之前对象工作中需要获取地图上的一些数据, 手工找寻复制 费时费力, 逢此契机, 准备使用代码尽可能简化机械重复操作, 力图一劳永逸.
首选简洁易入门的Python. 下文就是对流程的总结, 及简述每步的意义. 并不Hack,重在感受编程的用途和基本工具的使用.
以百度地图为例,需求如下:
想要收集该关键词匹配到的所有公司的名称,地址,和联系方式(没有电话/手机的则忽略),
(1). 点击 Network,选择XHR
这是为了能够获取接口的返回值,即为了能拿到原始的数据
(2). 点击clear,清理掉当前所有接口信息的返回
(3). 点击左侧下方的页码,如第3页. 这时在控制台就发现有新的接口请求
(4). 选中第一个,右键->Copy->Copy as Curl
(Windows为Copy as Curl Bash)
这时就把这个接口的请求复制了下来
(1). 依次点击 Import->Raw text
,粘贴,点击Continue->Import
(2). 点击右侧>
图标,选择 Python - Requests
(1). 复制代码到Pycharm, 找到url和headers里面的pn, 将其后面的内容替换为 ' + pn + '&nn=' + nn + '
(这是为了把页码写活, 多次请求替代人工翻页;)
(2). 再在代码中添加对数据的筛选, 如去掉没有联系方式的内容; 及最后将数据写入到csv的逻辑
最终代码如下:
import requests
import json
import csv
import urllib
def cui():
a = 1
pnInt = 1
print(111)
wd = urllib.parse.quote("xxxx")
while a < 30:
nnInt = pnInt * 10 - 10
print(pnInt, nnInt)
print("++++++++++")
fetch(pnInt, nnInt, wd)
a = a + 1
pnInt = pnInt + 1
def fetch(pnInt, nnInt, wd):
pn = str(pnInt)
nn = str(nnInt)
# ' + pn + '&nn=' + nn + '
url = 'https://map.baidu.com/?newmap=1&reqflag=pcmap&biz=1&from=webmap&da_par=direct&pcevaname=pc4.1&qt=con&from=webmap&c=245&wd=%E8%88%9F%E5%B1%B1%E8%89%BA%E6%9C%AF%E5%9F%B9%E8%AE%AD&wd2=&pn=' + pn + '&nn=' + nn + '&db=0&sug=0&addr=0&&da_src=pcmappg.poi.page&on_gel=1&src=7&gr=3&l=11&auth=xxxxxxxseckey=xxxxxxxxxxxxxxxxxxxxxxxxxxxxcb80e3ae5bb6a5e50a29d1f9face80bde809c0809b62dc348fb8e9375c542f12cea0f3973b2f8374a4ee078076449048d0030069230a67109146098f873a7ecf0d18d2d7cf627c8f2f33584cc3c674ac5c0eff12722764e7da6a3bb0a02054e4801d774ac0cff4ab78f2a83420ea09639fae7c7b6f7e26aac71cc1034e0575aaf147d9f3ec2307548774f52ee4f90bfc50d20871f853d017c39288420493c900287f0ebaf2ab330a523f3fb8401c852c74b01e041925921ca1bbbe2ad4fe58851985119079d972d1d5583a3acc0b0912e&device_ratio=1&tn=B_NORMAL_MAP&u_loc=13526910,3651307&ie=utf-8&b=(13524456.32,3410109.5;13662696.32,3554493.5)&t=1622983893693'
payload = {}
headers = {
'Connection': 'keep-alive',
'sec-ch-ua': '" Not;A Brand";v="99", "Google Chrome";v="91", "Chromium";v="91"',
'sec-ch-ua-mobile': '?0',
'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.77 Safari/537.36',
'Accept': '*/*',
'Sec-Fetch-Site': 'same-origin',
'Sec-Fetch-Mode': 'cors',
'Sec-Fetch-Dest': 'empty',
'Referer': 'https://map.baidu.com/search/%E8%88%9F%E5%B1%B1%E8%89%BA%E6%9C%AF%E5%9F%B9%E8%AE%AD/@13593576.32,3482301.5,11z?querytype=s&da_src=shareurl&wd=%E8%88%9F%E5%B1%B1%E8%89%BA%E6%9C%AF%E5%9F%B9%E8%AE%AD&c=29&src=0&pn=' + pn + '&nn=' + nn + '&sug=0&l=10&b=(13259104.722474225,3292542.035257731;13409631.837938145,3449759.244742268)&from=webmap&biz_forward=%7B%22scaler%22:1,%22styles%22:%22pl%22%7D&seckey=xxxxxxxxxxx9c0809b62dc348fb8e9375c542f12cea0f3973b2f8374a4ee078076449048d0030069230a67109146098f873a7ecf0d18d2d7cf627c8f2f33584cc3c674ac5c0eff12722764e7da6a3bb0a02054e4801d774ac0cff4ab78f2a83420ea09639fae7c7b6f7e26aac71cc1034e0575aaf147d9f3ec2307548774f52ee4f90bfc50d20871f853d017c39288420493c900287f0ebaf2ab330a523f3fb8401c852c74b01e041925921ca1bbbe2ad4fe58851985119079d972d1d5583a3acc0b0912e&device_ratio=1',
'Accept-Language': 'zh-CN,zh;q=0.9,en;q=0.8,ca;q=0.7',
'Cookie': 'BIDUPSID=xxxxxxx; PSTM=1621914601; __yjs_duid=1_7b92c81608ccfdbad0dc7906094e07961621959460314; BDORZ=B490B5EBF6F3CD402E515D22BCDA1598; BAIDUID=08209514AAE7C66A7FD0952DF04ECBB7:FG=1; validate=18765; H_PS_PSSID=31254; BDRCVFR[PaHiFN6tims]=9xWipS8B-FspA7EnHc1QhPEUf; delPer=0; PSINO=3; BDRCVFR[tox4WRQ4-Km]=mk3SLVN4HKm; BDRCVFR[-pGxjrCMryR]=mk3SLVN4HKm; BDRCVFR[CLK3Lyfkr9D]=mk3SLVN4HKm; MCITY=-289%3A; ab_sr=1.0.0_Y2Q0MjM2MGI0ODU3M2IwNGI3OWNkOWJkNWEyZWU2NDBkMzlhYWQzMDk2MzZkYTUzZmViYmNlNDM4ZjM3MTM5ZWNhNGU1MTc3OTRiMjNiOGYyN2UzNDBmZDE3NDJjZTQ0; BCLID=7585045023682664764; BDSFRCVID=OePOJeC627XmgEOelBU3o48vuPWbG-QTH6aoohZzyJCRtXDnQwcjEG0PSx8g0K4bAOqsogKK0eOTHkDF_2uxOjjg8UtVJeC6EG0Ptf8g0f5; H_BDCLCKID_SF=JbAtoKD-JKvJfJjkM4rHqR_Lqxby26nqLHO9aJ5nJD_BqJ3aQPTqQptJDUPJqn5t523KbMKaQpP-HJ7qMpoMjfk10a-fbbQP0GbxKl0MLUOtbb0xyn_VMM3beMnMBMPj5mOnaPQY3fAKftnOM46JehL3346-35543bRTLnLy5KJYMDF9Dj0hj6Q3eU5H2bbe56uXQ4D8Kb7Vbp7sQxnkbfJBD4JLabolJCTxbK54aK-Wf45VynrM06L7yajK255LWN5W-K3zW4jsJDoG55bpQT8rMlAOK5Oib4ja_KIbab3vOIJNXpO1MU0zBN5thURB2DkO-4bCWJ5TMl5jDh3Mb6ksD-FtqjtDfnkDoC8hfb6HHTrz-tb5-ICShUFshjbTB2Q-5KL-ytbv8-jkbfJWWfFeja7q-lQ7tJ603fbdJJjoOqcuXPr1ett_babhaPvmQgTxoUJvBCnJhhvG-4clb60ebPRiJPQ9QgbWKpQ7tt5W8ncFbT7l5hKpbt-q0x-jLTnhVn0M5DK0hID9jTLaDToMhfQ2etrKK572sJOOaCvbjbvOy4oTj6j-3-c9el3-JnRiLbA2fPQhSDbRjpJG3MvB-fnjb4DDX57MafjaLJ7sffDlQft205kbeMtjBbQaaGTh_n7jWhk2eq72y-RUQlRX5q79atTMfNTJ-qcH0KQpsIJM5-DWbT8EjHCeJT_OJbkJVCvMaP55K43xKITjh6PgbJ39BtQmJJufhn6j3l7qDhoaDPPMebK00bJa0KrIQg-q3R7O2Uc0JqcJ0ROiQ-Cu5UbB0x-jLN7OVn0MWKbDEq7lKPnJyUnQbtnnBPnR3H8HL4nv2JcJbM5m3x6qLTKkQN3T-PKO5bRh_CcJ-J8XMC_xjj3P; BCLID_BFESS=7585045023682664764; BDSFRCVID_BFESS=OePOJeC627XmgEOelBU3o48vuPWbG-QTH6aoohZzyJCRtXDnQwcjEG0PSx8g0K4bAOqsogKK0eOTHkDF_2uxOjjg8UtVJeC6EG0Ptf8g0f5; H_BDCLCKID_SF_BFESS=JbAtoKD-JKvJfJjkM4rHqR_Lqxby26nqLHO9aJ5nJD_BqJ3aQPTqQptJDUPJqn5t523KbMKaQpP-HJ7qMpoMjfk10a-fbbQP0GbxKl0MLUOtbb0xyn_VMM3beMnMBMPj5mOnaPQY3fAKftnOM46JehL3346-35543bRTLnLy5KJYMDF9Dj0hj6Q3eU5H2bbe56uXQ4D8Kb7Vbp7sQxnkbfJBD4JLabolJCTxbK54aK-Wf45VynrM06L7yajK255LWN5W-K3zW4jsJDoG55bpQT8rMlAOK5Oib4ja_KIbab3vOIJNXpO1MU0zBN5thURB2DkO-4bCWJ5TMl5jDh3Mb6ksD-FtqjtDfnkDoC8hfb6HHTrz-tb5-ICShUFshjbTB2Q-5KL-ytbv8-jkbfJWWfFeja7q-lQ7tJ603fbdJJjoOqcuXPr1ett_babhaPvmQgTxoUJvBCnJhhvG-4clb60ebPRiJPQ9QgbWKpQ7tt5W8ncFbT7l5hKpbt-q0x-jLTnhVn0M5DK0hID9jTLaDToMhfQ2etrKK572sJOOaCvbjbvOy4oTj6j-3-c9el3-JnRiLbA2fPQhSDbRjpJG3MvB-fnjb4DDX57MafjaLJ7sffDlQft205kbeMtjBbQaaGTh_n7jWhk2eq72y-RUQlRX5q79atTMfNTJ-qcH0KQpsIJM5-DWbT8EjHCeJT_OJbkJVCvMaP55K43xKITjh6PgbJ39BtQmJJufhn6j3l7qDhoaDPPMebK00bJa0KrIQg-q3R7O2Uc0JqcJ0ROiQ-Cu5UbB0x-jLN7OVn0MWKbDEq7lKPnJyUnQbtnnBPnR3H8HL4nv2JcJbM5m3x6qLTKkQN3T-PKO5bRh_CcJ-J8XMC_xjj3P; BA_HECTOR=8k240g80012g85akjb1gbpdtl0q; BAIDUID_BFESS=EE9C87CC527526D94BAF4BBF7C68C795:FG=1; BAIDUID=119C90F3DD22536C575B00C437176785:FG=1; MCITY=-289%3A'
}
response = requests.request("GET", url, headers=headers, data=payload)
# print(response.text)
d = json.loads(response.text)
if "content" in d.keys():
print("have content!")
rs = d["content"]
# print("json对象d_json: ", d["content"][0]["addr"])
for val in rs:
address = val["addr"]
if "ext" in val.keys():
print("have ext!")
extInfo = val["ext"]
if len(extInfo) > 0:
info = extInfo["detail_info"]
if "name" in info.keys():
print("have name!")
name = info["name"]
phone = info["phone"]
if len(phone) > 0:
print(name)
print(phone)
print(address)
print("-------")
writeCsv(name, phone, address)
def writeCsv(name, phone, address):
print("name为:" + name)
print("手机号为:" + phone)
# 1. 创建文件对象; 以a+的方式打开是追加数据,而不是覆盖数据
f = open('所需信息.csv', 'a+', encoding='utf-8')
# 2. 基于文件对象构建 csv写入对象
csv_writer = csv.writer(f)
# 3. 构建列表头
# csv_writer.writerow(["机构名称", "联系方式", "详细地址"])
csv_writer.writerow([name, str(phone) + '\t', address])
f.close()
cui()
(3). 点击下方的 Terminal(终端),运行 python 文件名.py,这时在同级文件夹里,就出现了生成的csv文件
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