Luno

We make it safe and easy to buy, save, and manage your crypto.

Integrate the Luno API with the Python API

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

The Luno API offers a way to automate interactions with the Luno platform, a prominent cryptocurrency exchange. Through this API, you can programmatically access real-time market data, manage trades, and handle your wallet transactions. Integrating Luno with Pipedream enables you to create custom, serverless workflows that can react to Luno events, automate trading strategies, consolidate financial reports, and more. Pipedream's no-code platform allows you to seamlessly connect Luno to hundreds of other apps and orchestrate complex workflows with minimal effort.

Connect Luno

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    luno: {
      type: "app",
      app: "luno",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.luno.com/api/1/balance`,
      headers: {
        "Content-Type": `application/json`,
      },
      auth: {
        username: `${this.luno.$auth.key_id}`,
        password: `${this.luno.$auth.key_secret}`,
      },
    })
  },
})

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}}