Dock Certs
Make any document fraud-proof and instantly verifiable.
Integrate the Dock Certs API with the Python API
Setup the Dock Certs API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Dock Certs and Python remarkably fast. Free for developers.
Popular Dock Certs and Python Triggers#
Emit new event when a new credential is issued. See the documentation
Popular Dock Certs and Python Actions#
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Overview of Dock Certs#
The Dock Certs API provides a means for issuing verifiable credentials and decentralized identities, which are essential for managing digital proofs of various qualifications, memberships, or certifications. Using Pipedream's integration capabilities, you can automate the process of creating, revoking, and verifying these credentials. With Pipedream's serverless architecture, you can set up triggers and actions that respond to events in real-time, orchestrate data flow between Dock Certs and other services, and manage credentials with minimal manual intervention.
Connect Dock Certs#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
dock_certs: {
type: "app",
app: "dock_certs",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://${this.dock_certs.$auth.endpoint}.dock.io/profiles`,
headers: {
"DOCK-API-TOKEN": `${this.dock_certs.$auth.api_key}`,
},
})
},
})
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}}