Features Of Python
The features of a programming language refer to the services and facilities provided by its developers to enable efficient and effective programming. These features are designed to simplify and streamline the development process, offering tools and capabilities that address a wide range of programming needs. Real-time programmers leverage these features to create robust, scalable, and efficient applications that solve real-world problems. By utilizing the language's built-in functionalities, developers can focus on crafting innovative solutions rather than reinventing common programming constructs.
Python's Simplicity Explained Through 3 Key Features.
- Rich Set of APIs: Python provides a rich collection of Application Programming Interfaces (APIs), enabling developers to reuse pre-defined code efficiently. APIs in Python consist of modules, which are collections of functions, variables, and classes. This allows programmers to develop real-time applications with minimal effort, avoiding the need to write everything from scratch.
- Definition of API: An API (Application Programming Interface) is a collection of modules designed to simplify programming tasks by offering pre-built tools and functionalities.
- Definition of Module: A module is a collection of functions, variables, and classes that can be imported and used in Python programs.
- In-Built Garbage Collector: Python includes an automatic garbage collector that runs in the background of every Python program. Its primary purpose is to manage memory efficiently by collecting and freeing unused memory spaces. This improves the performance of Python-based applications by preventing memory leaks.
- Definition of Garbage Collector: The garbage collector is a background Python process that identifies and collects unused memory spaces during the execution of a program, enhancing application performance.
- User-Friendly Syntax: Python offers simple and intuitive syntax, making it easy for developers to write error-free code in a limited time. This feature is especially useful for beginners and professionals seeking to develop applications quickly and efficiently.
- These three features rich APIs, automatic garbage collection, and user-friendly syntax make Python one of the simplest and most effective programming languages for real-world application development.
- Freeware: Python is freeware, meaning it can be freely downloaded and used without any licensing costs. This makes Python accessible to anyone, contributing to its widespread adoption.
- Open Source: Python is open source, allowing developers to access its source code for customization and enhancement. The original standard Python released by the Python Software Foundation (PSF) is called CPython.
- Companies and developers have customized CPython to suit their specific needs, leading to the creation of Python Distributions tailored for different applications.
- JPython (or Jython): Designed to run Java-based applications by integrating Python with Java environments.
- IronPython (or Ipython): Customized for running .NET-based applications, particularly those using C#.
- RubyPython: Enables Python to execute Ruby-based applications seamlessly.
- MicroPython: Specifically tailored for developing microcontroller applications, making it ideal for IoT and embedded systems.
- Anaconda Python: Widely used for big data, machine learning, and Hadoop-based applications due to its extensive data science libraries.
- Stackless Python: Designed to support concurrency, facilitating the development of scalable and efficient multitasking applications.
- PyPy: A Python distribution featuring a Just-In-Time (JIT) compiler for significantly faster execution of Python code.
These distributions demonstrate Python's flexibility and adaptability, catering to a wide range of applications across various industries.
When a Python program is executed, it undergoes two main phases Compilation Phase and Execution Phase.
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During the compilation phase, the Python Compiler reads the source code (e.g.,
Sum.py) line by line. - The compiler converts the source code into an intermediate form called Byte Code, which is a platform-independent representation of the code.
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The generated Byte Code is saved with a
.pycextension.
Example Process:
Sum.py → (Line by Line) → Python Compiler → Sum.pyc (Byte Code)
- Since Python compiles the source code into Byte Code line by line, it is referred to as an interpreted language.
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During execution, the PVM (Python Virtual Machine) reads the Byte Code (
Sum.pyc) line by line. - The PVM converts the Byte Code into Machine Code, which is understood by the operating system and processor.
- Finally, the machine code is executed, producing the program's result.
Example Process:
Sum.pyc → (Line by Line) → PVM → Machine Code → OS + Processor → Program Result
- Since the PVM executes the Byte Code line by line, Python is also considered an interpreted language.
- In the Compilation Phase, the source code is converted into Byte Code by the Python Compiler.
- In the Execution Phase, the Byte Code is executed by the PVM, which converts it into Machine Code for the OS and processor.
- Python’s line-by-line interpretation during both phases makes it an interpreted programming language.
Python is platform-independent because its execution environment handles all values as objects, ensuring compatibility across different operating systems.
Object-Based Value Storage:
In Python, all values, regardless of type, are stored as objects. These objects have no dependency on the operating system, making Python execution consistent across platforms.
Unlimited Storage in Objects:
Python objects can store an unlimited number of values, unlike some other programming languages where data types have fixed or OS-dependent memory sizes.
Comparison with Platform-Dependent Languages:
Languages like C and C++ are platform-dependent because their data types (keywords) have memory sizes that vary between operating systems.
Comparison with Java:
Java is also platform-independent, as its pre-defined data types have consistent memory sizes across operating systems.
However, Java's data types typically store single values, whereas Python objects can store multiple values without predefined limits.
Object-Oriented Nature of Python:
Python's reliance on objects for storing values ensures flexibility and scalability, distinguishing it from languages that rely heavily on primitive data types.
7. Memory Management:
In Python, objects manage memory dynamically, providing storage adaptability without OS constraints.
This feature simplifies cross-platform application development and usage, ensuring Python’s reputation as a robust platform-independent language.
Programming Languages are broadly categorized into 2 types.
1. Static Typed Programming Languages
In static-typed languages, the data type of a variable must be explicitly declared during variable declaration. If not specified, it leads to a compile-time error.
Characteristics
- Mandatory declaration of variable types before usage.
- Type checking is done at compile time.
- Ensures type safety but reduces flexibility.
Examples
- C, C++, Java, .Net
2. Dynamically Typed Programming Languages
In dynamically typed languages, data types do not need to be explicitly declared. The programming environment assigns the data type based on the value assigned to the variable.
Characteristics
- No need for explicit type declarations.
- Type checking is done at runtime.
- Offers greater flexibility but may introduce runtime type-related errors.
Examples
Python.
We have two types of programming Languages. They are
Low-Level Programming Languages:
- Represent data in lower-level formats such as binary, octal, or hexadecimal number systems.
- These formats are closer to the hardware, offering more control but requiring significant manual effort to manage.
High-Level Programming Language:
- Automatically convert low-level data (binary, octal, hexadecimal) into an understandable decimal format for the programmer.
- Python is considered a high-level programming language because it abstracts low-level details, allowing developers to focus on logic without dealing with hardware-specific data representation.
Extensible Programming Language:
- An extensible programming language allows its features or capabilities to be extended or reused by other programming languages. In essence, the code written in an extensible language can be incorporated or called from another language to extend its functionality.
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Example: Python is extensible because you can write Python functions or modules that can be called from other programming languages like C or C++ using tools such as Python/C API or libraries like
ctypesorSWIG.
Embedded Programming Language:
- An embedded programming language allows itself to integrate or embed code written in other languages. It acts as a host language, leveraging the services of the embedded code for additional functionality.
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Example: Python can embed C or C++ code using libraries like
cythonorctypes. This makes Python an embedded language in this context because it can integrate and use the functionality of other languages.
- Python is a user-friendly programming language that provides clear and helpful error messages, aiding developers in troubleshooting and debugging.
- Its exception handling capabilities allow developers to gracefully manage runtime errors, ensuring smooth and stable program execution.
- These features collectively make Python a robust and reliable language, ideal for both beginners and advanced users in diverse programming domains.
- Seamless Integration of Third-Party APIs: Python extensively supports third-party libraries and APIs, enabling the development of high-performance, real-time applications with concise and efficient code.
- Wide Range of Third-Party Libraries: Python's ecosystem includes powerful libraries like NumPy (by Travis Oliphant), Pandas (by Wes McKinney), SciPy, Matplotlib, Seaborn, and NLTK, which cater to diverse domains like data analysis, machine learning, and natural language processing.
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Ease of Access with pip:
The Python package manager
pip(and its versions likepip3.10) makes it easy to install, update, and manage third-party libraries, streamlining the development process.
- Support for First and Second-Party APIs: Alongside third-party APIs, Python includes a robust built-in library (First Party) and support for operating system libraries (Second Party), providing a comprehensive development toolkit.
- Python supports procedural programming with functions, modules, and control flow structures for step-by-step programming.
- It fully supports object-oriented programming with features like classes, objects, inheritance, and encapsulation.
- Python allows combining both procedural and object-oriented paradigms within the same program for flexibility.
- This dual support makes Python versatile, suitable for both simple scripts and complex, large-scale applications.