Heap

Fuel product growth and team agility. Heap automatically captures web and mobile app behavioral data. Retroactively analyze behavioral data without writing code.

Integrate the Heap API with the Python API

Setup the Heap API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Heap 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 Heap

The Heap API enables you to automate and integrate your user analytics data with other applications. With Heap, you can extract insights on how users interact with your product, track events without code, and funnel this data into your CRM, marketing tools, or custom dashboards. It's about connecting the dots between user actions and your strategic moves. Heap's API lets you push or pull data, so you're always up-to-date on user behavior and can personalize user experiences at scale.

Connect Heap

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    heap: {
      type: "app",
      app: "heap",
    }
  },
  async run({steps, $}) {
    // From the docs: https://docs.heap.io/reference#track-1
    // "Requests are limited to 30 requests per 30 seconds per identity per app_id"
    return await axios($, {
      method: "POST",
      url: `https://heapanalytics.com/api/track`,
      headers: {
        "Content-Type": "application/json",
      },
      data: {
        app_id: this.heap.$auth.app_id,
        identity: params.identity,
        event: params.event,
        timestamp: params.timestamp || (new Date()).toISOString(),
        properties: params.properties,
      }
    })
  },
})

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

1
2
3
4
5
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}}