Data scraping from Vivino.com

Question

I am trying to collect data from vivino.com and the DataFrame comes out empty, I can see that my soup is collecting the website info, but can't see where my error is.

My code:

def get_data():  

    headers = {"User-Agent":"Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:66.0) Gecko/20100101 Firefox/66.0", "Accept-Encoding":"gzip, deflate", "Accept":"text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8", "DNT":"1","Connection":"close", "Upgrade-Insecure-Requests":"1"}

    r = requests.get("https://www.vivino.com/explore?e=eJzLLbI1VMvNzLM1UMtNrLA1NTBQS660DQhRS7Z1DQ1SKwDKpqfZliUWZaaWJOao5SfZFhRlJqeq5dsmFierlZdExwJVJFcWA-mCEgC1YxlZ", headers=headers)#, proxies=proxies)
    content = r.content
    soup = BeautifulSoup(content, "html.parser")

and as I need the wine maker, wine name and ratings this is how I've tried this:

alls = []
    for d in soup.findAll('div', attrs={'class':'explorerCard__titleColumn--28kWX'}):
        
        Winery = d.find_all("a", attrs={"class":"VintageTitle_winery--2YoIr"})
        Wine = d.find_all("a", attrs={"class":"VintageTitle_wine--U7t9G"})
        Rating = d.find_all("div", attrs={"class":"VivinoRatingWide_averageValue--1zL_5"})
        num_Reviews = d.find_all("div", attrs={"class":"VivinoRatingWide__basedOn--s6y0t"})
        Stars = d.find_all("div", attrs={"aria-label":"rating__rating--ZZb_x rating__vivino--1vGCy"})

        alll=[]

        if Winery is not None:
            #print(n[0]["alt"])
            alll.append(Winery.text)

        else:
            alll.append("unknown-winery")

        if Wine is not None:
            #print(wine.text)
            alll.append(wine.text)
        else:
            alll.append("0")

        if Rating is not None:
            #print(rating.text)
            alll.append(rating.text)

        else:
            alll.append("0")
...

and then getting the data into a DataFrame:

results = []
for i in range(1, no_pages+1):
    results.append(get_data())
flatten = lambda l: [item for sublist in l for item in sublist]
df = pd.DataFrame(flatten(results),columns=['Winery','Wine','Rating','num_review', 'Stars'])
df.to_csv('redwines.csv', index=False, encoding='utf-8')

Answer 1

The previous answer is correct but it needs the user-agent header set:

import requests
import pandas as pd

r = requests.get(
    "https://www.vivino.com/api/explore/explore",
    params = {
        "country_code": "FR",
        "country_codes[]":"pt",
        "currency_code":"EUR",
        "grape_filter":"varietal",
        "min_rating":"1",
        "order_by":"price",
        "order":"asc",
        "page": 1,
        "price_range_max":"500",
        "price_range_min":"0",
        "wine_type_ids[]":"1"
    },
    headers= {
        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:66.0) Gecko/20100101 Firefox/66.0"
    }
)
results = [
    (
        t["vintage"]["wine"]["winery"]["name"], 
        f'{t["vintage"]["wine"]["name"]} {t["vintage"]["year"]}',
        t["vintage"]["statistics"]["ratings_average"],
        t["vintage"]["statistics"]["ratings_count"]
    )
    for t in r.json()["explore_vintage"]["matches"]
]
dataframe = pd.DataFrame(results,columns=['Winery','Wine','Rating','num_review'])

print(dataframe)

You will need to increment the page field to iterate over the next results