#!/usr/bin/python #-*- coding: utf-8 -*- import os import re import csv import time import json import jieba from jieba import analyse import itchat import base64 from snownlp import SnowNLP import requests import sys from collections import Counter import matplotlib.pyplot as plt from pylab import * from faceApi import FaceAPI mpl.rcParams['font.sans-serif'] = ['SimHei'] from PIL import Image import numpy as np from wordcloud import WordCloud def analyseSex(firends): sexs = list(map(lambda x:x['Sex'],friends[1:])) counts = Counter(sexs).items() counts = sorted(counts, key=lambda x:x[0], reverse=False) counts = list(map(lambda x:x[1],counts)) labels = ['Unknow','Male','Female'] colors = ['red','yellowgreen','lightskyblue'] plt.figure(figsize=(8,5), dpi=80) plt.axes(aspect=1) plt.pie(counts, labels=labels, colors=colors, labeldistance = 1.1, autopct = '%3.1f%%', shadow = False, startangle = 90, pctdistance = 0.6 ) plt.legend(loc='upper right',) plt.title(u'%s的微信好友性别组成' % friends[0]['NickName']) plt.show() def analyseLocation(friends): freqs = {} headers = ['NickName','Province','City'] with open('location.csv','w',encoding='utf-8',newline='',) as csvFile: writer = csv.DictWriter(csvFile, headers) writer.writeheader() for friend in friends[1:]: row = {} row['NickName'] = friend['NickName'] row['Province'] = friend['Province'] row['City'] = friend['City'] if(friend['Province']!=None): if(friend['Province'] not in freqs): freqs[friend['Province']] = 1 else: freqs[friend['Province']] = 1 writer.writerow(row) for (k,v) in freqs: print("{0}:{1}".format(k,v)) def analyseHeadImage(frineds): # Init Path basePath = os.path.abspath('.') baseFolder = basePath + '\\HeadImages\\' if(os.path.exists(baseFolder) == False): os.makedirs(baseFolder) # Analyse Images faceApi = FaceAPI() use_face = 0 not_use_face = 0 image_tags = '' for index in range(1,len(friends)): friend = friends[index] # Save HeadImages imgFile = baseFolder + '\\Image%s.jpg' % str(index) imgData = itchat.get_head_img(userName = friend['UserName']) if(os.path.exists(imgFile) == False): with open(imgFile,'wb') as file: file.write(imgData) # Detect Faces time.sleep(1) result = faceApi.detectFace(imgFile) if result == True: use_face += 1 else: not_use_face += 1 # Extract Tags result = faceApi.extractTags(imgFile) image_tags += ','.join(list(map(lambda x:x['tag_name'],result))) labels = [u'使用人脸头像',u'不使用人脸头像'] counts = [use_face,not_use_face] colors = ['red','yellowgreen','lightskyblue'] plt.figure(figsize=(8,5), dpi=80) plt.axes(aspect=1) plt.pie(counts, #性别统计结果 labels=labels, #性别展示标签 colors=colors, #饼图区域配色 labeldistance = 1.1, #标签距离圆点距离 autopct = '%3.1f%%', #饼图区域文本格式 shadow = False, #饼图是否显示阴影 startangle = 90, #饼图起始角度 pctdistance = 0.6 #饼图区域文本距离圆点距离 ) plt.legend(loc='upper right',) plt.title(u'%s的微信好友使用人脸头像情况' % friends[0]['NickName']) plt.show() image_tags = image_tags.encode('iso8859-1').decode('utf-8') back_coloring = np.array(Image.open('face.jpg')) wordcloud = WordCloud( font_path='simfang.ttf', background_color="white", max_words=1200, mask=back_coloring, max_font_size=85, random_state=75, width=800, height=480, margin=15 ) wordcloud.generate(image_tags) plt.imshow(wordcloud) plt.axis("off") plt.show() def analyseSignature(friends): signatures = '' emotions = [] pattern = re.compile("1f\d.+") for friend in friends: signature = friend['Signature'] if(signature != None): signature = signature.strip().replace('span', '').replace('class', '').replace('emoji', '') signature = re.sub(r'1f(\d.+)','',signature) if(len(signature)>0): nlp = SnowNLP(signature) emotions.append(nlp.sentiments) signatures += ' '.join(jieba.analyse.extract_tags(signature,5)) with open('signatures.txt','wt',encoding='utf-8') as file: file.write(signatures) # Sinature WordCloud back_coloring = np.array(Image.open('flower.jpg')) wordcloud = WordCloud( font_path='simfang.ttf', background_color="white", max_words=1200, mask=back_coloring, max_font_size=75, random_state=45, width=960, height=720, margin=15 ) wordcloud.generate(signatures) plt.imshow(wordcloud) plt.axis("off") plt.show() wordcloud.to_file('signatures.jpg') # Signature Emotional Judgment count_good = len(list(filter(lambda x:x>0.66,emotions))) count_normal = len(list(filter(lambda x:x>=0.33 and x<=0.66,emotions))) count_bad = len(list(filter(lambda x:x<0.33,emotions))) print(count_good * 100/len(emotions)) print(count_normal * 100/len(emotions)) print(count_bad * 100/len(emotions)) labels = [u'负面消极',u'中性',u'正面积极'] values = (count_bad,count_normal,count_good) plt.rcParams['font.sans-serif'] = ['simHei'] plt.rcParams['axes.unicode_minus'] = False plt.xlabel(u'情感判断') plt.ylabel(u'频数') plt.xticks(range(3),labels) plt.legend(loc='upper right',) plt.bar(range(3), values, color = 'rgb') plt.title(u'%s的微信好友签名信息情感分析' % friends[0]['NickName']) plt.show() # login wechat and extract friends itchat.auto_login(hotReload = True) friends = itchat.get_friends(update = True) analyseSex(friends) analyseSignature(friends) analyseHeadImage(friends) analyseLocation(friends)