Integrate the Vext API with the Python API

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

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Popular Vext and Python Actions#

Send Query with the Vext API

Send a query request to your LLM pipeline. 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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Overview of Vext#

The Vext API lets you automate interactions with the Vext application, which is designed for versatile text transformations, parsing, and encoding. On Pipedream, you can craft serverless workflows that utilize Vext API to process and manipulate text data on-the-fly, without the need for manual intervention. Imagine automating complex text parsing tasks, encoding/decoding data in various formats, or even integrating with other services to enhance data processing pipelines.

Connect Vext#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    vext: {
      type: "app",
      app: "vext",
    }
  },
  async run({steps, $}) {
    const data = {
      "payload": `Hello`,
    }
    return await axios($, {
      method: "post",
      url: `https://payload.vextapp.com/hook/${this.vext.$auth.endpoint_id}/catch/123`,
      headers: {
        "Content-Type": `application/json`,
        "Apikey": `Api-key ${this.vext.$auth.api_key}`,
      },
      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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