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process.py
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from wxpy import *
import math
from PIL import Image
import matplotlib.pyplot as plt
import jieba
from wordcloud import WordCloud
import numpy as np
import os
import wc2char
friends = None
downloaded_avatar = False
# 创建存放文件夹
def create_filepath(path_name):
avatar_dir = os.getcwd() + '\\' + path_name + '\\'
if not os.path.exists(avatar_dir):
os.mkdir(avatar_dir)
return avatar_dir
def login_success():
print('login success!')
def developing():
print("功能开发中...")
# 下载头像
def download_avatar():
global downloaded_avatar
avatar_dir = create_filepath('avatar')
print("头像下载中，请稍等...")
if not downloaded_avatar:
num = 0
for friend in friends:
friend.get_avatar(avatar_dir + '\\' + str(num) + '.jpg')
# print("昵称 ： %s" % friend.nick_name)
num+=1
if num % 20 == 0:
print("头像读取中，请耐心等待{}%".format(round(num/len(friends)*100,2)),end='\r')
downloaded_avatar = True
print('\n')
return avatar_dir
def process(number):
if number == 1:
gen_avatar()
elif number == 2:
gen_sex()
elif number == 3:
gen_word_cloud()
elif number == 4 or number == 7:
developing()
elif number == 5:
same_friend()
elif number == 6:
gen_avatar_hanzi()
else:
pass
def gen_avatar():
print("#1 ----生成所有微信好友图片墙----")
# 保存好友头像
# 初始化机器人，扫码登录
global friends
if friends == None:
bot = Bot(console_qr=True, login_callback=login_success )
friends = bot.friends(update=True)
avatar_dir = download_avatar()
# 拼接头像
length = len(os.listdir(avatar_dir))
image_size = 1920
each_size = math.ceil(image_size / math.floor(math.sqrt(length)))
# 计算所需行数和列数的头像数
x_lines = math.ceil(math.sqrt(length))
y_lines = math.ceil(math.sqrt(length))
image = Image.new('RGB',(each_size * x_lines, each_size * y_lines))
x = 0
y = 0
for (_,__,files) in os.walk(avatar_dir):
for pic_name in files:
try:
with Image.open(avatar_dir+pic_name) as img:
img = img.resize((each_size,each_size))
image.paste(img,(x*each_size,y*each_size))
x+=1
if x == x_lines:
x=0
y+=1
except:
print('读取失败')
img = image.save(os.getcwd()+'/wechat_avatar.png')
plt.imread('wechat_avatar.png')
print('wechat_avatar.png已保存至目录。')
print('#1 Finish!!')
plt.show()
def gen_avatar_hanzi():
# 初始化机器人，扫码登录
global friends
if friends == None:
bot = Bot( login_callback=login_success,console_qr=True) #
friends = bot.friends(update=True)
print("#6 ----头像拼接汉字----")
input_str = input('请输入汉字（建议为6个或9个，用于微信六宫格或九宫格；包括标点符号）：')
#将字转化为汉字库的点阵数据
outlist = wc2char.char2bit(input_str)
#获取当前文件夹路径
workspace = os.getcwd()
avatar_dir = download_avatar()
#先读取用户本人头像，存储名为用户名称
selfHead = avatar_dir + '0.jpg'
avatar_dir = "avatar"
print("生成中，请稍等...")
#将头像图片按点阵拼接成单字图片
wc2char.head2char(workspace,avatar_dir,selfHead,outlist)
print("完成！ 已输出至目录 avatar_output ")
print('#6 Finish!!')
#统计好友的性别，微信中男性为1，女性为2，未知为0
def gen_sex():
print("#2 ----好友男女比例和地区统计----")
# 初始化机器人，扫码登录
global friends
if friends == None:
bot = Bot( login_callback=login_success) # console_qr=True,
friends = bot.friends(update=True)
# result = friends.stats_text()
# print(result)
stat = friends.stats()
# print(stat)
plt.figure(figsize=(8,5), dpi=80)
plt.axes(aspect=1)
plt.pie([stat['sex'][1], stat['sex'][2], stat['sex'][0]],
labels=['男','女','未知'],
labeldistance = 1.1,
autopct = '%3.1f%%',
shadow = False,
startangle = 90,
pctdistance = 0.6
)
plt.legend(loc='upper left',)
plt.rcParams['font.sans-serif'] = ['SimHei']
plt.title('微信中的男女比例')
plt.show()
top_n = list(filter(lambda x: x[0], stat['city'].most_common()))[:10]
top_n_list = ['{}'.format(k) for k, v in top_n]
top_n_number_list = ['{:.2}'.format(v/len(friends)) for k, v in top_n]
plt.title('好友城市分布TOP10')
plt.bar(range(len(top_n_list)),top_n_number_list,tick_label=top_n_list,color="blue")
plt.show()
top_n = list(filter(lambda x: x[0], stat['province'].most_common()))[:10]
top_n_list = ['{}'.format(k) for k, v in top_n]
top_n_number_list = ['{:.2}'.format(v/len(friends)) for k, v in top_n]
plt.title('好友省份分布TOP10')
plt.bar(range(len(top_n_list)),top_n_number_list,tick_label=top_n_list,color="blue")
plt.show()
print('#2 Finish!!')
# 生成签名词云
def gen_word_cloud():
print("#3 ----好友签名制作词云和情感分析----")
# 初始化机器人，扫码登录
global friends
if friends == None:
bot = Bot(console_qr=True, login_callback=login_success) #cache_path=True,
friends = bot.friends(update=True)
# 获取好友签名信息并储存在 siglist 中
siglist = []
for _,friend in enumerate(friends):
sigture = friend.signature
# 如果存在签名的话
if len(sigture) > 0:
# 将个性签名中的表情符号去掉（这里没有去除干净，利用正则表达式）
sigture = sigture.replace('span','').replace('class','').replace('emoji','').replace('< =','').replace('"','').replace('</>','').replace('>','')
siglist.append(sigture)
# 将siglist中的元素拼接为一个字符串
text = ''.join(siglist)
# jieba(结巴分词：有全模式、精确模式、默认模式、新词识别、搜索引擎模式）
# jieba.cut()所接收的两个参数，第一个参数为需要分词的字符串，第二个为是否采用全模式
word_list = jieba.cut(text, cut_all=True)
# 空格拼接
word_space_split = ' '.join(word_list)
# 字体的颜色为对应路径的背景图片的颜色
coloring = plt.imread('bg.jpg')
# coloring = np.array(Image.open("wechat.jpg"))
# font_path: 字体路径； random_state: 为每个字体返回一个PIL颜色； scale：按照比例放大画布；max_font_size:显示的最大字体的大小
# 如果参数 mask 为空，则使用二维遮罩绘制词云。如果 mask 非空，设置的宽高值将被忽略，遮罩形状被 mask 取代
my_wordcloud = WordCloud(background_color="white", max_words=2000,
mask=coloring, max_font_size=120, random_state=42, scale=3,
font_path="./simkai.ttf").generate(word_space_split)
plt.imshow(my_wordcloud)
plt.axis("off")
plt.show()
my_wordcloud.to_file(os.path.join("wechatfriends_wordcloud.png"))
print('#3 Finish!!')
print('wechatfriends_wordcloud.png 已保存至目录。')
# 共同好友检测
def same_friend():
print("#5 ----共同好友检测----")
# 初始化机器人，扫码登录
global friends
if friends == None:
bot = Bot(console_qr=True, login_callback=login_success)
friends = bot.friends(update=True)
print("请另一位同学扫码登录")
bot_tmp = Bot( login_callback=login_success,cache_path=False,console_qr=True) #,console_qr=True
other_friend = bot_tmp.friends(update=True)
result = mutual_friends(friends,other_friend)
print("共同好友有{}个".format(len(result)))
for i in result:
print(i)
print('#5 Finish!!')