CoinMarketCap is a website that provides cryptocurrency market cap rankings, charts, and more.
Returns all static metadata available for one or more cryptocurrencies. See the documentation
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Returns a mapping of all cryptocurrencies to unique CoinMarketCap ids. See the documentation
Returns a paginated list of all active cryptocurrencies with latest market data. See the documentation
Returns the latest market quote for 1 or more cryptocurrencies. Use the ""convert"" option to return market values in multiple fiat and cryptocurrency conversions in the same call. At least one ""id"" or ""slug"" or ""symbol"" is required for this request. See the documentation
The CoinMarketCap API delivers real-time and historical cryptocurrency market data, including price, volume, market cap, and much more, for over 9,000 cryptocurrencies. With this data, you can track crypto trends, compare currency performance, or integrate up-to-date information into apps, widgets, or websites. Pipedream's platform enables developers to create automated workflows that can harness the vast array of data from CoinMarketCap to trigger actions, notify stakeholders, or power analytics dashboards.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
coinmarketcap: {
type: "app",
app: "coinmarketcap",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://${this.coinmarketcap.$auth.environment}-api.coinmarketcap.com/v1/key/info`,
headers: {
"X-CMC_PRO_API_KEY": `${this.coinmarketcap.$auth.api_key}`,
},
})
},
})
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:
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}}