Integrate the Yahoo! Fantasy Sports API with the Python API

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

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Popular Ways to Connect Yahoo! Fantasy Sports with Python#

Run Python Code with Python API on New Football League Transactions from Yahoo! Fantasy Sports API

Yahoo! Fantasy Sports + Python

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Popular Yahoo! Fantasy Sports and Python Triggers#

New Football League Transactions from the Yahoo! Fantasy Sports API

Emit new event when a new football league transaction occurs

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Popular Yahoo! Fantasy Sports 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 Yahoo! Fantasy Sports#

The Yahoo! Fantasy Sports API opens a realm of possibilities for sports enthusiasts and developers, allowing them to tap into fantasy leagues, player stats, and real-time scoring. Leverage this data source within Pipedream to automate team management, notifications, and data analysis. You can create dynamic workflows that react to league updates, automate team roster changes, or aggregate statistics for insightful analytics, all with real-time triggers and seamless integrations with hundreds of apps.

Connect Yahoo! Fantasy Sports#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    yahoo_fantasy_sports: {
      type: "app",
      app: "yahoo_fantasy_sports",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.login.yahoo.com/openid/v1/userinfo`,
      headers: {
        Authorization: `Bearer ${this.yahoo_fantasy_sports.$auth.oauth_access_token}`,
      },
    })
  },
})

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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