What do you want to automate
with Verifalia and Python?
Prompt, edit and deploy AI agents that connect to Verifalia, Python and 2,500+ other apps in seconds.
Trusted by 1,000,000+ developers from startups to Fortune 500 companies
Popular Verifalia and Python Actions#
Delete a previously submitted email verification job. See the docs for more information
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Get the number of credit packs and free daily credits available to the account. See the docs for more information
Verify an email address and check if it is properly formatted, really exists and can accept mails, flagging spam traps, disposable emails and much more. See the docs for more information
Verify a list of email address and check if it is properly formatted, really exists and can accept mails, flagging spam traps, disposable emails and much more. See the docs for more information
Overview of Verifalia#
Verifalia's API provides robust email validation and verification services, ensuring that email addresses in your lists are accurate and deliverable. Leveraging Verifalia within Pipedream workflows can automate the process of cleaning up email lists, improve email marketing efficiency, and maintain communication channel integrity. By integrating Verifalia's capabilities, you can cut down on bounces, identify disposable email addresses, and segment lists based on quality scores.
Connect Verifalia#
import { VerifaliaRestClient } from "verifalia"
export default defineComponent({
props: {
verifalia: {
type: "app",
app: "verifalia",
}
},
async run({steps, $}) {
const verifaliaClient = new VerifaliaRestClient({
username: this.verifalia.$auth.username,
password: this.verifalia.$auth.password
});
return await verifaliaClient
.emailValidations
.submit('batman@gmail.com', true);
},
})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