Python

divmod(7,2) //(3,1)

if b > a:
  print("b is greater than a")
elif a == b:
  print("a and b are equal")
else:
  print("a is greater than b")

fruits = ["apple", "banana", "cherry"]
for x in fruits:
  print(x)

a,b = 2,0

a,b = 2,0
a,b,a = 1,a,4
>>>a,b(4,2)

def reverseList(head):
    prev = None
    while head:
        cur = head
        head = head.next
        cur.next = prev
        prev = cur
    return prev

def reverseList(head):
    prev = None
    while head:
        head.next,prev,head = prev,head,head.next
    return prev

if __name__ == '__main__':

L = range(1,5)#创建连续list，即[1,2,3,4],间隔默认为1，不包含最后一个元素
L = range(1,10,2)#创建间隔为2的连续list，即[1,3,5,7,9],同样不包含最后一个元素
L.append(var) #追加元素
L.insert(index,var)#在指定位置追加元素
L.pop(var) #返回最后一个元素，并在list中删除
L.remove(var) #删除第一次出现的该元素
L.count(var) #该元素在列表中出现的个数
L.remove(var) #删除第一次出现的该元素
L.extend(list) #追加list，即合并list到L上
L.sort() #排序
L.reverse() #倒序
len(L)#获取列表长度
del L[1] #删除指定下标的元素
del L[1:3] #删除指定下标范围的元素

m = n = 3
test = [[0] * m] * n
print("test =", test)

test[0][0] = 233
print("test =", test)

//输出
test = [[0, 0, 0], [0, 0, 0], [0, 0, 0]]
test = [[233, 0, 0], [233, 0, 0], [233, 0, 0]]

test = [[0 for i in range(m)] for j in range(n)]

dict_1={
  'name':'zhangsan',
  'age':22,
  'phone':110,
  'sex':'男'
}
dict2=dict.copy() #克隆字典，即另一个拷贝。

name=dict_1['name']

//如果key不存在则直接添加数据，如果key存在则修改数据
dict_1['name']='lisi'
dict_1['sss']='4s'

del dict['Name']  # 删除键是'Name'的条目
dict.clear()      # 清空字典所有条目
del dict

keys=dict_1.keys()

values=dict_1.values()
#for循环 取出所有的value
for value in values:
    print(value)

items=dict_1.items()
#for循环遍历items
for item in items:
    # print(item)
    #从元组中 根据索引取出数据
    key=item[0]
    value=item[1]
    print('键：%s值：%s'%(key,value))

#python2中 有has_key函数，可以直接调用
dict_1.has_key(key)
if 'phone' in dict_1.keys():
    print('有这个key')
else:
    print('没有这个key')

import threading

from smtplib import SMTP
from email.header import Header
from email.mime.text import MIMEText


def main():
    # 请自行修改下面的邮件发送者和接收者
    sender = 'abcdefg@126.com'
    receivers = ['uvwxyz@qq.com', 'uvwxyz@126.com']
    message = MIMEText('用Python发送邮件的示例代码.', 'plain', 'utf-8')
    message['From'] = Header('王大锤', 'utf-8')
    message['To'] = Header('骆昊', 'utf-8')
    message['Subject'] = Header('示例代码实验邮件', 'utf-8')
    smtper = SMTP('smtp.126.com')
    # 请自行修改下面的登录口令
    smtper.login(sender, 'secretpass')
    smtper.sendmail(sender, receivers, message.as_string())
    print('邮件发送完成!')


if __name__ == '__main__':
    main()

from smtplib import SMTP
from email.header import Header
from email.mime.text import MIMEText
from email.mime.image import MIMEImage
from email.mime.multipart import MIMEMultipart

import urllib


def main():
    # 创建一个带附件的邮件消息对象
    message = MIMEMultipart()
    
    # 创建文本内容
    text_content = MIMEText('附件中有本月数据请查收', 'plain', 'utf-8')
    message['Subject'] = Header('本月数据', 'utf-8')
    # 将文本内容添加到邮件消息对象中
    message.attach(text_content)

    # 读取文件并将文件作为附件添加到邮件消息对象中
    with open('/Users/Hao/Desktop/hello.txt', 'rb') as f:
        txt = MIMEText(f.read(), 'base64', 'utf-8')
        txt['Content-Type'] = 'text/plain'
        txt['Content-Disposition'] = 'attachment; filename=hello.txt'
        message.attach(txt)
    # 读取文件并将文件作为附件添加到邮件消息对象中
    with open('/Users/Hao/Desktop/汇总数据.xlsx', 'rb') as f:
        xls = MIMEText(f.read(), 'base64', 'utf-8')
        xls['Content-Type'] = 'application/vnd.ms-excel'
        xls['Content-Disposition'] = 'attachment; filename=month-data.xlsx'
        message.attach(xls)
    
    # 创建SMTP对象
    smtper = SMTP('smtp.126.com')
    # 开启安全连接
    # smtper.starttls()
    sender = 'abcdefg@126.com'
    receivers = ['uvwxyz@qq.com']
    # 登录到SMTP服务器
    # 请注意此处不是使用密码而是邮件客户端授权码进行登录
    # 对此有疑问的读者可以联系自己使用的邮件服务器客服
    smtper.login(sender, 'secretpass')
    # 发送邮件
    smtper.sendmail(sender, receivers, message.as_string())
    # 与邮件服务器断开连接
    smtper.quit()
    print('发送完成!')


if __name__ == '__main__':
    main()

import urllib.parse
import http.client
import json


def main():
    host  = "106.ihuyi.com"
    sms_send_uri = "/webservice/sms.php?method=Submit"
    # 下面的参数需要填入自己注册的账号和对应的密码
    params = urllib.parse.urlencode({'account': '你自己的账号', 'password' : '你自己的密码', 'content': '您的验证码是：147258。请不要把验证码泄露给其他人。', 'mobile': '接收者的手机号', 'format':'json' })
    print(params)
    headers = {'Content-type': 'application/x-www-form-urlencoded', 'Accept': 'text/plain'}
    conn = http.client.HTTPConnection(host, port=80, timeout=30)
    conn.request('POST', sms_send_uri, params, headers)
    response = conn.getresponse()
    response_str = response.read()
    jsonstr = response_str.decode('utf-8')
    print(json.loads(jsonstr))
    conn.close()


if __name__ == '__main__':
    main()

class Node(object)
        def _init_(sef,data,next = None):
               self.data = data
               self.next = next

INSTALLED_APPS = [
    'rest_framework',
]

# 下面的配置根据项目需要进行设置
REST_FRAMEWORK = {
    # 配置默认页面大小
    # 'PAGE_SIZE': 10,
    # 配置默认的分页类
    # 'DEFAULT_PAGINATION_CLASS': '...',
    # 配置异常处理器
    # 'EXCEPTION_HANDLER': '...',
    # 配置默认解析器
    # 'DEFAULT_PARSER_CLASSES': (
    #     'rest_framework.parsers.JSONParser',
    #     'rest_framework.parsers.FormParser',
    #     'rest_framework.parsers.MultiPartParser',
    # ),
    # 配置默认限流类
    # 'DEFAULT_THROTTLE_CLASSES': (
    #     '...'
    # ),
    # 配置默认授权类
    # 'DEFAULT_PERMISSION_CLASSES': (
    #     '...',
    # ),
    # 配置默认认证类
    # 'DEFAULT_AUTHENTICATION_CLASSES': (
    #     '...',
    # ),
}

try:
    token = 'eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJleHAiOjE1OTQ4NzIzOTEsInVzZXJpZCI6MTAwMDF9.FM-bNxemWLqQQBIsRVvc4gq71y42I9m2zt5nlFxNHUo'
    payload = jwt.decode(token, settings.SECRET_KEY)
except InvalidTokenError:
    raise AuthenticationFailed('无效的令牌或令牌已经过期')

import dlib
import cv2
import numpy as np
import math
predictor_path='shape_predictor_68_face_landmarks.dat'
 
#使用dlib自带的frontal_face_detector作为我们的特征提取器
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor(predictor_path)

def landmark_dec_dlib_fun(img_src):
    img_gray = cv2.cvtColor(img_src,cv2.COLOR_BGR2GRAY)
 
    land_marks = []
 
    rects = detector(img_gray,0)
 
    for i in range(len(rects)):
        land_marks_node = np.matrix([[p.x,p.y] for p in predictor(img_gray,rects[i]).parts()])
        # for idx,point in enumerate(land_marks_node):
        #     # 68点坐标
        #     pos = (point[0,0],point[0,1])
        #     print(idx,pos)
        #     # 利用cv2.circle给每个特征点画一个圈，共68个
        #     cv2.circle(img_src, pos, 5, color=(0, 255, 0))
        #     # 利用cv2.putText输出1-68
        #     font = cv2.FONT_HERSHEY_SIMPLEX
        #     cv2.putText(img_src, str(idx + 1), pos, font, 0.8, (0, 0, 255), 1, cv2.LINE_AA)
        land_marks.append(land_marks_node)
 
    return land_marks
'''
方法： Interactive Image Warping 局部平移算法
'''
 
 
def localTranslationWarp(srcImg,startX,startY,endX,endY,radius):
 
    ddradius = float(radius * radius)
    copyImg = np.zeros(srcImg.shape, np.uint8)
    copyImg = srcImg.copy()
 
    # 计算公式中的|m-c|^2
    ddmc = (endX - startX) * (endX - startX) + (endY - startY) * (endY - startY)
    H, W, C = srcImg.shape
    for i in range(W):
        for j in range(H):
            #计算该点是否在形变圆的范围之内
            #优化，第一步，直接判断是会在（startX,startY)的矩阵框中
            if math.fabs(i-startX)>radius and math.fabs(j-startY)>radius:
                continue
 
            distance = ( i - startX ) * ( i - startX) + ( j - startY ) * ( j - startY )
 
            if(distance < ddradius):
                #计算出（i,j）坐标的原坐标
                #计算公式中右边平方号里的部分
                ratio=(  ddradius-distance ) / ( ddradius - distance + ddmc)
                ratio = ratio * ratio
 
                #映射原位置
                UX = i - ratio  * ( endX - startX )
                UY = j - ratio  * ( endY - startY )
 
                #根据双线性插值法得到UX，UY的值
                value = BilinearInsert(srcImg,UX,UY)
                #改变当前 i ，j的值
                copyImg[j,i] =value
 
    return copyImg

#双线性插值法
def BilinearInsert(src,ux,uy):
    w,h,c = src.shape
    if c == 3:
        x1=int(ux)
        x2=x1+1
        y1=int(uy)
        y2=y1+1
 
        part1=src[y1,x1].astype(np.float)*(float(x2)-ux)*(float(y2)-uy)
        part2=src[y1,x2].astype(np.float)*(ux-float(x1))*(float(y2)-uy)
        part3=src[y2,x1].astype(np.float) * (float(x2) - ux)*(uy-float(y1))
        part4 = src[y2,x2].astype(np.float) * (ux-float(x1)) * (uy - float(y1))
 
        insertValue=part1+part2+part3+part4
        return insertValue.astype(np.int8)

def face_thin_auto(src):
 
    landmarks = landmark_dec_dlib_fun(src)
 
    #如果未检测到人脸关键点，就不进行瘦脸
    if len(landmarks) == 0:
        return
 
    for landmarks_node in landmarks:
        left_landmark= landmarks_node[3]
        left_landmark_down=landmarks_node[5]
 
        right_landmark = landmarks_node[13]
        right_landmark_down = landmarks_node[15]
 
        endPt = landmarks_node[30]
 
 
        #计算第4个点到第6个点的距离作为瘦脸距离
        r_left=math.sqrt((left_landmark[0,0]-left_landmark_down[0,0])*(left_landmark[0,0]-left_landmark_down[0,0])+
                         (left_landmark[0,1] - left_landmark_down[0,1]) * (left_landmark[0,1] - left_landmark_down[0, 1]))
 
        # 计算第14个点到第16个点的距离作为瘦脸距离
        r_right=math.sqrt((right_landmark[0,0]-right_landmark_down[0,0])*(right_landmark[0,0]-right_landmark_down[0,0])+
                         (right_landmark[0,1] -right_landmark_down[0,1]) * (right_landmark[0,1] -right_landmark_down[0, 1]))
 
        #瘦左边脸
        thin_image = localTranslationWarp(src,left_landmark[0,0],left_landmark[0,1],endPt[0,0],endPt[0,1],r_left)
        #瘦右边脸
        thin_image = localTranslationWarp(thin_image, right_landmark[0,0], right_landmark[0,1], endPt[0,0],endPt[0,1], r_right)
 
    #显示
    cv2.imshow('thin',thin_image)
    cv2.imwrite('thin.jpg',thin_image)

def main():
    src = cv2.imread('timg4.jpg')
    cv2.imshow('src', src)
    face_thin_auto(src)
    cv2.waitKey(0)
 
if __name__ == '__main__':
    main()