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Function fabricator
Create Python functions based on detailed specifications.
System
Your task is to create Python functions based on the provided natural language requests. Each request will describe the desired functionality of the function, including the input parameters and expected return value. Implement the functions according to the given specifications, ensuring that they handle edge cases, perform necessary validations, and follow best practices for Python programming. Please include appropriate comments in the code to explain the logic and assist other developers in understanding the implementation.
user
I want a function that can solve a Sudoku puzzle. The function should take a 9x9 Sudoku grid as input, where empty cells are represented by the value 0. The function should solve the puzzle using a backtracking algorithm and return the solved grid. If the puzzle is unsolvable, it should return None. The function should also validate the input grid to ensure it is a valid Sudoku puzzle.
Here is a function to solve a Sudoku puzzle using backtracking:
pythondef solve_sudoku(grid): """ Solve a Sudoku puzzle using backtracking recursions. Args: grid (list[list]): 9x9 Sudoku grid Returns: grid: Solved 9x9 Sudoku grid None: If the puzzle is unsolvable """ # Validate Sudoku grid size if len(grid) != 9: return for row in grid: if len(row) != 9: return # Helper functions for checking constraints def is_valid(num, pos): # Check row constraints for i in range(9): if grid[pos[0]][i] == num and pos[1] != i: return False # Check column constraints for i in range(9): if grid[i][pos[1]] == num and pos[0] != i: return False # Check box constraints box_x = pos[1] // 3 box_y = pos[0] // 3 for i in range(box_y*3, box_y*3 + 3): for j in range(box_x * 3, box_x*3 + 3): if grid[i][j] == num and (i,j) != pos: return False return True def find_empty(): # Find an unassigned cell for i in range(9): for j in range(9): if grid[i][j] == 0: return (i, j) return None # Backtracking function def solve(): find = find_empty() if not find: return True else: row, col = find for num in range(1,10): if is_valid(num, (row, col)): grid[row][col] = num if solve(): return True grid[row][col] = 0 return False if solve(): return grid else: return None
This implementation first validates the grid size, then uses helper functions to check row, column and box constraints to test if a number placement is valid. The backtracking recursion uses these constraints to recursively try different number placements until a solution is found. Empty cells are represented by 0.
The key aspects are:
- Validate input
- Use constraints to check valid placements
- Backtracking function to recursively place numbers
- Handle when no solution exists
Let me know if you have any other questions!
API request
pythonimport anthropic client = anthropic.Anthropic( # defaults to os.environ.get("ANTHROPIC_API_KEY") api_key="my_api_key", ) message = client.messages.create( model="claude-3-opus-20240229", max_tokens=2000, temperature=0, system="Your task is to create Python functions based on the provided natural language requests. Each request will describe the desired functionality of the function, including the input parameters and expected return value. Implement the functions according to the given specifications, ensuring that they handle edge cases, perform necessary validations, and follow best practices for Python programming. Please include appropriate comments in the code to explain the logic and assist other developers in understanding the implementation.", messages=[{"role":"user","content":"I want a function that can solve a Sudoku puzzle. The function should take a 9x9 Sudoku grid as input, where empty cells are represented by the value 0. The function should solve the puzzle using a backtracking algorithm and return the solved grid. If the puzzle is unsolvable, it should return None. The function should also validate the input grid to ensure it is a valid Sudoku puzzle."}] ) print(message.content)