回复内容:
最近用到过的几个:自动化图表用到 matplotlib: python plotting,粗鄙如我也能秒杀excel的图表啦
轻量级demo神器 Welcome | Flask (A Python Microframework),django拜拜吧
dm预研用 scikit-learn: machine learning in Python
很好玩的主题模型实现 gensim: Topic modelling for humans
ctypes、nltk什么的就不说了,免得被人说土,虽然用的还是蛮多的…… 下面很多不是python的模块:
私生子系列
=====================================
Python和Lisp的私生子:
Welcome to Hy’s documentation!
如果你了解lisp就知道这货多么的可爱。
=====================================
Python和Excel的vba的私生子:
Python in Excel
利用python 让你的EXCEL飞起来。
=====================================
Python不需要AUTOCAD这个老婆,就可以生dxf这个私生子。
ezdxf 0.7.0 documentation
=====================================
python也可以是别人的私生子:
aardio
有了这货,写桌面程序就不需要你学习古老的TK,庞大的QT,直接拖界面或者用html写界面或者用flash写界面或者。。。。
你还可以吧c++代码 .net代码,php代码,lisp代码,python代码,本身的aardio代码揉进1个程序里为你服务,都说python是胶水语言,我觉得这货是胶水的胶水。
=====================================
python因为长得漂亮(官方说法是“优雅”),被“微软”这个大款xx了
IronPython - Home
===================================== Python资源大全 - python模块大全,python资料 vinta/awesome-python · GitHub
整理了各个用途的各种有趣的模块 这看你如何定义有趣啦。
如果指新奇好玩的话。我想到以下这些~
有时邂逅那些能简化我们的工作的库,也会由衷会心一笑觉得pythonic,也觉得有趣呢,可以参考我的另一个回答 Python 中的哪些库让你相见恨晚?
- 首先,当然是python内置的彩蛋 > import this
The Zen of Python, by Tim Peters
Beautiful is better than ugly.
Explicit is better than implicit.
Simple is better than complex.
Complex is better than complicated.
- faker
A library for generating fake data such as names, addresses, and phone numbers
- 之前好像还在博客里看到一个比较恶搞的模块 girlfriend ,现在pypi里好像没有了
- pydown
- vim
- lassie
- Pipe
A Python library to use infix notation in Python顾名思义即可~如果你喜欢linux下的管道机制(我十分喜欢管道这个设计),那么你也会喜欢上这个库的
- twosheds
- pyquery
- geeknote
多逛github吧,上边有许多好玩的东西呢! antigravity… 之前做游戏,用过一个图形化模块。PyGame小小的推荐一下。
手机客户端竟然不能贴图。。。
----------------------------------------------------发现手机端可以贴图了!
果断上两张!


自己做的哦!游戏图片来自素材。字体丑了点见谅。另外csdn有源码下载。就叫python版flappybird! __future__ scapy 数值计算: numpy + scipy
画图: matplotlib
profile: line_profiler

Python and C each have their own advantages, and the choice should be based on project requirements. 1) Python is suitable for rapid development and data processing due to its concise syntax and dynamic typing. 2)C is suitable for high performance and system programming due to its static typing and manual memory management.

Choosing Python or C depends on project requirements: 1) If you need rapid development, data processing and prototype design, choose Python; 2) If you need high performance, low latency and close hardware control, choose C.

By investing 2 hours of Python learning every day, you can effectively improve your programming skills. 1. Learn new knowledge: read documents or watch tutorials. 2. Practice: Write code and complete exercises. 3. Review: Consolidate the content you have learned. 4. Project practice: Apply what you have learned in actual projects. Such a structured learning plan can help you systematically master Python and achieve career goals.

Methods to learn Python efficiently within two hours include: 1. Review the basic knowledge and ensure that you are familiar with Python installation and basic syntax; 2. Understand the core concepts of Python, such as variables, lists, functions, etc.; 3. Master basic and advanced usage by using examples; 4. Learn common errors and debugging techniques; 5. Apply performance optimization and best practices, such as using list comprehensions and following the PEP8 style guide.

Python is suitable for beginners and data science, and C is suitable for system programming and game development. 1. Python is simple and easy to use, suitable for data science and web development. 2.C provides high performance and control, suitable for game development and system programming. The choice should be based on project needs and personal interests.

Python is more suitable for data science and rapid development, while C is more suitable for high performance and system programming. 1. Python syntax is concise and easy to learn, suitable for data processing and scientific computing. 2.C has complex syntax but excellent performance and is often used in game development and system programming.

It is feasible to invest two hours a day to learn Python. 1. Learn new knowledge: Learn new concepts in one hour, such as lists and dictionaries. 2. Practice and exercises: Use one hour to perform programming exercises, such as writing small programs. Through reasonable planning and perseverance, you can master the core concepts of Python in a short time.

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.


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