Rockset is a serverless search and analytics engine that allows you to create live dashboards and real-time data APIs on DynamoDB, Kafka, S3 and more.
Add documents to a collection in Rockset. Learn more at https://docs.rockset.com/rest/#adddocuments.
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Create a new integration with Rockset. Learn more at https://docs.rockset.com/rest/#createintegration
Rockset is a real-time indexing database service designed for low-latency, high-concurrency analytics. With the Rockset API, you can query your datasets, create and manage collections, and integrate with event streams for real-time analytics. Using Pipedream's serverless platform, you can automate workflows that react to database events, sync data across services, or trigger actions based on analytical insights.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
rockset: {
type: "app",
app: "rockset",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.rs2.usw2.rockset.com/v1/orgs/self/users/self`,
headers: {
"Authorization": `ApiKey ${this.rockset.$auth.apikey}`,
},
})
},
})
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}}