Klazify
The most accurate Content Classification API.
Integrate the Klazify API with the Python API
Setup the Klazify API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Klazify and Python remarkably fast. Free for developers.
Popular Klazify and Python Actions#
Submit a website URL for categorization by the API. See the documentation.
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Get information about a company's domain. See the documentation.
Get the expiration date of a domain. See the documentation.
Get the technology stack of a domain. See the documentation.
Overview of Klazify#
The Klazify API offers a way to classify websites into categories, discover company logo URLs, and access social media links from a domain. When integrated into Pipedream, this functionality can expand, allowing you to automate workflows for marketing analysis, content filtering, or business intelligence. You can trigger actions based on website categories, enrich CRM data with company logos, or compile lists of social media profiles for outreach.
Connect Klazify#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
klazify: {
type: "app",
app: "klazify",
}
},
async run({steps, $}) {
const data = {
"url": `{your_url}`,
}
return await axios($, {
method: "post",
url: `https://www.klazify.com/api/categorize`,
headers: {
Authorization: `Bearer ${this.klazify.$auth.api_key}`,
"Accept": `application/json`,
"Content-Type": `application/json`,
},
data,
})
},
})
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}}