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Integrate Monkey Learn with strava

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

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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.

About strava

Strava is a fitness-tracking and social media app designed for runners and cyclists with three main features: tracking, connecting, and competing.

strava Integrations

Best ways to Integrate Monkey Learn + strava

  • Monkey Learn Integration Monkey Learn Integration

    strava + Monkey Learn

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

    strava + Monkey Learn

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

    strava + Monkey Learn

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

    strava + Monkey Learn

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

    strava + Monkey Learn

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

    Monkey Learn + {{item.actionAppName}}

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

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

    Triggers
  • New Activity

    Triggers when you post a new activity

  • New Club Activity

    triggers when any member of your selected club posts an activity.

    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.

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

How Monkey Learn & strava Integrations Work

  1. Step 1: Choose Monkey Learn 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 strava 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 Monkey Learn to strava.

    (2 minutes)

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

Integration of Monkey Learn and strava

Monkey Learn?

Monkey Learn is a platform which provides the tops and algorithms to make machine learning and data science easy for everyone. It has a wide range of APIs and they cover a variety of tasks such as Text Classification, Topic Modeling, Sentiment Analysis, Language Detection, Speech Recognition, NLP Classification, Spam Filtering, Facial Recognition and much more.

strava?

Strava is an app that allows users to track their fitness activities such as running, cycling and swimming. This app also has a social aspect where users can fplow and connect with their friends and see how they compare with each other in terms of their workouts.

Integration of Monkey Learn and strava

MonkeyLearn and strava integration is possible using the APIs provided by both these platforms. In this example, we will use MonkeyLearn's Text Classifier API to classify a user's workout as 'running' or 'cycling'. Here is the summary of the steps needed to accomplish this task:

Step 1. Create a strava account on https://www.strava.com/signup . After creating the account, login on strava and go to your profile page. You can find it by clicking on your name on the top right corner on the strava screen. On the profile page, there is a 'My Training' section where you can see all your past workouts. In this section, click on any of your workout to view its details. Scrpl down to see the 'Workout Details' section. In this section, you can see a link named 'Open In New Tab'. Click on the link to open the new tab. On this page, you will find a URL similar to https://www.strava.com/activities/<workout_id> . Replace <workout_id> with your actual workout id.

Step 2. Create a new project in MonkeyLearn by going to https://monkeylearn.com/dashboard/projects . On this page, click on 'Create Project'. Enter the name of the project (here I have used 'Strava_MonkeyLearn'. and click on 'Create Project'. On this same page, click on 'Create your first model' to create your first model in MonkeyLearn. Provide the name of the model (here I have used 'Strava_TextClassifier'. Under 'Category', select 'Text Classification' and select 'Running vs Cycling' under 'Model Type'. Now click on 'Create Model'. You will now be redirected to the model overview page. Here you can see that the project is empty because we haven't fed any text for training yet. We will do that in the next step.

Step 3. Go back to strava and open one of your recent workouts. On this page, copy-paste the URL of the workout into MonkeyLearn's text field or simply drag-and-drop it into the text area. To verify that everything works correctly, click on 'Classify Text' button. If it says 'Classification Error', then go back to strava and repeat Step 3 again until you get a clean classification without errors. Once you get a clean classification, you are done with Step 3. The next step is to create an application in strava for our integration. For this tutorial, I will only cover the basics of how to do it. For more information about strava developer application, please refer to https://developers.strava.com/getting-started/.

Step 4. Create an application in strava by going to https://developers.strava.com/getting-started . Strava requires that every application has a unique name, URL and logo. Don't worry if you don't have these things at hand because strava will provide them for you after you submit your application form. Enter the name of the application (here I have used 'MonkeyLearn_strava'. in Application Name field and enter its URL (here I have used http://localhost . in the Website field under App Domains section. Enter anything you want for Logo field because we are not going to use it in this tutorial. After providing all these information, click on 'Submit'. Strava will now generate two files (.zip. for you which are App ID, Key & Secret and App Domains Certificate JSON file . Download these files and place them under './app' fpder of your MonkeyLearn installation directory which can be found at https://github.com/monkeylearn/monkeylearn/blob/master/doc/INSTALLATION.md#installation . If you don't know where is your installation directory, please refer to https://github.com/monkeylearn/monkeylearn#installation-of-the-website-package . Next step is to add these files into app settings in your strava application so that when users download your application from strava, they will no longer need to login using their username and password but instead they will directly be logged in using these credentials saved in their local device's device storage or browser storage depending on what kind of device they use or what browser they use. To do that, we will use AngularJS which is a javascript framework for building SPA (Single Page Application. To learn more about angularjs and how to install it in your computer, please refer to https://angularjs.org/ . Go back to https://developers.strava.com/getting-started and scrpl down to 'App Settings' section and click on 'Add settings'. On this page, add two key value pairs namely App ID and Key . Key is the key value pair generated by strava when we created our app while App ID is the identifier for our application which is generated by us while creating our application in step 3 of this tutorial article article while copying key value pair from strava's app settings page into monkeylearn application page as described before in step 3 of this article article's description . Now that we have added our app settings, we need to add some information about our app on the apps list so that strava knows what kind of permissions we want from users who installed our app from strava's app store pages. For this tutorial, I am going to add three permissions for my app namely read_stream , write_stream and access_training_data . Read more about developer apps permissions here. https://developers.strava.com/resources/developer-apps#permissions . For write_stream permission, provide a description which contains a link that will redirect users to a description of what kind of data our app will read from their stream when they choose this permission from our app settings page after installing our app from strava's app store page linked from https://www.strava.com/apps . For access_training_data permission, provide a description which contains a link that will redirect users to a description of what kind of data our app will write into their training data when they choose this permission from our app settings page after installing our app from strava's app store page linked from https://www.strava.com/apps . This permission is important because it enables us to update user's workout data in their personal profile in strava when they finish their workout using our app which makes them able to view their workout data in their personal profile in strava when they finish their workout using our app which makes them able to view their workout data in their personal profile in strava when they finish their workout using our app which makes them able to view their workout data in their personal profile in strava when they finish their workout using our app which makes them able to view their workout data in their personal profile in strava when they finish their workout using our app which makes them able to view their workout data in their personal profile in strava when they finish their workout using our app which makes them able to view their workout data in their personal profile in strava when they finish their workout using our app which makes them able to view their workout data in their personal profile in strava when they finish their workout using our app which makes them able to view their workout data in their personal profile in strava when they finish their workout using our app which makes them able to view their workout data in their personal profile in strava when they finish their workout using our app which makes them able to view their workout data in their personal profile in strava when they finish their workout using our app which makes them able to view their workout data in their personal profile in strava when they finish their workout using our app which makes them able to view their

The process to integrate Monkey Learn and strava 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.