Introduction
Introduction
Integrates’ backend is an HTTP web service written in Python, served with Hypercorn and built with Starlette.
Principles
- Functional: The codebase favors functions over classes and avoids direct mutations.
- No need to reinvent the wheel: Leveraging third-party packages when available.
Getting started
To view changes reflected as you edit the code, you can run:
As explained in the introduction
section, this command launches a replica of the platform
using the test data defined in common/schemas/database-design.json
. Inside
the schemas/tables
directory you find all the data launched by default.
This is useful as it allows you to modify anything you wish to test,
for example:
This portion of the code that is in the stakeholder_state.cue
file defines
your local user, with this you can modify the role, registration
status, and all metadata information.
Remember, after doing any modifications to the local database
you need to run the following:
And update your local environment so your changes can be reflected.
More on this can be found in the database design section.
Linting
The back uses Prospector and Mypy to enforce compliance with a defined coding style.
To view linting issues, run:
To view and auto-fix formatting issues, run:
Testing
The back-end uses pytest as a test runner.
To execute unit tests on your computer, run:
To execute a functional test on your computer, run:
Web server
The back-end is served by Hypercorn, a program with two sides:
- 🌐 On one side it speaks the HTTP protocol, receiving requests and sending responses.
- 🐍 On the other it speaks Python (ASGI), passing request data to Python code for processing.
This lower-level is challenging to build an application directly on top of, which is where Starlette comes in handy.
Starlette abstracts requests handling, and provides utilities for building web applications, such as declaring routes, middlewares, and managing sessions and cookies.
Modules
You can find them in the back/integrates
directory.
api
This module implements a GraphQL API. You can find more details about it here.
db_model
Declares the structure of each entity used in the application and interacts with database-specific modules to read from and write to a data store.
It provides functions to perform CRUD operations for each entity, taking care of batching and caching using dataloaders. Designed to be agnostic for easy swapping of the underlying data store.
This module is also responsible for controlling concurrent writes, using strategies like optimistic locking.