Extract Text with MonkeyLearn API on Weekly schedule from Schedule API

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Trigger workflow on

Weekly schedule from the Schedule API

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Extract Text with the MonkeyLearn API

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Getting Started#

This integration creates a workflow with a Schedule trigger and MonkeyLearn action. When you configure and deploy the workflow, it will run on Pipedream's servers 24x7 for free.

Select this integration
Configure the Weekly schedule trigger
1. Connect your Schedule account
2. Configure Cron Schedule
Configure the Extract Text action
1. Connect your MonkeyLearn account
2. Select a Extractor Id
3. Configure Data
4. Optional- Configure Production Model
Deploy the workflow
Send a test event to validate your setup
Turn on the trigger

Details#

This integration uses pre-built, source-available components from Pipedream's GitHub repo. These components are developed by Pipedream and the community, and verified and maintained by Pipedream.

To contribute an update to an existing component or create a new component, create a PR on GitHub. If you're new to Pipedream component development, you can start with quickstarts for trigger span and action development, and then review the component API reference.

Trigger#

Weekly schedule on Schedule

Description:Trigger your workflow on one or more days each week at a specific time (with timezone support).

Version:0.0.1

Key:schedule-weekly

View on GitHub

Schedule Overview#

The Schedule app in Pipedream is a powerful tool that allows you to trigger workflows at regular intervals, ranging from every minute to once a year. This enables the automation of repetitive tasks and the scheduling of actions to occur without manual intervention. By leveraging this API, you can execute code, run integrations, and process data on a reliable schedule, all within Pipedream's serverless environment.

Trigger Code#

import schedule from "../../schedule.app.mjs";

export default {
  name: "Weekly schedule",
  version: "0.0.1",
  key: "schedule-weekly",
  type: "source",
  description: "Trigger your workflow on one or more days each week at a specific time (with timezone support).",
  props: {
    schedule,
    cron: {
      propDefinition: [
        schedule,
        "cron",
      ],
      default: {
        cron: "0 10 * * 1",
      },
    },
  },
};

Trigger Configuration#

This component may be configured based on the props defined in the component code. Pipedream automatically prompts for input values in the UI and CLI.

Label	Prop	Type	Description
Schedule	`schedule`	`app`	This component uses the Schedule app.
Cron Schedule	`cron`	`$.interface.timer`	Enter a cron expression

Trigger Authentication#

The Schedule API does not require authentication.

About Schedule#

Trigger workflows on an interval or cron schedule.

Action#

Extract Text on MonkeyLearn

Description:Extracts information from texts with a given extractor. [See the docs here](https://monkeylearn.com/api/v3/#extract)

Version:0.0.1

Key:monkeylearn-extract-text

View on GitHub

MonkeyLearn Overview#

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.

Action Code#

import app from "../../monkeylearn.app.mjs";
import { ConfigurationError } from "@pipedream/platform";

export default {
  key: "monkeylearn-extract-text",
  name: "Extract Text",
  description: "Extracts information from texts with a given extractor. [See the docs here](https://monkeylearn.com/api/v3/#extract)",
  version: "0.0.1",
  type: "action",
  props: {
    app,
    extractorId: {
      propDefinition: [
        app,
        "extractorId",
      ],
    },
    data: {
      propDefinition: [
        app,
        "data",
      ],
    },
    productionModel: {
      propDefinition: [
        app,
        "productionModel",
      ],
    },
  },
  async run({ $ }) {
    const {
      extractorId,
      data,
      productionModel,
    } = this;
    if (!data || !Array.isArray(data) || data.length === 0) {
      throw new ConfigurationError("Data array is required and must have at least one string to be classified.");
    }
    const response = await this.app.extractText($, extractorId, data, productionModel);
    $.export("$summary", "Successfully extracted from all elements");
    return response;
  },
};

Action Configuration#

This component may be configured based on the props defined in the component code. Pipedream automatically prompts for input values in the UI.

Label	Prop	Type	Description
MonkeyLearn	`app`	`app`	This component uses the MonkeyLearn app.
Extractor Id	`extractorId`	`string`	Select a value from the drop down menu.
Data	`data`	`string[]`	A list of up to 500 data elements. Each element must be a string with the text.
Production Model	`productionModel`	`boolean`	Indicates if the extractions are performed by the production model. Only use this parameter on custom models. Note that you first need to deploy your model to production.

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Popular Triggers#

Custom Interval from the Schedule API

Trigger your workflow every N hours, minutes or seconds.

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Daily schedule from the Schedule API

Trigger your workflow every day.

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Monthly Schedule from the Schedule API

Trigger your workflow on one or more days each month at a specific time (with timezone support).

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Weekly schedule from the Schedule API

Trigger your workflow on one or more days each week at a specific time (with timezone support).

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Popular Actions#

Classify Text with the MonkeyLearn API

Classifies texts with a given classifier. See the docs here

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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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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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