What is the difference between java and python
What is the difference between java and python?
(1) The python virtual machine is not as powerful as java, and the java virtual machine is the core of java , the core of Python is that you can easily use C language functions or C libraries.
(2). Python is fully dynamic and you can modify your own code at runtime. Java can only be implemented through workarounds. Python's variables are dynamic, while Java's variables are static and need to be declared in advance, so the code prompt function of Java IDE is better than that of Python IDE.
(3), Python has been around for decades. Process-oriented was the mainstream decades ago, so there are many programs using Python that use process-oriented design methods. Many concepts come from the C language. Classes are in Python. It was added later, and Java was designed to implement C without pointers (the reference counting used by COM components, the virtual machine used by Java), mainly using object-oriented design methods, and many concepts are oop concepts. Process-oriented, relatively simple and intuitive, but easy to design noodle programs, object-oriented, relatively abstract and elegant, but easy to be over-abstracted.
(4), it is easy to get started with python in actual use, but to learn to work with python, you need to learn various python libraries. The power of pyhton lies in the library. Why python libraries are powerful? The reason is that python libraries can be used Python, C language, C and other designs are then provided for Python to use, so whether it is GPU operation, neural network, intelligent algorithm, data analysis, image processing, scientific calculation, various libraries are waiting for you to use. Java does not have as many open source libraries as Python. Many libraries are used internally by commercial companies, or are released as just a jar package, and the original code cannot be seen. Because the Python virtual machine does not have good compilation support as Java (or it is deliberately designed this way), the source code (linux) is generally used directly, or the source code is simply packaged (such as pyexe).
(5). Python has many virtual machine implementations, such as cython, Pyston, pypy, jython, IronPython, etc., which are suitable for business languages, plug-in languages, or domain-oriented languages. However, Java has a huge virtual machine and is very difficult to implement. It is rarely used in plug-in languages and is not convenient to publish.
(6). Java is mainly used in areas with strong business logic, such as shopping mall systems, erp, oa, finance, insurance and other traditional database transaction fields. Through transaction codes similar to ssh framework, it can be used for commercial databases such as oralce, db2, SQL Server has good support, strong software engineering concepts, and is suitable for software engineering-style multi-player development mode. Python is mainly used for web data analysis, scientific computing, financial analysis, signal analysis, image algorithms, mathematical calculations, statistical analysis, algorithm modeling, server operation and maintenance, automated operations, strong rapid development concepts, and is suitable for rapid development teams or individual agile models. .
(7). Java is supported by many commercial companies, such as SAP, Oracle, IBM, etc., with commercial containers, middleware, and enterprise framework ejb. There are many open source organizations that support python, such as qt, linux, and google. Many open source programs support python, such as pyqt, redis, spark, etc.
(8). Python is most used for scripts, Java is most used for web, pyhotn is the glue that can stick all kinds of unrelated things together, and java is gay and can be used to form hundreds of pieces through software engineering. A personal team competes with you, with a strong commercial atmosphere. However, I think Python is still more powerful because it can easily call C or C libraries, but software engineering and commercial operations are not as good as Java and is suitable for quick development.
(9), about money. If you want to write programs and sell software using Java, you can use IBM servers, Oracle databases, and EMC storage. The price is high, and commercial procurement companies like this kind of high-end. If you want to directly use a program to generate money, use Python. Python can implement quant finance, data backtesting, stock trading, options trading, gold trading, Bitcoin trading, hedging arbitrage, and statistical arbitrage. There are many open source libraries, data analysis libraries, and machines. You can refer to the learning library.
(10), Java and Python can all run on the Linux operating system, but many Linuxes can natively support Python, and Java needs to be installed by yourself. The reason why java and python are stronger than c# is that they support linux, osx, unix, and arm. The reason why Java and Python are more popular than C is that they do not require pointers.
(11). For the mobile Internet, python can only run on Android or ios through the runtime library. Java natively supports Android development, but cannot be used on ios.
(12). For big data, hadoop is developed with java, and spark is developed with Scala. It is more convenient to call spark with python for analysis.
The above is the detailed content of What is the difference between java and python. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics



The speed of mobile XML to PDF depends on the following factors: the complexity of XML structure. Mobile hardware configuration conversion method (library, algorithm) code quality optimization methods (select efficient libraries, optimize algorithms, cache data, and utilize multi-threading). Overall, there is no absolute answer and it needs to be optimized according to the specific situation.

It is impossible to complete XML to PDF conversion directly on your phone with a single application. It is necessary to use cloud services, which can be achieved through two steps: 1. Convert XML to PDF in the cloud, 2. Access or download the converted PDF file on the mobile phone.

There is no built-in sum function in C language, so it needs to be written by yourself. Sum can be achieved by traversing the array and accumulating elements: Loop version: Sum is calculated using for loop and array length. Pointer version: Use pointers to point to array elements, and efficient summing is achieved through self-increment pointers. Dynamically allocate array version: Dynamically allocate arrays and manage memory yourself, ensuring that allocated memory is freed to prevent memory leaks.

There is no APP that can convert all XML files into PDFs because the XML structure is flexible and diverse. The core of XML to PDF is to convert the data structure into a page layout, which requires parsing XML and generating PDF. Common methods include parsing XML using Python libraries such as ElementTree and generating PDFs using ReportLab library. For complex XML, it may be necessary to use XSLT transformation structures. When optimizing performance, consider using multithreaded or multiprocesses and select the appropriate library.

XML formatting tools can type code according to rules to improve readability and understanding. When selecting a tool, pay attention to customization capabilities, handling of special circumstances, performance and ease of use. Commonly used tool types include online tools, IDE plug-ins, and command-line tools.

XML can be converted to images by using an XSLT converter or image library. XSLT Converter: Use an XSLT processor and stylesheet to convert XML to images. Image Library: Use libraries such as PIL or ImageMagick to create images from XML data, such as drawing shapes and text.

An application that converts XML directly to PDF cannot be found because they are two fundamentally different formats. XML is used to store data, while PDF is used to display documents. To complete the transformation, you can use programming languages and libraries such as Python and ReportLab to parse XML data and generate PDF documents.

Use most text editors to open XML files; if you need a more intuitive tree display, you can use an XML editor, such as Oxygen XML Editor or XMLSpy; if you process XML data in a program, you need to use a programming language (such as Python) and XML libraries (such as xml.etree.ElementTree) to parse.