Integrate the ChartMogul API with the Python API

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

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Popular ChartMogul and Python Actions#

Add Custom Attributes To Customer Via Email with the ChartMogul API

Adds custom attributes to customers that have the specified email address. See the docs here

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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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Add Custom Attributes To Customer Via UUID with the ChartMogul API

Adds custom attributes to a given customer. See the docs here

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Add Tags To Customer Via Email with the ChartMogul API

Adds tags to customers that have the specified email address. See the docs here

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Add Tags To Customer Via UUID with the ChartMogul API

Adds tags to a given customer. See the docs here

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Overview of ChartMogul#

ChartMogul is an analytics platform designed to help subscription businesses analyze their revenue, churn, and other key performance indicators (KPIs). By leveraging the ChartMogul API, you can import, manipulate, and retrieve customer subscription data to gain insights into the financial health of your business. When used with Pipedream, you can automate complex workflows, combine subscription data with external tools, and react in real-time to changes in your subscription metrics.

Connect ChartMogul#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    chartmogul: {
      type: "app",
      app: "chartmogul",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.chartmogul.com/v1/ping`,
      auth: {
        username: `${this.chartmogul.$auth.account_token}`,
        password: `${this.chartmogul.$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#

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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