Integrate the LaunchDarkly (OAuth) API with the Python API

Setup the LaunchDarkly (OAuth) API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate LaunchDarkly (OAuth) and Python remarkably fast. Free for developers.

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Popular LaunchDarkly (OAuth) and Python Actions#

Run Python Code with the Python API

Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.

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Overview of LaunchDarkly (OAuth)#

Launch Darkly's API provides the means to automate feature flagging and manage experiments in your software delivery. This power, harnessed within Pipedream's serverless environment, can transform how you handle software deployment strategies, perform A/B testing, and control access to new features. The API's capabilities extend to updating flags, fetching flag statuses, and managing user segments, all of which can be integrated into sophisticated, automated workflows that react to external triggers or scheduled events.

Connect LaunchDarkly (OAuth)#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    launch_darkly_oauth: {
      type: "app",
      app: "launch_darkly_oauth",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://app.launchdarkly.com/api/v2/projects`,
      headers: {
        Authorization: `Bearer ${this.launch_darkly_oauth.$auth.oauth_access_token}`,
      },
    })
  },
})

Overview of Python#

Develop, run and deploy your Python code in Pipedream workflows. Integrate seamlessly between no-code steps, with connected accounts, or integrate Data Stores and manipulate files within a workflow.

This includes installing PyPI packages, within your code without having to manage a requirements.txt file or running pip.

Below is an example of using Python to access data from the trigger of the workflow, and sharing it with subsequent workflow steps:

Connect Python#

def handler(pd: "pipedream"):
  # Reference data from previous steps
  print(pd.steps["trigger"]["context"]["id"])
  # Return data for use in future steps
  return {"foo": {"test":True}}

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