UUnonymous 0.0.1

A tool to substitue patterns/names in a file tree

UUnonymous

This description can be found on GitHub here

UUnonymous facilitates the replacement of keywords or regex-patterns within a file tree or zipped archive. It recursively traverses the tree, opens supported files and substitutes any found pattern or keyword with a replacement. Besides contents, UUnonymous will substitue keywords/patterns in file/folder-paths as well.

The result will be either a copied or replaced version of the original file-tree with all substitutions made.

As of now, UUnonymous supports text-based files, like .txt, .html, .json and .csv. UTF-8 encoding is assumed. Besides text files, UUnonymous is also able to handle (nested) zip archives. These archives will be unpacked in a temp folder, processed and zipped again.

Installation

$ pip install UUnonymous

Usage

Import the Anomymize class in your code and create an anonymization object like this:

from uunonymous import Anonymize

# refer to csv files in which keywords and substitutions are paired
anonymize_csv = Anonymize('/Users/casper/Desktop/keys.csv')

# using a dictionary instead of a csv file:
my_dict = {
    'A1234': 'aaaa',
    'B9876': 'bbbb',
}
anonymize_dict = Anonymize(my_dict)

# specifying a zip-format to zip unpacked archives after processing (.zip is default)
anonymize_zip = Anonymize('/Users/casper/Desktop/keys.csv', zip_format='gztar')

When using a csv-file, UUnonymous will assume your file contains two columns: the left column contains the keywords which need to be replaced, the right column contains their substitutions. Column headers are mandatory, but don't have to follow a specific format.

When using a dictionary only (absence of the pattern argument), the keys will be replaced by their values.

Performance might be enhanced when your keywords can be generalized into regular expressions. Anynomize_UU will search these patterns and replace them instead of matching the entire dictionary/csv-file against file contents or file/folder-paths. Example:

anonymize_regex = Anonymize(my_dict, pattern=r'[A-B]\d{4}')

By default is case sensitive by default. The regular expressions that take care of the replacements can be modified by using the flag parameter. It takes one or more variables which can be found here. Multiple variables are combined by a bitwise OR (the | operator). Example for a case-insensitive substitution:

anonymize_regex = Anonymize(my_dict, flags=re.IGNORECASE)

By using the use_word_boundaries argument (defaults to False), the algorithm ignores substring matches. If 'ted' is a key in your dictionary, without use_word_boundaries the algorithm will replace the 'ted' part in f.i. 'created_at'. You can overcome this problem by setting use_word_boundaries to True. It will put the \b-anchor around your regex pattern or dictionary keys. The beauty of the boundary anchors is that '@' is considered a boundary as well, and thus names in email addresses can be replaced. Example:

anonymize_regex = Anonymize(my_dict, use_word_boundaries=True)

Windows usage

There is an issue with creating zip archives. Make sure you run UUnonymous as administrator.

Inplace replacements vs. replacements in a copy

UUnonymous is able to create a copy of the processed file-tree or replace it. The substitute method takes a mandatory source-path argument (path to a file, folder or zip-archive, either a string or a Path object) and an optional target-path argument (again, a string or Path object). The target needs to refer to a folder. The target-folder will be created if it doesn't exist.

When the target argument is provided, UUnonymous will create a processed copy of the source into the target-folder. If the source is a single file, and the file path does not contain elements that will be replaced, and the target-folder is identical to the source folder, than the processed result will get a 'copy' extension to prevent overwriting.

When the target argument is omitted, the source will be overwritten by a processed version of it:

# process the datadownload.zip file, replace all patterns and write
# a copy to the 'bucket' folder.
anonymize_regex.substitute(
    '/Users/casper/Desktop/datadownload.zip', 
    '/Users/casper/Desktop/bucket'
)

# process the 'download' folder and replace the original by its processed 
# version
anonymize_regex.substitute('/Users/casper/Desktop/download')

# process a single file, and replace it
anonymize_regex.substitute('/Users/casper/Desktop/my_file.json')

Todo

Testing ;)