Mux
Build Better Video: Stream beautiful video to any device and monitor your video performance with our APIs.
Integrate the Mux API with the Python API
Setup the Mux API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Mux and Python remarkably fast. Free for developers.
Popular Mux and Python Actions#
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Adds an asset track (for example, subtitles) to an asset. See the documentation
Returns an Asset or Livestream ID from a Playback ID. See the documentation
Overview of Mux#
Mux is a powerful API that simplifies the process of working with video and audio data. By leveraging Mux on Pipedream, you unlock the potential to automate video and audio streaming workflows, analyze media performance, and integrate seamlessly with other services to enrich your media content strategy. With Mux's ability to manage video assets, including uploading, encoding, and delivering content across devices, combined with Pipedream's serverless execution model, you can create dynamic, scalable, and highly customized media operations.
Connect Mux#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
mux: {
type: "app",
app: "mux",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.mux.com/video/v1/assets`,
headers: {
"Content-Type": `application/json`,
},
auth: {
username: `${this.mux.$auth.access_key}`,
password: `${this.mux.$auth.secret_key}`,
},
})
},
})
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}}