Chargify

Billing & Revenue Management for B2B SaaS

Integrate the Chargify API with the Python API

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

 
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Overview of Chargify

The Chargify API enables seamless integration of subscription billing, management, and reporting functionalities. With Chargify, you can automate the creation and management of customer subscriptions, handle invoicing, apply taxes, and track analytics related to your billing processes. It's a powerful tool for businesses with recurring revenue models to keep their billing systems in sync with other business operations, reducing manual workload and increasing efficiency.

Connect Chargify

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    chargify: {
      type: "app",
      app: "chargify",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://${this.chargify.$auth.subdomain}.chargify.com/subscriptions.json`,
      headers: {
        "content-type": `application/json`,
        "accept": `application/json`,
      },
      auth: {
        username: `${this.chargify.$auth.api_key}`,
        password: ``,
      },
    })
  },
})

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}}