Update main.py #4
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WalkthroughThe code replaces two previous Fibonacci number implementations—a naive recursive and an iterative dynamic programming approach—with a single memoized recursive solution. The new implementation introduces a helper function for recursion with memoization and updates the public interface to initialize and use this memoization strategy. Changes
Estimated code review effort1 (~2 minutes) Poem
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Summary of Changes
Hello @atharvsabdeai, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!
This pull request streamlines the main.py file by consolidating the Fibonacci sequence calculation logic. It removes duplicate and less efficient implementations, retaining only the optimized memoized recursive approach. This change aims to improve code maintainability and ensure a single, performant method for computing Fibonacci numbers.
Highlights
- Code Simplification: Removed two redundant implementations of the Fibonacci sequence calculation (a naive recursive version and an iterative dynamic programming version) from
main.py. - Algorithm Consolidation: Standardized the Fibonacci calculation in
main.pyto exclusively use a memoized recursive approach, improving efficiency for repeated calls with the same input and overall code clarity.
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Actionable comments posted: 1
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📒 Files selected for processing (1)
main.py(1 hunks)
🔇 Additional comments (2)
main.py (2)
2-15: LGTM! Well-implemented memoized recursive approach.The memoization logic is correct and follows standard patterns. The base case handling and recursive formula are properly implemented.
26-30: LGTM! Main execution block is correct.The expected output comment is accurate - the 5th Fibonacci number is indeed 5. The main block structure and function call are appropriate.
| def nth_fibonacci(n): | ||
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| # Create a memoization table and initialize with -1 | ||
| memo = [-1] * (n + 1) | ||
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| # Call the utility function | ||
| return nth_fibonacci_util(n, memo) |
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🛠️ Refactor suggestion
Add input validation for edge cases.
The wrapper function logic is correct, but consider adding validation for negative inputs to prevent potential issues with array creation.
def nth_fibonacci(n):
+ if n < 0:
+ raise ValueError("Fibonacci number is not defined for negative integers")
# Create a memoization table and initialize with -1
memo = [-1] * (n + 1)📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| def nth_fibonacci(n): | |
| # Create a memoization table and initialize with -1 | |
| memo = [-1] * (n + 1) | |
| # Call the utility function | |
| return nth_fibonacci_util(n, memo) | |
| def nth_fibonacci(n): | |
| if n < 0: | |
| raise ValueError("Fibonacci number is not defined for negative integers") | |
| # Create a memoization table and initialize with -1 | |
| memo = [-1] * (n + 1) | |
| # Call the utility function | |
| return nth_fibonacci_util(n, memo) |
🤖 Prompt for AI Agents
In main.py around lines 19 to 24, the nth_fibonacci function lacks input
validation for negative values, which can cause errors when creating the memo
array. Add a check at the start of the function to raise a ValueError or return
an appropriate response if n is negative, preventing invalid array creation and
ensuring robust input handling.
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Code Review
This pull request refactors the Fibonacci number calculation by removing two implementations (a naive recursive one and an iterative one) and keeping a memoized recursive solution.
My review focuses on two main points:
- Robustness: The removed iterative solution is more robust than the remaining recursive one, as it is not susceptible to Python's recursion depth limit. I've recommended reinstating an improved version of the iterative approach.
- Maintainability: A small suggestion is made to remove a comment that specifies the output, as it can become outdated and misleading. This follows PEP 8 guidelines.
The changes are a good step towards simplifying the code, but choosing the iterative approach would lead to a more robust and efficient final implementation.
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| # Recursive case: calculate Fibonacci number | ||
| # and store it in memo | ||
| memo[n] = nth_fibonacci_util(n - 1, memo) + nth_fibonacci_util(n - 2, memo) | ||
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Performance Improvement: Good implementation of memoization for the Fibonacci function, which improves the time complexity from O(2^n) to O(n). This addresses the exponential growth problem in the original implementation and prevents potential stack overflow for large inputs.
| # Recursive case: calculate Fibonacci number | ||
| # and store it in memo | ||
| memo[n] = nth_fibonacci_util(n - 1, memo) + nth_fibonacci_util(n - 2, memo) | ||
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Missing Documentation: Consider adding docstrings to both nth_fibonacci_util and nth_fibonacci functions to explain their purpose, parameters, expected return values, and the memoization approach being used.
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| # Wrapper function that handles both initialization | ||
| # and Fibonacci calculation | ||
| def nth_fibonacci(n): |
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Input Validation: Consider adding input validation to handle negative values of n or non-integer inputs, which aren't currently addressed and could cause unexpected behavior.
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| if __name__ == "__main__": | ||
| n = 5 |
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Misleading Comment: The comment # Output: 5 is misleading as it suggests the output will always be 5, regardless of input. Either remove the comment or make it clearer that this is the expected output specifically for n=5.
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