CODING WITH PYTHON:

A SIMPLE AND STRAIGHTFORWARD GUIDE FOR BEGINNERS TO LEARN FAST PROGRAMMING WITH PYTHON.

Table of Contents

Introduction

Chapter 1 ​ What is Python?

Features of the Python

History of the Python

Why You Should Use Python

General Terms in the Python

Advantages of Python Language

Disadvantages of using Python programming

Chapter 2 ​ Why Python?

The Alternatives

Python is Different

Advantages of Using Python in Data Analysis

Chapter 3 ​ Installing Python

Choosing a Python Version

General Installations Instruction

Installation on Windows

Installation on Linux (Ubuntu)

Installation on Mac OS

Running Programs

Interactive Interpreter or Interactive Mode via Shell

Script from Command Line

Python IDE (Integrated Development Environment)

Chapter 4 ​ What are Data Types?

Strings

Numeric Data Type

Booleans

List

Variables

Chapter 5 ​ How to Read Errors and Troubleshooting Your Code

How to override the base class

Overloading

Final Notes about Inheritances

Chapter 6 ​ Variables

Creating a Variable

Variable Naming and Assignment

Variable Declaration and Assignment

Variable Naming Rules

Static Type and Dynamic Type

Chapter 7 ​ Lists

Chapter 8 ​ Dictionaries

Dictionaries vs. lists

Useful methods

Value or key check

Chapter 9 ​ Functions

Definition Statement and Function Calls

Parameters

Keyword Arguments

Return Values

Chapter 1 0               User’s Input and Loop

The input () method

The While Loop

Chapter 1 1               Tuples

How to Create a Tuple

Accessing Tuple Elements

Changing, Reassigning, and Deleting Tuples

Tuple Membership Test

Python Tuple Methods

Built-in Functions with Tuples

Iterating Through a Tuple

Tuples vs. Lists

Chapter 1 2               Control Statements

If Statement

If-Else Statement

If Elif Else Statement

Nested If

Chapter 1 3               File Management

Why use modules?

How Create a Module on Python

Import Statement

How to Import a Module?

Namespaces in Modules

What Are the Attributes?

Errors

Encoding

Newline

Handling Files

Xlsx files

What is Sequence in Python?

Chapter 1 4               Getting Started; Python Tips and Tricks

Web Scraping

Chapter 1 5               Things We Can Do in Python

Comment

Reading and Writing

Files

Integers

Triple Quotes

Strings

Escape Sequences

Operator Precedence

Variables

The Scope of a Variable

Modifying Values

The Assignment Operator

Chapter 1 6               Working with Files

Opening and Reading

Writing to Text Files

Buffer Size/Binary Files

Deleting and Renaming

Chapter 1 7               Python in the Real World

What is Python Used For?

Robotics

Machine Learning

Cybersecurity

Web Development

Conclusion

Introduction

There are various operating systems that you are able to work without there. Each of them is set up to handle different situations and help you to get different things done with your work. But you will find that one of the best coding languages out there, the one that will help you to get the most done while still being easy to maintain and work with, is the Python language. 

There are a lot of coders and programmers out there who love to work with the Python language. And as we go through this guidebook and learn a bit more about this language and what it is able to help us do, you will not take long before you realize why it is such a popular option to work with, and why so many people love it. Some of the different benefits that you will be able to see when it is time to work with the Python language includes:

Python is an easy coding language to learn how to use. If you have never had a chance to work with any coding language at all, then you are going to really enjoy working with the Python language overall. This is going to make it easier for us to handle some of the coding that we are not used to, and you will be able to catch on to some of the basics that come with coding in Python and more in no time at all. 

Python has a lot of power and resources behind it. Sometimes there is worry that working with this language is going to be too easy that you will not be able to handle some of the more complicated codes that you would like to work with. The Python language is often going to be advertised as a beginner's language, and this can keep a few programmers away from it. 

The good news here is that the Python language is not just a good coding language for beginners to get started with. It is also a good language that is going to help you to get a lot of the different codes that you want. We will take a look at some of the different options that you can do when it is time to code, and we are going to spend some time on them in this guidebook as well. And you will be able to handle them with plenty of strength that comes in the Python language. 

And if there are a few things that you may struggle within this language, or that are not strong enough to handle, then you will be able to combine in another language, while still relying on the Python syntax. You will find that Python works well with a lot of other coding languages, and several of the libraries that work with Python can help you to get this done. This will ensure that the few tasks you need help with will work well, while still choosing the Python language. 

Python has a great standard library to work with. For the beginner coder, and someone who is just getting started with some of the work that comes with the Python language, or any coding for that matter, you will find that the regular library of Python is going to have all of the parts that you need. You will be able to use the standard library of Python in order to handle all of the coding that we are going to explore in this guidebook. 

Python has a lot of extensions and other libraries that can help to add to the capabilities that come with this language. Even though there is a lot that we are able to do when it comes to working on the Python language, you will find that there are also some good extensions that you can take a look at as well. These are going to be good options to go with because they will extend out what the Python language is able to handle, and will make it easier to handle things like science, math, machine learning, data science, and so much more. 

The kinds of extensions that you are going to use will really depend on what your goals are overall with the language. If you want to work with machine learning and this language, then there are a lot of great libraries and extensions that you are able to choose to help with that as well. But there are also some that work with other features and capabilities as well, so you need to make sure that you are choosing the right one for your needs. 

Python has a large community that can provide beginners with the support and helps they need. At some point, there will be some part of coding that you are not sure how to do, or you are going to run into something that may not make sense when it is time to work on your coding. This is going to happen with many beginners, so it is nothing to be worried about But since there is a nice community out there of other programmers and coders who like to use Python, you will be able to find the assistance that you need in no time. 

This community will be there to help you to get going overall, and they can answer all of your questions, make sure that you understand what is going on, and just provide you with all of the resources that you need to make sure you are doing well. You can visit this community as often as you need to make sure that you are able to handle all of the different coding options that you want to work with too.

Python is considered an OOP language that relies on classes and objects to keep things nice and organized Right now, that may not seem to mean all that much for you. But in the long run, it is going to help us to make sure that we can keep all of the parts of our code organized and easy to work with. The code is set up so that you can create the classes that you need while still ensuring that you can add in the objects of the code and find everything later on. 

This was not something that we were able to find with some of the traditional coding languages out there. These could sometimes be harder to work with than Python and other options because they are not going to be that organized and things can move around on you. But in Python, the code is going to rely on those classes and more to ensure that it works the way that you want, and that you are able to find the objects that you need. 

Python is a great general-purpose language that is easy to learn, has all of the features that you would want in a coding language, and so much more. If you don’t want to get into a language that is too technical, but you do want to make sure that you pick out a language that is able to handle a lot of different programming tasks at the same time, then Python is the right language for your needs. 

You would want to go through and work with the Python language for many reasons, especially when you are new to the world of coding. For those who have never been able to do any coding in the past, you will find that the Python coding adds in all of the ease of use that you need to see success while still ensuring that you are going to be able to get all of the power that you need actually to complete some of the coding that you would like. 

Chapter 1 What is Python?

The introduction of technologies, especially computers, has influenced our behavior differently. Some people spend most of their time on computers that create programs and websites to make a living, while others mess around with computers to try to understand many different things about how machines work. Programming is one of the areas in networks that most people in the world focus on as a source of income. They can work in a company or computer repair to protect computers from attacks such as hackers or viruses.

One of the most advanced programming tools is Python because anyone, including beginners or experts, can easily use and read it. The secret to using Python is that you can read it because it contains syntax, which allows you as a programmer to express your concepts without necessarily creating a coding page. This is what makes Python easier to use and read than the other codes, including C ++ and Java. Overall, Python is the best language for you because of its usability and readability. We are therefore confident that it will be easy for you to read and understand all the codes you enter while creating your first program during and after this course.

Features of the Python

Python has the following characteristics:

•                               Large library: it works with other programming projects such as searching for texts, connecting to the web servers and exchanging files.

•                               Interactive: Using the Python is very simple because you can easily test codes to determine if they work.

•                               It is free software; so you can always download it from the internet with your computer.

•                               Python programming language can be extended to other modules such as C ++ and C.

•                               Has an elegant syntax that makes it easy for beginners to read and use.

•                               Has several basic data types to choose from.

History of the Python

Python programming was discovered by Guido Van Rossum in 1989 while he was carrying out a project at the Dutch research institute CWI, but it was later discontinued. Guido has successfully used a number of basic languages, the so-called ABC language, to work on the Python. According to Van Rossum, the strength of the python language is that you can either keep it simple or extend it to more platforms to support many platforms at once. The design allowed the system to communicate with the libraries and various file formats easily.

Since its introduction, many programmers now use Python in the world, and in fact, many tools are included to improve operation and efficiency. Many programmers have taken various initiatives to educate everyone about using python programming language and how it can help ease the fear of complex computer codes.

However, the Python was made open source by Van Rossum a few years ago to allow all programmers access and even make changes to it. This has changed a lot in the field of programming. For example, there was a release of the Python 2.0. Python 2.0 was community-oriented, making it transparent in the development process. While many people don't use Python, there are still some programmers and organizations that use part of the version.

The Python 3, a unique version, was released in 2008. Although the version has many different functions, it is completely different from the first two versions and it is not easy to update the program. While this version is not backwards compatible, it has a small creator to show what needs to be changed when uploading the files.

Why You Should Use Python

There are many types of computer coding programs in the world, each with its advantages and disadvantages. However, Python has proven to be the best option for a variety of reasons, such as readability, and can be used on many platforms without changing things. Using Python has the following advantages;

Readability

Since it is designed in the English language, a beginner will find it easy to read and us. There are also a number of rules that help the programmer understand how to format everything, and this makes it easy for a programmer to create a simple code that other people can follow when using their projects with it.

Community

Today, there are many workshops for Python worldwide. A beginner can visit online, offline or both to learn more or even seek clarification on Python. Also, online and offline workshops can improve your understanding of Python, as well as your socialization skills. It is best for the personal computer as it works successfully on many different platforms. In fact, all beginners find it easy to code or learn from the expert.

Libraries

For over 25 years, programmers have been using Python to teach the beginners how to use different codes written with it. The system is very open to programmers and they can use the available codes indefinitely. In fact, a student can download and install the system and use it for their personal use, such as writing your codes and completing the product.

General Terms in the Python

Understanding the standard terms used in Python is essential to you. It makes everything easy to know when you get started. Following are the most common terms in the Python programming language;

•                               Function: refers to a code block that is called when a programmer uses a calling program. The goal is also to provide free services and accurate calculation.

•                               Class: a template used for developing user-defined objects. It is friendly and easy to use by everyone including the beginners.

•                               Ver Immutable: refers to an object with a fixed value and is contained within the code. These can be numbers, strings, or tuples. Such an object cannot be changed.

•                               St Docstring: Refers to a string that is displayed in the function, class definition, and module. This object is always available in the documentation tools.

•                               List: refers to the data type built into the Python and contains values sorted. Such values include strings and numbers.

•                               LE IDLE: Stands for an integrated development environment that allows the users to type the code while interpreting and editing it in the same window. Best suited for beginners because it is an excellent example of code.

•                               Interactive: Python has become the most suitable programming language for beginners due to its interactive nature. As a beginner, you can try out many things in the IDLE (interpreter to see their response and effects).

•                               Qu Triple Quoted String: The string helps an individual to have single and double quotes in the string, making it easy to go through different lines of code.

•                               Object: it refers to all data in a state such as attitudes, methods, defined behaviors or values.

•                               Type: refers to a group of data categories in the programming language and differences in properties, functions and methods.

•                               Tuple: Refers to the datatype built into the Python and is an unchanging set of values, although it contains some changeable values.

Advantages of Python Language

Using the Python program has many advantages over other programming languages such as C ++ and Java. You will be happy to see the availability and how easy it is to learn and use the Python program. Ideally, these are the best programming languages you can use right now, especially if you are a beginner. Following are some of the advantages of using Python language;

It is easy to use, write and read

Many programmers face some challenges when using programming languages such as Java and C ++. They are difficult to view due to their design. One has to spend a lot of his / her time learning about the use of parentheses and it is not easy to recognize some of the words used in these programming languages. Such words can scare you, especially if you are just getting acquainted with the programming languages. Unlike Java and C ++ languages, Python does not use crazy brackets. It only uses indents, making it easy to read the page. It uses English which makes it easy to understand characters.

In addition to using indents, Python uses a lot of white spaces, making it easy to learn and read what's needed. It consists of many places with comments to allow you to understand or get clarification in case the program confuses you. So check it out and you will see how easy it is to use the Python programming language.

It uses English as the primary language

Using Python is easy because the main language is English. As a beginner, you will spend less time reading and understanding the basic words used when programming in Python. So, whether you speak native or non-native English, Python is best for you because most words are simple and easy to understand.

Python is already available on some computers

Some computers such as macOS systems and Ubuntu come with Python pre-installed. In this case, you just need to download the text interpreter to get started with Python programming. However, you must download the program on your computer if you are using a Windows computer. In fact, Python works fine even if you didn't install it from the beginning.

Python works perfectly with other programming languages

For the first time, you will be using Python alone. However, you will realize that Python can work with other languages as you continue programming. Some of the programming languages that you can work with Python include C ++ and JavaScript. Try to learn more about Python and what it can do practically. You will be able to discover many things over time.

Th Python can be used to test many things

You need to download the test interpreter once you have downloaded the Python. Test interpreter plays an important role in enabling Python to read the information. It's good to use a simple product like Notepad that is available in your Windows or other interpreters.

Disadvantages of using Python programming

While there are many advantages to using Python, it is essential to recognize some of the adverse effects of using it. Some individuals prefer to use other programming languages such as C ++ and JavaScript for Python because of the following negative effects of Python.

Python has a slow speed

While Python works well with other programming languages and is suitable for beginners, it is unfortunate that Python is not ideal for programmers looking for a high speed program as it is a slower translated language than the other options. The level of speed depends on the content you are translating because some benchmarks with Python code work faster compared to other codes. Currently, many programmers around the world are trying to solve this problem by making the interpreting speed faster. It is hopeful that Python will run at the same rate or even faster than C and C ++ soon.

Python is not available in most mobile browsers

While Python works well for those who have regular computers and is accessible on many server platforms and desktops to help individuals create the codes they are looking for, it is not yet ready for mobile computing. Programmers are trying to transition the program to mobile computing to cater to today's large numbers of people who use cell phones.

Limited design

Python program is not a better option for programmers looking for a program with many design options. For example, the design language is not available in some other options; so you will need more time to test and sometimes a lot of errors can occur when you run the program.

Chapter 2 Why Python?

I have experience coding in several programming languages. Last week, I was discussing a project with a friend who is a developer, and out of nowhere, he asked me the question “Why Python? Of all the languages that are available, why did you settle with Python?” My friend definitely caught me off guard because I had never thought about it. The day I started programming with Python was the day I almost stopped coding in any other language. I still occasionally use other languages depending upon the project, but, if given the choice, I pick Python every time.

But, why? Yes, this is a small question but it carries a lot of weight. I spent a few days figuring out the advantages of using Python over other languages. Of course, I can list a few problems, too. I am going to share my point of view with you now.

The Alternatives

Before we look into Python, let’s talk about the alternatives we can use for programming.

The C Family

UNIX is arguably the first operating system that was widely used across different computer systems. AT&T Bell Laboratories developed the operating system for minicomputers in the late 1960s based upon a language that we now call the C language. AT&T forced companies using Bell systems to use UNIX which meant UNIX was ported to various different computer systems along with the C language. Because the C language became so common, many languages that were developed later provided a similar coding environment to make it easier for C language programmers to use them. 

The list of C-family programming languages is a long one, but some became more famous than others. C, C++ and C# are the three most popular, closely followed by Objective C. 

Advantages

•                     As of October 2019, C is the most widely used language family after Java and Python. Embedded systems and operating systems still depend heavily on C language

•                     Every programmer should learn at least one of the C, C++ or C# languages to understand what happens in the background during program execution

Disadvantages

•                     It is difficult to learn as it forces programmer to focus on things that modern programming languages take care of automatically

•                     The syntax, although it inspired a lot of other languages, is very ugly.

•                     A lot of extraneous lines of codes are required even to perform the most basic tasks.

Java Platform

Thanks to the millions of web applications developed using the language, Java is possibly the most widely used programming language in the world. Released as a core component of the Java platform in 1995 by Sun Microsystems, it enabled applications built using Java to run on any computer system that has Java Virtual Machine (JVM). Although it has a syntax similar to C and C++ languages, it doesn’t demand low-level considerations from the programmers. Oracle has acquired Sun Microsystems and now manages Java platform. 

For years, Microsoft’s C# and Sun’s Java remained in a cold war, each trying to outdo the other programming language. Both languages were heavily criticized for adding new features just to win a competition instead of following a standard direction. It was not until 2004 that both languages took to separate ways and developed into the unique languages as we know them today.  

Even then, Java remains the top programming language in the world and Java platform runs on almost every laptop, game console, data center, and even supercomputers.  

Advantages

•                     Java frees the programmer from computer dependencies and offers a vast degree of freedom

•                     Java is compatible with almost all computer systems. It means almost every program created using Java language will run on all those systems without any issues.

Disadvantages

•                     There have been serious security issues with Java over the years. Severe security vulnerabilities were found in the last Java version and Oracle advised every Java user to update to the latest version.

•                     Java programs are known to be slower than the competition even though there have been huge performance improvements in recent versions.

•                     For a long time Java remained a proprietary platform. Even after Sun declared it open-source, a long copyright battle ensued between Oracle and Google over the use of Java in Google’s Android.

Python is Different

We have briefly tackled the best options we have if we don’t want to use Python. They are great options but before you jump ship, let me tell you why I chose Python over others. 

•                     Python is one of the easiest high-level programming languages to learn. It means the time it takes from setup to coding programs is very short.

•                     Code written in Python is easier to understand. It enables programmers to consult codes written by other programmers to adapt for their project.

•                     Python is an interpreter language. Code is executed one line at a time which makes debugging easier for beginners.

•                     Python code can run on any computer no matter if it’s Windows, Linux, UNIS, or a macOS based system.

•                     Python has a vast standard library that provides methods for unique project requirements.

•                     Python supports various coding paradigms including Object Oriented Programming (OOP) and functional programming.

•                     Python programming language is free and open source. This has helped create an active programmer community and detailed tutorials are available for free on the Internet.

•                     The open source nature of the language has also enabled many programmers to extend Python capabilities by writing special libraries. These libraries are available on the Internet free of charge for everyone’s use.

•                     It’s very easy to create Graphical User Interface (GUI) through Python.

•                    One of the biggest advantages of Python is its ability to integrate with different programming languages. You can import a specific library and start coding in a completely different language and Python will understand the codes. Python supports extended integration with C++ and Java. Not only that, Python code can be placed inside a code written with another programming language. 

These are the general advantages of Python over other programming languages. Depending upon your project, Python might be able to provide even more benefits. We are going to see how Python makes data analysis easy.

Advantages of Using Python in Data Analysis

Strong with Strings

Python has a special place for strings. There are multiple string related operations supported by Python. These operations are a big help in data analysis stages of parsing and processing if you are dealing with string data. 

Dedicated Libraries

There are dedicated libraries in Python that help make data analysis projects easier to handle. The libraries are regularly updated which means they are compatible with the latest analysis algorithms.

Some of the popular data analysis libraries available on Python are:

NumPy: Collection of mathematical functions for fast calculations

SciPy: Offers advanced scientific tools

Pandas: Offers robust handling of mathematical components using data structures

Matplotlib: Offers data visualization methods including line plots, bar charts, and scatter plots.

Highly Scalable

Python is very efficient in handling large and complex datasets. This quality has made this programming language invaluable to companies like YouTube, Facebook, and Amazon that deal with huge data on a consistent basis. 

Fast Deployment

With a simple coding syntax and straightforward development process, it’s definitely faster to create and deploy applications using Python as compared to other languages. 

If you look at the larger picture, Python provides the easiest yet most robust coding environment. It’s faster to learn and deploy applications. It integrates well with other programming languages and technologies. There are tons of free tutorials and documentations available online for help if you are not able to resolve an issue. 

All of the above qualities make Python the best package when it comes to programming languages. Yes, you might find that another programming language suits your needs better for a specific application, for example, for web applications JavaScript is more popular, and for database, SQL is used more. But, as a whole, Python offers you everything you need for 90% of the programming tasks.

Knowing all this, do you still think I made a mistake sticking with Python? Personally, I think it was a great decision. I told my friend all these points and he was amazed by how versatile Python is. Whenever I meet someone who asks me where they should start with programming, I recommend they start with Python. 

Chapter 3 Installing Python

To code in Python, you must have the Python Interpreter installed in your computer. You must also have a text editor in which you will be writing and saving your Python codes. The good thing with Python is that it can run on various platforms like Windows, Linux, and Mac OS. Most of the current versions of these operating systems come installed with Python. You can check whether Python has been installed on your operating system by running this command on the terminal or operating system console: 

Python

Type the above command on the terminal of your operating system then hit the Enter/Return key.  

The command should return the version of Python installed on your system. If Python is not installed, you will be informed that the command is not recognized; hence you have to install Python.  

Choosing a Python Version

The main two versions of Python are 2.x and 3.x. Python 3.x is obviously the latest one but Python 2.x as of today is most likely still the most used one. Python 3.x is however growing much faster in terms of adoption.  Python 2.x is still in use in many software companies. More and more enterprises however are moving to Python 3.x. There are several technical differences between the 2 versions. We can summarize in very a simple way as Python 2.x is legacy and Python 3.x is the future. The advice for you is to go for the latest version Python 3.x. From 2020 Python 2.x is not be supported anymore. 

General Installations Instruction

Installing Python is very easy. All you need to do is follow the steps described below:

Go to Python downloads page https://www.python.org/downloads/

Click the link related to your operating system

Click on the latest release and download according to your operating system

Launch the package and follow the installation instructions (we recommend to leave the default settings)               

Make sure you click on Add Python 3.x to PATH. Once the installation is finished you are set to go!

Access your terminal IDLE 

Test that all works by writing your first Python code: 

☐       print ("I'm running my first Python code")  

Press enter or return, this is what you should get

You can do the same also by launching this command using a file.  We will address this after we address the Python IDLE or another code editor.

Installation on Windows

To install Python on Windows, download Python from its official website then double click the downloaded setup package to launch the installation. You can download the package by clicking this link: 

https://www.python.org/downloads/windows/

It will be good for you to download and install the latest package of Python as you will be able to enjoy using the latest Python packages. After downloading the package, double click on it and you will be guided through on-screen instructions on how to install Python on your Windows OS.  

Installation on Linux (Ubuntu)

In Linux, there are a number of package managers that can be used for installation of Python in various Linux distributions.  For example, if you are using Ubuntu Linux, run this command to install Python: 

$ sudo apt-get install python3-minimal 

Python will be installed on your system. However, most of the latest versions of various Linux distributions come installed with Python. Just run the “python” command. If you get a Python version as the return, then Python has been installed on your system. If not, go ahead and install Python.  

Installation on Mac OS 

To install Python in Mac OS, you must first download the package. You can find it by opening the following link on your web browser: 

https://www.python.org/downloads/mac-osx/

After the setup has been downloaded, double click it to launch the installation. You will be presented with on screen instructions that will guide through the installation process. Lastly, you will have Python running on your Mac OS system.  

Running Programs

One can run Python programs in two main ways: 

•                     Interactive interpreter

•                     Script from command line

Interactive Interpreter or Interactive Mode via Shell

Python comes with a command line which is commonly referred to as the interactive interpreter. You can write your Python code directly on this interpreter and press the enter key. You will get instant results. If you are on Linux, you only have to open the Linux terminal then type “python”. Hit the enter key and you will be presented with the Python interpreter with the >>> symbol. To access the interactive Python interpreter on Windows, click Start -> All programs, then identify “Python …” from the list of programs. In my case, I find “Python 3.5” as I have installed Python 3.5. Expand this option and click “Python …”. In my case, I click “Python 3.5(64-bit)” and I get the interactive Python interpreter.  

Here, you can write and run your Python scripts directly. To write the “Hello” example, type the following on the interpreter terminal: 

print("Hello")

Hit the enter/return key and the text “Hello” will be printed on the interpreter: 

Script from Command Line 

This method involves writing Python programs in a file, then invoking the Python interpreter to work on the file. Files with Python should be saved with a .py extension. This is a designation to signify that it is a Python file. For example, script.py, myscript.py, etc. After writing your code in the file and saving with the name “mycode.py”, you can open the operating system command line and invoke the Python interpreter to work on the file. For example, you can run this command on the command line to execute the code on the file mycode.py: 

python mycode.py  

The Python interpreter will work on the file and print the results on the terminal.   

Python IDE (Integrated Development Environment) 

If you have a GUI (Graphical User Interface) application capable of supporting Python, you can run the Python on a GUI environment. The following are the Python IDEs for the various operating systems: 

•                     UNIX- IDLE

•                     Windows- PythonWin

Macintosh comes along with IDLE IDE, downloadable from the official website as MacBinary or BinHex'd files. 

Chapter 4 What are Data Types?

Every program has certain data that allows it to function and operate in the way we want. The data can be a text, a number, or any other thing in between. Whether complex in nature or as simple as you like, these data types are the cogs in a machine that allow the rest of the mechanism to connect and work. 

Python is a host to a few data types and, unlike its competitors, it does not deal with an extensive range of things. That is good because we have less to worry about and yet achieve accurate results despite the lapse. Python was created to make our lives, as programmers, a lot easier. 

Strings

In Python, and other programming languages, any text value that we may use, such as names, places, sentences, they are all referred to as strings. A string is a collection of characters, not words or letters, which is marked by the use of single or double quotation marks.

To display a string, use the print command, open up a parenthesis, put in a quotation mark, and write anything. Once done, we generally end the quotation marks and close the bracket.  

Numeric Data Type

Just as the number suggests, Python is able to recognize numbers rather well. The numbers are divided into two pairs:

Integer – A positive and negative whole numbers that are represented without any decimal points.

Float – A real number that has a decimal point representation.

This means, if you were to use 100 and 100.00, one would be identified as an integer while the other will be deemed as a float. So why do we need to use two various number representations?

If you are designing a program, suppose a small game that has a character’s life of 10, you might wish to keep the program in a way that whenever a said character takes a hit, his life reduces by one or two points. However, to make things a little more precise, you may need to use float numbers. Now, each hit might vary and may take 1.5, 2.1, or 1.8 points away from the life total.

Using floats allows us to use greater precision, especially when calculations are on the cards. If you aren’t too troubled about the accuracy, or your programming involves whole numbers only, stick to integers.

Booleans

Boolean (or bool) is a data type that can only operate on and return two values: True or False. Booleans are a vital part of any program, except the ones where you may never need them, such as our first program. These are what allow programs to take various paths if the result is true or false.

Here’s an example. Suppose you are traveling to a country you have never been to. There are two choices you are most likely to face.

If it is cold, you will be packing your winter clothes. If it is warm, you will be packing clothes which are appropriate for warm weather. Simple, right? That is exactly how the Booleans work. We will look into the coding aspect of it as well. For now, just remember, when it comes to true and false, you are dealing with a bool value.

List

While this is slightly more advanced for someone at this stage of learning, the list is a data type that does exactly what it sounds like. It lists objects, values, or stores data within square brackets ([]). Here’s what a list would look like:

month = ['Jan', 'Feb', 'March', 'And so on!']

Variables

You have the passengers, but you do not have a mode of commuting; they will have nowhere to go. These passengers would just be folks standing around, waiting for some kind of transportation to pick them up. Similarly, data types cannot function alone. They need to be ‘stored’ in these vehicles, which can take them places. These special vehicles, or as we programmers refer to as containers, are called ‘variables,’ and they are exactly what perform the magic for us.

Variables are specialized containers that store a specific value in them and can then be accessed, called, modified, or even removed when the need arises. Every variable that you may create will hold a specific type of data in them. You cannot add more than one type of data within a variable.

In other programming languages, you will find that in order to create a variable, you need to use the keyword ‘var’ followed by an equals mark ‘=’ and then the value. In Python, it is a lot easier, as shown below:

name = "John"

age = 33

weight = 131.50

is_married = True

In the above, we have created a variable named ‘name’ and given it a value of characters. If you recall strings, we have used double quotation marks to let the program know that this is a string.

We then created a variable called age. Here, we simply wrote 33, which is an integer as there are no decimal figures following that. You do not need to use quotation marks here at all.

Next, we created a variable ‘weight’ and assigned it a float value.

Finally, we created a variable called ‘is_married’ and assigned it a ‘True’ bool value. If you were to change the ‘T’ to ‘t’ the system will not recognize it as a bool and will end up giving an error.

Focus on how we used the naming convention for the last variable. We will be ensuring that our variables follow the same naming convention.

You can even create blank variables in case you feel like you may need these at a later point in time or wish to initiate them at no value at the start of the application. For variables with numeric values, you can create a variable with a name of your choosing and assign it a value of zero. Alternatively, you can create an empty string as well by using opening and closing quotation marks only.

empty_variable1 = 0

empty_variable2 = ""

You do not have to name them like this necessarily; you can come up with more meaningful names so that you and any other programmer who may read your code would understand. I have given them these names to ensure anyone can immediately understand their purpose.

Now we have learned how to create variables, let’s learn how to call them. What’s the point of having these variables if we are never going to use them, right?

Let’s create a new set of variables. Have a look here:

name = "Jonah"

age = 47

height_in_cm = 170

occupation = "Programmer"

I do encourage you to use your own values and play around with variables if you like.

In order for us to call the name variable, we simply need to type the name of the variable. In order to print that to the console, we will do this:

print(name)

Output

Jonah

The same goes for the age, the height variable, and occupation. But what if we wanted to print them together and not separately?

Try running the code below and see what happens:

print(name age height_in_cm occupation)

Surprised? Did you end up with this?

print(name age height_in_cm occupation)

^

SyntaxError: invalid syntax

Process finished with exit code 1

Here is the reason why that happened. When you were using a single variable, the program knew what variable that was. The minute you added a second, a third, and a fourth variable, it tried to look for something that was written in that manner. Since there wasn’t any, it returned with an error that otherwise says:

“Umm… Are you sure, Sir? I tried looking everywhere, but I couldn’t find this ‘name age height_in_cm occupation’ element anywhere.”

All you need to do is add a comma to act as a separator like so:

print(name, age, height_in_cm, occupation)

Output:

Jonah 47 170 Programmer

“Your variables, Sir!”

And now, it knew what we were talking about. The system recalled these variables and was successfully able to show us what their values were. But what happens if you try to add two strings together? What if you wish to merge two separate strings and create a third-string as a result?

first_name = “John”

last_name = “Wick”        

To join these two strings into one, we can use the ‘+’ sign. The resulting string will now be called a String Object, and since this is Python we are dealing with, everything within this language is considered as an object.

first_name = "John"

last_name = "Wick"

first_name + last_name

Here, we did not ask the program to print the two strings. If you wish to print these two instead, simply add the print function and type in the string variables with a + sign in the middle within parentheses. Sounds good, but the result will not be quite what you expect:

first_name = "John"

last_name = "Wick"

print(first_name + last_name)

Output:

JohnWick

Why do you think that happened? Certainly, we did use a space between the two variables. The problem is that the two strings have combined together, quite literally here, and we did not provide a white space (blank space) after John or before Wick; it will not include that. Even the white space can be a part of a string. To test it out, add one character of space within the first line of code by tapping on the friendly spacebar after John. Now try running the same command again, and you should see “John Wick” as your result.

The process of merging two strings is called concatenation. While you can concatenate as many strings as you like, you cannot concatenate a string and an integer together. If you really need to do that, you will need to use another technique first to convert the integer into a string and then concatenate the same. To convert an integer, we use the str() function.

text1 = "Zero is equal to "

text2 = 0

print(text1 + str(text2))  

Output:

Zero is equal to 0

Python reads the codes in a line-by-line method. First, it will read the first line, then the second, then third, and so on. This means we can do a few things beforehand as well, to save some time for ourselves.

text1 = "Zero is still equal to "

text2 = str(0)

print(text1 + text2)

Output:

Zero is still equal to 0

You may wish to remember this as we will be visiting the conversion of values into strings a lot sooner than you might expect.

There is one more way through which you can print out both string variables and numeric variables, all at the same time, without the need for ‘+’ signs or conversion. This way is called String Formatting. To create a formatted string, we follow a simple process, as shown here:

print(f“ This is where {var 1} will be. Then {var 2}, then {var 3} and so on”)

Var 1, 2, and 3 are variables. You can have as many as you like here. Notice the importance of whitespace. Try not to use the spacebar as much. You might struggle at the start but will eventually get the hang of it.

When we start the string, we place the character ‘f’ to let Python know that this is a formatted string. Here, the curly brackets are performing a part of placeholders. Within these curly brackets, you can recall your variables. One set of curly brackets will be a placeholder for each variable that you would like to call upon. To put this in practical terms, let’s look at an example:

show = "GOT"

name1 = "Daenerys"

name2 = "Jon"

name3 = "Tyrion"

seasons = 8

print(f"The show called {show} had characters like {name1}, {name2} and {name3} in all {seasons} seasons. ")

Output:

The show called GOT had characters like Daenerys, Jon, and Tyrion in all 8 seasons.

Chapter 5 How to Read Errors and Troubleshooting Your Code

These codes are great because they will save you a lot of time and will make your code look nicer because you can reuse parts of your code without tiring yourself out by having to rewrite it so many times. This is something that you can do with object-oriented programming, or OOP, languages, a category which Python is a part of. You can work with inheritances so you can use a parent code and then make some adjustments to the parts of the code that you want and make the code unique. As a beginner, you will find that these inheritances can be quite easy to work with because you can get the code to work the way you want it to work without having to write it out a million times over.   

To help you keep things simple and to understand how inheritances work a little better, an inheritance is when you will take a ‘parent’ code and copy it down into a ‘child’ code. You will then be able to work on the child code and make some adjustments without having to make any changes in the parent part of the code. You can do this one time and stop there, or you can keep on going down the line and change the child code at each level without making any changes to the parent code.  

Working with inheritances can be a fun part of making your own code, and you can make it look so much nicer without all that mess. 

How to override the base class 

The next thing that we can work on when it comes to inheritance codes is how to override a base class. There will be a lot of times that while you are working on a derived class, you have to go in and override what you have placed inside a base class. What this means is that you will take a look at what was placed inside the base class and then make changes to alter some of the behavior that was programmed inside of it. This helps to bring in new behavior which will then be available inside the child class that you plan to create from that base class.  

This does sound a little bit complicated to work with, but it can really be useful because you can choose and pick the parental features that you would like to place inside the derived class, which ones you would like to keep around, and which ones you no longer want to use. This whole process will make it easier for you to make some changes to the new class and keep the original parts from your base class that might help you out later. It is a simple process that you can use to make some changes in the code and get rid of parts of the base class that is no longer working and replaces them with something that will work better.   

Overloading

Another process that you may want to consider when you’re working with inheritances is learning how to ‘overload.’ When you work on the process known as overloading, you can take one of the identifiers that you are working with and then use that to define at least two methods, if not more. For the most part, there will only be two methods that are inside of each class, but sometimes this number will be higher. The two methods should be inside the exact same class, but they need to have different parameters so that they can be kept separate in this process. You will find that it is a good idea to use this method when you want the two matched methods to do the same tasks, but you would like them to do that task while having different parameters.  

This is not something that is common to work with, and as a beginner, you will have very little need to use this since many experts don’t actually use it either. But it is still something that you may want to spend your time learning about just in case you do need to use it inside of your code. There are some extra modules available for you that you can download so you can make sure that overloading will work for you.  

Final Notes about Inheritances 

As you are working on your codes, you will find that it is possible that you could work on more than one inheritance code. If you are doing this, it means that you can make a line of inheritances that are similar to each other, but you can also make some changes to them as well if needed. You will notice that multiple inheritances are not all that different from what you did with a normal inheritance. Instead, you are just adding more steps and continuously repeating yourself so you can make the changes that you want.   

When you want to work with multiple inheritances, you have to take one class and then give it two or more parent classes to get it started. This is important once you are ready to write your own code, but you can also use the inheritances to make sure the code looks nice as you write it out.  

Now, as a beginner, you may be worried that working with these multiple inheritances might be difficult because it sounds too complicated. When you are working with these types of inheritances, you will create a new class, which we will call Class3, and you will find that this class was created from the features that were inside of Class2. Then you can go back a bit further and will find that Class2 was created with the features that come from Class1 and so on and so forth. Each layer will contain features from the class that was ahead of it, and you can really go down as far as you would like. You can have ten of these classes if you would like, with features from the past parent class in each one, as long as it works inside of your code.  

One of the things that you should remember when you’re creating new code and if you are considering to add in some multiple inheritances is that the Python language will not allow you to create a circular inheritance. You can add in as many parent classes as you want, but you are not allowed to go into the code and make the parent class go in a circle, or the program will get mad at you if you do so. Expanding out the example that we did above to make another class or more is fine, but you must make sure that you are copying the codes out properly before you even make changes so you can get this program to work.  

As you start to write out some more codes using the Python programming language, you will find that working with different types of inheritances is actually pretty popular. There are many times when you can just stick with the same block of code in the program and then make some changes without having to waste your time and tire yourself out by rewriting the code over and over again. 

Chapter 6 Variables

Creating a Variable

It is very easy to create a variable in Python. The assignment operator “=” is used for this purpose. The value to the left of the assignment operator is the variable identifier or name of the variable. The value to the right of the operator is the value assigned to the variable. Take a look at the following code snippet. 

Name = ‘Mike’ # A string variable 

Age = 15 # An integer variable 

Score = 102.5 # A floating type variable 

Pass = True # A Boolean variable

In the script above we created four different types of variables. You can see that we did not specify the type of variable with the variable name. For instance we did not write “string Name” or “int Age”. We only wrote the variable name. This is because Python is a loosely typed language. Depending upon the value being stored in a variable, Python assigns type to the variable at runtime. For instance when Python interpreter interprets the line “Age = 15”, it checks the type of the value which is integer in this case. Hence, Python understands that Age is an integer type variable. 

To check type of a variable, pass the variable name to “type” function as shown below: type( Age) 

You will see that the above script, when run, prints “int” in the output which is basically the type of Age variables

Python allows multiple assignment which means that you can assign one value to multiple variables at the same time. Take a look at the following script: 

Age = Number = Point = 20 #Multiple Assignment 

print (Age)

print (Number)

print (Point)

In the script above, integer 20 is assigned to three variables: Age, Number and Point. If you print the value of these three variables, you will see 20 thrice in the output. 

For any programming language, the basic part is to store the data in memory and process it. No matter what kind of operation we are going to perform, we must have the object of operation. It is difficult for a skillful woman to cook without rice. In Python language, constants and variables are the main ones. In fact, both of them are identification codes used by program designers to access data contents in memory.

The biggest difference between the two is that the contents of variables will change with the execution of the program, while the contents of constants are fixed forever. In the process of program execution, it is often necessary to store or use some data. For example, if you want to write a program to calculate the mid-term exam results, you must first input the students' results, and then output the total score, average score and ranking after calculation. This part describes how to store and access this data. 

Variable Naming and Assignment 

In a program, program statements or instructions tell the computer which Data to access and execute step by step according to the instructions in the program statements. These data may be words or numbers. What we call variable is the most basic role in a programming language, that is, a named memory unit allocated by the compiler in programming to store changeable data contents. The computer will store it in "memory" and take it out for use when necessary. In order to facilitate identification, it must be given a name. We call such an object "variable." For example:

> > firstsample = 3 

> > > second sample = 5 

> > > result = firstsample + secondsample 

In the above program statement, firstsample, secondsample, result are variables, and number 3 is the variable value of firstsample. Since the capacity of memory is limited, in order to avoid wasting memory space, each variable will allocate memory space of different sizes according to requirements, so "Data Type" is used to regulate it. 

Variable Declaration and Assignment 

Python is an object-oriented language, all data are regarded as objects, and the method of an Object reference is also used in variable processing. The type of variable is determined when the initial value is given, so there is no need to declare the data type in advance. The value of a variable is assigned with "=" and beginners easily confuse the function of the assignment operator (=) with the function of "equal" in mathematics. In programming languages, the "=" sign is mainly used for assignment. 

The syntax for declaring a variable is as follows: 

variable name = variable value 

e.g. number = 10. 

The above expression indicates that the value 10 is assigned to the variable number. In short, in Python language, the data type does not need to be declared in advance when using a variable, which is different from that in C language, which must be declared in advance before using a variable. Python interpretation and operation system will automatically determine the data type of the variable according to the value of the variable given or set. For example, the data type of the above variable number is an integer. If the content of the variable is a string, the data type of the variable is a string. 

Variable Naming Rules

For an excellent programmer, readability of program code is very important. Although variable names can be defined by themselves as long as they conform to Python's regulations, when there are more and more variables, simply taking variables with letter names such as abc will confuse people and greatly reduce readability. Considering the readability of the program, it is best to name it according to the functions and meanings given by variables. For example, the variable that stores height is named "Height" and the variable that stores weight is named "Weight." Especially when the program scale is larger, meaningful variable names will become more important. For example, when declaring variables, in order to make the program readable, it is generally used to start with lowercase letters, such as score, salary, etc. In Python, variable names also need to conform to certain rules. If inappropriate names are used, errors may occur during program execution. Python is a case-sensitive language. In other words, number and Number are two different variables. Variable names are not limited in length. Variable names have the following limitations: the first character of a variable name must be an English letter, underlined "_" and cannot be a number. Subsequent characters can match other upper- and lower-case English letters, numbers, underlined "_,” and no space character is allowed. You cannot use Python's built-in reserved words (or keywords). Although Python version 3. X supports foreign language variable names; it is recommended that you try not to use words to name variables. On the one hand, it is more troublesome to switch input methods when inputting program code. On the other hand, the reading of program code will not be smooth. The so-called reserved word usually has special meaning and function, so it will be reserved in advance and cannot be used as a variable name or any other identifier name. 

The following is an example of a valid variable name: pageresponse 

fileName4563

level

Number_

dstance

The following is an example of an invalid variable name: 

2_sample

for

$ levelone

The user name learning classroom uses the help () function to query Python reserved word. The help () function is Python's built-in function. If you are not sure about the method and property usage of a specific object, you can use the help () function to query. 

The Python reserved words mentioned above can be viewed by using the help () function. As long as "help ()" is executed, the help interactive mode will be entered. In this mode, the instructions to be queried will be input, and the relevant instructions will be displayed. 

We can continue to input the instructions we want to query in help mode. When we want to exit help interactive mode, we can input Q or quit. You can also take parameters when entering the help () command, such as help (" keywords "), Python will directly display help or description the information without entering help interactive mode.

Although Python uses dynamic data types, it is very strict in data processing, and its data type is "strong type." For example: 

> > > firstsample = 5 

> > > secondsample = "45" 

> > > print (firstsample + secondsample) # 

shows that TypeError variable firstsample is of numeric type and variable secondsample is of string type. 

Some programming languages will convert the type unconsciously and automatically convert the value A to the string type, so firstsample + secondsample will get 545. Python language prohibits different data types from operating, so executing the above statement obviously Indicates information about the wrong type. 

There is a difference between "strongly typed" and "weakly typed" in the data types of strong and weak type programming languages in small classrooms. One of the trade-offs is the safety of data type conversion. The strong type has a strict inspection for data type conversion. 

Different types of operations must be explicitly converted, and programs will not automatically convert. For example, Python and Ruby prefer strong types. 

However, most weak type programming languages adopt Implicit Conversion. If you don't pay attention to it, unexpected type conversion will occur, which will lead to wrong execution results.

JavaScript is a weak type of programming language. 

Static Type and Dynamic Type 

When Python is executed, the way to determine the data type belongs to "dynamic type." 

What is the dynamic type? 

The data types of programming languages can be divided into "Statically-Typed" and "Dynamically-Typed" according to the type checking method.

1.​ Static types are compiled with the type checked first, so the variables must be explicitly declared before they are used. The types of variables cannot be arbitrarily changed during execution. Java and C are such programming languages. For example, the following C language program statement declares that the variable number is of int integer type, and the initial value of the variable is set to 10. When we assign "apple" to number again, an error will occur, because "apple" is a string, and compilation will fail due to type discrepancy during compilation. 

int firstsample = 10 

firstsample = "apple"

#Error:

Types do not match 

2.​ Dynamic types are compiled without prior type checking, and data types are determined according to variable values during execution. Therefore, there is no need to declare types before variables are used. The same variable can also be given different types of values, and Python is a dynamic type. For example, the following program statement declares the variable number and sets the initial value to the integer 10. When we assign the string apple to number, the type will be automatically converted. 

firstsample = 10

firstsample = "love"

Print (firstsample)

# output string love 

Python has a Garbage Collection mechanism. When the object is no longer in use, the interpreter will automatically recycle and free up memory space. In the above example, when the integer object number is reassigned to another string object, the original integer object will be deleted by the interpreter. If the object is determined not to be used, we can also delete it by using the "del" command with the following syntax: del object name 

For example:

> > number = "apple”

> > > print( number) # output apple 

> > > del number # deletes string object number 

> > > print( number) #Error: number does not define the execution result. 

Since the variable number has been deleted, if the number variable is used again, an undefined error message for the variable will appear.

Chapter 7 Lists

In Python it is possible to define a list, to which a name can be attributed, inserting elements in square brackets ("[..]"). Those who already work with other languages for programming or development will certainly know arrays, or "vectors", which are variables intended to contain further variables; syntactically and conceptually the lists can remember arrays, but their functioning has some peculiarities that make them different.

Basically a list can exist but be empty, that is, not present any element inside it:

# Example of empty list

list_name = []

If a list is not empty, it will be necessary to separate the elements that compose it by a comma. It is therefore possible to define lists that contain elements associated with a single type of data:

# Example of a list containing only numeric values

list_name = [15, 25, 35, 45, 55]

# Example of a list containing only strings

list_name = ['Homer', 'Bart', 'Lisa']

Just as you can create lists that present elements of different nature:

# Example of list containing elements of different types

# numbers and strings

list_name = [65, 'Homer', 7.3]

Finally, the creation of nested lists is also allowed, i.e. lists that have other lists among their elements.

# Example of nested list

list_name = ['Homer', 3.7, 10, [29, 39, 49]].

Automatic generation of lists of integers

range () is a native Python function (or more properly an "immutable sequence type") designed to automatically generate a list based on a range of values or a numeric value passed as an argument; it is particularly useful when you need to define lists made up of a large number of numerical elements.

In the case of a parameter expressed as an interval, we will have an instruction like the following:

# Using range () to generate

# a list based on an interval

>>> range (1.8)

will lead to the generation of a list consisting of 7 elements:

[1, 2, 3, 4, 5, 6, 7]

These elements will be the result of the call to the range () function which will evaluate the two arguments of the range by returning a list containing all the integer values starting from the first, included in the list, up to the second, excluded from the list instead.

The two arguments of the interval may be followed by a third argument called step; it specifies the interval between successive values, which is why if, for example, you want to obtain a list made up of only the odd numbers covered between "1" and "8" you could operate in this way:

# Using range () to generate

# a list based on an interval

# with steps equal to 2

>>> range (1,8,2)

# list generated

# [1, 3, 5, 7]

When, on the other hand, we pass the function an integer as in the example below:

# Using range () to generate

# a list based on an integer

>>> range (5)

you will get a list populated like this:

[0, 1, 2, 3, 4]

The elements present will therefore be 8, placing the "0" as an element and (not) initial value.

Indexing of the elements of a list 

By default and lists in Python, internal elements are indexed numerically; indexing will start from "0", so a list consisting of three elements will have "0", "1" and "2" as indexes. It follows that a specific element of a list can be called up via its index, as in the following example: 

# Access to an element of a list 

# through its index 

# definition of the elements in the list 

>>> list_name = ['a', 'b', 'c', 'd', 'e'] 

# access to element with index "3" 

>>> list_name [3]

In this case, the element called will be "d", ie the fourth inserted in the list, this is because "a" is associated with the index "0", "b" to "1", "c" to "2" and di consequence "d" has as index "3".

Access to the elements in the list could also take place through negative indexing, where the last element will have the index "-1", the penultimate "-2" and so on. A call like the following will therefore have the result of allowing access to the "a" element.

# Access to an element of a list 

# through the negative index 

# definition of the elements in the list

>>> list_name = ['a', 'b', 'c', 'd', 'e'] 

# access to element with index "-5" 

>>> list_name [-5]

It is also possible to access the elements of a list on the basis of a range of values; be careful that the two components of the range will correspond to the index numbers, which is why an expression like this: 

# Access to multiple elements of a list 

# through an interval 

# definition of the elements in the list 

>>> list_name = ['a', 'b', 'c', 'd', 'e'] 

# access to elements with interval "0: 2" 

>>> list_name [0: 2] 

will allow access to the elements "a", "b", ie those whose index goes from "0" to "2" (excluded). The colon symbol (":"), used for the definition of the interval, is called slicing operator. It can also be used for other purposes, such as defining the index from which to start for data access: 

# Access to multiple elements of a list 

# starting from a specific index 

# definition of the elements in the list 

>>> list_name = ['a', 'b', 'c', 'd', 'e'] 

# access to the first element in the list ('a') via negative index 

# the last 4 elements will be excluded 

>>> list_name [: - 4] 

# access from the third element to the last 

# 'c', 'd' and 'e' 

>>> list_name [2:]

# access to all items in the list 

>>> list_name [:]

Python has constructs that allow you to perform more advanced operations than simply accessing values, such as those dedicated to manipulating lists.

Chapter 8 Dictionaries

We will cover a new data type which facilitates a flexible way to organize data. Using the knowledge about lists, soon you will be able to create data structures that will be useful in almost any application you may think of.

A dictionary can store many values just like a list. However, they can index different data types. Keys of a dictionary are associated with values. When combined, that is called the key-value pair. Let’s start by creating a new dictionary variable.

1.​ flat = {'rooms': '2', 'bathrooms': '1', 'floor': '3rd', 'apartment': '306'} # Note the curly braces  

2.​ print(f"My Apartment has {flat['rooms']} rooms, {flat['bathrooms']} bathroom")  

Program output:

C:\Users\...\PycharmProjects\GettingStarted\venv\Scripts\Python.exe C:/Users/…/PycharmProjects/GettingStarted/Start.py

My Apartment has 2 rooms, 1 bathroom

Process finished with exit code 0

Dictionaries, unlike lists, can be identified by other data types that are not necessarily integers, although it can use integers as keys as well.

Dictionaries vs. lists

The order of list items does matter when trying to compare them to other lists. Meanwhile, dictionaries can find if a list that already exists, even if the keys are out of order. This does not mean that the order is not important. If a coder maintains a uniform order in their lists, then this is not an issue. However, the main problem appears once you start getting unordered data, especially from users. 

Try this following sequence in the editor.

1.​ flat = ['rooms', 'bathrooms', 'floor', 'apartment']  

2.​ apartment = ['apartment', 'bathrooms', 'rooms', 'floor']  

3.​ print(flat == apartment) # When you use == you are asking if they are equal to 

each other  

4.​ flat = {'rooms': '2', 'bathrooms': '1', 'floor': '3rd', 'apartment': '306'} # Note the curly braces  

5.​ apartment = {'apartment': '306', 'bathrooms': '1', 'rooms': '2', 'floor': '3rd'}  

6.​ print(flat == apartment)  

Program output:

C:\Users\...\PycharmProjects\GettingStarted\venv\Scripts\Python.exe C:/..

False

True

Process finished with exit code 0

Useful methods

There are a few useful methods that you can use with dictionaries. These methods are particularly useful when combined with loops. All of the following methods need to be used by adding a dot notation after the name of the variable followed by a parenthesis. 

The first method is the keys(), which will output the keys to a dictionary. The next method is the value(), which will output the values of keys. The last method is the items() which will output both the keys and values between parenthesis and separated by a comma. 

Try out the example below.

1.​ flat = {'rooms': '2', 'bathrooms': '1', 'floor': '3rd', 'apartment': '306'}  

2.​ print(flat.keys())  

3.​ print(flat.values())  

4.​ print(flat.items())  

Program output:

C:\Users\...\PycharmProjects\GettingStarted\venv\Scripts\Python.exe C:/Users/…/PycharmProjects/GettingStarted/MyFirstProgram.py

dict_keys(['rooms', 'bathrooms', 'floor', 'apartment'])

dict_values(['2', '1', '3rd', '306'])

dict_items([('rooms', '2'), ('bathrooms', '1'), ('floor', '3rd'), ('apartment', '306')])

Process finished with exit code 0

Value or key check

While using a dictionary, one of the functions that will most likely be needed regularly is to check for a certain value in your dictionary. For this exercise, we will be using two operators; the ‘in’ and the ‘not’ operators. These two operators can tell you if a certain key or value in a dictionary exists. Note that these operators can also be used in lists as well as logic. These operators will come out with a Boolean output either ‘True’ or ‘False’. 

Here are some lines of codes to try out.

1.​ flat = {'rooms': 2, 'bathrooms': 1, 'floor': '3rd', 'apartment': 306}  

2.​ print('rooms' in flat.keys()) # Determining if there is a key called rooms  

3.​ print('1st' in flat.values()) # Determining if there is a value called 1st  

4.​ print(3 not in flat.items())  #Determining if there is neither a value nor key of 3  

Program output:

C:\Users\...\PycharmProjects\GettingStarted\venv\Scripts\Python.exe C:/Users/…/PycharmProjects/GettingStarted/MyFirstProgram.py

True

False

True

Process finished with exit code 0

There is another method that can be used with dictionaries, and it makes it easy to fetch a specific piece of data. This is called the get() method. 

Check out the example below, to see how it is used inside the editor.

1.​ flat = {'rooms': 2, 'bathrooms': 1, 'floor': '3rd', 'apartment': 306}  

2.​ print(f"I live in the apartment {flat.get('apartment')}") #getting the apartment number

Program Output:

C:\Users\...\PycharmProjects\GettingStarted\venv\Scripts\Python.exe C:/Users/…/PycharmProjects/GettingStarted/MyFirstProgram.py

I live in the apartment 306

Chapter 9 Functions

Another cornerstone of programming are the functions. Unlike the built-in ones that are ready to go once you’ve started, user-defined functions open up unlimited possibilities. Using functions helps programmers abstract their code and simplify modifications in the future. Think of it as a container which is labeled and will only run once you call it, making it perfect for event-driven programming. In this part, we are going to take a closer look at how to create, alter, and place functions to get the most out of your programs.

Definition Statement and Function Calls

There is a distinct method to define a function. The syntax of that is in the code that follows. In this hypothetical example, we will be creating a function that will square a given number.

1.​ def greetUser():  # Definition statement starts with def which is reserved, followed by the function name.  

2. ​ purpose = input('State your purpose: ')  # First line of the code block.  

3. ​ print(purpose)  # Second line of the code block.  

4.​ #For good code writing practices, you should add two empty lines (breaks) after your function bloc.  

5.​ print('You have reached the umbrella corporation website') # This is the first thing that will run in the program.  

6.​ greetUser()  # The function will only run after you call it like that (name of the function followed by parenthesis). 

Program output:

C:\Users\...\PycharmProjects\GettingStarted\venv\Scripts\Python.exe C:/Users/ …/PycharmProjects/GettingStarted/MyFirstProgram.py

You have reached the umbrella corporation website

State your purpose: I'm looking for Alice...

I'm looking for Alice...

Process finished with exit code 0

As explained, programs will run in a sequence of lines so that line one will be followed by line two, and so on. For that same reason, a function needs to be defined before calling it. If you try and call a function ahead of time, your IDE will prompt you with an error. 

Parameters

Now let’s explore how to add parameters to our functions. In many cases, we need to take information from the user or elsewhere and use it inside of a function. This technique is used by all programmers, regardless of what kind of program they are creating. Follow the instructions below to see how it works.

1.​ def greetUser(userName):  # This is the parameter that we pass when the function is called on lines 7 and 8.  

2.​ purpose = input('State your purpose: ')  

3.​ print(f'Hello {userName.title()}, are these your intentions: "{purpose}" ?')  

# Here we are using the parameter.  

# We are also using the title method, to avoid any user error.  

4.​   

5.​   

6.​ print('You have reached the umbrella corporation website')  # This is the first thing that will run in the program.  

7.​ greetUser("rEbEcEa")  # Once you have added a parameter you need to supply a value while calling the function.  

8.​ greetUser("dr. Green")  # Each time you call a function, the new parameter is 

passed.  

Program output:

C:\Users\...\PycharmProjects\GettingStarted\venv\Scripts\Python.exe C:/Users/…/PycharmProjects/GettingStarted/MyFirstProgram.py

You have reached the umbrella corporation website

State your purpose: I'm looking for Alice

Hello Rebecea, are these your intentions: "I'm looking for Alice”?

State your purpose: Create a virus!

Hello Dr. Green, are these your intentions: "Create a virus!”?

Process finished with exit code 0

Keyword Arguments

In most cases, you may be passing more than one parameter into your program. In cases like these you need to pass the value of these parameters with respect to how they were defined in the function. Let’s see an example.

1.​ def greetUser(firstName, lastName):  

2.​ purpose = input('State your purpose: ')  

3.​ print(f'Hello {firstName.title()} {lastName.title()}, are these your intentions: "{purpose}" ?')  

4.​   

5.​   

6.​ print('You have reached the umbrella corporation website')  

7.​ greetUser("rebecca", "chambers")  # In this function call we have the first name as the first parameter.  

8.​ greetUser('chambers', 'rebecca')  # In this function call we have the last name as the first parameter  

Program output:

C:\Users\...\PycharmProjects\GettingStarted\venv\Scripts\Python.exe C:/Users/…/PycharmProjects/GettingStarted/MyFirstProgram.py

You have reached the umbrella corporation website

State your purpose: Rescue Alice

Hello Rebecca Chambers, are these your intentions: "Rescue Alice”?

State your purpose: Rescue Alice

Hello Chambers Rebecca, are these your intentions: "Rescue Alice”?

Process finished with exit code 0

In rare cases, a programmer will need to pass parameters out of order. Although this is not always recommended, there are cases where it is necessary. To do that, all you have to do is add the parameter name while calling the function. Let’s take a look at the next example.

1.​ def greetUser(firstName, lastName):  

2.​ purpose = input('State your purpose: ')  

3.​ print(f'Hello {firstName.title()} {lastName.title()}, are these your intentions: "{purpose}" ?')  

4.​   

5.​   

6.​ print('You have reached the umbrella corporation website')  

7.​ greetUser("rebecca", "chambers")  # In this function call, we have the first name as the first parameter.  

8.​ greetUser('chambers', 'rebecca')  # In this function call, we have the last name as the first parameter  

9.​ greetUser(lastName = 'chambers', firstName='Rebecca') # We swapped the order and still were able to pass the   

parameters as desired.   

Program output:

C:\Users\...\PycharmProjects\GettingStarted\venv\Scripts\Python.exe C:/Users/…/PycharmProjects/GettingStarted/MyFirstProgram.py

You have reached the umbrella corporation website

State your purpose: Saving Alice

Hello Rebecca Chambers, are these your intentions: "Saving Alice" ?

State your purpose: Saving Alice

Hello Chambers Rebecca, are these your intentions: "Saving Alice" ?

State your purpose: Saving Alice

Hello Rebecca Chambers, are these your intentions: "Saving Alice" ?

Process finished with exit code 0

Return Values

There are many cases where you will take a piece of information from the user, run a function and need to return that value to the user again. It is very simply done by writing ‘return’ in front of the variables you wish to return. In this next example, we are going to create a very simple function that will calculate the square of any number and return the value to the user.

1.​ def squareNum(numA):  # Parameter  

2.​ return numA *numA  # Add the return at the beginning or else, by default, it will return none.  

3.​   

4.​ print(squareNum(3))  # Note that the function was called as an argument and it can also be saved into a variable if necessary.   

Program output:

C:\Users\...\PycharmProjects\GettingStarted\venv\Scripts\Python.exe C:/Users/…/PycharmProjects/GettingStarted/MyFirstProgram.py

9

Process finished with exit code 0

Chapter 10                   User’s Input and Loop

Python programming, like all other types of coding, is intended to solve the problems that end users face. To do that, you need to get additional information from the end user. For example, if someone needs to check if he is eligible to play on the basketball team or if he is qualified to vote in the elections, you can create a program that can give him the correct answer he needs.

In this type of program, we need to know the age of the user before we give an answer, which means that we have to build an interface that asks for an answer from the user regarding his or his age. The user will enter his or her age into the program using the input () method. Once he or she reaches age, they can know the answer.

The input () method

The input () method is actually a stop for Python programs because it waits for the user to fill in the program with some text. Once the Python program has received the user's input, it can store the same in some kind mostof variable that you create yourself. This makes programming and operation easy. I have created a program that repeats the information you enter in the shell prompt. It is interesting. Let's check it out.

message = input ("This program repeats everything you write. Just like a parrot:")

print (message)

= RESTART: C: / Users / saifia-computers / Desktop / Python.py

This program repeats everything you write. Like a parrot: Terminator has been destroyed.

Terminator has been destroyed.

>>> Sam

Retrace (most recent call last)

File "<pyshell # 136>", line 1, in <module>

Sam

NameError: name 'Sam' is not defined

>>>

= RESTART: C: / Users / saifia-computers / Desktop / Python.py

>>>

This program repeats everything you write. Just like a parrot: I have been selected for the basketball team.

I have been selected on the basketball team.

>>>

You can see that the program returns whatever you say to it. The second attempt gave an error because I did not run the program again. This means that you have to run the program from the beginning every time you want to run it.

The program took an argument from the user. It was a kind of instruction that the adhering program used exactly the same wording as the user entered. The prompt asks users to enter the information they want to display in the shell. When the user presses enter, he executes the instructions.

You should write a clean code to make it easier for users to understand and act on the instructions. The prompt should be clear and easy to follow so that the user knows what to do. Let's write another program with the input () method.

qualification = input ("Enter your name and educational qualification:")

print ("Your information:" + qualification + "!")

= RESTART: C: / Users / saifia-computers / Desktop / Python.py

Enter your name and teaching qualification: John, MA (English literature)

Your data: John, MA (English literature)!

>>>

If you want to write a longer code that spans multiple lines, you can do that with the input () function in Python. For example, if you want to let the user know why you need a certain type of information, you can add an extra line in the code. This code is longer than one line. This is useful because users cannot easily enter the program with their personal information if you do not tell them why you need a piece of information in the first place. To achieve this goal, you can add the prompt within a variable and then pass the variable to the input () function.

prompt = "We need your information to provide you with a custom job search."

prompt + = "\ nEnter your name and educational qualification:"

qualification = input (prompt)

print ("Your information:" + qualification + "!")

= RESTART: C: / Users / saifia-computers / Desktop / Python.py

We need your data to let you search for a tailor-made job.

Enter your name and teaching qualification: Mazhar, MSc (Computer Science)

Your data: Mazhar, MSc (Computer Science)!

>>>

Let's dig deeper into how the input () function works. When entering information in the input () function, Python interprets it as a string. Let's see how to enter numeric numbers. For example, you require the age of the user to put in the record so you can do that with the following method.

user_age = input ("what is your legal age?")

= RESTART: C: / Users / saifia-computers / Desktop / Python.py

>>>

what is your legal age? 23

>>> user_age

'23'

>>>

= RESTART: C: / Users / saifia-computers / Desktop / Python.py

what is your legal age? 54

>>> user_age

'54'

>>>

The user's age information has been successfully stored in the variable called user_age. When we ask Python to return the number, it returns in quotes, meaning it is interpreted as a string. If you want to use the same as a number, an error is displayed.

= RESTART: C: / Users / saifia-computers / Desktop / Python.py

what is your legal age? 25

>>> user_age> = 25

Retrace (most recent call last)

File "<pyshell # 143>", line 1, in <module>

user_age> = 25

TypeError: '> =' not supported between instances of 'str' and 'int'

>>>

Python displays an error because it cannot compare a string to an integer. This problem can be solved if you use the int () function in your code. It teaches Python how to treat an input as a numeric value. It converts a string representation of a given number into a numeric representation. You can tell Python to interpret a number as it is and to perform the math function you want. You can run a conditional test by Python to see if your age is greater than or equal to 25 or not.

user_age = input ("what is your legal age?")

user_age = int (user_age)

if user_age> = 25:

print ("\ nYou are legally entitled to vote!")

different:

print ("\ nYou are not eligible to vote. Return to your home.")

= RESTART: C: / Users / saifia-computers / Desktop / Python.py

what is your legal age? 20

You are not eligible to vote. Please go back to your house.

>>>

= RESTART: C: / Users / saifia-computers / Desktop / Python.py

>>>

what is your legal age? 25

You are legally eligible to vote!

>>>

= RESTART: C: / Users / saifia-computers / Desktop / Python.py

what is your legal age? 24

You are not eligible to vote. Please go back to your house.

>>>

= RESTART: C: / Users / saifia-computers / Desktop / Python.py

what is your legal age? 30

You are legally eligible to vote!

>>>

You can see in the examples above that Python is fully competent in recognizing the numbers. It calculated perfectly and answered my questions when I entered different numbers in the program.

The While Loop

A while loop can be used to count numbers and perform various other tasks efficiently.

my_num = 1

while my_num <= 10:

print (my_num)

my_num + = 1

= RESTART: C: / Users / saifia-computers / Desktop / Python.py

1

2

3

4

5

6

7

8

9

10

>>>

The while loop requires that all variables in the code remain ready. The Python while loop has a break statement that helps us stop the statement at whatever point we want the loop to stop. We need to add the true element which means that the loop will continue as long as the condition is true.

a = 1

while a <10:

print (a)

if a == 5:

break

a + = 1

= RESTART: C: / Users / saifia-computers / Desktop / Python.py

1

2

3

4

5

>>>

While loop is very interesting. I'll write the program that repeated what I said to it and then put it in the while loop. The while loop will keep the program running unless you press the keyword that I will put in the program. Let's see.

prompt = "\ nMy creator made me repeat what you say:"

prompt + = "\ nI will continue unless you enter 'stop' to terminate the program."

a = ""

while a! = 'stop':

a = input (prompt)

print (a)

= RESTART: C: / Users / saifia-computers / Desktop / Python.py

My creator made sure to repeat everything you say:

I will continue unless you enter 'stop' to terminate the program. I feel dizzy.

I feel dizzy.

My creator made sure to repeat everything you say:

I will continue unless you enter 'stop' to terminate the program. Are you dizzy

Are you dizzy

My creator made sure to repeat everything you say:

I will continue unless you enter 'stop' to terminate the program. How did you learn Python?

How did you learn Python?

My creator made sure to repeat everything you say:

I will continue unless you enter 'stop' to terminate the program. You repeat so well.

You repeat so well.

My creator made sure to repeat everything you say:

I will continue unless you enter 'stop' to terminate the program. You are like a parrot.

You are like a parrot.

My creator made sure to repeat everything you say:

I will continue unless you enter 'stop' to terminate the program. stop

stop

>>> Can you repeat it now?

SyntaxError: invalid syntax

>>>

You can see that after I quit, the program no longer accepts and repeats my text. This way you can get rid of the while loop. If the thought goes around in your mind that or you can use a different value instead of quitting, I'll make it easier for you to understand the following example. I will use the same program, but a different value to end the program.

prompt = "\ nMy creator made me repeat what you say:"

prompt + = "\ nI will continue unless you enter 'stop it' to terminate the program:"

a = ""

while a! = 'stop it':

a = input (prompt)

print (a)

= RESTART: C: / Users / saifia-computers / Desktop / Python.py

My creator made sure to repeat everything you say:

I will continue unless you enter 'quit' to end the program: I want to reach the top of Mount Everest.

I want to reach the top of Mount Everest.

My creator made sure to repeat everything you say:

I will continue unless you enter 'quit' to end the program: quit it

stop

>>>

The prompt in a while loop defines what action a user should take. It tells him that there are generally two options: write what he or she wants to repeat or exit the program. Python ran the while loop and repeated multiple statements that I entered into the program. When I wanted to end the program, I managed to do it by entering the keyword I set to separate from the while loop.

There is still a problem. Python takes the keyword, stop it, as a message. It ends the loop, but also displays the same text. The rest of the code is retained, but there will be a small change to note.

prompt = "\ nMy creator made me repeat what you say:"

prompt + = "\ nI will continue unless you enter 'stop it' to terminate the program:"

a = ""

while a! = 'stop it':

a = input (prompt)

if a! = 'stop it':

print (a)

= RESTART: C: / Users / saifia-computers / Desktop / Python.py

My creator made sure to repeat everything you say:

I will continue unless you enter 'quit' to end the program: I want to reach the top of Mount Everest.

I want to reach the top of Mount Everest.

My creator made sure to repeat everything you say:

I will continue unless you enter 'quit' to end the program: quit it

>>>

(Matthes, 2016)

Chapter 11                   Tuples

A tuple is a sequence type that contains an ordered collection of objects. A tuple, unlike a list, is immutable; you won’t be able to change its elements once it is created. A tuple can hold items of different types and can have as many elements as you want subject to availability of memory.

Besides being immutable, you can tell a tuple apart from a list by the use of parentheses instead of square brackets. The use of parentheses, however, is optional. You can create a tuple without them. A tuple can store items of different types as well as contain any number of objects.

How to Create a Tuple

To create a tuple, you can place the items within parentheses and separate them with a comma.

Example of a numeric tuple

mytuple_x = (10, 9, 8, 7, 6, 5, 4, 3, 2, 1)     

Example of a mixed-type tuple

mytuple_y = ("soprano", 10, 4.3)     

Example of a string tuple           

mytuple_z = ("b", "Jon", "library")          

It’s likewise possible to create a nested tuple:

my_tuple4 = ("Python", (5, 15, 20), [2, 1, 4])

You can create a tuple with only one item but since this will look like a string, you’ll have to place a comma after the item to tell Python that it is a tuple.

my_tuple5 = ("program",)

You may also create an empty tuple:

my_tuple = ()

You can create a tuple without the parentheses:

numbers = 5, 3, 4, 0, 9

Accessing Tuple Elements

There are different ways to access items in a tuple.

Indexing

If you know how to access elements in a list through indexing, you can use the same procedure to access items in a tuple. The index operator indicates the index of the element you want to access. The first element is on index zero. Accessing an item outside the scope of the indexed elements will generate an IndexError. In addition, accessing an index with a non-integer numeric type will raise a NameError. 

To illustrate how tuples work, create my_tuple with strings as elements.

>>> my_tuple = ('p', 'r', 'o', 'g', 'r', 'a', 'm', 'm', 'e', 'r')

>>>

To access the first element on the tuple:

>>> my_tuple[0]

'p'

>>>

To access the 8th element:

>>> my_tuple[7]

'm'

>>>

To access the 6th element:

>>> my_tuple[5]

'a'

>>>

Negative Indexing

As it is a sequence type, Python allows negative indexing on tuples. The last element has -1 index, the penultimate element has -2 index, and so on.

>>> my_tuple = ('p', 'r', 'o', 'g', 'r', 'a', 'm', 'm', 'e', 'r')

>>> my_tuple[-1]

'r'

>>>my_tuple[-7]

'g'

>>>

Slicing a Tuple

If you want to access several items at the same time, you will have to use the slicing operator, the colon (:). By now, you must be very familiar with how slicing works.

To see how you can slice a range of items from a tuple, create new_tuple:

>>>new_tuple = ('i', 'm', 'm', 'u', 't', 'a', 'b', 'l', 'e')

>>>

To access the elements on the 4th to the 6th index:

>>> new_tuple[4:7]     

('t', 'a', 'b')                 

>>>

4 is the index of the first item and 7 is the index of the first item to be excluded.

To access tuple elements from index 2 to the end:

>>> new_tuple[2:]

('m', 'u', 't', 'a', 'b', 'l', 'e')

>>>

To access tuple items from the beginning to the 3rd index:

>>> new_tuple[:4]

('i', 'm', 'm', 'u')

>>>

Changing, Reassigning, and Deleting Tuples

A tuple is immutable so you cannot alter its elements. However, if it contains an element which is a mutable data type, you can actually modify this particular element. This is true in situations where one of the elements is a list. In such cases, you can modify the nested items within the list element.

>>> my_tuple = ('a', 5, 3.5, ['P', 'y', 't', 'h', 'o', 'n'])

>>>

Replacing a Tuple

To replace the item on index 2 of the list which is on index 3 of my_tuple:

>>>my_tuple[3][2] = 'x'

>>>

3 is the index of the list, 2 is the index.

>>> my_tuple                       

('a', 5, 3.5, ['P', 'y', 'x', 'h', 'o', 'n'])

>>>

While you may not replace or modify other data types, you can reassign a tuple to an entirely different set of values or elements.

Reassigning a Tuple

To reassign a tuple, you can just list a different set of elements and assign it to the tuple. To reassign new_tuple:

>>> my_tuple = ('c', 'o', 'd', 'e', 'r')

>>>

Deleting a Tuple

To delete a tuple and all the items stored in it, you will use the keyword del.

The syntax is:

del tuple_name

Hence, to delete new_tuple:

>>>del my_tuple

Tuple Membership Test

To test if a tuple contains a specific item, you can use the membership operators ‘in’ and ‘not in’

>>> our_tuple = ('p', 'r', 'o', 'g', 'r', 'a', 'm', 'm', 'e', 'r')

>>>'g'in our_tuple

True

>>>'l'in our_tuple

False

>>>'e'not in our_tuple

False

>>>'x'not in'our_tuple'

True

>>>

Python Tuple Methods

Only two Python methods work with tuples:

Count(x)

Returns the number of elements which is equal to the given element.

The syntax is:

mytuple.count(a)

Example:

>>> new_tuple = ("p", "r", "o", "g", "r", "a", "m", "m", "e", "r")

>>> new_tuple.count('m')

2

>>> new_tuple.count(‘r’)

3

>>> new_tuple.count('x')

0

>>>

Index(x)

Returns the index of the first element which is equal to the given element.

The syntax is:

mytuple.index(a)

Example:

>>> new_tuple = ("p", "r", "o", "g", "r", "a", "m", "m", "e", "r")

>>> new_tuple.index('m')

6

>>> new_tuple.index(‘r’)

1

>>> new_tuple.index('g')

3

>>>

Built-in Functions with Tuples

Several built-in functions are often used with tuple to carry out specific tasks. Here are the functions that you can use with a tuple:

Len()

Returns the number of elements on a tuple.

>>> tuple_one = ('cat', 'dog', 'lion', 'elephant', 'zebra')

>>>len(tuple_one)

5

>>>

Max()

Returns the largest element 0n a tuple.

>>> numbers_tuple = (1, 5, 7, 9, 10, 12)

>>>max(numbers_tuple)

12

>>>

When a tuple holds items of purely string data type, max() evaluates the items alphabetically and returns the last item.

>>> my_tuple = ('car', 'zebra', 'book', 'hat', 'shop', 'art')

>>>max(my_tuple)

'zebra'

>>>

Using max() on tuples with mixed data types (string  and numbers) will raise a TypeError due to the use of unorderable types.

Min()

Returns the smallest element on a tuple.

>>> numbers_tuple = (1, 5, 7, 9, 10, 12)

>>>min(numbers_tuple)

1

>>>

When used on a tuple that contains purely string data type min() evaluates the items alphabetically and returns the first item.

>>> my_tuple = ('car', 'zebra', 'book', 'hat', 'shop', 'art')

>>> min(my_tuple)

'art'

>>>

Sorted()

Returns a sorted list but does not sort the tuple itself.

>>> my_tuple = ('dog', 'bird', 'ant', 'cat', 'elephant')

>>> sorted(my_tuple)

['ant', 'bird', 'cat', 'dog', 'elephant']

>>>

The order of elements inside the my_tuple, however, remains the same:

>>> my_tuple

('dog', 'bird', 'ant', 'cat', 'elephant')

>>>

Sum()

Returns the total of all items on a tuple.

>>> my_tuple = (5, 10, 15, 20, 25, 30)

>>>sum(my_tuple)

105

>>>

Tuple()

Converts iterables like string, list, dictionary, or set to a tuple.

How to convert a string to a tuple

Example #1:

>>>tuple("Programmer")

('P', 'r', 'o', 'g', 'r', 'a', 'm', 'm', 'e', 'r')

>>>

Example #2:

>>> my_string = ("Hello World")

>>>tuple(my_string)

('H', 'e', 'l', 'l', 'o', ' ', 'W', 'o', 'r', 'l', 'd')

>>>

How to Convert a Dictionary to a Tuple

Example #1:

>>>tuple({'Name':'Joshua', 'Animal':'elephant', 'Color': 'blue', 'Age':22} )

('Age', 'Color', 'Name', 'Animal')

>>>

Example #2:

>>> my_dict = {'Name':'Jack', 'Area':'Florida', 'subscription':'premium'}

>>> tuple(my_dict)

('Name', 'Area', 'subscription')

>>>

How to Convert a List to a Tuple

Example #1:

>>>tuple(['red', 'blue', 'yellow', 'green', 'orange', 'violet'])

('red', 'blue', 'yellow', 'green', 'orange', 'violet')

>>>

Example #2:

>>> my_list = ['interest', 'rate', 'principal', 'discount', 'rollover']

>>>tuple(my_list)

('interest', 'rate', 'principal', 'discount', 'rollover')

>>>

Enumerate()

Returns an enumerate object containing the value and index of all tuple elements as  pairs.

>>> my_tuple = (1, 3, 5, 7, 9, 11, 13, 15)

>>>enumerate(my_tuple)

<enumerate object at 0x03237698>

>>>

Iterating Through a Tuple

You can iterate through each item in a tuple with the ‘for’ loop.

>>> for fruit in ('apple', 'peach', 'pineapple', 'banana', 'orange'):

print("I love " + fruit)

I love apple

I love peach

I love pineapple

I love banana

I love orange

Tuples vs. Lists

Except for the symbols used to enclose their elements and the fact that one is mutable and the other is not, tuples and lists are similar in many respects. You will likely use a tuple to hold elements which are of different data types while you will prefer a list when working on elements of similar data types.

There are good reasons to choose tuple over a list to handle your data.

The immutable nature of tuples results in faster iteration which can help improve a program’s performance.

Immutable tuple elements can be used as dictionary keys, something that is not possible with a list.

Implementing unchangeable data as a tuple will ensure that it will stay write-protected.

Chapter 12                   Control Statements

Sometimes, you may need to run certain statements based on conditions. The goal in control statements is to evaluate an expression or expressions, then determine the action to perform depending on whether the expression is TRUE or FALSE. There are numerous control statements supported in Python:

If Statement

With this statement, the body of the code is only executed if the condition is true. If false, then the statements after If block will be executed. It is a basic conditional statement in Python. 

Example:

#!/usr/bin/python3

ax = 7

bx = 13

if ax > bx:

print('ax is greater than bx')

The above code prints nothing. We defined variables ax and bx. We then compare their values to check whether ax is greater than bx. This is false, hence nothing happens. The > is “greater than” sign. Let us change it to >, this symbol means: “less than sign”.

Let see how we can write:

#!/usr/bin/python3

ax = 7

bx = 13

if ax < bx:

print('ax is greater than bx')

This prints the following:

The condition/expression was true, hence the code below the If expression is executed. Sometimes, you may need to have the program do something even if the condition is false. This can be done with an indentation in the code. 

Example:

#!/usr/bin/python3

ax = 10

if ax < 5:

print ("ax is less than 5")

print (ax)

if ax > 15:

print ("ax is greater than 15")

print (ax)

print ("No condition is True!")

In the above code, the last print() statement is at the same level as the two Ifs. This means even any of the two is true, this statement will not be executed. However, the statement will be executed if both Ifs are false. Running the program outputs this:

The last print() statement as executed as shown in the result above. 

If-Else Statement

This statement helps us specify a statement to execute in case the If expression is false. If the expression is true, the Ifblock is executed. If the expression is false, the Else block will run. The two blocks cannot run at the same time. It’s only one of that can run. It is an advanced If statement. 

Example:

#!/usr/bin/python3

ax = 10

bx = 7

if ax > 30:

print('ax is greater than 30')

else:

print('ax isnt greater than 30')

The code will give this result once executed:

The value of variable ax is 30. The expression if ax > 30: evaluates into a false. As a result, the statement below If, that is, the first print() statement isn’t executed. The else part, which is always executed when the If expression is false will be executed, that is, the print() statement below the else part. 

Suppose we had this:

#!/usr/bin/python3

ax = 10

bx = 7

if ax < 30:

print('ax is less than 30')

else:

print('ax is greater than 30')

This will give this once executed:

In the above case, the print() statement within the If block was executed. The reason is that the If expression as true. 

Another example:

#!/usr/bin/python3

ax = 35

if ax % 2 ==0:

print("It is eve")

else:

print("It is odd")

The code outputs:

The If expression was false, so the else part was executed. 

If Elif Else Statement

This statement helps us test numerous conditions. The block of statements under the elif statement that evaluates to true is executed immediately. You must begin with If statement, followed by elif statements that you need then lastly the else statement, which must only be one. 

Example:

#!/usr/bin/python3

ax = 6

bx = 9

bz = 11

if ax > bx:

print('ax is greater than bx')

elif ax < bz:

print('ax is less than bz')

else:

print('The else part ran')

The code outputs the following:

We have three variables namely ax, bx, and bz. The first expression of the If statement is to check whether ax is greater than bx, which is false. The elif expression checks whether ax is less than bx, which is true. The print() statement below this was executed. 

Suppose we had this:

#!/usr/bin/python3

ax = 6

bx = 9

bz = 11

if ax > bx:

print('ax is greater than bx')

elif ax > bz:

print('ax is less than bz')

else:

print('The else part ran')

The code will output:

In the above cases, both the If and elif expressions are false, hence the else part was executed. 

Another example:

#!/usr/bin/python3

day = "friday"

if day == "monday":

print("Day is monday")

elif day == "tuesday":

print("Day is tuesday")

elif day == "wednesday":

print("Day is wednesday")

elif day == "thursday":

print("Day is thursday")

elif day == "friday":

print("Day is friday")

elif day == "saturday":

print("Day is saturday")

elif day == "sunday":

print("Day is sunday")

else:

print("Day is unkown")

The value of day if friday. We have used multiple elif expressions to check for its value. The elif expression for friday will evaluate to true, hence its print() statement will be executed. 

Nested If

An If statement can be written inside another If statement. That is how we get nested If.

Example:

#!/usr/bin/python3

day = "holiday"

balance = 110000

if day == "holiday":

if balance > 70000:

print("Go for outing")

else:

print("Stay indoors")

else:

print("Go to work")

We have two variables day and balance. The code gives the following result:

The first if expression is true as it’s a holiday. The second if expression is also true since balance is greater than 70000. The print() statement below that expression is executed. The execution of the program stops there. Suppose the balance is less than 70000 as shown below:

#!/usr/bin/python3

day = "holiday"

balance = 50000

if day == "holiday":

if balance > 70000:

print("Go for outing")

else:

print("Stay indoors")

else:

print("Go to work")

The value of balance is 50000. The first if expression is true, but the second one is false. The nested else part is executed. We get this result from the code:

Note that the nested part will only be executed if and only if the first if expression is true. If the first if is false, then the un-nested else part will run. Example:

#!/usr/bin/python3

day = "workday"

balance = 50000

if day == "holiday":

if balance > 70000:

print("Go for outing")

else:

print("Stay indoors")

else:

print("Go to work")

The value for day is workday. The first if expression testing whether it’s a holiday is false, hence the Python interpreter will move to execute the un-nested else part and skip the entire nested part. The code gives this result:

Chapter 13                   File Management

Why Use Modules?

Modules allow us to organize the elements and components inside our codes in an easier way, providing us with a big package of variables that are auto contained. Names that are defined on a superior level in a module file automatically will become an attribute of the object of the imported module. 

Another advantage of using modules is that they let us reuse the code, using data services and linking individual files to broaden our program. 

The main reason why we think that the modules are a very useful tool when it comes to programming is that they are really helpful to organize and reuse our code. This is very important when we talk about OOP (Object-Oriented Programming) since on that mode, the modularization and reusage are very popular. Since Python is a programming language oriented for that, it comes very user-friendly. 

Imagine that you want to create an application or a program, more complicated than what we have been doing until now. For it, you are going to need one of the former codes to complement. Here is when you see the real benefit of the modules since you will be able to simply add one of the old codes to the complex application you want to do. 

In modules, we will also have modularization. It is based on dividing our codes into several tiny pieces of codes, so that, at the moment of making the sophisticated program or application, it won’t have hundreds and hundreds of lines of codes that could be annoying and hard to read. Instead, the code will be separated into tiny files. 

How Create a Module on Python

Creating a module is something straightforward that anyone can do, all that needs to be done is to create a file with the .py extension, then, that file will be stored on a folder of your preference; this is known as import. 

In case we want to create a module of our own, you will have to do the following. We will make a program on which we will create a module that could be used later. 

The module syntax is as follows:  

As you could see, the syntax is straightforward, since it is pretty much like creating a function. After we created it, we must be able to import it from another program, in order to do that, we will use the import statement. 

Import Statement

A module is able to contain definitions of a function and even statements, which can be executable. With this, it is possible to initialize a module since they execute only when our module is on the import statement. 

Modules are capable of importing other modules that is why people use to put the import type statements at the beginning of each since with the names of our imported modules, they will locate on a space named global; function that modules have for importing. 

With the help of the last example, we can manage to import the module created earlier and use the functions that we defined there. 

As you see in this example, we created the op variable, who takes the task of storing a string, which will specify the option that the users choose. Then, two variables would be initialized, a and b; they will store the value of the operators we are going to use to perform the mathematical operations. 

Afterward, the result variable will store the value that the function calculator returns, according to the operators and the type of operation that the users want. The function calculator comes from the module that we have imported. 

When the Python interpreter finds the import statement, it imports the module, as long as it is located on the full search path. The search path is nothing but a list where all the directories that Python accesses before importing any module are located. 

How to Import a Module? 

For being able to import a module, we just have to follow some instructions and steps that are performed at the moment of the execution: 

We look for the module through the module search path, compile to byte code, and lastly, we execute the byte-code of our module to build then an object that defines it. 

How can I search for a module through Search Path? 

To search for a module, our search system compounds of the concatenation of paths; these can be seen on the directory “Home” of our program. After this, the environment PYTHONPATH will be located from left to right, and that is how we will find the directory of default libraries. 

Namespaces in Modules

As you know, modules are files. Python creates a module object in which all the names that we assigned in that module-file will be contained. What does that mean? This means that namespaces are just places where all the names that later become attributes are created. 

What Are the Attributes?  

Attributes are the names that have been assigned to a value considered of a higher level on a module file, which does not belong to a function or class. 

Errors

When working with files, we will have an optional string. That string will specify the way about how we will handle the errors of coding that may arise in our program. 

Those errors can only be handled and managed on files .txt 

Ignore_errors()= This control statement will ignore the comments that have a wrong format. 

Stric_errors()= This control statement will generate a subclass or an UnicodeError error type in case that there is any kind of fail, mistake or error at the code of the file we are working with. 

Encoding

Now we'll talk about string encoding, which we often use when we're working with data storage. But what are data storages? This is just to say that they are the representation in characters of the coding; your system is based on bits and bytes in one familiar character.  

The string encoding is expressed in the following way:

Newline

When we talk about the newline mode we refer to the mode that controls the functionalities of creating a new line, these can be: '\r', " ", none,'\n', and '\r\n'. 

Newline statements are universal, and newlines are universal and can be seen as a way of interpreting the text sequences of our code. 

1. The end-of-line sentence in UNIX: "\n". 

2. The end-of-line sentence in Windows: "\r\n"?  

3. The end-of-line sentence in Max OS: "\r".  

Handling Files

Handling the File Not Found Exception Error 

There will be times when you will encounter the FileNotFoundError. Handling such error depends on your intent or purpose with regards to opening the file. Here are common reasons you will encounter this error: 

You did not pass the directory and filename as a string. 

You misspelled the directory and filename. 

You did not specify the directory. 

You did not include the correct file extension. 

The file does not exist. 

The first method to handle the FileNotFoundError exception is to make sure that all the typical reasons do not cause it. Once you do, then you will need to choose the best way to handle the error, which is entirely dependent on the reason you are opening a file in the first place. 

Xlsx files

These files are those that allow us to work in spreadsheets as if we were working in a windows Excel program; if our operating system is windows, these files will have a much smaller weight to a file of type xlsx in another operating system. 

This type of file is beneficial when we work with databases, numerical calculations, graphics and any other type of automation. 

To start working with this type of file, we will have to install the necessary library and this is done through the command "pip3 install openpyxl" in the Python terminal. 

Once our command has been executed, the openpyxl module will be installed in our Python file. 

Now we will create our first xlsx file:   

In this example we can see that we have created our file by importing the workbook function, which belongs to the openpyxl module, then we have added our parameters such as: "wb" assigning the workbook function and declaring that it will be our working document, then we add the name and save the file. 

Add information to the file with the xlsx module:   

To add information to our file, we will rely on the append function 

Now, to our document docxlsx.xlsx, we have added a tuple that contains words like Python, document. Once we have created this, the append function will allow us to add the information contained in the tuple in a message. 

Here we can see that the main function of append() is to admit iterable data such as tuples. 

Read documents in xlsx: 

To read an xlsx file, we will only need to import the load_workbook class and know the name of the file we are going to work with. It is also very important that the files are in the same folder in which the program is stored; otherwise, an automatic error will be generated. 

Once this is done, we will specify the object to work with, and we will ask for the information we need to read in order to print and compile it finally. 

What is Sequence in Python?

The sequence of program execution is not a highway linking the north and the south. It can run from the north to the south to the end. The sequence of program execution may be as complicated as a highway in the busy area, with nine turns and 18 turns, which is easy to make people dizzy.   

To write a good program, it is very important to control the process of program execution. Therefore, it is necessary to use the process control structure of the program. Without them, it is impossible to use the program to complete any complicated work.  

The programming language has been continuously developed for decades. Structured Programming has gradually become the mainstream of program development. Its main idea is to execute the entire program in sequence from top to bottom. Python language is mainly executed from top to bottom according to the sequence of program source code, but sometimes the execution sequence will be changed according to needs.  

At this time, the computer can be told which sequence to execute the program preferentially through flow control instructions. The process control of the program is like designing a traffic direction extending in all directions for the highway system.  

It is recognized that most program codes for process control are executed in sequence from top to bottom line after line, but for operations with high repeatability, it is not suitable to execute in sequence. Any Python program, no matter how complex its structure is, can be expressed or described using three basic control processes: sequence structure, selection structure, and loop structure.   

The first line statement of the sequence structure program is the entry point and is executed from top to bottom to the last line statement of the program. The selection structure allows the program to select the program block to be executed according to whether the test condition is established or not. If the condition is True, some program statements are executed. If the condition is False, other program statements are executed.   

Chapter 14                   Getting Started; Python Tips and Tricks

We are going to look at some of the tips and tricks that will help you to get started with Python, along with how we can work with web scraping and debugging some of our programs as well. 

Let’s get started with this one to help us get started and finalize how good our codes can be.  

Web Scraping

Imagine for a moment that we are going to pull up a large amount of data from many websites, and we want to be able to do this at a very fast rate. 

How would we be able to go through this without having to manually go through each of the websites that we have and gathering the data in this manner? 

This is where the process of web scraping is going to come into play.  

Web scraping is going to be used by companies in order to collect a large amount of information form websites. 

But why does someone want to go through and collect all of this data, in such large amounts, from these websites in the first place? 

There are a lot of reasons for this, and some of them are going to include the following: 

Price comparison: Some of the different services that are out there, such as ParseHub, will work with this process in order to collect data from websites for online shopping and then can use this in order to compare prices of similar products.  

Email address gathering: We can use the process of web scraping in order to help with marketing. 

This can help us to collect the email IDs that come with customers and then send out bulk emails to these individuals as well.  

Social media scraping: Web scraping is going to be used to collect data from social media sites and then figure out what is trending.  

Research and development: Web scraping is going to be used to help a company collect a lot of data from websites. 

We can then analyze this and use it to finish our surveys and to help out with research and development. 

Job listing: Details regarding openings of jobs, interviews, and more can be collected from a variety of websites and then we can list them in one place in order to make them easier for the user to access  

Web scraping is going to be more of an automated method that we can use in order to get a huge amount of data from any website that we choose. 

The data that we are able to get out of these websites will be unstructured. 

And this web scraping helps a company to collect all of this data and then will ensure that they are able to store it in a structured form. 

There are a variety of methods that we are able to use in order to scrape these websites that we want, including online Services, writing out some of your own codes, and APIs.  

Talking about whether or not scraping of this kind if seen as legal or not, it can depend on what the website says. 

Some websites are fine with this, and some are not. 

You can check with each website to figure out whether they are fine with it, and if they are, you are able to continue on with your web scraping tools and gather up the information that you need.  

Since we are talking about Python here, we are going to take some time to see how we are able to use Python to help out with web scraping. 

But this brings up the reasons why we would want to work with Python to help out with this process rather than working with some of the other coding languages that are out there. Some of the features that come with Python and can make it more suitable for web scraping will include: 

It is easy to use: The code that you are able to use along with Python is going to be simple.  This ensures that any of the codes that you want to use for web scraping will not be as messy to work with and can be easy to use.  

A large library collection: There are a lot of libraries that work with data science and web scraping that are also compatible with what the Python language is able to do. 

These include options like Pandas, Matplotlib, and NumPy. 

This is why you will find that the Python language is going to be suitable for web scraping and even for some of the other manipulations that you want to do with the extracted data.  

Dynamically typed: This is something in Python where you will not need to go through and define all of the types of data that you are using with our variables. 

Instead, you are able just to use these variables wherever you would like. 

This is going to save a lot of time when it comes to working on the codes and can make your job faster than ever.  

The syntax of Python is going to be easy to understand the syntax that we are able to see with Python is easy to understand, mainly because the statements that come with this are going to be written in English. 

It is going to be expressive and easy to read, and the indentations will make it easier for us to figure out between the different parts of the code.  

A small line of code is able to handle some large tasks. 

Web scraping is a process that we are going to use in order to save some time. 

And with Python, you are able to write out a small amount of code in order to get some of the big tasks that you would like to accomplish done. 

This is going to save you time not only when it comes to figuring out the important data that comes in that website, but can also help you to save time when you would like to write out the codes.  

Community: At times, when you are a beginner, you are going to find that there are parts of the code that are hard to work with and are not going to go as smoothly as you had hoped in the process. 

This is where you will find the Python language to be healthy. 

If you get stuck while writing out some of your code, you will like that the Python community is going to help you to answer your questions and get things done on the code in no time.  

Now that we know some of the benefits that come with Python, especially the ones that are going to help us to handle some of the web scrapings that we want to do, it is time for us to take things to the next step and look at how the process of web scraping is going to work. 

When you run out the code that you want to work within web scraping, you will find that there is a request that is sent out to the URL. 

Then there is going to be a response sent back from that request, and then the server is able to send the data and allows you a chance to read the page, whether it is XML or HTML at the time.  

The code is then able to go through and parse the XML or HTML page, find the data, and takes it out. 

The location where you are going to find this data when it is extracted will depend on what you told the code to do. 

Often it is going to be moved over to a database so that you are able to search through it later and learn more from it as well.  

There are going to be a few simple steps that you are able to take to make something to help us go through the process of extracting the data with the help of web scraping in Python. 

The steps that will help you to use Python to help with web scraping ill include: 

Find the URL that you would like to scrape in the first place.  

Inspect the page that you are planning on using. 

Find the data that is on the page that you would like to extract. 

Write out the code that you would like to use with the help of Python in order to complete this process.  

Run the code that you just wrote and then extract out the data that you would like to use.  

Store the data in the format that would be the most helpful for you in the process.  

There are also a few options that you are able to use when it is time to work on the process of web scraping. 

As we know, Python is already able to be used for a lot of different types of applications, and there are going to be a ton of libraries with Python that is going to be used for different purposes. 

There are a few libraries that work the best when it comes to working with the process of data web scraping will include: 

Selenium: This is going to be a web testing library. 

It is going to be used to help automate some of the activities that are found on your browser.  

BeautifulSoup: This is going to be one of those packages that you are able to use with Python to help us to parse HTML and XML documents. 

It is also able to create parse trees that can help us to extract the data in an easy manner.  

Pandas: This is one of the best libraries to rely on when it is time to handle any kind of work that you would like in data analysis and data science. 

Pandas are often going to be used to help out with any of the data analysis and the data manipulation that you would like. 

When it comes to web scraping, you will find that Pandas is going to be used in order to extract the data and then get it stored in the right format in the way that you would like along the way.  

There are many times when a company is going to try and gather up data from other websites and from many other sources. 

This is one of the first steps that is going to be found when we are working with data analysis and using that information to improve a business through their customers, the industry, or from the other competition out there.  

But going through and gathering all of that data in a manual manner is going to take too long, and can be really hard to work with as well. 

And with the large amounts of data that are being used and generated on a daily basis, it is no wonder that so many companies are working with processes like web scraping to handle all of the work in a timely manner as well.  

When we work with web scraping and do some of the codings that are necessary with the help of Python, we will find that we are able to get through the information in a fast manner and get it stored in the right place for our needs, without having to do all of the work manually. 

This can make the process of data analysis much easier overall and will ensure that we are able to see some of the results that we want with this as well. 

And with some of the right Python algorithms and codes, we can get data scraping done in no time.  

Chapter 15                   Things We Can Do in Python

In this part, we will discuss many things that you can do in Python. Some of the things we can do in Python include the comments, reading and writing, files and integers, strings, and variables. We are sure that after reading this, you will be able to create the program that will run effectively. Due to the interactive and descriptive nature of the Python, a beginner can handle many things using it. Therefore, we will discuss some aspects and comments in Python to help you get started. You can make amazing codes in a short time using the Python programming language. 

Comment

A comment, in the Python programming, starts with the # sign. This continues until the programmer gets to the end of the line. A good example is; 

# This is a comment

Print (hello, thanks for contacting us)

It instructs your computer to print “hello, thanks for contacting us”. In fact, the Python interpreter ignores all the comments. As a programmer, however, you should not leave a comment after every line. You can put in a comment when you need to explain something. Since long comments are not supported by Python, it is important to use short and descriptive comments to avoid them going across the lines.

Reading and Writing

You will realize that some program requests specific information or show the text on the screen. Sometimes we start the program code by informing the readers about our programs. To make things look easy for the other coders, it is important to give it the name or title that is simple and descriptive.

As a programmer, you can use a string literal that comprises the print function to get the right data. String literal is a line of the text surrounded by the quotes. They can be either double or single quotes. Although the type of quotes a programmer use matters less, the programmer must end with the quotes that he/she has used at the beginning of the phrase. You can command your computer to display a phrase or a word on the screen by just doing as mentioned above.

Files

Apart from using the print function to obtain a string when printing on the screen, it can be used to write something onto the file. First, you will have to open up the myfile.txt and write on it before assigning it the myfile which is a variable. Once you have completed the first step, you will have to assign “w” in the new line to tell the program that you will only write or make changes after the file has opened. It is not mandatory to use print function; just use the right methods like read method.

Read method is used to open specific files to help you read the available data. You can use this option to open a specific file. Generally, the read method helps the programmers to read the contents into variable data, making it easy for them to open the program they would like to read.

Integers

Always make sure that the integers are kept as whole numbers if you are using them. They can be negative or positive only if there are no decimals. However, if your number has a decimal point, use it as a floating number. Python will automatically display such integers in the screen.

Moreover, you cannot place one number next to others if you are using the integers because Python is a strongly typed language; thus it will not recognize them when you use them together. However, you put both the number and the string together by making sure you turn the number into a string first before going to the next steps.

Triple Quotes

After reading and understanding both the single and double quotes, it is now a time to look at the triple quotes. The triple quotes are used to define the literal that spans many lines. You can use three singles, double, or single when defining an authentic.

Strings

Although a string is seen as a complicated thing to many beginners, it is a term used by the programmers when referring to a sequence of characters and works just like a list. A string contains more functionality which is specific than a list. You will find it challenging to format the strings when writing out the code because some messages will not be fixed easily due to its functionality. String formatting is the only way to go away within such a situation.

Escape Sequences

They are used to donate special characters which are hard to type on the keyboard or those that can be reserved to avoid confusion that may occur in programming.

Operator Precedence

It will help you to track what you are doing in Python. In fact, it makes things easy when ordering the operation to receive the right information. So, take enough time to understand how the operator precedence works to avoid confusion.

Variables

Variables refer to the labels donated somewhere in the computer memory to store something like holding values and numbers. In the programming typed statistically, the variables have predetermined values. However, Python enables you to use one variable to store many different types. For example, in the calculator, variables are like memory function to hold values which can be retrieved in case you need them later. The variables can only be erased if you store them in the newer value. You will have to name the variable and ensure it has an integer value.

Moreover, the programmer can define a variable in Python by providing the label value. For instance, a programmer can name a variable count and even make it an integer of one, and this can be written as; count=1. It allows you to assign the same name to the variable, and in fact, the Python interpreter cannot read through the information if you are trying to access values in the undefined variable. It will display a message showing syntax error. Also, Python provides you with the opportunity of defining different variables in one line even though this not a good according to our experience. 

The Scope of a Variable

It is not easy to access everything in Python, and there will be differences in the length of the variables. However, the way we define the variable plays a vital role in determining the location and the duration of accessing the variables. The part of the program that allows you to access the variable is called the Scope while the time taken for accessing the variable is a lifetime. 

Global variables refer to the variables defined in the primary file body. These variables are visible throughout the file and also in the file that imports specific data. As such, these variables cause a long-term impact which you may notice when working on your program. This is the reason why it is not good to use global variables in the Python program. We advise programmers to add stuff into the global namespace only if they plan to use them internationally. A local variable is a variable defined within another variable. You can access local variables from the region they are assigned. Also, the variables are available in the specific parts of the program.

Modifying Values

For many programming languages, it is easy for an individual to define a particular variable whose values have been set. The values which cannot be modified or changed, in the programming language, are called constants. Although this kind of restrictions is not allowed in Python, there are used to ensure some variables are marked indicating that no one should change those values. You must write the name in capital letters, separated with underscores. A good example is shown below.

NUMBER_OF_HOURS_IN_A_DAY=24

It is not mandatory to put the correct number at the end. Since Python programming does not keep tracking and has no rules for inserting the correct value at the end, you are free and allowed to say, for example, that they are 25 hours in a day. However, it is important to put the correct value for other coders to use in case they want. 

Modifying values is essential in your string as it allows a programmer to change the maximum number in the future. Therefore, understanding the working of the string in the program contributes a lot to the success of your program. One has to learn and know where to store the values, the rules governing each value, and how to make them perform well in a specific area. 

The Assignment Operator

It refers to an equal sign (=). You will be using the assignment operator to assign values to the variable located at the left side on the right of the statement. However, you must evaluate if the value on the right side is an arithmetic expression. Note that the assignment operator is not a mathematical sign in the programming because, in programming, we are allowed to add all types of things and make them look like they are equivalent to a certain number. This sign is used to show that those items can be changed or turned into the part on the other side.

Chapter 16                   Working with Files

In this part, we’ll discuss working with files. Often during your programming journey, you'll want to pull in data from external files and manipulate that data. For example, maybe you have a large word document, but you only want sentences that contain certain words and phrases. With Python, you can read the document, do a search for the desired strings, join these strings into a list, and write a new document containing just the target strings. Python has many built-in functions and features that make loading, reading, and even writing to external files simple. Let’s see the various ways we can interact with a file using Python.

Opening and Reading

To begin our exploration of files, we’ll first need a text file to work with. Copy any text you’d like into a text editor and save it to the same directory as your Python scripts, saving it with the “.txt” format. If you need text to work with, you can try writing the following and running the script:

import this

Running this script will activate a Python Easter Egg, printing out the Zen of Python (a list of the principles that guide design in Python). If you would like, you can copy that text into a text file and save it. 

To open a file in Python, we can use the open() function, which takes two arguments. The first argument is the file that you want to open, while the second argument specifies the mode that the file will be opened in. For instance, if you have a folder called “Projects” on your C drive, you would have to specify that Python looks for the targeted file by passing in: 

C:\\Projects\\test_text.txt.

With this in mind, you can assign the contents of a file to a variable by doing this:

text_file = open("text_test.txt", "r")

The first argument specifies where Python should look for the file that you want to open. If the file is in the same directory as the program you are writing, all you need to do is provide the name and extension of the file. If this isn’t the case and the file is located elsewhere, you’ll need to provide the full path to the file, as mentioned above. 

In the case above, the r specifies that we want to open the document in read-only mode. The other file-handling options include: 

w mode - Specifies you want to open the file in write-only mode. 

w will create the file that has been passed in as the first argument if the file doesn’t already exist. Be careful when using this, because the data in the file will be erased if the file already exists. 

a mode – Used for opening the file in appending-mode. Appending is for adding text to the current body of the file. If the file doesn’t exist yet, the file will be created. Unlike w, the existing data in the file isn’t erased if the file already exists. This is because any new data is added to the end of the file. 

r+ - Specifies that you want to both read and write to the file.

After you have created a file object by using the open() function and the assignment operator, it’s possible to read out individual lines in the document by using the readline() function, which is done by using dot notation on the file object:

text_file.readline()

Each time the readline() function is called, it moves to the next line in the text document. This means that if you call the function and print the results three times, Python will print out the first three lines in the document. 

A more efficient way of printing out multiple lines from a file is by using a for loop. We can easily print out all the lines in a text file by writing a statement like:

for i in text_file:

print(i)

Now that you know how to open files in Python, you should also know how to close them. You can close a file you’ve opened simply by using the close() function on it, like this:

text_file.close()

You should get in the habit of closing files after you are done working with them, because this frees up resources your system is using to keep the file open. 

Writing to Text Files

Let’s learn how to write text to a file in Python. For us to accomplish this, we can use either the a or w modes, but if we use w, the current content of our text file will be erased whenever our program runs. For this reason, it’s often smarter to write to files in a/append mode. Writing to a file in Python can be accomplished using the intuitively named write() function. The function merely takes in the text you want to write as an argument and is invoked with dot notation on the text file object you’ve created. We could create and write to a text file by doing this:

target_file = open("write_test.txt", "a")

# \n creates a new line

target_file.write("All we have to do is type in a sentence to write to the document. \n")

target_file.write("Using the write function multiple times will write multiples lines to the document. \n") 

Much like we can use a for loop to read from a text document, we can also use a for loop to write to a text document. We could make a list full of strings to write and then use a for loop to write to the document, which would write our list items on different lines.

list_to_write = ["This", " is", " our", " word", " list"]

for w in list_to_write:

target_file.write(w)

target_file.close()  

Remember that you can format how your string is written into the text document by using the escape character and formatting options.

Buffer Size/Binary Files

When you first start writing your programs, you’ll probably only be working with small text files that don’t take up a lot of memory. However, when you start to work with larger collections of data and bigger text files, you’ll want to know how to specify a buffer size. Buffering our file allows us to read it in small chunks, so that it doesn’t take up too much memory. Python will divide the text document up, reading it in by the specified buffer size. We can declare the desired buffer size by using the read() function and passing in the buffer size as an argument.

When we pass in the buffer size, Python expects a numerical value. We are specifying the number of bytes to read at one time. Let’s say we wanted to read our test text file 20 bytes at a time.

text = open("test_text.txt", "r")

print(text.read(20))

Printing the text variable would now display the first 20 bytes of the text document. If you wanted to loop through the entire document, you would need to use a while loop, setting the end condition as the length of the file, and then updating the current value of the text variable by using the function again to get the next 20 bytes. After opening the file, try running the code below and notice it prints out the text file in blocks of 20 bytes.

text = target_file.read(20)

while len(text):

print(text)

text = target_file.read(20)

Python interprets non-text files in binary, so the term “binary file” describes non-text files (as opposed to ASCII or other human-readable file encodings). We can work with these non-text files by using specific modes that let the open() function know we want to read or write binary: rb and wb. If you were aiming to open an image file and copy it over to another file, this could be done simply by opening an image file with the mode set to rb and then copy the lines of data over by opening a new file with the mode set to wb. 

Deleting and Renaming

There are two other functions that you should be aware of when working with files in Python. The remove() function and rename() function help you deal with files in a folder, either by deleting the files or renaming the files. These are part of the os library, so this means that the functions will need to be imported before they can be used. 

from os import remove, rename

This remove() function takes the name of the target file as its only parameter, so the syntax looks like this:

remove(target_file)

Meanwhile, the rename() function takes in two arguments, the current name of the target file and the name you wish to rename the file to. 

rename("old_filename.txt","new_filename.txt")

Chapter 17                   Python in the Real World

Now that you know the basics behind Python programming, you might be wondering where exactly could you apply your knowledge. Keep in mind that you only started your journey, so right now, you should focus on practicing all the concepts and techniques you learned. However, having a specific goal in mind can be extremely helpful and motivating.

As mentioned earlier, Python is a powerful and versatile language with many practical applications. It is used in many fields, from robotics to game development and web-based application design. In this part, you are going to explore some of these fields to give you an idea about what you can do with your newly acquired skills.

What is Python Used For? 

You're on your way to work listening to your favorite Spotify playlist and scrolling through your Instagram feed. Once you arrive at the office, you head over to the coffee machine, and while waiting for your daily boost, you check your Facebook notifications. Finally, you head to your desk, take a sip of coffee, and you think, "Hey, I should Google to learn what Python is used for." At this point, you realize that every technology you just used has a little bit of Python in it.

Python is used in nearly everything, whether we are talking about a simple app created by a startup company or a giant corporation like Google. Let’s go through a brief list of all the ways you can use Python. 

Robotics

Without a doubt, you’ve probably heard about tiny computers like the Raspberry Pi or Arduino board. They are tiny, inexpensive devices that can be used in a variety of projects. Some people create cool little weather stations or drones that can scan the area, while others build killer robots because why not. Once the hardware problems are solved, they all need to take care of the software component. 

Python is the ideal solution, and it is used by hobbyists and professionals alike. These tiny computers don't have much power, so they need the most powerful programming language that uses the least amount of resources. After all, resources also consume power, and tiny robots can only pack so much juice. Everything you have learned so far can be used in robotics because Python is easily combined with any hardware components without compatibility issues. Furthermore, there are many Python extensions and libraries specifically designed for the field of robotics.

In addition, Google uses some Python magic in their AI-based self-driving car. If Python is good for Google and for creating killer robots, what more can you want? 

Machine Learning

You’ve probably heard about machine learning because it is the new popular kid on the block that every tech company relies on for something. Machine learning is all about teaching computer programs to learn from experience based on data you already have. Thanks to this concept, computers can learn how to predict various actions and results. 

Some of the most popular machine learning examples can be found in: 

Google Maps: Machine learning is used here to determine the speed of the traffic and to predict for you the most optimal route to your destination based on several other factors as well. 

Gmail: SPAM used to be a problem, but thanks to Google’s machine learning algorithms, SPAM can now be easily detected and contained. 

Spotify or Netflix: Noticed how any of these streaming platforms have a habit of knowing what new things to recommend to you? That's all because of machine learning. Some algorithms can predict what you will like based on what you have watched or listened to so far.

Machine learning involves programming, as well as a great deal of mathematics. Python's simplicity makes it attractive for both programmers and mathematicians. Furthermore, unlike other programming languages, Python has a number of add-ons and libraries created explicitly for machine learning and data science, such as Tensorflow, NumPy, Pandas, and Scikit-learn. 

Cybersecurity

Data security is one of the biggest concerns of our century. By integrating our lives and business into the digital world, we make it vulnerable to unauthorized access. You probably read every month about some governmental institution or company getting hacked or taken offline. Most of these situations involve terrible security due to outdated systems and working with antiquated programming languages. 

Python's own popularity is something that makes it far more secure than any other. How so? When something is popular, it becomes driven by a large community of experts and testers. For this reason, Python is often patched, and security issues are plugged in less than a day. This makes it a popular language in the field of cybersecurity.

Web Development

As mentioned several times before, Python is simple yet powerful. Many companies throughout the world, no matter the size, rely on Python to build their applications, websites, and other tools. Even giants like Google and Facebook rely on Python for many of their solutions.

The main advantages of working with Python so that we won't explore them yet again. However, it is worth mentioning that Python is often used as a glue language, especially in web development. Creating web tools always involves several different programming languages, database management languages, and so on. Python can act as the integration language by calling C++ data types and combining them with other elements, for example. C++ is mentioned because in many tech areas, the critical performance components are written in C++, which offers unmatched performance. However, Python is used for high-level customization.

Conclusion

Thank you for making it through to the end of Coding with Python: A Simple and Straightforward Guide for Beginners to Learn in the Fast Way the Programming with Python, let’s hope it was informative and able to provide you with all of the tools you need to achieve your goals whatever they may be.     

The next step is to spend some time taking a look at some of the different parts that we are able to focus on when it is time to work with coding our own applications and more. Many people are worried about getting into coding because they think that it is going to be too difficult for them to get started, and they worry that they will never be able to handle all of the work that is going to come with their coding needs.     

And that is part of the beauty that is going to come with using the Python language, and we hope that you are able to see this when it comes with this kind of language and with the examples that are in this guidebook, you will find that you will be able to work with the Python language. This is going to be an easy language for beginners and advanced coders to work with, but you will find that it has a lot of power behind it and will help you to get some of the work done in coding that you would like.     

This guidebook has spent some time looking at the benefits of working with the Python language, and all of the different options that you are able to work with when it comes time to work on your program. We spent some time looking at how to write out some of our own conditional statements, our loops, exceptions, inheritances, and so much more. We even spent some time looking more in-depth about the work we can do with OOP languages and the classes that we would like to work with, and this will ensure that we can keep things as organized as possible within the code that we do.     

When we are able to put all of these parts together inside of our work of coding, you will find that it is a lot easier to work with some of the coding that we want, even when we are a beginner. You will find that this is easier to accomplish than you think, and we are able to make codes that work with all sorts of projects. And considering that Python is going to work well with a lot of the major companies out there and some of the platforms that they want to use as well, including the Google search engine and some of the functionality of the YouTube site, you can see why this is a language that you are able to learn, and get a lot of use out of as well.  

You no longer have to be worried or scared about working with a coding language. While some of the coding languages in the past may have been a bit difficult to work with and would not provide you with the results that you wanted all of the time, you will find that Python is not going to come with this kind of situation at all. You may have even glanced through some of the different parts of this ahead of time and noticed that it is easy enough to read some of these codes, before even starting. Take that as a confidence boost, and see how easy working with this language can be.  

There may be a lot of different coding languages that we are able to work with when it comes to focusing on the coding that you would like to accomplish. But Python keeps proving that it is one of the best options out there for us to work with. When you are ready to learn more about coding in Python and all of the neat things that we are able to do with it, make sure to check out this guidebook and take a look at how great it can be.  