Panoramic Authentication SDK
Project description
Panoramic Auth SDK
Getting Started
This SDK handles the access token generation using client_credentials flow against Panoramic. To install the SDK in your app, add it to your requirements.txt:
panoramic-auth==1.0.0
All you then need to do is subclass the OAuth2Client Python class from the SDK, pass your client_id and client_secret, and use the session attribute from your subclass when making HTTP requests:
# Import the class as usual
from panoramic.auth import OAuth2Client
# Note subclassing OAuth2Client below
class PanoramicApiClient(OAuth2Client):
def __init__(self, base_url: str, client_id: str, client_secret: str):
super().__init__(client_id, client_secret)
self.base_url = base_url
def async_data(self, data: Dict[str, Any]) -> Dict[str, Any]:
url = urljoin('https://platform.panoramichq.com/api/example')
# Note self.session below
response = self.session.post(url=url, json=data)
response.raise_for_status()
return response.json()
Development
This repository does not have a dedicated docker image. At the moment, we create python virtual environment using command (in directory .venv
inside current directory):
> python3 -m venv .venv
If you use pyenv and pyenv-virtualenv, you can create it using:
> pyenv virtualenv panoramic-auth
Then, you can switch to it from command-line using following command:
> source .venv/bin/activate
Or if using pyenv-virtualenv:
pyenv local panoramic-auth
Lastly, use following command to install dependencies (make sure you have correct python environment active):
> make install
Install pre-commit - useful to avoid commiting code that doesn't pass the linter:
> make pre-commit-install
This installs git hooks that run pre-commit.
Tests
Use following command to run all tests:
> make tests
Release process
To release a new version of the library, follow these steps:
- In your PR, update version in setup.py and add entry to CHANGELOG.md
- After merge, tag the commit with version number from setup.py. For example
git tag v0.1.1
. You can also do this by creating a new release. - This triggers a Travis pipeline which runs tests, linters and uploads the package to PyPI
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