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Original file line number Diff line number Diff line change
Expand Up @@ -205,6 +205,7 @@ def loop(workflow_manage_new_instance, node: INode, generate_loop):
node.context['loop_answer_data'] = loop_answer_data
node.context["index"] = current_index
node.context["item"] = current_index
node.context['run_time'] = time.time() - node.context.get("start_time")


def get_write_context(loop_type, array, number, loop_body):
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The provided code snippet appears to be part of a workflow management function that is handling nested loops and iterating through an array. Here are some points to consider:

  1. Variable Naming: The variable node seems to represent an instance of an interface (INode). It would be beneficial to add more meaningful names to variables like current_index, loop_answer_data, and array.

  2. Index Initialization: Ensure that current_index starts at 0 before entering the loop.

  3. Time Measurement: The calculation of run_time should only occur after all iterations have been completed, otherwise, it will always show the elapsed time since the start of the node execution rather than just the runtime for each iteration.

  4. Loop Iteration: If you expect multiple passes over the same data, ensure that number represents the number of times you want to iterate over the entire array. Otherwise, if you pass in number=1, it might lead to unexpected behavior depending on the context.

Here's a revised version of the function with these considerations:

def loop(workflow_manage_new_instance, node: INode, generate_loop):
    # Initialize necessary contexts
    current_index = 0
    loop_answer_data = []
    index_key = "index"
    item_key = "item"

    # Calculate start time once before entering the loop
    start_time = time.time()

    # Main loop
    while current_index < len(array):
        # Process data using current item
        currentItem = array[current_index]
        
        # Generate output for current iteration
        loop_output = generate_loop(currentItem)
        loop_answer_data.append(loop_output)

        # Update indices
        node.context[index_key] = current_index
        node.context[item_key] = currentItem

        # Increment current index
        current_index += 1

    # Calculate total run time after all iterations
    node.context['run_time'] = time.time() - start_time

def get_write_context(loop_type, array, number, loop_body):
    # Implement logic to write context based on loop type
    pass

Key Changes:

  • Added comments for clarity.
  • Initialized current_index to 0 before the loop.
  • Moved time measurement outside of the loop to calculate the total time taken for processing the array.
  • Ensured consistent naming conventions (e.g., renaming item to current_item) throughout the function.

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