Book Image

Learning Python for Forensics - Second Edition

By : Preston Miller, Chapin Bryce
Book Image

Learning Python for Forensics - Second Edition

By: Preston Miller, Chapin Bryce

Overview of this book

Digital forensics plays an integral role in solving complex cybercrimes and helping organizations make sense of cybersecurity incidents. This second edition of Learning Python for Forensics illustrates how Python can be used to support these digital investigations and permits the examiner to automate the parsing of forensic artifacts to spend more time examining actionable data. The second edition of Learning Python for Forensics will illustrate how to develop Python scripts using an iterative design. Further, it demonstrates how to leverage the various built-in and community-sourced forensics scripts and libraries available for Python today. This book will help strengthen your analysis skills and efficiency as you creatively solve real-world problems through instruction-based tutorials. By the end of this book, you will build a collection of Python scripts capable of investigating an array of forensic artifacts and master the skills of extracting metadata and parsing complex data structures into actionable reports. Most importantly, you will have developed a foundation upon which to build as you continue to learn Python and enhance your efficacy as an investigator.
Table of Contents (15 chapters)

TQDM – a simpler progress bar

The tqdm module (version 4.23.2) can create a progress bar with any Python iterator:

In the preceding example, we wrapped an iterator that was created by range(100) around tqdm. That alone creates the progress bar that's displayed in the image. An alternative method, using the trange() function, makes our task even simpler. We'll use this module to create a progress bar for processing each WAL frame.

The following code creates the same progress bar, as shown in the previous screenshot. trange() is an alias for tqdm(xrange()) and makes creating a progress bar even simpler:

>>> from tqdm import trange 
>>> from time import sleep 
>>> for x in trange(100): 
...     sleep(1)