Book Image

Learning Python for Forensics

By : Chapin Bryce
Book Image

Learning Python for Forensics

By: Chapin Bryce

Overview of this book

This book will illustrate how and why you should learn Python to strengthen your analysis skills and efficiency as you creatively solve real-world problems through instruction-based tutorials. The tutorials use an interactive design, giving you experience of the development process so you gain a better understanding of what it means to be a forensic developer. Each chapter walks you through a forensic artifact and one or more methods to analyze the evidence. It also provides reasons why one method may be advantageous over another. We cover common digital forensics and incident response scenarios, with scripts that can be used to tackle case work in the field. Using built-in and community-sourced libraries, you will improve your problem solving skills with the addition of the Python scripting language. In addition, we provide resources for further exploration of each script so you can understand what further purposes Python can serve. With this knowledge, you can rapidly develop and deploy solutions to identify critical information and fine-tune your skill set as an examiner.
Table of Contents (24 chapters)
Learning Python for Forensics
Credits
About the Authors
Acknowledgments
About the Reviewer
www.PacktPub.com
Preface
Index

Moving on to our writers


Within the writers directory, we have two scripts: csv_writer.py and kml_writer.py. Both of these writers are called depending on the types of data being processed in the metadata_parser.py framework.

Writing spreadsheets – csv_writer.py

In this chapter, we will use the csv.DictWriter instead of csv.Writer just as in Chapter 5, Databases in Python, and Chapter 6, Extracting Artifacts from Binary Files. As a reminder, the difference is that the DictWriter writes dictionary objects to a CSV file and the csv.Writer function is more suited for writing lists.

The great thing about the csv.DictWriter is that it requires an argument, fieldnames, when creating the writer object. The fieldnames argument should be a list that represents the desired order of columns in the output. In addition, all possible keys must be included in the fieldnames list. If a key exists that is not contained in the list, an exception will be raised. On the other hand, if a key is not present in the...