Google Cloud Translate

Dynamically translate between languages using Google machine learning

Integrate the Google Cloud Translate API with the Python API

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

Translate with the Google Cloud Translate API

Translate text using Google Cloud Translate

 
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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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Overview of Google Cloud Translate

The Google Cloud Translate API empowers developers to dynamically translate text between thousands of language pairs, integrate language translation into applications, websites, tools, and other solutions. By leveraging this API within Pipedream's serverless platform, you can create automated workflows that respond to events from hundreds of sources, transforming and routing your data to various destinations, all while breaking down language barriers.

Connect Google Cloud Translate

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    google_cloud_translate: {
      type: "app",
      app: "google_cloud_translate",
    }
  },
  async run({steps, $}) {
    const data = {
      "q": `¡hola mundo!`,
      "target": `en`,
    }
    return await axios($, {
      method: "post",
      url: `https://translation.googleapis.com/language/translate/v2?key=${this.google_cloud_translate.$auth.api_key}`,
      headers: {
        "Content-Type": `application/json; charset=utf-8`,
      },
      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

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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}}