I am trying to scrape the data on some pages with BeauitfulSoup but I cannot seem to get the data that I want. I am having trouble splitting the data. I'll post my code below but what I am trying to do is grab each address and split it. For instance, if you try the code below, I can get the data that I want but I can't seem to figure out how to split it on the tag. My output I am attempting is, address = ['2 Warriston's Close','High Street, Edinburgh EH1 1PG','United Kingdom']
from bs4 import BeautifulSoup as bs
import requests
url = 'https://www.hauntedplaces.org/item/mary-kings-close/'
page = requests.get(url)
soup = bs(page.text, 'lxml')
region = soup.select('dd.data')[0]
# Need something here to split the region variable so I can separate for csv file.
# Trying to use soup.select('dd.data')[0].split() but no avail.
print(region)
So, instead of the HTML, you want to get the text inside of the tags. BeautifulSoup has a text attribute. So, in this case to get what you want you can just add the line:
print(region.text.split('\n')[:3])
Related
I'm very new to Python and am attempting my first web scraping project. I'm attempting to extract the data following a tag within a XML data source. I've attached an image of the data I'm working with. My issue is that, it seems like no matter what tag I try to extract I constantly return no results. I am able to return the entire data source so I know the connection is not the issue.
My ultimate goal is to loop through all of the data and return the data following a particular tag. I think if I can understand why I'm unable to print a singular particular tag I should be able to figure out how to loop through all of the data. I've looked through similar posts but I think the tree in my set of data is particularly troublesome (that and my inexperience).
My Code:
from bs4 import BeautifulSoup
import requests
#Assign URL to scrape
URL = "http://api.powertochoose.org/api/PowerToChoose/plans?zip_code=78364"
#Fetch the raw HTML Data
Data = requests.get(URL)
Soup = BeautifulSoup(Data.text, "html.parser")
tags = Soup.find_all('fact_sheet')
print (tags)
Try to check the response of your example first, it is JSON not XML so no BeautifulSoup needed here, simply iterate the data list to pick your fact_sheets:
for plan in Data.json()['data']:
print(plan['fact_sheet'])
Out:
https://rates.cleanskyenergy.com:8443/rates/DownloadDoc?path=a70e9298-5537-481a-985c-c7a005b2e4f3.html&id_plan=223344
https://texpo-prod-api.eroms.works/api/v1/document/ViewProductDocument?type=efl&rateCode=SRCPLF24PTC&lang=en
https://www.txu.com/Handlers/PDFGenerator.ashx?comProdId=TCXSIMVL1212AR&lang=en&formType=EnergyFactsLabel&custClass=3&tdsp=AEPTCC
https://signup.myvaluepower.com/Home/EFL?productId=32653&Promo=16410
https://docs.cloud.flagshippower.com/EFL?term=36&duns=007924772&product=galleon&lang=en&code=FPSPTC2
...
As you've already realized by now, you're getting the data as json, so doing something like:
fact_sheet_links = [d['fact_sheet'] for d in Data.json()['data']]
would get you the data you want.
But also, if you'd prefer to work with the xml, you can add headers to the request:
Data = requests.get(URL, headers={ 'Accept': 'application/xml' })
and get an xml response. When I did this, Soup.find_all('fact_sheet') still did not work (although I've seen this method used in some tutorials, so it might be a version problem - and it might still work for you), but it did work when I used find_all with lambda:
tags = Soup.find_all(lambda t: 'fact_sheet' in t.name)
and the results after altering your code looked like this. That just gives you the tags though, so if you want a list of the contents instead, one way would be to use list comprehension:
fact_sheet_links = [t.text for t in tags]
so that you get them like this.
I am trying to webscrape this website. To do so,
I run the following code:
from bs4 import BeautifulSoup
import requests
url = "https://www.ecb.europa.eu/press/pressconf/2022/html/index_include.en.html"
soup = BeautifulSoup(requests.get(url).content)
data = []
for link in soup.select('div.title > a'):
soup = BeautifulSoup(requests.get(f"https://www.ecb.europa.eu{link['href']}").content)
data.append({
'text':' '.join([p.text for p in soup.select('main .section p:not([class])')])
})
print(data)
This works fine. What is the issue? The problem is that the webscraped text comes without information on paragraphs split and on bold character. This is a problem since I would then need to make some calls on the basis of that.
Can anyone suggest how to maintain meta-information in the text?
Thanks a lot!
A solution is to determine in the website code source what are the markers for paragraphs split and bold characters.
Then, the "soup" variable, you can localize what interests you using the markers as a string to be searched in "soup".
Looking briefly at the source code of your website, I think the answer relies in following markers (I needed to add ' otherwise the markers are hidden by stackoverflow):
"<'/a><'/div><'div class="subtitle">"
So to preface the website I've been trying to scrape seems to have/use (I'm unsure about the jargon with things relating to web development and the like) javascript code and I've been having varying success trying to scrape different tables on different pages.
For instance on this page: http://www.tennisabstract.com/cgi-bin/player.cgi?p=NovakDjokovic I was easily able to 'inspect element' then go to Network find the correct 'Name' of the script and then find the Request URL I needed to get the table that I wanted. The code I used for this was:
url = 'http://www.minorleaguesplits.com/tennisabstract/cgi-bin/frags/NovakDjokovic.js'
content = requests.get(url)
soup = BeautifulSoup(content.text, 'html.parser')
table = soup.find('table', id='tour-years', attrs= {'class':'tablesorter'})
dfs = pd.read_html(str(table))
df = pd.concat(dfs)
However, now when I'm looking at a different page on the same site, say this one http://www.tennisabstract.com/charting/20190714-M-Wimbledon-F-Roger_Federer-Novak_Djokovic.html, I'm unable to find the Request URL that will allow me to eventually get the table that I want. I repeat the same process as I did above, but there's no .js script under the Network tab that has the table. I do see the table when I'm looking at the html elements, but of course I can't get it without the correct url.
So my question would be, how can I get the table from this page http://www.tennisabstract.com/charting/20190714-M-Wimbledon-F-Roger_Federer-Novak_Djokovic.html ?
TIA!
On looking at the source code of the html page, you can see that all the data is already loaded in the script tag. Only thing you want is extract the variable value and load it to beautifulsoup.
The following code gives all the variables and the values from script tag
import requests, re
from bs4 import BeautifulSoup
res = requests.get("http://www.tennisabstract.com/charting/20190714-M-Wimbledon-F-Roger_Federer-Novak_Djokovic.html")
soup = BeautifulSoup(res.text, "lxml")
script = soup.find("script", attrs={"language":"JavaScript"}).text
var_only = script[:script.index("$(document)")].strip()
Next you can use regex to get the variable values - https://regex101.com/r/7cE85A/1
Python3 - Beautiful Soup 4
I'm trying to parse the weather graph out of the website:
https://www.wunderground.com/forecast/us/ny/new-york-city
But when I grab the weather graph html but beautiful soup seems to grab all around it.
I am new to Beautiful Soup. I think it is not able to grab this because either it is not able to parse the tag thing they have going on or because the javascript that populates the graph hasn't loaded or is not parsable by BS (at least the way I'm using it).
As far as my code goes, it's extremely basic
import requests, bs4
url = 'https://www.wunderground.com/forecast/us/ny/new-york-city'
requrl = requests.get(url, headers={'user-agent': 'Mozilla/5.0'})
requrl.raise_for_status()
bs = bs4.BeautifulSoup(requrl.text, features="html.parser")
a = str(bs)
x = 'weather-graph'
print(a[a.find('x'):])
#Also tried a.find('weather-graph') which returns -1
I have verified that each piece of the code works in other scenarios. The last line should find that string and print out everything after that.
I tried making x many different pieces of the html in and around the graph but got nothing of substance.
There is an API you can use. Same as the page does. Don't know if key expires. You may need to do some ordering on output but you can do that by datetime field
import requests
r = requests.get('https://api.weather.com/v1/geocode/40.765/-73.981/forecast/hourly/240hour.json?apiKey=6532d6454b8aa370768e63d6ba5a832e&units=e').json()
for i in r['forecasts']:
print(i)
If unsure I will happily update to show you how to build dataframe and order.
Hello there stack community!
I'm having an issue that I can't seem to resolve since it looks like most of the help out there is for Python 2.7.
I want to pull a table from a webpage and then just get the linktext and not the whole anchor.
Here is the code:
from urllib.request import urlopen
from bs4 import BeautifulSoup
import re
url = 'http://www.craftcount.com/category.php?cat=5'
html = urlopen(url).read()
soup = BeautifulSoup(html)
alltables = soup.findAll("table")
## This bit captures the input from the previous sequence
results=[]
for link in alltables:
rows = link.findAll('a')
## Find just the names
top100 = re.findall(r">(.*?)<\/a>",rows)
print(top100)
When I run it, I get: "TypeError: expected string or buffer"
Up to the second to the last line, it does everything correctly (when I swap out 'print(top100)' for 'print(rows)').
As an example of the response I get:
michellechangjewelry
And I just need to get:
michellechangjewelry
According to pythex.org, my (ir)regular expression should work, so I wanted to see if anyone out there knew how to do that. As an additional issue, it looks like most people like to go the other way, that is, from having the full text and only wanting the URL part.
Finally, I'm using BeautifulSoup out of "convenience", but I'm not beholden to it if you can suggest a better package to narrow down the parsing to the linktext.
Many thanks in advance!!
BeautifulSoup results are not strings; they are Tag objects, mostly.
Look for the text of the <a> tags, use the .string attribute:
for table in alltables:
link = table.find('a')
top100 = link.string
print(top100)
This finds the first <a> link in a table. To find all text of all links:
for table in alltables:
links = table.find_all('a')
top100 = [link.string for link in links]
print(top100)