How do I validate dicts in Python using NumPy?

Validating dictionaries in Python can be performed using the NumPy library, particularly when working with numerical data. The validation process typically involves checking for required keys, data types, and any other specific criteria that should be adhered to in the dictionary objects.

NumPy offers tools that can facilitate the validation of numerical entries efficiently. Below is an example that demonstrates how to validate dictionaries using NumPy's capabilities.

import numpy as np def validate_dict(data, required_keys, expected_types): for key in required_keys: if key not in data: return False, f"Missing key: {key}" if not isinstance(data[key], expected_types[key]): return False, f"Incorrect type for key: {key}. Expected {expected_types[key].__name__}, got {type(data[key]).__name__}" return True, "Validation successful" # Example usage my_dict = { 'name': 'John Doe', 'age': 30, 'height': 175.5 } required_keys = ['name', 'age', 'height'] expected_types = { 'name': str, 'age': int, 'height': float } is_valid, message = validate_dict(my_dict, required_keys, expected_types) print(message) # Output: Validation successful or appropriate error message

Python NumPy Validate Dict Dictionary Validation Data Validation

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