Python + Azure Cosmos DB for AI Applications: A Beginner’s Guide

Hello everyone! I am Shibam Goyaland Chanchal Kuntal Microsoft Learn Student Ambassador, I am fascinated by the amazing ways technology is changing the world. I am particularly excited about the potential of AI, which can unlock the power of information to solve complex problems and make our lives easier.

Today we’ll look at a powerful combination. Azure Cosmos DB And Python. This duo can help you build innovative, data-driven AI applications!

Why choose Python?

Python has become an essential language for data-driven applications for several reasons.

• versatility: Python is not limited to a single domain. It thrives in web development, data science, machine learning, scripting, and more. This makes it an invaluable skill for any individual who focuses on technology.
• Easy to learn: Python prioritizes readability, making its syntax easier for beginners to understand compared to other languages.
• Powerful libraries: Python’s extensive ecosystem boasts libraries such as: panda, NumPyand MattplotlipMakes data manipulation, analysis, and visualization incredibly easy.
• High demand: Companies across industries are actively seeking Python developers, and mastering this language opens the door to exciting career opportunities.

The rise of NoSQL and Azure CosmosDB:

Traditional relational databases have long been the standard, but the need for flexibility, scalability, and agility has spurred the rise of NoSQL databases.

Azure Cosmos DB A fully managed NoSQL database service that offers several benefits:

• pliability: CosmosDB is highly customizable to your needs and allows you to store data in JSON, SQL, or other formats, giving you the freedom to choose the approach that best suits your data.
• Scalability: Easily scale your database as needed without sacrificing performance.
• Global Distribution: Deploy your database globally for low-latency access, ideal for applications that require data to be available across multiple locations.
• Seamless integration with Python: CosmosDB is compatible with Python, making it easy to connect, query, and manipulate data.

Let’s look at the basic structure Azure Cosmos DB Account Understand how data is structured.

• account: The top-level container that stores Cosmos DB resources.
• Database: Logical grouping of containers within an account.
• container: Similar to a table in a relational database, it stores actual data.
• Items: An individual data record (document) within a container.

Let’s take a practical look: Exploring the sample notebook

To make all this concrete, let’s look at the following: Azure CosmosDB Samples for NoSQL.

Getting started:

1. Fork the repository: Head to GitHub repo Then click “Fork” to create your own copy of the sample, allowing you to experiment without affecting the original.
2. Fork Clone: use feather Clone the forked repository to your local machine. This is the basis for development.
3. Preferences: that Installing a laptop Shows how to install and link the required libraries. Azure Cosmos DB.
1. Important Note: Enable vector search in CosmosDB for specific AI-based applications. In these sample projects, we deploy CosmosDB using provisioned throughput instead of serverless for optimal performance.

Before looking at specific use cases, let’s look at how Azure Cosmos DB fits into the broader data ecosystem and how it can be used to power a variety of AI applications.

Case Study and Lessons Learned:

Ready to dive deeper?

Try Azure yourself:

as a result:

Integration with Python Azure Cosmos DB NoSQL provides a powerful foundation for building AI applications that can leverage data in interesting and innovative ways. Take the leap, explore samples, and discover a world of possibilities that awaits you!

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