Learn Python AIML
Python Programming Language – Introduction
Python tutorial provides basic and advanced concepts of Python. Our Python tutorial is designed for beginners and professionals. Python is a simple, general purpose, high level, and object-oriented programming language. Python is an interpreted scripting language also. Guido Van Rossum is known as the founder of Python programming.
Python includes all topics of Python Programming such as installation, control statements, Strings, Lists, Tuples, Dictionary, Modules, Exceptions, Date and Time, File I/O, Programs, etc. There are also given Python interview questions to help you better understand Python Programming.
What is Python?
Python is a general-purpose, dynamic, high-level, and interpreted programming language. It supports Object Oriented programming approach to develop applications. It is simple and easy to learn and provides lots of high-level data structures.
Python is an easy-to-learn yet powerful and versatile scripting language, which makes it attractive for Application Development.
With its interpreted nature, Python’s syntax and dynamic typing make it an ideal language for scripting and rapid application development.
Python supports multiple programming patterns, including object-oriented, imperative, and functional or procedural programming styles.
Python is not intended to work in a particular area, such as web programming. It is a multipurpose programming language because it can be used with web, enterprise, 3D CAD, etc.
We don’t need to use data types to declare variable because it is dynamically typed, so we can write a=10 to assign an integer value in an integer variable.
Python makes development and debugging fast because no compilation step is included in Python development, and the edit-test-debug cycle is very fast.
Python has many web-based assets, open-source projects, and a vibrant community. Learning the language, working together on projects, and contributing to the Python ecosystem are all made very easy for developers.
Because of its straightforward language framework, Python is easier to understand and write code in. This makes it a fantastic programming language for novices. Additionally, it assists seasoned programmers in writing clearer, error-free code.
Python is an open-source, cost-free programming language. It is utilized in several sectors and disciplines as a result.
In Python, code readability and maintainability are important. As a result, even if the code was developed by someone else, it is easy to understand and adapt by some other developer.
Python has many third-party libraries that can be used to make its functionality easier. These libraries cover many domains, for example, web development, scientific computing, data analysis, and more.
Why Python Programming?
Every programming language serves some purpose or use-case according to a domain, and Python is no exception. An introduction to Python programming can help us understand the purpose of the language. For example, Python is widely used in data science, machine learning, and artificial intelligence due to its simplicity and powerful libraries. Similarly, JavaScript is the most popular language among web developers as it gives the developer the power to handle applications via different frameworks like React, Vue, Angular, which are used to build beautiful user interfaces. Similarly, they have pros and cons at the same time. so if we consider python it is general-purpose which means it is widely used in every domain the reason is it’s very simple to understand, scalable because of which the speed of development is so fast. Now you get the idea why besides learning python it doesn’t require any programming background so that’s why it’s popular amongst developers as well. Python has simpler syntax similar to the English language and also the syntax allows developers to write programs with fewer lines of code. Since it is open-source there are many libraries available that make developers’ jobs easy ultimately results in high productivity. They can easily focus on business logic and Its demanding skills in the digital era where information is available in large data sets.
IEEE spectrum list of top programming language 2021. The list of programming languages is based on popularity.
Python Basic Syntax
There is no use of curly braces or semicolon in Python programming language. It is English-like language. But Python uses the indentation to define a block of code. Indentation is nothing but adding whitespace before the statement when it is needed. For example –
def func():
statement 1
statement 2
…………………
…………………
statement N
In the above example, the statements that are the same level to the right belong to the function. Generally, we can use four whitespaces to define indentation.
Instead of Semicolon as used in other languages, Python ends its statements with a NewLine character.
Python is a case-sensitive language, which means that uppercase and lowercase letters are treated differently. For example, ‘name’ and ‘Name’ are two different variables in Python.
In Python, comments can be added using the ‘#’ symbol. Any text written after the ‘#’ symbol is considered a comment and is ignored by the interpreter. This trick is useful for adding notes to the code or temporarily disabling a code block. It also helps in understanding the code better by some other developers.
‘If’, ‘otherwise’, ‘for’, ‘while’, ‘try’, ‘except’, and ‘finally’ are a few reserved keywords in Python that cannot be used as variable names. These terms are used in the language for particular reasons and have fixed meanings. If you use these keywords, your code may include errors, or the interpreter may reject them as potential new Variables.
Why learn Python?
Python provides many useful features to the programmer. These features make it the most popular and widely used language. We have listed below few-essential features of Python.
- Easy to use and Learn: Python has a simple and easy-to-understand syntax, unlike traditional languages like C, C++, Java, etc., making it easy for beginners to learn.
- Expressive Language: It allows programmers to express complex concepts in just a few lines of code or reduces Developer’s Time.
- Interpreted Language: Python does not require compilation, allowing rapid development and testing. It uses Interpreter instead of Compiler.
- Object-Oriented Language: It supports object-oriented programming, making writing reusable and modular code easy.
- Open Source Language: Python is open source and free to use, distribute and modify.
- Extensible: Python can be extended with modules written in C, C++, or other languages.
- Learn Standard Library: Python’s standard library contains many modules and functions that can be used for various tasks, such as string manipulation, web programming, and more.
- GUI Programming Support: Python provides several GUI frameworks, such as Tkinter and PyQt, allowing developers to create desktop applications easily.
- Integrated: Python can easily integrate with other languages and technologies, such as C/C++, Java, and . NET.
- Embeddable: Python code can be embedded into other applications as a scripting language.
- Dynamic Memory Allocation: Python automatically manages memory allocation, making it easier for developers to write complex programs without worrying about memory management.
- Wide Range of Libraries and Frameworks: Python has a vast collection of libraries and frameworks, such as NumPy, Pandas, Django, and Flask, that can be used to solve a wide range of problems.
- Versatility: Python is a universal language in various domains such as web development, machine learning, data analysis, scientific computing, and more.
- Large Community: Python has a vast and active community of developers contributing to its development and offering support. This makes it easy for beginners to get help and learn from experienced developers.
- Career Opportunities: Python is a highly popular language in the job market. Learning Python can open up several career opportunities in data science, artificial intelligence, web development, and more.
- High Demand: With the growing demand for automation and digital transformation, the need for Python developers is rising. Many industries seek skilled Python developers to help build their digital infrastructure.
- Increased Productivity: Python has a simple syntax and powerful libraries that can help developers write code faster and more efficiently. This can increase productivity and save time for developers and organizations.
- Big Data and Machine Learning: Python has become the go-to language for big data and machine learning. Python has become popular among data scientists and machine learning engineers with libraries like NumPy, Pandas, Scikit-learn, TensorFlow, and more.
Where is Python used?
Python is a general-purpose, popular programming language, and it is used in almost every technical field. The various areas of Python use are given below.
- Data Science: Data Science is a vast field, and Python is an important language for this field because of its simplicity, ease of use, and availability of powerful data analysis and visualization libraries like NumPy, Pandas, and Matplotlib.
- Desktop Applications: PyQt and Tkinter are useful libraries that can be used in GUI – Graphical User Interface-based Desktop Applications. There are better languages for this field, but it can be used with other languages for making Applications.
- Console-based Applications: Python is also commonly used to create command-line or console-based applications because of its ease of use and support for advanced features such as input/output redirection and piping.
- Mobile Applications: While Python is not commonly used for creating mobile applications, it can still be combined with frameworks like Kivy or BeeWare to create cross-platform mobile applications.
- Software Development: Python is considered one of the best software-making languages. Python is easily compatible with both from Small Scale to Large Scale software.
- Artificial Intelligence: AI is an emerging Technology, and Python is a perfect language for artificial intelligence and machine learning because of the availability of powerful libraries such as TensorFlow, Keras, and PyTorch.
- Web Applications: Python is commonly used in web development on the backend with frameworks like Django and Flask and on the front end with tools like JavaScript and HTML.
- Enterprise Applications: Python can be used to develop large-scale enterprise applications with features such as distributed computing, networking, and parallel processing.
- 3D CAD Applications: Python can be used for 3D computer-aided design (CAD) applications through libraries such as Blender.
- Machine Learning: Python is widely used for machine learning due to its simplicity, ease of use, and availability of powerful machine learning libraries.
- Computer Vision or Image Processing Applications: Python can be used for computer vision and image processing applications through powerful libraries such as OpenCV and Scikit-image.
- Speech Recognition: Python can be used for speech recognition applications through libraries such as SpeechRecognition and PyAudio.
- Scientific computing: Libraries like NumPy, SciPy, and Pandas provide advanced numerical computing capabilities for tasks like data analysis, machine learning, and more.
- Education: Python’s easy-to-learn syntax and availability of many resources make it an ideal language for teaching programming to beginners.
- Testing: Python is used for writing automated tests, providing frameworks like unit tests and pytest that help write test cases and generate reports.
- Gaming: Python has libraries like Pygame, which provide a platform for developing games using Python.
- IoT: Python is used in IoT for developing scripts and applications for devices like Raspberry Pi, Arduino, and others.
- Networking: Python is used in networking for developing scripts and applications for network automation, monitoring, and management.
- DevOps: Python is widely used in DevOps for automation and scripting of infrastructure management, configuration management, and deployment processes.
- Finance: Python has libraries like Pandas, Scikit-learn, and Statsmodels for financial modeling and analysis.
- Audio and Music: Python has libraries like Pyaudio, which is used for audio processing, synthesis, and analysis, and Music21, which is used for music analysis and generation.
- Writing scripts: Python is used for writing utility scripts to automate tasks like file operations, web scraping, and data processing.
Python Popular Frameworks and Libraries
Python has wide range of libraries and frameworks widely used in various fields such as machine learning, artificial intelligence, web applications, etc. We define some popular frameworks and libraries of Python as follows.
- Web development (Server-side) – Django Flask, Pyramid, CherryPy
- GUIs based applications – Tk, PyGTK, PyQt, PyJs, etc.
- Machine Learning – TensorFlow, PyTorch, Scikit-learn, Matplotlib, Scipy, etc.
- Mathematics – Numpy, Pandas, etc.
- BeautifulSoup: a library for web scraping and parsing HTML and XML
- Requests: a library for making HTTP requests
- SQLAlchemy: a library for working with SQL databases
- Kivy: a framework for building multi-touch applications
- Pygame: a library for game development
- Pytest: a testing framework for Python
- Django REST framework: a toolkit for building RESTful APIs
- FastAPI: a modern, fast web framework for building APIs
- Streamlit: a library for building interactive web apps for machine learning and data science
- NLTK: a library for natural language processing
Pythone Vs Java which should we learn?
Python
Python is a high-level, interpreted programming language. It was invented back in 1991, by Guido Van Rossum. Python is an object-oriented programming language that has large enormous library support making the implementation of various programs and algorithms easy. Its language constructs and object-oriented approach aim to help programmers to write clear, logical code for various projects. The biggest strength of Python is its huge collection of standard libraries which can be used for the following:
- Machine Learning
- GUI Applications (like Kivy, Tkinter, PyQt, etc. )
- Web frameworks like Django (used by YouTube, Instagram, and Dropbox)
- Image processing (like OpenCV, Pillow)
- Web scraping (like Scrapy, BeautifulSoup, and Selenium)
- Test frameworks
- Multimedia
- Scientific computing
- Text processing and many more.
Java
Java is a high-level, object-oriented programming language that was originally developed by James Gosling at Sun Microsystems in 1995. Java has a syntax similar to C and C++ but with low-level difficulties. Java is platform-independent (WORA – Write Once Run Anywhere) meaning compiled java code can run on different platforms without recompilation. Java can be used to develop the following applications:
- Desktop GUI Applications
- Mobile Application
- Artificial intelligence
- Web applications
- Big Data technology
- Gaming applications
- Business applications
What is the future scope of ML and AI using the Python language?
- The future scope of AI and ML in python is very high. These two field are increasing rapidly over the past few years and will be the most important in the coming years.
- The most in demand job roles in this career is increasing at very high rate. There are various job opportunities for AI and ML professionals in the world.
- There is scope in developing machines in robotics, computer vision, language detection machine, game playing, expert systems, speech recognition machine and much more.
- Most of the human work is done by using AI and ML. With their use we can create machines which can solve human problems on their own without any human effort.
- Python is a very easy language to learn and is regarded as the best programming language in these fields because they are easy to code and has pre built libraries which help to write code faster and simpler.
PYTHON CHAPTERS
Chapter 1: Python Basics
Chapter 2: Loops & Functions
Chapter 3: Unit Tests & Classes
Chapter 4: Style Guides, Scripts, Imports
Chapter 5: Introduction to NumPy
Chapter 6: NumPy Implementation Details
Chapter 7: Introduction to Pandas
Chapter 8: Basic Data Wrangling With Pandas
Chapter 9: Advanced Data Wrangling With Pandas
Starting Course
After Intro
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