Simple and powerful service for encryption-based data anonymization and community sharing, Enabling GDPR, CCPA, and HIPAA data protection compliance
Encrypts sensitive data using AnonyFlow encryption service with a unique private key managed by AnonyFlow. See the documentation
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Decrypts protected data using AnonyFlow decryption service with a unique private key, managed by AnonyFlow. See the documentation
The AnonyFlow API provides a way to manage and automate data privacy operations. Use it on Pipedream to orchestrate data anonymization workflows for compliance with privacy regulations like GDPR. This API can handle personal data extraction, anonymization, and deletion requests programmatically. With Pipedream's serverless platform, you can integrate these privacy functions into your existing systems, triggering actions based on webhooks, schedules, or other apps' events.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
anonyflow: {
type: "app",
app: "anonyflow",
}
},
async run({steps, $}) {
const data = {
"data": `YOUR_DATA`,
}
return await axios($, {
method: "post",
url: `https://api.anonyflow.com/anony-value`,
headers: {
"x-api-key": `${this.anonyflow.$auth.api_key}`,
"accept": `application/json`,
},
data,
})
},
})
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}}