Since this code contains external python library lxml but I need to change code such that it works with python internal library + request library only .because Zapier doesn't support external libraries
from lxml import html
import requests
import lxml.html
# download & parse web page
doc = requests.get('https://www.makeuseof.com/feed/')
parser = lxml.html.fromstring(doc.content)
#find all image tags
x = parser.xpath('//img')
#get all image tags
la=[]
for t in x:
la.append((t.get("src")))
#remove multiple tags
for cell in set(la):
if cell is not None:
print(cell)
PS I have heard urlib can do but I have no such idea. Also above code just find the images from feed pages
Related
I am trying to read in a url in python 3 however when I tried it did not completely red in the URL
Here is my code
my_url="https://www.newegg.ca/Video-Cards-Video-Devices/Category/ID-38?Tpk=graphics%20cards"
Uclient=uReq(my_url)
page_html=Uclient.read()
Have you tried importing it using requests? As you do not show you direct imports I am assuming you are using urllib.request. The code below should provide you the entire html text available before any javascript is loaded (if the case)
import requests
my_url="https://www.newegg.ca/Video-Cards-Video-Devices/Category/ID-38?Tpk=graphics%20cards"
r = requests.get(my_url)
print (r.text)
I'm actually trying to code a little "GPS" and actually I couldn't use Google API because of the daily restriction.
I decided to use a site "viamichelin" which provide me the distance between two adresses. I created a little code to fetch all the URL adresses I needed like this :
import pandas
import numpy as np
df = pandas.read_excel('C:\Users\Bibi\Downloads\memoire\memoire.xlsx', sheet_name='Clients')
df2= pandas.read_excel('C:\Users\Bibi\Downloads\memoire\memoire.xlsx', sheet_name='Agences')
matrix=df.as_matrix(columns=None)
clients = np.squeeze(np.asarray(matrix))
matrix2=df2.as_matrix(columns=None)
agences = np.squeeze(np.asarray(matrix2))
compteagences=0
comptetotal=0
for j in agences:
compteclients=0
for i in clients:
print agences[compteagences]
print clients[compteclients]
url ='https://fr.viamichelin.be/web/Itineraires?departure='+agences[compteagences]+'&arrival='+clients[compteclients]+'&arrivalId=34MTE1MnJ5ZmQwMDMzb3YxMDU1ZDFvbGNOVEF1TlRVNU5UUT1jTlM0M01qa3lOZz09Y05UQXVOVFl4TlE9PWNOUzQzTXpFNU5nPT1jTlRBdU5UVTVOVFE9Y05TNDNNamt5Tmc9PTBqUnVlIEZvbmQgZGVzIEhhbGxlcw==&index=0&vehicle=0&type=0&distance=km¤cy=EUR&highway=false&toll=false&vignette=false&orc=false&crossing=true&caravan=false&shouldUseTraffic=false&withBreaks=false&break_frequency=7200&coffee_duration=1200&lunch_duration=3600&diner_duration=3600&night_duration=32400&car=hatchback&fuel=petrol&fuelCost=1.393&allowance=0&corridor=&departureDate=&arrivalDate=&fuelConsumption='
print url
compteclients+=1
comptetotal+=1
compteagences+=1
All my datas are on Excel that's why I used the pandas library. I have all the URL's needed for my project.
Although, I would like to extract the number of kilometers needed but there's a little problem. In the source code, I don't have the information I need, so I can't extract it with Python... The site is presented like this:
Michelin
When I click on "inspect" I can find the information needed (on the left) but I can't on the source code (on the right) ... Can someone provide me some help?
Itinerary
I have already tried this, without succeeding :
import os
import csv
import requests
from bs4 import BeautifulSoup
requete = requests.get("https://fr.viamichelin.be/web/Itineraires?departure=Rue%20Lebeau%2C%20Liege%2C%20Belgique&departureId=34MTE1Mmc2NzQwMDM0NHoxMDU1ZW44d2NOVEF1TmpNek5ERT1jTlM0MU5qazJPQT09Y05UQXVOak16TkRFPWNOUzQxTnpBM01nPT1jTlRBdU5qTXpOREU9Y05TNDFOekEzTWc9PTBhUnVlIExlYmVhdQ==&arrival=Rue%20Rys%20De%20Mosbeux%2C%20Trooz%2C%20Belgique&arrivalId=34MTE1MnJ5ZmQwMDMzb3YxMDU1ZDFvbGNOVEF1TlRVNU5UUT1jTlM0M01qa3lOZz09Y05UQXVOVFl4TlE9PWNOUzQzTXpFNU5nPT1jTlRBdU5UVTVOVFE9Y05TNDNNamt5Tmc9PTBqUnVlIEZvbmQgZGVzIEhhbGxlcw==&index=0&vehicle=0&type=0&distance=km¤cy=EUR&highway=false&toll=false&vignette=false&orc=false&crossing=true&caravan=false&shouldUseTraffic=false&withBreaks=false&break_frequency=7200&coffee_duration=1200&lunch_duration=3600&diner_duration=3600&night_duration=32400&car=hatchback&fuel=petrol&fuelCost=1.393&allowance=0&corridor=&departureDate=&arrivalDate=&fuelConsumption=")
page = requete.content
soup = BeautifulSoup(page, "html.parser")
print soup
Looking at the inspector for the page, the actual routing is done via a JavaScript invocation to this rather long URL.
The data you need seems to be in that response, starting from _scriptLoaded(. (Since it's a JavaScript object literal, you can use Python's built-in JSON library to load the data into a dict.)
I'm not a programmer, but I'm trying to teach myself Python so that I can pull data off various sites for projects that I'm working on. I'm using "Automate the Boring Stuff" and I'm having trouble getting the examples to work with one of the pages I'm trying to pull data from.
I'm using Anaconda as my prompt with Python 3.65. Here's what I've done:
Step 1: create the beautiful soup object
import requests, bs4
res = requests.get('https://www.almanac.com/weather/history/zipcode/02111/2017-05-15')
res.raise_for_status()
weatherTest = bs4.BeautifulSoup(res.text)
type(weatherTest)
This works, and returns the result
<class 'bs4.BeautifulSoup'>
I've made the assumption that the "noStarchSoup" that was in the original text (in place of weatherTest here) is a name the author gave to the object that I can rename to something more relevant to me. If that's not accurate, please let me know.
Step 2: pull an element out of the html
Here's where I get stuck. The author had just mentioned how to pull a page down into a file (which I would prefer not to do, I want to use the bs4 object), but then is using that file as his source for the html data. The exampleFile was his downloaded file.
import bs4
exampleFile = open('https://www.almanac.com/weather/history/zipcode/02111/2017-05-15')
I've tried using weatherTest in place of exampleFile, I've tried running the whole thing with the original object name (noStarchSoup), I've even tried it with exampleFile, even though I haven't downloaded the file.
What I get is
"OSError: [Errno 22] Invalid argument:
'https://www.almanac.com/weather/history/zipcode/02111/2017-05-15'
The next step is to tell it what element to pull but I'm trying to fix this error first and kind of spinning my wheels here.
Couldn't resist here!
I found this page during my search but this answer didn't quite help... try this code :)
Step 1: download Anaconda 3.0+
Step 2: (function)
# Import Libraries
import bs4
import requests
def import_high_short_tickers(market_type):
if market_type == 'NADAQ':
page = requests.get('https://www.highshortinterest.com/nasdaq/')
elif market_type == 'NYSE':
page = requests.get('https://www.highshortinterest.com/nyse/')
else:
logger.error("Invalid market_type: " + market_type)
return None
# Parse the HTML Page
soup = bs4.BeautifulSoup(page.content, 'html.parser')
# Grab only table elements
all_soup = soup.find_all('table')
# Get what you want from table elements!
for element in all_soup:
listing = str(element)
if 'https://finance.yahoo.com/' in listing:
# Stuff the results in a pandas data frame (if your not using these you should)
data = pd.read_html(listing)
return data
Yes Yes its very crude but don't hate!
Cheers!
I am planning to scraping exchange rates with Python.After I get the raw data from HTML pages, what kind of processing will I need to get prepared for my output/visualization? Will I need some text processing, NLP algorithms, graph processing or cleaning of your data?
I don't know exactly what you need but according to your comment, you can use following code to extract all data from that page:
import urllib
import bs4
url=urllib.urlopen('http://www.tcmb.gov.tr/kurlar/201501/02012015.xml').read().decode('Windows-1252')
soup=bs4.BeautifulSoup(url)
data=soup.get_text(' ')
print(data)
this script wrote on python 2.7 and you need to install beautifulsoup4.
or you can use below code. in this code I extract rates for us dollar:
import urllib.request
import xml.etree.ElementTree as ET
url=urllib.request.urlopen('http://www.tcmb.gov.tr/kurlar/201501/02012015.xml').read()
f=open('data.xml','w+b')
f.write(url)
f.close()
tree = ET.parse('data.xml')
root = tree.getroot()
for i in range(len(root[0])):
print(root[0][i].text)
or you can extract all rates for ForexBuying:
for i in root.iter('ForexBuying'):
print(i.text)
One really newbie question.
I'm working on a small python script for my home use, that will collect data of a specific air ticket.
I want to extract the data from skyscanner (using BeautifulSoap and urllib). Example:
http://www.skyscanner.net/flights/lond/rome/120922/120929/airfares-from-london-to-rome-in-september-2012.html
And I'm interested in all the data that are stored in this kind of element, specially the price: http://shrani.si/f/1w/An/1caIzEzT/capture.png
Because they are not located in the HTML, can I extract them?
I believe the problem is that these values are rendered through a javascript code which your browser runs and urllib doesn't - You should use a library that can execute javascript code.
I just googled crawler python javascript and I got the some stackoverflow questions and answers which recommends the use of selenium or webkit. You can use those libraries through scrapy. Here are two snippets:
Rendered/interactive javascript with gtk/webkit/jswebkit
Rendered Javascript Crawler With Scrapy and Selenium RC
I have been working on this same exact issue. I have been introduced to Beautifulsoup and later since learned about Scrapy. Beautifulsoup is very easy to use, especially if you're new at this. Scrapy apparently has more "features", but I believe you can accomplish your needs with Beautifulsoup.
I had the same issues about not being able to gain access to a website that loaded information through Javascript and thankfully Selenium was the savior.
A great introduction to Selenium can be found here.
Install: pip install selenium
Below is a simple class I put together. You can save it as a .py file and import it into your project. If you call the method retrieve_source_code(self, domain) and send the hyperlink that you are trying to parse it will return the source code of the fully loaded page when you can then put into Beautifulsoup and find the information you're looking for!
Ex:
airfare_url = 'http://www.skyscanner.net/flights/lond/rome/120922/120929/airfares-from-london-to-rome-in-september-2012.html'
soup = BeautifulSoup(SeleniumWebScraper.retrieve_source_code(airfare_url))
Now you can parse soup like you normally would with Beautifulsoup.
I hope that helps you!
from selenium import webdriver
import requests
class SeleniumWebScraper():
def __init__(self):
self.source_code = ''
self.is_page_loaded = 0
self.driver = webdriver.Firefox()
self.is_browser_closed = 0
# To ensure the page has fully loaded we will 'implicitly' wait
self.driver.implicitly_wait(10) # Seconds
def close(self):
self.driver.close()
self.clear_source_code()
self.is_page_loaded = 0
self.is_browser_closed = 1
def clear_source_code(self):
self.source_code = ''
self.is_page_loaded = 0
def retrieve_source_code(self, domain):
if self.is_browser_closed:
self.driver = webdriver.Firefox()
# The driver.get method will navigate to a page given by the URL.
# WebDriver will wait until the page has fully loaded (that is, the "onload" event has fired)
# before returning control to your test or script.
# It's worth nothing that if your page uses a lot of AJAX on load then
# WebDriver may not know when it has completely loaded.
self.driver.get(domain)
self.is_page_loaded = 1
self.source_code = self.driver.page_source
return self.source_code
You don't even need BeautifulSoup to extract data.
Just do this and your response is converted to a Dictionary which is very easy to handle.
text = json.loads("You text of the main response content")
You can now print any key value pair from the dictionary.
Give it a try. It is super easy.