Best web scraping APIs to extract HTML content without getting blocked.
Retrieve data from a social media scraping job by responseId. See the documentation
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Use ScrapingBot API to initiate scraping data from a social media site. See the documentation
Use ScrapingBot API to extract specific data from Google or Bing search results. See the documentation
Use ScrapingBot API to extract specific data from a webpage. See the documentation
ScrapingBot API on Pipedream allows you to scrape websites without getting blocked, fetching crucial information while bypassing common defenses. Whether you're extracting product details, real estate listings, or automating competitor research, this API combined with Pipedream's serverless platform offers you the tools to automate these tasks efficiently. Pipedream's ability to trigger workflows via HTTP requests, schedule them, or react to events, means you can create robust scraping operations that integrate seamlessly with hundreds of other apps.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
scrapingbot: {
type: "app",
app: "scrapingbot",
}
},
async run({steps, $}) {
const data = {
"url": ``,
}
return await axios($, {
method: "post",
url: `http://api.scraping-bot.io/scrape/raw-html`,
headers: {
"Content-Type": `application/json`,
},
auth: {
username: `${this.scrapingbot.$auth.username}`,
password: `${this.scrapingbot.$auth.api_key}`,
},
data,
})
},
})
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:
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}}