The Way to build Real-time Data Products
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Tinybird is a real-time analytics API platform that allows developers to ingest, transform, and consume large amounts of data with low latency. By leveraging SQL and data streaming, Tinybird helps in building data-intensive applications or augmenting existing ones with real-time analytics features. On Pipedream, you can automate data ingestion, transformation, and delivery to unlock insights and drive actions in real time, transforming how you respond to user behavior and operational events.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
tinybird: {
type: "app",
app: "tinybird",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.tinybird.co/v0/tokens`,
headers: {
Authorization: `Bearer ${this.tinybird.$auth.token}`,
},
})
},
})
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}}