What do you want to automate
with Tomba and Python?
Prompt, edit and deploy AI agents that connect to Tomba, Python and 3,000+ other apps in seconds.
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Popular Tomba and Python Actions#
Look up person and company data based on an email. See the documentation
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Generate or retrieve the most likely email address from a blog post URL. See the documentation
Generate or retrieve the most likely email address from a domain name, a first name and a last name. See the documentation
Generate or retrieve the most likely email address from a LinkedIn URL. See the documentation
Overview of Tomba#
The Tomba API is a comprehensive email finder and verification service that enables you to discover, verify, and enrich email addresses and contact data. With Tomba, you can find email addresses from domains, names, LinkedIn profiles, or blog posts, verify email deliverability, and gather detailed company intelligence. Leverage Pipedream's capabilities to integrate Tomba with hundreds of other apps, creating powerful automated workflows for lead generation, email verification, contact enrichment, and competitive research.
Connect Tomba#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
tomba: {
type: "app",
app: "tomba",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.tomba.io/v1/me`,
headers: {
"X-Tomba-Key": `${this.tomba.$auth.api_key}`,
"X-Tomba-Secret": `${this.tomba.$auth.api_secret}`,
},
})
},
})
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