Zenserp
Zenserp enables you to scrape search engine result pages in a fast and scalable way. Getting SERPs has never been easier.
Integrate the Zenserp API with the Python API
Setup the Zenserp API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Zenserp and Python remarkably fast. Free for developers.
Popular Zenserp and Python Actions#
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Overview of Zenserp#
The Zenserp API enables you to automate search engine queries, parsing SERPs (Search Engine Results Pages) to extract valuable data such as search results, location-based results, and even Google image searches. Within Pipedream's platform, you can harness this API to create workflows that react to various triggers, like webhooks or schedules, to perform automated searches and process the resulting data. This can be powerful for SEO analysis, market research, and content monitoring. Pipedream's serverless architecture makes it seamless to integrate Zenserp with other apps to augment your workflows.
Connect Zenserp#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
zenserp: {
type: "app",
app: "zenserp",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://app.zenserp.com/api/v2/search`,
headers: {
"apikey": `${this.zenserp.$auth.api_key}`,
},
params: {
"q": `Pipedream`,
},
})
},
})
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}}