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Python *args: Accept Variable Positional Arguments

The *args parameter collects extra positional arguments into a tuple. It is useful when the number of operands varies, but each value should still have a clear meaning.

3 views Published Oct 17, 2026 Updated Oct 18, 2026 Admin

This guide explains *args: accept variable positional arguments through a focused Python example. You will learn the behavior to expect, why it matters in a real program, and how to recognize the common mistakes before applying it in your own project.

What You Will Learn


The *args parameter collects extra positional arguments into a tuple. It is useful when the number of operands varies, but each value should still have a clear meaning.

When and Why to Use It


The following example focuses on a practical use of *args: Accept Variable Positional Arguments.

Step-by-Step Example


def calculate_total(*prices):
    return sum(prices)

print(calculate_total(8, 12, 5))
print(calculate_total())

Understanding the Example


The first call sums three values to 25; the second has an empty args tuple and returns 0. The star is part of the definition, not the argument values.

Expected Output


25
0

Important Behavior and Edge Cases


Do not use *args to hide an unclear interface when a named list argument would explain intent better.

Try It Yourself


Write a function that finds the largest value from several positional arguments, handling an empty call.

Common Beginner Mistakes


  • Do not use *args to hide an unclear interface when a named list argument would explain intent better.
  • Confusing a returned value with printed output, or failing to verify a function’s behavior with different input values.
  • Skipping the practice step and assuming the example covers every input. Test at least one normal case and one edge case relevant to this topic.

Key Takeaways


  • The *args parameter collects extra positional arguments into a tuple.
  • The first call sums three values to 25; the second has an empty args tuple and returns 0.
  • Apply the technique deliberately, checking its documented input requirements and failure behavior before integrating it into a larger project.
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