What do you want to automate
with Constant Contact and Python?
Prompt, edit and deploy AI agents that connect to Constant Contact, Python and 3,000+ other apps in seconds.
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Popular Constant Contact and Python Actions#
Add a new email address to your Constant Contact account. This action sends a confirmation email to the new address. Once confirmed, the email address can be used in the from_email and reply_to_email fields of your email campaigns. See the documentation
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Create a new email campaign. See the documentation
Create a new contact or update an existing one based on their email address. This method is appropriate when a contact has given explicit permission to receive emails. See the documentation
Overview of Constant Contact#
The Constant Contact API allows users to automate email marketing efforts by managing contacts, sending emails, and tracking results. With Pipedream, you can connect Constant Contact to other apps to create powerful workflows. You can trigger events, sync contact lists, automate email campaigns, and analyze email performance with ease. Pipedream's serverless platform offers a streamlined approach to integrating Constant Contact's functionalities into diverse, automated sequences.
Connect Constant Contact#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
constant_contact: {
type: "app",
app: "constant_contact",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.cc.email/v3/account/summary`,
headers: {
Authorization: `Bearer ${this.constant_contact.$auth.oauth_access_token}`,
},
})
},
})
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