chatra

Chatra is a live chat messenger app designed to infuse the most popular elements of mobile messengers into traditional live chat software.

Integrate the chatra API with the Python API

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

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.

 
Try it

Overview of chatra

The Chatra API enables the automation of customer support processes by allowing the programmatic sending of messages, retrieval of chat history, and management of ongoing conversations. With Pipedream's serverless platform, you can harness this API to integrate real-time chat capabilities with other applications, set up automated responses based on specific triggers, and analyze customer interactions to enhance support strategies.

Connect chatra

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    chatra: {
      type: "app",
      app: "chatra",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://app.chatra.io/api/messages/XGDsxHtLppJTJ3vZk`,
      headers: {
        "Content-Type": `application/json`,
        "Authorization": `Chatra.Simple ${this.chatra.$auth.public_key}:${this.chatra.$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

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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}}