When should Python code use secrets and compare_digest instead of random and normal equality?

Uses cryptographically secure token generation and timing-resistant comparison at credential boundaries.

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Python's secrets module is for security-sensitive values such as reset tokens, API keys, and nonces. The random module is designed for simulation and reproducible sampling, not adversarial guessing. I generate enough entropy with token_bytes, token_hex, or token_urlsafe, store only a hash when the raw token need not be recovered, and give the token an expiry and one-time-use rule.

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Uses cryptographically secure token generation and timing-resistant comparison at credential boundaries.

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Uses cryptographically secure token generation and timing-resistant comparison at credential boundaries.
Python's secrets module is for security-sensitive values such as reset tokens, API keys, and nonces. The random module is designed for simulation and reproducible sampling, not adversarial guessing. I generate enough entropy with token_bytes, token_hex, or token_urlsafe, store only a hash when the raw token need not be recovered, and give the token an expiry and one-time-use rule.
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Using random for reset tokens
Comparing signatures with ordinary equality
Logging a raw token to diagnose a failure

When should Python code use secrets and compare_digest instead of random and normal equality?

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