def search_all_user(keyword):
cookie = Cookie_Process.read_cookie() # 获取文件中存储的cookie
mhf = mysqlHelper(get_db()[0],
get_db()[1],
get_db()[2],
get_db()[3],
get_db()[4], int(get_db()[5]))
sqlf = "select wb_userid from keyword_weibo where keyword = %s "
all_id_temp = mhf.findAll(sqlf, keyword) # 查询涉及到关键字的所有的用户ID
all_id = [] # 对要爬取的用户id列表进行去重
for i in all_id_temp:
if i not in all_id:
all_id.append(i)
id_num = len(all_id)
print('查询到涉及关键字为 {} 的微博用户总数量为 {}\n'.format(keyword, str(id_num)))
mh = mysqlHelper(get_db()[0],
get_db()[1],
get_db()[2],
get_db()[3],
get_db()[4], int(get_db()[5]))
sql = "insert into keyword_userinfo(user_id,user_name,user_sex,user_address,user_weizhi,user_renzheng,user_oneword,user_wbnum,user_follow,user_fan,user_url,keyword) values(%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)"
userinfos = []
for i in range(len(all_id)):
temp_user_data = fetch_user_data(int(all_id[i][0]), keyword, cookie)
if (temp_user_data != None): # 判断返回的用户数据列表是否为空
userinfos.extend(temp_user_data)
if ((i + 1) % 50 == 0): # 每多少条数据执行一次 提交 插入数据库操作
mh.open()
for i in range(len(userinfos)):
mh.cud(
sql,
(userinfos[i]['user_id'], userinfos[i]['user_name'],
userinfos[i]['user_sex'], userinfos[i]['user_address'],
userinfos[i]['user_weizhi'],
userinfos[i]['user_renzheng'],
userinfos[i]['user_oneword'], userinfos[i]['user_wbnum'],
userinfos[i]['user_follow'], userinfos[i]['user_fan'],
userinfos[i]['user_url'], keyword))
mh.tijiao()
mh.close()
userinfos = [] # 提交数据库之后将列表清空
if len(userinfos) > 0: # 将余下的数据提交数据库
mh.open()
for i in range(len(userinfos)):
mh.cud(sql,
(userinfos[i]['user_id'], userinfos[i]['user_name'],
userinfos[i]['user_sex'], userinfos[i]['user_address'],
userinfos[i]['user_weizhi'], userinfos[i]['user_renzheng'],
userinfos[i]['user_oneword'], userinfos[i]['user_wbnum'],
userinfos[i]['user_follow'], userinfos[i]['user_fan'],
userinfos[i]['user_url'], keyword))
mh.tijiao()
mh.close()
def search_all_comment(keyword):
cookie = Cookie_Process.read_cookie() # 获取文件中存储的cookie
mhf = mysqlHelper(get_db()[0], get_db()[1], get_db()[2], get_db()[3], get_db()[4], int(get_db()[5]))
sqlf = "select wb_id from keyword_weibo where keyword = %s "
all_wbid_temp = mhf.findAll(sqlf, keyword) #查询涉及到关键字的所有的微博id
all_wbid = [] # 对要爬取的微博id列表进行去重
for i in all_wbid_temp:
wbid = i[0]
# print(wbid)
if wbid not in all_wbid:
all_wbid.append(wbid)
wb_num = len(all_wbid)
print('查询到涉及关键字为 {} 的微博总数量为 {}\n'.format(keyword,str(wb_num)))
for i in range(len(all_wbid)):
print("============ 正在爬取第 {} 条微博的评论 ===========".format(int(i)+1))
fetch_comment_data(str(all_wbid[i]),keyword,cookie)
def search_all_comment_id(userid):
mhf = mysqlHelper(get_db()[0],
get_db()[1],
get_db()[2],
get_db()[3],
get_db()[4], int(get_db()[5]))
sqlf = "select wb_id from user_weibo where wb_userid =%s"
all_wbid_temp = mhf.findAll(sqlf, userid) #查询涉及到关键字的所有的微博id
all_wbid = [] # 对要爬取的微博id列表进行去重
for i in all_wbid_temp:
wbid = i[0]
# print(wbid)
if wbid not in all_wbid:
all_wbid.append(wbid)
wb_num = len(all_wbid)
print("这个家伙有{}条微博已经被爬下来了\n".format(str(wb_num)))
for i in range(len(all_wbid)):
print("============ 正在爬取第 {} 条微博的评论 ===========".format(int(i) + 1))
fetch_comment_data(str(all_wbid[i]), userid)
def fetch_comment_data(wbid, userid):
cookie = Cookie_Process.read_cookie() # 获取文件中存储的cookie
cookies = {"Cookie": cookie}
proxies = get_random_ip(ip_list)
r_comment = requests.get('https://weibo.cn/comment/{}'.format(wbid),
cookies=cookies,
proxies=proxies)
soup_comment = BeautifulSoup(r_comment.text, 'lxml')
flag = False
try:
flag = soup_comment.select('.c')[-1].text.startswith('还没有人针对')
except Exception as e:
page_num = 1
if flag:
print("--------- 此微博没有人评论！ ---------\n")
return
else:
try:
page_num = int(
soup_comment.select_one(".pa").text.split()[-1].split("/")
[-1].split("页")[0])
except Exception as e:
page_num = 1
mh = mysqlHelper(get_db()[0],
get_db()[1],
get_db()[2],
get_db()[3],
get_db()[4], int(get_db()[5]))
sql = "insert into comment(wb_id,comment_content,comment_userid,comment_username,comment_like,comment_createtime,userid) values(%s,%s,%s,%s,%s,%s,%s)"
page_id = 1
commentinfos = []
print("--------- 此微博 {} 的评论页数共有 {} 页 ---------\n".format(wbid, page_num))
while page_id < page_num + 1:
time.sleep(random.uniform(4.5, 6.5)) #设置睡眠时间
print("++++++ 正在爬取此微博 {} 的第 {} 页评论...... ++++++\n".format(
wbid, page_id))
r_comment = requests.get(url_comment.format(wbid, page_id),
cookies=cookies)
soup_comment = BeautifulSoup(r_comment.text, 'lxml')
comment_list = soup_comment.select(".c")
for l in comment_list:
if str(l.get("id")).startswith("C_"):
comment_content = filter_emoji(l.select_one(".ctt").text)
comment_userid = l.select_one("a").get("href")[3:]
comment_username = l.select_one("a").text
comment_like = l.select_one(".cc").text.strip()[2:-1]
comment_createtime = time_process(
l.select_one(".ct").text.strip()[:-5])
print("评论内容 ：" + comment_content)
print("评论用户ID：" + comment_userid)
print("评论用户名：" + comment_username)
print("评论赞数 ：" + comment_like)
print("评论时间 ：" + comment_createtime)
print('----------------------------\n')
commentinfo = {
'wb_id': wbid, # 生成一条评论信息的列表
'comment_content': comment_content,
'comment_userid': comment_userid,
'comment_username': comment_username,
'comment_like': comment_like,
'comment_createtime': comment_createtime,
'userid': userid
}
commentinfos.append(commentinfo)
page_id = page_id + 1
if (len(commentinfos) >= 100):
mh.open()
for i in range(len(commentinfos)):
mh.cud(sql, (commentinfos[i]['wb_id'],
commentinfos[i]['comment_content'],
commentinfos[i]['comment_userid'],
commentinfos[i]['comment_username'],
commentinfos[i]['comment_like'],
commentinfos[i]['comment_createtime'], userid))
mh.tijiao()
mh.close()
commentinfos = []
if (len(commentinfos) > 0):
mh.open()
for i in range(len(commentinfos)):
mh.cud(
sql,
(commentinfos[i]['wb_id'], commentinfos[i]['comment_content'],
commentinfos[i]['comment_userid'],
commentinfos[i]['comment_username'],
commentinfos[i]['comment_like'],
commentinfos[i]['comment_createtime'], userid))
mh.tijiao()
mh.close()
print("--------- 此微博的全部评论爬取完毕！---------\n\n")
def fetch_pages(user_id):
cookie = Cookie_Process.read_cookie() # 获取文件中存储的cookie5625254784
cookies = {"Cookie": cookie}
# 通过' https://weibo.cn/%d '网站微博第一页获取用户的用户名和总页数
proxies = get_random_ip(ip_list)
url_user = "******" % (user_id, 1)
r_user = requests.get(url_user, cookies=cookies, proxies=proxies)
soup_user = BeautifulSoup(r_user.text, 'lxml')
# 判断用户是否发表了微博，如没有，则返回
panduan_weibo = soup_user.select_one('.tc').text[3:-1]
if panduan_weibo == '0':
print('此用户微博数量为0！')
return
user_contents = soup_user.select_one('.ut').select('.ctt')
temp_user = user_contents[0].text.split()
wb_username = temp_user[0] # 获取微博用户名
# print(wb_username)
try:
page_num = int(
soup_user.select_one('.pa').text.split()[1].split('/')[1]
[:-1]) - 1 # 获取微博总页数
print('--------- 微博总页数为：' + str(page_num) + ' ---------\n')
except Exception as e:
page_num = 1
mblogs = [] # 此次时间单位内的搜索全部结果先临时用列表保存，后存入数据库
page_id = 1
while page_id <= page_num:
try:
mblogs.extend(fetch_weibo_data(
user_id, wb_username,
page_id)) # 每页调用fetch_data函数进行微博信息的抓取,中国日报4466
if (flag == 1):
continue
except Exception as e:
print(e)
if (page_id % 20 == 0): # 每多少条数据执行一次 提交 插入数据库操作
# 保存到mysql数据库
mh = mysqlHelper(get_db()[0],
get_db()[1],
get_db()[2],
get_db()[3],
get_db()[4], int(get_db()[5]))
sql = "insert into user_weibo(wb_userid,wb_username,wb_id,wb_content,wb_createtime,wb_forwardnum,wb_commentnum,wb_likenum) values(%s,%s,%s,%s,%s,%s,%s,%s)"
mh.open()
for i in range(len(mblogs)):
mh.cud(
sql,
(mblogs[i]['wb_userid'], mblogs[i]['wb_username'],
mblogs[i]['wb_id'], filter_emoji(mblogs[i]['wb_content']),
mblogs[i]['wb_createtime'], mblogs[i]['wb_forwardnum'],
mblogs[i]['wb_commentnum'], mblogs[i]['wb_likenum']))
mh.tijiao()
mh.close()
mblogs = [] # 提交数据库之后将列表清空
page_id = page_id + 1
if len(mblogs) > 0: # 将余下的数据提交数据库
# 保存到mysql数据库
mh = mysqlHelper(get_db()[0],
get_db()[1],
get_db()[2],
get_db()[3],
get_db()[4], int(get_db()[5]))
sql = "insert into user_weibo(wb_userid,wb_username,wb_id,wb_content,wb_createtime,wb_forwardnum,wb_commentnum,wb_likenum) values(%s,%s,%s,%s,%s,%s,%s,%s)"
mh.open()
for i in range(len(mblogs)):
mh.cud(sql,
(mblogs[i]['wb_userid'], mblogs[i]['wb_username'],
mblogs[i]['wb_id'], filter_emoji(mblogs[i]['wb_content']),
mblogs[i]['wb_createtime'], mblogs[i]['wb_forwardnum'],
mblogs[i]['wb_commentnum'], mblogs[i]['wb_likenum']))
mh.tijiao()
mh.close()