Integrate the Alchemy API with the Python API

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

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Popular Ways to Connect Alchemy with Python#

Run Python Code with Python API on New GraphQL Query (Instant) from Alchemy API

Alchemy + Python

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Popular Alchemy and Python Triggers#

New GraphQL Query (Instant) from the Alchemy API

Emit new event when a new GraphQL query is uploaded to Alchemy's Custom Webhook service. See the documentation

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Popular Alchemy and Python Actions#

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 Alchemy#

The Alchemy API provides a robust platform for sending and managing faxes programmatically, giving you the power to integrate fax capabilities into automated workflows. With Pipedream, you can tap into these capabilities to build event-driven serverless workflows. Automate the sending of faxes when certain triggers occur, receive status updates, and connect with countless other services to streamline document management, notifications, and data synchronization tasks.

Connect Alchemy#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    alchemy: {
      type: "app",
      app: "alchemy",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.g.alchemy.com/prices/v1/${this.alchemy.$auth.api_key}/tokens/by-symbol?symbols=ETH`,
    })
  },
})

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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