![]() ![]() ![]() If you haven’t installed the mongo shell yet, follow these instructions: On the following page, choose the “Connect with the mongo shell” option as this is what we’ll use for the rest of our tutorial. The two things we need to configure are the IP Whitelist addresses and a database user.įor the IP whitelist, click on “Add your Current IP Address” and then select a username/password that you will remember. Select your preferred cloud provider, supply a name for your cluster, and click Create Cluster:Īfter the cluster is created, let’s configure the security options. Once you do, you need to create a project:Īnd then, create the actual MongoDB Cluster: To start the setup on MongoDB Atlas, all you need to do is to create an account. This is a service that you can access using your favorite web browser it can be installed on all three major public cloud providers (Amazon Web Services, Microsoft Azure, Google Cloud Platform), comes with a free tier, and with just a few clicks, you will have provisioned a fully functioning MongoDB database. The most effective way to achieve this is to use the MongoDB Database-as-a-Service offering called MongoDB Atlas. MongoDB can handle dynamic data models and schema that can easily store unstructured data sets and in the case of variable data loads, MongoDB can scale horizontally, which is extremely cost-efficient when compared to traditional SQL databases, which can usually only scale vertically. Effectively, each MongoDB document follows the Javascript Object Notation (JSON) format. The data fields can be of an arbitrary number and type, even within the same collection. Indexes, a fundamental feature for efficient query execution, are also supported in MongoDB on any field or subfield of the documents, and they are defined at the collection level.Ī collection contains a number of documents, and a document contains data fields. In other words, in a relational database, tables are related by keys, and in MongoDB, collections contain unstructured and often arbitrary data. In a traditional relational SQL database (i.e., MySQL, PostgreSQL), tables are used for defining the structure of a data set and rows for the actual data, while in MongoDB, we have collections and text documents containing name-value pairs, respectively. Pymongo-fastapi-crud/main.The best way to start understanding MongoDB basics is to grasp the following comparison: MongoDB Open the main.py file in your favorite code editor and add the following: Let's start by implementing a simple root / endpoint that returns a welcome message. If you prefer, you can use a graphical file explorer instead. Note: We'll be using shell commands to create files and directories, and navigate through them. Next, we'll create a directory for our project, navigate to it, and scaffold the files needed for the project. We'll use pip-the package installer for Python, which is also included with your Python installation: python -m pip install 'fastapi' 'pymongo' python-dotenv Now that we have a virtual environment, we can install the required packages. Once you’ve logged into your virtual environment, the python executable will use Version 3 automatically. This is because, on some operating systems, both Python 2 and 3 are installed. Note: You might have to run this command using the python3 executable. Source env-pymongo-fastapi-crud/bin/activate ![]() Execute the following command from the terminal: python3 -m venv env-pymongo-fastapi-crud We'll use the venv package, which comes with your Python installation. We'll use PyMongo to connect to the cluster and query data.īefore we begin, we'll create a virtual Python environment to isolate the project from the rest of the globally-installed Python packages. It's cloud-based and you can create a free account and cluster in minutes, without installing anything on your machine. MongoDB Atlas is MongoDB's database-as-a-service platform. We'll be storing the books in a MongoDB Atlas cluster. It also generates a Swagger API documentation that we'll put to use when testing the application. It's a lightweight, modern, and easy-to-use framework for building APIs. To build the API, we'll use the FastAPI framework.
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