Braintree

We provide the global commerce tools people need to build businesses, accept payments, and enable beautiful commerce experiences for their users.

Integrate the Braintree API with the Python API

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

The Braintree API provides a robust platform for handling online payments, including payment processing, merchant account management, fraud prevention, and data analysis. With Pipedream, you can automate workflows that trigger on a variety of Braintree events, such as new transactions or customer records. These automations can integrate seamlessly with other services, facilitating custom notifications, data synchronization, and more, streamlining ecommerce operations and enhancing customer experiences.

Connect Braintree

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    braintree: {
      type: "app",
      app: "braintree",
    }
  },
  async run({steps, $}) {
    const data = {
      "query": `query { ping }`,
    }
    return await axios($, {
      method: "post",
      url: `https://${this.braintree.$auth.environment}.braintree-api.com/graphql`,
      headers: {
        "Braintree-Version": `2019-01-01`,
        "Content-Type": `application/json`,
      },
      auth: {
        username: `${this.braintree.$auth.public_key}`,
        password: `${this.braintree.$auth.private_key}`,
      },
      data,
    })
  },
})

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}}