Python3学习笔记（MOOC）

文本进度条实例

#!/usr/bin/env python3
import time
#for i in range(101):
#       print ("\r{:3.0f}%".format(i),end="")
#       time.sleep(0.1)
scale = 50
print("执行开始".center(scale//2,"-"))
start = time.perf_counter()
for i in range(scale+1):
        a = '*' * i
        b = '-' * (scale - i)
        c = (i/scale)*100
        time.sleep(0.1)
        dur = time.perf_counter() - start
        print ("\r{:^3.0f}%[{}->{}]{:.2f}s".format(c,a,b,dur),end="")
print("")
print("执行结束".center(scale//2,"-"))

BMI指数计算（if条件）

#!/usr/bin/env python3
def BMI():
        height,weight = eval(input("请输入身高（米）和体重（公斤）[逗号隔开]："))
        bmi = weight / pow(height,2)
        print("BMI指数为：{:0.2f}".format(bmi))
        who,nat="",""
        if bmi < 18.5:
                who, nat = "偏瘦","偏瘦"
        elif 18.5 <= bmi < 24:
                who, nat = "正常","正常"
        elif 24 <= bmi < 25:
                who, nat = "正常","偏胖"
        elif 25 <= bmi < 28:
                who, nat = "偏胖","偏胖"
        elif 28 <= bmi < 30:
                who, nat = "偏胖","肥胖"
        else:
                who, nat = "肥胖","肥胖"
        print("BMI指标为：国际：{} 国内：{}".format(who,nat))
try:
        BMI()
except:
        print("输入错误")

π值计算（公式和蒙特卡罗方法）

#!/usr/bin/env python3
#计算pi
pi = 0
N = 100
for k in range(N):
        pi += 1/pow(16,k)*(4/(8*k+1)-2/(8*k+4)-1/(8*k+5)-1/(8*k+6))
print("圆周率是：{}".format(pi))

#蒙特卡洛方法

from random import random
from time import perf_counter
DARTS = 1000*1000
hits = 0.0
start = perf_counter()
for i in range(1,DARTS+1):
        x,y = random(),random()
        dist = pow(x**2+y**2,0.5)
        if dist <= 1.0:
                hits += 1
pi = 4* (hits/DARTS)
print("圆周率是：{}".format(pi))
print("运行时间是：{:.2f}s".format(perf_counter()-start))

异常处理

#!/usr/bin/env python3
try:
        num = eval(input("请输入一个整数："))
        print(num ** 2)
except:#try执行错误后执行
        print("输入错误")
else:#正常运行后执行
        print("输入正确")
finally:#无论try是否执行正确，在最后都会执行
        print("程序结束")

递归实例：斐波那契数列、汉诺塔、科赫雪花

#!/usr/bin/env python3
#斐波那契数列
def fibo(n):
    if n == 1 or n == 2:
        return 1
    else:
        return fibo(n-1)+fibo(n-2)
print(fibo(8))
#汉诺塔
def hano(n,src,mid,dst):
    if n == 1:
          print(n,"{}->{}".format(src,dst))
    else:
        hano(n-1,src,dst,mid)
        print(n,"{}->{}".format(src,dst))
        hano(n-1,mid,src,dst)
hano(3,"A","B","C")
#科赫雪花
import turtle
def koch(size,n):
    if n == 0:
        turtle.fd(size)
    else:
        for angle in [0,60,-120,60]:
            turtle.left(angle)
            koch(size/3,n-1)
def main():
    turtle.setup(800,800)
    turtle.penup()
    turtle.goto(-200,100)
    turtle.pendown()
    turtle.pensize(2)
    level = 3
    koch(400,level)
    turtle.right(120)
    koch(400,level)
    turtle.right(120)
    koch(400,level)
    turtle.hideturtle()
main()

词频统计

#统计单词频率
def getTtext(filename):
    txt = open(filename,'r',encoding='utf-8').read()
    txt = txt.lower()
    for ch in '!"#$%&()*+,-./:;<=>?@[\\]^_‘{|}~':
        txt = txt.replace(ch,' ')
    return txt
text = getTtext('text.txt')
words = text.split()
counts = {}
for word in words:
    counts[word] = counts.get(word,0) + 1
items = list(counts.items())
items.sort(key=lambda x:x[1],reverse=True)
for i in range(10):
    word,count = items[i]
    print("{0:<10}{1:>5}".format(word,count))

jieba jieba分词的三种模式
# 精确模式：jieba.lcut把文本的切分开，不存在冗余单词
# 全模式：把文本中所有可能的词语都扫描出来，冗余
# 搜索引擎模式：在精确基础上，对长词再次切分

In [1]: import jieba
In [2]: jieba.lcut("中国是一个伟大的国家").
Out[2]: ['中国', '是', '一个', '伟大', '的', '国家']
In [3]: jieba.lcut("中国是一个伟大的国家",cut_all=True)
Out[3]: ['中国', '国是', '一个', '伟大', '的', '国家']
In [4]: jieba.lcut_for_search("中华人民共和国是伟大的")
Out[4]: ['中华', '华人', '人民', '共和', '共和国', '中华人民共和国', '是', '伟大', '的']
In [5]: jieba.add_word("故园旧梦")