1、判断一个数字是否为素数;

import math
# -----------------判断一个数是否是素数------------------
def sushu(a):
i=1
for i in range(2,a):
if a%i==0:
print(i)
break
if i==a-1:
print('素数')
else:
print('不是素数')
# return; if __name__=="__main__":
sushu(17)

2、输出100以内的素数;

#---------习题说明:编写一个函数,判断一个数是否为素数,然后调用该函数输出100以内的素数---------------
# -------------------------------------------------------
def sushu02(a):
j=1
list=[]
for i in range(3,a):
for j in range(2,i):
if(i%j==0):
break
if j==i-1:
# print(i)
list.append(i)
return list # print(i,'\t')
if __name__=="__main__":
x=input("please input number:",)
t=int(x)
su=sushu02(t)
print(su)

实现效果:

aaarticlea/png;base64,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" alt="" width="660" height="88" />

3、判断三边能否构成三角形;

# ------------习题2,编写一个函数,判断三个数是否能构成一个三角形------------
import sys
def triangle(a,b,c):
if(a+b>c and a+c>b and b+c>a):
print('组成三角形' ,a,b,c)
if(a==b==c):
print("等边三角形")
elif (a == b or a == c or b == c):
print("等腰三角形")
elif(a**2+b**2==c**2 or a**2+c**2==b**2 or c**2+b**2==a**2):
print("直角三角形")
else:
print("普通三角形")
else:
print("不能组成三角形")
if __name__=="__main__":
print("please input three number:")
x=input("first number:",)
y=input("second number:",)
z=input("thrid number:",)
triangle(int(x),int(y),int(z))

实现效果:

aaarticlea/png;base64,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" alt="" width="600" height="167" />

4、输入三个数中的最大值;

#!/bin/env python
# #!--*--coding:utf-8 --*--
# ----*auth:freem*
####-----习题3:编写一个函数,输入三个数,输出最大值
import sys def com(x,y,z):
maxn=x;
if y>maxn:
maxn=y;
if z>maxn:
maxn=z
return maxn
if __name__=="__main__":
a=input("please input first number:",)
b=input("please input second number:",)
c=input("please input third number:",)
m=com(a,b,c)
print("a,b,c中最大值为:",m)

实现效果:

aaarticlea/png;base64,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" alt="" width="506" height="93" />

5、计算三角形面积;

#!/bin/env python
# #!--*--coding:utf-8 --*--
# ----*auth:freem* # -------------------习题4:编写一个函数,输入三个数,作为三角形的三个边长,计算三角形的面积---- import math def tri_area(x,y,z): # 海伦公式 p=(x+y+z)/2 S=sqart(p*(p-x)(p-y)(p-z))
if(x+y>z and x+z >y and z+y>x):
p=(x+y+z)/2
temp=p*(p-x)*(p-y)*(p-z)
S=math.sqrt(temp)
print("三角形面积为:",S)
else:
print("对不起,您输入的边长大小不能构成三角形!") if __name__=="__main__":
a=float(input("请输入第一条边:",))
b=float(input("请输入第二条边:",))
c=float(input("请输入第三条边:",))
# print(type(a))
tri_area(a,b,c)

实现效果:

aaarticlea/png;base64,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" alt="" width="447" height="101" />

aaarticlea/png;base64,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" alt="" width="470" height="105" />
6、计算传入的列表的最大值、最小值和平均值,并以元组的方式返回;

#!/bin/env python
# #!--*--coding:utf-8 --*--
# ----*auth:freem* # -------习题5:编写一个函数,计算传入的列表的最大值、最小值和平均值,并以元组的方式返回,然后调用该函数
import math
def deal_num(li):
list=[] list.append(float(max(li)))
list.append(float(min(li)))
sum=0
for i in li:
sum=sum+float(i)
aver=float(sum)/li.__len__()
list.append(aver)
print("list:",list)
return tuple(list)
if __name__=="__main__":
# print("请输入一个序列:")
# while
ll=input("please input a list,just contain number:",)
lll=ll.split(',')
# print(type(lll))
deal=deal_num(lll)
print("tuple contain max_number,min_number and average_number:",deal)

实现效果:

aaarticlea/png;base64,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" alt="" width="500" height="75" />

7、计算传入的列表的最大值、最小值和平均值,并以列表的方式返回;

#!/bin/env python
# #!--*--coding:utf-8 --*--
# ----*auth:freem* # ---习题6:编写一个函数,计算传入的元组的最大值、最小值和平均值,并以列表的方式返回,然后调用该函数。
import math
def deal_num(li):
list=[] list.append(float(max(li)))
list.append(float(min(li)))
sum=0
for i in li:
sum=sum+float(i)
aver=float(sum)/li.__len__()
list.append(aver)
print("list:",list)
return list
if __name__=="__main__":
# print("请输入一个序列:")
# while
ll=input("please input a list,just contain number:",)
lll=tuple(ll.split(','))
print("tuple:",lll)
# print(type(lll))
deal=deal_num(lll)
print("list contain max_number,min_number and average_number:",deal)

实现效果:

aaarticlea/png;base64,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" alt="" width="556" height="107" />

8、统计字符串中不同字符的个数;

#!/bin/env python
# #!--*--coding:utf-8 --*--
# ----*auth:freem* # ---习题7:编写一个函数,接收传入的字符串,统计大写字母的个数、小写字母的个数、数字的个数、其它字符的个数,并以元组的方式返回这些数,然后调用该函数; import sys
def deal_char(li):
list=[] # list.append(float(max(li)))
# list.append(float(min(li)))
upper=0
lower=0
num=0
other=0
# str.__len__()
for i in range(li.__len__()):
if li[i].isupper():
upper+=1
elif li[i].islower():
lower+=1
elif li[i].isnumeric():
num+=1
else:
other+=1
list.append(upper)
list.append(lower)
list.append(num)
list.append(other) print("list:",list)
return tuple(list)
if __name__=="__main__":
# print("请输入一个序列:")
# while
ll=input("please input some char(or a string):",) # print(type(lll))
deal=deal_char(ll)
print("tuple contain count with upper char,lower char ,number and others:",deal)

实现效果:

aaarticlea/png;base64,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" alt="" width="597" height="134" />

python 函数小实例的更多相关文章

  1. python函数小案例

    python函数 目录 python函数 1.写一个函数求三个数的和,并返回结果 2.写一个函数,求平均值,并返回结果 写一个函数,求每个数与平均值之间的差,并放回结果 1.写一个函数求三个数的和,并 ...

  2. Python 入门小实例笔记

    实例1:打印用户输入的姓名与手机号码知识点:编码,获取输入,变量,标准输出 #encoding=utf-8 import time #1.提示用户输入信息 name = input ("请输 ...

  3. python: DOM 小实例

    一.全选 全部取消  反选 全选:选择指定的所有项目. 全部取消: 取消所有选定的项目. 反选: 选择未选定的,之前已选定的则取消. <!DOCTYPE html> <html la ...

  4. python函数的实例,书写一个创建有针对性的专用密码字典的程序

    python学习,实战学习,函数的学习与使用,综合知识的运用.包括for ,while循环,if...else.. 和if... elif ... else 的条件判断! 问题描述:书写一个创建有针对 ...

  5. Python Tkinter小实例——模拟掷骰子

    什么是Tkinter? Tkinter 是 Python 的标准 GUI 库.Python 使用 Tkinter 可以快速的创建 GUI 应用程序. 由于 Tkinter 是内置到 python 的安 ...

  6. Python 函数小程序初解

    目录 作业 ==程序代码自上往下运行,建议自上而下的完成下列任务== 作业 文件a.txt内容:每一行内容分别为商品名字,价钱,个数,求出本次购物花费的总钱数 sum = 0 f = open('a. ...

  7. python爬虫小实例

    1.python爬取贴吧壁纸 1.1.获取整个页面数据 #coding=utf-8 import urllib def getHtml(url): page = urllib.urlopen(url) ...

  8. Python(五)编程小实例

    Python(五)编程小实例 抓取网页信息,并生成txt文件内容! Python抓取网页技能--Python抓取网页就是我们常看见的网络爬虫,我们今天所要用到的就是我们Python中自带的模块,用这些 ...

  9. python第六天 函数 python标准库实例大全

    今天学习第一模块的最后一课课程--函数: python的第一个函数: 1 def func1(): 2 print('第一个函数') 3 return 0 4 func1() 1 同时返回多种类型时, ...

随机推荐

  1. Atitit 图像处理 常用8大滤镜效果 Jhlabs 图像处理类库 java常用图像处理类库

    Atitit 图像处理 常用8大滤镜效果 Jhlabs 图像处理类库 java常用图像处理类库1.1. 5种常用的Photoshop滤镜,分别针对照片的曝光.风格色调.黑白照片处理.锐利度.降噪这五大 ...

  2. Liferay7 BPM门户开发之45: 集成Activiti文件上传部署流程BPMN模型

    开发文件上传,部署流程模板. 首先,开发jsp页面,deploy.jsp <%@ include file="/init.jsp" %> <h3>${RET ...

  3. 项目中是用eCharts

    1.首先在项目中引入echart.js库. <!DOCTYPE HTML> <%@page contentType="text/html; charset=UTF-8&qu ...

  4. 对HTML5新增JS Api的思考

    1.为什么javascript的变量名不使用css中的命名方法,而选择使用驼峰命名法 因为在javascript中“-”表示减法,所以如果使用“-”的话会出现不必要的问题. 2.在javascript ...

  5. 云计算之路-阿里云上:消灭“黑色n秒”第三招——禁用网卡的TCP/IP Offload

    程咬金有三板斧,我们有三招.在这篇博文中我们要出第三招,同时也意味着昨天在“希望的田野”上的第二招失败了. 前两招打头(CPU)不凑效,这一招要换一个部位,但依然要坚持攻击敌人最弱(最忙最累)部位的原 ...

  6. ASP.NET MVC路由解析

    继续往下看<ASP.NET MVC5框架揭秘>. ASP.NET系统通过注册路由和现有的物理文件路径发生映射.而对于ASP.NET MVC来说,请求的是某个Controller中的具体的A ...

  7. 轻松自动化---selenium-webdriver(python) (十一)

    本节重点: 控制滚动条到底部 有时候我们需要控制页面滚动条上的滚动条,但滚动条并非页面上的元素,这个时候就需要借助js是来进行操作.一般用到操作滚动条的会两个场景: 注册时的法律条文需要阅读,判断用户 ...

  8. CNN笔记

    Deep Learning是全部深度学习算法的总称,CNN是深度学习算法在图像处理领域的一个应用. 转 http://blog.csdn.net/stdcoutzyx/article/details/ ...

  9. 实现winform DataGridView控件判断滚动条是否滚动到当前已加载的数据行底部

    判断 DataGridView控件滚动条是否滚动到当前已加载的数据行底部,其实方法很简单,就是为DataGridView控件添加Scroll事件,然后写入以下代码就可以了,应用范围:可实现分部加载数据 ...

  10. 【转】Xml序列化

    XML序列化是将对象的公共属性和字段转换为XML格式,以便存储或传输的过程.反序列化则是从XML输出中重新创建原始状态的对象.XML序列化中最主要的类是XmlSerializer类.它的最重要的方法是 ...