MongoDB with Async Python Course
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Source code and course GitHub repositorygithub.com/talkpython/mongodb-for-async-python-course
What's this course about and how is it different?
This course will teach you how to use MongoDB and document databases to build simpler and faster data-driven applications.
We start by explaining the origin and major concepts of NoSQL and document databases. You then learn how to work with MongoDB from its native shell as well as many of the CLI and GUI management tools.
Many MongoDB courses stop there. This course is meant to be a practical end-to-end coverage of MongoDB. We go beyond scratching the surface by covering real-world topics.
You'll see how to use Beanie (a popular ODM for MongoDB - think ORM for NoSQL) to map classes to MongoDB. Beanie is based on state-of-the-art Python technologies such as Pydantic and Python's async and await.
In this code-based and hands-on, demo-driven course, we will build some simple example apps using Beanie. Then we'll move on to modeling real PyPI data with 100,000s of records in MongoDB. Once we have our Python code working with the PyPI data, we'll build out a full FastAPI API around the data showing the smooth integration of Beanie and async MongoDB within FastAPI.
After we master working with MongoDB from Python, we'll turn our attention to performance. We take a large database with millions of data points and make it run hundreds of times faster than you get out-of-the-box with MongoDB. We test our performance changes with both custom Python code and the Locust load testing framework.
We wrap up the course by deploying MongoDB to production Linux servers. There are a few very important steps to getting MongoDB running in production and we'll go step-by-step through this setup.
In the end, you'll be ready to start building and running high-performance, MongoDB-backed, data-driven applications.
View the full course outline.
What will you learn?
In this course, you will:
- How document databases, such as MongoDB, work
- Where MongoDB fits in the larger scope of databases used in the world
- How to install and configure MongoDB and several management tools and GUIs
- A basic set of MongoDB's native shell commands and queries
- Foundational technologies such as Pydantic and Python's async and await
- How to design data models with Beanie and Pydantic
- Understand the tradeoffs when modeling data with documents
- Learn when it's a good idea (and when it's a bad one) to embed data within other records
- Use ORM-style programming with MongoDB and Beanie
- Use more efficient "in-place" operations such as addToSet with Beanie
- Design projection classes in Pydantic for improved performance
- How to safely store user accounts (namely passwords) in MongoDB
- To deeply integrate Beanie and MongoDB with FastAPI
- Create complex indexes in MongoDB from Beanie for 1000x performance boosts
- Use indexes to enforce data integrity in MongoDB
- Safely deploy MongoDB in a self-hosted environment within a cloud provider on multiple Linux machines
- Use the load testing framework Locust to probe and test the performance limits of your MongoDB-based web APIs
And lots more
View the full course outline.
Who is this course for?
For anyone who wants to use the latest Python technologies to work with MongoDB.
As for prerequisites, we assume:
- Basic familiarity with the Python programming language and core tools (e.g. pip)
- That you have very minimal understanding and experience with some database technology (relational or NoSQL)
The tools chosen and featured during this course are 100% free and most of them are open source or have free and solid alternatives.
Concepts backed by concise visuals
While exploring a topic interactively with demos and live code is very engaging, it can lose the forest for the trees. That's why when we hit a new topic, we stop and discuss it with concise and clear visuals.
Here's an example that visually compares the top-level data in a document database to the embedded and nested objects within that same record for MongoDB.
Follow along with subtitles and transcripts
Each course comes with subtitles and full transcripts. The transcripts are available as a separate searchable page for each lecture. They also are available in course-wide search results to help you find just the right lecture.
Who am I? Why should you take my course?
My name is Michael, nice to meet you. ;) There are a couple of reasons I'm especially qualified to teach you Python.
1. I'm the host of the #1 podcast on Python called Talk Python To Me. Over there, I've interviewed many of the leaders and creators in the Python community. I bring that perspective to all the courses I create.
2. I've been a professional software trainer for over 10 years. I have taught literally thousands of professional developers in hundreds of courses throughout the world.
3. Students have loved my courses. Here are just a few quotes from past students of mine.
"Michael is super knowledgeable, loves his craft, and he conveys it all well. I would highly recommend his training class anytime." - Robert F.
"Michael is simply an outstanding instructor." - Kevin R.
"Michael was an encyclopedia for the deep inner workings of Python. Very impressive." - Neal L.
Free office hours keep you from getting stuck
One of the challenges of self-paced online learning is getting stuck. It can be hard to get the help you need to get unstuck.
That's why at Talk Python Training, we offer live, online office hours. You drop in and join a group of fellow students to chat about your course progress and see solutions via screen sharing.
Just visit your account page to see the upcoming office hour schedule.
This course is delivered in very high resolution
This course is delivered in 1440p (4x the pixels as 720p). When you're watching the videos for this course, it will feel like you're sitting next to the instructor looking at their screen.
Every little detail, menu item, and icon is clear and crisp. Watch the introductory video at the top of this page to see an example.
The time to act is now
MongoDB is one of the most wanted and loved databases. It's far and away the most popular document database. This course presents the best, most cutting-edge frameworks for building MongoDB powered apps with Python. Dive in to learn the skills you need gain true mastery over MongoDB.