#1 Platform For Marketing & Customer Engagement On WhatsApp
The WATI API allows you to power up your customer engagement by leveraging WhatsApp messaging. With Pipedream's capabilities, you can create serverless workflows that integrate WATI to automate personalized notifications, process inbound messages, and manage contacts. This can help scale your customer service, marketing campaigns, and streamline communications with WhatsApp's wide user base.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
wati: {
type: "app",
app: "wati",
}
},
async run({steps, $}) {
return await axios($, {
url: `${this.wati.$auth.api_endpoint}/api/v1/getContacts`,
headers: {
"Accept": `*/*`,
"Authorization": `${this.wati.$auth.access_token}`,
},
})
},
})
Snowflake offers a cloud database and related tools to help developers create robust, secure, and scalable data warehouses. See Snowflake's Key Concepts & Architecture.
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.
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.
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.
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
},
})