国内使用 Python 作为主要开发语言的知名网站有哪些？-Python Tutorial-php.cn

Home

Backend Development

Python Tutorial

国内使用 Python 作为主要开发语言的知名网站有哪些？

WBOYWBOYWBOYWBOYWBOYWBOYWBOYWBOYWBOYWBOYWBOYWBOYWB

Jun 06, 2016 pm 04:23 PM

回复内容：

全部都在这里。
http://simple-is-better.com/sites/

China auto parts supplies
办公室创意生活
Sohu 邮箱
海报网
果壳网
福窝网
豆瓣
爱调研
易度在线云办公
优容网
快玩游戏
九九房
金融界
虎扑-hoopchina
贷帮网
趣奇网
欢聚网
知乎
时尚时空
游嘻板: YxPad
DNSPod 国际版
http://42qu.com
浮云脱水小说站
咕咚网
股票预警服务“涨吧”
美团
网站安全体检中心
下厨房
贝太厨房
cityweekend
flashbuy
快盘
Wopus问答
好看簿
咕咚网
三万三小游戏
ezEngage:社会化登录服务
扇贝网
TeamCola

douban用python做開發。面包旅行 - 记录探索世界的轨迹也算吧，官方的招聘说明里加入我们 - 面包旅行有提到需要python开发人员。贷帮网招Python程序猿。。。有意者请发送简历到gsy@daibang.com

Python Online Course: http://www.pythonpie.com 使用Python+Django+uWSGI+eventlet+MC开发的

最经典的案例莫过于豆瓣了 python怎么感觉不错，创业首选人力成本低。

Statement

The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn

Python vs. C : Learning Curves and Ease of UseApr 19, 2025 am 12:20 AM

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.

Python vs. C : Memory Management and ControlApr 19, 2025 am 12:17 AM

Python and C have significant differences in memory management and control. 1. Python uses automatic memory management, based on reference counting and garbage collection, simplifying the work of programmers. 2.C requires manual management of memory, providing more control but increasing complexity and error risk. Which language to choose should be based on project requirements and team technology stack.

Python for Scientific Computing: A Detailed LookApr 19, 2025 am 12:15 AM

Python's applications in scientific computing include data analysis, machine learning, numerical simulation and visualization. 1.Numpy provides efficient multi-dimensional arrays and mathematical functions. 2. SciPy extends Numpy functionality and provides optimization and linear algebra tools. 3. Pandas is used for data processing and analysis. 4.Matplotlib is used to generate various graphs and visual results.

Python and C : Finding the Right ToolApr 19, 2025 am 12:04 AM

Whether to choose Python or C depends on project requirements: 1) Python is suitable for rapid development, data science, and scripting because of its concise syntax and rich libraries; 2) C is suitable for scenarios that require high performance and underlying control, such as system programming and game development, because of its compilation and manual memory management.

Python for Data Science and Machine LearningApr 19, 2025 am 12:02 AM

Python is widely used in data science and machine learning, mainly relying on its simplicity and a powerful library ecosystem. 1) Pandas is used for data processing and analysis, 2) Numpy provides efficient numerical calculations, and 3) Scikit-learn is used for machine learning model construction and optimization, these libraries make Python an ideal tool for data science and machine learning.

Learning Python: Is 2 Hours of Daily Study Sufficient?Apr 18, 2025 am 12:22 AM

Is it enough to learn Python for two hours a day? It depends on your goals and learning methods. 1) Develop a clear learning plan, 2) Select appropriate learning resources and methods, 3) Practice and review and consolidate hands-on practice and review and consolidate, and you can gradually master the basic knowledge and advanced functions of Python during this period.

Python for Web Development: Key ApplicationsApr 18, 2025 am 12:20 AM

Key applications of Python in web development include the use of Django and Flask frameworks, API development, data analysis and visualization, machine learning and AI, and performance optimization. 1. Django and Flask framework: Django is suitable for rapid development of complex applications, and Flask is suitable for small or highly customized projects. 2. API development: Use Flask or DjangoRESTFramework to build RESTfulAPI. 3. Data analysis and visualization: Use Python to process data and display it through the web interface. 4. Machine Learning and AI: Python is used to build intelligent web applications. 5. Performance optimization: optimized through asynchronous programming, caching and code

Python vs. C : Exploring Performance and EfficiencyApr 18, 2025 am 12:20 AM

Python is better than C in development efficiency, but C is higher in execution performance. 1. Python's concise syntax and rich libraries improve development efficiency. 2.C's compilation-type characteristics and hardware control improve execution performance. When making a choice, you need to weigh the development speed and execution efficiency based on project needs.

See all articles