Learn Python - Full Fundamental Course for Beginners | Python Tutorial for Beginners [2019]

Brief Summary

This YouTube transcript provides a comprehensive introduction to Python language fundamentals. It covers essential topics such as:

• What Python is and its key features.
• The history and development of Python.
• Basic concepts like identifiers, reserved words, and data types.
• The differences between Python 2.x and 3.x.
• Practical aspects like type casting and the use of various data types.

The transcript aims to equip beginners with a solid foundation in Python programming.

Introduction to Python Language Fundamentals

The video introduces a series of Python language fundamentals, including input/output statements, operators, and flow control, spanning approximately 25 topics. It stresses the importance of mastering the basic concepts, as proficiency in these areas will greatly simplify understanding more advanced topics later on. The initial units, such as language fundamentals, operators, and flow control, require special attention to ensure a solid grasp, which will make subsequent concepts easier to understand.

Language Fundamentals: Introduction

The language fundamentals section covers a range of topics, starting with an introduction to Python, its origins, and syntax. It also explores the application areas of Python, highlighting its features and limitations. The discussion includes different Python flavours like Jon, Anaconda, and IronPython, as well as various versions such as Python 2.x and 3.x. Key concepts such as identifiers, reserved words, and data types are also addressed, with a mention of the 14 data types to be discussed. The section concludes with an overview of type casting, explaining how to convert between different data types.

What is Python?

Python is defined as a programming language used to develop various applications, from small tools to web applications. It's a high-level language, meaning it's programmer-friendly and abstracts away from low-level, machine-specific details. This allows programmers to focus on the logic of their code without worrying about memory management or other low-level activities. Python's syntax is designed to be easily readable and understandable, even without prior programming knowledge.

High Level Programming Language

Python is a high-level programming language, which means it is programmer-friendly and does not require developers to manage low-level details. The code is easy to understand, even without programming knowledge. Low-level activities such as memory management and security are handled by Python itself. The example code provided demonstrates how Python's syntax is simple and readable, making it easy to understand the logic without needing programming expertise.

General Purpose Programming Language

Python is a general-purpose, high-level programming language suitable for developing various types of applications, including desktop, web, data science, and machine learning applications. The term "high-level" indicates that Python is programmer-friendly, abstracting away low-level activities like memory management and security. "General purpose" means Python is not limited to a specific domain and can be used across different fields.

Who Developed Python?

Python was developed by Guido van Rossum, who is often referred to as the "father of Python." He began developing Python in 1989 while working at the National Research Institute in the Netherlands. Python was officially released to the public in 1991. Despite being older than Java (which came out in 1995), Python's popularity surged later due to its suitability for modern market requirements like artificial intelligence, machine learning, and IoT.

Why Python Became Popular?

Python's popularity surged due to its simplicity, ease of understanding, and concise code, making it ideal for current market needs such as artificial intelligence, machine learning, and IoT. Its ability to write less code to fulfil requirements, also known as concise code, is highly valued. The language's suitability for trending market requirements has driven its increased adoption and popularity.

Pre Requisites to Learn Python

To learn Python, no prior programming knowledge is required; the ability to read English is sufficient. Python's ease of use allows even school children to learn and write programs. The video uses the "Hello, World!" program to illustrate Python's simplicity compared to C and Java, where significantly more code is needed to achieve the same result.

Hello World Program in Python, Java and C

The "Hello, World!" program is used to compare the simplicity of Python with C and Java. In C, the program requires multiple lines of code, including header files and a main function. Java requires even more lines, including a class declaration and a main method. In contrast, Python achieves the same result with a single line: print("Hello, World!"). This illustrates Python's concise syntax and ease of use.

Sum of Two Numbers in Python, Java and C

The process of summing two numbers is compared across C, Java, and Python to further demonstrate Python's simplicity. C requires variable declarations, assignments, and a printf statement. Java involves class and method declarations, along with System.out.println. Python accomplishes the same task with just two lines: assigning values to variables a and b, and then printing their sum using print(a + b).

Dynamically Typed Programming Language

Python is a dynamically typed programming language, meaning that you don't need to explicitly declare the type of a variable. The type is inferred at runtime based on the assigned value. This contrasts with statically typed languages like Java, where you must declare the type of each variable (e.g., int a = 10). Python automatically determines the type, making the code more flexible and easier to write.

Example of Dynamically Typed

In Python, the type of a variable is determined at runtime based on the assigned value, unlike Java, where you must declare the type explicitly. For example, in Python, you can assign an integer to a variable a, and later assign a string to the same variable without issue. The type() function can be used to check the current type of a variable at any point in the code.

Why Guido Van Rossum Selected the Word Python

Guido van Rossum, the creator of Python, named the language after the comedy show "Monty Python's Flying Circus," which he enjoyed. This choice was not related to snakes or any technical reason. The video also shares the stories behind the names of Java and Hadoop, highlighting how personal interests and serendipitous events can influence the naming of technology projects.

Programming Paradigms

Python is a versatile language that supports multiple programming paradigms, including functional, object-oriented, scripting, and modular programming. It borrows features from C (functional), C++ (object-oriented), and Perl/Shell script (scripting). This multi-paradigm support allows Python to be used in various ways, making it highly adaptable.

Application Areas of Python

Python is a general-purpose language used in various application areas, including desktop, web, network applications, game development, data analysis, machine learning, artificial intelligence, and IoT. It is used by major companies like Google, Yahoo, Facebook, NASA, Dropbox, and Netflix. Python's versatility and extensive library support make it a popular choice across different domains.

Top Companies Using Python

Many world-class software companies use Python extensively. These include Google, Facebook, Instagram, Spotify, Quora, Netflix, and Dropbox. Python is used in areas such as web search, video sharing (YouTube), and data storage. The language's versatility and ease of integration make it a favourite in various industries.

Features of Python

Python has several key features that make it a popular choice for developers. These include its simplicity and ease of learning, its status as freeware and open source, its high-level nature, platform independence, portability, dynamic typing, support for both procedure-oriented and object-oriented programming, being interpreted, extensible, embedded capabilities, and an extensive library. These features contribute to Python's flexibility and wide applicability.

Simple and Easy to Learn

Python is simple and easy to learn because it has a small set of reserved words (only 33), and its code reads like English statements. This makes it easier for programmers to understand and write code. The concise nature of Python code reduces development time and project costs.

Freeware and Open Source

Python is freeware, meaning it can be used without paying any license fees, even for commercial purposes. It is maintained by the Python Software Foundation, a non-profit organisation. Python is also open source, allowing anyone to access and modify its source code. This has led to the development of multiple customized versions, such as Jon, IronPython, and Anaconda Python, tailored for specific needs.

High Level Programming Language

Python is a high-level programming language, which means it is programmer-friendly and abstracts away low-level details. Programmers can easily read, understand, and write Python code. Low-level activities such as memory management and security are handled by Python itself, freeing developers from these concerns.

Platform Independent

Python is platform-independent, meaning that Python applications can run on different operating systems (e.g., Windows, Linux, macOS) without modification. This is achieved through the Python Virtual Machine (PVM), which converts Python code into a platform-specific format. While Python code is platform-independent, the PVM itself is platform-dependent, requiring a separate version for each operating system.

Portable

Python is portable, meaning Python applications can be easily migrated from one platform to another without requiring significant changes. This is because Python code does not depend on the underlying platform. The process of moving Python programs between different operating systems is straightforward.

Dynamically Typed

Python is dynamically typed, meaning that you don't need to declare the type of a variable explicitly. The type is inferred at runtime based on the assigned value. This allows a single variable to hold values of different types throughout its lifetime.

Procedure Oriented and Object Oriented

Python supports both procedure-oriented and object-oriented programming paradigms. It is an all-rounder, incorporating features from C (procedure-oriented) and C++ (object-oriented). This allows developers to choose the most appropriate style for their project.

Interpreted

Python is an interpreted language, meaning that Python code does not need to be compiled before execution. The Python interpreter handles compilation internally, making the development process more straightforward.

Extensible

Python is extensible, meaning you can extend the functionality of Python applications with code written in other languages like C or Java. This allows you to use existing codebases and improve performance-critical sections by using lower-level languages.

Embedded

Python is embeddable, meaning you can use Python code within applications written in other languages like C# or Java. This allows you to leverage Python's features and libraries in projects primarily built using other technologies.

Extensive Library

Python has an extensive library, offering a wide range of modules and packages for various tasks. This rich library support simplifies development and allows programmers to write concise code. For example, generating a six-digit OTP can be done in just a few lines of Python code using the random library.

Limitations of Python

Python has limitations in mobile application development and enterprise-level applications due to insufficient library support. Additionally, as an interpreted language, Python's performance is relatively low compared to compiled languages like C and C++.

Flavors of Python

Python has multiple flavours, each customized for specific purposes. These include CPython (the standard version), Jon (for Java integration), IronPython (for .NET integration), RubyPython (for Ruby integration), and Anaconda Python (for data science). These flavours exist because Python is open source, allowing for customization to meet different needs.

Python Versions

Python has evolved through several major versions, including Python 1.0 (released in 1994), Python 2.0 (released in 2000), and Python 3.0 (released in 2008). The latest version is Python 3.7.2. Python 3.x is not backward-compatible with Python 2.x, meaning code written for Python 2.x may not run on Python 3.x without modification.

Python 2x vs Python 3x

Python 3.x is not backward-compatible with Python 2.x, as it was developed as a completely independent language. This means that Python 3.x does not guarantee support for code written in Python 2.x. While this lack of backward compatibility can be a problem, it allows Python 3.x to freely add new features and improve the language without being constrained by older versions.

Identifiers

In Python, an identifier is a name used to identify a variable, class, method, or module. Identifiers must follow specific rules: they can only contain alphabet symbols (a-z, A-Z), digits (0-9), and underscores (_). They cannot start with a digit, and Python is case-sensitive, meaning that total, Total, and TOTAL are treated as different identifiers. There is no length limit for identifiers, but it is recommended to keep them concise and meaningful.

Rules to Define Identifiers

Rules for defining Python identifiers include: only alphabet symbols, digits, and underscores are allowed; identifiers cannot start with a digit; Python is case-sensitive; there is no length limit, but it's best to keep them concise; and reserved words cannot be used as identifiers.

Special Identifiers

Special identifiers in Python include those prefixed with underscores. A single underscore (e.g., _x) indicates a protected variable, while two underscores (e.g., __x) indicate a private variable. Identifiers starting and ending with two underscores (e.g., __init__) are magic variables or methods with special meanings in Python.

Reserved Words

Reserved words, or keywords, are predefined words in Python that have special meanings and cannot be used as identifiers. Python has 33 reserved words, all containing alphabet symbols, with only True, False, and None starting with uppercase letters. The video notes that Python does not have a switch statement or a do-while loop, and data types like int, float, and boolean are not reserved words.

Listing Reserved Words

To programmatically list all reserved words in Python, you can use the keyword module. By importing the keyword module and accessing keyword.kwlist, you can retrieve a list of all reserved words in the language.

Data Types

Data types represent the type of data stored in a variable. Python is a dynamically typed language, so you don't need to declare the type of a variable explicitly. The type is inferred based on the assigned value. Python has several built-in data types, including int, float, complex, bool, str, list, tuple, set, frozenset, dict, bytes, bytearray, range, and None.

Dynamically Typed Languages

In dynamically typed languages like Python, you don't need to declare the type of a variable explicitly. The type is inferred based on the assigned value. This contrasts with statically typed languages like Java, where you must declare the type of each variable.

Data Types in Python

Python includes several built-in data types, including int, float, complex, bool, str, list, tuple, set, frozenset, dict, bytes, bytearray, range, and None. The video emphasizes that everything in Python is an object.

In Data Type

The int data type is used to represent whole numbers without a decimal point. In Python 3, there is no separate long data type; the int type can represent arbitrarily large integers. Integer values can be represented in decimal, binary, octal, or hexadecimal forms.

Representing Integral Values

Integral values can be represented in decimal, binary, octal, or hexadecimal forms. Decimal is the default number system. Binary numbers are prefixed with 0b or 0B, octal numbers with 0o or 0O, and hexadecimal numbers with 0x or 0X.

Float Data Type

The float data type is used to represent numbers with a decimal point. Floating-point values can only be represented in decimal form, not binary, octal, or hexadecimal. They can also be represented in exponential form (scientific notation).

Exponential Form

Floating-point values can be represented in exponential form (scientific notation) using the E or e notation. This is useful for representing very large or very small numbers in a compact form. For example, 1.2E3 is equivalent to 1.2 x 10^3, or 1200.0.

Complex Data Type

The complex data type is used to represent complex numbers in the form a + bj, where a is the real part and b is the imaginary part. The imaginary unit is represented by j. The real and imaginary parts can be integers or floating-point numbers. Arithmetic operations can be performed on complex numbers.

Syntax of Complex Data Type

The syntax for complex numbers in Python is a + bj, where a is the real part and b is the imaginary part. The imaginary unit j must be used. The real and imaginary parts can be integers or floating-point numbers. The real and imaginary parts can be accessed using .real and .imag attributes, respectively.

Boolean Data Type

The bool data type represents logical values, which can be either True or False. In Python, True and False must be capitalized. Internally, True is represented as 1 and False as 0, allowing boolean values to be used in arithmetic operations.

String Data Type

The str data type represents a sequence of characters. Strings can be enclosed in single quotes, double quotes, or triple quotes. Python does not have a separate character data type; single characters are also represented as strings.

String Representation

Strings in Python can be represented using single quotes, double quotes, or triple quotes. Triple quotes are used for multi-line strings and docstrings. If a string contains a single quote, it can be enclosed in double quotes, and vice versa.

Triple Quotes

Triple quotes (either single or double) are used for multi-line strings and docstrings. They allow you to define strings that span multiple lines without using escape characters. They are also useful for including both single and double quotes within a string.

Index in String

Python strings support indexing, allowing you to access individual characters using their position. Python supports both positive and negative indexing. Positive indices start from 0, while negative indices start from -1 (representing the last character).

Slice Operator

The slice operator is used to extract a portion (substring) of a string. The syntax is s[begin:end], where begin is the starting index and end is the ending index (exclusive). If begin is omitted, it defaults to 0. If end is omitted, it defaults to the end of the string.

Applications of Slice Operator

The slice operator can be used to perform various string manipulations, such as converting the first letter of a string to uppercase or extracting specific parts of a string. The video provides examples of how to use the slice operator in combination with other string methods to achieve these tasks.

Mathematical Operations on Strings

Python supports certain mathematical operations on strings. The + operator is used for string concatenation, but both operands must be strings. The * operator is used for string repetition, where one operand must be a string and the other an integer.

String Reputation Operator

The * operator can be used to repeat a string multiple times. For example, "Durga" * 3 will result in "DurgaDurgaDurga". This is known as the string repetition operator.

Data Types Summary

The video summarizes the key properties of Python's data types, including their description, mutability, order preservation, indexing, and whether duplicates are allowed. This summary provides a clear overview of the characteristics of each data type.

Type Casting

Type casting is the process of converting a value from one data type to another. Python provides several built-in functions for type casting, including int(), float(), complex(), bool(), and str().

Int Type Casting Function

The int() function is used to convert a value to an integer. It can convert float values (truncating the decimal part), boolean values (True to 1, False to 0), and strings containing integers (in base 10). It cannot convert complex numbers directly.

Float Type Casting Function

The float() function is used to convert a value to a floating-point number. It can convert integer values, boolean values (True to 1.0, False to 0.0), and strings containing numbers (either integers or floats in base 10). It cannot convert complex numbers directly.

Complex Type Casting Function

The complex() function is used to create a complex number. It can take one or two arguments. If one argument is provided, it becomes the real part, and the imaginary part is 0. If two arguments are provided, the first becomes the real part, and the second becomes the imaginary part.

Bool Type Casting Function

The bool() function is used to convert a value to a boolean. For integers and floats, 0 is considered False, and any other value is True. For strings, an empty string is False, and any non-empty string is True.

Str Type Casting Function

The str() function is used to convert a value to a string. It can convert integers, floats, complex numbers, and boolean values into their string representations.

Immutability

Immutability means that once an object is created, its value cannot be changed. In Python, fundamental data types like int, float, complex, bool, and str are immutable. If you try to modify an immutable object, a new object is created instead.

Object Reusability

Python uses object reusability to optimize memory usage. If multiple variables are assigned the same immutable value, they may all point to the same object in memory. This is particularly true for small integers and strings.

Water Registration Application

The video uses a water registration application as an example to illustrate the benefits and drawbacks of object reusability and immutability. In this scenario, if all users share the same city (e.g., Hyderabad), Python might reuse the same string object for the city name across all user records.

Advantages and Disadvantages of Object Reusability

Object reusability improves memory utilization and performance, but it can lead to issues if the shared object is mutable. If one user modifies the shared object, all other users will see the change. To prevent this, Python's immutable data types ensure that changes create new objects, avoiding unintended side effects.

List Data Structure

A list is a data structure that can hold a collection of items. Lists are mutable, meaning their contents can be changed after creation. Lists are ordered, meaning the items have a specific sequence, and they allow duplicate values.

List Properties

Lists are mutable, meaning their contents can be changed after creation. They preserve insertion order, allowing you to access elements in the order they were added. Lists allow duplicate elements and support indexing and slicing.

Tuple Data Structure

A tuple is similar to a list, but it is immutable, meaning its contents cannot be changed after creation. Tuples are often used to represent fixed collections of items.

Set Data Structure

A set is a data structure that stores a collection of unique items. Sets do not preserve insertion order, and they do not allow duplicate values.

Frozen Set Data Structure

A frozen set is an immutable version of a set. Once created, its contents cannot be changed.

Dictionary Data Structure

A dictionary is a data structure that stores key-value pairs. Each key must be unique, and the dictionary allows you to quickly retrieve values based on their corresponding keys.

Range Data Type

The range data type represents a sequence of numbers. It is often used in loops to iterate over a range of values. Range objects are immutable.

Bytes Data Type

The bytes data type represents a sequence of byte values (integers between 0 and 255). Bytes objects are immutable.

Byte Array Data Type

The bytearray data type is similar to bytes, but it is mutable, meaning its contents can be changed after creation.

Escape Characters

Escape characters are special characters used in strings to represent certain actions or symbols. Common escape characters include \n (newline), \t (tab), \r (carriage return), \b (backspace), \' (single quote), \" (double quote), and \\ (backslash).

Comments

Comments are used to add explanatory notes to your code. In Python, single-line comments start with the # symbol. Multi-line comments are not directly supported, but you can use triple-quoted strings as docstrings for documentation purposes.

Constants

Python does not have a built-in mechanism for declaring constants. However, it is a common convention to use uppercase variable names to indicate that a variable should be treated as a constant.

Fundamental Data Types vs Immutability

The video discusses the concept of immutability in Python, particularly in relation to fundamental data types. It