HI, I've got a list of 10 websites in CSV. All of the sites have the same general format, including a large table. I only want the the data in the 7th columns. I am able to extract the html and filter the 7th column data (via RegEx) on an individual basis but I can't figure out how to loop through the CSV. I think I'm close but my script won't run. I would really appreciate it if someone could help me figure-out how to do this. Here's what i've got:
#Python v2.6.2
import csv
import urllib2
import re
urls = csv.reader(open('list.csv'))
n =0
while n <=10:
for url in urls:
response = urllib2.urlopen(url[n])
html = response.read()
print re.findall('td7.*?td',html)
n +=1
When I copied your routine, I did get a white space / tab error error. Check your tabs. You were indexing into the URL string incorrectly using your loop counter. This would have also messed you up.
Also, you don't really need to control the loop with a counter. This will loop for each line entry in your CSV file.
#Python v2.6.2
import csv
import urllib2
import re
urls = csv.reader(open('list.csv'))
for url in urls:
response = urllib2.urlopen(url[0])
html = response.read()
print re.findall('td7.*?td',html)
Lastly, be sure that your URLs are properly formed:
http://www.cnn.com
http://www.fark.com
http://www.cbc.ca
Related
I'm very beginner to python but I know intermediate JavaScript. I have one project to complete this is like a scraper but I want to automate some work for me.
1 ) I have a Excel with more than 1000 data and it also has URLs. I want to code that python visit every URL from that Excel sheet and search first page for Some predefine search texts (List of Texts)
2 ) If my code find any of the Text from that web page then it should return true else false
I want any idea or logic to do this kind of process. Any help will make my head pain less 😅
it is very heavy work which is not very good idea to do in JavaScript that's why I want to do it in Python
An easy way to do this would be to get the requests module. Then learn how to use the csv module which can read spreadsheets such as excel spreadsheets. Then here is what you want to do
import csv
import requests
URLS = []
def GetUrlFromCSVFile():
global URLS
#Figure out how to get link from csv file then append them to the URLS list
for url in URLS:
r = requests.get(URL, headers=#You Should Probs get some headers)
if whatever_keyword_u_looking_for in r.text:
print("Found")
else:
print("Not here")
I suggest the following:
Read about the csv library - to read the content of an excel file.
Read about the requests library - to get the page's content from its URL.
Read about regular expressions in the re library.
Since I've been trying to figure out how to make a loop and I couldn't make it from another threads, I need help. I am totally new to this so editing existing codes is hard for me.
I am trying to web scrape data from website. Here's what I've done so far, but I have to insert pages "manually". I want it to automatically scrape prices in zl/m2 from 1 to 20 pages for example:
import requests
from bs4 import BeautifulSoup
link=("https://ogloszenia.trojmiasto.pl/nieruchomosci-mam-do-wynajecia/wi,100.html?strona=1")
page = requests.get(link).text
link1=("https://ogloszenia.trojmiasto.pl/nieruchomosci-mam-do-wynajecia/wi,100.html?strona=2")
page1 = requests.get(link1).text
link2=("https://ogloszenia.trojmiasto.pl/nieruchomosci-mam-do-wynajecia/wi,100.html?strona=3")
page2 = requests.get(link2).text
pages=page+page1+page2+page3+page4+page5+page6
soup = BeautifulSoup(pages, 'html.parser')
price_box = soup.findAll('p', attrs={'class':'list__item__details__info details--info--price'})
prices=[]
for i in range(len(price_box)):
prices.append(price_box[i].text.strip())
prices
I've tried with this code, but got stuck. I don't know what should I add to get output from 20 pages at once and how to save it to csv file.
npages=20
baselink="https://ogloszenia.trojmiasto.pl/nieruchomosci-mam-do-wynajecia/wi,100.html?strona="
for i in range (1,npages+1):
link=baselink+str(i)
page = requests.get(link).text
Thanks in advance for any help.
Python is whitespace sensitive, so the code block of any loops needs to be indented, like so:
for i in range (1,npages+1):
link=baselink+str(i)
page = requests.get(link).text
If you want all of the pages in a single string (so you can use the same approach as with your pages variable above), you can append the strings together in your loop:
pages = ""
for i in range (1,npages+1):
link=baselink+str(i)
pages += requests.get(link).text
To create a csv file with your results, you can look into the csv.writer() method in python's built-in csv module, but I usually find it easier to write to a file using print():
with open(samplefilepath, mode="w+") as output_file:
for price in prices:
print(price, file=output_file)
w+ tells python to create the file if it doesn't exist and overwrite if it does exist. a+ would append to the existing file if it exists
I'm trying to scrape specific text from a website. Because I'm new in Python, I find it difficult to scrape a text with a single script, so I used this code first:
import urllib
import requests
from bs4 import BeautifulSoup
htmltext = urllib.urlopen("https://io.winmasters.com/Feeds/api/event /282576?lang=el").read()
data = htmltext
soup = BeautifulSoup(data)
f = open('/Desktop/text.txt', 'w')
f.write(data)
f.close()`
and next I'm trying to write a script for searching the text and print specific words.
with open("/Desktop/text.txt") as openfile:
for line in openfile:
for part in line.split():
if "odds=" in part:
print part
but the search script doesn't return the text I'm searching for. Any suggestions please?
If you simply want the values associated with the odds key, without any context at all, you could simply do the following:
import urllib
from json import loads # JSON parser
jsontext = urllib.urlopen("https://io.winmasters.com/Feeds/api/event/282576?lang=el").read()
data = loads(jsontext) # Parse the JSON
odds = [[b['odds'] for b in a['children']] for a in data['children']]
The nested list comprehension takes advantage of the structure of the data. An advantage of using the data structure is that you can do quite rich analytics without too much effort. If you wanted other info in addition to the odds then this would probably better implemented as a nested for-loop.
How about:
import sys
from bs4 import Beautiful Soup
import mechanize
def viewPage(url):
browser=mechanize.Browser()
browser.set_handle_robots(False)
browser.addheaders=[('user-agent','MozillaMozilla/5.0')]
page=browser.open(url)
source_code=page.read()
soup=BeautifulSoup(source_code)
info=soup.findAll("insert what you want to locate")
print(info)
viewPage("www.xkcd.com")
I have a program that when you choose a webpage it reads off all the links, chooses one at random and goes to it, doing the same. It basically crawls across the interweb. The code above is a modified excerpt.
I am writing a code which creates several URLs, which again are stored in a list.
The next step would be, open each URL, download the data (which is only text, formatted in XML or JSON) and save the downloaded data.
My code works fine thanks to the online community here up. It stuck at the point to open the URL and download the data. I want the url.request to loop through the list with my created urls and call each url seperately, open it, display it and move on to the next. But it only does the loop to create the urls, but then nothing. No feedback, nothing.
import urllib.request
.... some calculations for llong and llat ....
#create the URLs and store in list
urls = []
for lat,long,lat1,long1 in (zip(llat, llong,llat[1:],llong[1:])):
for pages in range (1,17):
print ("https://api.flickr.com/services/rest/?method=flickr.photos.search&format=json&api_key=5.b&nojsoncallback=1&page={}&per_page=250&bbox={},{},{},{}&accuracy=1&has_geo=1&extras=geo,tags,views,description".format(pages,long,lat,long1,lat1))
print (urls)
#accessing the website
data = []
for amounts in urls:
response = urllib.request.urlopen(urls)
flickrapi = data.read()
data.append(+flickrapi)
data.close()
print (data)
What am I doing wrong`?
The next step would be, downloading the data and save them to a file or somewhere else for further processing.
Since I will receive heaps of data, like a lot lot lot, I am not sure what would be the best way to store it to precess it with R (or maybe Python? - need to do some statistical work on it). Any suggestions?
You're not appending your generated urls to the url list, you are printing them:
print ("https://api.flickr.com/services/rest/?method=flickr.photos.search&format=json&api_key=5.b&nojsoncallback=1&page={}&per_page=250&bbox={},{},{},{}&accuracy=1&has_geo=1&extras=geo,tags,views,description".format(pages,long,lat,long1,lat1))
Should be:
urls.append("https://api.flickr.com/services/rest/?method=flickr.photos.search&format=json&api_key=5.b&nojsoncallback=1&page={}&per_page=250&bbox={},{},{},{}&accuracy=1&has_geo=1&extras=geo,tags,views,description".format(pages,long,lat,long1,lat1))
Then you can iterate over the urls as planned.
But you'll run into the error on the following line:
response = urllib.request.urlopen(urls)
Here you are feeding the whole set of urls into urlopen, where you should be passing in a single url from urls which you have named amounts like so:
response = urllib.request.urlopen(amounts)
I am trying to scrape rows off of over 1200 .htm files that are on my hard drive. On my computer they are here 'file:///home/phi/Data/NHL/pl07-08/PL020001.HTM'. These .htm files are sequential from *20001.htm until *21230.htm. My plan is to eventually toss my data in MySQL or SQLite via a spreadsheet app or just straight in if I can get a clean .csv file out of this process.
This is my first attempt at code (Python), scraping, and I just installed Ubuntu 9.04 on my crappy pentium IV. Needless to say I am newb and have some roadblocks.
How do I get mechanize to go through all the files in the directory in order. Can mechanize even do this? Can mechanize/Python/BeautifulSoup read a 'file:///' style url or is there another way to point it to /home/phi/Data/NHL/pl07-08/PL020001.HTM? Is it smart to do this in 100 or 250 file increments or just send all 1230?
I just need rows that start with this "<tr class="evenColor">" and end with this "</tr>". Ideally I only want the rows that contain "SHOT"|"MISS"|"GOAL" within them but I want the whole row (every column). Note that "GOAL" is in bold so do I have to specify this? There are 3 tables per htm file.
Also I would like the name of the parent file (pl020001.htm) to be included in the rows I scrape so I can id them in their own column in the final database. I don't even know where to begin for that. This is what I have so far:
#/usr/bin/python
from BeautifulSoup import BeautifulSoup
import re
from mechanize import Browser
mech = Browser()
url = "file:///home/phi/Data/NHL/pl07-08/PL020001.HTM"
##but how do I do multiple urls/files? PL02*.HTM?
page = mech.open(url)
html = page.read()
soup = BeautifulSoup(html)
##this confuses me and seems redundant
pl = open("input_file.html","r")
chances = open("chancesforsql.csv,"w")
table = soup.find("table", border=0)
for row in table.findAll 'tr class="evenColor"'
#should I do this instead of before?
outfile = open("shooting.csv", "w")
##how do I end it?
Should I be using IDLE or something like it? just Terminal in Ubuntu 9.04?
You won't need mechanize. Since I do not exactly know the HTML content, I'd try to see what matches, first. Like this:
import glob
from BeautifulSoup import BeautifulSoup
for filename in glob.glob('/home/phi/Data/*.htm'):
soup = BeautifulSoup(open(filename, "r").read()) # assuming some HTML
for a_tr in soup.findAll("tr", attrs={ "class" : "evenColor" }):
print a_tr
Then pick the stuff you want and write it to stdout with commas (and redirect it > to a file). Or write the csv via python.
MYYN's answer looks like a great start to me. One thing I'd point out that I've had luck with is:
import glob
for file_name in glob.glob('/home/phi/Data/*.htm'):
#read the file and then parse with BeautifulSoup
I've found both the os and glob imports to be really useful for running through files in a directory.
Also, once you're using a for loop in this way, you have the file_name which you can modify for use in the output file, so that the output filenames will match the input filenames.