Integrate the Microsoft Azure AI Translator API with the Python API

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

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Popular Microsoft Azure AI Translator and Python Actions#

Break Sentence with the Microsoft Azure AI Translator API

Identifies the positioning of sentence boundaries in a piece of text. See the documentation

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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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Detect Language with the Microsoft Azure AI Translator API

Identifies the language of a piece of text. See the documentation

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Translate Text with the Microsoft Azure AI Translator API

Translate text into the specified language. See the documentation

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Connect Microsoft Azure AI Translator#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    microsoft_azure_ai_translator: {
      type: "app",
      app: "microsoft_azure_ai_translator",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `${this.microsoft_azure_ai_translator.$auth.endpoint}/languages`,
      headers: {
        "Ocp-Apim-Subscription-Key": `${this.microsoft_azure_ai_translator.$auth.api_key}`,
        "Ocp-Apim-Subscription-Region": `${this.microsoft_azure_ai_translator.$auth.location}`,
        "Content-Type": `application/json`,
      },
      params: {
        "api-version": `3.0`
      },
    })
  },
})

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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