프로그래밍 언어 특징비교분석

Typing System

• Python is dynamically typed, meaning you don’t need to declare the type of variable explicitly; the interpreter infers the type at runtime.
• Java is statically typed, where you must explicitly declare the type of every variable, making it more strict in terms of type checks before code execution.

Performance

• Java is generally faster than Python as Java bytecode is compiled to native machine code at runtime by the Just-In-Time (JIT) compiler of the JVM. This makes Java a preferred choice for high-performance applications, including server-side technologies.
• Python is interpreted and dynamically typed, which leads to slower execution. However, for many applications, especially web and data analysis tasks, this speed difference is not critical. Python can also interface with C libraries to bypass performance bottlenecks.

Development and Maintenance Cost

• Java's verbose nature and static typing mean that it may require more code to perform the same task, potentially increasing development time and costs. However, its robustness and efficiency can lower maintenance costs for large, complex applications.
• Python allows for rapid development with less code, which can reduce initial development costs. However, its dynamic nature might increase maintenance costs due to potential runtime errors and the need for more testing.

Object and Datatype

• Java: Handling of Primitives and Objects; pass by copy of value

1. Primitive Data Types (int, float, char, etc.):
   • Primitive Data types contain value
   • Pass by Value: Java passes a copy of the value of the primitive data type to methods. This means if you pass a primitive data type to a method and then change its value inside that method, the change does not affect the original variable outside the method because only a copy was passed.
2. Objects (Instances of classes, Arrays, etc.):
   • Object variable contains reference to the object.
   • Pass by copied Value of the Reference: you can modify the object's attributes or contents through this reference, and the changes will reflect in the original object. However, if you reassign the reference to a new object inside the method, this reassignment does not affect the original reference. Because the act of copying is just adding another channel to the object only.

• Python: Everything as Objects

1. Immutables (int, float, str, tuple):
   • Passing copied value of the object: Although technically passed by object reference, since they are immutable, any attempt to modify an immutable results in the creation of a new object. Changes to an immutable object inside a function do not affect the original object outside the function.
   • Reassignment inside a Function: Leads to the local variable pointing to a new object, while the outside variable remains unchanged.
2. Mutables (list, dict, set, etc.):
   • Passing coped value of Object Reference: When mutables are passed to functions, both the outside and inside variables point to the same object. Any changes to the object inside the function will affect it outside the function because they are the same object. But reassignment makes a new object.

Object-Oriented Programming (OOP) Philosophy

• Explicit OOP: Everything in Java is an object, except for the primitive data types, which do not fit into the class hierarchy. Java enforces OOP by requiring all code to be part of a class.
• Access Modifiers: Java uses access modifiers (private, protected, public) to control access to classes, methods, and fields, enforcing encapsulation—a core OOP principle.
• Fixed Structure: Once a class is defined in Java, its structure (the attributes and methods it contains) is fixed. All instances of the class will have the same attributes and methods, which cannot be changed dynamically.
• Inheritance Restrictions: Java supports single inheritance, meaning a class can inherit from one superclass only, although it can implement multiple interfaces to somewhat mitigate this limitation.

Java: OOP로 생산성, 접근자로 보안성 확보

• Implicit OOP: Python supports OOP but does not require it. You can write Python programs in a functional or procedural style if you prefer.
• Conventional Encapsulation: Python uses naming conventions (e.g., prefixing with an underscore for "private" attributes) to suggest that certain details should be treated as private, but these are not enforced by the language.
• Dynamic Attributes: Python classes are flexible. New attributes can be added to instances at runtime. Also, Python supports adding methods to instances or classes during runtime.
• Multiple Inheritance: Python supports multiple inheritance, allowing a class to inherit from multiple parent classes, which provides a lot of flexibility but can also lead to complexity like the diamond problem (which Python addresses with the C3 linearization algorithm).

Python: Function-Oriented Flexibility

• Python often emphasizes simplicity and flexibility. It allows developers to create and use functions in a straightforward manner, without the need to encapsulate them within classes unless necessary. This approach can make Python code more concise and easier to write for certain types of tasks, especially scripting, data analysis, and rapid prototyping:
• Modular and Reusable Functions: Python encourages the use of standalone functions that can be easily reused and moved around. These functions can be imported from modules and used directly without the need for class instantiation.
• Built-in and Third-Party Libraries: Many Python libraries are designed with functions that operate independently of class instances. Libraries like `math` and `os` provide functional interfaces that don't require the user to create objects to use their functionality.

Java: Class-Based Structure

• Java, being a strictly object-oriented programming language, requires everything to be part of a class. This means even simple programs need at least one class to run. Java's structure promotes a more organized and modular approach at the expense of verbosity and complexity for smaller tasks:
  • - Everything Is an Object: In Java, operations are generally performed through objects. This design enforces a disciplined object-oriented approach, which can enhance maintainability and scalability in large applications.
  • - Class Methods (Static Methods): Java does allow for methods that can be called without creating an instance of the class (static methods), but these are still defined within class structures and must be called on the class itself, not an instance.
• Practical Implications - Python is often preferred for applications where speed of development, flexibility, and ease of use are paramount. It's well-suited to tasks like scripting, data manipulation, and single-page web applications where complex class structures might be overkill.
• - Java shines in environments where robustness, long-term maintainability, and clear modular design are required. It's ideal for large enterprise applications, Android app development, and server-side technologies.

Compile Language  vs Interpreter Language (Build tools)

Why Python Doesn't Require an External Build System

Python is fundamentally different from Java in how it is executed, which influences its dependency on build systems:

1. Interpretation vs. Compilation: Python code is interpreted, not compiled into machine code beforehand. The interpreter reads and executes Python code directly, which means there's no need for a separate compilation step.
2. Dynamic Typing: Python's dynamic typing system doesn't require the kind of upfront type checking that Java's static typing system does. This eliminates the need for certain complexities in the build process.
3. complex Structure : Java is commonly used in large-scale enterprise environments that often involve multi-module projects with intricate dependency trees. Managing such complexity manually becomes impractical, hence the need for automated tools that can handle dependency resolution, project lifecycle management, and build optimization efficiently.