Python is a widely used popular programming language all over the world. It was created by Guido Van Rossum in 1991. It offers readable code, easier syntax, vast libraries and framework support to give developers an effective overall experience. With advancement in technology, Python has been the most used programming language, offering a high level of integrity with cutting edge technologies.
It is widely used for developing machine learning models, web development, software development, system scripting and much more. Let us learn some of the crucial highlights of the Python programming language in this article.
What is Python Programming Language?
Python is a versatile, high-level programming language known for its simplicity and readability. It was developed by Guido van Rossum and initially released in 1991. Python emphasizes code readability and simplicity, making it an excellent language for beginners and powerful enough for professionals.
Python is a multi-paradigm programming language. Object-oriented programming and structured programming are fully supported, and many features support functional programming and aspect-oriented programming.
Python is used in every field, from web development to artificial intelligence, and also from game development to data analytics. The beauty of Python is that the user can harness all its under-the-hood power using its straightforward and accessible syntax.
Characteristics of Python
Python’s simplicity, readability, and versatility have contributed to its widespread adoption and popularity in industry and academia. The features of the language are mentioned below in detail:
- Simple and Readable Syntax: The syntax in Python is designed to be clear and readable, making it easy for beginners to learn and understand code.
- Interpreted and Interactive: Python is an interpreted language, meaning that an interpreter executes code line by line, enabling interactive programming and rapid development.
- Dynamic Typing: Python is dynamically typed, meaning that variable types are determined at runtime, providing flexibility and ease of use.
- High-level Language: Python abstracts away many low-level details, allowing developers to focus on solving problems without worrying about memory management or system-level tasks.
- Large Standard Library: Python comes with a comprehensive standard library that provides modules and functions for a wide range of tasks, from file I/O to networking to regular expressions.
- Third-party Libraries and Ecosystems: Python has a vast ecosystem of third-party libraries and frameworks that extend its functionality for various domains, including web development, data science, and more.
- Platform Independence: Python is available on multiple platforms, including Windows, macOS, Linux, and various Unix-like operating systems, making it highly portable.
- Object-oriented Programming (OOPs): Python supports object-oriented programming, allowing developers to create reusable and modular code through classes and objects.
- Support for Functional Programming: Python also supports functional programming paradigms, including higher-order functions, lambda expressions, and list comprehensions.
- Community Support: Python has a large and active community of developers who contribute to its development, provide support through forums and online resources, and create educational materials to help others learn.
Key Takeaways: What is in the box with Python?
- Python offers readability, concise code and indentation to help create optimized programs.
- Python can handle machine learning algorithms with powerful libraries and frameworks.
- It can easily create web applications on a server.
- It can connect with database systems and implement modifications and updates.
- It can be used to handle big data and in data science and data analysis processes.
- It is used for software development and much more.
Python is the Core of the Trending Tech
There is no trend in the computer science and data engineering worlds more than big data, cloud computing, and machine learning, and Python is right at the core of these movements.
Python has a vast ecosystem of libraries and frameworks that extend its functionality for various purposes. The Python Package Index (PyPI) contains thousands of open-source packages covering a wide range of domains, including scientific computing, web development, machine learning, natural language processing, and more. Some of the most popular libraries and frameworks in Python are:
|
Fundamental Libraries in Python |
|
| Library | Description |
| NumPy |
|
| Pandas |
|
| Matplotlib |
|
| Scikit-learn |
|
| TensorFlow |
|
| Beautiful Soup |
|
Utilization of Python in Different Fields
Python is a versatile programming language with a wide range of uses across various domains. Its versatility, ease of use, and a large ecosystem of libraries and frameworks make it a popular choice for developers worldwide.
Here are some of the uses of the Python programming language in variable fields:
- Web Development– Python is used to create web apps and webpages. Frameworks like Django and Flask provide tools and libraries for building scalable and secure web applications.
- Data Science and Machine Learning– Python is popular in the field of data science and machine learning due to libraries like NumPy, Pandas, SciPy, and sci-kit-learn. These libraries provide tools for data manipulation, analysis, visualization, and machine learning model development.
- Artificial Intelligence– Python is widely used in artificial intelligence and deep learning projects. Libraries like TensorFlow, Keras, and PyTorch provide tools for building and training neural networks and other AI models.
- Scientific Computing- Python is used extensively in scientific computing and computational science for tasks such as simulation, modelling, and data analysis. Libraries like SciPy and Matplotlib are commonly used for these purposes.
- Automation and Scripting- Python is well-suited for automating repetitive tasks and writing scripts for various purposes, such as system administration, file manipulation, and data processing.
- Game Development– Python is used in game development, both for scripting and building game engines. Libraries like Pygame provide tools for developing 2D games, while other frameworks like Unity support Python scripting for game development.
- Educational Purposes- Python is often used as a teaching language in educational settings due to its simplicity and readability. It is used to introduce programming concepts to beginners and is widely used in computer science education.
Major Data Types Used in Python
There are different primitive data types in Python programming language. The data types in Python not only include int, float, and str, but also consist of frozen set, byte array, and many more. A brief analysis of the data types in Python is mentioned below:
|
Data Types in Python Programming Language |
|
| Data Type | Description |
| Integer (int) | It is a data type with all the integer values without the decimal parts |
| float | Float is an absolute value which contains both integers as well as the decimal points |
| complex | The complex data type is a special data type that contains the imaginary as well as the real part of the value. The imaginary value consists of i (iota). |
| String (str) | The string is a group of characters that forms a word. Strings are stored by adding double inverted commas |
| boolean (bool) | Bool is a data type that consists of only the boolean values that are 0 and 1, true or false, and On or off. |
| list | The list is a collection of data, these are stored using the square brackets |
| tuple | These are also the collection of data, which are stored using round brackets |
| dictionary (dict) | Special data types have descriptions of different key values |
| set | Set is a collection of unique data which can be changed and are unordered |
| NoneType | This is a data type that consists of null values or zeroes |
| bytes | These are the sequences of bytes that cannot be edited or manipulated |
| byte array | These are the sequences of bytes that can be edited. |
How to Add Comments in Python
Comments are statements that are only visible to the developers and do not participate in the functionalities of the code. The comments make it easy for the developers to locate a particular block of code with specific functionalities. The comments in Python can be added by the following ways:
- There are two types of comments in Python, including single-lined comments and multi-line comments.
- For adding a single-lined comment in Python, the hashtag is used in front of the comment.
| #This is a single-lined comment
print(“Hello World”) #this is a single-lined comment |
- For adding multi-lined comments in Python, double inverted commas are utilized three times before and after the comment.
| “””
This a multi-line comment It spans multiple lines “”” print(“Hello World”) |
Cons of Python programming language
While Python is a powerful and versatile programming language with many advantages, it also has some limitations and drawbacks. Here are some of the cons of Python:
- Python is an interpreted language, which can make it slower compared to compiled languages like C or C++. This can be a limitation for performance-critical applications or when dealing with large-scale computational tasks.
- Python’s Global Interpreter Lock (GIL) can hinder performance in multithreaded applications by allowing only one thread to execute Python bytecodes at a time. This can limit the benefits of multithreading for CPU-bound tasks.
- Python’s packaging ecosystem can be complex, especially when managing dependencies for projects with multiple libraries and versions. Dependency conflicts and compatibility issues can arise, making package management challenging.
- While Python provides support for multithreading and multiprocessing, its support for parallelism is limited compared to other languages like Julia or Go. This can be a limitation for highly parallelized tasks.
Artificial Intelligence with Python
AI is making revolutionary changes in technology with most businesses adopting it to make their processes more effective and optimized. With the power of AI, machines are becoming smarter. Even Python frameworks and libraries can be integrated with AI to make more effective and automated tools. There are many libraries in Python which can help in building complex algorithms and implementation, such as TensorFlow, Keras, Genism, OpenCV, etc.
With the integration of AI, more powerful problem-solving methods and informed decision-making can be done. There is a wide range of advancements which artificial intelligence will be making in the field of technology. Making the best use of AI to make our work effective is important. Let us learn more about Generative AI to dive deep into the subject.
Deocode DSA With Python
Enroll in our Decode DSA with Python Program to learn programming along with data structures and algorithms with our interactive classes and hands-on practical learning. With this course, you will get guidance from top industry experts and seamless doubt support throughout the course,. Learn with industry-relevant projects and complete quizzes, assignments and assessments to obtain completion certifications and much more only at pwskills.com.
Python Programming Language FAQs
Q1. Why is Python called Python?
Ans. Python is named after the British comedy group Monty Python, specifically the television show “Monty Python’s Flying Circus," which aired during the late 1960s and early 1970s. The name Python not only reflects Guido van Rossum’s fondness for Monty Python but also captures the playful and approachable spirit of the language.
Q2. What is the difference between Python and C?
Ans. Python is an interpreted programming language, whereas C is a compiled programming language. Python has a simpler and more readable syntax compared to C. Python handles memory management automatically through garbage collection, while C requires manual memory management.
Q3. Where did Python come from?
Ans. Python was developed by Guido van Rossum on February 20, 1991. A detailed analysis of the Python programming language is mentioned above in the article.
