├── .ipynb_checkpoints ├── AN OVERVIEW OF PYTHON-checkpoint.ipynb └── Python Fundamentals-checkpoint.ipynb ├── AN OVERVIEW OF PYTHON.ipynb ├── Python Fundamentals.ipynb └── README.md /.ipynb_checkpoints/AN OVERVIEW OF PYTHON-checkpoint.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [], 3 | "metadata": {}, 4 | "nbformat": 4, 5 | "nbformat_minor": 5 6 | } 7 | -------------------------------------------------------------------------------- /.ipynb_checkpoints/Python Fundamentals-checkpoint.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [], 3 | "metadata": {}, 4 | "nbformat": 4, 5 | "nbformat_minor": 5 6 | } 7 | -------------------------------------------------------------------------------- /AN OVERVIEW OF PYTHON.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "id": "c2e0f49d", 6 | "metadata": {}, 7 | "source": [ 8 | "### **What is python programming language?**\n", 9 | "\n", 10 | "- Python is a high-level programming language known for its simplicity, readability, and versatility. It was created by Guido van Rossum and released in 1991.\n", 11 | "\n", 12 | "Python emphasizes code readability and offers a wide range of features and libraries, making it popular among developers for various applications.\n", 13 | "Reference: https://docs.python.org/3/tutorial/index.html " 14 | ] 15 | }, 16 | { 17 | "cell_type": "markdown", 18 | "id": "b9d700a0", 19 | "metadata": {}, 20 | "source": [ 21 | "### **Common Feature Provided By python.** \n", 22 | "\n", 23 | "Easy-to-Read Syntax:\n", 24 | "- Python uses a clean and readable syntax, which makes it easier to write and understand code.\n", 25 | "\n", 26 | "**Interpreted Language:**\n", 27 | "- Python is an interpreted language, meaning that code execution occurs line by line, which allows for rapid development and testing.\n", 28 | "\n", 29 | "**Object-Oriented Programming (OOP):**\n", 30 | "- Python supports OOP principles, enabling developers to structure their code using classes, objects, and inheritance.\n", 31 | "\n", 32 | "**Dynamic Typing:**\n", 33 | "- Python uses dynamic typing, allowing variables to be assigned without explicitly declaring their data types.\n", 34 | "\n", 35 | "**Large Standard Library:**\n", 36 | "- Python comes with an extensive standard library that provides a wide range of modules and functions for various tasks, such as file I/O, networking, web development, and more.\n", 37 | "\n", 38 | "**Cross-Platform Compatibility:**\n", 39 | "- Python is available on multiple platforms, including Windows, macOS, Linux, and more, making it highly portable." 40 | ] 41 | }, 42 | { 43 | "cell_type": "markdown", 44 | "id": "e31ae6e3", 45 | "metadata": {}, 46 | "source": [ 47 | "### **Advantages and disadvantages of Python programming language.**\n", 48 | "\n", 49 | "**Readability and Ease of Use:**\n", 50 | "- Python's clean syntax and high readability make it easy to learn and understand, even for beginners.\n", 51 | "\n", 52 | "**Large and Active Community:**\n", 53 | "- Python has a large community of developers who contribute to its growth and provide support through online forums, tutorials, and libraries.\n", 54 | "\n", 55 | "**Vast Ecosystem of Libraries and Frameworks:**\n", 56 | "- Python offers an extensive collection of libraries and frameworks for various purposes, such as data analysis (NumPy, Pandas), web development (Django, Flask), machine learning (TensorFlow, scikit-learn), and more.\n", 57 | "\n", 58 | "**Rapid Prototyping and Development:**\n", 59 | "- Python's simplicity and expressiveness enable quick prototyping and development cycles, allowing developers to iterate and test ideas efficiently.\n", 60 | "\n", 61 | "**Integration and Extensibility:**\n", 62 | "- Python can easily integrate with other languages like C, C++, and Java, allowing developers to leverage existing code and libraries from different languages.\n", 63 | "\n", 64 | "**Scalability:**\n", 65 | "- Python supports scalable development through frameworks like Django, which provide robust solutions for building complex and scalable web applications." 66 | ] 67 | }, 68 | { 69 | "cell_type": "markdown", 70 | "id": "2771162a", 71 | "metadata": {}, 72 | "source": [ 73 | "### **Disadvantages of Python Programming Language.**\n", 74 | "\n", 75 | "**Performance:**\n", 76 | "- Python is an interpreted language, which can result in slower execution compared to compiled languages like C or C++. However, performance-critical sections can be optimized using libraries or by implementing critical sections in a lower-level language.\n", 77 | "\n", 78 | "**Global Interpreter Lock (GIL):**\n", 79 | "- Python's GIL allows only one thread to execute Python bytecode at a time, limiting the potential for true parallelism in certain scenarios, especially for CPU-bound tasks. However, Python provides mechanisms to work around this limitation, such as multiprocessing or using libraries designed for parallel computing.\n", 80 | "\n", 81 | "**Mobile Application Development:**\n", 82 | "- While Python can be used for mobile app development using frameworks like Kivy or BeeWare, it is not as commonly used as languages like Swift for iOS or Java/Kotlin for Android." 83 | ] 84 | }, 85 | { 86 | "cell_type": "markdown", 87 | "id": "4dd97424", 88 | "metadata": {}, 89 | "source": [ 90 | "### **Uses and application of Python programming language.** \n", 91 | "\n", 92 | "**Web Development:**\n", 93 | "- Python's web frameworks, such as Django and Flask, are widely used for building dynamic websites and web applications.\n", 94 | "\n", 95 | "**Data Analysis and Visualization:**\n", 96 | "- Python's libraries like NumPy, Pandas, and Matplotlib provide powerful tools for data manipulation, analysis, and visualization.\n", 97 | "\n", 98 | "**Machine Learning and Artificial Intelligence:**\n", 99 | "- Python is extensively used for machine learning tasks, thanks to libraries like TensorFlow, scikit-learn, PyTorch, and Keras.\n", 100 | "\n", 101 | "**Scripting and Automation:**\n", 102 | "- Python's simplicity and versatility make it an ideal choice for scripting tasks and automating repetitive tasks.\n", 103 | "\n", 104 | "**Scientific Computing:**\n", 105 | "- Python is used in scientific research and computational modeling due to its extensive scientific libraries, such as SciPy and Biopython.\n", 106 | "\n", 107 | "**DevOps and Infrastructure:**\n", 108 | "- Python is utilized for managing infrastructure and automating deployment tasks with tools like Ansible and Fabric.\n", 109 | "\n", 110 | "**Game Development:**\n", 111 | "- Python is employed in game development through libraries like Pygame, enabling developers to create 2D games and prototypes.\n", 112 | "\n", 113 | "**Internet of Things (IoT):** \n", 114 | "- Python's lightweight nature and availability of libraries like Raspberry Pi GPIO allow it to be used in IoT projects.\n" 115 | ] 116 | } 117 | ], 118 | "metadata": { 119 | "kernelspec": { 120 | "display_name": "Python 3 (ipykernel)", 121 | "language": "python", 122 | "name": "python3" 123 | }, 124 | "language_info": { 125 | "codemirror_mode": { 126 | "name": "ipython", 127 | "version": 3 128 | }, 129 | "file_extension": ".py", 130 | "mimetype": "text/x-python", 131 | "name": "python", 132 | "nbconvert_exporter": "python", 133 | "pygments_lexer": "ipython3", 134 | "version": "3.9.7" 135 | } 136 | }, 137 | "nbformat": 4, 138 | "nbformat_minor": 5 139 | } 140 | -------------------------------------------------------------------------------- /Python Fundamentals.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "id": "3241957e", 6 | "metadata": {}, 7 | "source": [ 8 | "### **Python Fundamentals.**\n", 9 | "\n", 10 | "**Python** is a popular programming language known for its simplicity and readability. It supports various programming techniques and falls under the category of high-level, interpreted languages.\n", 11 | "\n", 12 | "Here are some fundamental concepts in Python:\n", 13 | "\n", 14 | "**Variables:**\n", 15 | "- In Python, variables are used to store values. You can define a variable by assigning a value to it using the '=' operator.\n", 16 | "\n", 17 | "For example:\n", 18 | "\n", 19 | "```python\n", 20 | "\n", 21 | "name = \"John\"\n", 22 | "age = 25\n", 23 | "\n", 24 | "```\n", 25 | "\n", 26 | "**Comments:**\n", 27 | "- Comments are used to add explanatory notes to the code. They are ignored by the interpreter. In Python, you can write single-line comments using the '#' symbol and multi-line comments using triple quotes (''' '''). \n", 28 | "\n", 29 | "For example:\n", 30 | "\n", 31 | "```python \n", 32 | "\n", 33 | "# This is a single-line comment\n", 34 | "\n", 35 | "'''\n", 36 | "This is a\n", 37 | "multi-line comment (This is called docstring in Python, not excecuted unless when called)\n", 38 | "'''\n", 39 | "\n", 40 | "```\n", 41 | "\n", 42 | "**Keywords:** \n", 43 | "- Python has a set of reserved words called keywords that have predefined meanings in the language. Examples of keywords include 'if', 'else', 'for', 'while', 'def', 'class', etc. You cannot use keywords as identifiers (variable names).\n", 44 | "\n", 45 | "**Identifiers:**\n", 46 | "- Identifiers are names given to entities such as variables, functions, classes, etc. \n", 47 | "\n", 48 | "In Python, identifiers must follow certain rules:\n", 49 | "\n", 50 | "- They can contain letters (a-z, A-Z), digits (0-9), and underscores (_).\n", 51 | "- They cannot start with a digit.\n", 52 | "- They are case-sensitive (e.g., 'name' and 'Name' are different identifiers).\n", 53 | "\n", 54 | "**Literals:**\n", 55 | "- Literals are raw values used in the code. Examples include string literals (\"hello\"), numeric literals (25, 3.14), boolean literals (True, False), and more.\n", 56 | "\n", 57 | "**Built-in Functions:**\n", 58 | "- Python provides a rich set of built-in functions that are readily available for use. One of the most commonly used functions is print(), which is used to display output to the console.\n", 59 | "\n", 60 | "For example:\n", 61 | "\n", 62 | "```python\n", 63 | " print(\"Hello, world!\")\n", 64 | "```\n", 65 | "\n", 66 | "**Operators:**\n", 67 | "- Python supports various operators for performing operations on variables and values. Some common operators include arithmetic operators (+, -, *, /), assignment operators (=, +=, -=), comparison operators (==, !=, >, <), logical operators (and, or, not), and more.\n", 68 | "\n", 69 | "**PEP8:**\n", 70 | "- PEP8 is a style guide for Python code, which suggests guidelines and conventions to improve code readability and maintainability. It covers aspects such as indentation, line length, naming conventions, and more. Adhering to PEP8 helps in writing clean and consistent Python code." 71 | ] 72 | }, 73 | { 74 | "cell_type": "markdown", 75 | "id": "c917509e", 76 | "metadata": {}, 77 | "source": [ 78 | "These are just some of the fundamental concepts in Python programming. Python offers many more features and libraries that make it a versatile language for various applications" 79 | ] 80 | }, 81 | { 82 | "cell_type": "code", 83 | "execution_count": 2, 84 | "id": "6dc80cfe", 85 | "metadata": {}, 86 | "outputs": [ 87 | { 88 | "name": "stdout", 89 | "output_type": "stream", 90 | "text": [ 91 | "John 25\n" 92 | ] 93 | } 94 | ], 95 | "source": [ 96 | "#Varaibles:\n", 97 | "name = \"John\"\n", 98 | "age = 25\n", 99 | "\n", 100 | "print(name, age)" 101 | ] 102 | }, 103 | { 104 | "cell_type": "code", 105 | "execution_count": 3, 106 | "id": "39a9ac89", 107 | "metadata": {}, 108 | "outputs": [ 109 | { 110 | "data": { 111 | "text/plain": [ 112 | "'\\nThis is a\\nmulti-line comment\\n'" 113 | ] 114 | }, 115 | "execution_count": 3, 116 | "metadata": {}, 117 | "output_type": "execute_result" 118 | } 119 | ], 120 | "source": [ 121 | "#Comment In Python \n", 122 | "\n", 123 | "# This is a single-line comment\n", 124 | "\n", 125 | "'''\n", 126 | "This is a\n", 127 | "multi-line comment\n", 128 | "'''" 129 | ] 130 | } 131 | ], 132 | "metadata": { 133 | "kernelspec": { 134 | "display_name": "Python 3 (ipykernel)", 135 | "language": "python", 136 | "name": "python3" 137 | }, 138 | "language_info": { 139 | "codemirror_mode": { 140 | "name": "ipython", 141 | "version": 3 142 | }, 143 | "file_extension": ".py", 144 | "mimetype": "text/x-python", 145 | "name": "python", 146 | "nbconvert_exporter": "python", 147 | "pygments_lexer": "ipython3", 148 | "version": "3.9.7" 149 | } 150 | }, 151 | "nbformat": 4, 152 | "nbformat_minor": 5 153 | } 154 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | ## **Python BoootCamp by Lux Academy and Data Science East Africa Guide.** 2 | 3 | --- 4 | This is the Python3 BoootCamp by [Lux Academy](https://twitter.com/lux_academy) and [Data Science East Africa](https://twitter.com/DSEAfrica) learners guide.To add a question to this list, please submit an [issue](https://github.com/HarunMbaabu/Python-BoootCamp-Guide/issues), or fork this repo and submit a pull request. 5 | 6 | --- 7 | 8 | - **What is Python?** 9 | 10 | Python is an interpreted, high-level language created by Guido van Rossum and released in 1991.It is dynamically typed and garbage collected. 11 | Python programs have the extension .py and can be run from the command line by typing python file_name.py. 12 | 13 | 14 | --- 15 | - **Modern Python Road Map** 16 | 17 | 18 | --- 19 | 20 | Probably its most noticeable characteristic is its use of significant white space to delimit code blocks, instead of the more popular {} symbols. 21 | End-of-line semicolons (;) are optional and usually not used in Python. Python becomes the best solution in many domains from web applications, data analysis, data science, machine learning, and AI. 22 | 23 | --- 24 | ### **Here is a full curriculum for learning Python programming language:** 25 | 26 | --- 27 | **1 - AN OVERVIEW OF PYTHON** 28 | - What is python programming language? 29 | - Common Feature Provided By python. 30 | - Advantages and disadvantages of Python programming language. 31 | - Uses and application of Python programming language. 32 | 33 | [Link to Python Overview NoteBook ](https://github.com/HarunMbaabu/Python-BoootCamp-Guide/blob/main/AN%20OVERVIEW%20OF%20PYTHON.ipynb) 34 | 35 | --- 36 | **2 - THE PYTHON ENVIRONMENT** 37 | - Starting Python programming language, setting up the environment, for windows, Unix and MacOS. 38 | - Different methods for executing Python code and programs. 39 | --- 40 | 41 | **3 - GETTING STARTED: Python fundamentals.** 42 | - Python as a programming language , programming techniques supported python programming language and it’s programming language category. 43 | - Variables, defining and using variables in python programming language. 44 | - Comments, keywords, identifiers, rules to follow when defining identifiers literals. 45 | - Built-in functions in python programming language like print( … ) 46 | - Operators in python programming language. 47 | - PEP8 rules and standards in Python programming language. 48 | 49 | --- 50 | **Project 1:** This project tests the mastery of Python basics, these include, what python is, uses and applications of python programming language, types of programming techniques that python supports, variables, keywords, identifiers, literals, type conversion, operators and ability to execute an run python program and code on different environment. 51 | 52 | --- 53 | 54 | 55 | 4 - FLOW CONTROL AND DECISION MAKING IN PYTHON 56 | - Introduction to flow control and decision making in python programming language. 57 | - Indentation and white space in python 58 | - Conditional statements and expressions in python. 59 | - Loops in Python programming language 60 | - Relational and boolean operators and their application in decision making in python. 61 | 62 | --- 63 | **Project 2:** The second projects aims to test the mastery content covered on the past two chapters, covered so far, first aims to ensure retention of all the information from section one (Python fundamentals) and test the ability to build on top of Python fundamentals to integrate decision making and flow control to solve real world problems using Python programming language. 64 | 65 | --- 66 | **5 - INTRODUCTION TO DATA STRUCTURES: PYTHON BUILT-IN DATA STRUCTURES** 67 | - Differences between data types and data structures in Python programming language. 68 | - Introduction to lists and list methods and operations. 69 | - Introduction to tuples in python and tuple methods and operations. 70 | - Introduction dictionary in python and tuple methods and operations. 71 | - Introduction to sets, methods and operations that we can perform on sets. 72 | - Application and use cases of the above data structures in real world problems. 73 | - Indexing and slicing in Python programming language. 74 | 75 | --- 76 | **Project 3:** This will focus on testing the mastery of built in data types in python, methods and operations that we can perform on Python programming language, and how to build real world applications using the content covered so far. 77 | 78 | --- 79 | 80 | 6 - FUNCTIONS 81 | - What are functions , defining and calling functions in the Python programming language? 82 | - Scope, parameters and arguments in python programming language. 83 | - Recursive and lambda functions in Python programming functions. 84 | - Nested function in Python programming language. 85 | - Decorators in Python programming language. 86 | 87 | --- 88 | **Project 4:** This project is aims to see if you can write functions comfortably, these includes recursive functions that calls themselves and incorporating loops and conditional statements inside functions, it will also test if you have mastered different scopes in python and the difference between arguments and parameters 89 | 90 | --- 91 | **7 - CLASSES IN PYTHON** 92 | - Introduction to classes in Python. 93 | - Defining classes in python 94 | - Constructors and methods in python 95 | - Instance data 96 | - Properties, class methods and data 97 | 98 | --- 99 | **Project 5:** This project will involve creating classes and objects and methods and functions in classes. 100 | 101 | --- 102 | **8 - ERRORS AND EXCEPTION HANDLING** 103 | - Syntax errors 104 | - Exceptions 105 | - Using try/catch/else/finally 106 | - Handling multiple exceptions 107 | - Ignoring exceptions 108 | 109 | --- 110 | **Project 6:** This will focus on testing if you can correct bugs and refact your python code without breaking the functionality. 111 | 112 | --- 113 | **9 - WORKING WITH FILES** 114 | - File overview 115 | - Opening a text file 116 | - Reading a text file 117 | - Writing to a text file 118 | - Reading and writing raw (binary) data 119 | - Converting binary data with struct 120 | --- 121 | **Project 7:** This project aims to test if you can handle files using Python programming language, this is opening files, writing on it save and close. 122 | 123 | --- 124 | **10 - MODULES AND PACKAGES** 125 | - The import statement 126 | - Module search path 127 | - Creating Modules 128 | - Using packages 129 | - Function and Module aliases 130 | --- 131 | **Project 8:** This project tests if you can install and import packages and the best packages handling practices. 132 | 133 | --- 134 | **11 - REGULAR EXPRESSIONS IN PYTHON** 135 | - RE syntax overview 136 | - RE Objects 137 | - Searching and matching 138 | - Compilation flags 139 | - Groups and special groups 140 | - Replacing text 141 | - Splitting strings 142 | --- 143 | **Project 9:** Project 9 tests if you can perform regular expressions using python, for instance getting a character from a file or text document. 144 | 145 | --- 146 | **12 - NETWORK SERVICES** 147 | Grabbing web content, Sending email and Using SSH for remote access 148 | 149 | **Project 7:** This project tests if you have mastered the application of python in networking services like creating scripts and programs using python programming language that can send emails or perform web scraping . 150 | 151 | --- 152 | **Final Project: Capstone Projects.** 153 | These are two projects that test everything Python related to prepare you for any python related field, this might me, Python for data science and machine learning or python for web development. These projects will get you ready for junior python developers roles. 154 | —-- 155 | Here you are comfortable to specialize into Python for Data Science or for Web development. 156 | 157 | 158 | 159 | --- 160 | #### **What Is Python** 161 | 162 | ![image](https://user-images.githubusercontent.com/51136314/169713121-418f5164-b538-4c99-8b19-500a9b229690.png) 163 | 164 | Python is an interpreted, high-level language created by Guido van Rossum and released in 1991. It is dynamically typed and garbage collected. 165 | 166 | Python programs have the extension .py and can be run from the command line by typing python file_name.py. 167 | 168 | Probably its most noticeable characteristic is its use of significant white space to delimit code blocks, instead of the more popular {} symbols. 169 | 170 | End-of-line semicolons (;) are optional and usually not used in Python. 171 | 172 | Python becomes the best solution in many domains from web applications, data analysis, data science, machine learning, and AI. 173 | 174 | 175 | --- 176 | #### **Common Feature Provided By python.** 177 | 178 | - Simplicity: Think less of the syntax of the language and more of the code. 179 | 180 | - Open Source: A powerful language and it is free for everyone to use and alter as needed. 181 | 182 | - Portability: Python code can be shared and it would work the same way it was intended to. Seamless and hassle-free. 183 | 184 | - Being Embeddable & Extensible: Python can have snippets of other languages inside it to perform certain functions. 185 | 186 | - Being Interpreted: The worries of large memory tasks and other heavy CPU tasks are taken care of by Python itself leaving you to worry only about coding. 187 | 188 | - Huge amount of libraries: Data Science? Python has you covered. Web Development? Python still has you covered. 189 | 190 | - Object Orientation: Objects help breaking-down complex real-life problems into such that they can be coded and solved to obtain solutions. 191 | 192 | --- 193 | #### **Advantages and disadvantages of Python programming language.** 194 | **Advantages of Python.** 195 | - Easy to use and learn: For beginners, Python is straightforward to use. It is a high-level programming language, and its syntax is like the English language. These reasons make the language easy to learn and adapt to. Compared to Java and C, in Python, the same task can be performed using fewer lines of code. As a result of its easy learning, the principles in Python can be executed faster compared to other languages. 196 | 197 | - Increased productivity: Python is a very productive language. The simple nature of Python helps the developers to concentrate on solving the issues in it. To understand the syntax and behavior of the programming language, the users do not have to spend hours, so more work is done. 198 | 199 | - Flexibility: This language is very flexible, and hence it allows the user to try new things. The users can develop new sorts of the application using Python programming language. The language does not restrict the user from trying something different. Other programming languages do not provide this type of flexibility and freedom, and hence Python is more preferred in these matters. 200 | 201 | - Extensive library: Python provides the user with a vast library. Python’s standard library is massive, and just about every function one needs to perform is available in its library. This is because it has a hugely supportive community and corporate sponsorship. External libraries are not used by users while working with Python. 202 | 203 | 204 | - Supportive community: The Python language was created years ago, and hence it has a mature community that can support every type of developer, starting from beginners’ level to expert level. There are enough guides, tutorials, and documentation available on the Python programming language, which helps the developers to understand the language faster and better. Because of its supportive community, Python has rapid growth compared to other languages. 205 | 206 | 207 | **Disadvantages of Python** 208 | 209 | - Speed: Compared to Java or C, the rate of Python is slower. Python is an interpreted language that is dynamically typed. For the execution of a code, each line of the code needs to be explicitly ordered since the language gets interpreted. This is time-consuming, and hence it slows down the process of execution. The dynamic structure of Python also slows its speed because while executing the code, the excess work also needs to be completed. Therefore, in cases where fast acceleration is required, Python is not used there very commonly. 210 | 211 | - Memory consumption: Python has a very high memory consumption. This is because it is flexible to the data types. It uses large amounts of memory. Python is not a good choice for tasks where the user wants to optimize memory, i.e., a memory-intensive language. 212 | 213 | - Mobile development: Python is strong in server platforms and desktops, and hence it is a fantastic server-side programming language. But it is not appropriate for mobile development. For mobile development, Python is a fragile language. Since it is not memory efficient and has a prolonged power for processing, due to these reasons, Python does not have many built-in mobile applications. Carbonnelle is a built-in application present in Python. 214 | 215 | - Database access: Python provides easy programming. However, when it interacts with the database, some issues arise. Compared to technologies like JDBC and ODBC, which are pretty famous, the database access layer of the Python programming language is primitive and underdeveloped. Large enterprises that usually need smooth interaction with complex legacy data do not prefer the usage of Python. 216 | 217 | - Runtime errors: The users of Python mentioned various issues they faced with the language design. Since the language of Python is dynamically typed, there can be changes in the data type of a variable at any time. Therefore, it needs to be tested more often, and also, there are errors in the language displayed during runtime. 218 | 219 | - Simplicity: Python is a straightforward and easy-to-use programming language which is also a disadvantage of the language. The users of Python get so accustomed to its easy syntax and extensive library feature that they face issues while learning other programming languages. Some users also feel that the Java codes are unnecessary due to their complexity. Therefore, Python has a very vulnerable nature, and the users start taking everything lightly. 220 | 221 | --- 222 | #### **Applications of Python.** 223 | - Artificial Intelligence 224 | - Desktop Application 225 | - Automation 226 | - Web Development 227 | - Data Wrangling, Exploration And Visualisation. 228 | 229 | 230 | ## **Reference:** 231 | - **W3Schools Python Tutorial:** https://www.w3schools.com/python/ 232 | - **Python Tutorial .net:** https://www.pythontutorial.net/ 233 | - **Learn Python Programming by Programiz:** https://www.programiz.com/python-programming 234 | - **Python Full Course for Beginners by Mosh:** https://youtu.be/_uQrJ0TkZlc 235 | 236 | 237 | 238 | --------------------------------------------------------------------------------