Integrate the Instabot API with the Python API

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

Popular Instabot 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.

Try it

Overview of Instabot#

The Instabot API offers the ability to programmatically interact with the Instabot platform, enabling the automation of chatbot conversations and data. By leveraging this API with Pipedream, you can create powerful workflows to enhance user engagement, collect insightful data, and streamline communications. It supports various operations like sending messages, managing users, and retrieving conversation logs, which can be harnessed for targeted marketing, customer support automation, and real-time analytics.

Connect Instabot#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    instabot_chatbot_platform: {
      type: "app",
      app: "instabot_chatbot_platform",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.instabot.io/v1/users`,
      headers: {
        "X-Instabot-Api-Key": `${this.instabot_chatbot_platform.$auth.api_key}`,
        "Authorization": `X-Instabot-Master-Api-Key ${this.instabot_chatbot_platform.$auth.master_api_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#

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}}