JAVA PATH<\/b>: [Source (.java)] -> (javac) -> [Bytecode (.class)] -> [JVM Engine] -> (JIT) -> [Optimized Machine Code]
\nPYTHON PATH<\/b>: [Source (.py)] -> (CPython) -> [Bytecode (.pyc)] -> [Python Interpreter Engine] -> [Line-by-Line]<\/p>\n\n<\/div>\n\n\n\n

Java vs Python Performance: How Do Concurrency Models and Infrastructure Costs Compare?<\/strong><\/h2>\n\n\n\n
When analyzing raw runtime capability, performance must be evaluated across execution speed, multithreading throughput, and cloud resource consumption.<\/p>\n\n\n\n
Execution Speed and Calculations<\/strong><\/h3>\n\n\n\n
In terms of computational speed and mathematical performance, Java performs much better than Python. The performance of heavy algorithms, loops, and data manipulation can be up to three to five times faster due to the JIT compiler’s work in native Java. However, for Python to compensate for this, it needs to use C-based packages like NumPy or PyTorch.<\/p>\n\n\n\n
Concurrency and Multithreading<\/strong><\/h3>\n\n\n\n
Managing parallel operations is a key differentiator in server environments:<\/p>\n\n\n\n
\n
Java (Project Loom):<\/strong> Introduces lightweight virtual threads managed directly by the JVM rather than through OS threads. This enables a Java process to manage millions of concurrent connections without consuming much memory.<\/li>\n\n\n\n
Python (The GIL Factor):<\/strong> Python relies on asyncio for I\/O tasks and multiprocessing for CPU tasks. While current efforts make the Global Interpreter Lock (GIL) optional, enabling true multi-core thread execution, configuring high-concurrency systems in Python still requires more architectural planning than in Java.<\/li>\n<\/ul>\n\n\n\n
Cloud Infrastructure Overhead<\/strong><\/h3>\n\n\n\n
Web applications in Java need more memory initially when starting up the JVM, but once an intensive process is involved, Java garbage collection systems like G1GC and ZGC are excellent at managing the system. Python, on the other hand, is lightweight when starting up and hence perfect for use in serverless functions, but due to consistent traffic in a global enterprise environment, Python needs horizontal scaling of containers more than Java.<\/p>\n\n\n\n
Which Ecosystems, Libraries, and Use Cases Dominate Java vs Python?<\/strong><\/h2>\n\n\n\n
The choice between Java vs Python is often dictated by the existing libraries, community tools, and frameworks built for a given industry vertical.<\/p>\n\n\n\n
Python: The AI and Scientific Hub<\/strong><\/h3>\n\n\n\n
Python is the unchallenged standard language for machine learning, artificial intelligence, and data analytics. This ecosystem includes:<\/p>\n\n\n\n
\n
Machine Learning:<\/strong> PyTorch and TensorFlow serve as the foundation for training deep neural networks. GitHub reports that Python powers over 582,000 new AI-tagged repositories, up 50.7% year over year.<\/li>\n\n\n\n
Generative AI:<\/strong> Frameworks like LangChain, LlamaIndex, and Hugging Face Transformers are taking over LLM pipeline orchestration and the development of automated agents.<\/li>\n\n\n\n
Web Services:<\/strong> The FastAPI framework has gained popularity among developers, with 38% of respondents using it in surveys, compared to 35% for Django and 34% for Flask.<\/li>\n<\/ul>\n\n\n\n
Java: The Enterprise Backbone<\/strong><\/h3>\n\n\n\n
Java remains the ideal programming language for the implementation of secure systems, capable of processing massive transaction volume within the following industries:<\/p>\n\n\n\n
\n
Enterprise Architecture:<\/strong> Spring Boot is still a dominant framework for microservices, offering automated configuration, security filters, and data integration.<\/li>\n\n\n\n
Big Data Infrastructure:<\/strong> While Python analyzes data, the distributed systems that store and stream it, including Apache Kafka, Apache Cassandra, and Apache Spark, are built primarily in Java and Scala.<\/li>\n\n\n\n
Mobile Software:<\/strong> Java remains central to the Android ecosystem, powering billions of active mobile deployments worldwide.<\/li>\n<\/ul>\n\n\n\n
How Do Code Readability, Type Safety, and Maintainability Impact Large Codebases?<\/strong><\/h2>\n\n\n\n
Code quality directly affects how easily engineering teams can update, refactor, and debug systems over multi-year enterprise lifecycles.<\/p>\n\n\n\n
Python: Clean and Expressive<\/strong><\/h3>\n\n\n\n
Python is designed for maximum readability, using clean whitespace indentation instead of curly braces or semicolons to reduce visual boilerplate. As a dynamically typed language, Python does not require developers to declare variable types. This characteristic significantly accelerates early-stage development and prototyping, making it the preferred option for teams delivering end-to-end Python development services<\/a>.<\/p>\n\n\n\n
def calculate_discount(price):\nif price > 100:\n return price * 0.9\n return price<\/code><\/pre>\n\n\n\nJava: Structured and Type-Safe<\/strong><\/h3>\n\n\n\nJava is statically typed and uses object-oriented programming. Each and every variable, parameter, and return type of any method has to be specified in advance at the time of compilation. Although Java’s verbose nature is pointed out by its critics, it provides very safe mechanisms due to type checking that occurs before code deployment.<\/p>\n\n\n\n public class PricingEngine {\npublic double calculateDiscount(double price) {\n if (price > 100.0) {\n return price * 0.9;\n }\n return price;\n }\n}<\/code><\/pre>\n\n\n\nJava vs Python Metrics: Direct Comparison Matrix<\/strong><\/h2>\n\n\n\nComparison Aspect<\/strong><\/td> Java<\/strong><\/td> Python<\/strong><\/td><\/tr> Execution Performance<\/strong><\/td> Fast (JIT compiled near-native speeds)<\/td> Moderate (Interpreted bytecode overhead)<\/td><\/tr> Type Discipline<\/strong><\/td> Static (Enforced at compile time)<\/td> Dynamic (Checked at runtime execution)<\/td><\/tr> Concurrency Model<\/strong><\/td> Virtual Threads via Project Loom<\/td> Asyncio and Multiprocessing pipelines<\/td><\/tr> Syntax Style<\/strong><\/td> Verbose, explicit class structures<\/td> Clean, minimalist, indentation-based<\/td><\/tr> Primary Frameworks<\/strong><\/td> Spring Boot, Quarkus, Micronaut<\/td> FastAPI, Django, PyTorch, LangChain<\/td><\/tr> Cloud Cold-Starts<\/strong><\/td> Higher footprint (Mitigated by GraalVM)<\/td> Low footprint (Ideal for serverless)<\/td><\/tr> Primary Domain<\/strong><\/td> Enterprise FinTech, Microservices, Android<\/td> Artificial Intelligence, ML, Data Science<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\nHow to Choose Between Java and Python for Your Next Project?<\/strong><\/h2>\n\n\n\nJava vs. Python is finally more of an architectural choice rather than a competition in syntax. Your choice should definitely match your project requirements and limitations:<\/p>\n\n\n\n With your project goals, team skills, and infrastructure constraints:<\/p>\n\n\n\n \nDeploy Python<\/strong> if you are launching an AI startup, building automated workflows<\/a>, developing data analysis platforms, or need to bring a software product to market quickly.<\/li>\n\n\n\n Deploy Java<\/strong> if you are building dependable financial systems, scaling high-throughput enterprise APIs<\/a>, constructing complex microservices, or leading a large engineering team over a long-term system lifecycle.<\/li>\n<\/ul>\n\n\n\nFrequently Asked Questions (FAQ) About Java vs Python<\/strong><\/h2>\n\n\n\n\n\nWhich language is easier to learn for beginners, Java or Python?<\/strong><\/h3>\n\n\nPython is much easier to pick up for a beginner compared to Java. Python has an easy-to-understand, English-like syntax, with little boilerplate code, thus making it easier for a programmer to concentrate on the program logic and not worry about formatting rules. In contrast to Python, which allows writing programs in one or two lines of code, Java has a mandatory structural framework even for simple programs.<\/p>\n\n<\/div>\n<\/div>\n\nHow do Java and Python compare in terms of execution speed and performance?<\/strong><\/h3>\n\n\nJava is much faster compared to Python, with the former running CPU-bound processes, intricate logical computations, and enterprise applications between 10 and 50 times faster than standard Python (CPython). Though Java is designed with high runtime throughput and scalable processing capacity in mind, Python explicitly prioritizes programmer efficiency and code readability over performance.<\/p>\n\n<\/div>\n<\/div>\n \nWhat are the main differences between Java and Python regarding syntax and type systems?<\/strong><\/h3>\n\n\nThe first main difference between Java and Python is that Java is a statically typed programming language that uses brackets for its verbose syntax, whereas Python is a dynamically typed programming language.<\/p>\n\n<\/div>\n<\/div>\n \nHow do Java and Python differ in their dominance within fields like Data Science and Artificial Intelligence?<\/strong><\/h3>\n\n\nPython completely dominates the fields of Data Science, Artificial Intelligence, and Machine Learning because of its massive, specialized ecosystem of libraries such as NumPy, Pandas, TensorFlow, and Scikit-learn. Its simple syntax allows researchers and data analysts to focus on solving complex mathematical problems rather than fighting with code implementation. Java can be used for data science and powers major big data frameworks like Hadoop and Apache Spark, but it lacks the cutting-edge, community-driven AI libraries and rapid development capabilities that make Python the default choice for data professionals.<\/p>\n\n<\/div>\n<\/div>\n \nWhat are the career prospects and job markets like for Java developers compared to Python developers?<\/strong><\/h3>\n\n\nBoth Java and Python offer exceptional career prospects and high-paying job opportunities, but they target slightly different sectors of the tech industry. Java developers are in continuous demand by large corporations, banks, healthcare industries, and Android mobile app development teams, ensuring long-term job stability in enterprise backend roles. Python developers<\/a> enjoy exploding demand across modern tech sectors such as data engineering, machine learning research, cloud computing, and DevOps, making Python highly lucrative for professionals looking to work at the forefront of automation and data analysis.<\/p>\n\n<\/div>\n<\/div>\n<\/div>\n<\/div><\/body><\/html>\n","protected":false},"excerpt":{"rendered":" Quick Summary: Java vs. Python, which should you select in 2026? Select […]<\/p>\n","protected":false},"author":3,"featured_media":11136,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[13,10491],"tags":[],"class_list":["post-11135","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-website-development","category-python"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.cmarix.com\/blog\/wp-json\/wp\/v2\/posts\/11135","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.cmarix.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.cmarix.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.cmarix.com\/blog\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/www.cmarix.com\/blog\/wp-json\/wp\/v2\/comments?post=11135"}],"version-history":[{"count":6,"href":"https:\/\/www.cmarix.com\/blog\/wp-json\/wp\/v2\/posts\/11135\/revisions"}],"predecessor-version":[{"id":52318,"href":"https:\/\/www.cmarix.com\/blog\/wp-json\/wp\/v2\/posts\/11135\/revisions\/52318"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.cmarix.com\/blog\/wp-json\/wp\/v2\/media\/11136"}],"wp:attachment":[{"href":"https:\/\/www.cmarix.com\/blog\/wp-json\/wp\/v2\/media?parent=11135"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.cmarix.com\/blog\/wp-json\/wp\/v2\/categories?post=11135"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.cmarix.com\/blog\/wp-json\/wp\/v2\/tags?post=11135"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}

Metric Type<\/strong><\/td>	Python<\/strong><\/td>	Java<\/strong><\/td><\/tr>
TIOBE Index Rank (June 2026)<\/strong><\/td>	#1 overall (18.96% market share)<\/td>	#4 overall (7.90% market share)<\/td><\/tr>
Stack Overflow Usage (2025)<\/strong><\/td>	57.85% (Up 7 percentage points YoY)<\/td>	29.4% of professional developers<\/a><\/td><\/tr>
Primary Strengths<\/strong><\/td>	Dominates AI\/ML, LLMs, and Data Science<\/td>	Powers 90%+ of Fortune 500 corporate backends<\/td><\/tr>
Average U.S. Salary<\/strong><\/td>	$125,740 per annum<\/td>	$117,037 to $150,000 per annum<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n Java has adapted to up-to-date infrastructure needs through a predictable six-month release cadence. The maturation of Project Loom and GraalVM native images allows Java to compile into fast-starting binaries, making it highly competitive in containerized, serverless cloud environments. On the other hand, Python initiatives by the Python Software Foundation<\/a> to optimize the CPython runtime have substantially improved raw execution speed, compensating for the massive growth of its community among a global developer population estimated at 47.2 million.<\/p>\n\n\n\n How Do Core Architecture and Compilation Engines Differ Between Java and Python?<\/strong><\/h2>\n\n\n\n The fundamental architectural difference between Java vs Python<\/strong> lies in how source code is transformed into executable machine instructions:<\/p>\n\n\n\n \n Java Compilation Procedure:<\/strong> Java follows an extremely stringent two-stage compilation system. Java files (source code) are compiled using the javac tool to produce platform-independent bytecode (.class) files. This bytecode file is loaded and executed by the JVM, which includes a Just-In-Time (JIT) compiler that monitors the running program, analyzes “hot spots” in the code, and compiles them into native machine language.<\/li>\n\n\n\n Python Interpretation Path:<\/strong> Python is an interpreted language that uses the standard CPython runtime. Source code (.py) is parsed into bytecode (.pyc), which the Python interpreter executes line by line. This line-by-line interpretation eliminates compiled buildup wait times, allowing experienced Dedicated Developers<\/a> to test changes instantly, though it results in a slight performance trade-off compared to ahead-of-time compilation.<\/li>\n<\/ul>\n\n\n \n JAVA PATH<\/b>: [Source (.java)] -> (javac) -> [Bytecode (.class)] -> [JVM Engine] -> (JIT) -> [Optimized Machine Code] \nPYTHON PATH<\/b>: [Source (.py)] -> (CPython) -> [Bytecode (.pyc)] -> [Python Interpreter Engine] -> [Line-by-Line]<\/p>\n\n<\/div>\n\n\n\n Java vs Python Performance: How Do Concurrency Models and Infrastructure Costs Compare?<\/strong><\/h2>\n\n\n\n When analyzing raw runtime capability, performance must be evaluated across execution speed, multithreading throughput, and cloud resource consumption.<\/p>\n\n\n\n Execution Speed and Calculations<\/strong><\/h3>\n\n\n\n In terms of computational speed and mathematical performance, Java performs much better than Python. The performance of heavy algorithms, loops, and data manipulation can be up to three to five times faster due to the JIT compiler’s work in native Java. However, for Python to compensate for this, it needs to use C-based packages like NumPy or PyTorch.<\/p>\n\n\n\n Concurrency and Multithreading<\/strong><\/h3>\n\n\n\n Managing parallel operations is a key differentiator in server environments:<\/p>\n\n\n\n \n Java (Project Loom):<\/strong> Introduces lightweight virtual threads managed directly by the JVM rather than through OS threads. This enables a Java process to manage millions of concurrent connections without consuming much memory.<\/li>\n\n\n\n Python (The GIL Factor):<\/strong> Python relies on asyncio for I\/O tasks and multiprocessing for CPU tasks. While current efforts make the Global Interpreter Lock (GIL) optional, enabling true multi-core thread execution, configuring high-concurrency systems in Python still requires more architectural planning than in Java.<\/li>\n<\/ul>\n\n\n\n Cloud Infrastructure Overhead<\/strong><\/h3>\n\n\n\n Web applications in Java need more memory initially when starting up the JVM, but once an intensive process is involved, Java garbage collection systems like G1GC and ZGC are excellent at managing the system. Python, on the other hand, is lightweight when starting up and hence perfect for use in serverless functions, but due to consistent traffic in a global enterprise environment, Python needs horizontal scaling of containers more than Java.<\/p>\n\n\n\n Which Ecosystems, Libraries, and Use Cases Dominate Java vs Python?<\/strong><\/h2>\n\n\n\n The choice between Java vs Python is often dictated by the existing libraries, community tools, and frameworks built for a given industry vertical.<\/p>\n\n\n\n Python: The AI and Scientific Hub<\/strong><\/h3>\n\n\n\n Python is the unchallenged standard language for machine learning, artificial intelligence, and data analytics. This ecosystem includes:<\/p>\n\n\n\n \n Machine Learning:<\/strong> PyTorch and TensorFlow serve as the foundation for training deep neural networks. GitHub reports that Python powers over 582,000 new AI-tagged repositories, up 50.7% year over year.<\/li>\n\n\n\n Generative AI:<\/strong> Frameworks like LangChain, LlamaIndex, and Hugging Face Transformers are taking over LLM pipeline orchestration and the development of automated agents.<\/li>\n\n\n\n Web Services:<\/strong> The FastAPI framework has gained popularity among developers, with 38% of respondents using it in surveys, compared to 35% for Django and 34% for Flask.<\/li>\n<\/ul>\n\n\n\n Java: The Enterprise Backbone<\/strong><\/h3>\n\n\n\n Java remains the ideal programming language for the implementation of secure systems, capable of processing massive transaction volume within the following industries:<\/p>\n\n\n\n \n Enterprise Architecture:<\/strong> Spring Boot is still a dominant framework for microservices, offering automated configuration, security filters, and data integration.<\/li>\n\n\n\n Big Data Infrastructure:<\/strong> While Python analyzes data, the distributed systems that store and stream it, including Apache Kafka, Apache Cassandra, and Apache Spark, are built primarily in Java and Scala.<\/li>\n\n\n\n Mobile Software:<\/strong> Java remains central to the Android ecosystem, powering billions of active mobile deployments worldwide.<\/li>\n<\/ul>\n\n\n\n How Do Code Readability, Type Safety, and Maintainability Impact Large Codebases?<\/strong><\/h2>\n\n\n\n Code quality directly affects how easily engineering teams can update, refactor, and debug systems over multi-year enterprise lifecycles.<\/p>\n\n\n\n Python: Clean and Expressive<\/strong><\/h3>\n\n\n\n Python is designed for maximum readability, using clean whitespace indentation instead of curly braces or semicolons to reduce visual boilerplate. As a dynamically typed language, Python does not require developers to declare variable types. This characteristic significantly accelerates early-stage development and prototyping, making it the preferred option for teams delivering end-to-end Python development services<\/a>.<\/p>\n\n\n\n def calculate_discount(price):\nif price > 100:\n return price * 0.9\n return price<\/code><\/pre>\n\n\n\nJava: Structured and Type-Safe<\/strong><\/h3>\n\n\n\nJava is statically typed and uses object-oriented programming. Each and every variable, parameter, and return type of any method has to be specified in advance at the time of compilation. Although Java’s verbose nature is pointed out by its critics, it provides very safe mechanisms due to type checking that occurs before code deployment.<\/p>\n\n\n\n public class PricingEngine {\npublic double calculateDiscount(double price) {\n if (price > 100.0) {\n return price * 0.9;\n }\n return price;\n }\n}<\/code><\/pre>\n\n\n\nJava vs Python Metrics: Direct Comparison Matrix<\/strong><\/h2>\n\n\n\nComparison Aspect<\/strong><\/td> Java<\/strong><\/td> Python<\/strong><\/td><\/tr> Execution Performance<\/strong><\/td> Fast (JIT compiled near-native speeds)<\/td> Moderate (Interpreted bytecode overhead)<\/td><\/tr> Type Discipline<\/strong><\/td> Static (Enforced at compile time)<\/td> Dynamic (Checked at runtime execution)<\/td><\/tr> Concurrency Model<\/strong><\/td> Virtual Threads via Project Loom<\/td> Asyncio and Multiprocessing pipelines<\/td><\/tr> Syntax Style<\/strong><\/td> Verbose, explicit class structures<\/td> Clean, minimalist, indentation-based<\/td><\/tr> Primary Frameworks<\/strong><\/td> Spring Boot, Quarkus, Micronaut<\/td> FastAPI, Django, PyTorch, LangChain<\/td><\/tr> Cloud Cold-Starts<\/strong><\/td> Higher footprint (Mitigated by GraalVM)<\/td> Low footprint (Ideal for serverless)<\/td><\/tr> Primary Domain<\/strong><\/td> Enterprise FinTech, Microservices, Android<\/td> Artificial Intelligence, ML, Data Science<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\nHow to Choose Between Java and Python for Your Next Project?<\/strong><\/h2>\n\n\n\nJava vs. Python is finally more of an architectural choice rather than a competition in syntax. Your choice should definitely match your project requirements and limitations:<\/p>\n\n\n\n With your project goals, team skills, and infrastructure constraints:<\/p>\n\n\n\n \nDeploy Python<\/strong> if you are launching an AI startup, building automated workflows<\/a>, developing data analysis platforms, or need to bring a software product to market quickly.<\/li>\n\n\n\n Deploy Java<\/strong> if you are building dependable financial systems, scaling high-throughput enterprise APIs<\/a>, constructing complex microservices, or leading a large engineering team over a long-term system lifecycle.<\/li>\n<\/ul>\n\n\n\nFrequently Asked Questions (FAQ) About Java vs Python<\/strong><\/h2>\n\n\n\n\n\nWhich language is easier to learn for beginners, Java or Python?<\/strong><\/h3>\n\n\nPython is much easier to pick up for a beginner compared to Java. Python has an easy-to-understand, English-like syntax, with little boilerplate code, thus making it easier for a programmer to concentrate on the program logic and not worry about formatting rules. In contrast to Python, which allows writing programs in one or two lines of code, Java has a mandatory structural framework even for simple programs.<\/p>\n\n<\/div>\n<\/div>\n\nHow do Java and Python compare in terms of execution speed and performance?<\/strong><\/h3>\n\n\nJava is much faster compared to Python, with the former running CPU-bound processes, intricate logical computations, and enterprise applications between 10 and 50 times faster than standard Python (CPython). Though Java is designed with high runtime throughput and scalable processing capacity in mind, Python explicitly prioritizes programmer efficiency and code readability over performance.<\/p>\n\n<\/div>\n<\/div>\n \nWhat are the main differences between Java and Python regarding syntax and type systems?<\/strong><\/h3>\n\n\nThe first main difference between Java and Python is that Java is a statically typed programming language that uses brackets for its verbose syntax, whereas Python is a dynamically typed programming language.<\/p>\n\n<\/div>\n<\/div>\n \nHow do Java and Python differ in their dominance within fields like Data Science and Artificial Intelligence?<\/strong><\/h3>\n\n\nPython completely dominates the fields of Data Science, Artificial Intelligence, and Machine Learning because of its massive, specialized ecosystem of libraries such as NumPy, Pandas, TensorFlow, and Scikit-learn. Its simple syntax allows researchers and data analysts to focus on solving complex mathematical problems rather than fighting with code implementation. Java can be used for data science and powers major big data frameworks like Hadoop and Apache Spark, but it lacks the cutting-edge, community-driven AI libraries and rapid development capabilities that make Python the default choice for data professionals.<\/p>\n\n<\/div>\n<\/div>\n \nWhat are the career prospects and job markets like for Java developers compared to Python developers?<\/strong><\/h3>\n\n\nBoth Java and Python offer exceptional career prospects and high-paying job opportunities, but they target slightly different sectors of the tech industry. Java developers are in continuous demand by large corporations, banks, healthcare industries, and Android mobile app development teams, ensuring long-term job stability in enterprise backend roles. Python developers<\/a> enjoy exploding demand across modern tech sectors such as data engineering, machine learning research, cloud computing, and DevOps, making Python highly lucrative for professionals looking to work at the forefront of automation and data analysis.<\/p>\n\n<\/div>\n<\/div>\n<\/div>\n<\/div><\/body><\/html>\n","protected":false},"excerpt":{"rendered":" Quick Summary: Java vs. Python, which should you select in 2026? Select […]<\/p>\n","protected":false},"author":3,"featured_media":11136,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[13,10491],"tags":[],"class_list":["post-11135","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-website-development","category-python"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.cmarix.com\/blog\/wp-json\/wp\/v2\/posts\/11135","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.cmarix.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.cmarix.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.cmarix.com\/blog\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/www.cmarix.com\/blog\/wp-json\/wp\/v2\/comments?post=11135"}],"version-history":[{"count":6,"href":"https:\/\/www.cmarix.com\/blog\/wp-json\/wp\/v2\/posts\/11135\/revisions"}],"predecessor-version":[{"id":52318,"href":"https:\/\/www.cmarix.com\/blog\/wp-json\/wp\/v2\/posts\/11135\/revisions\/52318"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.cmarix.com\/blog\/wp-json\/wp\/v2\/media\/11136"}],"wp:attachment":[{"href":"https:\/\/www.cmarix.com\/blog\/wp-json\/wp\/v2\/media?parent=11135"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.cmarix.com\/blog\/wp-json\/wp\/v2\/categories?post=11135"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.cmarix.com\/blog\/wp-json\/wp\/v2\/tags?post=11135"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}