Decorator in JavaScript

This feature isn’t included in the newest ECMA-262, JavaScript in other words. You should always use Babel to use this in your project.

The examples I’ve attached to this post were written in JSFiddle, with the Babel + JSX configuration. If you want to use this feature in your project, you ought to set up Babel on your own.

Without a Decorator

class Medium {
  constructor(writer) {
    this.writer = writer;
  }

  getWriter() {
    return this.writer;
  }
}

There’s a class, Medium, that takes the name of the writer in its constructor. And there’s a function that returns the writer’s name.

Let’s create a property that is of Medium type.

const medium = new Medium('Jane');

const fakeMedium = {
  writer: 'Fake Jane',
  getWriter: medium.getWriter,
};

medium is created using Medium’s constructor function, unlike fakeMedium which is an object literal. But it has the same properties as medium.

Now, let’s compare the result of getWriter from each.

medium.getWriter(); // Jane
fakeMedium.getWriter(); // Fake Jane

Why are the values different?

It’s because JavaScript’s normal function this is bound to the object that actually invokes the function.

medium.getWriter() is called by the medium object, however, fakeMedium.getWriter() is called by fakeMedium. So, the this inside the function, getWriter, looks up the value from fakeMedium.

To get the same result as when medium.getWriter is called, let’s use Object.defineProperty. What Object.defineProperty does is define new properties on the object or modify the existing properties on the object and then it returns the object.

const fakeMedium = { ... };
let isDefining;
let fn = fakeMedium.getWriter;
Object.defineProperty(fakeMedium, 'getWriter', {
  get() {
    console.log('Access to getWriter');
    if (isDefining) {
      return fn;
    }
    isDefining = true;
    const boundFn = this.getWriter.bind(medium);
    isDefining = false;
    
    return boundFn;
  }
});

Whenever fakeMedium.getWriter is called, Access to getWriter will be printed twice. But why twice?

1. When you call fakeMedium.getWriter(), its getter-mode is detected and runs the customized get method.
2. Inside the get method, the getWriter is newly bound by medium — this.getWriter.bind(medium). Here, this refers to fakeMedium itself. So it’s the same as fakeMedium.getWriter.bind(medium). That’s why its get is called once again.
3. But before the function is bound, isDefining is set to true, so the codes under the if-condition won’t be executed until isDefining is set back to false again.

But this way is really a pain in the neck. Because every time you make a new instance of Medium, you should do this again.

Can’t we do this in a more elegant way?

With a Decorator

Any function can be a decorator. Basically, you can use a decorator for either a class or a method in a class. It takes three arguments — target, value, and descriptor.

function decorator(target, value, descriptor) {}

1. target refers to either the class or a prototype of the class.
2. value is undefined for a class and is the name of the method for a method.
3. descriptor is an object that contains definable properties on an object — such as configurable, writable, enumerable, and value. It’s undefined for a class.

function autobind(target, value, descriptor) {}
class Medium {
  ...
  @autobind
  getWriter() {
    return this.writer;
  }
}

A decorator is used with an at sign (@), with the name of the function that you’ll use as a decorator — and it takes three arguments as I just explained.

function autobind(target, value, descriptor) {
  const fn = descriptor.value;
  
  return {
    configurable: true,
    get() {
      return fn.bind(this);
    }
  }
}

descriptor.value is the name of the function on which you put the decorator function — in this case, it’s getWriter itself.

Note that the return value of autobind is a new object, then getWriter adopts the return value to its environment.

What’s good about using decorators is that they are reusable. All you need to do after defining the decorator function is merely to write @autobind on functions.

Here’s another example of making class member properties read-only, which is even easier.

function readonly(target, value, descriptor) {
  descriptor.writable = false;
  return descriptor;
}
class Medium {
  @readonly
  signUpDate = '2019-04-23';
}
const medium = new Medium();
medium.signUpDate; // 2019-04-23
medium.signUpDate = '1999-11-11'; 
medium.signUpDate; // 2019-04-23
^ The value isn't changed!

This time, the descriptor of the property has been changed by setting the writable property as false and that is all. Dead simple. Right?

Full Code Comparison

Here’s the comparison of the full code.

class Medium {
  constructor(writer) {
    this.writer = writer;
  }

  getWriter() {
    console.log(this.writer);
  }
}

const medium = new Medium('Jane');
const fakeMedium = {
  writer: 'Fake Jane',
  getWriter: medium.getWriter,
};

medium.getWriter(); // Jane
fakeMedium.getWriter(); // Fake Jane

/* Do auto-binding job for the same values */
let isDefining;
let fn = fakeMedium.getWriter;
Object.defineProperty(fakeMedium, 'getWriter', {
  get() {
    if (isDefining) {
      return fn;
    }
    isDefining = true;
    const boundFn = this.getWriter.bind(medium);
    isDefining = false;
    
    return boundFn;
  }
});

medium.getWriter(); // Jane
fakeMedium.getWriter(); // Jane

Without decorator

function autobind(target, value, descriptor) {
  const fn = descriptor.value;
  
  return {
    configurable: true,
    get() {
      return fn.bind(this);
    }
  }
}

class Medium {
  constructor(writer) {
    this.writer = writer;
  }
  
  @autobind
  getWriter() {
    console.log(this.writer);
  }
}

const medium = new Medium('Jane');
const fakeMedium = {
  writer: 'Fake Jane',
  getWriter: medium.getWriter,
};

medium.getWriter(); // Jane
fakeMedium.getWriter(); // Jane

With decorator

Try it out by yourself!

Conclusion

A decorator is very useful, powerful, amazing, and remarkable. Honestly, I don’t see any reason to say no to use this awesome feature.

You can check the proposal out on GitHub.

Thank you for reading!

#javascript #react #node-js #programming #webdev

What is GEEK

Buddha Community

What is JavaScript - Stackfindover - Blog

Who invented JavaScript, how it works, as we have given information about Programming language in our previous article ( What is PHP ), but today we will talk about what is JavaScript, why JavaScript is used The Answers to all such questions and much other information about JavaScript, you are going to get here today. Hope this information will work for you.

Who invented JavaScript?

JavaScript language was invented by Brendan Eich in 1995. JavaScript is inspired by Java Programming Language. The first name of JavaScript was Mocha which was named by Marc Andreessen, Marc Andreessen is the founder of Netscape and in the same year Mocha was renamed LiveScript, and later in December 1995, it was renamed JavaScript which is still in trend.

What is JavaScript?

JavaScript is a client-side scripting language used with HTML (Hypertext Markup Language). JavaScript is an Interpreted / Oriented language called JS in programming language JavaScript code can be run on any normal web browser. To run the code of JavaScript, we have to enable JavaScript of Web Browser. But some web browsers already have JavaScript enabled.

Today almost all websites are using it as web technology, mind is that there is maximum scope in JavaScript in the coming time, so if you want to become a programmer, then you can be very beneficial to learn JavaScript.

JavaScript Hello World Program

In JavaScript, ‘document.write‘ is used to represent a string on a browser.

<script type="text/javascript">
	document.write("Hello World!");
</script>

How to comment JavaScript code?

• For single line comment in JavaScript we have to use // (double slashes)
• For multiple line comments we have to use / * – – * /

<script type="text/javascript">

//single line comment

/* document.write("Hello"); */

</script>

Advantages and Disadvantages of JavaScript

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The essential JavaScript concepts that you should understand

As a JavaScript developer of any level, you need to understand its foundational concepts and some of the new ideas that help us developing code. In this article, we are going to review 16 basic concepts. So without further ado, let’s get to it.

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How to Use Zapier with MongoDB

I’m a huge fan of automation when the scenario allows for it. Maybe you need to keep track of guest information when they RSVP to your event, or maybe you need to monitor and react to feeds of data. These are two of many possible scenarios where you probably wouldn’t want to do things manually.

There are quite a few tools that are designed to automate your life. Some of the popular tools include IFTTT, Zapier, and Automate. The idea behind these services is that given a trigger, you can do a series of events.

In this tutorial, we’re going to see how to collect Twitter data with Zapier, store it in MongoDB using a Realm webhook function, and then run aggregations on it using the MongoDB query language (MQL).

The Requirements

There are a few requirements that must be met prior to starting this tutorial:

• A paid tier of Zapier with access to premium automations
• A properly configured MongoDB Atlas cluster
• A Twitter account

There is a Zapier free tier, but because we plan to use webhooks, which are premium in Zapier, a paid account is necessary. To consume data from Twitter in Zapier, a Twitter account is necessary, even if we plan to consume data that isn’t related to our account. This data will be stored in MongoDB, so a cluster with properly configured IP access and user permissions is required.

You can get started with MongoDB Atlas by launching a free M0 cluster, no credit card required.

While not necessary to create a database and collection prior to use, we’ll be using a zapier database and a tweets collection throughout the scope of this tutorial.

Understanding the Twitter Data Model Within Zapier

Since the plan is to store tweets from Twitter within MongoDB and then create queries to make sense of it, we should probably get an understanding of the data prior to trying to work with it.

We’ll be using the “Search Mention” functionality within Zapier for Twitter. Essentially, it allows us to provide a Twitter query and trigger an automation when the data is found. More on that soon.

As a result, we’ll end up with the following raw data:

{
    "created_at": "Tue Feb 02 20:31:58 +0000 2021",
    "id": "1356701917603238000",
    "id_str": "1356701917603237888",
    "full_text": "In case anyone is interested in learning about how to work with streaming data using Node.js, I wrote a tutorial about it on the @MongoDB Developer Hub. https://t.co/Dxt80lD8xj #javascript",
    "truncated": false,
    "display_text_range": [0, 188],
    "metadata": {
        "iso_language_code": "en",
        "result_type": "recent"
    },
    "source": "<a href='https://about.twitter.com/products/tweetdeck' rel='nofollow'>TweetDeck</a>",
    "in_reply_to_status_id": null,
    "in_reply_to_status_id_str": null,
    "in_reply_to_user_id": null,
    "in_reply_to_user_id_str": null,
    "in_reply_to_screen_name": null,
    "user": {
        "id": "227546834",
        "id_str": "227546834",
        "name": "Nic Raboy",
        "screen_name": "nraboy",
        "location": "Tracy, CA",
        "description": "Advocate of modern web and mobile development technologies. I write tutorials and speak at events to make app development easier to understand. I work @MongoDB.",
        "url": "https://t.co/mRqzaKrmvm",
        "entities": {
            "url": {
                "urls": [
                    {
                        "url": "https://t.co/mRqzaKrmvm",
                        "expanded_url": "https://www.thepolyglotdeveloper.com",
                        "display_url": "thepolyglotdeveloper.com",
                        "indices": [0, 23]
                    }
                ]
            },
            "description": {
                "urls": ""
            }
        },
        "protected": false,
        "followers_count": 4599,
        "friends_count": 551,
        "listed_count": 265,
        "created_at": "Fri Dec 17 03:33:03 +0000 2010",
        "favourites_count": 4550,
        "verified": false
    },
    "lang": "en",
    "url": "https://twitter.com/227546834/status/1356701917603237888",
    "text": "In case anyone is interested in learning about how to work with streaming data using Node.js, I wrote a tutorial about it on the @MongoDB Developer Hub. https://t.co/Dxt80lD8xj #javascript"
}

The data we have access to is probably more than we need. However, it really depends on what you’re interested in. For this example, we’ll be storing the following within MongoDB:

{
    "created_at": "Tue Feb 02 20:31:58 +0000 2021",
    "user": {
        "screen_name": "nraboy",
        "location": "Tracy, CA",
        "followers_count": 4599,
        "friends_count": 551
    },
    "text": "In case anyone is interested in learning about how to work with streaming data using Node.js, I wrote a tutorial about it on the @MongoDB Developer Hub. https://t.co/Dxt80lD8xj #javascript"
}

Without getting too far ahead of ourselves, our analysis will be based off the followers_count and the location of the user. We want to be able to make sense of where our users are and give priority to users that meet a certain followers threshold.

Developing a Webhook Function for Storing Tweet Information with MongoDB Realm and JavaScript

Before we start connecting Zapier and MongoDB, we need to develop the middleware that will be responsible for receiving tweet data from Zapier.

Remember, you’ll need to have a properly configured MongoDB Atlas cluster.

We need to create a Realm application. Within the MongoDB Atlas dashboard, click the Realm tab.

For simplicity, we’re going to want to create a new application. Click the Create a New App button and proceed to fill in the information about your application.

From the Realm Dashboard, click the 3rd Party Services tab.

We’re going to want to create an HTTP service. The name doesn’t matter, but it might make sense to name it Twitter based on what we’re planning to do.

Because we plan to work with tweet data, it makes sense to call our webhook function tweet, but the name doesn’t truly matter.

With the exception of the HTTP Method, the defaults are fine for this webhook. We want the method to be POST because we plan to create data with this particular webhook function. Make note of the Webhook URL because it will be used when we connect Zapier.

The next step is to open the Function Editor so we can add some logic behind this function. Add the following JavaScript code:

exports = function (payload, response) {

    const tweet = EJSON.parse(payload.body.text());

    const collection = context.services.get("mongodb-atlas").db("zapier").collection("tweets");

    return collection.insertOne(tweet);

};

In the above code, we are taking the request payload, getting a handle to the tweets collection within the zapier database, and then doing an insert operation to store the data in the payload.

There are a few things to note in the above code:

1. We are not validating the data being sent in the request payload. In a realistic scenario, you’d probably want some kind of validation logic in place to be sure about what you’re storing.
2. We are not authenticating the user sending the data. In this example, we’re trusting that only Zapier knows about our URL.
3. We aren’t doing any error handling.

When we call our function, a new document should be created within MongoDB.

By default, the function will not deploy when saving. After saving, make sure to review and deploy the changes through the notification at the top of the browser window.

Creating a “Zap” in Zapier to Connect Twitter to MongoDB

So, we know the data we’ll be working with and we have a MongoDB Realm webhook function that is ready for receiving data. Now, we need to bring everything together with Zapier.

For clarity, new Twitter matches will be our trigger in Zapier, and the webhook function will be our event.

Within Zapier, choose to create a new “Zap,” which is an automation. The trigger needs to be a Search Mention in Twitter, which means that when a new Tweet is detected using a search query, our events happen.

For this example, we’re going to use the following Twitter search query:

url:developer.mongodb.com -filter:retweets filter:safe lang:en -from:mongodb -from:realm

The above query says that we are looking for tweets that include a URL to developer.mongodb.com. The URL doesn’t need to match exactly as long as the domain matches. The query also says that we aren’t interested in retweets. We only want original tweets, they have to be in English, and they have to be detected as safe for work.

In addition to the mentioned search criteria, we are also excluding tweets that originate from one of the MongoDB accounts.

In theory, the above search query could be used to see what people are saying about the MongoDB Developer Hub.

With the trigger in place, we need to identify the next stage of the automation pipeline. The next stage is taking the data from the trigger and sending it to our Realm webhook function.

As the event, make sure to choose Webhooks by Zapier and specify a POST request. From here, you’ll be prompted to enter your Realm webhook URL and the method, which should be POST. Realm is expecting the payload to be JSON, so it is important to select JSON within Zapier.

We have the option to choose which data from the previous automation stage to pass to our webhook. Select the fields you’re interested in and save your automation.

The data I chose to send looks like this:

{
    "created_at": "Tue Feb 02 20:31:58 +0000 2021",
    "username": "nraboy",
    "location": "Tracy, CA",
    "follower_count": "4599",
    "following_count": "551",
    "message": "In case anyone is interested in learning about how to work with streaming data using Node.js, I wrote a tutorial about it on the @MongoDB Developer Hub. https://t.co/Dxt80lD8xj #javascript"
}

The fields do not match the original fields brought in by Twitter. It is because I chose to map them to what made sense for me.

When deploying the Zap, anytime a tweet is found that matches our query, it will be saved into our MongoDB cluster.

Analyzing the Twitter Data in MongoDB with an Aggregation Pipeline

With tweet data populating in MongoDB, it’s time to start querying it to make sense of it. In this fictional example, we want to know what people are saying about our Developer Hub and how popular these individuals are.

To do this, we’re going to want to make use of an aggregation pipeline within MongoDB.

Take the following, for example:

[
    {
        "$addFields": {
            "follower_count": {
                "$toInt": "$follower_count"
            },
            "following_count": {
                "$toInt": "$following_count"
            }
        }
    }, {
        "$match": {
            "follower_count": {
                "$gt": 1000
            }
        }
    }, {
        "$group": {
            "_id": {
                "location": "$location"
            },
            "location": {
                "$sum": 1
            }
        }
    }
]

There are three stages in the above aggregation pipeline.

We want to understand the follower data for the individual who made the tweet, but that data comes into MongoDB as a string rather than an integer. The first stage of the pipeline takes the follower_count and following_count fields and converts them from string to integer. In reality, we are using $addFields to create new fields, but because they have the same name as existing fields, the existing fields are replaced.

The next stage is where we want to identify people with more than 1,000 followers as a person of interest. While people with fewer followers might be saying great things, in this example, we don’t care.

After we’ve filtered out people by their follower count, we do a group based on their location. It might be valuable for us to know where in the world people are talking about MongoDB. We might want to know where our target audience exists.

The aggregation pipeline we chose to use can be executed with any of the MongoDB drivers, through the MongoDB Atlas dashboard, or through the CLI.

Conclusion

You just saw how to use Zapier with MongoDB to automate certain tasks and store the results as documents within the NoSQL database. In this example, we chose to store Twitter data that matched certain criteria, later to be analyzed with an aggregation pipeline. The automations and analysis options that you can do are quite limitless.

If you enjoyed this tutorial and want to get engaged with more content and like-minded developers, check out the MongoDB Community.

This content first appeared on MongoDB.

Original article source at: https://www.thepolyglotdeveloper.com/

#mongodb #zapier