Make sure you have the following pre-requisites needed to proceed further:

• A working computer or laptop
  
• Ubuntu OS (preferably 16.04)
• Python 3.x
• A working internet connection

If you come from a background of a language such as Java, C, or C++, you might be familiar with the concept of grouping logically connected statements using curly braces. This is not the case, however, in Python. Instead, the logically connected statements, including classes, functions, conditional statements, and loops, are grouped using indentation. Indentation keeps the code clean and easy to read. We shall explore this in more detail in the coming sections. For now, however, let's say goodbye to braces. I recommend that you use tabs for indentation, as typing an equal number of spaces in every line becomes very time-consuming.

Just like all other languages, to carry out the conditional operations, Python makes use of conditional statements. The conditional statements supported by Python are as follows:

• if condition
• if...else condition
• else...if conditional ladder, known as elif in Python

The if condition or the if statement takes a statement and returns either a Boolean True or a Boolean False value after evaluating the statement. If the condition returns True, the code proceeding the if statement (equally indented) is executed. If the statement/condition evaluates to False, then either the else block of code gets executed if there is one, or the block of...

Loops are utilities that every programming language has. With the help of loops, we execute tasks or statements that are repetitive in nature, which, without loops, would take up lots of lines of code. This, in a way, defeats the purpose of having a programming language in the first place. If you are familiar with Java, C, or C ++, you might have already come across while, for, and do...while loops. Python is pretty much the same, except that it doesn't support do...while loops. Thus, the loops that we are going to study in the following section in Python are the following:

• while loop
• for loop

Remember that when we discussed lists in the first chapter of the book, we mentioned that lists can actually...

Functions and methods are used to design or make a logical unit of code that can be reused throughout the course of your script or other scripts. Functions actually form the basis of code reuse and bring modularity to the code structure. They keep the code clean and easier to modify.

The following code represents the basic syntax of defining methods in Python:

def print_message(message):
    print(message)
    statement 2
    statement 

Python methods do not have a return type in their definition as you might have seen in C, C++, or Java, such as void, in, float, and so on. A Python method may or may not return a value, but we do not explicitly need...

Every Python script is called a module. Python has been designed with reusability and ease of code in mind. For this reason, every Python file we create becomes a Python module and is eligible to be invoked or used within any other file or script. You might have learned in Java how to import classes and reuse them with other classes. The idea is pretty much the same here, except that we are importing the whole file as a module and we can reuse any method, class, or variable of the imported file. Let's take a look at an example. We will create two files, child.py and parent.py, and put the following code in each, as follows:

A generator is a special kind of iterator in Python. In other words, a Python generator is a function that returns us a generator iterator by issuing the yield command, which can be iterated upon. There might be occasions in which we would want a method or function to return us a series of values, instead of just one. We might, for example, want our method to partially carry out a task, return the partial results to the caller, and then resume the work right from the place where it returned the last value. Usually, when a method terminates or returns a value, its execution begins again from the start. This is what generators try to address. A generator method returns a value and a control to the caller and then continues its execution right from where it left off. A generator method is a normal Python method with a yield statement. The following code...

In this chapter, we discussed abut conditions, loops, methods, iterators, packages, generators, and comprehensions. All of these are widely used in Python. The reason why we covered these topics is because when we get into automating penetration testing and cyber security test cases later on, we will see these concepts widely used within our code files. In the next chapter, we will explore the object-oriented nature of Python. We will explore how to deal with XML, CSV, and JSON data in Python. We will also read about files, IO, and regular expressions.

1. Name a real-world use case in which generators are used.
2. Can we store a function name in a variable and then invoke it via a variable?
3. Can we store a module name in a variable?

• Generators and Comprehensions: http://jpt-pynotes.readthedocs.io/en/latest/generators-comprehensions.html
• Modules: https://docs.python.org/3/tutorial/modules.html