Accredible is the industry-leading digital credentialing platform. Securely issue, manage, track, and verify your credentials faster and more easily for a fraction of the cost.
This source triggers when a new credential is issued to a recipient. See the documentation.
Emit new event when an existing credential's details are updated or modified. See the documentation.
Issue a new credential to a given recipient. See the documentation
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Remove a specific credential from the system. See the documentation
Modify the details of an existing credential. See the documentation
The Accredible API lets you automate the creation and management of digital certificates, badges, and blockchain credentials. Using Pipedream, you can connect the Accredible API to myriad services for streamlined workflow automation. Create digital certificates when a student completes a course, update credentials with new information, or share achievements across social platforms or via email. Pipedream's serverless platform enables you to integrate these actions with other apps, such as learning management systems, CRMs, and communication tools, without writing extensive code.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
accredible: {
type: "app",
app: "accredible",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.accredible.com/v1/issuer/details`,
headers: {
"Content-Type": `application/json`,
"Authorization": `Token token=${this.accredible.$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}}