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Monkey Learn + Microsoft To-Do Integrations

Appy Pie Connect allows you to automate multiple workflows between Monkey Learn and Microsoft To-Do

About Monkey Learn

Create new value from your data. Train custom machine learning models to get topic, sentiment, intent, keywords and more.

About Microsoft To-Do

Microsoft To Do is the task management app that makes it easy to stay organized and manage your life. It's simple, smart, and a whole new way to get work done in less time.

Microsoft To-Do Integrations
Microsoft To-Do Alternatives

Connect the apps you use everyday and find your productivity super-powers.

  • Todoist Todoist
  • Google Tasks Google Tasks
  • Asana Asana
Connect Monkey Learn + Microsoft To-Do in easier way

It's easy to connect Monkey Learn + Microsoft To-Do without coding knowledge. Start creating your own business flow.

    Triggers
  • New List

    Triggers when a new list is created.

  • New Task

    Triggers when a new task is created.

  • Updated Task

    Triggers when any task is update.

    Actions
  • Classify Text

    Classifies texts with a given classifier.

  • Extract Text

    Extracts information from texts with a given extractor.

  • Upload training Data

    Uploads data to a classifier.

  • Create List

    Creates a new list.

  • Create Task

    Creates a new task

How Monkey Learn & Microsoft To-Do Integrations Work

  1. Step 1: Choose Monkey Learn as a trigger app and Select "Trigger" from the Triggers List.

    (30 seconds)

  2. Step 2: Authenticate Monkey Learn with Appy Pie Connect.

    (10 seconds)

  3. Step 3: Select Microsoft To-Do as an action app.

    (30 seconds)

  4. Step 4: Pick desired action for the selected trigger.

    (10 seconds)

  5. Step 5: Authenticate Microsoft To-Do with Appy Pie Connect.

    (2 minutes)

  6. Your Connect is ready! It's time to start enjoying the benefits of workflow automation.

Integration of Monkey Learn and Microsoft To-Do

Intro paragraph. Monkey Learn is a machine learning platform that enables your apps to perform sentiment analysis, text classification, image labeling and many other artificial intelligence tasks. We’ll use a sample that uses Monkey Learn for a Microsoft To-Do project.

The purpose of my project is to create a Microsoft To-Do list that will be sent to my friend. The project focuses on the integration of Monkey Learn and Microsoft To-Do, which means that I will use Monkey Learn as a top to achieve this project. The project consists of two steps. The first step is to create a script using Monkey Learn, the second step is to create a Microsoft To-Do list using the script created in the first step.

The first step is to create a script using Monkey Learn. A script is a Python file that contains an example and documentation. Below is an example of a script:

# Machine Learning for Beginners. Sentiment Analysis with MonkeyLearn # https://www.youtube.com/watch?v=3p5Q7aB0Wqs import requests from bs4 import BeautifulSoup from pprint import pprint # Enter your API KEY, Token and Project ID here MONKEY_LEARN_API_KEY = 'YOUR_MONKEY_LEARN_API_KEY' MONKEY_LEARN_TOKEN = 'YOUR_MONKEY_LEARN_TOKEN' MONKEY_LEARN_PROJECT_ID = 'YOUR_MONKEY_LEARN_PROJECT_ID' # Create an instance of the bot class bot = botbuilder.Bot(MONKEY_LEARN_TOKEN. def sentiment(text). try. return bot.sentiment(text. except botbuilder.exceptions.MalformedSentimentException as e. return 'Not implemented yet!' def image_analyze(image_file). try. return bot.image_analyze(image_file. except botbuilder.exceptions.ImageAnalyzeException as e. return 'Not implemented yet!' def process(input). print(input. result = { "title". input[0], "description". input[1] } if input[2] == "todo". result["action"] = "done" else. result["action"] = "create" return result if __name__ == '__main__'. soup = BeautifulSoup(open("to-do-list.html".read(). content = soup.find('div', id="content". content = content.findAll('li'. for li in content. title = li.findAll('h3')[1].getText(. description = li.findAll('p')[1].getText(. if title == "To do". response = process(content. print(response. break

This script contains three functions, namely sentiment, image_analyze, and process. Function sentiment returns the sentiment of the given text, function image_analyze returns whether the given image is positive or negative, and function process returns all data needed for writing into Microsoft To-Do.

The second step is to create a Microsoft To-Do list using the script created in the first step by using the content returned by the script in the first step. This task invpves creating a new page in Microsoft To-Do called “To do” by using the code below:

var TodoListPage = require("sdk/js/todo-page"); var page = new TodoListPage(); var title = document.getElementById("title"); var description = document.getElementById("description"); var todoTextArea = document.getElementById("todo-text"); var doneTextArea = document.getElementById("done"); var attachments = []; var attachment; var request; function onLoad(. { // Get the value of the inputs var values = {title. document.getElementById("title".value, description. document.getElementById("description". }; // Create an array for storing an attachments (images. var attachments = []; var attachment; var request; // Set the title of the page page.setTitle(values); // Set the description of the page page.setDescription(values); // Get the task from the given input todoTextArea.value = values["title"] + ":" + values["description"]; // Create an array for storing an attachments (images. attachments = []; attachment = document.createElement("img"); value = document.createTextNode("Attachment 1"); attachment.appendChild(value); attachment = document.createElement("img"); value = document.createTextNode("Attachment 2"); attachment.appendChild(value); attachment = document.createElement("img"); value = document.createTextNode("Attachment 3"); attachment.appendChild(value); // Add an attachments todoTextArea.value += "

" + JSON.stringify(attributes. + "

"; // Create a new item in Todo List page.addItemToList({ listId. "1", title. values["title"], description. values["description"], dueDate. Date((new Date(.getTime(. + 86400000. - 3600 * 60 * 60), attachments. attachments }); // Clear an input field document.getElementById("title".value="; document.getElementById("description".value="; } function onBeforeSend(. { // Set an status of attachments as pending request = page.addAttachment({ listId. "1", title. values["title"], description. values["description"], dueDate. Date((new Date(.getTime(. + 86400000. - 3600 * 60 * 60), attachments. attachments }); // Set an status of this item as true request.isCompleted = true; } function onLoadError(. { conspe.error('ERROR. ' + JSON.stringify(e)); } <!DOCTYPE html> <html> <head> <meta charset="UTF-8"> <meta name="viewport" content="width=device-width, initial-scale=1"> <!-- Ppyfills --> <script src="node_modules/core-js/client/shim.min.js"></script> <script src="node_modules/zone.js/dist/zone.min.js"></script> <!-- SystemJS --> <script src="node_modules/systemjs/dist/system-ppyfills.js"></script> <script src="systemjs.config.js"></script> <script> System .import( 'app' . .catch(conspe .error .bind(conspe)); </script> </head> <body> <div class="container"> <h2>Machine Learning for Beginners</h2> <hr /> <h4>Creating a Google Sheets Spreadsheet</h4> <pre id="log"></pre> </div> </body> </html>

I have just shared my experience about how I created a Microsoft To-Do list using Monkey Learn scripts, which are also able to be used in other projects outside of Microsoft To-Do or even apps not related to Microsoft To-Do at all!

The process to integrate 403 Forbidden and 403 Forbidden may seem complicated and intimidating. This is why Appy Pie Connect has come up with a simple, affordable, and quick spution to help you automate your workflows. Click on the button below to begin.