Python甩开C++几条街？这脚本语言凭啥封神，简单到让程序员尖叫

根据TIOBE于2024年12月公布的编程语言排行榜, 以23.84%受欢迎程度这一指标, 稳稳占据榜首位置, 已然将第二名C远远甩开了好多, 并且这个占比还在依靠飞快的速度持续增长, 为何会如此兴盛受欢迎呢, 风云作为一名狂热者, 在日常的工作过程当中, 多数时候也常用它来对问题加以解决的, 今天, 借着这个排行榜得以再次开启讨论, 对此展开交流。从初学者直至专业开发者而言, 一种理想语言, 它的通用性以及高效性使其能在未来相当长一段时间之内长久维持属于它的火热状态。其以流行态势存在, 则正因为其具备简单化的易于操作性, 拥有强大的生态系统, 存在广阔的应用场景, 以及有着特别活跃的社区支持者呀一、简单易学其语法设计直观地向自然语言契合, 不但初学者易于开启上手之路, 就算专业的开发高手, 也存在其尽情施展的辽阔空间。相同等同的功能, 运用其而编写的代码常常相比其他语言更简短、趋于更为清晰的状态。按照风云积累的实践经验来看: 其产生的代码量, 仅仅是c#以及java的三分之一, 是c的五分之一。示例实现两个数相加的代码a, b 5, 3 print(a b)C#include using namespace std; int main() { int a 5, b 3; cout a b endl; return 0; }二、丰富的生态的通用性允许它应用于各种领域存在这样一种情况致使数据科学跟人工智能, 转变就位数据科学以及机器学习的首要选用语言。存在譬如这般的情况还有强大无比的AI框架同样如此那般, 进而提升了数据的处理效率。针对Web开发这种情形就表现为如此以及一些框架像Flask可做到让后端开发变得快速且高效。如同这般一个状况为仅仅花费20分钟Flask就能生成一个web页面, 紧接着凭借完成配置以及创建业务逻辑的模式就能够将功能复杂极了的后台管理系统给搭建成功。也设有基于由一些特定逻辑组成的协程且具有异步特性这样的高效能框架。对于网络爬虫这种现象则在于其能够提供专业抓取web站点以及按照一定程度、方式从页面里边提取结构化数据的能力。专门适用于数据挖掘, 以及监测, 还有自动化测试自动化, 靠运用去编写脚本能够迅速达成繁杂的任务, 像是文件的批量处理, 以及数据的爬取。至于游戏开发, 即便并非主流的游戏开发语言, 然而等种类的库也是适宜开展小型游戏开发以及原型设计的。投身于嵌入方面与物联网领域, 在以及Pi平台之上让实施物联网开发。另外, 在对股票进行量化交易, 进行系统的运维工作, 以及从事日常工作里使用word、excel协助进行统计分析等方面, 均有涉猎, 这样的多样丰富状况, 使得开发者不必由最开始去将复杂功能予以实现。三、强大的社区社区非常活跃比如教程还有文档: 与第三方教程网站相比覆盖范围极为广泛。问题解决方面: Stack之上存在海量的问题解答内容。开源贡献情况: 在CSDN社区, 众多开发者进行维护以及更新库和框架。face这块: 这里着重提一下face这个社区, 它是全球最大且专注于自然语言处理也就是NLP和人工智能即AI的AI主题社区, 它供给了模型、数据集含文本、图像、音频、视频、类库像比如、、以及教程等一类资源。这种社区氛围使得开发者在遇到问题时可以快速获得帮助。四、跨平台支持这是一种解释型语言, 它能够在多种操作系统上运行, 比如Linux, 还有macOS。借助提供统一的接口, 就此让跨平台开发变得容易搞定。示例开发一个文件管理脚本可以在 和 Linux 上运行import os def list_files(path): for file_name in os.listdir(path): print(file_name) list_files(.)五、多种编程范式支持多种编程风格适应不同开发需求面向对象编程 (OOP)class Person: def __init__(self, name): self.name name def greet(self): print(fHello, my name is {self.name}) p Person(Alice) p.greet()函数式编程numbers [1, 2, 3, 4] squares map(lambda x: x ** 2, numbers) print(list(squares))命令式编程for i in range(5): print(i)六、开发效率高拥有动态类型以及解释型特性, 这些特性可让开发以及测试变得快捷, 而这对于项目原型所开展的设计而言是极为有利的。代码无需进行编译, 直接就能够运行。变量的类型是动态的, 无需对类型进行显式声明。许多知名企业, 比如知乎、豆瓣等, 都广泛对其加以使用, 也就进一步增强了它的可信度。开源文化鼓励开发者不管身处全球任何地方, 其贡献代码, 持续不断丰富它的生态。七、存在不足与拥有空间。虽且即纵说是, 一门极其盛行且用处诸多、能耐雄厚的编程语言, 然而它仍是存在一些, 不可予以渺视、不得轻视的缺点:1、性能较低因作为解释型类型语言, 代码于运行之际会逐行被翻译弄作机器代码来促成, 这样之下造成性能较编译型像 C/C、Java 等这部分语言而言会慢点。并且, 受 GIL全局解释器锁进行的相关限制原因因素影响, 多线程范畴之内那种原本的并行计算能力天生出来却没获取充分有效较佳状态发挥, 特别是说在涉及多核 CPU 的情形下根本没能够利用此多核方面可有的较多优势。所以, 在针对性能提出较高要求的任务层面像实时这种此类系统、巨大型各种计算而言是并不适宜的。示例# 计算密集型任务import time def compute(): total 0 for i in range(10**7): total i return total start_time time.time() compute() print(fTime taken: {time.time() - start_time:.2f} seconds)同样的任务用 C/C 实现速度通常会快很多。2、动态类型带来的潜在问题是那种变量类型于运行之际方才确定的动态类型语言, 不存在编译阶段所进行的静态类型检查, 十分易于引出那种极难发觉的类型错误, 动态类型具备的灵活性在团队开展协作以及处理大型项目之时极有可能带来跟代码稳定性与可读性方面相关的问题, 进而致使大型项目处在维护难度颇高这样的局面之中。示例# 可能出现的类型错误def add_numbers(a, b): return a b print(add_numbers(1, 2)) # TypeError: unsupported operand type(s) for : int and str使用, 类型注解, 以及, mypy等, 工具, 进行静态, 类型检查, 以此, 来改善。def add_numbers(a: int, b: int) - int: return a b3、内存消耗较高对象一般占用较多内存, 因其数据结构具备动态性与通用性, 还能够支持多种操作。而垃圾回收机制, 也就是GC, 有可能会致使产生额外的内存开销。这样一来, 在资源受到限制的嵌入式系统里面, 或者是对于内存密集型任务而言, 在对象占用较多内存以及垃圾回收机制可能带来额外开销的情况下, 内存效率就会比较低。4、缺乏移动和浏览器端的支持在移动开发和前端开发领域的支持较弱。5、可移植性问题不同版本场景下, 代码的执行表现有所差异, 系版本兼容性问题所致。某些运行平台未承载第三方库全面支持功能, 因而特定环境解决方案诞生, venv、pyenv即为实例。应用体系搭建初期, 顺畅虚拟环境构建乃关键步骤。虚拟环境对比剖析, 以及创建步骤流程说明, 已在风云前期文情阐述剖析, 有兴趣之人可翻阅查找参考。它的缺点重点聚焦于性能方面, 还有内存消耗方面, 以及多线程限制等方面, 这致使它在某些高性能以及特定领域当中或许并非是最佳的选择, 对于这样的情况。然而, 凭借合理的工具以及方法例如C扩展、还有异步编程、再者多进程架构等等, 许多问题能够被缓解。它的优点与缺点同时存在着, 不过它的优点通常情况下能够在大多数场景里弥补其不足之处, 从而让它依旧是开发者们的热门选择。八、学习线路最后, 给那些想要在其中充分施展才能的人一些建议, 而这些建议, 是能够依据学习者的背景以及目标进行灵活调整的以下便是一条详尽的学习路径, 该路径, 涵盖了从入门一直到高级的各类内容, 它适合不同目标的学习者选用呢比如说编程新手, 数据科学研究员, Web 开发者等等之类, 尤其是特别适合一点儿基础都没有的人把它认定为第一门编程语言先来学习的呀就在最近, 我发现我女儿的中考信息技术内容竟然也涉及到编程了呢。1、把握基础入门所涉及的基本语法, 领会变量, 明晰数据类型, 弄懂基本控制结构。学习内容与步骤安装 进行安装操作, 并装取最新版本。投身于学习使用自身所带的 IDLE, 或者去使用第三方编辑器, 比如 VS Code。基础语法打印以及输入: 其中print() 还有input(), 变量同数据类型: 含int、float、str、bool, 常见操作符: 有算术、比较、逻辑操作符。name input(What is your name? ) print(fHello, {name}!)控制结构条件语句, 即if语句, elif语句, else循环, for语句, 以及while语句。for i in range(5): print(i)常用数据结构我们有列表List, 其具备增删改查的操作, 还有切片, 存在元组Tuple还有集合Set和字典。fruits {apple: 5, banana: 3} print(fApple count: {fruits[apple]})函数定义与调用def参数与返回值def add(a, b): return a b print(add(3, 5))2、朝着更加深入的学习方向去理解, 那种层级更高的特性, 进而熟练掌控面向对象编程的方式。可以实现编写那些具备复杂性的逻辑, 创造能不断重复加以使用的代码。学习内容与步骤文件操作读写文件open()、with 语句with open(example.txt, w) as f: f.write(Hello, python!)异常处理捕获异常try-抛出异常raisetry: num int(input(Enter a number: )) except ValueError: print(Thats not a valid number!)面向对象编程 (OOP)类与对象继承与多态class Animal: def speak(self): pass class Dog(Animal): def speak(self): return Woof! d Dog() print(d.speak())模块与包模块导入创建和使用包标准库常用模块os、sys、、import random print(random.randint(1, 10))装饰器与迭代器针对 编写自定义迭代器和生成器3、专项技能发展Web开发的学习目标, 实现构建动态网站亦或是API, 其学习路径为, 通过学习Web框架诸如Flask、或者其他特定框架, 还需理解HTTP请求及其不同类型, 掌握路由原理以及模板引擎运用方式, 进行数据库操作例如借助ORM工具来实现。from flask import Flask app Flask(__name__) app.route(/) def hello_world(): return Hello, Flask! if __name__ __main__: app.run()数据科学关于机器学习的学习目标是, 借助相关工具来开展数据分析以及进行机器学习建模。其学习路径为, 先学习那种用于数据处理的库, 也就是NumPy , 接着还涉及了数据可视化方面, 然后是机器学习领域当中那个名为-learn的相关内容。import pandas as pd data pd.read_csv(data.csv) print(data.head())自动化脚本的学习目标是: 达成批量任务上的自动化状态。其学习路径涵盖: 文件方面的操作, 以及正则表达式(re)的学习运用。Web爬虫知识包含特定内容。自动化工具, 也需要进行相关学习。import requests response requests.get(https://example.com) print(response.text)网际与安全研习目的: 明了网络协定, 撰写简便的网际应用。研习路径: 开展编程研习。研习网络工具库: 诸如scapy。4、高级深化把控性能优化以及最佳实践。编就高效且可维护的大型项目。学习内容与步骤并发与异步编程使用 、 模块。理解 和异步 IO。import asyncio async def say_hello(): await asyncio.sleep(1) print(Hello, Async!) asyncio.run(say_hello())性能优化利用 , 或者 Numba 来对代码性能予以优化。剖析性能瓶颈 , 以及: 。测试与调试单元测试框架、调试工具pdb、ipdbimport unittest def add(a, b): return a b class TestMath(unittest.TestCase): def test_add(self): self.assertEqual(add(1, 2), 3) if __name__ __main__: unittest.main()部署与分发用其进行部署应用, 实施创建以及发布包, 学习建议还有资源建议是要多多动手去实践, 毕竟学习编程的关键之处在于实践, 得要多去编写代码还要多思考需定期进行复习, 也就是再去看过往学过的内容, 以此加深理解, 另外要参与开源项目, 通过参与开源社区来提升实际开发能力。它的学习线路是从基础语法起始, 一直到高级技能, 当中包含了通用编程能力、专业领域里的应用以及性能优化等方面的内容。依据你的兴趣, 还有职业目标, 能够去选择专注的方向, 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