MySQL is an open-source relational database management system.
Emit new event when you add or modify a new row in a table. See the docs here
Emit new event when new rows are returned from a custom query. See the docs here
Emit new event when a new table is added to a database. See the docs here
Extracts information from texts with a given extractor. See the docs here
The MySQL application on Pipedream enables direct interaction with your MySQL databases, allowing you to perform CRUD operations—create, read, update, delete—on your data with ease. You can leverage these capabilities to automate data synchronization, report generation, and event-based triggers that kick off workflows in other apps. With Pipedream's serverless platform, you can connect MySQL to hundreds of other services without managing infrastructure, crafting complex code, or handling authentication.
import mysql from '@pipedream/mysql';
export default defineComponent({
props: {
mysql,
},
async run({steps, $}) {
// Component source code:
// https://github.com/PipedreamHQ/pipedream/tree/master/components/mysql
const queryObj = {
sql: "SELECT NOW()",
values: [], // Ignored since query does not contain placeholders
};
return await this.mysql.executeQuery(queryObj);
},
});
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.
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,
})
},
})