Pros of GraalPython

• High-performance Python implementation with JIT compilation
• Seamless Java interoperability through Truffle framework
• Supports Python 3.8+ features and standard library

Cons of GraalPython

• Larger footprint and longer startup time
• Less mature and potentially less stable than CPython
• Limited support for some Python C extensions

Code Comparison

GraalPython:

import java
from java.lang import System

System.out.println("Hello from GraalPython!")

Jep:

from jep import Jep

with Jep() as jep:
    jep.eval('System.out.println("Hello from Jep!");')

Key Differences

• GraalPython aims for full Python language compatibility, while Jep focuses on Python-Java integration
• GraalPython is part of the GraalVM ecosystem, whereas Jep is a standalone project
• Jep uses CPython and allows embedding Python in Java applications, while GraalPython is a separate Python implementation

Use Cases

• GraalPython: High-performance Python applications, polyglot environments
• Jep: Embedding Python in existing Java applications, tighter Java-Python integration

Community and Support

• GraalPython: Backed by Oracle, active development, growing community
• Jep: Smaller but dedicated community, longer project history

Pros of Jython

• Full Python implementation in Java, allowing seamless integration with Java libraries
• Supports most Python standard library modules
• Can compile Python code to Java bytecode for improved performance

Cons of Jython

• Slower development cycle compared to CPython
• Limited support for C extension modules
• Not fully compatible with the latest Python versions

Code Comparison

Jython:

from javax.swing import JFrame, JLabel

frame = JFrame("Hello, Jython!")
label = JLabel("Welcome to Jython")
frame.add(label)
frame.setSize(300, 100)
frame.setVisible(True)

Jep:

import jep
from java.awt import Frame

jep.shared.create_java_instance("java.awt.Frame", "Hello, Jep!")
frame = jep.shared.get_java_instance("frame")
frame.setSize(300, 100)
frame.setVisible(True)

Both Jython and Jep aim to bridge Python and Java, but they take different approaches. Jython provides a complete Python implementation in Java, offering broader compatibility with Python libraries. Jep, on the other hand, focuses on embedding CPython in Java applications, which can be more suitable for specific use cases where tighter integration with existing Java code is required.

Pros of JPype

• More mature project with longer development history
• Supports a wider range of Java versions
• Better integration with Java threading and synchronization

Cons of JPype

• Slower startup time compared to Jep
• More complex setup process
• Less actively maintained in recent years

Code Comparison

JPype example:

import jpype
jpype.startJVM()
java.lang.System.out.println("Hello, World!")
jpype.shutdownJVM()

Jep example:

import jep
jep.init_jvm()
jep.eval('System.out.println("Hello, World!");')

Both Jep and JPype are libraries for integrating Java and Python, allowing Python code to call Java methods and classes. JPype provides a more comprehensive Java integration but may be slower to start up, while Jep offers a simpler interface and faster startup times. JPype supports a wider range of Java versions and has better threading support, but Jep is more actively maintained and has a simpler setup process. The choice between the two depends on specific project requirements, such as performance needs, Java version compatibility, and the complexity of Java integration required.

Pros of Pyjnius

• More actively maintained with recent updates
• Broader platform support, including Android
• Simpler setup process for many use cases

Cons of Pyjnius

• Less flexible in handling complex Java types
• May have performance overhead in certain scenarios
• Limited support for advanced Java features like anonymous classes

Code Comparison

Pyjnius:

from jnius import autoclass
String = autoclass('java.lang.String')
s = String("Hello World")
print(s.toLowerCase())

Jep:

import jep
jep.shared.jep_java_import('java.lang.String')
s = String("Hello World")
print(s.toLowerCase())

Both libraries aim to provide Python-Java interoperability, but they differ in implementation and focus. Pyjnius is part of the Kivy project and is designed with mobile development in mind, while Jep is more focused on embedding Python in Java applications. Pyjnius generally offers an easier setup process and broader platform support, making it a good choice for many Python developers looking to use Java libraries. However, Jep may provide better performance and more advanced Java integration in certain scenarios, particularly when working with complex Java types or when embedding Python in Java applications.