Confection collects, stores, and distributes data in a way that's unaffected by client-side disruptions involving cookies, cross-domain scripts, and device IDs. It's also compliant with global privacy laws so it’s good for people too.
Emit new event when a UUID receives a value for the configured Event Name. The latest value as well a history of all values ever received for that Event Name will be returned.
Emit new event when the UUID is significant enough to be classified as a lead. You define the field of significance and if a UUID gets a value for this field, it will trigger.
Emit new event when any UUID is created or updated. To learn more about how Confection handles UUIDs, visit https://confection.io/main/demo/#uuid.
This action will retrieve the full details of a specified UUID.
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
This action will retrieve all UUIDs that have a likeness score of at least 50 (default) with the provided UUID. The likeness score can be customized in configuration.
Confection is an API that enables you to easily create and manage serverless
functions. Using Confection, you can deploy your functions to any number of
providers, including AWS Lambda, Google Cloud Functions, and Azure Functions.
Confection also provides a convenient command-line interface, making it easy to
manage your functions from your terminal.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
confection: {
type: "app",
app: "confection",
}
},
async run({steps, $}) {
const data = {
"key": `${this.confection.$auth.secret_key}`,
}
return await axios($, {
url: `https://transmission.confection.io/${this.confection.$auth.account_id}/account/`,
data,
})
},
})
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}}