Basics of Python Programming: A Quick Guide for Beginners

Python is an object-oriented programming language that can support a wide range of applications like web development, desktop applications, etc. Its general-purpose programming features make coding easy, comprehensive and readable even for beginners. 

Now that you have been familiarised with the installation and basics of Python programming, it's time to dig in a little more and understand the different data types that are available along with the operators and expressions that make the programming more user-friendly. In this chapter, we will learn about data type categorization and the operators present. Here you will learn the following nuances: 1. Data types supported by the Python. 2. Use of variables to store and access the data. 3. Operators do mathematical works and logical functions. 4. Variety of expressions to serve the range of applications. 

It's now the time for the readers to acquaint themselves with the control flow in the programming. So far the users have seen the linear path of execution, where the execution commences from the top and moves sequentially to the bottom. Further, our world is filled with tasks required to run in loops, for example in banking applications, unless the user enters the correct password the system prompts the dialogue “Please enter the correct password”. In this chapter, we introduce the concept of control flow through which the users can decide the execution path for the program and the looping constructs to iterate through the tasks. Our key takeaways from this chapter are listed below: 1. Understanding the decision control statements. 2. Programming with if-else ladder and its variants. 3. A hand on for, and while loop statements. 4. Understanding the control flow alterations the jump statements like break, continue and pass.

Functions are one of the primary concepts in every programming language. They provide an easy way to package the programming logic and use it as and when required as many times at any place. Thus they help to reduce the redundancy in code and increase the reproducibility. With the increase in the length of code, it is often a good idea to divide the code into separate modules by splitting the code into different functions based on its utility. This is a much- sought practice to organise the lengthy code. They also help in unit testing the code as testing small units in isolation is quite an easy task. This deliberate use of functions thus supports language flexibility and a user-friendly interface. In this chapter the pertinent takeaways would be: 1. Understanding functions and function calls. 2. Comprehending the concept of local and global variables. 3. Programming with the recursive functions.

Unlike primitive data types like integers, floats and Boolean, a string is an ordered sequence of characters each of which can be accessed easily. Further, one of the important built-in data types of Python is lists. Lists and strings share many similarities like, lists are a sequence of values. List indices work similarly to string indices. But unlike strings lists are mutable. In this chapter, we introduce the core concepts of lists and strings and several operators that are used to make programming with these user-friendly.

Another important data type of Python is dictionary. In the previous chapter, we acquainted the readers with the lists and strings. In this chapter, we shall discuss dictionaries and lists. lists are the ordered collection of objects but dictionaries are an unordered collection of objects. dictionary values are referred to using key-value pair instead of positional offset. Due to this, they have found great usage in search tables, records and aggregation. Another concept introduced in this chapter is tuples. These are immutable like strings and represent a stable collection of arbitrary items. 

From the previous chapters, we anticipate that the readers have garnered enough working knowledge of Python and its elementary concepts. In this chapter, we introduce to the user the concept of files. These are one of the major built-in object types in Python. We can create, call, work, and close the files using several functions as enunciated below. One of the primary tasks of files is method exporting and common file-processing tasks such as input and output display to external files, flush buffers, etc.

In this chapter, we introduce the concept of exception handling in Python. They are used to specify the alternate sequence of actions the program needs to jump to at the occurrence of the event. For example, if we want to print several pages from the printer and somewhere in the middle of the job the paper gets stuck in the printer. In such as situation we would want to jump to the function that aborts the printing and handles this situation by instant shut down of the printer. In such events comes the exception handling. When the program jumps to the exception handler part the current sequence of commands is abandoned and the commands given to the exception handler are executed. After the exception is tackled the programming returns to the point where the marker left. 

Useful codes are often stored as separate files to increase modularity and reusability. Modules refer to a single file of code while a package is a collection of modules. A good programmer utilises both these aspects to enhance the program view and manage the hierarchy. In this chapter, we introduce the basics of working with the modules and packages.

In this chapter, we explore the OOP concepts in programming that offer an effective way of making coding more easy and comprehensive. It facilitates redundancy and allows customizing the existing code.

Anticipating that the user has a good knowledge of the core elements of Python we now explore the applicative aspect of Python. In this chapter, we will look at Python, especially from the Machine Learning (ML) point of view. We will discuss the various libraries and their utility in ML and then lay hands over the programming demonstrations.

After the successful comprehension of the different aspects of Python and its applications in ML, it's now the time to look at how they can be combined and put to work using common examples. This will surely increase the reader's comprehension of the intricacies of Python and demonstrate the efficiency of the language in making the programming simple.