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# -*- coding: utf-8 -*-
#### IMPORTS 1.0
import os
import re
import scraperwiki
import urllib2
from datetime import datetime
from bs4 import BeautifulSoup
#### FUNCTIONS 1.0
def validateFilename(filename):
filenameregex = '^[a-zA-Z0-9]+_[a-zA-Z0-9]+_[a-zA-Z0-9]+_[0-9][0-9][0-9][0-9]_[0-9QY][0-9]$'
dateregex = '[0-9][0-9][0-9][0-9]_[0-9QY][0-9]'
validName = (re.search(filenameregex, filename) != None)
found = re.search(dateregex, filename)
if not found:
return False
date = found.group(0)
now = datetime.now()
year, month = date[:4], date[5:7]
validYear = (2000 <= int(year) <= now.year)
if 'Q' in date:
validMonth = (month in ['Q0', 'Q1', 'Q2', 'Q3', 'Q4'])
elif 'Y' in date:
validMonth = (month in ['Y1'])
else:
try:
validMonth = datetime.strptime(date, "%Y_%m") < now
except:
return False
if all([validName, validYear, validMonth]):
return True
def validateURL(url):
try:
r = urllib2.urlopen(url)
count = 1
while r.getcode() == 500 and count < 4:
print ("Attempt {0} - Status code: {1}. Retrying.".format(count, r.status_code))
count += 1
r = urllib2.urlopen(url)
sourceFilename = r.headers.get('Content-Disposition')
if sourceFilename:
ext = os.path.splitext(sourceFilename)[1].replace('"', '').replace(';', '').replace(' ', '')
else:
ext = os.path.splitext(url)[1]
validURL = r.getcode() == 200
validFiletype = ext.lower() in ['.csv', '.xls', '.xlsx']
return validURL, validFiletype
except:
print ("Error validating URL.")
return False, False
def validate(filename, file_url):
validFilename = validateFilename(filename)
validURL, validFiletype = validateURL(file_url)
if not validFilename:
print filename, "*Error: Invalid filename*"
print file_url
return False
if not validURL:
print filename, "*Error: Invalid URL*"
print file_url
return False
if not validFiletype:
print filename, "*Error: Invalid filetype*"
print file_url
return False
return True
def convert_mth_strings ( mth_string ):
month_numbers = {'JAN': '01', 'FEB': '02', 'MAR':'03', 'APR':'04', 'MAY':'05', 'JUN':'06', 'JUL':'07', 'AUG':'08', 'SEP':'09','OCT':'10','NOV':'11','DEC':'12' }
for k, v in month_numbers.items():
mth_string = mth_string.replace(k, v)
return mth_string
#### VARIABLES 1.0
entity_id = "DFT004_DFT_gov"
url = "https://data.gov.uk/dataset/financial-transactions-data-dft"
errors = 0
data = []
#### READ HTML 1.0
html = urllib2.urlopen(url)
soup = BeautifulSoup(html, 'lxml')
#### SCRAPE DATA
blocks = soup.select('div.dataset-resource-text')
for block in blocks:
link = block.find_next('a').find_next('a')['href']
if '.csv' in link or '.xlsx' in link or '.xls' in link:
link_text = block.find('span', 'inner-cell').text.replace(' return', '').strip()
csvYr = link_text.split()[-1]
csvMth = link_text.split()[-2][:3]
if 'to 11th May 2010' in block.find('span','inner-cell').text.strip():
csvMth = 'Q0'
csvYr = '2010'
if 'April 2009 to March 2010' in block.find('span','inner-cell').text.strip():
csvMth = 'Y1'
csvYr = '2009'
if '12th' in csvYr:
csvMth = 'May'
csvYr = '2010'
csvMth = convert_mth_strings(csvMth.upper())
data.append([csvYr, csvMth, link])
#### STORE DATA 1.0
for row in data:
csvYr, csvMth, url = row
filename = entity_id + "_" + csvYr + "_" + csvMth
todays_date = str(datetime.now())
file_url = url.strip()
valid = validate(filename, file_url)
if valid == True:
scraperwiki.sqlite.save(unique_keys=['l'], data={"l": file_url, "f": filename, "d": todays_date })
print filename
else:
errors += 1
if errors > 0:
raise Exception("%d errors occurred during scrape." % errors)