Asynchronous library for accessing Swagger-1.1-enabled APIs
Project description
About
Swagger.py is a Python library for using Swagger defined API’s.
Swagger itself is best described on the Swagger home page:
Swagger is a specification and complete framework implementation for describing, producing, consuming, and visualizing RESTful web services.
The Swagger specification defines how API’s may be described using Swagger.
Swagger.py also supports a WebSocket extension, allowing a WebSocket to be documented, and auto-generated WebSocket client code.
Usage
Install the latest release from PyPI.
$ sudo pip install aioswagger11
Or install from source using the setup.py script.
$ sudo ./setup.py install
API
Swagger.py will dynamically build an object model from a Swagger-enabled RESTful API.
Here is a simple example using the Asterisk REST Interface
#!/usr/bin/env python3
import json
import asyncio
import aiohttp
from aioswagger11.client import SwaggerClient
from aioswagger11.http_client import AsynchronousHttpClient
http_client = AsynchronousHttpClient()
http_client.set_api_key('localhost', 'hey:peekaboo')
async def run(ari,msg_json):
channelId = msg_json['channel']['id']
await ari.channels.answer(channelId=channelId)
await ari.channels.play(channelId=channelId,
media='sound:hello-world')
# In a real program you should wait for the PlaybackFinished event instead
await asyncio.sleep(3)
await ari.channels.continueInDialplan(channelId=channelId)
async def main():
ari = SwaggerClient(
"http://localhost:8088/ari/api-docs/resources.json",
http_client=http_client)
ws = ari.events.eventWebsocket(app='hello')
async for msg_str in ws:
if msg.type == aiohttp.WSMsgType.CLOSED:
break
elif msg.type != aiohttp.WSMsgType.TEXT:
continue # ignore
msg_json = json.loads(msg_str)
if msg_json['type'] == 'StasisStart':
asyncio.ensure_future(run(ari,msg_json))
if __name__ == "__main__":
loop = asyncio.get_event_loop()
loop.run_until_complete(main())
swagger-codegen
There are the beginnings of a Mustache-based code generator, but it’s not functional… yet.
Data model
The data model presented by the swagger_model module is nearly identical to the original Swagger API resource listing and API declaration. This means that if you add extra custom metadata to your docs (such as a _author or _copyright field), they will carry forward into the object model. I recommend prefixing custom fields with an underscore, to avoid collisions with future versions of Swagger.
There are a few meaningful differences.
Resource listing
The file and base_dir fields have been added, referencing the original .json file.
The objects in a resource_listing’s api array contains a field api_declaration, which is the processed result from the referenced API doc.
API declaration
A file field has been added, referencing the original .json file.
Development
The code is documented using Sphinx, which allows IntelliJ IDEA to do a better job at inferring types for autocompletion.
To keep things isolated, I also recommend installing (and using) virtualenv.
$ sudo pip install virtualenv $ mkdir -p ~/virtualenv $ virtualenv ~/virtualenv/swagger $ . ~/virtualenv/swagger/bin/activate
Setuptools is used for building. Pytest is used for unit testing, with the coverage plugin installed to generated code coverage reports. Pass --with-coverage to generate the code coverage report. HTML versions of the reports are put in cover/index.html.
$ ./setup.py develop # prep for development (install deps, launchers, etc.) $ ./setup.py nosetests # run unit tests $ ./setup.py bdist_egg # build distributable
License
Copyright (c) 2013, Digium, Inc. Copyright (c) 2018, Matthias Urlichs
Swagger.py is licensed with a BSD 3-Clause License.
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