Scrape data from bloomberg

Question

I want to scrape data from the Bloomberg website. The data under "IBVC:IND Caracas Stock Exchange Stock Market Index" needs to be scraped.

Here is my code so far:

import requests
from bs4 import BeautifulSoup as bs

headers = {
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) '
                  'Chrome/58.0.3029.110 Safari/537.36 '
}
res = requests.get("https://www.bloomberg.com/quote/IBVC:IND", headers=headers)

soup = bs(res.content, 'html.parser')
# print(soup)
itmes = soup.find("div", {"class": "snapshot__0569338b snapshot"})

open_ = itmes.find("span", {"class": "priceText__1853e8a5"}).text
print(open_)
prev_close = itmes.find("span", {"class": "priceText__1853e8a5"}).text

I can't find the required values in the HTML. Which library should I use to handle that? I'm currently using BeautifulSoup and Requests.

Answer 1

As indicated in other answers, the content is generated via JavaScript, hence not inside the plain html. For the given problem, two different angles of attack have been proposed

• Selenium aka The Big Guns: This will let you automate virtually any task in a browser. Comes at a certain cost though in terms of speed.
• API Request aka Thought Through: This is not always feasible. When it is however the case then it is much more efficient.

I elaborate on the second one. @ViniciusDAvila already laid out the typical blueprint for such a solution: navigate to the site, inspect the Network and figure out which request is responsible for fetching the data.

Once this is done, the rest is a matter of execution:

Scraper

import requests
import json
from urllib.parse import quote


# Constants
HEADERS = {
    'Host': 'www.bloomberg.com',
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:70.0) Gecko/20100101 Firefox/70.0',
    'Accept': '*/*',
    'Accept-Language': 'de,en-US;q=0.7,en;q=0.3',
    'Accept-Encoding': 'gzip, deflate, br',
    'Referer': 'https://www.bloomberg.com/quote/',
    'DNT': '1',
    'Connection': 'keep-alive',
    'TE': 'Trailers'
}
URL_ROOT = 'https://www.bloomberg.com/markets2/api/datastrip'
URL_PARAMS = 'locale=en&customTickerList=true'
VALID_TYPE = {'currency', 'index'}


# Scraper
def scraper(object_id: str = None, object_type: str = None, timeout: int = 5) -> list:
    """
    Get the Bloomberg data for the given object.
    :param object_id: The Bloomberg identifier of the object.
    :param object_type: The type of the object. (Currency or Index)
    :param timeout: Maximal number of seconds to wait for a response.
    :return: The data formatted as dictionary.
    """
    object_type = object_type.lower()
    if object_type not in VALID_TYPE:
        return list()
    # Build headers and url
    object_append = '%s:%s' % (object_id, 'IND' if object_type == 'index' else 'CUR')
    headers = HEADERS
    headers['Referer'] += object_append
    url = '%s/%s?%s' % (URL_ROOT, quote(object_append), URL_PARAMS)
    # Make the request and check response status code
    response = requests.get(url=url, headers=headers)
    if response.status_code in range(200, 230):
        return response.json()
    return list()

Test

# Index
object_id, object_type = 'IBVC', 'index'
data = scraper(object_id=object_id, object_type=object_type)
print('The open price for %s %s is: %d' % (object_type, object_id, data[0]['openPrice']))
# The open price for index IBVC is: 50094

# Exchange rate
object_id, object_type = 'EUR', 'currency'
data = scraper(object_id=object_id, object_type=object_type)
print('The open exchange rate for USD per {} is: {}'.format(object_id, data[0]['openPrice']))
# The open exchange rate for USD per EUR is: 1.0993