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  • Book Overview & Buying Learning Python for Forensics
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Learning Python for Forensics

Learning Python for Forensics

By : Preston Miller, Chapin Bryce
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Learning Python for Forensics

Learning Python for Forensics

5 (4)
By: Preston Miller, 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 (18 chapters)
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15
B. Python Technical Details
17
Index

Data type conversions

In some situations, the initial data type might not be the desired data type and needs to be changed while preserving its content. For example, when a user inputs arguments from the command line, the commands are commonly captured as strings and sometimes that user input needs to be, for example, an integer. We need to use the integer class constructor to convert that string object before processing the data. Imagine we have a simple script that returns the square of a user-supplied integer; we need to first convert the user-input to an integer prior to squaring the input. One of the most common ways to convert data types is to wrap the variable or string with the constructor method seen in the following example for each of the data types:

>>> int('123456') # The string 123456
123456 # Is now the integer 123456
>>> str(45) # The integer 45
'45' # Is now the string 45
>>> float('37.5') # The string 37.5
37.5 # Is now the float 37.5

Invalid conversions, for example, converting the letter 'a' to an integer will raise a ValueError. This error will state that the specified value cannot be converted to the desired type. In this case, we would want to use the built-in ord() method, which converts a character to its integer equivalent based on the ASCII value. In other scenarios, we might need to use other methods to convert data types. The following is a table of common built-in data type conversion methods that we can utilize for most scenarios.

Method

Description

str(), int(), float(), dict(), list(), set(), tuple()

Class constructor methods

hex(), oct()

Converts an integer to base 16 (hex) or base 8 (octal) representation

chr(), unichr()

Converts an integer to an ASCII or Unicode character

ord()

Converts a character to an integer

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Learning Python for Forensics
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