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scrapehero/amazon_reviews.py

Last active November 16, 2022 03:43
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Python 3 code to extract amazon reviews
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amazon_reviews.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Written as part of https://www.scrapehero.com/how-to-scrape-amazon-product-reviews-using-python/
from lxml import html
from json import dump,loads
from requests import get
import json
from re import sub
from dateutil import parser as dateparser
from time import sleep
def ParseReviews(asin):
# This script has only been tested with Amazon.com
amazon_url = 'http://www.amazon.com/dp/'+asin
# Add some recent user agent to prevent amazon from blocking the request
# Find some chrome user agent strings here https://udger.com/resources/ua-list/browser-detail?browser=Chrome
headers = {'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/62.0.3202.94 Safari/537.36'}
for i in range(5):
response = get(amazon_url, headers = headers, verify=False, timeout=30)
if response.status_code == 404:
return {"url": amazon_url, "error": "page not found"}
if response.status_code != 200:
continue
# Removing the null bytes from the response.
cleaned_response = response.text.replace('\x00', '')
parser = html.fromstring(cleaned_response)
XPATH_AGGREGATE = '//span[@id="acrCustomerReviewText"]'
XPATH_REVIEW_SECTION_1 = '//div[contains(@id,"reviews-summary")]'
XPATH_REVIEW_SECTION_2 = '//div[@data-hook="review"]'
XPATH_AGGREGATE_RATING = '//table[@id="histogramTable"]//tr'
XPATH_PRODUCT_NAME = '//h1//span[@id="productTitle"]//text()'
XPATH_PRODUCT_PRICE = '//span[@id="priceblock_ourprice"]/text()'
raw_product_price = parser.xpath(XPATH_PRODUCT_PRICE)
raw_product_name = parser.xpath(XPATH_PRODUCT_NAME)
total_ratings = parser.xpath(XPATH_AGGREGATE_RATING)
reviews = parser.xpath(XPATH_REVIEW_SECTION_1)
product_price = ''.join(raw_product_price).replace(',', '')
product_name = ''.join(raw_product_name).strip()
if not reviews:
reviews = parser.xpath(XPATH_REVIEW_SECTION_2)
ratings_dict = {}
reviews_list = []
# Grabing the rating section in product page
for ratings in total_ratings:
extracted_rating = ratings.xpath('./td//a//text()')
if extracted_rating:
rating_key = extracted_rating[0]
raw_raing_value = extracted_rating[1]
rating_value = raw_raing_value
if rating_key:
ratings_dict.update({rating_key: rating_value})
# Parsing individual reviews
for review in reviews:
XPATH_RATING = './/i[@data-hook="review-star-rating"]//text()'
XPATH_REVIEW_HEADER = './/a[@data-hook="review-title"]//text()'
XPATH_REVIEW_POSTED_DATE = './/span[@data-hook="review-date"]//text()'
XPATH_REVIEW_TEXT_1 = './/div[@data-hook="review-collapsed"]//text()'
XPATH_REVIEW_TEXT_2 = './/div//span[@data-action="columnbalancing-showfullreview"]/@data-columnbalancing-showfullreview'
XPATH_REVIEW_COMMENTS = './/span[@data-hook="review-comment"]//text()'
XPATH_AUTHOR = './/span[contains(@class,"profile-name")]//text()'
XPATH_REVIEW_TEXT_3 = './/div[contains(@id,"dpReviews")]/div/text()'
raw_review_author = review.xpath(XPATH_AUTHOR)
raw_review_rating = review.xpath(XPATH_RATING)
raw_review_header = review.xpath(XPATH_REVIEW_HEADER)
raw_review_posted_date = review.xpath(XPATH_REVIEW_POSTED_DATE)
raw_review_text1 = review.xpath(XPATH_REVIEW_TEXT_1)
raw_review_text2 = review.xpath(XPATH_REVIEW_TEXT_2)
raw_review_text3 = review.xpath(XPATH_REVIEW_TEXT_3)
# Cleaning data
author = ' '.join(' '.join(raw_review_author).split())
review_rating = ''.join(raw_review_rating).replace('out of 5 stars', '')
review_header = ' '.join(' '.join(raw_review_header).split())
try:
review_posted_date = dateparser.parse(''.join(raw_review_posted_date)).strftime('%d %b %Y')
except:
review_posted_date = None
review_text = ' '.join(' '.join(raw_review_text1).split())
# Grabbing hidden comments if present
if raw_review_text2:
json_loaded_review_data = loads(raw_review_text2[0])
json_loaded_review_data_text = json_loaded_review_data['rest']
cleaned_json_loaded_review_data_text = re.sub('<.*?>', '', json_loaded_review_data_text)
full_review_text = review_text+cleaned_json_loaded_review_data_text
else:
full_review_text = review_text
if not raw_review_text1:
full_review_text = ' '.join(' '.join(raw_review_text3).split())
raw_review_comments = review.xpath(XPATH_REVIEW_COMMENTS)
review_comments = ''.join(raw_review_comments)
review_comments = sub('[A-Za-z]', '', review_comments).strip()
review_dict = {
'review_comment_count': review_comments,
'review_text': full_review_text,
'review_posted_date': review_posted_date,
'review_header': review_header,
'review_rating': review_rating,
'review_author': author
}
reviews_list.append(review_dict)
data = {
'ratings': ratings_dict,
'reviews': reviews_list,
'url': amazon_url,
'name': product_name,
'price': product_price
}
return data
return {"error": "failed to process the page", "url": amazon_url}
def ReadAsin():
# Add your own ASINs here
AsinList = ['B01ETPUQ6E', 'B017HW9DEW', 'B00U8KSIOM']
extracted_data = []
for asin in AsinList:
print("Downloading and processing page http://www.amazon.com/dp/" + asin)
extracted_data.append(ParseReviews(asin))
sleep(5)
f = open('data.json', 'w')
dump(extracted_data, f, indent=4)
f.close()
if __name__ == '__main__':
ReadAsin()
@DavidRoldan523
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DavidRoldan523 commented May 21, 2019 via email

@DavidRoldan523
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DavidRoldan523 commented Jun 17, 2019 via email

@amritadey
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amritadey commented Jun 19, 2019 via email

@wanyi233
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Hi David,

Thanks for sharing the code! There seems a small typo on line 71. Should it be "if int(data['number_reviews']) % 2 == 0" rather than "if number_page_reviews % 2 == 0"?

Another quick question is that there seems a maximum limit of 5,000 reviews that can be extracted. For example, for this Instant Pot pressure cooker (ASIN: B00FLYWNYQ), it has over 34k review, but I can only extract 5000 from it.

Thanks!

@dnoftzger
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Hi David,

I was able to successfully apply your code to a few ASINs. However, isn't your code supposed to produce a json or csv file? I cannot find one anywhere after running the code. The only thing I changed were the ASINs listed and the code ran successfully. I figured I would find it in my jupyter notebooks 'Files' tab. Also looked in my downloaded files in Windows. No luck... Any advice on what I ought to do from here?

@amritadey
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amritadey commented Jul 13, 2020 via email

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