scrubadub

library2.0.1pypypiunverified

Scrubadub is a Python library designed to clean personally identifiable information (PII) from unstructured text. It automatically detects and replaces various types of sensitive data like names, email addresses, phone numbers, and more, with configurable placeholders. The library is actively maintained, currently at version 2.0.1, and receives regular updates, including major releases that introduce new detectors and architectural changes.

auth-security

pip install scrubadub

github ↗package ↗

INSTALL

IMPORT

SIG · SCRUBADUB

scrubadub

auth-securitypythonv2.0.1

Install

58.0s avg

Import

7336ms

Disk

5530MB

Pass rate

4/ 10

Env Coverage4 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v2.0.1 · 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

glibc

py 3.10

✕ build_error

✓ 60.3s

py 3.11

✕ build_error

✓ 59.86s

py 3.12

✕ build_error

✓ 55.48s

py 3.13

✕ build_error

✓ 56.44s

py 3.9

✕ build_error

4/8 runs

5530MB installed

● package 5530MB

Code

Verified usage

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

clean

✓ import scrubadub cleaned_text = scrubadub.clean(text)

The primary convenience function for quick cleaning.

Scrubber

✓ from scrubadub import Scrubber scrubber = Scrubber() cleaned_text = scrubber.clean(text)

Use the Scrubber class for more fine-grained control, adding/removing specific detectors, or configuring post-processors.

Detector

✓ from scrubadub.detectors import EmailDetector scrubber = Scrubber() scrubber.add_detector(EmailDetector())

Import specific detector classes to add them to a Scrubber, especially for optional or external detectors.

This quickstart demonstrates the basic usage of `scrubadub.clean()` for straightforward PII redaction. It also illustrates how to use the `Scrubber` class to manually add detectors for more customized control over the scrubbing process, especially useful for optional or external detectors not loaded by default.

import scrubadub text = "My cat can be contacted on example@example.com, or 1800 555-5555. His name is John Doe." cleaned_text = scrubadub.clean(text) print(cleaned_text) # For more control, use the Scrubber class from scrubadub import Scrubber from scrubadub.detectors import TextBlobNameDetector # Example of an optional detector scrubber = Scrubber() # Add a detector if it's not enabled by default or for custom configuration scrubber.add_detector(TextBlobNameDetector()) controlled_cleaned_text = scrubber.clean(text) print(controlled_cleaned_text)

Debug

Known issues

breakingVersion 2.0.0 introduced significant changes, including the splitting of the library into smaller sub-packages and a shift from loading all detectors by default to loading only a default set. Code relying on previously auto-loaded detectors (e.g., spaCy, Stanford NER) will need explicit `add_detector()` calls or installation of optional packages (`scrubadub_spacy`, `scrubadub_stanford`, `scrubadub_address`).

fix

Review the changelog for v2.0.0. For previously implicitly available detectors, explicitly install the relevant sub-package (e.g., `pip install scrubadub-spacy`) and add the detector to your `Scrubber` instance using `scrubber.add_detector(DetectorClass())`.

affects: >=2.0.0

breakingPython 2.7 and 3.5 support was dropped starting from version 2.0.0. If you require these Python versions, you must use `scrubadub` version 1.2.2 or earlier.

fix

Upgrade to Python 3.6+ or pin `scrubadub` to `==1.2.2` for older Python versions.

affects: >=2.0.0

gotchaOnly a default set of detectors are loaded when initializing a `Scrubber` or using `scrubadub.clean()` since version 2.0.0. If you need functionality from optional or external detectors (e.g., `SpacyNameDetector`, `AddressDetector`), you must explicitly install their packages and add them to your `Scrubber` instance.

fix

Install the required optional packages (e.g., `pip install scrubadub-spacy`) and then use `scrubber.add_detector(DetectorClass())` to enable them.

affects: >=2.0.0

gotchaAttempting to add two detectors with the same name to a `Scrubber` instance will result in a `KeyError`.

fix

Ensure each detector you add has a unique name. If adding multiple instances of the same detector class with different configurations, assign a unique `name` parameter during instantiation (e.g., `EmailDetector(name='work_email_detector')`).

affects: All versions

gotchaVersion 2.0.1 fixed an issue where the `scikit-learn` dependency was incorrectly named. Users might have encountered installation problems with `scrubadub==2.0.0` due to this.

fix

Ensure you are using `scrubadub==2.0.1` or later to avoid this specific dependency naming issue.

affects: 2.0.0

Upgrade

Version history

2.0.1latest on PyPI · released Sep 1, 2023

Audit

Dependencies

cataloguerequiredRequired for core functionality.

dateparserrequiredRequired for core functionality.

fakerrequiredRequired for core functionality.

phonenumbersrequiredRequired for core functionality (phone number detection).

python-stdnumrequiredRequired for core functionality.

scikit-learnrequiredRequired for core functionality.

textblobrequiredRequired for core functionality (name detection).

typing-extensionsrequiredRequired for core functionality.

scrubadub-spacyoptionalEnables spaCy-based detectors for enhanced name and entity recognition.

scrubadub-stanfordoptionalEnables Stanford NER detectors for advanced entity recognition.

scrubadub-addressoptionalEnables address and postal code detection.

Agent activity

44 hits · last 30 days

node

OpenAI (training)

Resources

githubhttps://github.com/LeapBeyond/scrubadub ↗

packagehttps://pypi.org/project/scrubadub/ ↗