Skip to main content

A utility to determine the author of a document using linguistic analysis

Project description

A package that uses linguistic analysis in order to determine the author of a document. Currently version 0.0.1.


  1. Install the package from the PyPi homepage (run install)
  2. Import the package in your project (from authorid import authorid)
  3. You’re good to go! You can now run individual functions (i.e. by calling the package name.


authorid is a package meant to help analyze linguistic features of files and determine their potential author, provided a list of attributes. In order to invoke the primary utility, simply run and you will be prompted for a file containing the mystery text. After analysis is complete, the program will print a signature for that file, and prompt for a directory where .stats files are stored.

If this is the first time you are running authorid, exit out of the main program now, and copy the signature list to another file, ending with the signature .stats. A sample .stats file may look like the following:

first last

Remember to order the information correctly in order to ensure optimal results. Complete this step for various files, and when you have a directory containing your made .stats files (this process will be automated in 0.0.2), run once more, this time with a mystery file and providing the directory with your STATS files. The program will compare signatures with those in the list and provide a “best match” author.

Other utility functions are also available, which are listed below (also open sourced on GitHub):

def clean_up(s)
def average_word_length(text)
def type_token_ratio(text)
def hapax_legomana_ratio(text)
def split_on_separators(original, separators)
def average_sentence_length(text)
def avg_sentence_complexity(text)
def get_valid_filename(prompt)
def read_directory_name(prompt)
def compare_signatures(sig1, sig2, weight)
def read_signature(filename)
def run()

Note that text is a list of strings.

Project details

Release history Release notifications

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, size & hash SHA256 hash help File type Python version Upload date (8.4 kB) Copy SHA256 hash SHA256 Source None

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page