updated samples

services/query.service.ts

@@ -10,6 +10,17 @@ export class queryService {
         this.dataPrepService = new DataPrepService()
     }
 
+    public callFromOtherClass(){
+        const t0 = performance.now()
+        let i
+        for (i = 0; i <= 6000000000; i++) {
+        }
+        const t1 = performance.now()
+        const timeTakenInSeconds = (t1 - t0) / 1000;
+        console.log(`Time taken: ${timeTakenInSeconds} seconds to run this function`);
+    
+    }
+
     public query(storageAddress: Storage, ...conditions: Conditions[]): Observable<any> {
         let dataFromStorage: Subject<any> = new Subject()
         let filteredResult: Subject<any> = new Subject()
@@ -18,8 +29,6 @@ export class queryService {
         return filteredResult.pipe()
     }
 
-    
-
     // Search and Filter: Pure Observables
     private filterFromObs(dataFromStorage: Subject<any>, filteredResult: Subject<any>, ...conditions: Conditions[]) {
         dataFromStorage.subscribe({

test/test3.ts

@@ -2,6 +2,7 @@
 
 import mongoose, { Model } from "mongoose";
 import { Subject, from, map, of, interval, buffer, asyncScheduler, observeOn, takeUntil, delay, queueScheduler, bufferWhen } from "rxjs";
+import { queryService } from "../services/query.service";
 const used = process.memoryUsage();
 
 let MongooseConnection: mongoose.Connection
@@ -88,13 +89,8 @@ function handlers(element: any) {
     }, randomInt * 1000)
 }
 function printLog() {
-    const t0 = performance.now()
-    let i
-    for (i = 0; i <= 6000000000; i++) {
-    }
-    const t1 = performance.now()
-    const timeTakenInSeconds = (t1 - t0) / 1000;
-    console.log(`Time taken: ${timeTakenInSeconds} seconds to run this printLog()`);
+    let service = new queryService()
+    service.callFromOtherClass()
 }
 
 /* Explanation: So the producer will emit 1 data very 1 second indefinitely. For the consumer, when they subscribes to the producer, the data will be consumed.
@@ -102,8 +98,8 @@ So when the producer emits data, the next method of the consumer is called, and
 
 1.The console.log() statement logs the received data to the console. This task is synchronous and is executed immediately.
 2.The handler1() function is called with the received data as an argument. This task is asynchronous and is added to the event queue.
-3.The then() method of the Promise returned by handler1() is called with a callback function as an argument. This task is also asynchronous and is added to the event queue.
-4.The printLog() function is called. This task is synchronous and is executed immediately.
+The then() method of the Promise returned by handler1() is called with a callback function as an argument. This task is also asynchronous and is added to the event queue.
+3.The printLog() function is called. This task is synchronous and is executed immediately.
 
 After all synchronous tasks in the call stack are completed, the asynchronous tasks in the event queue are executed one by one, starting with the handler1() function call
 and followed by the then() callback function call.*/
@@ -116,17 +112,56 @@ function understandingOBS() {
             handler1(element).then((data) => { // asynchronous
                 handler2(data) // setTimeout will put the call into the call stack
             })
-            printLog() // synchronous: this must complete before the next data to be received
+            printLog()
         }
     })
 }
 
 /* Buffer */
-let bufferring = publishDataEverySecond.pipe(buffer(control)) // standard buffer 
-let buffered = publishDataEverySecond.pipe( // using buffer when
-    bufferWhen(() => interval(1000 + Math.random() * 4000))
-);
 function bufferOBS() {
+    /* This code defines a function called bufferOBS that creates a new observable called bufferring using
+     the buffer operator. The buffer operator collects all the emissions from the source observable (publishDataEverySecond)
+      into an array and emits the array each time a notification is emitted from the control observable (control).
+
+    The buffer operator takes the control observable as a parameter. In this case, control is not defined in
+     the code snippet you provided, but it should be an observable that emits a notification to trigger the buffer emission.
+
+    After creating the bufferring observable, the code subscribes to it using the subscribe method. The subscribe 
+    method takes a callback function that is invoked each time an element is emitted from the bufferring observable.
+
+    Inside the callback function, we log the received data using console.log. We then call handler1 with the received
+     data and chain a then operator to handle the result. In the then block, we call handler2 with the transformed data. */
+    let bufferring = publishDataEverySecond.pipe(buffer(control)) // standard buffer 
+    bufferring.subscribe((element) => {
+        console.log(`Data received: ${element}`)
+        handler1(element).then((data) => {
+            handler2(data)
+        })
+    })
+}
+
+function bufferWhenOBS() {
+    let buffered = publishDataEverySecond.pipe(
+        /* This code creates a buffered observable that buffers emissions from publishDataEverySecond. 
+        The bufferWhen operator is used to determine when to buffer data. In this case, it uses the 
+        interval operator to emit a value every random time between 1000 and 5000 milliseconds. This 
+        means that every 1 to 5 seconds, the buffered observable will emit an array of the buffered values. */
+        bufferWhen(() => interval(1000 + Math.random() * 4000))
+    );
+
+    /* This code defines a function bufferOBS that subscribes to the buffered observable and processes the 
+    buffered data by calling handler1 and handler2 on each element. When new data arrives, the next callback 
+    is invoked with an array of the buffered values.
+    
+    Inside the next callback, we log the received data using console.log. We then call handler1 with the 
+    received data and chain a then operator to handle the result. In the then block, we call handler2 
+    with the transformed data.
+    
+    Overall, this code sets up a pipeline of RxJS operators to create a buffered observable that buffers
+     emissions from the source observable for a certain amount of time. It then processes the buffered 
+     data using the handler1 and handler2 functions. This is useful when you want to group emissions 
+     from a source observable and process them together, for example, to reduce network traffic or to
+    process data in batches. */
     buffered.subscribe({
         next(element) {
             console.log(`Data received: ${element}`)
@@ -138,15 +173,41 @@ function bufferOBS() {
 }
 
 /*  Scheduler */
-let scheduler = publishDataEverySecond.pipe(observeOn(asyncScheduler)) //async scheduler
-let source$ = interval(1000, queueScheduler); // queue scheduler
-let result$ = source$.pipe(takeUntil(control))
-function scheduleOBS() {
-    result$.subscribe({
-        next: element => {
-            console.log(`Scheduler: ${element}`)
-        }
-    })
+function asyncScheduleOBS() {
+    const scheduleObservable = of(`Hello Observable passing through`)
+    const delayTime = 3000;
+    /* In this example, the source$ observable emits the value "Hello, RxJS!". We pass the source$ observable\
+     as a parameter to the task function, which is executed after a delay of 1 second using the asyncScheduler.
+    Inside the task function, we subscribe to the source$ observable and log its emitted values to the console.
+    By using an observable as the task parameter, you can create complex logic that can be executed at a specific time or interval. */
+    let subscription = asyncScheduler.schedule(() => {
+        scheduleObservable.subscribe((element) => {
+            console.log(element)
+        })
+    }, delayTime);
+}
+
+function queue_Scheduler() {
+    /* In this example, we use the observeOn operator to apply the queueScheduler to the observable stream.
+     We then subscribe to the stream and execute three tasks (task1, task2, and task3) in order using the queueScheduler.
+
+    The queueScheduler ensures that the tasks are executed in the order they were added to the queue, waiting for each task to 
+    complete before executing the next one. This is useful for tasks that need to run in order and should not be interrupted by other tasks.
+
+    Note that the queueScheduler is a synchronous scheduler, which means that tasks scheduled using this scheduler will be executed 
+    synchronously. If you need to schedule tasks asynchronously, you can use the asyncScheduler or other schedulers that provide asynchronous execution.*/
+    let task1 = () => console.log('Task 1');
+    let task2 = () => console.log('Task 2');
+    let task3 = () => console.log('Task 3');
+
+    of(null)
+        .pipe(
+            observeOn(queueScheduler)
+        )
+        .subscribe(() => {
+            task1();
+            task2();
+            task3();
+        });
 }
 
-understandingOBS()