https://github.com/superfaceai/station
Comlink metadata for self-integrating applications.
https://github.com/superfaceai/station
Last synced: 3 months ago
JSON representation
Comlink metadata for self-integrating applications.
- Host: GitHub
- URL: https://github.com/superfaceai/station
- Owner: superfaceai
- License: mit
- Created: 2021-04-14T06:58:07.000Z (almost 4 years ago)
- Default Branch: main
- Last Pushed: 2023-06-22T12:19:06.000Z (over 1 year ago)
- Last Synced: 2024-11-02T16:08:42.688Z (4 months ago)
- Language: TypeScript
- Homepage: https://superface.ai/catalog
- Size: 9.46 MB
- Stars: 23
- Watchers: 7
- Forks: 5
- Open Issues: 26
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
Awesome Lists containing this project
- jimsghstars - superfaceai/station - Comlink metadata for self-integrating applications. (TypeScript)
README
# station
[](https://github.com/superfaceai/station/actions/workflows/ci_cd.yml)
Where use-cases are born. In this repository we build curated use-cases. Examples in this repository are an ideal starting point for writing your own.
## Table of Contents
- [Background](#background)
- [Install](#install)
- [Usage](#usage)
- [Security](#security)
- [Support](#support)
- [Contributing](#contributing)
- [License](#license)
## Background
Superface (super-interface) is a higher-order API, an abstraction on top of modern APIs like GraphQL and REST. Superface is one interface to discover, connect, and query any use cases available via conventional APIs.
Through its focus on application-level semantics, Superface decouples the clients from servers, enabling fully autonomous evolution. As such, it minimizes the code base size as well as errors and downtimes while providing unmatched resiliency and redundancy.
Superface allows for switching providers without development at runtime in milliseconds. Furthermore, Superface decentralizes the composition and aggregation, and thus creates an Autonomous Integration Mesh.
Motivation behind Superface is nicely described in this [video](https://www.youtube.com/watch?v=BCvq3NXFb94) from APIdays conference.
You can learn more at https://superface.ai and https://superface.ai/docs.
## Install
Install dependencies:
```
yarn install
```
## Usage
```shell
# Check all files are correctly linked together
$ yarn check
# Runs linter on Profiles and maps
$ yarn lint
# Run tests
$ yarn test
# Record new trafic with live API calls
$ yarn test:record grid/path/to/test.ts
```
## Security
Superface is not a man-in-the-middle so it does not require any access to secrets that are needed to communicate with provider API. Superface CLI only prepares super.json file with authorization fields in the form of environment variables. You just set correct variables and communicate directly with provider API.
You can find more information in [OneSDK repository](https://github.com/superfaceai/one-sdk-js/blob/main/SECURITY.md).
## Support
If you need any additional support, have any questions, or you just want to talk you can do that through our [support page](https://superface.ai/docs/support).
### Adding new use-case
If you are starting with authoring, check our [guide](https://superface.ai/docs/guides/how-to-create).
Station repository has a defined structure. Here are the [Superface CLI](https://github.com/superfaceai/cli#usage) commands for creating boilerplate code for profiles, maps, mock map and providers.
#### Create new profile
```shell
yarn create:profile [scope](optional)/[name]
```
#### Create new provider
```shell
yarn create:provider [provider_name]
```
#### Create map for profile and provider
```shell
yarn create:map [scope](optional)/[name] [provider_name]
```
#### Create mock map
```shell
yarn create:mock-map [scope](optional)/[name]
```
#### Test the map
We encourage using the [Superface Testing](https://github.com/superfaceai/testing-lib) to write tests.
**1. Generate test boilerplate code**
For mock provider call command:
```shell
yarn create:mock-map-test [scope](optional)/[name]
```
For real provider call command:
```shell
yarn create:test [scope](optional)/[name] [provider_name]
```
The `create:test` command creates test file alongside map `.suma` file. The test inputs and expected result will be pregenerated from profile examples.
The created code looks like this:
```ts
import { SuperfaceTest } from '@superfaceai/testing';
import { buildSuperfaceTest } from '../../../test-config';
describe(`scope/name/provider_name}`, () => {
let superface: SuperfaceTest;
beforeEach(() => {
superface = buildSuperfaceTest({
profile: 'scope/name',
provider: 'provider_name',
});
});
describe('UseCase', () => {
it('performs successfully', async () => {
const result = await superface.run({
useCase: 'UseCase',
input: {
field1: '',
field2: '',
},
});
expect(() => result.unwrap()).not.toThrow();
expect(result).toMatchSnapshot();
});
});
});
```
_All inputs should be written directly to the test file and shouldn't use environment variables._
**2. Make a call against live API to record traffic and create a snapshot**
```shell
$ yarn test:record grid/[scope]/[name]/maps/[provider].test.ts
```
**3. Check result in the snapshot**
Snapshot for test run should be created in location:
```
grid/[scope]/[name]/maps/__snapshots__/[provider].test.ts.snap
```
**4. Do post processing for traffic recording**
We try to sanitize recordings and remove any sensitive data. But you should still look at the recording and make sure it doesn't contain sensitive data such as credentials or personal information that shouldn't be public.
**5. Run tests with recorded traffic**
```shell
$ yarn test grid/[scope]/[name]/maps/example.test.ts
```
### Debugging maps
You can set the OneSDK `DEBUG` environment variable to enable logging for debugging purposes:
```
DEBUG="superface:http*"
```
For example, when recording traffic:
```
$ DEBUG="superface:http*" yarn test:record grid/[scope]/[name]/maps/[provider].test.ts
```
### Enviroment variables
Secretes used for authentication during tests are stored in `.env` and loaded using `dotenv`. Run `cp .env.example .env` to start from the template.
### Automated publishing
Station uses Workflow to automate publishing. For details see the [CI / CD](https://github.com/superfaceai/station/blob/main/.github/workflows/ci_cd.yml) workflow.
## Contributing
**Please open an issue first if you want to make larger changes**
Feel free to contribute! Please follow the [Contribution Guide](CONTRIBUTING.md).
Licenses of node_modules are checked during CI/CD for every commit. Only the following licenses are allowed:
- 0BDS
- MIT
- Apache-2.0
- ISC
- BSD-3-Clause
- BSD-2-Clause
- CC-BY-4.0
- CC-BY-3.0;BSD
- CC0-1.0
- Unlicense
- UNLICENSED
Note: If editing the README, please conform to the [standard-readme](https://github.com/RichardLitt/standard-readme) specification.
## License
The Superface is licensed under the [MIT](LICENSE).
© 2022 Superface