本文实例讲解了Python中除法使用的注意事项,是非常重要的技巧,对于Python程序设计来说有很好的借鉴价值。具体分析如下:
现来看如下示例:
def avg(first, *rest): return (first + sum(rest)) / (1 + len(rest)) # Sample use avg(1, 2) # 1.5 avg(1, 2, 3, 4) # 2.5
源程序只是为了演示变长参数的使用,不过 Python 2.7.1 的解释器里,我得到的结果却和注释的结果不一样
>>> def avg(first, *rest): ... return (first + sum(rest)) / (1 + len(rest)) ... >>> avg(1, 2) 1 >>> avg(1, 2, 3, 4) 2
可以很明显的看到,小数点后的数据被截断了,我记得两个整数相除,"//" 应该才是取整,难道我记错了?
>>> def avg(first, *rest): ... return (first + sum(rest)) // (1 + len(rest)) # change '/' to '//' ... >>> avg(1, 2) 1 >>> avg(1, 2, 3, 4) 2
将 “/” 改成了“//”,得到的结果是一样的,“//”的确是取整这一点我是没记错,不过为什么“/”的结果也是截断了的?
同样的程序我在 3.4.1 的解释器里面做了测试,得到了预想的结果:
>>> def avg(first, *rest): ... return (first + sum(rest)) / (1 + len(rest)) ... >>> avg(1, 2) 1.5 >>> avg(1, 2, 3, 4) 2.5 >>> def avg(first, *rest): ... return (first + sum(rest)) // (1 + len(rest)) # change '/' to '//' ... >>> avg(1, 2) 1 >>> avg(1, 2, 3, 4) 2
可以看到在 3.4.1 的解释器里,“/”的结果保留了小数位,而“//”则是取整后的结果
搜索之后,找到了stackoverflow上的这个问题:Python里如何强制除法的结果为浮点数? 注意这个是针对 2.x 的版本,3.x 里面并不存在这样的问题
答案的前两个解决方案,都很不错:
方法1:
>>> from __future__ import division >>> a = 4 >>> b = 6 >>> c = a / b >>> c 0.66666666666666663
方法2:
类似于C语言里面的做法:
c = a / float(b)
相信本文所述实例会对大家的Python程序设计有一定的帮助。

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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'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.

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 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.

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.

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 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.


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