Browse AI

The easiest way to extract structured data from any website with no coding.

Integrate the Browse AI API with the Snowflake API

Setup the Browse AI API trigger to run a workflow which integrates with the Snowflake API. Pipedream's integration platform allows you to integrate Browse AI and Snowflake remarkably fast. Free for developers.

Execute Task with Browse AI API on New Row from Snowflake API
Snowflake + Browse AI
 
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Execute Task with Browse AI API on New Query Results from Snowflake API
Snowflake + Browse AI
 
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Execute Task with Browse AI API on Failed Task in Schema from Snowflake API
Snowflake + Browse AI
 
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Execute Task with Browse AI API on New Database from Snowflake API
Snowflake + Browse AI
 
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Execute Task with Browse AI API on New Deleted Role from Snowflake API
Snowflake + Browse AI
 
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New Row from the Snowflake API

Emit new event when a row is added to a table

 
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Task Completed (Instant) from the Browse AI API

Emits an event when a Browse AI task is completed. See the documentation

 
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New Query Results from the Snowflake API

Run a SQL query on a schedule, triggering a workflow for each row of results

 
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Task Finished With Error (Instant) from the Browse AI API

Emit new event when a task finishes with an error. See the documentation

 
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Failed Task in Schema from the Snowflake API

Emit new events when a task fails in a database schema

 
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Execute Task with the Browse AI API

Runs a robot on-demand with custom input parameters. See the documentation

 
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Insert Multiple Rows with the Snowflake API

Insert multiple rows into a table

 
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Insert Single Row with the Snowflake API

Insert a row into a table

 
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Overview of Browse AI

The Browse AI API enables the automation of data extraction from websites, turning web pages into organized data. It's built for non-coders and coders alike, allowing for custom web scraping and monitoring tasks. Within Pipedream, you can harness Browse AI to create intricate workflows that trigger actions in other apps based on the data you extract. Think of automated competitive analysis, price tracking, or content changes detection, all streamlined through Pipedream's serverless platform.

Connect Browse AI

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    browse_ai: {
      type: "app",
      app: "browse_ai",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.browse.ai/v2/robots`,
      headers: {
        Authorization: `Bearer ${this.browse_ai.$auth.api_key}`,
      },
    })
  },
})

Overview of Snowflake

Snowflake offers a cloud database and related tools to help developers create robust, secure, and scalable data warehouses. See Snowflake's Key Concepts & Architecture.

Getting Started

1. Create a user, role and warehouse in Snowflake

Snowflake recommends you create a new user, role, and warehouse when you integrate a third-party tool like Pipedream. This way, you can control permissions via the user / role, and separate Pipedream compute and costs with the warehouse. You can do this directly in the Snowflake UI.

We recommend you create a read-only account if you only need to query Snowflake. If you need to insert data into Snowflake, add permissions on the appropriate objects after you create your user.

2. Enter those details in Pipedream

Visit https://pipedream.com/accounts. Click the button to Connect an App. Enter the required Snowflake account data.

You'll only need to connect your account once in Pipedream. You can connect this account to multiple workflows to run queries against Snowflake, insert data, and more.

3. Build your first workflow

Visit https://pipedream.com/new to build your first workflow. Pipedream workflows let you connect Snowflake with 1,000+ other apps. You can trigger workflows on Snowflake queries, sending results to Slack, Google Sheets, or any app that exposes an API. Or you can accept data from another app, transform it with Python, Node.js, Go or Bash code, and insert it into Snowflake.

Learn more at Pipedream University.

Connect Snowflake

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import { promisify } from 'util'
import snowflake from 'snowflake-sdk'

export default defineComponent({
  props: {
    snowflake: {
      type: "app",
      app: "snowflake",
    }
  },
  async run({steps, $}) {
    const connection = snowflake.createConnection({
      ...this.snowflake.$auth,
      application: "PIPEDREAM_PIPEDREAM",
    })
    const connectAsync = promisify(connection.connect)
    await connectAsync()
    
    async function connExecuteAsync(options) {
      return new Promise((resolve, reject) => {
        connection.execute({
          ...options,
          complete: function(err, stmt, rows) {
            if (err) {
              reject(err)
            } else {
              resolve({stmt, rows})
            }
          }
        })
      })
    }
    
    // See https://docs.snowflake.com/en/user-guide/nodejs-driver-use.html#executing-statements
    const { rows } = await connExecuteAsync({
      sqlText: `SELECT CURRENT_TIMESTAMP()`,
    })
    return rows
  },
})