Transactional email service that delivers
Emit new event when the recipient clicks a link in your email. See the documentation
Emit new event when your email is successfully delivered with no errors. See the documentation
Emit new event when your email is not delivered. See the documentation
Emit new event when the recipient receives your email and opens it. See the documentation
Emit new event when your email is sent from the sending servers. See the documentation
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
This action sends a personalized e-mail to the specified recipient. See the documentation
This action sends a personalized e-mail to the specified recipient using templates. See the documentation
The MailerSend API integrates with Pipedream to create powerful email automation workflows, enabling you to send transactional emails, create and manage templates, and track email activities like opens or clicks. With these capabilities, you can automate routine communications, personalize mass mailings based on user actions or data, and gain insights into your email campaign performances, all within the context of a serverless Pipedream workflow.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
mailersend: {
type: "app",
app: "mailersend",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.mailersend.com/v1/domains`,
headers: {
Authorization: `Bearer ${this.mailersend.$auth.api_token}`,
},
})
},
})
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}}