Develop Reference

Save image/table from a webpage while scraping

I would need to scrape a image from this website: https://web.archive.org/web/
for example for stackoverflow, towardsdatascience.
URL
stackoverflow.com
towardsdatascience.com
I do not know how to include information on the table/image within
<div class="sparkline" style="width: 1225px;"><div id="wm-graph-anchor"><div id="wm-ipp-sparkline" title="Explore captures for this URL" style="height: 77px;"><canvas class="sparkline-canvas" width="1225" height="75" alt="sparklines"></canvas></div></div><div id="year-labels"><span class="sparkline-year-label">1996</span><span class="sparkline-year-label">1997</span><span class="sparkline-year-label">1998</span><span class="sparkline-year-label">1999</span><span class="sparkline-year-label">2000</span><span class="sparkline-year-label">2001</span><span class="sparkline-year-label">2002</span><span class="sparkline-year-label">2003</span><span class="sparkline-year-label">2004</span><span class="sparkline-year-label">2005</span><span class="sparkline-year-label">2006</span><span class="sparkline-year-label">2007</span><span class="sparkline-year-label">2008</span><span class="sparkline-year-label">2009</span><span class="sparkline-year-label">2010</span><span class="sparkline-year-label">2011</span><span class="sparkline-year-label">2012</span><span class="sparkline-year-label">2013</span><span class="sparkline-year-label">2014</span><span class="sparkline-year-label">2015</span><span class="sparkline-year-label">2016</span><span class="sparkline-year-label">2017</span><span class="sparkline-year-label">2018</span><span class="sparkline-year-label">2019</span><span class="sparkline-year-label selected-year">2020</span></div></div>
i.e. the image where the timeline is shown through years.
I would like to save per each website this image/table, if possible.
I tried to write some code, but it misses this part:
import json
import requests
def my_function(file):
urls = list(set(file.URL.tolist()))
df_url= pd.DataFrame(columns=['URL'])
df_url['URL']=urls
api_url = 'https://web.archive.org/__wb/search/metadata'
for url in df_url['URL']:
res = requests.get(api_url, params={'q': url})
# part to scrape the image
return
my_function(df)
Can you give me some input on how to get those images?

If you have each image URL in the for loop, you can download the images using python library urllib.request function urlretrive:
First import it at the beginning of the script using
import os
from urllib.parse import urlparse
import urllib.request
And then download them using
for url in df_url['URL']:
urllib.request.urlretrieve(url,os.path.basename(urlparse(url).path))
If you don't to save using URL basename, then don't make first 2 imports.

How to scrape data from JSON/Javascript of web page?

I'm new to Python, just get started with it today.
My system environment are Python 3.5 with some libraries on Windows10.
I want to extract football player data from site below as CSV file.
Problem: I can not extract data from soup.find_all('script')[17] to my expected CSV format. How to extract those data as I want ?
My code is shown as below.
from bs4 import BeautifulSoup
import re
from urllib.request import Request, urlopen
req = Request('http://www.futhead.com/squad-building-challenges/squads/343', headers={'User-Agent': 'Mozilla/5.0'})
webpage = urlopen(req).read()
soup = BeautifulSoup(webpage,'html.parser') #not sure if i need to use lxml
soup.find_all('script')[17] #My target data is in 17th
My expected output would be similar to this
position,slot_position,slug
ST,ST,paulo-henrique
LM,LM,mugdat-celik

As #josiah Swain said, it's not going to be pretty. For this sort of thing it's more recommended to use JS as it can understand what you have.
Saying that, python is awesome and here is you solution!
#Same imports as before
from bs4 import BeautifulSoup
import re
from urllib.request import Request, urlopen
#And one more
import json
# The code you had
req = Request('http://www.futhead.com/squad-building-challenges/squads/343',
headers={'User-Agent': 'Mozilla/5.0'})
webpage = urlopen(req).read()
soup = BeautifulSoup(webpage,'html.parser')
# Store the script
script = soup.find_all('script')[17]
# Extract the oneline that stores all that JSON
uncleanJson = [line for line in script.text.split('\n')
if line.lstrip().startswith('squad.register_players($.parseJSON') ][0]
# The easiest way to strip away all that yucky JS to get to the JSON
cleanJSON = uncleanJson.lstrip() \
.replace('squad.register_players($.parseJSON(\'', '') \
.replace('\'));','')
# Extract out that useful info
data = [ [p['position'],p['data']['slot_position'],p['data']['slug']]
for p in json.loads(cleanJSON)
if p['player'] is not None]
print('position,slot_position,slug')
for line in data:
print(','.join(line))
The result I get for copying and pasting this into python is:
position,slot_position,slug
ST,ST,paulo-henrique
LM,LM,mugdat-celik
CAM,CAM,soner-aydogdu
RM,RM,petar-grbic
GK,GK,fatih-ozturk
CDM,CDM,eray-ataseven
LB,LB,kadir-keles
CB,CB,caner-osmanpasa
CB,CB,mustafa-yumlu
RM,RM,ioan-adrian-hora
GK,GK,bora-kork
Edit: On reflection this is not the easiest code to read for a beginner. Here is a easier to read version
# ... All that previous code
script = soup.find_all('script')[17]
allScriptLines = script.text.split('\n')
uncleanJson = None
for line in allScriptLines:
# Remove left whitespace (makes it easier to parse)
cleaner_line = line.lstrip()
if cleaner_line.startswith('squad.register_players($.parseJSON'):
uncleanJson = cleaner_line
cleanJSON = uncleanJson.replace('squad.register_players($.parseJSON(\'', '').replace('\'));','')
print('position,slot_position,slug')
for player in json.loads(cleanJSON):
if player['player'] is not None:
print(player['position'],player['data']['slot_position'],player['data']['slug'])

So my understanding is that beautifulsoup is better for HTML parsing, but you are trying to parse javascript nested in the HTML.
So you have two options
Simply create a function that takes the result of soup.find_all('script')[17], loop and search the string manually for the data and extract it. You can even use ast.literal_eval(string_thats_really_a_dictionary) to make it even easier. This is may not be the best a approach but if you are new to python you might want to do it this just for practice.
Use the json library like in this example. or alternatively like this way. This is probably the better way to do.

Python - How to search for a zip file that resides in an iframe on https

Python - 2.7.5
Google Chrome
First off I am self taught coder and will accept any critique and/or suggestions to any of my posted codes below. This issue has been a joy to work through because I love challenging myself but I am afraid I have hit a brick wall and need some guidance. I will be as detailed as possible below to fully explain the overall picture of my script and then show where I am at with the actual issue that is explained in the title.
I am putting together a script that will go out and download data automatically, upzip, and export to a GDB. We serve a wide region of users and have a very large enterprise SDE setup containing large amount of public data that we have to go out and search and update for our end users. Most of our data is updated monthly by local government entities and we have to go out and search for the data manually, download, unzip, QAQC, etc. I am wanting to put a script a together that will automate the first part of this process by going out and downloading all my data for me and exporting to a local GDB, from there I can QAQC everything and upload to our SDE for our users to access.
The process has been pretty straight forward so far until I got to this issue I have before me. My script will search a webpage for specific keywords and find the relevant link and begin the download. For this post I will use two examples, one that works and one that is currently giving me issues. What works is my function for searching and downloading the Metro GIS dataset and below shows my current process for finding this. So far all http websites I have included will use the posted function below. Like Metro is being shown I plan on having a defined function for each group of data.
import requests, zipfile, StringIO, time, arcpy, urllib2, urlparse
from BeautifulSoup import BeautifulSoup
arcpy.env.overwriteOutput = True
workPath = -- #The output GDB
timestr = time.strftime("%Y%m%d")
gdbName = "GlobalSDEUpdate_" + timestr
gdbPath = workPath + "\\" + gdbName + ".gdb"
class global_DataFinder(object):
def __init__(self):
object.__init__(self)
self.gdbSetup()
self.metro()
def gdbSetup(self):
arcpy.CreateFileGDB_management(workPath, gdbName)
def fileDownload(self, key, url, dlPath, dsName):
page = urllib2.urlopen(url).read()
urlList = []
soup = BeautifulSoup(page)
soup.prettify()
for link in soup.findAll('a', href = True):
if not 'http://' in link['href']:
if urlparse.urljoin(url, link['href']) not in urlList:
zipDL = urlparse.urljoin(url, link['href'])
if zipDL.endswith(".zip"):
if key in zipDL:
urlList.append(zipDL)
for x in urlList:
print x
r = requests.get(x, stream=True)
z = zipfile.ZipFile(StringIO.StringIO(r.content))
z.extractall(dlPath)
arcpy.CreateFeatureDataset_management(gdbPath, dsName)
arcpy.env.workspace = dlPath
shpList = []
for shp in arcpy.ListFeatureClasses():
shpList.append(shp)
arcpy.FeatureClassToGeodatabase_conversion(shpList, (gdbPath + "\\" + dsName))
del shpList[:]
def metro(self):
key = "METRO_GIS_Data_Layers"
url = "http://www.ridemetro.org/Pages/NewsDownloads.aspx"
dlPath = -- *#Where my zipfiles output to*
dsName = "Metro"
self.fileDownload(key, url, dlPath, dsName)
global_DataFinder()
As you can see above this is the method I started with using Metro as my first testing point and this is currently working great. I was hoping all my sites going forward would like this but when I got to FEMA I ran into an issue.
The website National Flood Hazard Layer (NFHL) Status hosts floodplain data for many counties across the country is available for free to any who wish to use it. When arriving at the website you will see that you can search for the county you want, then the table queries out the search, then you can simply click and download the county you desire. When checking the source this is what I came across and noticed its in an iframe.
When accessing the iframe source link through Chrome and checking the png source url this is what you get - https://hazards.fema.gov/femaportal/NFHL/searchResult
Now here is where my problem lies, unlike http sites I have quickly learned that accessing a secured https site and scraping the page is different especially when its using javascript to show the table. I have spent hours searching through forums and tried different python packages like selenium, mechanize, requests, urllib, urllib2, and I seem to always hit a dead-end before I can securely establish a connection and parse the webpage and search for my counties zipfile. The code below shows the closest I have gotten and shows the error code I am getting.
(I always test in a separate script and then when it works I bring it over to my main script, so thats why this code snippet below is separated from my original)
import urllib2, httplib, socket, ssl
from BeautifulSoup import BeautifulSoup
url = "http://www.floodmaps.fema.gov/NFHL/status.shtml"
def test():
page = urllib2.urlopen(url).read()
urlList = []
soup = BeautifulSoup(page)
soup.prettify()
for link in soup.findAll("iframe", src=True):
r = urllib2.urlopen(link['src'])
iFrame = link['src']
print iFrame
def connect_patched(self):
"Connect to a host on a given (SSL) port."
sock = socket.create_connection((self.host, self.port),
self.timeout, self.source_address)
if self._tunnel_host:
self.sock = sock
self._tunnel()
self.sock = ssl.wrap_socket(sock, self.key_file, self.cert_file,
ssl_version=ssl.PROTOCOL_SSLv2)
httplib.HTTPSConnection.connect = connect_patched
test()
Error I get when running this test
urllib2.URLError: urlopen error [Errno 6] _ssl.c:504: TLS/SSL connection has been closed
I am hoping a more experienced coder can see what I have done and tell me if my current methods are the way to go and if so how to get past this final error and parse the datatable properly.
Working Edits with #crmackey
import requests
import os
import zipfile
from pyquery import PyQuery
from requests.packages.urllib3.exceptions import InsecureRequestWarning, InsecurePlatformWarning, SNIMissingWarning
import httplib
httplib.HTTPConnection._http_vsn = 10
httplib.HTTPConnection._http_vsn_str = 'HTTP/1.0'
# disable ssl warnings (we are not verifying SSL certificates at this time...future ehnancement?)
for warning in [SNIMissingWarning, InsecurePlatformWarning, InsecureRequestWarning]:
requests.packages.urllib3.disable_warnings(warning)
def download_zips(out_path):
url = 'http://www.floodmaps.fema.gov/NFHL/status.shtml'
download_prefix = 'https://hazards.fema.gov/femaportal/NFHL'
pq = PyQuery(requests.get(url, verify=False).content) #verify param important for SSL
src = pq.find('iframe').attr('src')
pq = PyQuery(requests.get(src, verify=False).content)
table = pq.find('table')
for a in table.find('a'):
href = a.attrib.get('href')
print href
url = '/'.join([download_prefix, href])
print url
r = requests.get(url, stream=True, verify=False)
out_zip = os.path.join(out_path, href.split('=')[-1])
with open(out_zip, 'wb') as f:
for chunk in r.iter_content(1024 *16): #grab 1KB at a time
if chunk:
f.write(chunk)
print 'downloaded zip: "{}"'.format(href.split('=')[-1])
out_path = r"C:\Users\barr\Desktop\Test"
download_zips(out_path)
All I added was the httplib and changed the HTTPConnection at the top. That allowed to me connect to the site using your script. Now here is the current problem. I am only getting 1 zip file in my out_path, and the zip file is empty. I checked the printed source in the debug window and its showing its trying to download the TERRITORY OF THE VIRGIN ISLAND zip file from the table so it looks like its trying but its not downloading anything. After it outputs that one empty zip file the script finishes and brings up no further error messages. I temporarily removed your lines that unzipped the file because they were returning an error since the folder was empty.

I was able to get the zip files downloaded by using the requests module and also opted for using PyQuery instead of Beautiful Soup. I think the issue you were facing has to do with the SSL cert validation, where the requests module will allow you to skip checking the certificate if you set the verify parameter to False.
The function below will download all the zip files and unzip them, from there, you can import the shapefiles into your geodatabase:
import requests
import os
import zipfile
from pyquery import PyQuery
from requests.packages.urllib3.exceptions import InsecureRequestWarning, InsecurePlatformWarning, SNIMissingWarning
# disable ssl warnings (we are not verifying SSL certificates at this time...future ehnancement?)
for warning in [SNIMissingWarning, InsecurePlatformWarning, InsecureRequestWarning]:
requests.packages.urllib3.disable_warnings(warning)
def download_zips(out_path):
url = 'http://www.floodmaps.fema.gov/NFHL/status.shtml'
download_prefix = 'https://hazards.fema.gov/femaportal/NFHL'
pq = PyQuery(requests.get(url, verify=False).content) #verify param important for SSL
src = pq.find('iframe').attr('src')
pq = PyQuery(requests.get(src, verify=False).content)
table = pq.find('table')
for a in table.find('a'):
href = a.attrib.get('href')
url = '/'.join([download_prefix, href])
r = requests.get(url, stream=True, verify=False)
out_zip = os.path.join(out_path, href.split('=')[-1])
with open(out_zip, 'wb') as f:
for chunk in r.iter_content(1024 *16): #grab 1KB at a time
if chunk:
f.write(chunk)
print 'downloaded zip: "{}"'.format(href.split('=')[-1])
# do more stuff like unzip?
unzipped = out_zip.split('.zip')[0]
with zipfile.Zipfile(out_zip, 'r') as f:
f.extractall(unzipped)

Problems crawling wordreference

I am trying to crawl wordreference, but I am not succeding.
The first problem I have encountered is, that a big part is loaded via JavaScript, but that shouldn't be much problem because I can see what I need in the source code.
So, for example, I want to extract for a given word, the first two meanings, so in this url: http://www.wordreference.com/es/translation.asp?tranword=crane I need to extract grulla and grúa.
This is my code:
import lxml.html as lh
import urllib2
url = 'http://www.wordreference.com/es/translation.asp?tranword=crane'
doc = lh.parse((urllib2.urlopen(url)))
trans = doc.xpath('//td[#class="ToWrd"]/text()')
for i in trans:
print i
The result is that I get an empty list.
I have tried to crawl it with scrapy too, no success. I am not sure what is going on, the only way I have been able to crawl it is using curl, but that is sloopy, I want to do it in an elegant way, with Python.
Thank you very much

It looks like you need a User-Agent header to be sent, see Changing user agent on urllib2.urlopen.
Also, just switching to requests would do the trick (it automatically sends the python-requests/version User Agent by default):
import lxml.html as lh
import requests
url = 'http://www.wordreference.com/es/translation.asp?tranword=crane'
response = requests.get("http://www.wordreference.com/es/translation.asp?tranword=crane")
doc = lh.fromstring(response.content)
trans = doc.xpath('//td[#class="ToWrd"]/text()')
for i in trans:
print(i)
Prints:
grulla
grúa
plataforma
...
grulla blanca
grulla trompetera

How to retrieve google URL from search query

So I'm trying to create a Python script that will take a search term or query, then search google for that term. It should then return 5 URL's from the result of the search term.
I spent many hours trying to get PyGoogle to work. But later found out Google no longer supports the SOAP API for search, nor do they provide new license keys. In a nutshell, PyGoogle is pretty much dead at this point.
So my question here is... What would be the most compact/simple way of doing this?
I would like to do this entirely in Python.
Thanks for any help

Use BeautifulSoup and requests to get the links from the google search results
import requests
from bs4 import BeautifulSoup
keyword = "Facebook" #enter your keyword here
search = "https://www.google.co.uk/search?sclient=psy-ab&client=ubuntu&hs=k5b&channel=fs&biw=1366&bih=648&noj=1&q=" + keyword
r = requests.get(search)
soup = BeautifulSoup(r.text, "html.parser")
container = soup.find('div',{'id':'search'})
url = container.find("cite").text
print(url)

What issues are you having with pygoogle? I know it is no longer supported, but I've utilized that project on many occasions and it would work fine for the menial task you have described.
Your question did make me curious though--so I went to Google and typed "python google search". Bam, found this repository. Installed with pip and within 5 minutes of browsing their documentation got what you asked:
import google
for url in google.search("red sox", num=5, stop=1):
print(url)
Maybe try a little harder next time, ok?

Here, link is the xgoogle library to do the same.
I tried similar to get top 10 links which also counts words in links we are targeting. I have added the code snippet for your reference :
import operator
import urllib
#This line will import GoogleSearch, SearchError class from xgoogle/search.py file
from xgoogle.search import GoogleSearch, SearchError
my_dict = {}
print "Enter the word to be searched : "
#read user input
yourword = raw_input()
try:
#This will perform google search on our keyword
gs = GoogleSearch(yourword)
gs.results_per_page = 80
#get google search result
results = gs.get_results()
source = ''
#loop through all result to get each link and it's contain
for res in results:
#print res.url.encode('utf8')
#this will give url
parsedurl = res.url.encode("utf8")
myurl = urllib.urlopen(parsedurl)
#above line will read url content, in below line we parse the content of that web page
source = myurl.read()
#This line will count occurrence of enterd keyword in our webpage
count = source.count(yourword)
#We store our result in dictionary data structure. For each url, we store it word occurent. Similar to array, this is dictionary
my_dict[parsedurl] = count
except SearchError, e:
print "Search failed: %s" % e
print my_dict
#sorted_x = sorted(my_dict, key=lambda x: x[1])
for key in sorted(my_dict, key=my_dict.get, reverse=True):
print(key,my_dict[key])