Python crawler to collect Tripadvisor data case implementation

preamble

Tripadvisor is the world's leading travel website, featuring reviews and advice from travelers around the world, comprehensive coverage of hotels, attractions, restaurants, airlines worldwide , as well as trip planning and hotel, attraction, and restaurant booking features.
Tripadvisor and its websites are present in 49 markets worldwide, with an average of 415 million unique visitors per month.

third-party repository

requests >>> pip install requests
parsel >>> pip install parsel

development environment (computer)

Version: python 3.8

Editor: pycharm 2021.2

Starting Code

Request data

headers = {
    'cookie': 'TADCID=foOmU9bDp6JGIXg2ABQCFdpBzzOuRA-9xvCxaMyI12wTEaQSQ4euq_1sNSDmJybFCMezFLrAnKRGZ_uvGNNO_9cSzuJeK8RQlE4; TAUnique=%1%enc%3AHARC1EMLan58P07MI4ZMcqI%2BzHGWu*6TE6zQDNwk%3D; TASSK=enc%3AAL%2Bm9xwFy7%2BjYONIRS%2F2kEbA%2FtOrlDbcW%2FwCSHs44XP9R3ddE%2BKJxi3FiDuozLe0Ov2ujtnFah8i0sN%2FRdUxZGis0TClwsaz7%2B7Uv8dh%2BvHM%2FfH9C%2FcEYLBYBtn1yLmBNg%3D%3D; ServerPool=A; PMC=V2*MS.2*MD.20220311*LD.20220311; TART=%1%enc%3AfD9OzCOGTHLKxR1qLNfmGZurd9xliidHT5bmQw2z505WnDQeBJdPDWc64WFlxikpNox8JbUSTxk%3D; TATravelInfo=V2*A.2*MG.-1*HP.2*FL.3*RS.1; TASID=9CCF4EA45B4141A8B5E4F03D36821474; ak_bmsc=31083286436C157F558D959D23D94849~000000000000000000000000000000~YAAQqF1kX6lPsVF/AQAAhTyqdw8F4+OoWZwjJCqsKUS/ykkFQHkXml5We7WY4q6KDUeIkm36a0Fs41jt7Jx6MFwnzloND2Iry1Iuwnj5I7oPxsI1RTjfGXSr408rscnzKPJHpRIXwuuiL+SNZxp233DOhrqrbTQ2cDTiGPk8qAYcLYq1OHpyOjLpc6L2zPbiSdvfDAuz2ujLUbWZV33YVrUd1UcmBMKJOSS/C12JeFdLCcjOihJvc4Zlu5HMYQUBdjTaV4zll3YO9YWxdm5pUT57vjI3WjxNhLwOXS93F3ogo/VOzmvk2n4rptCDH1vffz7Dpmp4yRn0dnX8RtiKiolFV00rBs0yC9Nxa67F0qPkJMMS6t6pNo+08PIre7VIiAIxQoWUNNiBiNDXeQ==; PAC=AHc5Ocqizh5jbN81AnjCtcF7k5P54vojrezhxeu8s4DdhkIZSMBuxXUioaVGVVo99Ysr_IbYXqNKjsddfzI8psluCp1NwuwQiBOvmdhP_r8ntVPeHXBc5u782Y8i4KrpV0a29aTnmykzihOxeEfilEfHZOGZxkWN8GRLwHay1MUpBazo7e4Pdtl3tndoYnNIDWcRtHzZJIDE9odWhqOzUE0%3D; TAReturnTo=%1%%2FRestaurants-g188590-Amsterdam_North_Holland_Province.html; roybatty=TNI1625!AJyUZ5ejQVombB9Jv3PVhqqhyMhwsanzT2C6omYz8l6mQNt%2FP5v6CLnnlymNXfhMwolnHznm%2BAmT81YSeygcVxnWHERn16eR747rX9fmWmeCMoris6ffxKTbJ6%2BjObZ6rmffv7I5wEGZ009WzKMlVA%2BXJAheGoIKHOD3gUDLVYlY%2C1; TATrkConsent=eyJvdXQiOiIiLCJpbiI6IkFMTCJ9; TASession=V2ID.9CCF4EA45B4141A8B5E4F03D36821474*SQ.9**GR.82*TCPAR.12*TBR.1*EXEX.98*ABTR.74*PHTB.27*FS.67*CPU.8***DS.5****FA.1*DF.0**LD.188590*EAU._; TAUD=LA-1646980142821-1*RDD-1-2022_03_11*LG-863371-2..*LD-863372-.....; _pbjs_userid_consent_data=3524755945110770; _li_dcdm_c=.; _lc2_fpi=b140173de591--01fxvvhm5q52dte42gshbn1234; __gads=ID=887c76ae8964a5bc:T=1646981079:S=ALNI_MYwTZNsJPdidCGF3BTM3pOV79wAUg; _lr_sampling_rate=100; _lr_retry_request=true; _lr_env_src_ats=false; __li_idex_cache=%7B%7D; pbjs_li_nonid=%7B%7D; __vt=bI5Nl4_3wIiyQqd-ABQCIf6-ytF7QiW7ovfhqc-AvRvwyUuxl21BvNUgBcewLtYtxhD9pK8plYHHUPpFuGJQzlL9HjsNiQXGwLu0f-XidRXohA9m08ary-La12XkjuKCU2QeR3ijnhWjQ8bnjvOcAaUKoA; bm_sv=867C80B13B2E8AE707E1A411B950E849~HDnKV8jbSFu9eHNiLb/p3fK3KqcxdMjPpLXFMD9YvvwLoQEuDGPgZZwEDhQeezJZJhdrUxX02mvzmDqkV7615Fm508wASvLcLsXmW/6+1K9pDp2UuCDIYbuZgv/2m76YS7Og/SBcU6xkIVnHhMVqpxWfro/1T3kO1LdXuFuprhA=; OptanonConsent=isGpcEnabled=0&datestamp=Fri+Mar+11+2022+14%3A53%3A51+GMT%2B0800+(%E4%B8%AD%E5%9B%BD%E6%A0%87%E5%87%86%E6%97%B6%E9%97%B4)&version=6.30.0&isIABGlobal=false&hosts=&consentId=cc7e2f72-5007-428f-a72e-392f9741b69d&interactionCount=1&landingPath=https%3A%2F%%2FRestaurants-g188590-Amsterdam_North_Holland_Province.html&groups=C0001%3A1%2CC0002%3A1%2CC0003%3A1%2CC0004%3A1',
    'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/99.0.4844.51 Safari/537.36',
}
url = '/Restaurants-g188590-Amsterdam_North_Holland_Province.html'
response = (url, headers=headers)

2. Access to data (web page source code)

html_data =

3. Parsing the data (extracting the content of the data we want Details page link)

selector = (html_data)
# Extract the content of the tag's attributes ::attr(href) link
link_list = ('.::attr(href)').getall()
for link in link_list:
    link = '/' + link

4. Send a request (to access all detail page links) to get data

detail_html = (link, headers=headers).text

5. Parsing data

detail_selector = (detail_html)
store_name = detail_selector.css('.fHibz::text').get()
comment_count = detail_selector.css('.eSAOV.H3:nth-child(2) .eBTWs::text').get()
address = detail_selector.css('.eSAOV.H3:nth-child(3) .:nth-child(1) .fhGHT::text').get()
city = detail_selector.css('.breadcrumbs li:nth-child(4) span::text').get()
phone = detail_selector.css('.eSAOV.H3:nth-child(3) .:nth-child(2) .fhGHT a::text').get()
score = detail_selector.css('.eEwDq .fdsdx::text').get()
website = (',"website":"(http.*?)"', detail_html)[0]
print(store_name, comment_count, city, address, phone, score, link, website)

6. Save data

with open('', mode='a', newline='', encoding='utf-8') as f:
    csv_writer = (f)
    csv_writer.writerow([store_name, comment_count, city, address, phone, score, link, website])

7. Getting the data

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