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Since FastAPI is based on OpenAPI, at this point you can also use the automatically generated docs. There are multiple options, and two are included by default. Try them out by accessing the following URLs:
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PostgreSQL
Mirror of the official PostgreSQL GIT repository. Note that this is just a *mirror* - we don't work with pull requests on github. To contribute, please see https://wiki.postgresql.org/wiki/Submitting_a_Patch
Building a web application involves more than just a web server; it requires a reliable and efficient database to store and manage the application's stateful data. Among the various database options available, PostgreSQL stands out as a popular choice for developers. Its extensive community and ecosystem provide invaluable support, making it easier to solve problems. PostgreSQL's reputation for reliability and stability further solidifies its position as a trusted solution. Additionally, PostgreSQL's compatibility with multiple platforms ensures flexibility in deployment. In this blog post, we will explore how to connect our FastAPI server with a PostgreSQL database. It's worth noting that the guide can be easily adapted for other databases like MySQL or MongoDB with minimal modifications.
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InfluxDB
Collect and Analyze Billions of Data Points in Real Time. Manage all types of time series data in a single, purpose-built database. Run at any scale in any environment in the cloud, on-premises, or at the edge.
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swagger-ui
Swagger UI is a collection of HTML, JavaScript, and CSS assets that dynamically generate beautiful documentation from a Swagger-compliant API.
SwaggerUI: http://localhost:8080/docs
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To do this, we can use the Tortoise-ORM. Begin by installing the package:
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Redoc: http://localhost:8080/redoc
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fastapi-postgres-gcp-blog
Source code for a guide on deploying a FastAPI application with a PostgreSQL database to GCP
You can find all the source code here: https://github.com/GlennViroux/fastapi-postgres-gcp-blog
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When I was building Ballistic, I chose for FastAPI as the web framework for my backend API in Python, since it had gained significant popularity in the Python community in a very short amount of time. Apart from its performance, powered by the usage of the asyncio library, I was convinced by the core integration of type annotations and the well-built documentation. Take into account that good documentation and a broad community can save you tons of time when developing your backend.
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Mergify
Updating dependencies is time-consuming.. Solutions like Dependabot or Renovate update but don't merge dependencies. You need to do it manually while it could be fully automated! Add a Merge Queue to your workflow and stop caring about PR management & merging. Try Mergify for free.
