好玩有趣，入门级绘图库turtle，文档在此。
文档中的实例：太阳花。
from turtle import *
color('red', 'yellow')
begin_fill()
while True:
forward(200)
left(170)
if abs(pos()) < 1:
break
end_fill()
done()画一个六芒星：
import turtle as t
# size传入最大的圆的半径
def draw_Star(size):
t.setup(1200, 1000)
t.speed(11)
t.pensize(2)
t.pencolor('grey')
for r, pen_size in [(size//7, 3), (size*6//7, 4), (size, 4)]:
t.penup()
t.goto(0, -r)
t.pendown()
t.pensize(pen_size)
t.circle(r)
t.penup()
t.goto(0, 0)
r = size * 5.5 // 7
for i in range(6):
t.pendown()
t.pensize(3)
t.seth(i * 60 + 30)
t.fd(r)
t.goto(0, 0)
t.goto(0, r)
t.seth(-150)
t.pensize(5)
for i in range(6):
t.fd(r)
t.left(60)
r = r - size // 50
t.goto(0, r)
t.pensize(10)
t.seth(-120)
t.pencolor('orange')
for i in range(3):
t.fd(r * (3**0.5))
t.left(120)
t.penup()
t.goto(0, 0)
t.seth(30)
t.fd(r)
t.seth(-180)
t.pendown()
for i in range(3):
t.fd(r * (3 ** 0.5))
t.left(120)
t.hideturtle()
t.done()
draw_Star(400)不停向下打印的版本：
import time
def bar(scale):
print('===========执行开始============')
for i in range(scale + 1):
a = '*' * i
b = '.' * (scale - i)
c = (i / scale) * 100
print('\r{:^3.0f}%[{}->{}]'.format(c, a, b), end = '')
time.sleep(0.05)
print('\n===========执行结束============')单行刷新版本：
import time
def pro_bar(scale):
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
dur = time.perf_counter() - start
print('\r{:^3.0f}%[{}->{}] {:.2f}s'.format(c, a, b, dur), end = '')
time.sleep(0.05)
print('\n' + '执行结束'.center(scale // 2, '='))
pro_bar(50)单行刷新效果在cmd窗口中运行才有效，IDLE禁\r转义字符。
随机数生成使用random库，文档在此。思路即是随机生成点，落在正方形内。计算正方形内的圆内落点与正方形内落点之比，近似为面积之比，随机数越随机，数量越大越准确。
from random import random
from time import perf_counter
def calPI(N = 100):
hits = 0
start = perf_counter()
for i in range(1, N*N+1):
x, y = random(), random()
dist = pow(x ** 2 + y ** 2, 0.5)
if dist <= 1.0:
hits += 1
pi = (hits * 4) / (N * N)
use_time = perf_counter() - start
return pi, use_time
PI, use_time = calPI(1000)
print('\nuse Monte Carlo method to calculate PI: {}'.format(PI))
print('use time: {} s'.format(use_time))koch雪花曲线是分形几何中的一个经典曲线。
使用turtle库，简单的递归即可绘制。
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(1200, 1000)
turtle.speed(11)
turtle.penup()
turtle.goto(-300, 200)
turtle.pendown()
turtle.pensize(2)
level = 4
koch(600, level) # 3阶科赫曲线
turtle.right(120)
koch(600, level)
turtle.right(120)
koch(600, level)
turtle.hideturtle()
turtle.done()
main()输入一组数据，计算均值，方差，中位数，绝对相对误差
# -*- coding: utf-8 -*-
# 输入数据
def getNum():
nums = []
iNumStr = input('please input a sequence of numbers (enter to exit): ')
while iNumStr != '':
nums.append(eval(iNumStr))
iNumStr = input('please input a sequence of numbers (enter to exit): ')
return nums
# 平均数
def average(numbers):
return sum(numbers) / len(numbers)
# 标准差
def dev(numbers, average):
sdev = 0.0
for num in numbers:
sdev += (num - average) ** 2
return pow(sdev / len(numbers), 0.5)
# 中位数
def median(numbers):
sorted(numbers)
size = len(numbers)
if size % 2 == 0:
return (numbers[size//2-1] + numbers[size//2]) / 2
else:
return numbers[size//2]
# 绝对与相对误差
def rel_dev(numbers, average):
_max = max(abs(max(numbers) - average), abs(min(numbers) - average))
return _max, _max / average
def main():
nums = getNum()
if len(nums) == 0:
print('no data')
else:
ave = average(nums)
devs = rel_dev(nums, ave)
print('和:{:.4f},平均数:{:.4f},中位数:{:.4f},方差:{:.4f},绝对误差:{:4f},相对误差:{:.4f}' \
.format(sum(nums), ave, median(nums), dev(nums, ave), devs[0], devs[1]))
if __name__ == '__main__':
main()小说词频统计
策略：
中文小说：使用第三方库jieba切分，统计
英文小说：去掉特殊干扰字符，直接切分为单词，遍历统计
统计莎士比亚经典名著：Hamlet。统计最高出现单词。
def getText():
txt = open('novels/hamlet.txt', 'r').read()
txt = txt.lower() # 去掉大小写干扰
# 去掉特殊符号干扰
for ch in '!"#$%&()*+,-./:;<=>?@[\\]^_`{|}~\'':
txt = txt.replace(ch, ' ')
return txt
hamletTxt = getText()
words = hamletTxt.split()
counts = {}
for word in words:
counts[word] = counts.get(word, 0) + 1
items = list(counts.items())
# 将其按照词出现数量按照降序排列
items.sort(key = lambda x : x[1], reverse = True)
for i in range(20):
word, count = items[i]
print('{:^10}{:^10}'.format(word, count))其中一个jieba库是一个对中文文本依照汉字间关联概率进行词组划分的第三方库，使用简单，且非常好用，文档在此
import jieba
def getWords():
txt = open('novels/threekingdoms.txt', 'r', encoding = 'utf-8').read()
words = jieba.lcut(txt)
counts = {}
for word in words:
if len(word) == 1:
continue
else:
counts[word] = counts.get(word, 0) + 1
word_list = list(counts.items())
word_list.sort(key = lambda x : x[1], reverse = True)
return word_listimport jieba
def countWords(excludes, merges):
txt = open('novels/threekingdoms.txt', 'r', encoding = 'utf-8').read()
words = jieba.lcut(txt)
counts = {}
# 取出长度为一的词和符号以及excludes中的词
for word in words:
if len(word) == 1 or word in excludes:
continue
else:
counts[word] = counts.get(word, 0) + 1
# 合并名称相同的人名
for merge in merges:
for name in merge[1]:
counts[merge[0]] += counts.get(name, 0)
del counts[name]
word_list = list(counts.items())
word_list.sort(key = lambda x : x[1], reverse = True)
return word_list
excludes = {'却说','二人','不可','主公','陛下','汉中','只见','众将','后主','蜀兵','上马','大叫','太守','此人','夫人',
'先主','后人','背后','城中','天子','一面','何不','大军','忽报','先生','百姓','何故','不能','如此','如何',
'然后','先锋','不如','赶来','原来','令人','江东','下马','喊声','正是','徐州','忽然','荆州','左右','军马',
'因此','成都','不见','未知','大败','大事','之后','一军','引军','起兵','军中','接应','引兵','次日','大喜',
'进兵','大惊','可以','以为','大怒','不得','心中','下文','一声','追赶','粮草','天下','东吴','于是','都督',
'曹兵','一齐','分解','回报','分付','只得','出马','三千','大将','许都','随后','报知','今日','不敢','魏兵',
'前面','之兵','且说','众官','洛阳','领兵','商议','军士','星夜','精兵','城上','之计','不肯','相见','其言',
'一日','而行','文武','襄阳','准备','若何','出战','亲自','必有','一人','人马','不知','何人','此事','之中',
'伏兵','祁山','乘势','忽见','大笑','樊城','兄弟','首级','立于','西川','传令','当先','五百','一彪','坚守',
'此时','之间','投降','五千','埋伏','长安','三路','遣使','将军','关兴','军师','朝廷','三军','大王','回见',
'大将军','必然','将士','是夜','小路' }
merges = [ ('刘备',('玄德','玄德曰','玄德问','刘玄德','玄德大','玄德自','玄德闻','皇叔','刘皇叔')),
('关羽',('关公','云长','关云长')),
('孔明',('诸葛亮','孔明曰','孔明笑','孔明之','孔明自')),
('曹操',('丞相','孟德','曹公','曹孟德')),
('张飞',('翼德','张翼德'))
]
word_list = countWords(excludes, merges)
for i in range(30):
word, count = word_list[i]
print('{0:^10}{1:{3}^10}{2:^15}'.format(i+1, word, count, chr(12288))) # chr(12288)为中文空格结果如下，当然其中类似将军、英雄、主公、大哥、君这种词语无法判断指的是谁，这里仅统计能够判断的，所以这里只能做一个相对的参考。
让梦想慢慢成长
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