What do you want to automate
with Confection and Python?
Prompt, edit and deploy AI agents that connect to Confection, Python and 2,500+ other apps in seconds.
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Popular Confection and Python Triggers#
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
Popular Confection and Python Actions#
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.
Overview of Confection#
Confection API provides a robust solution for collecting, managing, and utilizing user data in compliance with privacy regulations. It helps businesses capture data lost due to ad blockers and privacy tech, ensuring you don't miss out on valuable insights. With Pipedream, you can harness this data in real-time, triggering actions, analyzing trends, or integrating with other services for a comprehensive data strategy.
Connect Confection#
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,
})
},
})
Overview of Python#
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:
Connect Python#
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}}Trusted by 1,000,000+ developers from startups to Fortune 500 companies