Deploy a Python API on Vercel using Postgres

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  • PostgresWithFastAPI

    In this tutorial, we'll learn how to build and deploy a Postgres FastAPI application on Vercel by creating a simple task manager application. To follow along, ensure you clone the Github repository for this project. Let's get started!.

  • SQLAlchemy

    The Database Toolkit for Python

    We can now set up our Postgres database to store our user's records with our server setup. We'll use SQLAlchemy ORM (Object Relational Mapper) to connect our database with our application. To begin, we'll need to create a database with the following steps. First, switch to the system's Postgres user account.

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  • pydantic

    Data validation using Python type hints

    Let's define a schema for our application. We need to define a Pydantic schema that will read data and return it from the API. Open the Schema.py file and add the following code snippet to it:

  • fastapi

    FastAPI framework, high performance, easy to learn, fast to code, ready for production

    Now that you have this knowledge, how do you intend to build your next FastAPI application? Perhaps you can learn more about FastAPI and Arctype from their website and use what you've learned as inspiration for your next project. Feel free to reach out on Twitter and share your progress and questions.

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