How do I validate dicts in Python for production systems?

Validating dictionaries in Python is essential for ensuring data integrity and maintaining robust applications in production systems. Proper validation can help avoid runtime errors and unexpected behavior by ensuring that the data structures conform to expected formats and types.

One effective way to validate dictionaries is by using libraries such as jsonschema, pydantic, or even custom validation functions. Below is an example of how to validate a dictionary using the jsonschema library.

import jsonschema from jsonschema import validate # Define the schema for the dictionary schema = { "type": "object", "properties": { "name": {"type": "string"}, "age": {"type": "integer", "minimum": 0}, "email": {"type": "string", "format": "email"} }, "required": ["name", "age", "email"] } # Example dictionary data = { "name": "John Doe", "age": 30, "email": "john.doe@example.com" } # Validate the dictionary against the schema try: validate(instance=data, schema=schema) print("Data is valid.") except jsonschema.exceptions.ValidationError as err: print("Data is invalid:", err)

Python dictionary validation jsonschema data integrity production systems

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