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Description
Clear and concise description of the problem
As a developer I'd love if the API for test context (fixtures) mirrored that of playwright test
This would be better for the following reasons:
- It makes context modifications easier to share
- Its not reliant on setting up
beforeEachbefore a test to modify its context. You could easily share customizedtest/describeand/oritblocks. UsingbeforeEachis clunky and not easily sharable. - Its (perhaps subjectively) more ergonomic and discoverable. Certainly works better for typing with TypeScript, which for large teams (especially enterprises) this is a huge win.
Suggested solution
Allow for test context to be set on the test function level, via test /it, and/or describe. e.g.
// my-test.ts
import { describe as base } from 'vitest;
import type { Todo } from './todo';
import * as faker from '@faker-js/faker';
// Declare the types of your fixtures.
interface TodoFixtures {
todos: Todo[];
};
// Extend base test by providing "todo"
// This new "describe" can be used in multiple test files, and each of them will get the fixtures.
export const describe = base.extend<TodoFixtures>({
todo: async (use) => {
let i = 0;
const todos = [];
for (i; i < 25; i++) {
todos.push({
due: faker.date.between('2020-01-01T00:00:00.000Z', '2030-01-01T00:00:00.000Z'),
assigned: faker.name.findName(),
text: faker.lorem.lines()
})
}
use(todos)
},
});Alternative
No response
Additional context
This is largely brought about because on my team of 24+ engineers we would like to be able to have standard patterns for faking data. One of the requirements when it comes to sharing API data is having fake datasets that can be re-used for testing and tested against schema so that can test that our validators work correctly. Its also the same fake data factory datasets used for our API test responses, and for data transformers, among other things. We really started to scale the @playwright/test approach well and our team is finding this API to be rather clunky by comparison, and having to declare a module augmentation adds more overhead and is prone to error.
Validations
- Follow our Code of Conduct
- Read the Contributing Guidelines.
- Read the docs.
- Check that there isn't already an issue that request the same feature to avoid creating a duplicate.