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MonkeyLearn

Text Analysis

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Integrate the MonkeyLearn API with the PostgreSQL API

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

Popular Ways to Connect MonkeyLearn with PostgreSQL

Classify Text with MonkeyLearn API on New Column from PostgreSQL API
PostgreSQL + MonkeyLearn
 
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Classify Text with MonkeyLearn API on New or Updated Row from PostgreSQL API
PostgreSQL + MonkeyLearn
 
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Classify Text with MonkeyLearn API on New Row Custom Query from PostgreSQL API
PostgreSQL + MonkeyLearn
 
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Classify Text with MonkeyLearn API on New Row from PostgreSQL API
PostgreSQL + MonkeyLearn
 
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Classify Text with MonkeyLearn API on New Table from PostgreSQL API
PostgreSQL + MonkeyLearn
 
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Popular MonkeyLearn and PostgreSQL Triggers

New Column from the PostgreSQL API

Emit new event when a new column is added to a table. See the documentation

 
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New or Updated Row from the PostgreSQL API

Emit new event when a row is added or modified. See the documentation

 
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New Row from the PostgreSQL API

Emit new event when a new row is added to a table. See the documentation

 
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New Row Custom Query from the PostgreSQL API

Emit new event when new rows are returned from a custom query that you provide. See the documentation

 
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New Table from the PostgreSQL API

Emit new event when a new table is added to the database. See the documentation

 
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Popular MonkeyLearn and PostgreSQL Actions

Classify Text with the MonkeyLearn API

Classifies texts with a given classifier. See the docs here

 
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Delete Row(s) with the PostgreSQL API

Deletes a row or rows from a table. See the documentation

 
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Extract Text with the MonkeyLearn API

Extracts information from texts with a given extractor. See the docs here

 
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Execute Custom Query with the PostgreSQL API

Executes a custom query you provide. See the documentation

 
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Upload Training Data with the MonkeyLearn API

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

 
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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

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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 PostgreSQL

On Pipedream, you can leverage the PostgreSQL app to create workflows that automate database operations, synchronize data across platforms, and react to database events in real-time. Think handling new row entries, updating records from webhooks, or even compiling reports on a set schedule. Pipedream's serverless platform provides a powerful way to connect PostgreSQL with a variety of apps, enabling you to create tailored automation that fits your specific needs.

Connect PostgreSQL

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import postgresql from "@pipedream/postgresql"

export default defineComponent({
  props: {
    postgresql,
  },
  async run({ steps, $ }) {
    // Component source code:
    // https://github.com/PipedreamHQ/pipedream/tree/master/components/postgresql

    const queryObj = {
      text: "SELECT NOW()",
      values: [], // Ignored since query does not contain placeholders
    };
    const { rows } = await this.postgresql.executeQuery(queryObj);
    return rows;
  },
})
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