Registry / auth-security / password-strength

password-strength

library0.0.3.post2pypypi✓ verified 86d ago

The `password-strength` library (PyPI slug: `password-strength`, current version `0.0.3.post2`) provides tools for password strength assessment and validation. It allows defining a `PasswordPolicy` with various rules (e.g., minimum length, character types, entropy) to test if a password meets specified security requirements. The library also offers `PasswordStats` to get a normalized strength score and detailed analysis of a password. While the PyPI package itself was last updated in 2019, its GitHub repository shows more recent activity, suggesting ongoing relevance.

auth-security

pip install password-strength

github ↗package ↗

INSTALL

IMPORT

SIG · PASSWORD-STRENGTH

password-strength

auth-securitypythonv0.0.3.post2

Install

1.6s avg

Import

13ms

Disk

16MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.0.3.post2 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.920 runs

installs and imports cleanly · install 0.0s · import 0.014s · 17.9MB

glibc

py 3.10–3.920 runs

installs and imports cleanly · install 1.6s · import 0.013s · 18MB

16MB installed

● package 16MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

PasswordPolicy

✓ from password_strength import PasswordPolicy

PasswordStats

✓ from password_strength import PasswordStats

This quickstart demonstrates how to define a password policy using `PasswordPolicy.from_names` and test a password against it. It also shows how to get detailed strength statistics, including entropy, complexity, and a normalized strength score using `PasswordStats`.

from password_strength import PasswordPolicy, PasswordStats # Define a password policy policy = PasswordPolicy.from_names( length=8, uppercase=1, numbers=1, special=1, nonletters=1 ) # Test a password against the policy password = "StrongP@ssw0rd!" errors = policy.test(password) if not errors: print(f"Password '{password}' meets the policy requirements.") else: print(f"Password '{password}' failed the following checks: {', '.join(errors)}") # Get detailed strength statistics stats = PasswordStats(password) print(f"\nPassword entropy (bits): {stats.entropy_bits:.2f}") print(f"Password complexity (0.00-0.99): {stats.complexity:.2f}") print(f"Password strength (0.00-1.00): {stats.strength:.2f}")

Debug

Known issues

gotchaThe default entropy calculation might be less intuitive for users than a complexity score or explicit policy checks. While `entropy_bits` is a fundamental measure, `complexity` (0.00-0.99) or `strength` (0.00-1.00) are often more digestible for direct user feedback.

fix

Prefer using `policy.test()` to get a list of failed rules or `PasswordStats().complexity` / `PasswordStats().strength` for a more user-friendly score, especially when providing feedback to end-users.

affects: <=0.0.3.post2

gotchaA password might pass basic length and character type rules but still contain easily guessable repetitions (e.g., 'aaaaaa', '123123'). The library's `Policy` object doesn't inherently check for overly repetitive patterns beyond what the entropy calculation might implicitly catch.

fix

For enhanced security, consider adding custom checks for known weak patterns, dictionary words, or sequential characters, potentially by extending the `PasswordPolicy` or implementing separate validation functions. The library offers the flexibility to define custom validation rules or combine with other techniques.

affects: <=0.0.3.post2

deprecatedDirect manipulation or reliance on `weak_bits`, `medium_bits`, `strong_bits` constants might be less recommended than using the `Policy` object's named rules, as policies provide a clearer, more configurable approach to defining acceptable passwords.

fix

Define password requirements using `PasswordPolicy.from_names()` or by directly instantiating `PasswordPolicy` with desired rules, which is generally more readable and maintainable.

affects: <=0.0.3.post2

Errors

Common errors & fixes

ModuleNotFoundError: No module named 'password_strength'

The library is not installed or the Python environment is incorrect.

fix

Ensure the library is installed in your current environment using `pip install password-strength`. If using virtual environments, activate the correct one before running your script.

TypeError: 'PasswordPolicy' object is not callable

Attempting to call a `PasswordPolicy` object like a function instead of using its `test()` method.

fix

Access validation methods on the `PasswordPolicy` object. For example, use `policy.test(password)` instead of `policy(password)`.

AttributeError: 'PasswordStats' object has no attribute 'test'

Confusing `PasswordStats` (for analysis) with `PasswordPolicy` (for validation). `PasswordStats` provides statistical properties, not policy testing.

fix

Use `PasswordPolicy` for testing against defined rules (`policy.test(password)`). Use `PasswordStats` to get raw metrics like entropy or complexity (`PasswordStats(password).strength`).

Upgrade

Version history

0.0.3.post2latest on PyPI · released Jan 4, 2019

Audit

Dependencies

No dependency data recorded yet.

Agent activity

11 hits · last 30 days

node

OpenAI (training)

Resources

githubhttps://github.com/kolypto/py-password-strength ↗

packagehttps://pypi.org/project/password-strength/ ↗