TD Ameritrade
TD Ameritrade is a stockbroker that offers an electronic trading platform for the trade of financial assets including common stocks, preferred stocks, futures contracts, exchange-traded funds, forex, options, mutual funds, fixed income investments, margin lending, and cash management services.
Integrate the TD Ameritrade API with the Python API
Setup the TD Ameritrade API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate TD Ameritrade and Python remarkably fast. Free for developers.
Popular TD Ameritrade and Python Actions#
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Overview of TD Ameritrade#
The TD Ameritrade API offers access to a brokerage's suite of trading services. With it, you can retrieve market data, manage accounts, place trades, and get updates on orders and positions. Integrating the TD Ameritrade API with Pipedream allows for the automation of various trading strategies and the syncing of financial data with other services, all in a serverless environment.
Connect TD Ameritrade#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
td_ameritrade: {
type: "app",
app: "td_ameritrade",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.tdameritrade.com/v1/userprincipals`,
headers: {
Authorization: `Bearer ${this.td_ameritrade.$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}}