How could i get all the categories mentioned on each listing page of the same website "https://www.sfma.org.sg/member/category". for example, when i choose alcoholic beverage category on the above mentioned page, the listings mentioned on that page has the category information like this :-
Catergory: Alcoholic Beverage, Bottled Beverage, Spirit / Liquor / Hard Liquor, Wine, Distributor, Exporter, Importer, Supplier
how can i extract the categories mentioned here with in same variable.
The code i have written for this is :-
category = soup_2.find_all('a', attrs ={'class' :'clink'})
links = [links['href'] for links in category]
cat_name = [cat_name.text.strip() for cat_name in links]
but it is producing the below output which are all the links on the page & not the text with in the href:-
['http://www.sfma.org.sg/about/singapore-food-manufacturers-association',
'http://www.sfma.org.sg/about/council-members',
'http://www.sfma.org.sg/about/history-and-milestones',
'http://www.sfma.org.sg/membership/',
'http://www.sfma.org.sg/member/',
'http://www.sfma.org.sg/member/alphabet/',
'http://www.sfma.org.sg/member/category/',
'http://www.sfma.org.sg/resources/sme-portal',
'http://www.sfma.org.sg/resources/setting-up-food-establishments-in-singapore',
'http://www.sfma.org.sg/resources/import-export-requirements-and-procedures',
'http://www.sfma.org.sg/resources/labelling-guidelines',
'http://www.sfma.org.sg/resources/wsq-continuing-education-modular-programmes',
'http://www.sfma.org.sg/resources/holistic-industry-productivity-scorecard',
'http://www.sfma.org.sg/resources/p-max',
'http://www.sfma.org.sg/event/',
.....]
What i need is the below data for all the listings of all the categories on the base URL which is "https://www.sfma.org.sg/member/category/"
['Ang Leong Huat Pte Ltd',
'16 Tagore Lane
Singapore (787476)',
'Tel: +65 6749 9988',
'Fax: +65 6749 4321',
'Email: sales#alh.com.sg',
'Website: http://www.alh.com.sg/',
'Catergory: Alcoholic Beverage, Bottled Beverage, Spirit / Liquor / Hard Liquor, Wine, Distributor, Exporter, Importer, Supplier'
Please excuse if the question seems to be novice, i am just very new to python,
Thanks !!!
The following targets the two javascript objects housing mapping info about companies names, categories and the shown tags e.g. bakery product. More more detailed info on the use of regex and splitting item['category'] - see my SO answer here.
It handles unquoted keys with hjson library.
You end up with a dict whose keys are the company names (I use permalink version of name, over name, as this should definitely be unique), and whose values are a tuple with 2 items. The first item is the company page link; the second is a list of the given tags e.g. bakery product, alcoholic beverage). The logic is there for you to re-organise as desired.
import requests
from bs4 import BeautifulSoup as bs
import hjson
base = 'https://www.sfma.org.sg/member/info/'
p = re.compile(r'var tmObject = (.*?);')
p1 = re.compile(r'var ddObject = (.*?);')
r = requests.get('https://www.sfma.org.sg/member/category/manufacturer')
data = hjson.loads(p.findall(r.text)[0])
lookup_data = hjson.loads(p1.findall(r.text)[0])
name_dict = {item['id']:item['name'] for item in lookup_data['category']}
companies = {}
for item in data['tmember']:
companies[item['permalink']] = (base + item['permalink'], [name_dict[i] for i in item['category'].split(',')])
print(companies)
Updating for your additional request at end (Address info etc):
I then loop companies dict visiting each company url in tuple item 1 of value for current dict key; extract the required info into a dict, which I add the category info to, then update the current key:value with the dictionary just created.
import requests
from bs4 import BeautifulSoup as bs
import hjson
base = 'https://www.sfma.org.sg/member/info/'
p = re.compile(r'var tmObject = (.*?);')
p1 = re.compile(r'var ddObject = (.*?);')
r = requests.get('https://www.sfma.org.sg/member/category/manufacturer')
data = hjson.loads(p.findall(r.text)[0])
lookup_data = hjson.loads(p1.findall(r.text)[0])
name_dict = {item['id']:item['name'] for item in lookup_data['category']}
companies = {}
for item in data['tmember']:
companies[item['permalink']] = (base + item['permalink'], [name_dict[i] for i in item['category'].split(',')])
with requests.Session() as s:
for k,v in companies.items():
r = s.get(v[0])
soup = bs(r.content, 'lxml')
tel = soup.select_one('.w3-text-sfma ~ p:contains(Tel)')
fax = soup.select_one('.w3-text-sfma ~ p:contains(Fax)')
email = soup.select_one('.w3-text-sfma ~ p:contains(Email)')
website = soup.select_one('.w3-text-sfma ~ p:contains(Website)')
if tel is None:
tel = 'N/A'
else:
tel = tel.text.replace('Tel: ','')
if fax is None:
fax = 'N/A'
else:
fax = fax.text.replace('Fax: ','')
if email is None:
email = 'N/A'
else:
email = email.text.replace('Email: ','')
if website is None:
website = 'N/A'
else:
website = website.text.replace('Website: ','')
info = {
# 'Address' : ' '.join([i.text for i in soup.select('.w3-text-sfma ~ p:not(p:nth-child(n+4) ~ p)')])
'Address' : ' '.join([i.text for i in soup.select('.w3-text-sfma ~ p:nth-child(-n+4)')])
, 'Tel' : tel
, 'Fax': fax
, 'Email': email
,'Website' : website
, 'Categories': v[1]
}
companies[k] = info
Example entry in companies dict:
Related
I am trying to extract the Name, License No., Date Of Issue and Validity from an Image I processed using Pytesseract. I am quite a lot confused with regex but still went through few documentations and codes over the web.
I got till here:
import pytesseract
import cv2
import re
import cv2
from PIL import Image
import numpy as np
import datetime
from dateutil.relativedelta import relativedelta
def driver_license(filename):
"""
This function will handle the core OCR processing of images.
"""
i = cv2.imread(filename)
newdata=pytesseract.image_to_osd(i)
angle = re.search('(?<=Rotate: )\d+', newdata).group(0)
angle = int(angle)
i = Image.open(filename)
if angle != 0:
#with Image.open("ro2.jpg") as i:
rot_angle = 360 - angle
i = i.rotate(rot_angle, expand="True")
i.save(filename)
i = cv2.imread(filename)
# Convert to gray
i = cv2.cvtColor(i, cv2.COLOR_BGR2GRAY)
# Apply dilation and erosion to remove some noise
kernel = np.ones((1, 1), np.uint8)
i = cv2.dilate(i, kernel, iterations=1)
i = cv2.erode(i, kernel, iterations=1)
txt = pytesseract.image_to_string(i)
print(txt)
text = []
data = {
'firstName': None,
'lastName': None,
'age': None,
'documentNumber': None
}
c = 0
print(txt)
#Splitting lines
lines = txt.split('\n')
for lin in lines:
c = c + 1
s = lin.strip()
s = s.replace('\n','')
if s:
s = s.rstrip()
s = s.lstrip()
text.append(s)
try:
if re.match(r".*Name|.*name|.*NAME", s):
name = re.sub('[^a-zA-Z]+', ' ', s)
name = name.replace('Name', '')
name = name.replace('name', '')
name = name.replace('NAME', '')
name = name.replace(':', '')
name = name.rstrip()
name = name.lstrip()
nmlt = name.split(" ")
data['firstName'] = " ".join(nmlt[:len(nmlt)-1])
data['lastName'] = nmlt[-1]
if re.search(r"[a-zA-Z][a-zA-Z]-\d{13}", s):
data['documentNumber'] = re.search(r'[a-zA-Z][a-zA-Z]-\d{13}', s)
data['documentNumber'] = data['documentNumber'].group().replace('-', '')
if not data['firstName']:
name = lines[c]
name = re.sub('[^a-zA-Z]+', ' ', name)
name = name.rstrip()
name = name.lstrip()
nmlt = name.split(" ")
data['firstName'] = " ".join(nmlt[:len(nmlt)-1])
data['lastName'] = nmlt[-1]
if re.search(r"[a-zA-Z][a-zA-Z]\d{2} \d{11}", s):
data['documentNumber'] = re.search(r'[a-zA-Z][a-zA-Z]\d{2} \d{11}', s)
data['documentNumber'] = data['documentNumber'].group().replace(' ', '')
if not data['firstName']:
name = lines[c]
name = re.sub('[^a-zA-Z]+', ' ', name)
name = name.rstrip()
name = name.lstrip()
nmlt = name.split(" ")
data['firstName'] = " ".join(nmlt[:len(nmlt)-1])
data['lastName'] = nmlt[-1]
if re.match(r".*DOB|.*dob|.*Dob", s):
yob = re.sub('[^0-9]+', ' ', s)
yob = re.search(r'\d\d\d\d', yob)
data['age'] = datetime.datetime.now().year - int(yob.group())
except:
pass
print(data)
I need to extract the Validity and Issue Date as well. But not getting anywhere near it. Also, I have seen using regex shortens the code like a lot so is there any better optimal way for it?
My input data is a string somewhat like this:
Transport Department Government of NCT of Delhi
Licence to Drive Vehicles Throughout India
Licence No. : DL-0820100052000 (P) R
N : PARMINDER PAL SINGH GILL
: SHRI DARSHAN SINGH GILL
DOB: 10/05/1966 BG: U
Address :
104 SHARDA APPTT WEST ENCLAVE
PITAMPURA DELHI 110034
Auth to Drive Date of Issue
M.CYL. 24/02/2010
LMV-NT 24/02/2010
(Holder's Sig natu re)
Issue Date : 20/05/2016
Validity(NT) : 19/05/2021 : c
Validity(T) : NA Issuing Authority
InvCarrNo : NA NWZ-I, WAZIRPUR
Or like this:
in
Transport Department Government of NCT of Delhi
Licence to Drive Vehicles Throughout India
2
Licence No. : DL-0320170595326 () WN
Name : AZAZ AHAMADSIDDIQUIE
s/w/D : SALAHUDDIN ALI
____... DOB: 26/12/1992 BG: O+
\ \ Address:
—.~J ~—; ROO NO-25 AMK BOYS HOSTEL, J.
— NAGAR, DELHI 110025
Auth to Drive Date of Issue
M.CYL. 12/12/2017
4 wt 4
Iseue Date: 12/12/2017 a
falidity(NT) < 2037
Validity(T) +: NA /
Inv CarrNo : NA te sntian sana
Note: In the second example you wouldn't get the validity, will optimise the OCR for later. Any proper guide which can help me with regex which is a bit simpler would be good.
You can use this pattern: (?<=KEY\s*:\s*)\b[^\n]+ and replace KEY with one of the issues of the date, License No. and others.
Also for this pattern, you need to use regex library.
Code:
import regex
text1 = """
Transport Department Government of NCT of Delhi
Licence to Drive Vehicles Throughout India
Licence No. : DL-0820100052000 (P) R
N : PARMINDER PAL SINGH GILL
: SHRI DARSHAN SINGH GILL
DOB: 10/05/1966 BG: U
Address :
104 SHARDA APPTT WEST ENCLAVE
PITAMPURA DELHI 110034
Auth to Drive Date of Issue
M.CYL. 24/02/2010
LMV-NT 24/02/2010
(Holder's Sig natu re)
Issue Date : 20/05/2016
Validity(NT) : 19/05/2021 : c
Validity(T) : NA Issuing Authority
InvCarrNo : NA NWZ-I, WAZIRPUR
"""
for key in ('Issue Date', 'Licence No\.', 'N', 'Validity\(NT\)'):
print(regex.findall(fr"(?<={key}\s*:\s*)\b[^\n]+", text1, regex.IGNORECASE))
Output:
['20/05/2016']
['DL-0820100052000 (P) R']
['PARMINDER PAL SINGH GILL']
['19/05/2021 : c']
You can also use re with a single regex based on alternation that will capture your keys and values:
import re
text = "Transport Department Government of NCT of Delhi\nLicence to Drive Vehicles Throughout India\n\nLicence No. : DL-0820100052000 (P) R\nN : PARMINDER PAL SINGH GILL\n\n: SHRI DARSHAN SINGH GILL\n\nDOB: 10/05/1966 BG: U\nAddress :\n\n104 SHARDA APPTT WEST ENCLAVE\nPITAMPURA DELHI 110034\n\n\n\nAuth to Drive Date of Issue\nM.CYL. 24/02/2010\nLMV-NT 24/02/2010\n\n(Holder's Sig natu re)\n\nIssue Date : 20/05/2016\nValidity(NT) : 19/05/2021 : c\nValidity(T) : NA Issuing Authority\nInvCarrNo : NA NWZ-I, WAZIRPUR"
search_phrases = ['Issue Date', 'Licence No.', 'N', 'Validity(NT)']
reg = r"\b({})\s*:\W*(.+)".format( "|".join(sorted(map(re.escape, search_phrases), key=len, reverse=True)) )
print(re.findall(reg, text, re.IGNORECASE))
Output of this short online Python demo:
[('Licence No.', 'DL-0820100052000 (P) R'), ('N', 'PARMINDER PAL SINGH GILL'), ('Issue Date', '20/05/2016'), ('Validity(NT)', '19/05/2021 : c')]
The regex is
\b(Validity\(NT\)|Licence\ No\.|Issue\ Date|N)\s*:\W*(.+)
See its online demo.
Details:
map(re.escape, search_phrases) - escapes all special chars in your search phrases to be used as literal texts in a regex (else, . will match any chars, ? won't match a ? char, etc.)
sorted(..., key=len, reverse=True) - sorts the search phrases by length in descending order (to get longer matches first)
"|".join(...) - creates an alternation pattern, a|b|c|...
r"\b({})\s*:\W*(.+)".format( ... ) - creates the final regex.
Regex details
\b - a word boundary (NOTE: replace with (?m)^ if your matches occur at the beginning of a line)
(Validity\(NT\)|Licence\ No\.|Issue\ Date|N) - Group 1: one of the search phrases
\s* - zero or more whitespaces
: - a colon
\W* - zero or more non-word chars
(.+) - (capturing) Group 2: one or more chars other than line break chars, as many as possible.
I'm doing a web scraping data university research project. I started working on a ready GitHub project, but this project does not retrieve all the data.
The project works like this:
Search Google using keywords: example: (accountant 'email me at' Google)
Extract a snippet.
Retrieve data from this snippet.
The issue is:
The snippets extracted are like this: " ... marketing division in 2009. For more information on career opportunities with our company, email me: vicki#productivedentist.com. Neighborhood Smiles, LLC ..."
The snippet does not show all, the "..." hides information like role, location... How can I retrieve all the information with the script?
from googleapiclient.discovery import build #For using Google Custom Search Engine API
import datetime as dt #Importing system date for the naming of the output file.
import sys
from xlwt import Workbook #For working on xls file.
import re #For email search using regex.
if __name__ == '__main__':
# Create an output file name in the format "srch_res_yyyyMMdd_hhmmss.xls in output folder"
now_sfx = dt.datetime.now().strftime('%Y%m%d_%H%M%S')
output_dir = './output/'
output_fname = output_dir + 'srch_res_' + now_sfx + '.xls'
search_term = sys.argv[1]
num_requests = int(sys.argv[2])
my_api_key = "replace_with_you_api_key" #Read readme.md to know how to get you api key.
my_cse_id = "011658049436509675749:gkuaxghjf5u" #Google CSE which searches possible LinkedIn profile according to query.
service = build("customsearch", "v1", developerKey=my_api_key)
wb=Workbook()
sheet1 = wb.add_sheet(search_term[0:15])
wb.save(output_fname)
sheet1.write(0,0,'Name')
sheet1.write(0,1,'Profile Link')
sheet1.write(0,2,'Snippet')
sheet1.write(0,3,'Present Organisation')
sheet1.write(0,4,'Location')
sheet1.write(0,5,'Role')
sheet1.write(0,6,'Email')
sheet1.col(0).width = 256 * 20
sheet1.col(1).width = 256 * 50
sheet1.col(2).width = 256 * 100
sheet1.col(3).width = 256 * 20
sheet1.col(4).width = 256 * 20
sheet1.col(5).width = 256 * 50
sheet1.col(6).width = 256 * 50
wb.save(output_fname)
row = 1 #To insert the data in the next row.
#Function to perform google search.
def google_search(search_term, cse_id, start_val, **kwargs):
res = service.cse().list(q=search_term, cx=cse_id, start=start_val, **kwargs).execute()
return res
for i in range(0, num_requests):
# This is the offset from the beginning to start getting the results from
start_val = 1 + (i * 10)
# Make an HTTP request object
results = google_search(search_term,
my_cse_id,
start_val,
num=10 #num value can be 1 to 10. It will give the no. of results.
)
for profile in range (0, 10):
snippet = results['items'][profile]['snippet']
myList = [item for item in snippet.split('\n')]
newSnippet = ' '.join(myList)
contain = re.search(r'[\w\.-]+#[\w\.-]+', newSnippet)
if contain is not None:
title = results['items'][profile]['title']
link = results['items'][profile]['link']
org = "-NA-"
location = "-NA-"
role = "-NA-"
if 'person' in results['items'][profile]['pagemap']:
if 'org' in results['items'][profile]['pagemap']['person'][0]:
org = results['items'][profile]['pagemap']['person'][0]['org']
if 'location' in results['items'][profile]['pagemap']['person'][0]:
location = results['items'][profile]['pagemap']['person'][0]['location']
if 'role' in results['items'][profile]['pagemap']['person'][0]:
role = results['items'][profile]['pagemap']['person'][0]['role']
print(title[:-23])
sheet1.write(row,0,title[:-23])
sheet1.write(row,1,link)
sheet1.write(row,2,newSnippet)
sheet1.write(row,3,org)
sheet1.write(row,4,location)
sheet1.write(row,5,role)
sheet1.write(row,6,contain[0])
print('Wrote {} search result(s)...'.format(row))
wb.save(output_fname)
row = row + 1
print('Output file "{}" written.'.format(output_fname))
content = driver.find_element_by_class_name('topics-sec-block')
container = content.find_elements_by_xpath('//div[#class="col-sm-7 topics-sec-item-cont"]')
the code is below:
for i in range(0, 40):
title = []
url = []
heading=container[i].find_element_by_xpath('//div[#class="col-sm-7 topics-sec-item-cont"]/a/h2').text
link = container[i].find_element_by_xpath('//div[#class="col-sm-7 topics-sec-item-cont"]/a')
title.append(heading)
url.append(link.get_attribute('href'))
print(title)
print(url)
it is giving me the 40 number of lines but all lines have same title and url as (some of them is given below):
['Stuck in Mexico: Central American asylum seekers in limbo']
['https://www.aljazeera.com/news/2020/03/stuck-mexico-central-american-asylum-seekers-limbo-200305103910955.html']
['Stuck in Mexico: Central American asylum seekers in limbo']
['https://www.aljazeera.com/news/2020/03/stuck-mexico-central-american-asylum-seekers-limbo-200305103910955.html']
I read through the bs4 documentation but I wasnt able to find a means to extract just the names of the speakers and their corporate titles from the HTML below (e.g. name = Jonathan Tan, title = Managing Director). Can anyone help me with this?
Also, while I have learned some basics, what's the best way to improve my ability to select and extract information from HTML?
#generate a list of useful urls
url_list = []
url = "http://www.fccsingapore.com/events/upcoming-events"
webpage_response = requests.get(url)
webpage = webpage_response.content
soup = BeautifulSoup(webpage, "html.parser")
all_href = soup.find_all("a")
for link in all_href:
if "http://www.fccsingapore.com/events" in link.get("href"):
url_list.append(link.get("href"))
counter = 0
for i in url_list:
counter += 1
print("The program has " + str(counter) + " events to output.")
#extract useful information from each link
for link in url_list[:1]:
webpage_response = requests.get(link)
event = BeautifulSoup(webpage_response.content, "html.parser")
title = event.find("h1").get_text()
date_and_time = event.find("div", attrs={"class":"field field-name-event-date-formated field-type-ds field-label-above"})
date_time = date_and_time.find("div", attrs={"class":"field-item even"})
event_date = date_time.text[:11]
event_time = date_time.text[12:]
address_details = event.find("div", attrs={"class":"field field-name-field-address field-type-text-long field-label-above"})
address = address_details.find("div", attrs={"field-item even"}).get_text()
reg_details = event.find("div", attrs={"class":"field field-name-event-reg-date-format field-type-ds field-label-above"})
registration = reg_details.find("div", attrs={"class":"field-item even"}).get_text()
reg_start = registration[:11]
reg_end = registration[13:]
for detail in event.find_all("ul"):
details =detail.find("li")
print(details)
<li class="first odd sf-item-1 sf-depth-2 sf-no-children" id="menu-1302-1"><a class="sf-depth-2" href="/hr/about" title="">About HR Services</a></li>
<li class="first odd sf-item-1 sf-depth-2 sf-no-children" id="menu-3617-1"><a class="sf-depth-2" href="/publications/news" title="">Latest News</a></li>
<li class="first odd sf-item-1 sf-depth-2 sf-no-children" id="menu-791-1"><a class="sf-depth-2" href="/about-us/fccs-at-a-glance" title="">French Chamber at a Glance</a></li>
<li>iCalendar</li>
<li>Jonathan Tan, Managing Director, Singapore at UnaBiz </li>
<li>Wandrille Doucerain, CMO UnaBiz & Head of IoT Asia at ENGIE</li>
I am trying to create a bar graph in pygal that uses the api for hacker news and charts the most active news based on comments. I posted my code below, but I cannot figure out why my graph keep saying "No data"??? Any suggestions? Thanks!
import requests
import pygal
from pygal.style import LightColorizedStyle as LCS, LightenStyle as LS
from operator import itemgetter
# Make an API call, and store the response.
url = 'https://hacker-news.firebaseio.com/v0/topstories.json'
r = requests.get(url)
print("Status code:", r.status_code)
# Process information about each submission.
submission_ids = r.json()
submission_dicts = []
for submission_id in submission_ids[:30]:
# Make a separate API call for each submission.
url = ('https://hacker-news.firebaseio.com/v0/item/' +
str(submission_id) + '.json')
submission_r = requests.get(url)
print(submission_r.status_code)
response_dict = submission_r.json()
submission_dict = {
'comments': int(response_dict.get('descendants', 0)),
'title': response_dict['title'],
'link': 'http://news.ycombinator.com/item?id=' + str(submission_id),
}
submission_dicts.append(submission_dict)
# Visualization
my_style = LS('#336699', base_style=LCS)
my_config = pygal.Config()
my_config.show_legend = False
my_config.title_font_size = 24
my_config.label_font_size = 14
my_config.major_label_font_size = 18
my_config.show_y_guides = False
my_config.width = 1000
chart = pygal.Bar(my_config, style=my_style)
chart.title = 'Most Active News on Hacker News'
chart.add('', submission_dicts)
chart.render_to_file('hn_submissons_repos.svg')
The values in the array passed to the add function need to be either numbers or dicts that contain the key value (or a mixture of the two). The simplest solution would be to change the keys used when creating submission_dict:
submission_dict = {
'value': int(response_dict.get('descendants', 0)),
'label': response_dict['title'],
'xlink': 'http://news.ycombinator.com/item?id=' + str(submission_id),
}
Notice that link has become xlink, this is one of the optional parameters that are defined in the Value Configuration section of the pygal docs.