如果打算亲手制作一个简单的python解释器需要掌握哪些知识?
我是一个计算机专业的学生,在学编译原理这门课程的过程中产生了自己制作一个python解释器的想法,不过我们的课程中只讲了前后文无关文法、词法分析、语法分析和四元式表示这几块内容,而且只讲了一些手动转换的方法,对一些实际的应用讲的不深。我了解到python语言是上下文相关的,在学校的课程中对这方面的文法也没有过详细的说明。我想在这里问一下如果我准备手动写一个python解释器需要掌握哪些技能点?
回复内容:
对于实现一个解释器,parser部分其实是相对比较无聊的工作,如果跳过这部分来实现的话,可能会更容易上手一些。vinzenz/libpypa · GitHub 可以尝试一下这个项目,独立的Python parser,C++写的,目前Dropbox的Python实现Pyston,就是使用这个库做为Python的parser。
另外也可以直接尝试直接调用CPython的ast模块,将parse好的AST导出到文件中去,再拿自己实现的解释器直接读取。Pyston在引入libpypa之前就是这么做的。
还有另外一个思路,直接实现一个Python bytecode的解释器,parse .pyc文件就可以了。
之后需要了解的就是Python对象模型(比如说一个Python对象在内存是如何表示的)。如果是拿C语言来实现的话大概就是“一切都是堆上分配的结构体”就可以了。
剩下的一块是GC,需要了解一下常见的集中GC实现方案。最简单的应该是引用计数。如果是C/C++实现的话,还直接用Boehm GC,自己这块就不用管了。
相关的Python实现:
Jython和IronPython不用说了,JVM和.net两个平台上的Python实现,如果对这两个平台熟悉的话可以直接拿来参考。
Dropbox的Pyston,C++实现,使用LLVM作为codegen,因为C++相对较难,并且还有JIT的部分,并不适合上手。
micronPython, https://micropython.org/ ,专门针对嵌入式芯片实现的Python,ansi C的,可以研究一下。
tinypy tinypy :: home , 64k代码实现的比较完整的Python,可以参考。
另外推荐Python源码剖析这本书,内容非常全面 Python源码剖析 (豆瓣) 。
Vczh Free Script
Vczh Free Script 2.0 beta 发布
来看这个,大二写的,除了语法不一样以外没有任何区别。
Parser 推荐用 PEG,可以方便地处理缩进。 不考虑语法分析这一步,想着重了解python对象模型的话,可以去看看《python源码剖析》。
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

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

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

PHP is mainly procedural programming, but also supports object-oriented programming (OOP); Python supports a variety of paradigms, including OOP, functional and procedural programming. PHP is suitable for web development, and Python is suitable for a variety of applications such as data analysis and machine learning.

PHP is suitable for web development and rapid prototyping, and Python is suitable for data science and machine learning. 1.PHP is used for dynamic web development, with simple syntax and suitable for rapid development. 2. Python has concise syntax, is suitable for multiple fields, and has a strong library ecosystem.

Python is more suitable for beginners, with a smooth learning curve and concise syntax; JavaScript is suitable for front-end development, with a steep learning curve and flexible syntax. 1. Python syntax is intuitive and suitable for data science and back-end development. 2. JavaScript is flexible and widely used in front-end and server-side programming.

PHP originated in 1994 and was developed by RasmusLerdorf. It was originally used to track website visitors and gradually evolved into a server-side scripting language and was widely used in web development. Python was developed by Guidovan Rossum in the late 1980s and was first released in 1991. It emphasizes code readability and simplicity, and is suitable for scientific computing, data analysis and other fields.

VS Code can run on Windows 8, but the experience may not be great. First make sure the system has been updated to the latest patch, then download the VS Code installation package that matches the system architecture and install it as prompted. After installation, be aware that some extensions may be incompatible with Windows 8 and need to look for alternative extensions or use newer Windows systems in a virtual machine. Install the necessary extensions to check whether they work properly. Although VS Code is feasible on Windows 8, it is recommended to upgrade to a newer Windows system for a better development experience and security.

VS Code can be used to write Python and provides many features that make it an ideal tool for developing Python applications. It allows users to: install Python extensions to get functions such as code completion, syntax highlighting, and debugging. Use the debugger to track code step by step, find and fix errors. Integrate Git for version control. Use code formatting tools to maintain code consistency. Use the Linting tool to spot potential problems ahead of time.

Running Python code in Notepad requires the Python executable and NppExec plug-in to be installed. After installing Python and adding PATH to it, configure the command "python" and the parameter "{CURRENT_DIRECTORY}{FILE_NAME}" in the NppExec plug-in to run Python code in Notepad through the shortcut key "F6".

VS Code extensions pose malicious risks, such as hiding malicious code, exploiting vulnerabilities, and masturbating as legitimate extensions. Methods to identify malicious extensions include: checking publishers, reading comments, checking code, and installing with caution. Security measures also include: security awareness, good habits, regular updates and antivirus software.
