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Integrate MySQL with Monkey Learn

Appy Pie Connect allows you to automate multiple workflows between MySQL and Monkey Learn

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About MySQL

MySQL is currently the most popular database management system software used for managing the relational database.

About Monkey Learn

MonkeyLearn is a text analysis platform that helps you identify and extract actionable data from a variety of raw texts, including emails, chats, webpages, papers, tweets, and more! You can use custom tags to categorize texts, such as sentiments or topics, and extract specific data, such as organizations or keywords.

Monkey Learn Integrations

Best ways to Integrate MySQL + Monkey Learn

  • MySQL Integration Monkey Learn Integration

    MySQL + Monkey Learn

    Classify Text in monkeylearn when New Row is created in MySQL Read More...
    Close
    When this happens...
    MySQL Integration New Row
     
    Then do this...
    Monkey Learn Integration Classify Text
  • MySQL Integration Monkey Learn Integration

    MySQL + Monkey Learn

    Extract Text in monkeylearn when New Row is created in MySQL Read More...
    Close
    When this happens...
    MySQL Integration New Row
     
    Then do this...
    Monkey Learn Integration Extract Text
  • MySQL Integration Monkey Learn Integration

    MySQL + Monkey Learn

    Upload training Data in monkeylearn when New Row is created in MySQL Read More...
    Close
    When this happens...
    MySQL Integration New Row
     
    Then do this...
    Monkey Learn Integration Upload training Data
  • MySQL Integration Monkey Learn Integration

    MySQL + Monkey Learn

    Classify Text in monkeylearn when New Table is created in MySQL Read More...
    Close
    When this happens...
    MySQL Integration New Table
     
    Then do this...
    Monkey Learn Integration Classify Text
  • MySQL Integration Monkey Learn Integration

    MySQL + Monkey Learn

    Extract Text in monkeylearn when New Table is created in MySQL Read More...
    Close
    When this happens...
    MySQL Integration New Table
     
    Then do this...
    Monkey Learn Integration Extract Text
  • MySQL Integration {{item.actionAppName}} Integration

    MySQL + {{item.actionAppName}}

    {{item.message}} Read More...
    Close
    When this happens...
    {{item.triggerAppName}} Integration {{item.triggerTitle}}
     
    Then do this...
    {{item.actionAppName}} Integration {{item.actionTitle}}
Connect MySQL + Monkey Learn in easier way

It's easy to connect MySQL + Monkey Learn without coding knowledge. Start creating your own business flow.

    Triggers
  • New Row

    Triggered when you add a new row.

  • New Row (Custom Query)

    Triggered when new rows are returned from a custom query that you provide. Advanced Users Only

  • New Table

    Triggered when you add a new table.

    Actions
  • Create Row

    Adds a new row.

  • Delete Row

    Delete a row.

  • Update Row

    Updates an existing row.

  • 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.

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Page reviewed by: Abhinav Girdhar  | Last Updated on July 01, 2022 5:55 am

How MySQL & Monkey Learn Integrations Work

  1. Step 1: Choose MySQL as a trigger app and authenticate it on Appy Pie Connect.

    (30 seconds)

  2. Step 2: Select "Trigger" from the Triggers List.

    (10 seconds)

  3. Step 3: Pick Monkey Learn as an action app and authenticate.

    (30 seconds)

  4. Step 4: Select a resulting action from the Action List.

    (10 seconds)

  5. Step 5: Select the data you want to send from MySQL to Monkey Learn.

    (2 minutes)

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

Integration of MySQL and Monkey Learn

MySQL (often called “Mysql”. is a free and open source relational database management system (RDBMS. It is one of the most popular database management systems in the world. It is developed, marketed, and supported by Oracle Corporation. In this tutorial, we are going to learn how to integrate MySQL with Monkey Learn.

  • Integration of MySQL and Monkey Learn
  • In this section, we will discuss how to integrate MySQL and Monkey Learn. Firstly, we need to develop an API application from Monkey Learn side that can handle the requests made by the MySQL database. We need to build a REST API app in Django using Python 3.5 and then deploy it on Heroku. Below is the code for the same:

    # -- coding. utf-8 -- from django.http import HttpResponse import json from django.core import serializers from django.urls import path from .models import * #Create your views here class hello_world(serializers.ModelSerializer). class Meta. model = HelloWorld fields = ('text', 'result_type'. def get_success_message(self). return "Your text is %s" % self.data['result_type'] @view('hello_world'. def hello_world(request). "" Receive a POST request and send a response back "" data = {'text'. request.POST['text']} if request.method == 'POST'. serializer = HelloWorld(. serializer.is_valid(raise_exception=True. serializer.save(. return HttpResponse(serializer.data. else. return HttpResponse('Hello World!!'. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 # -- coding . utf - 8 -- from django . http import HttpResponse import json from django . core import serializers from django . urls import path from . models import * #Create your views here class hello_world ( serializers . ModelSerializer . . class Meta . model = HelloWorld fields = ( 'text' , 'result_type' . def get_success_message ( self . . return "Your text is %s" % self . data [ 'result_type' ] @ view ( 'hello_world' . def hello_world ( request . . " " Receive a POST request and send a response back " " data = { 'text' . request . POST [ 'text' ] } if request . method == 'POST' . serializer = HelloWorld ( . serializer . is_valid ( raise_exception = True . serializer . save ( . return HttpResponse ( serializer . data . else . return HttpResponse ( 'Hello World!!' )

    Here, we have an endpoint that handles the GET requests and responds with a JSON structure containing the text sent by the user and the result type of the classification that was performed on the text sent by the user. The result_type attribute is used to represent the classifier type in the JSON structure that will be returned by our API app. The user can select any of the classes available in our app and send his/her text to classify it. The above snippet shows how to create an endpoint for GET requests to handle GET requests sent by users to retrieve their results after performing a classification on texts they submit via our app. Below is the code for creating an endpoint for POST requests:

    @view('hello_world'. def hello_world(request). "" Receive a POST request and send a response back "" data = {'text'. request.POST['text']} if request.method == 'POST'. serializer = HelloWorld(. serializer.is_valid(raise_exception=True. serializer.save(. return HttpResponse(serializer.data. else. return HttpResponse('Hello World!!'. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 @ view ( 'hello_world' . def hello_world ( request . . " " Receive a POST request and send a response back " " data = { 'text' . request . POST [ 'text' ] } if request . method == 'POST' . serializer = HelloWorld ( . serializer . is_valid ( raise_exception = True . serializer . save ( . return HttpResponse ( serializer . data . else . return HttpResponse ( 'Hello World!!' )

    In the above snippet, we have an endpoint that handles POST requests sent by users to perform a classification on their text. We validate their input text using is_valid(), which returns True if the input text contains only alphabets or False otherwise. If the input text is valid, we use save(. to persist it to our database. Next, we will build an endpoint that allows users to retrieve their results using HTTP methods POST and GET:

    class HelloWorldView(generics.GenericAPIView). "" Returns hello world message "" queryset = HelloWorld.objects.all(. serializer_class = HelloWorldSerializer def get(self, request, *args, **kwargs). "" Get a list of all hello worlds "" return self.render(request, 'hello_world_listing.html', {'hello_worlds'. self.queryset}. @property def hello_worlds(self). "" Returns hello worlds in the form of a list "" return self.queryset 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 class HelloWorldView ( generics . GenericAPIView . . " " Returns hello world message " " queryset = HelloWorld . objects . all ( . serializer_class = HelloWorldSerializer def get ( self , request , * args , * * kwargs . . " " Get a list of all hello worlds " " return self . render ( request , 'hello_world_listing.html' , { 'hello_worlds' . self . queryset } . @ property def hello _ worlds ( self . . " " Returns hello worlds in the form of a list " " return self . queryset

    The snippet above shows how we can create our views for our API app by defining two endpoints — one for getting all the available results and another for getting the details of one result based on its unique identifier retrieved by the ID attribute of its object in our DBMS — represented by the unique identifier assigned to each of its objects in our DBMS table. Here, we have created an endpoint called get(. that returns an html page showing all the records saved in our DBMS table, along with details such as their unique identifier and result type — which is used as the label of their corresponding HTML table row in our API app’s HTML page — besides other details such as title and description of these records saved in our DBMS table along with their unique identifiers — which are used as labels for their corresponding thumbnail image in our API app’s HTML page:

    <html> <head> <title>Hello World</title> <link rel="stylesheet" rel="nofollow" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.7/css/bootstrap.min.css"> </head> <body> <div class="container"> <h1>Howdy</h1> <table class="table table-bordered"> <thead> <tr> <th>ID</th> <th>Text</th> <th>Result Type</th> <th>Thumbnail</th> </tr> </thead> <tbody> {% for hello_world in hello_worlds %} <tr> <td><a rel="nofollow" href="{{ hello_world.id }}">{{ hello_world.id }}</a></td> <td><a rel="nofollow" href="{{ hello_world.name }}">{{ hello_world.text }}</a></td> <td><a rel="nofollow" href="#img_{{ hello_world.id }}">{{ hello_world.thumbnail }}</a></td> </tr> {% endfor %} </tbody> </table> </div> </body> </html> 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

    The process to integrate MySQL and Cliniko 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.