Query for all information about Yahoo! Finance summary, stocks, quotes, movers, etc… as an official site.
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
The Yahoo! Finance API is an online platform that provides access to financial
data. With the API, developers can use Yahoo's financial data to build custom
applications and analytical tools, including stock portfolios, pricing alerts
and other data-driven services.
The Yahoo! Finance API offers a comprehensive set of features and functions,
including historical quotes, stock market news and comprehensive financial
data. This data can be used to build custom financial applications and
analytics tools, such as stock portfolio analysis, stock price alerts and other
data-driven services.
Yahoo! Finance API allows developers to access financial data from across a
range of markets and securities, including stocks, mutual funds, options and
futures. With access to real-time market data, developers can build interactive
charts and trading systems, portfolio monitoring and stock market analysis.
Examples of applications you can build using Yahoo! Finance API:
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
yahoo_finance_by_apidojo: {
type: "app",
app: "yahoo_finance_by_apidojo",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://apidojo-yahoo-finance-v1.p.rapidapi.com/auto-complete`,
headers: {
"X-RapidAPI-Key": `${this.yahoo_finance_by_apidojo.$auth["X-RapidAPI-Key"]}`,
"X-RapidAPI-Host": `apidojo-yahoo-finance-v1.p.rapidapi.com`,
},
params: {
"q": `tesla`,
region: `US`,
},
})
},
})
Python API on Pipedream offers developers to build or automate a variety of
tasks from their web and cloud apps. With the Python API, users are able to
create comprehensive and flexible scripts, compose and manage environment
variables, and configure resources to perform a range of functions.
By using Pipedream, you can easily:
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}}