Search API
Your real-time SERP API solution. Mastering proxy management, CAPTCHAs, and JSON parsing for seamless web data extraction.
Integrate the Search API API with the Python API
Setup the Search API API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Search API and Python remarkably fast. Free for developers.
Popular Search API and Python Actions#
Google Images API uses /api/v1/search?engine=google_images API endpoint to scrape real-time results. See the documentation
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Google Search API uses /api/v1/search?engine=google API endpoint to scrape real-time results. See the documentation
Google Trends API uses /api/v1/search?engine=google_trends API endpoint to scrape real-time results. See the documentation
Overview of Search API#
The Search API API allows you to create and manage a search engine for your website or application, providing robust search capabilities like full-text search, faceting, filtering, and autocomplete. Integrating this API into Pipedream workflows unleashes the potential for automating content indexing, performing complex searches based on triggers, and synchronizing search results with other apps for analytics, monitoring, or further processing.
Connect Search API#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
search_api: {
type: "app",
app: "search_api",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://www.searchapi.io/api/v1/search`,
params: {
"q": `{{your_query}}`, //string to use as search query
engine: `{{your_engine}}`, //ex. "google"
api_key: `${this.search_api.$auth.api_key}`,
},
})
},
})
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}}