Browserless is a service that allows you to run headless Chrome instances in the cloud.
The Browserless API on Pipedream allows you to automate browser actions without the overhead of managing your own browser infrastructure. This service provides a way to run Chrome browser sessions programmatically, making it ideal for web scraping, automated testing, and screenshot capture. Leveraging this on Pipedream, you can create serverless workflows that interact with web pages, extract data, and perform actions as a human would, all in a scalable and efficient manner.
import puppeteer from 'puppeteer-core@14.1.0';
export default defineComponent({
props: {
browserless: {
type: "app",
app: "browserless",
}
},
async run({steps, $}) {
// See the browserless docs for more info:
// https://www.browserless.io/docs/
const browser = await puppeteer.connect({
browserWSEndpoint: `wss://chrome.browserless.io?token=${this.browserless.$auth.api_key}`
})
const page = await browser.newPage()
const url = "https://example.com"
const type = "png"
await page.goto(url)
const screenshot = await page.screenshot()
// export the base64-encoded screenshot for use in future steps,
// along with the image type and filename
$.export("screenshot", Buffer.from(screenshot, 'binary').toString('base64'))
$.export("type", type)
$.export("filename",`${url.replace(/[&\/\\#, +()$~%.'":*?<>{}]/g, '_')}-${+new Date()}.${type}`)
await browser.close()
},
})
You can execute custom Go scripts on-demand or in response to various triggers and integrate with thousands of apps supported by Pipedream. Writing with Go on Pipedream enables backend operations like data processing, automation, or invoking other APIs, all within the Pipedream ecosystem. By leveraging Go's performance and efficiency, you can design powerful and fast workflows to streamline complex tasks.
package main
import (
"fmt"
pd "github.com/PipedreamHQ/pipedream-go"
)
func main() {
// Access previous step data using pd.Steps
fmt.Println(pd.Steps)
// Export data using pd.Export
data := make(map[string]interface{})
data["name"] = "Luke"
pd.Export("data", data)
}