Integrate the Amazon Polly API with the Python API

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

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Popular Amazon Polly 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 Amazon Polly#

The Amazon Polly API lets you convert text into lifelike speech using deep learning. With Polly, you can create applications that talk and build entirely new categories of speech-enabled products. Pipedream's platform enables you to integrate Polly's capabilities into workflows that can automate tasks, like generating audio files from blog posts or alert messages, and piping them to various services or storage solutions.

Connect Amazon Polly#

import AWS from 'aws-sdk'
import { PollyClient, StartSpeechSynthesisTaskCommand } from "@aws-sdk/client-polly"

export default defineComponent({
  props: {
    amazon_polly: {
      type: "app",
      app: "amazon_polly",
    }
  },
  async run({steps, $}) {
    const { accessKeyId, secretAccessKey } = auths.amazon_polly
    // Create an Amazon Polly service client object.
    const creds = new AWS.Credentials(accessKeyId, secretAccessKey);
    const pollyClient = new PollyClient({ credentials: creds, region: "us-east-1" });

    // Create input data
    var data = {
      OutputFormat: "mp3",
      OutputS3BucketName: "videoanalyzerbucket",
      Text: "Hello David, How are you?",
      TextType: "text",
      VoiceId: "Joanna",
      SampleRate: "22050",
    };

    return await pollyClient.send(new StartSpeechSynthesisTaskCommand(data));
  },
})

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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