1.8 Why Python?
3 min read•june 24, 2024
, created by , draws inspiration from , inheriting its focus on readability and simplicity. It improves upon ABC with features like and , making it more versatile and efficient for developers.
As an language, Python's growth is fueled by global collaboration. Its extensive and third-party packages cover a wide range of applications, from data analysis to web development, contributing to its popularity across various domains.
Python's Origins and Popularity
Influence of ABC on Python
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- Python's creator Guido van Rossum worked on developing ABC before creating Python
- ABC was a general-purpose programming language developed in the 1980s that emphasized code readability and simplicity
- Python inherited several key features from ABC such as the use of to define code blocks, high-level data types like lists and dictionaries, and an emphasis on code readability and simplicity
- Python aimed to address some of ABC's limitations by adding support for exception handling, incorporating modules for code organization and reuse, and implementing more efficient memory management
Open-source nature of Python
- Python is an open-source programming language, meaning its source code is freely available for anyone to view, modify, and distribute under a permissive
- Python's open-source nature has contributed to its widespread adoption and growth by encouraging collaboration and contributions from a global community of developers and enabling the creation of a vast ecosystem of libraries and frameworks
- Python's standard library is extensive and well-maintained, providing a wide range of built-in modules for various tasks that are continuously updated and expanded by the Python community
- Third-party packages extend Python's functionality with numerous libraries available for specific domains such as data analysis (, ) and web development (, ) that are easily installable using package managers like
Python vs other languages
- Python consistently ranks among the most popular programming languages in industry metrics such as the where it often holds a top position, where it frequently appears in the top 5, and where it is one of the most used languages on the platform
- Python's popularity has been steadily increasing over the years, attributed to its simplicity, versatility, and large community support
- Compared to other popular languages:
- Python's popularity has surpassed Java in recent years due to its simplicity and rapid development capabilities
- Python and JavaScript often compete for the top spot, with JavaScript's dominance in web development keeping it highly popular
- Python is more popular than C/C++ for general-purpose programming and scripting, while C/C++ remain dominant in system programming and performance-critical applications
- Python's popularity spans various domains including data analysis and scientific computing (NumPy, Pandas, SciPy), machine learning and artificial intelligence (, , ), web development (Django, Flask, ), and scripting and automation where it is used extensively for system administration and DevOps tasks
Key Features of Python
- Python is an , which means code can be executed directly without the need for compilation, facilitating rapid development and debugging
- It supports , allowing variables to change types during runtime, which increases flexibility in programming
- Python is a language, abstracting many low-level details and making it easier for developers to focus on problem-solving
- is a significant advantage of Python, as code written on one operating system can typically run on others without modification
- Python supports multiple programming paradigms:
- , allowing developers to create and use classes and objects
- , supporting first-class functions and other functional programming concepts
Key Terms to Review (28)
ABC: ABC is a fundamental concept in programming that refers to the basic building blocks of object-oriented programming. It stands for Abstraction, Encapsulation, and Polymorphism, which are the three key principles that underlie the object-oriented paradigm. These principles enable programmers to create complex and modular software systems by breaking down problems into smaller, manageable components.
Cross-Platform Compatibility: Cross-platform compatibility refers to the ability of software, hardware, or a computing environment to function seamlessly across multiple operating systems or platforms without the need for significant modifications or adaptations. It is a crucial consideration in software development and technology selection, ensuring that applications, tools, and devices can be used effectively by a wide range of users regardless of their chosen platform.
Django: Django is a high-level Python web framework that enables rapid development of secure and maintainable websites. It was designed to simplify the process of building complex, database-driven web applications, providing a comprehensive set of tools and features to streamline the development lifecycle.
Dynamic Typing: Dynamic typing is a programming language feature where the type of a variable is determined at runtime, rather than at compile-time. This means that variables in dynamically-typed languages can hold values of any data type, and the type can change during the program's execution.
Exception Handling: Exception handling is a programming construct that allows a program to gracefully manage and respond to unexpected or exceptional situations that may arise during the execution of a program. It provides a structured way to handle errors, unexpected inputs, or other exceptional conditions, preventing the program from crashing or behaving unexpectedly.
FastAPI: FastAPI is a modern, fast (high-performance), web framework for building APIs with Python. It is designed to be efficient, easy to use, and scalable, making it a popular choice for building RESTful APIs and microservices.
Flask: Flask is a lightweight, open-source web framework for Python that is used to build web applications. It is designed to be easy to use and get started with, making it a popular choice for developers who are new to web development or want to quickly build and deploy web applications.
Functional Programming: Functional programming is a programming paradigm that emphasizes the use of pure functions, where the output of a function depends solely on its input, without modifying any external state. This approach promotes code that is more declarative, modular, and easier to reason about, making it a powerful tool for solving complex problems in a wide range of applications, including in the context of Python programming.
GitHub Octoverse: GitHub Octoverse is an annual report published by GitHub that provides insights into the global software development community. It analyzes trends, technologies, and contributions across the GitHub platform, offering a comprehensive view of the evolving landscape of software development.
Guido van Rossum: Guido van Rossum is the creator of the Python programming language, a widely-used and influential high-level language known for its simplicity, readability, and versatility in a variety of applications, including data science and analysis.
High-Level Programming: High-level programming refers to programming languages that are designed to be more human-readable and abstracted from the underlying computer hardware. These languages provide a higher level of abstraction, making it easier for programmers to focus on the logic and functionality of their applications rather than the low-level details of the computer's operation.
Indentation: Indentation refers to the consistent spacing or alignment of code elements, typically achieved through the use of whitespace characters like spaces or tabs. It is a fundamental aspect of code formatting that enhances readability and helps convey the logical structure of a program.
Interpreted Language: An interpreted language is a type of programming language where the source code is executed directly by an interpreter, rather than being compiled into machine-readable binary code. This allows for dynamic, interactive, and rapid development, making interpreted languages well-suited for tasks such as scripting, data analysis, and rapid prototyping.
Modules: Modules are self-contained units of code in Python that encapsulate related functions, classes, and variables. They provide a way to organize and reuse code, making it easier to develop and maintain complex applications.
NumPy: NumPy is a powerful open-source library for numerical computing in Python, providing support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. It is a fundamental library for scientific computing in Python, and its efficient implementation and use of optimized underlying libraries make it a crucial tool for data analysis, machine learning, and a wide range of scientific and engineering applications.
Object-Oriented Programming: Object-Oriented Programming (OOP) is a programming paradigm that focuses on creating objects, which are instances of classes, to represent and manipulate data. It emphasizes the use of encapsulation, inheritance, and polymorphism to create modular, reusable, and maintainable code.
Open-Source: Open-source refers to software or technology that is freely available to the public, with the source code accessible and modifiable by anyone. This approach to software development promotes transparency, collaboration, and community-driven innovation.
OSI-approved license: An OSI-approved license is a software license that has been reviewed and approved by the Open Source Initiative (OSI), a non-profit organization that promotes and protects open-source software. These licenses are designed to ensure that software remains open-source and accessible to the public, allowing for collaboration, modification, and distribution.
Pandas: Pandas is a powerful open-source Python library used for data manipulation and analysis. It provides high-performance, easy-to-use data structures and data analysis tools, making it a popular choice for working with structured (tabular, multidimensional, potentially heterogeneous) and time series data.
Pip: Pip is a package installer for Python that allows users to easily install, upgrade, and remove Python packages and their dependencies. It is a crucial tool for managing Python libraries and modules, enabling seamless integration of external software components into Python projects.
Python: Python is a high-level, general-purpose programming language known for its simplicity, readability, and versatility. It has become a popular choice for a wide range of applications, from web development and data analysis to scientific computing and artificial intelligence.
Python's design philosophy emphasizes code readability, making it an excellent language for beginners and experienced programmers alike. Its extensive standard library and vast ecosystem of third-party packages provide developers with a wealth of tools and resources to tackle a variety of tasks efficiently.
Python Package Index: The Python Package Index (PyPI) is a repository of software for the Python programming language. It allows users to find and install packages developed by the Python community.
PyTorch: PyTorch is an open-source machine learning library for the Python programming language, primarily used for developing and deploying deep learning models. It provides a flexible and intuitive framework for building, training, and deploying neural networks, making it a popular choice among researchers, data scientists, and machine learning engineers.
Scikit-learn: Scikit-learn is a powerful open-source machine learning library for the Python programming language. It provides a wide range of algorithms and tools for tasks such as classification, regression, clustering, and dimensionality reduction, making it a popular choice for data scientists and machine learning practitioners across various industries and applications.
Stack Overflow Developer Survey: The Stack Overflow Developer Survey is an annual survey conducted by Stack Overflow, a popular online community for developers, to gain insights into the software development industry. It provides valuable data on the preferences, trends, and demographics of developers around the world, making it a crucial resource for understanding the Python programming language's popularity and adoption.
Standard Library: The standard library is a collection of pre-written, pre-tested code that comes bundled with the Python programming language. It provides a wide range of functionality, from file input/output to network communication, without the need for additional downloads or installations.
TensorFlow: TensorFlow is an open-source machine learning framework developed by Google that is widely used for building and deploying powerful artificial intelligence models. It provides a flexible ecosystem of tools, libraries, and community resources that allow developers to quickly and easily build and deploy machine learning-powered applications.
Tiobe Index: The Tiobe Index is a measure of the popularity and usage of programming languages worldwide. It is calculated based on the number of search engine results for queries related to each language, providing an indication of the relative demand and adoption of different programming languages in the software development community.