Angular Component Performance Profiler

This challenge requires you to build a reusable Angular component that can measure and display the execution time of specific functions within your application. This is crucial for identifying performance bottlenecks and optimizing your Angular application's responsiveness.

Problem Description

You need to create a high-level Angular component that acts as a time profiler. This profiler should allow developers to "wrap" specific functions, measuring how long each execution takes. The collected performance data should then be displayed in a user-friendly format within the profiler component.

Key Requirements:

• Wrappable Functions: The profiler should provide a mechanism to easily wrap any given function. This means the original function should still execute as intended, but its execution time will be recorded.
• Data Collection: The profiler must record the execution time for each wrapped function call.
• Data Aggregation: For each unique wrapped function, the profiler should aggregate the performance data, including:
  • Total number of calls.
  • Total execution time.
  • Average execution time.
  • Minimum execution time.
  • Maximum execution time.
• Display: The profiler component should present this aggregated data in a clear and organized manner. A table format is recommended.
• Reusability: The profiler should be a standalone component, easily integrated into different parts of an Angular application.
• Enabling/Disabling: Optionally, the profiler should be configurable to be enabled or disabled globally, allowing developers to turn profiling on/off without code changes.

Expected Behavior:

When a function is wrapped by the profiler, each time it is invoked, the profiler will:

1. Record the start time.
2. Execute the original function.
3. Record the end time.
4. Calculate the duration.
5. Update the aggregated statistics for that function.
6. Return the result of the original function.

The profiler component itself will display a list of all profiled functions and their aggregated statistics.

Edge Cases:

• Asynchronous Functions: The profiler should correctly handle asynchronous functions (e.g., those returning Promises or Observables).
• Functions with Arguments/Return Values: The profiler should not interfere with the arguments passed to wrapped functions or their return values.
• Rapid Invocations: The profiler should handle a high volume of function calls efficiently.
• No Functions Profiled: The profiler should gracefully handle the case where no functions are being profiled.

Examples

Example 1: Profiling a Synchronous Function

Consider a simple synchronous function:

function calculateSum(a: number, b: number): number {
  // Simulate some work
  for (let i = 0; i < 1000000; i++) {}
  return a + b;
}

If this function is wrapped by the profiler and called twice:

// Assuming profiler service has a method like `profileFunction(func, funcName)`
const profiledSum = profilerService.profileFunction(calculateSum, 'calculateSum');

profiledSum(5, 3); // First call
profiledSum(10, 2); // Second call

Expected Output (in the profiler component's display):

Explanation: The profiler records the start and end times for each call to calculateSum. It then aggregates these times to show the total, average, minimum, and maximum execution durations.

Example 2: Profiling an Asynchronous Function

Consider an asynchronous function simulating an API call:

function fetchData(id: string): Promise<any> {
  return new Promise(resolve => {
    setTimeout(() => {
      // Simulate API response
      resolve({ id, data: 'some data' });
    }, 150); // Takes 150ms
  });
}

If this function is wrapped by the profiler and called once:

const profiledFetchData = profilerService.profileFunction(fetchData, 'fetchData');

profiledFetchData('user-123').then(result => {
  console.log(result);
});

Expected Output (in the profiler component's display):

Explanation: The profiler correctly waits for the Promise returned by fetchData to resolve before calculating the duration, ensuring accurate measurement of asynchronous operations.

Constraints

• Angular Version: Compatible with Angular 12 or later.
• Language: Solution must be written in TypeScript.
• Profiling Overhead: The profiling mechanism itself should introduce minimal overhead to avoid significantly impacting the actual performance of the profiled functions.
• Data Storage: Aggregated profiling data should be stored in memory for the duration of the application's runtime. There's no requirement for persistent storage.

Notes

• Consider using a service to manage the profiling logic and data. This service can then be injected into the profiler component.
• The performance.now() API is a good candidate for high-precision time measurement.
• Think about how to handle potential errors within the profiled functions. The profiler should still record timing information even if an error occurs.
• For the display, consider using Angular Material or another UI library for table components, or build a custom table.
• The "enabling/disabling" feature could be implemented using an injectable configuration service or an @Input() property on the profiler component.