Python實現(xiàn)并行抓取整站40萬條房價數(shù)據(jù)(可更換抓取城市)
寫在前面
這次的爬蟲是關(guān)于房價信息的抓取,目的在于練習10萬以上的數(shù)據(jù)處理及整站式抓取。
數(shù)據(jù)量的提升最直觀的感覺便是對函數(shù)邏輯要求的提高,針對Python的特性,謹慎的選擇數(shù)據(jù)結(jié)構(gòu)。以往小數(shù)據(jù)量的抓取,即使函數(shù)邏輯部分重復,I/O請求頻率密集,循環(huán)套嵌過深,也不過是1~2s的差別,而隨著數(shù)據(jù)規(guī)模的提高,這1~2s的差別就有可能擴展成為1~2h。
因此對于要抓取數(shù)據(jù)量較多的網(wǎng)站,可以從兩方面著手降低抓取信息的時間成本。
1)優(yōu)化函數(shù)邏輯,選擇適當?shù)臄?shù)據(jù)結(jié)構(gòu),符合Pythonic的編程習慣。例如,字符串的合并,使用join()要比“+”節(jié)省內(nèi)存空間。
2)依據(jù)I/O密集與CPU密集,選擇多線程、多進程并行的執(zhí)行方式,提高執(zhí)行效率。
一、獲取索引
包裝請求request,設置超時timeout
# 獲取列表頁面 def get_page(url): headers = { 'User-Agent': r'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) ' r'Chrome/45.0.2454.85 Safari/537.36 115Browser/6.0.3', 'Referer': r'http://bj.fangjia.com/ershoufang/', 'Host': r'bj.fangjia.com', 'Connection': 'keep-alive' } timeout = 60 socket.setdefaulttimeout(timeout) # 設置超時 req = request.Request(url, headers=headers) response = request.urlopen(req).read() page = response.decode('utf-8') return page
一級位置:區(qū)域信息
二級位置:板塊信息(根據(jù)區(qū)域位置得到板塊信息,以key_value對的形式存儲在dict中)
以dict方式存儲,可以快速的查詢到所要查找的目標。-> {'朝陽':{'工體','安貞','健翔橋'......}}
三級位置:地鐵信息(搜索地鐵周邊房源信息)
將所屬位置地鐵信息,添加至dict中。 -> {'朝陽':{'工體':{'5號線','10號線' , '13號線'},'安貞','健翔橋'......}}
解碼后的url:http://bj.fangjia.com/ershoufang/--r-朝陽|w-5號線|b-惠新西街
根據(jù)url的參數(shù)模式,可以有兩種方式獲取目的url:
1)根據(jù)索引路徑獲得目的url
# 獲取房源信息列表(嵌套字典遍歷) def get_info_list(search_dict, layer, tmp_list, search_list): layer += 1 # 設置字典層級 for i in range(len(search_dict)): tmp_key = list(search_dict.keys())[i] # 提取當前字典層級key tmp_list.append(tmp_key) # 將當前key值作為索引添加至tmp_list tmp_value = search_dict[tmp_key] if isinstance(tmp_value, str): # 當鍵值為url時 tmp_list.append(tmp_value) # 將url添加至tmp_list search_list.append(copy.deepcopy(tmp_list)) # 將tmp_list索引url添加至search_list tmp_list = tmp_list[:layer] # 根據(jù)層級保留索引 elif tmp_value == '': # 鍵值為空時跳過 layer -= 2 # 跳出鍵值層級 tmp_list = tmp_list[:layer] # 根據(jù)層級保留索引 else: get_info_list(tmp_value, layer, tmp_list, search_list) # 當鍵值為列表時,迭代遍歷 tmp_list = tmp_list[:layer] return search_list
2)根據(jù)dict信息包裝url
{'朝陽':{'工體':{'5號線'}}}
參數(shù):
—— r-朝陽
—— b-工體
—— w-5號線
組裝參數(shù):http://bj.fangjia.com/ershoufang/--r-朝陽|w-5號線|b-工體
1 # 根據(jù)參數(shù)創(chuàng)建組合url 2 def get_compose_url(compose_tmp_url, tag_args, key_args): 3 compose_tmp_url_list = [compose_tmp_url, '|' if tag_args != 'r-' else '', tag_args, parse.quote(key_args), ] 4 compose_url = ''.join(compose_tmp_url_list) 5 return compose_url
二、獲取索引頁最大頁數(shù)
# 獲取當前索引頁面頁數(shù)的url列表 def get_info_pn_list(search_list): fin_search_list = [] for i in range(len(search_list)): print('>>>正在抓取%s' % search_list[i][:3]) search_url = search_list[i][3] try: page = get_page(search_url) except: print('獲取頁面超時') continue soup = BS(page, 'lxml') # 獲取最大頁數(shù) pn_num = soup.select('span[class="mr5"]')[0].get_text() rule = re.compile(r'\d+') max_pn = int(rule.findall(pn_num)[1]) # 組裝url for pn in range(1, max_pn+1): print('************************正在抓取%s頁************************' % pn) pn_rule = re.compile('[|]') fin_url = pn_rule.sub(r'|e-%s|' % pn, search_url, 1) tmp_url_list = copy.deepcopy(search_list[i][:3]) tmp_url_list.append(fin_url) fin_search_list.append(tmp_url_list) return fin_search_list
三、抓取房源信息Tag
這是我們要抓取的Tag:
['區(qū)域', '板塊', '地鐵', '標題', '位置', '平米', '戶型', '樓層', '總價', '單位平米價格']
# 獲取tag信息 def get_info(fin_search_list, process_i): print('進程%s開始' % process_i) fin_info_list = [] for i in range(len(fin_search_list)): url = fin_search_list[i][3] try: page = get_page(url) except: print('獲取tag超時') continue soup = BS(page, 'lxml') title_list = soup.select('a[class="h_name"]') address_list = soup.select('span[class="address]') attr_list = soup.select('span[class="attribute"]') price_list = soup.find_all(attrs={"class": "xq_aprice xq_esf_width"}) # select對于某些屬性值(屬性值中間包含空格)無法識別,可以用find_all(attrs={})代替 for num in range(20): tag_tmp_list = [] try: title = title_list[num].attrs["title"] print(r'************************正在獲取%s************************' % title) address = re.sub('\n', '', address_list[num].get_text()) area = re.search('\d+[\u4E00-\u9FA5]{2}', attr_list[num].get_text()).group(0) layout = re.search('\d[^0-9]\d.', attr_list[num].get_text()).group(0) floor = re.search('\d/\d', attr_list[num].get_text()).group(0) price = re.search('\d+[\u4E00-\u9FA5]', price_list[num].get_text()).group(0) unit_price = re.search('\d+[\u4E00-\u9FA5]/.', price_list[num].get_text()).group(0) tag_tmp_list = copy.deepcopy(fin_search_list[i][:3]) for tag in [title, address, area, layout, floor, price, unit_price]: tag_tmp_list.append(tag) fin_info_list.append(tag_tmp_list) except: print('【抓取失敗】') continue print('進程%s結(jié)束' % process_i) return fin_info_list
四、分配任務,并行抓取
對任務列表進行分片,設置進程池,并行抓取。
# 分配任務 def assignment_search_list(fin_search_list, project_num): # project_num每個進程包含的任務數(shù),數(shù)值越小,進程數(shù)越多 assignment_list = [] fin_search_list_len = len(fin_search_list) for i in range(0, fin_search_list_len, project_num): start = i end = i+project_num assignment_list.append(fin_search_list[start: end]) # 獲取列表碎片 return assignment_list
p = Pool(4) # 設置進程池 assignment_list = assignment_search_list(fin_info_pn_list, 3) # 分配任務,用于多進程 result = [] # 多進程結(jié)果列表 for i in range(len(assignment_list)): result.append(p.apply_async(get_info, args=(assignment_list[i], i))) p.close() p.join() for result_i in range(len(result)): fin_info_result_list = result[result_i].get() fin_save_list.extend(fin_info_result_list) # 將各個進程獲得的列表合并
通過設置進程池并行抓取,時間縮短為單進程抓取時間的3/1,總計時間3h。
電腦為4核,經(jīng)過測試,任務數(shù)為3時,在當前電腦運行效率最高。
五、將抓取結(jié)果存儲到excel中,等待可視化數(shù)據(jù)化處理
# 存儲抓取結(jié)果 def save_excel(fin_info_list, file_name): tag_name = ['區(qū)域', '板塊', '地鐵', '標題', '位置', '平米', '戶型', '樓層', '總價', '單位平米價格'] book = xlsxwriter.Workbook(r'C:\Users\Administrator\Desktop\%s.xls' % file_name) # 默認存儲在桌面上 tmp = book.add_worksheet() row_num = len(fin_info_list) for i in range(1, row_num): if i == 1: tag_pos = 'A%s' % i tmp.write_row(tag_pos, tag_name) else: con_pos = 'A%s' % i content = fin_info_list[i-1] # -1是因為被表格的表頭所占 tmp.write_row(con_pos, content) book.close()
附上源碼
#! -*-coding:utf-8-*- # Function: 房價調(diào)查 # Author:蘭茲 from urllib import parse, request from bs4 import BeautifulSoup as BS from multiprocessing import Pool import re import lxml import datetime import cProfile import socket import copy import xlsxwriter starttime = datetime.datetime.now() base_url = r'http://bj.fangjia.com/ershoufang/' test_search_dict = {'昌平': {'霍營': {'13號線': 'http://bj.fangjia.com/ershoufang/--r-%E6%98%8C%E5%B9%B3|w-13%E5%8F%B7%E7%BA%BF|b-%E9%9C%8D%E8%90%A5'}}} search_list = [] # 房源信息url列表 tmp_list = [] # 房源信息url緩存列表 layer = -1 # 獲取列表頁面 def get_page(url): headers = { 'User-Agent': r'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) ' r'Chrome/45.0.2454.85 Safari/537.36 115Browser/6.0.3', 'Referer': r'http://bj.fangjia.com/ershoufang/', 'Host': r'bj.fangjia.com', 'Connection': 'keep-alive' } timeout = 60 socket.setdefaulttimeout(timeout) # 設置超時 req = request.Request(url, headers=headers) response = request.urlopen(req).read() page = response.decode('utf-8') return page # 獲取查詢關(guān)鍵詞dict def get_search(page, key): soup = BS(page, 'lxml') search_list = soup.find_all(href=re.compile(key), target='') search_dict = {} for i in range(len(search_list)): soup = BS(str(search_list[i]), 'lxml') key = soup.select('a')[0].get_text() value = soup.a.attrs['href'] search_dict[key] = value return search_dict # 獲取房源信息列表(嵌套字典遍歷) def get_info_list(search_dict, layer, tmp_list, search_list): layer += 1 # 設置字典層級 for i in range(len(search_dict)): tmp_key = list(search_dict.keys())[i] # 提取當前字典層級key tmp_list.append(tmp_key) # 將當前key值作為索引添加至tmp_list tmp_value = search_dict[tmp_key] if isinstance(tmp_value, str): # 當鍵值為url時 tmp_list.append(tmp_value) # 將url添加至tmp_list search_list.append(copy.deepcopy(tmp_list)) # 將tmp_list索引url添加至search_list tmp_list = tmp_list[:layer] # 根據(jù)層級保留索引 elif tmp_value == '': # 鍵值為空時跳過 layer -= 2 # 跳出鍵值層級 tmp_list = tmp_list[:layer] # 根據(jù)層級保留索引 else: get_info_list(tmp_value, layer, tmp_list, search_list) # 當鍵值為列表時,迭代遍歷 tmp_list = tmp_list[:layer] return search_list # 獲取房源信息詳情 def get_info_pn_list(search_list): fin_search_list = [] for i in range(len(search_list)): print('>>>正在抓取%s' % search_list[i][:3]) search_url = search_list[i][3] try: page = get_page(search_url) except: print('獲取頁面超時') continue soup = BS(page, 'lxml') # 獲取最大頁數(shù) pn_num = soup.select('span[class="mr5"]')[0].get_text() rule = re.compile(r'\d+') max_pn = int(rule.findall(pn_num)[1]) # 組裝url for pn in range(1, max_pn+1): print('************************正在抓取%s頁************************' % pn) pn_rule = re.compile('[|]') fin_url = pn_rule.sub(r'|e-%s|' % pn, search_url, 1) tmp_url_list = copy.deepcopy(search_list[i][:3]) tmp_url_list.append(fin_url) fin_search_list.append(tmp_url_list) return fin_search_list # 獲取tag信息 def get_info(fin_search_list, process_i): print('進程%s開始' % process_i) fin_info_list = [] for i in range(len(fin_search_list)): url = fin_search_list[i][3] try: page = get_page(url) except: print('獲取tag超時') continue soup = BS(page, 'lxml') title_list = soup.select('a[class="h_name"]') address_list = soup.select('span[class="address]') attr_list = soup.select('span[class="attribute"]') price_list = soup.find_all(attrs={"class": "xq_aprice xq_esf_width"}) # select對于某些屬性值(屬性值中間包含空格)無法識別,可以用find_all(attrs={})代替 for num in range(20): tag_tmp_list = [] try: title = title_list[num].attrs["title"] print(r'************************正在獲取%s************************' % title) address = re.sub('\n', '', address_list[num].get_text()) area = re.search('\d+[\u4E00-\u9FA5]{2}', attr_list[num].get_text()).group(0) layout = re.search('\d[^0-9]\d.', attr_list[num].get_text()).group(0) floor = re.search('\d/\d', attr_list[num].get_text()).group(0) price = re.search('\d+[\u4E00-\u9FA5]', price_list[num].get_text()).group(0) unit_price = re.search('\d+[\u4E00-\u9FA5]/.', price_list[num].get_text()).group(0) tag_tmp_list = copy.deepcopy(fin_search_list[i][:3]) for tag in [title, address, area, layout, floor, price, unit_price]: tag_tmp_list.append(tag) fin_info_list.append(tag_tmp_list) except: print('【抓取失敗】') continue print('進程%s結(jié)束' % process_i) return fin_info_list # 分配任務 def assignment_search_list(fin_search_list, project_num): # project_num每個進程包含的任務數(shù),數(shù)值越小,進程數(shù)越多 assignment_list = [] fin_search_list_len = len(fin_search_list) for i in range(0, fin_search_list_len, project_num): start = i end = i+project_num assignment_list.append(fin_search_list[start: end]) # 獲取列表碎片 return assignment_list # 存儲抓取結(jié)果 def save_excel(fin_info_list, file_name): tag_name = ['區(qū)域', '板塊', '地鐵', '標題', '位置', '平米', '戶型', '樓層', '總價', '單位平米價格'] book = xlsxwriter.Workbook(r'C:\Users\Administrator\Desktop\%s.xls' % file_name) # 默認存儲在桌面上 tmp = book.add_worksheet() row_num = len(fin_info_list) for i in range(1, row_num): if i == 1: tag_pos = 'A%s' % i tmp.write_row(tag_pos, tag_name) else: con_pos = 'A%s' % i content = fin_info_list[i-1] # -1是因為被表格的表頭所占 tmp.write_row(con_pos, content) book.close() if __name__ == '__main__': file_name = input(r'抓取完成,輸入文件名保存:') fin_save_list = [] # 抓取信息存儲列表 # 一級篩選 page = get_page(base_url) search_dict = get_search(page, 'r-') # 二級篩選 for k in search_dict: print(r'************************一級抓?。赫谧ト ?s】************************' % k) url = search_dict[k] second_page = get_page(url) second_search_dict = get_search(second_page, 'b-') search_dict[k] = second_search_dict # 三級篩選 for k in search_dict: second_dict = search_dict[k] for s_k in second_dict: print(r'************************二級抓?。赫谧ト ?s】************************' % s_k) url = second_dict[s_k] third_page = get_page(url) third_search_dict = get_search(third_page, 'w-') print('%s>%s' % (k, s_k)) second_dict[s_k] = third_search_dict fin_info_list = get_info_list(search_dict, layer, tmp_list, search_list) fin_info_pn_list = get_info_pn_list(fin_info_list) p = Pool(4) # 設置進程池 assignment_list = assignment_search_list(fin_info_pn_list, 2) # 分配任務,用于多進程 result = [] # 多進程結(jié)果列表 for i in range(len(assignment_list)): result.append(p.apply_async(get_info, args=(assignment_list[i], i))) p.close() p.join() for result_i in range(len(result)): fin_info_result_list = result[result_i].get() fin_save_list.extend(fin_info_result_list) # 將各個進程獲得的列表合并 save_excel(fin_save_list, file_name) endtime = datetime.datetime.now() time = (endtime - starttime).seconds print('總共用時:%s s' % time)
總結(jié):
當抓取數(shù)據(jù)規(guī)模越大,對程序邏輯要求就愈嚴謹,對python語法要求就越熟練。如何寫出更加pythonic的語法,也需要不斷學習掌握的。
以上就是本文的全部內(nèi)容,希望本文的內(nèi)容對大家的學習或者工作能帶來一定的幫助,同時也希望多多支持腳本之家!
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