MonkeyLearn
Text Analysis
Integrate the MonkeyLearn API with the Snowflake API
Setup the MonkeyLearn API trigger to run a workflow which integrates with the Snowflake API. Pipedream's integration platform allows you to integrate MonkeyLearn and Snowflake remarkably fast. Free for developers.
Popular MonkeyLearn and Snowflake Triggers#
Popular MonkeyLearn and Snowflake Actions#
Extracts information from texts with a given extractor. See the docs here
Uploads data to a classifier. This component can be used to upload new data to a classifier, to update the tags of texts that have already been uploaded, or both. See the docs here
Overview of MonkeyLearn#
MonkeyLearn is a text analysis platform that employs machine learning to extract and process data from chunks of text. By leveraging the MonkeyLearn API on Pipedream, you can automate the categorization of text, extract specific data, analyze sentiment, and more, all in real-time. This enables the development of powerful custom workflows that can analyze customer feedback, automate email processing, or provide insightful analytics on textual data from various sources.
Connect MonkeyLearn#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
monkeylearn: {
type: "app",
app: "monkeylearn",
}
},
async run({steps, $}) {
const data = {
"data": [
"This is a great tool!",
]
}
return await axios($, {
method: "post",
url: `https://api.monkeylearn.com/v3/classifiers/cl_pi3C7JiL/classify/`,
headers: {
"Authorization": `Token ${this.monkeylearn.$auth.api_key}`,
"Content-Type": `application/json`,
},
data,
})
},
})
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#
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
},
})