ProAbono is the smart subscription management software that automates your daily routine.
Emit new event when a new customer is created. See the documentation
Emit new event when a new offer is created. See the documentation
Emit new event when a new subscription is created. See the documentation
Creates a new customer or updates an existing one in the ProAbono system. See the documentation
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Initializes a new subscription for a customer in the ProAbono system. See the documentation
Fetches an existing customer from the proabono system. See the documentation
ProAbono is a service built to manage subscription billing with fine-grained control over pricing, features, customers, and usage. With the ProAbono API, Pipedream can be your automation partner to streamline subscription operations. Use cases include synchronizing customer data, updating subscription details, and managing billing events. Pipedream's serverless platform allows you to trigger workflows on schedule, by webhook, or via other app events, making it ideal for integrating with ProAbono to handle complex subscription logic.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
proabono: {
type: "app",
app: "proabono",
}
},
async run({steps, $}) {
return await axios($, {
url: `${this.proabono.$auth.api_endpoint}/v1/Customers`,
headers: {
"Accept": `application/json`,
},
auth: {
username: `${this.proabono.$auth.agent_key}`,
password: `${this.proabono.$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}}