250124 ‐ further optimize performance - cywongg/2025 GitHub Wiki

To make this code responsive, faster, and more robust, I would suggest the following improvements:

1. Optimize the Foreach Loop for Parallelism

The current implementation processes each corporateAction sequentially. If the operations for each item in corporateActions are independent, you could use parallelization to improve performance. For example, Task.WhenAll can process all corporate actions concurrently:

public async Task UpdateCorporateActionUploadStatusAsync<T>(ICollection<T> corporateActions, int feeType) 
    where T : ISelectedCorporateAction
{
    var tasks = corporateActions.Select(async corporateAction =>
    {
        // Get basket instrument IDs
        var basketInstrumentIds = MainWindow
            .GetInstrumentByUdlEliot(corporateAction.UdlEliotCode)
            .Select(instrument => instrument.BasketInstrumentID)
            .ToList();

        // Get updated fees
        var updatedFees = GetUpdatedFees(factorDataSetsByBasketInstrumentId, basketInstrumentIds, feeType);

        // Find the corporate action to update
        var corporateActionToUpdate = FindCorporateActionToUpdate(corporateAction);

        // Update status if the corporate action exists
        if (corporateActionToUpdate != null)
        {
            await UpdateCorporateActionStatusAsync(corporateAction, corporateActionToUpdate, updatedFees, basketInstrumentIds.Count);
        }
    });

    await Task.WhenAll(tasks);
}

By doing this, all corporate actions will be processed concurrently, making the function faster for large collections. However, ensure the operations are thread-safe, and be cautious about potential bottlenecks (e.g., database/network calls).

2. Avoid Repeated Calls to GetInstrumentByUdlEliot

If GetInstrumentByUdlEliot involves a network or database call, minimize repeated lookups by caching results. This can reduce latency significantly:

var instrumentCache = new Dictionary<string, List<int>>();
foreach (var corporateAction in corporateActions)
{
    if (!instrumentCache.TryGetValue(corporateAction.UdlEliotCode, out var basketInstrumentIds))
    {
        basketInstrumentIds = MainWindow
            .GetInstrumentByUdlEliot(corporateAction.UdlEliotCode)
            .Select(instrument => instrument.BasketInstrumentID)
            .ToList();

        instrumentCache[corporateAction.UdlEliotCode] = basketInstrumentIds;
    }

    // Proceed with the rest of the logic
}

This avoids redundant lookups, especially if multiple corporateActions share the same UdlEliotCode.

3. Optimize FindCorporateActionToUpdate

The current implementation searches _pdis and _cas sequentially. If these collections are large, lookups can be slow. To improve performance, consider creating indexed lookups (e.g., dictionaries) to provide O(1) lookups based on UdlEliotCode and ExerciseDate.

Example:

private void InitializeLookups()
{
    _pdisLookup = _pdis.ToDictionary(pdi => (pdi.UdlEliotCode, pdi.ExerciseDate));
    _casLookup = _cas.ToDictionary(ca => (ca.UdlEliotCode, ca.ExerciseDate));
}

private CompositeCorporateAction FindCorporateActionToUpdate(ISelectedCorporateAction corporateAction)
{
    // Try to find in _pdisLookup
    if (_pdisLookup.TryGetValue((corporateAction.UdlEliotCode, corporateAction.ExerciseDate), out var corporateActionToUpdate))
    {
        return corporateActionToUpdate;
    }

    // Try to find in _casLookup
    _casLookup.TryGetValue((corporateAction.UdlEliotCode, corporateAction.ExerciseDate), out corporateActionToUpdate);
    return corporateActionToUpdate;
}

This approach preprocesses collections into dictionaries for faster lookups, reducing the time complexity from O(n) to O(1) during the main operation.

4. Avoid Unnecessary Task.Run

In UpdateCorporateActionStatusAsync, the use of Task.Run may be unnecessary unless you're intentionally offloading heavy CPU-bound work to a background thread. If the operation is just an assignment, remove Task.Run to avoid the overhead:

private async Task UpdateCorporateActionStatusAsync(
    ISelectedCorporateAction corporateAction,
    CompositeCorporateAction corporateActionToUpdate,
    decimal updatedFees,
    int basketInstrumentCount)
{
    var status = $"{updatedFees} / {basketInstrumentCount}";

    if (corporateAction is SelectedCa)
    {
        corporateActionToUpdate.DivStatus = status;
    }
    else if (corporateAction is SelectedRfactor)
    {
        corporateActionToUpdate.EFactorStatus = status;
    }

    await Task.CompletedTask; // Keep async signature
}

This makes the code simpler and slightly faster.

5. Add Error Handling

Add robust error handling to ensure that failures in processing one corporateAction do not stop the entire batch:

public async Task UpdateCorporateActionUploadStatusAsync<T>(ICollection<T> corporateActions, int feeType) 
    where T : ISelectedCorporateAction
{
    var tasks = corporateActions.Select(async corporateAction =>
    {
        try
        {
            var basketInstrumentIds = MainWindow
                .GetInstrumentByUdlEliot(corporateAction.UdlEliotCode)
                .Select(instrument => instrument.BasketInstrumentID)
                .ToList();

            var updatedFees = GetUpdatedFees(factorDataSetsByBasketInstrumentId, basketInstrumentIds, feeType);

            var corporateActionToUpdate = FindCorporateActionToUpdate(corporateAction);

            if (corporateActionToUpdate != null)
            {
                await UpdateCorporateActionStatusAsync(corporateAction, corporateActionToUpdate, updatedFees, basketInstrumentIds.Count);
            }
        }
        catch (Exception ex)
        {
            // Log the exception and continue processing
            LogError($"Error processing corporate action {corporateAction.UdlEliotCode}", ex);
        }
    });

    await Task.WhenAll(tasks);
}

This ensures the method is more robust and does not fail catastrophically if there are exceptional cases.

6. Use Asynchronous Methods Where Possible

Ensure methods like GetInstrumentByUdlEliot and GetUpdatedFees are asynchronous if they involve I/O operations like database or API calls. This will improve responsiveness by not blocking threads.

7. Minimize Object Creation

Avoid creating new lists unnecessarily. For example, in basketInstrumentIds:

var basketInstrumentIds = MainWindow
    .GetInstrumentByUdlEliot(corporateAction.UdlEliotCode)
    .Select(instrument => instrument.BasketInstrumentID);

Unless ToList() is required downstream, you can work with an IEnumerable to minimize memory usage.

8. Profile and Monitor Performance

Finally, use tools like a profiler or logging to monitor bottlenecks. Identify whether database calls, CPU-bound operations, or I/O are the primary constraint.

Final Code with Improvements

Here’s how the updated code looks after incorporating the suggestions:

public async Task UpdateCorporateActionUploadStatusAsync<T>(ICollection<T> corporateActions, int feeType) 
    where T : ISelectedCorporateAction
{
    var instrumentCache = new Dictionary<string, List<int>>();
    
    var tasks = corporateActions.Select(async corporateAction =>
    {
        try
        {
            if (!instrumentCache.TryGetValue(corporateAction.UdlEliotCode, out var basketInstrumentIds))
            {
                basketInstrumentIds = MainWindow
                    .GetInstrumentByUdlEliot(corporateAction.UdlEliotCode)
                    .Select(instrument => instrument.BasketInstrumentID)
                    .ToList();

                instrumentCache[corporateAction.UdlEliotCode] = basketInstrumentIds;
            }

            var updatedFees = GetUpdatedFees(factorDataSetsByBasketInstrumentId, basketInstrumentIds, feeType);

            var corporateActionToUpdate = FindCorporateActionToUpdate(corporateAction);

            if (corporateActionToUpdate != null)
            {
                await UpdateCorporateActionStatusAsync(corporateAction, corporateActionToUpdate, updatedFees, basketInstrumentIds.Count);
            }
        }
        catch (Exception ex)
        {
            LogError($"Error processing corporate action {corporateAction.UdlEliotCode}", ex);
        }
    });

    await Task.WhenAll(tasks);
}

These optimizations should make the code faster, more robust, and responsive, especially for larger datasets.

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