Programming language interoperability is highly desirable for a variety of reasons, such as the fact that if a programmer implements specific functionality that has previously been implemented in another language, the software component can simply be reused. Because they are particularly well-suited and efficient at implementing features, certain languages regularly arise to handle issue areas. There are numerous third-party programs available for a variety of languages. When programmers have experience with and preferences for several programming languages, collaboration on complex projects is easier. A range of techniques and methods have been used to handle various cross-language communication challenges. The importance of interoperability and cross-language communication between Java and Python via socket programming is examined in this research article through an empirical model of different execution environment paradigms that can help guide the development of improved approaches for integrating Python libraries with Java without the need for extra libraries or third-party libraries. The interoperability strategy benefits from the quality and availability of Python libraries in Java by cutting down on development time, maintenance needs, general usability, upkeep, and system integration without incurring additional costs. It is versatile to use this interoperability strategy since identical scripts are run in Java client contexts in the same way that they were used in Python. There are different Python modules used in the research article to exemplify and evaluate the expressions, built-in functions, strings, collections, data exploration, statistical data analysis using NumPy, SciPy, and Pandas, and Scikit-Learn for machine learning with linear regression.