I need to scrape the items of the first page and then go to the next button to go to the second page and scrape and so on.
This is my code, but only scrape the first item of each page, if there are 20 pages enter to every page and scrape only the first item.
Could anyone please help me .
Thank you
Apologies for my english.
class CcceSpider(CrawlSpider):
name = 'ccce'
item_count = 0
allowed_domain = ['www.example.com']
start_urls = ['https://www.example.com./afiliados value=&categoria=444&letter=']
rules = {
# Reglas Para cada item
Rule(LinkExtractor(allow = (), restrict_xpaths = ('//li[#class="pager-next"]/a')), callback = 'parse_item', follow = True),
}
def parse_item(self, response):
ml_item = CcceItem()
#info de producto
ml_item['nombre'] = response.xpath('normalize-space(//div[#class="news-col2"]/h2/text())').extract()
ml_item['url'] = response.xpath('normalize-space(//div[#class="website"]/a/text())').extract()
ml_item['correo'] = response.xpath('normalize-space(//div[#class="email"]/a/text())').extract()
ml_item['descripcion'] = response.xpath('normalize-space(//div[#class="news-col4"]/text())').extract()
self.item_count += 1
if self.item_count > 5:
#insert_table(ml_item)
raise CloseSpider('item_exceeded')
yield ml_item
As you haven't given an working target url, I'm a bit guessing here, but most probably this is the problem:
parse_item should be a parse_page (and act accordingly)
Scrapy is downloading a full page which has - according to your description - multiple items and then passes this as a response object to your parse method.
It's your parse method's responsibility to process the whole page by iterating over the items displayed on the page and creating multiple scraped items accordingly.
The scrapy documentation has several good examples for this, one is here: https://doc.scrapy.org/en/latest/topics/selectors.html#working-with-relative-xpaths
Basically your code structure in def parse_XYZ should look like this:
def parse_page(self, response):
items_on_page = response.xpath('//...')
for sel_item in items_on_page:
ml_item = CcceItem()
#info de producto
ml_item['nombre'] = # ...
# ...
yield ml_item
Insert the right xpaths for getting all items on the page and adjust your item xpaths and you're ready to go.
Related
I am currently web scraping a few pages inside a list. I have the following code provided.
pages = {
"https://shop.supervalu.ie/shopping/wine-beer-spirits-germany/c-150410100",
"https://shop.supervalu.ie/shopping/wine-beer-spirits-small-bottles/c-150410110",
"https://shop.supervalu.ie/shopping/wine-beer-spirits-lager/c-150302375", #More than one page
"https://shop.supervalu.ie/shopping/wine-beer-spirits-stout/c-150302380",
"https://shop.supervalu.ie/shopping/wine-beer-spirits-ale/c-150302385",
"https://shop.supervalu.ie/shopping/wine-beer-spirits-lager/c-150302386",
"https://shop.supervalu.ie/shopping/wine-beer-spirits-stout/c-150302387",
"https://shop.supervalu.ie/shopping/wine-beer-spirits-ale/c-150302388", #More than one page
"https://shop.supervalu.ie/shopping/wine-beer-spirits-cider/c-150302389",
"https://shop.supervalu.ie/shopping/wine-beer-spirits-cider/c-150302390",
"https://shop.supervalu.ie/shopping/wine-beer-spirits-alcopops/c-150302395",
"https://shop.supervalu.ie/shopping/wine-beer-spirits-vodka/c-150302430",
"https://shop.supervalu.ie/shopping/wine-beer-spirits-irish-whiskey/c-150302435", #More than one page
}
products = []
prices = []
images = []
urls = []
def export_data():
logging.info("exporting data to pandas dataframe")
supervalu = pd.DataFrame({
'img_url' : images,
'url' : urls,
'product' : products,
'price' : prices
})
logging.info("sorting data by price")
supervalu.sort_values(by=['price'], inplace=True)
output_json = 'supervalu.json'
output_csv = 'supervalu.csv'
output_dir = Path('../../json/supervalu')
output_dir.mkdir(parents=True, exist_ok=True)
logging.info("exporting data to json")
supervalu.to_json(output_dir / output_json)
logging.info("exporting data to csv")
supervalu.to_csv(output_dir / output_csv)
def get_data(div):
raw_data = div.find_all('div', class_='ga-product')
raw_images = div.find_all('img')
raw_url = div.find_all('a', class_="ga-product-link")
product_data = [data['data-product'] for data in raw_data]
new_data = [d.replace("\r\n","") for d in product_data]
for name in new_data:
new_names = re.search(' "name": "(.+?)"', name).group(1)
products.append(new_names)
for price in new_data:
new_prices = re.search(' "price": ''"(.+?)"', price).group(1)
prices.append(new_prices)
for image in raw_images:
new_images = image['data-src']
images.append(new_images)
for url in raw_url:
new_url = url['href']
urls.append(new_url)
def scrape_page(next_url):
page = requests.get(next_url)
if page.status_code != 200:
logging.error("Page does not exist!")
exit()
soup = BeautifulSoup(page.content, 'html.parser')
get_data(soup.find(class_="row product-list ga-impression-group"))
try:
load_more_text = soup.find('a', class_='pill ajax-link load-more').findAll('span')[-1].text
if load_more_text == 'Load more':
next_page = soup.find('a', class_="pill ajax-link load-more").get('href')
logging.info("Scraping next page: {}".format(next_page))
scrape_page(next_page)
else:
export_data()
except:
logging.warning("No more next pages to scrape")
pass
for page in pages:
logging.info("Scraping page: {}".format(page))
scrape_page(page)
The main issue that appears is during the try exception handling of the next page. As not all of the pages provided have the the appropriate snippet, a ValueAttribute error will araise hence I have the aforementioned statement closed off in a try exception case. I want to skip the pages that don't have next page and scrape them regardless and continue looping the rest of the pages until a next page arises. All of the pages appear to be looped through but I never get the data exported. If I try the following code:
try:
load_more_text = soup.find('a', class_='pill ajax-link load-more').findAll('span')[-1].text
if load_more_text == 'Load more':
next_page = soup.find('a', class_="pill ajax-link load-more").get('href')
logging.info("Scraping next page: {}".format(next_page))
scrape_page(next_page)
except:
logging.warning("No more next pages to scrape")
pass
else:
export_data()
This would be the closest that I have gotten to the desired outcome. The above code works and the data gets exported but not all of the pages get exported because as a result - a new dataframe is created for every time a new next page appears and ends i.e. - code iterarets through the list, finds a next page, next page 'pages' get scraped and a new dataframe is created and deletes the previous data.
I'm hoping that someone would give me some guidance on what to do as I have been stuck on this part of my personal project and I'm not so sure on how I am supposed to overcome this obstacle. Thank you in advance.
I have modified my code as shown below and I have received my desired outcome.
load_more_text = soup.find('a', class_='pill ajax-link load-more')
if load_more_text:
next_page = soup.find('a', class_="pill ajax-link load-more").get('href')
logging.info("Scraping next page: {}".format(next_page))
scrape_page(next_page)
else:
export_data()
I'm trying to scrape data from amazon India website. I am not able collect response and parse the elements using the yield() method when:
1) I have to move from product page to review page
2) I have to move from one review page to another review page
Product page
Review page
Code flow:
1) customerReviewData() calls the getCustomerRatingsAndComments(response)
2) The getCustomerRatingsAndComments(response)
finds the URL of the review page and call the yield request method with getCrrFromReviewPage(request) as callback method, with url of this review page
3) getCrrFromReviewPage() gets new response of the firstreview page and scrape all the elements from the first review page (page loaded) and add it to customerReviewDataList[]
4) get URL of the next page if it exists and recursively call getCrrFromReviewPage() method, and crawl elements from next page, until all the review page is crawled
5) All the reviews gets added to the customerReviewDataList[]
I have tried playing around with yield() changing the parameters and also looked up the scrapy documentation for yield() and Request/Response yield
# -*- coding: utf-8 -*-
import scrapy
import logging
customerReviewDataList = []
customerReviewData = {}
#Get product name in <H1>
def getProductTitleH1(response):
titleH1 = response.xpath('normalize-space(//*[#id="productTitle"]/text())').extract()
return titleH1
def getCustomerRatingsAndComments(response):
#Fetches the relative url
reviewRelativePageUrl = response.css('#reviews-medley-footer a::attr(href)').extract()[0]
if reviewRelativePageUrl:
#get absolute URL
reviewPageAbsoluteUrl = response.urljoin(reviewRelativePageUrl)
yield Request(url = reviewPageAbsoluteUrl, callback = getCrrFromReviewPage())
self.log("yield request complete")
return len(customerReviewDataList)
def getCrrFromReviewPage():
userReviewsAndRatings = response.xpath('//div[#id="cm_cr-review_list"]/div[#data-hook="review"]')
for userReviewAndRating in userReviewsAndRatings:
customerReviewData[reviewTitle] = response.css('#cm_cr-review_list .review-title span ::text').extract()
customerReviewData[reviewDescription] = response.css('#cm_cr-review_list .review-text span::text').extract()
customerReviewDataList.append(customerReviewData)
reviewNextPageRelativeUrl = response.css('#cm_cr-pagination_bar .a-pagination .a-last a::attr(href)')[0].extract()
if reviewNextPageRelativeUrl:
reviewNextPageAbsoluteUrl = response.urljoin(reviewNextPageRelativeUrl)
yield Request(url = reviewNextPageAbsoluteUrl, callback = getCrrFromReviewPage())
class UsAmazonSpider(scrapy.Spider):
name = 'Test_Crawler'
allowed_domains = ['amazon.in']
start_urls = ['https://www.amazon.in/Philips-Trimmer-Cordless-Corded-QT4011/dp/B00JJIDBIC/ref=sr_1_3?keywords=philips&qid=1554266853&s=gateway&sr=8-3']
def parse(self, response):
titleH1 = getProductTitleH1(response),
customerReviewData = getCustomerRatingsAndComments(response)
yield{
'Title_H1' : titleH1,
'customer_Review_Data' : customerReviewData
}
I'm getting the following response:
{'Title_H1': (['Philips Beard Trimmer Cordless and Corded for Men QT4011/15'],), 'customer_Review_Data': <generator object getCustomerRatingsAndComments at 0x048AC630>}
The "Customer_review_Data" should be a list of dict of title and review
I am not able to figure out as to what mistake I am doing here.
When I use the log() or print() to see what data is captured in customerReviewDataList[], unable to see the data in the console either.
I am able to scrape all the reviews in customerReviewDataList[], if they are present in the product page,
In this scenario where I have to use the yield function I am getting the output stated above like this [https://ibb.co/kq8w6cf]
This is the kind of output I am looking for:
{'customerReviewTitle': ['Difficult to find a charger adapter'],'customerReviewComment': ['I already have a phillips trimmer which was only cordless. ], 'customerReviewTitle': ['Good Product'],'customerReviewComment': ['Solves my need perfectly HK']}]}
Any help is appreciated. Thanks in advance.
You should complete the Scrapy tutorial. The Following links section should be specially helpful to you.
This is a simplified version of your code:
def data_request_iterator():
yield Request('https://example.org')
class MySpider(Spider):
name = 'myspider'
start_urls = ['https://example.com']
def parse(self, response):
yield {
'title': response.css('title::text').get(),
'data': data_request_iterator(),
}
Instead, it should look like this:
class MySpider(Spider):
name = 'myspider'
start_urls = ['https://example.com']
def parse(self, response):
item = {
'title': response.css('title::text').get(),
}
yield Request('https://example.org', meta={'item': item}, callback=self.parse_data)
def parse_data(self, response):
item = response.meta['item']
# TODO: Extend item with data from this second response as needed.
yield item
So I've tried to loop on a formrequest that call my function that create, fill and yield the item, only pb : only one and only one item is done no matter how many times he looped and I can't figure out why ?
def access_data(self, res):
#receive all ID and request the infos
res_json = (res.body).decode("utf-8")
res_json = json.loads(res_json)
for a in res_json['data']:
logging.warning(a['id'])
req = FormRequest(
url='https://my_url',
cookies={my_cookies},
method='POST',
callback=self.fill_details,
formdata={'valeur': str(a['id'])},
headers={'X-Requested-With': 'XMLHttpRequest'}
)
yield req
def fill_details(self, res):
logging.warning("annonce")
item = MyItem()
item['html'] = res.xpath('//body//text()')
item['existe'] = True
item['ip_proxy'] = None
item['launch_time'] = str(mySpider.init_time)
yield item
To be sure everything is clear :
When I run this, the log "annonce" is printed only one time while my logging a['id'] in my request loop is printed a lot and i can't find a way to fix this
I found the way !
If any one has the same pb : as my url is always the same (only formdata change) the scrapy filter is taking the control and destroy the duplicates.
Activate dont_filter to true in the formrequest to make it works
How can I remove that? I Tried so many things and I am exhausted of trying to defeat this error by myself. I spent the last 3 hours looking at this and trying to get through it and I surrender to this code. Please help.
The first "for" statement grabs article titles from news.google.com
The second "for" statement grabs the time of submisssion from that article on news.google.com.
This is on django btw and this page shows the list of article titles and their time of submission in a list, going down. The weird unicode letters are popping up from the second "for" statement which is the time submissions. Here is my views.py:
def articles(request):
""" Grabs the most recent articles from the main news page """
import bs4, requests
list = []
list2 = []
url = 'https://news.google.com/'
r = requests.get(url)
try:
r.raise_for_status() == True
except ValueError:
print('Something went wrong.')
soup = bs4.BeautifulSoup(r.text, 'html.parser')
for (listarticles) in soup.find_all('h2', 'esc-lead-article-title'):
if listarticles is not None:
a = listarticles.text
list.append(a)
for articles_times in soup.find_all('span','al-attribution-timestamp'):
if articles_times is not None:
b = articles_times.text
list2.append(b)
list = zip(list,list2)
context = {'list':list}
return render(request, 'newz/articles.html', context)
Is there a way to tell scrapy to stop crawling based upon condition in the 2nd level page? I am doing the following:
I have a start_url to begin with (1st level page)
I have set of urls extracted from the start_url using parse(self,
response)
Then I add queue the links using Request with callback as parseDetailPage(self, response)
Under parseDetail (2nd level page) I come to know if I can stop crawling or not
Right now I am using CloseSpider() to accomplish this, but the problem is that the urls to be parsed are already queued by the time I start crawling second level pages and I do not know how to remove them from the queue. Is there a way to sequentially crawl the list of links and then be able to stop in parseDetailPage?
global job_in_range
start_urls = []
start_urls.append("http://sfbay.craigslist.org/sof/")
def __init__(self):
self.job_in_range = True
def parse(self, response):
hxs = HtmlXPathSelector(response)
results = hxs.select('//blockquote[#id="toc_rows"]')
items = []
if results:
links = results.select('.//p[#class="row"]/a/#href')
for link in links:
if link is self.end_url:
break;
nextUrl = link.extract()
isValid = WPUtil.validateUrl(nextUrl);
if isValid:
item = WoodPeckerItem()
item['url'] = nextUrl
item = Request(nextUrl, meta={'item':item},callback=self.parseDetailPage)
items.append(item)
else:
self.error.log('Could not parse the document')
return items
def parseDetailPage(self, response):
if self.job_in_range is False:
raise CloseSpider('End date reached - No more crawling for ' + self.name)
hxs = HtmlXPathSelector(response)
print response
body = hxs.select('//article[#id="pagecontainer"]/section[#class="body"]')
item = response.meta['item']
item['postDate'] = body.select('.//section[#class="userbody"]/div[#class="postinginfos"]/p')[1].select('.//date/text()')[0].extract()
if item['jobTitle'] is 'Admin':
self.job_in_range = False
raise CloseSpider('Stop crawling')
item['jobTitle'] = body.select('.//h2[#class="postingtitle"]/text()')[0].extract()
item['description'] = body.select(str('.//section[#class="userbody"]/section[#id="postingbody"]')).extract()
return item
Do you mean that you would like to stop the spider and resume it without parsing the urls which have been parsed?
If so, you may try to set the JOB_DIR setting. This setting can keep the request.queue in specified file on the disk.