.
  • GET / - view a list of all students.
  • GET /{id} - view a single student.
  • PUT /{id} - update a student.
  • DELETE /{id} - delete a student.

Create Student Route

Note how I am converting the ObjectId to a string before assigning it as the _id. MongoDB stores data as BSON. However, we are encoding and decoding our data as JSON strings. BSON has support for additional non-JSON-native data types, including ObjectId. JSON does not. Because of this, for simplicity, we convert ObjectIds to strings before storing them.
The create_student route receives the new student data as a JSON string in a POST request. Sanic will automatically convert this JSON string back into a Python dictionary which we can then pass to the sanic-motor wrapper.
The insert_one method response includes the _id of the newly created student. After we insert the student into our collection, we use the inserted_id to find the correct document and return it in the json_response.
sanic-motor returns the relevant model objects from any find method, including find_one. To override this behaviour, we specify as_raw=True.
Read Routes
The application has two read routes: one for viewing all students, and the other for viewing an individual student.
In our example code, we are not placing any limits on the number of students returned. In a real application, you should use sanic-motor's page and per_page arguments to paginate the number of students returned.
The student detail route has a path parameter of id, which Sanic passes as an argument to the show_student function. We use the id to attempt to find the corresponding student in the database. The conditional in this section is using an assignment expression, a recent addition to Python (introduced in version 3.8) and often referred to by the incredibly cute sobriquet "walrus operator."
If a document with the specified id does not exist, we raise a NotFound exception which will respond to the request with a 404 response.
Update Route
The update_student route is like a combination of the create_student and the show_student routes. It receives the id of the document to update as well as the new data in the JSON body.
We attempt to $set the new values in the correct document with update_one, and then check to see if it correctly modified a single document. If it did, then we find that document that was just updated and return it.
If the modified_count is not equal to one, we still check to see if there is a document matching the id. A modified_count of zero could mean that there is no document with that id. It could also mean that the document does exist but it did not require updating as the current values are the same as those supplied in the PUT request.
It is only after that final find fail when we raise a 404 Not Found exception.
Delete Route
Our final route is delete_student. Again, because this is acting upon a single document, we have to supply an id in the URL. If we find a matching document and successfully delete it, then we return an HTTP status of 204 or "No Content." In this case, we do not return a document as we've already deleted it! However, if we cannot find a student with the specified id, then instead, we return a 404.

Wrapping Up

I hope you have found this introduction to Sanic with MongoDB useful. If you would like to find out more about Sanic, please see their documentation. Unfortunately, documentation for sanic-motor is entirely lacking at this time. But, it is a relatively thin wrapper around the MongoDB Motor driver—which is well documented—so do not let that discourage you.
To see how you can integrate MongoDB with other async frameworks, check out some of the other Python posts on the MongoDB developer portal.
If you have questions, please head to our developer community website where the MongoDB engineers and the MongoDB community will help you build your next big idea with MongoDB.

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Table of Contents
  • Prerequisites