Kontent.ai
Complete control over your content. Kontent AI is the headless CMS that enables organizations to govern all things content to deliver standout experiences.
Integrate the Kontent.ai API with the Python API
Setup the Kontent.ai API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Kontent.ai and Python remarkably fast. Free for developers.
Popular Ways to Connect Kontent.ai with Python#
Popular Kontent.ai and Python Triggers#
Emit new event when a content item is created.
Emit new event when a content item is deleted.
Emit new event when a content item is moved to another workflow step.
Emit new event when a content item is published.
Emit new event when a content item is retored in a specific language after deletion.
Popular Kontent.ai and Python Actions#
Create a new content item based on a specific content type. See the documentation
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Overview of Kontent.ai#
The Kontent.ai API offers robust content management capabilities for developers to manage and deliver content across various platforms. With this API, you can automate content creation, update content items, retrieve assets, and sync your content with other services. On Pipedream, you can harness these features to create powerful workflows that trigger on specific events, process data, and connect with other apps to streamline your content operations.
Connect Kontent.ai#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
kontent_ai: {
type: "app",
app: "kontent_ai",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://manage.kontent.ai/v2/projects/${this.kontent_ai.$auth.environment}/items`,
headers: {
Authorization: `Bearer ${this.kontent_ai.$auth.management_api_key}`,
"Content-Type": `application/json`,
},
})
},
})
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}}