Cara Scrape Data Toko yang Terdapat di Tokopedia Menggunakan Python

./X3NUX September 01, 2024

Pada pembahasan kali ini admin akan menjelaskan cara scrape data toko yang sudah terdaftar di toko pedia denga menggunakan python.

Sebelum masuk pada pengambilan datanya, instal terlebih dahulu libary yang di butuhkan.

Pandas.
```
$ py -m pip install pandas
```
Requests.
```
$ py -m pip install requests
```

Selanjutnya kita akan mengambil API pada toko yang akan kita scrape, caranya sudah kami bahas pada pembahasan artikel sebelumnya.

Lalu kita akan melakukan import libary.

import requests
import pandas as pd

Copy url yang sudah kamu dapat tadi ke dalam visual studio code, lalu ubah beberapa variabelnya seperti di bawah ini.

url = 'https://gql.tokopedia.com/graphql/ShopProducts'

header = {'authority': 'gql.tokopedia.com',
  'accept': '*/*',
  'accept-language': 'id-ID,id;q=0.9,en-US;q=0.8,en;q=0.7',
  'content-type': 'application/json',
  'cookie': '_gcl_au=1.1.1413001030.1672228217; _UUID_NONLOGIN_=c1e6d871a598c87993e83a1501ab6f32; DID=c17aa6dcf617cbed0e6fba4639e43a825b415d046ba7852e650167030893d15c7b82e1ff1b4981e31e45c710a91c3b9c; DID_JS=YzE3YWE2ZGNmNjE3Y2JlZDBlNmZiYTQ2MzllNDNhODI1YjQxNWQwNDZiYTc4NTJlNjUwMTY3MDMwODkzZDE1YzdiODJlMWZmMWI0OTgxZTMxZTQ1YzcxMGE5MWMzYjlj47DEQpj8HBSa+/TImW+5JCeuQeRkm5NMpJWZG3hSuFU=; _UUID_CAS_=cf7fbfcb-eb64-4d6c-950c-4f9fa2b9d118; _CASE_=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; __auc=1457b782185589295917cd3559a; bm_sz=3B7F93DF63CC5463B284C008760717F3~YAAQJeUcuPacNmmFAQAAweubtRKzv/h6zWjqn5SFl1/+QcvAKpQoKTNeruq5GzfnEumQat0RYVVHW6/N1/u3GubO1aK8E3N3y7zv5woGs3FA39Nq02c4e5XMPXqKAeCmhvZP+WgRXFIdxvcj/qQTATSU6N5gnUkd2qROMfiniSVyoVnKT0Jp1q7qbG20eGPvoV1jUDoBVi+DsEbQbyJF/wWKkZi6gsnvMc9vtoYbzKAVtVmz2M58V600sFf95wWlgBimL7da8W2yVSfpv1UFSUkZ6/PPyjt5GQErqP6511QPFB5fAeI=~3553591~4340038; _gcl_aw=GCL.1673789178.CjwKCAiA5Y6eBhAbEiwA_2ZWITpDT3tQihrnx6f12R1Z_SS5v8I4QOajIsLsCgKIHBmbr7AQhXs29hoCq7MQAvD_BwE; _gid=GA1.2.187466445.1673789184; _gac_UA-126956641-6=1.1673789184.CjwKCAiA5Y6eBhAbEiwA_2ZWITpDT3tQihrnx6f12R1Z_SS5v8I4QOajIsLsCgKIHBmbr7AQhXs29hoCq7MQAvD_BwE; _SID_Tokopedia_=2cbN8ghfc7S2K0pY7QD_TuEW2UjeWPS2O1ckPmwBhOxxUGvMHcGgC1Dj7mHVNvXw_Yabyqn0PdI7y6d7hX5KhhChfrJ8L8wesNvy2dWfmdPeNccNKIgXnk9zSh1F7tDY; hfv_banner=true; _gac_UA-9801603-1=1.1673790632.CjwKCAiA5Y6eBhAbEiwA_2ZWITpDT3tQihrnx6f12R1Z_SS5v8I4QOajIsLsCgKIHBmbr7AQhXs29hoCq7MQAvD_BwE; _abck=9753AC2451958445CFC616A8A0ACC69F~0~YAAQdAA9Fz8WQheFAQAAtQGztQl2JPVldW2jyF2lyLROveJqugrSurw+hAtzhqLKjdiMGiMEEQUOK7wbF2svGPTvTZKvAJdCZ9a/LHFIz33dnoZNsyuiNUD8cz4Bs2JgrYP0jYztpAtELEl3p0MWYYOqYkD2ehperVYN9k50osr8Ibpg9XwkMWD84kSXqIva+iD/2S3v2UHX9Qc1Nxcz/ED2vsCcTdroFO6zqGhY3I7eW3A2PeMjTAtrKlnP+afU/eHC8CN9qqvQtCjdnFweZzLNrde/oTs7bSjH1dKTNOx2XYcIAPc+zJKWumSpaVip/0PS/GHOylPhscFAM8+GfFrrQpvYpDgH4dlyzuSZY9HmhgX9u/Vz4KaxsUewUoa6s8L2iVH2CSsyO7qAwrG/gcKE+5rvXamsPiLK~-1~-1~-1; bm_sv=1B822170B6B410104A16F59AFB03FD6F~YAAQdAA9FwMXQheFAQAA6hKztRJmnyLbeJqvg0JGGJL+FFCLBDx79fbufrZvOqjUsQT6Fz3tLyp0LMLUkc5r4ktYQw2uzBGvfxcaX8UKVw31lk38tkziCngLDtMKy59ck54G5RNDuboKddd5pecq9umBIOUoCKz/2CF/tdktZ6wM9VMTNih2K6q24tbVQzIgIgYR2iC/bJ+B9FWXOTVewUFT0iG9BWVvTyFiJvkG7cKd7UUckEXBkgbhWHlZhhZkmI26~1; bm_mi=CFA0C7801D2FC04AD26261DA272BCB06~YAAQDqwwF8FV7paFAQAASN/ntRKYqbuQbIVKdVIvWJAwJ1WYyZGYJmIU0ELE7V1QEJnMAdAGidbgkRcYOBlOG8gfD9GYSnS2OMwQT2cQWrvRSqAIw6NqBQOeDZB8d6ZfcgAwxkNIfXoMK6dRYHAf/w3SQ045N/hl3zVyDa3R5HgVnPCV4pqyO2kwFISJQmlq7kphSwZ/wcI08RcNivz7kT1LFwaC93YV7UJwCUDWiBSbu1juadUhA7W3QpRaDKdK26s3unvbRv585FgeSvM225yGX9Ttsmcn3slayFBuQ/UWGoISWeyoVYv24/Wwc1adg23JZdyk44mUxP0=~1; __asc=2fcddb57185b5e7f6ea4084192c; ak_bmsc=AA8432D6E8C5D880492BFABFEF624A8F~000000000000000000000000000000~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; _dc_gtm_UA-126956641-6=1; _dc_gtm_UA-9801603-1=1; _ga_70947XW48P=GS1.1.1673794055.3.1.1673794658.60.0.0; _ga=GA1.1.1251187054.1672228218',
  'origin': 'https://www.tokopedia.com',
  'referer': 'https://www.tokopedia.com/sentralkomputer-',
  'sec-ch-ua': '"Not_A Brand";v="99", "Google Chrome";v="109", "Chromium";v="109"',
  'sec-ch-ua-mobile': '?0',
  'sec-ch-ua-platform': '"Windows"',
  'sec-fetch-dest': 'empty',
  'sec-fetch-mode': 'cors',
  'sec-fetch-site': 'same-site',
  'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/109.0.0.0 Safari/537.36',
  'x-device': 'default_v3',
  'x-source': 'tokopedia-lite',
  'x-tkpd-lite-service': 'zeus',
  'x-version': '68ba647'}

query = f'[{{"operationName":"ShopProducts","variables":{{"sid":"12072236","page":1,"perPage":80,"etalaseId":"etalase","sort":1,"user_districtId":"2274","user_cityId":"176","user_lat":"","user_long":""}},"query":"query ShopProducts($sid:String\u0021, $page: Int, $perPage: Int, $keyword: String, $etalaseId: String, $sort: Int, $user_districtId:String, $user_cityId:String, $user_lat:String, $user_long:String) {{\\n  GetShopProduct(shopID:$sid, filter:{{page:$page, perPage:$perPage, fkeyword:$keyword, fmenu:$etalaseId, sort:$sort, user_districtId:$user_districtId, user_cityId:$user_cityId, user_lat:$user_lat, user_long:$user_long}}) {{\\n    status\\n    errors\\n    links {{\\n      prev\\n      next\\n      __typename\\n    }}\\n    data {{\\n      name\\n      product_url\\n      product_id\\n      price {{\\n        text_idr\\n        __typename\\n      }}\\n      primary_image {{\\n        original\\n        thumbnail\\n        resize300\\n        __typename\\n      }}\\n      flags {{\\n        isSold\\n        isPreorder\\n        isWholesale\\n        isWishlist\\n        __typename\\n      }}\\n      campaign {{\\n        discounted_percentage\\n        original_price_fmt\\n        start_date\\n        end_date\\n        __typename\\n      }}\\n      label {{\\n        color_hex\\n        content\\n        __typename\\n      }}\\n      label_groups {{\\n        position\\n        title\\n        type\\n        url\\n        __typename\\n      }}\\n      badge {{\\n        title\\n        image_url\\n        __typename\\n      }}\\n      stats {{\\n        reviewCount\\n        rating\\n        __typename\\n      }}\\n      category {{\\n        id\\n        __typename\\n      }}\\n      __typename\\n    }}\\n    __typename\\n  }}\\n}}\\n"}}]'


print('Mulai')

response = requests.post(url, headers=header, data=query)
products = response.json()[0]['data']['GetShopProduct']['data']

dtFrame = pd.DataFrame(products)
dtFrame.to_csv('data_toko_tokped.csv', encoding='utf-8')
print('Selesai.....')

Setelah itu hasil nya akan keluar dalam benntuk vcs.