def run(self):
delimiter = self.config.get('profiles_data', 'delimiter')
print(f"Scraper #{self._id}: Executing LinkedIn login...")
# Doing login on LinkedIn
linkedin_login(self.browser, self.config.get('linkedin', 'username'),
self.config.get('linkedin', 'password'))
start_time = time.time()
count = 0
for entry in self.entries:
count += 1
# Print statistics about ending time of the script
if count > 1:
time_left = ((time.time() - start_time) /
count) * (len(self.entries) - count + 1)
ending_in = time.strftime("%H:%M:%S", time.gmtime(time_left))
else:
ending_in = "Unknown time"
print(
f"Scraper #{self._id}: Scraping profile {count} / {len(self.entries)} - {ending_in} left"
)
try:
linkedin_url, known_graduation_date = self.parse_entry(
entry, delimiter)
scraping_result = self.scrap_profile(linkedin_url,
known_graduation_date)
self.results.append(scraping_result)
except CannotProceedScrapingException:
self.results.append(
ScrapingResult('TerminatedDueToHumanCheckError'))
self.interrupted = True
break
except:
with open("errlog.txt", "a") as errlog:
traceback.print_exc(file=errlog)
self.results.append(ScrapingResult('GenericError'))
# Closing the Chrome instance
self.browser.quit()
end_time = time.time()
elapsed_time = time.strftime('%H:%M:%S',
time.gmtime(end_time - start_time))
print(
f"Scraper #{self._id}: Parsed {count} / {len(self.entries)} profiles in {elapsed_time}"
)
def scrap_profile(profile_to_scrap, delimiter: str) -> ScrapingResult:
result = None
while result is None:
try:
result = get_profile_data(profile_to_scrap.split(delimiter))
except HumanCheckException:
linkedin_login(browser, config.username, config.password)
while browser.current_url != 'https://www.linkedin.com/feed/':
time.sleep(30)
print("Waiting for user to do human check...")
engine.say('Per favore esegui controllo umano')
engine.runAndWait()
return result
# Loading of configurations
config = ConfigParser()
config.read('config.ini')
if config.get('system', 'os') == 'linux':
display = Display(visible=0, size=(800, 800))
display.start()
headless_option = len(sys.argv) >= 2 and sys.argv[1] == 'HEADLESS'
# Creation of a new instance of Chrome
browser = webdriver.Chrome(executable_path=config.get('system', 'driver'), options=get_browser_options(headless_option, config))
# Doing login on LinkedIn
linkedin_login(browser, config.get('linkedin', 'username'), config.get('linkedin', 'password'))
message_to_user('Starting reading Linkedin profiles', config)
results = []
cont = 0
for query in open(config.get('profiles_data_by_name', 'input_file_name'), "r"):
cont += 1
print(f"Scraping {cont}")
query = query.split(config.get('profiles_data_by_name', 'delimiter'))
first_name = query[0]
last_name = query[1]
try:
def scrap_profile(self, profile_linkedin_url,
profile_known_graduation_date):
if not is_url_valid(profile_linkedin_url):
return ScrapingResult('BadFormattedLink')
# Scraping of the profile may fail due to human check forced by LinkedIn
try:
# Setting of the delay (seconds) between operations that need to be sure loading of page is ended
loading_pause_time = 2
loading_scroll_time = 1
# Opening of the profile page
self.browser.get(profile_linkedin_url)
if not str(self.browser.current_url).strip(
) == profile_linkedin_url.strip():
if self.browser.current_url == 'https://www.linkedin.com/in/unavailable/':
return ScrapingResult('ProfileUnavailable')
else:
raise HumanCheckException
# Scraping the Email Address from Contact Info (email)
# > click on 'Contact info' link on the page
self.browser.execute_script(
"(function(){try{for(i in document.getElementsByTagName('a')){let el = document.getElementsByTagName('a')[i]; "
"if(el.innerHTML.includes('Contact info')){el.click();}}}catch(e){}})()"
)
time.sleep(loading_pause_time)
# > gets email from the 'Contact info' popup
try:
email = self.browser.execute_script(
"return (function(){try{for (i in document.getElementsByClassName('pv-contact-info__contact-type')){ let "
"el = "
"document.getElementsByClassName('pv-contact-info__contact-type')[i]; if(el.className.includes("
"'ci-email')){ "
"return el.children[2].children[0].innerText; } }} catch(e){return '';}})()"
)
except:
pass
# Scraping the Phone from Contact Info (email)
try:
phone = self.browser.execute_script(
"return (function(){try{for (i in document.getElementsByClassName('pv-contact-info__contact-type')){ let "
"el = "
"document.getElementsByClassName('pv-contact-info__contact-type')[i]; if(el.className.includes("
"'ci-phone')){ "
"return el.children[2].children[0].innerText; } }} catch(e){return '';}})()"
)
except:
pass
# Scraping the Birthday from Contact Info (email)
try:
birthday = self.browser.execute_script(
"return (function(){try{for (i in document.getElementsByClassName('pv-contact-info__contact-type')){ let "
"el = "
"document.getElementsByClassName('pv-contact-info__contact-type')[i]; if(el.className.includes("
"'ci-birthday')){ "
"return el.children[2].children[0].innerText; } }} catch(e){return '';}})()"
)
except:
pass
# Scraping the Date Connected from Contact Info (email)
try:
connectedDate = self.browser.execute_script(
"return (function(){try{for (i in document.getElementsByClassName('pv-contact-info__contact-type')){ let "
"el = "
"document.getElementsByClassName('pv-contact-info__contact-type')[i]; if(el.className.includes("
"'ci-connected')){ "
"return el.children[2].children[0].innerText; } }} catch(e){return '';}})()"
)
self.browser.execute_script(
"document.getElementsByClassName('artdeco-modal__dismiss')[0].click()"
)
except:
pass
# Loading the entire page (LinkedIn loads content asynchronously based on your scrolling)
window_height = self.browser.execute_script(
"return window.innerHeight")
scrolls = 1
while scrolls * window_height < self.browser.execute_script(
"return document.body.offsetHeight"):
self.browser.execute_script(
f"window.scrollTo(0, {window_height * scrolls});")
time.sleep(loading_scroll_time)
scrolls += 1
try:
self.browser.execute_script(
"document.getElementsByClassName('pv-profile-section__see-more-inline')[0].click()"
)
time.sleep(loading_pause_time)
except:
pass
# Get all the job positions
try:
job_positions = self.browser.find_element_by_id(
'experience-section').find_elements_by_tag_name('li')
except:
job_positions = []
#Get all the educations
try:
educations = self.browser.find_element_by_id(
'education-section').find_elements_by_tag_name('li')
except:
educations = []
# Parsing of the page html structure
soup = BeautifulSoup(self.browser.page_source, 'lxml')
# Scraping the Name (using soup)
try:
name_div = soup.find('div', {'class': 'flex-1 mr5'})
name_loc = name_div.find_all('ul')
headline = name_div.find_all('h2')
headline = headline[0].get_text().strip()
profile_name = name_loc[0].find('li').get_text().strip()
locationNConnection = name_loc[1].find_all('li')
location = locationNConnection[0].get_text().strip()
try:
connection = locationNConnection[1].find('a').find(
'span').get_text().strip()
except:
connection = locationNConnection[1].find(
'span').get_text().strip()
except:
return ScrapingResult('ERROR IN SCRAPING NAME')
# Scraping the Desc (using soup)
try:
self.browser.execute_script(
"document.getElementsByClassName('lt-line-clamp__more')[0].click()"
)
time.sleep(loading_pause_time)
except:
pass
try:
if (self.browser.execute_script(
"return (els = document.getElementsByClassName('pv-oc')[0].getElementsByClassName('lt-line-clamp__line').length)"
)):
profile_desc = self.browser.execute_script(
"return (function(){els = document.getElementsByClassName('pv-oc')[0].getElementsByClassName('lt-line-clamp__line');results = [];for (var i=0; i < els.length; i++){results.push(els[i].innerText);}return results;})()"
)
else:
profile_desc = self.browser.execute_script(
"return (function(){els = document.getElementsByClassName('pv-oc')[0].getElementsByClassName('lt-line-clamp__raw-line');results = [];for (var i=0; i < els.length; i++){results.push(els[i].innerText);}return results;})()"
)
except:
profile_desc = []
# print(profile_desc)
# Parsing skills
try:
self.browser.execute_script(
"document.getElementsByClassName('pv-skills-section__additional-skills')[0].click()"
)
time.sleep(loading_pause_time)
except:
pass
try:
skills = self.browser.execute_script(
"return (function(){els = document.getElementsByClassName('pv-skill-category-entity');results = [];for (var i=0; i < els.length; i++){results.push(els[i].getElementsByClassName('pv-skill-category-entity__name-text')[0].innerText);}return results;})()"
)
except:
skills = []
education_list = []
# Parsing the job positions
if len(educations) > 0:
# Parse job positions to extract relative the data ranges
educations_data_ranges = []
x = 1
for education in educations:
try:
# Scraping of the last (hopefully current) Job
exp_section = soup.find('section',
{'id': 'education-section'})
exp_section = exp_section.find('ul')
div_tags = exp_section.contents[x].find('div')
a_tags = div_tags.find('a')
x += 1
# Scraping of the last Job - company_name, job_title
try:
education_name = a_tags.find(
'h3').get_text().strip()
except:
eudcation_name = None
try:
education_degree_name = a_tags.find_all(
'p')[0].get_text().strip()
except:
education_degree_name = None
try:
education_major = a_tags.find_all(
'p')[1].get_text().strip()
except:
education_major = None
try:
education_year = a_tags.find_all(
'p')[2].get_text().strip()
except:
education_year = None
# last_job_company_name = a_tags.find_all('span')[1].get_text().strip()
# last_job_title = exp_section.find('ul').find('li').find_all('span')[2].get_text().strip()
# spans = exp_section.find('ul').find('li').find_all('span')
#last_job_company_name = last_job_company_name.replace('Full-time', '').replace('Part-time', '').strip()
# Scraping of last Job - location
# last_job_location = Location()
# next_span_is_location = False
# for span in spans:
# if next_span_is_location:
# last_job_location.parse_string(span.get_text().strip())
# break
# if span.get_text().strip() == 'Location':
# next_span_is_location = True
# # Scraping of Industry related to last Job
# last_job_company_url = a_tags.get('href')
# if last_job_company_url not in self.industries_dict:
# try:
# self.browser.get('https://www.linkedin.com' + last_job_company_url)
# self.industries_dict[last_job_company_url] = self.browser.execute_script(
# "return document.getElementsByClassName("
# "'org-top-card-summary-info-list__info-item')["
# "0].innerText")
# except:
# self.industries_dict[last_job_company_url] = 'N/A'
# last_job_company_industry = self.industries_dict[last_job_company_url]
education_list.append(
Education(education_name=education_name,
degree_name=education_degree_name,
major=education_major,
year=education_year))
except:
pass
for x in range(3 - len(educations)):
education_list.append(
Education(education_name=None,
degree_name=None,
major=None,
year=None))
last_job = []
# Parsing the job positions
if len(job_positions) > 0:
# Parse job positions to extract relative the data ranges
job_positions_data_ranges = []
x = 1
for job_position in job_positions:
# Get the date range of the job position
try:
date_range_element = job_position.find_element_by_class_name(
'pv-entity__date-range')
date_range_spans = date_range_element.find_elements_by_tag_name(
'span')
date_range = date_range_spans[1].text
job_positions_data_ranges.append(date_range)
# Scraping of the last (hopefully current) Job
exp_section = soup.find('section',
{'id': 'experience-section'})
exp_section = exp_section.find('ul')
div_tags = exp_section.contents[x].find('div')
a_tags = div_tags.find('a')
x += 1
# Scraping of the last Job - company_name, job_title
try:
last_job_company_name = a_tags.find_all(
'p')[1].get_text().strip()
last_job_title = a_tags.find(
'h3').get_text().strip()
spans = a_tags.find_all('span')
except:
last_job_company_name = a_tags.find_all(
'span')[1].get_text().strip()
last_job_title = exp_section.find('ul').find(
'li').find_all('span')[2].get_text().strip()
spans = exp_section.find('ul').find('li').find_all(
'span')
last_job_company_name = last_job_company_name.replace(
'Full-time', '').replace('Part-time', '').strip()
# Scraping of last Job - location
last_job_location = Location()
next_span_is_location = False
for span in spans:
if next_span_is_location:
last_job_location.parse_string(
span.get_text().strip())
break
if span.get_text().strip() == 'Location':
next_span_is_location = True
# # Scraping of Industry related to last Job
# last_job_company_url = a_tags.get('href')
# if last_job_company_url not in self.industries_dict:
# try:
# self.browser.get('https://www.linkedin.com' + last_job_company_url)
# self.industries_dict[last_job_company_url] = self.browser.execute_script(
# "return document.getElementsByClassName("
# "'org-top-card-summary-info-list__info-item')["
# "0].innerText")
# except:
# self.industries_dict[last_job_company_url] = 'N/A'
# last_job_company_industry = self.industries_dict[last_job_company_url]
last_job.append(
Job(
position=last_job_title,
company=Company(
name=last_job_company_name,
#industry=last_job_company_industry
),
location=last_job_location))
except:
last_job.append(
Job(
position=None,
company=Company(
name=None,
#industry=last_job_company_industry
),
location=None))
for x in range(4 - len(job_positions)):
last_job.append(
Job(
position=None,
company=Company(name=None,
#industry=last_job_company_industry
),
location=None))
print(
"profile_name {} \n headline {} \n location {} \n connection {} \n profile_desc {} \n email {} \n phone {} \n birthday {} \n connectedDate {} \n skills {} \n last_job {} \n last_job {} \n last_job {} \n last_job {} \n education {} \n"
.format(profile_name, headline, location, connection,
profile_desc, email, phone, birthday,
connectedDate, skills, last_job[0], last_job[1],
last_job[2], last_job[3], education_list[0]))
return ScrapingResult(
Profile(
profile_name, headline, location, connection,
connectedDate, phone, birthday, profile_desc, email,
skills, last_job,
JobHistorySummary(profile_known_graduation_date,
job_positions_data_ranges),
education_list))
else:
return ScrapingResult(Profile(profile_name, email, skills))
except HumanCheckException:
if self.headless_option:
raise CannotProceedScrapingException
linkedin_logout(self.browser)
linkedin_login(self.browser,
self.config.get('linkedin', 'username'),
self.config.get('linkedin', 'password'))
while self.browser.current_url != 'https://www.linkedin.com/feed/':
message_to_user('Please execute manual check', self.config)
time.sleep(30)
return self.scrap_profile(profile_linkedin_url,
profile_known_graduation_date)
return summary
# Creating instance for voice feedbacks
engine = pyttsx3.init()
engine.say('Avvio lettura profili Linkedin')
engine.runAndWait()
# Loading of configurations
config: Configuration = load_configurations()
# Creation of a new instance of Chrome
browser = webdriver.Chrome(executable_path=config.driver_bin)
# Doing login on LinkedIn
linkedin_login(browser, config.username, config.password)
scraping_results = []
start_time = time.time()
industries_dict = {
} # Store all the industries scraped to speed up the scraping process
number_of_profiles = sum(1 for profile_data in open(config.input_file, "r"))
count = 1
for profile_data in open(config.input_file, "r"):
# Print statistics about ending time of the script
ending_in = time.strftime(
"%H:%M:%S",
time.gmtime(((time.time() - start_time) / count) *
def scrap_profile(self, profile_linkedin_url,
profile_known_graduation_date):
if not is_url_valid(profile_linkedin_url):
return ScrapingResult('BadFormattedLink')
# Scraping of the profile may fail due to human check forced by LinkedIn
try:
# Setting of the delay (seconds) between operations that need to be sure loading of page is ended
loading_pause_time = 2
loading_scroll_time = 1
# Opening of the profile page
self.browser.get(profile_linkedin_url)
if not str(self.browser.current_url).strip(
) == profile_linkedin_url.strip():
if self.browser.current_url == 'https://www.linkedin.com/in/unavailable/':
return ScrapingResult('ProfileUnavailable')
else:
raise HumanCheckException
# Scraping the Email Address from Contact Info (email)
# > click on 'Contact info' link on the page
self.browser.execute_script(
"(function(){try{for(i in document.getElementsByTagName('a')){let el = document.getElementsByTagName('a')[i]; "
"if(el.innerHTML.includes('Contact info')){el.click();}}}catch(e){}})()"
)
time.sleep(loading_pause_time)
# > gets email from the 'Contact info' popup
try:
email = self.browser.execute_script(
"return (function(){try{for (i in document.getElementsByClassName('pv-contact-info__contact-type')){ let "
"el = "
"document.getElementsByClassName('pv-contact-info__contact-type')[i]; if(el.className.includes("
"'ci-email')){ "
"return el.children[2].children[0].innerText; } }} catch(e){return '';}})()"
)
self.browser.execute_script(
"document.getElementsByClassName('artdeco-modal__dismiss')[0].click()"
)
except:
email = 'N/A'
# Loading the entire page (LinkedIn loads content asynchronously based on your scrolling)
window_height = self.browser.execute_script(
"return window.innerHeight")
scrolls = 1
while scrolls * window_height < self.browser.execute_script(
"return document.body.offsetHeight"):
self.browser.execute_script(
f"window.scrollTo(0, {window_height * scrolls});")
time.sleep(loading_scroll_time)
scrolls += 1
try:
self.browser.execute_script(
"document.getElementsByClassName('pv-profile-section__see-more-inline')[0].click()"
)
time.sleep(loading_pause_time)
except:
pass
# Get all the job positions
try:
job_positions = self.browser\
.find_element_by_id('experience-section')\
.find_elements_by_tag_name('li')
except NoSuchElementException:
print("job_positions is null")
job_positions = []
# Get all the education positions
try:
education_positions = self.browser\
.find_element_by_id('education-section')\
.find_elements_by_tag_name('li')
except NoSuchElementException:
print("job_positions is null")
education_positions = []
# Parsing of the page html structure
soup = BeautifulSoup(self.browser.page_source, 'lxml')
# Scraping the Name (using soup)
try:
name_div = soup.find('div', {'class': 'flex-1 mr5'})
name_loc = name_div.find_all('ul')
profile_name = name_loc[0].find('li').get_text().strip()
except:
return ScrapingResult('ERROR IN SCRAPING NAME')
# Parsing skills
try:
self.browser.execute_script(
"document.getElementsByClassName('pv-skills-section__additional-skills')[0].click()"
)
time.sleep(loading_pause_time)
except:
pass
try:
skills = self.browser.execute_script(
"return (function(){els = document.getElementsByClassName('pv-skill-category-entity');results = [];for (var i=0; i < els.length; i++){results.push(els[i].getElementsByClassName('pv-skill-category-entity__name-text')[0].innerText);}return results;})()"
)
except:
skills = []
# Parsing the job positions
if len(job_positions) > 0:
# Parse job positions to extract relative the data ranges
js = self.parsing_jobs(job_positions)
job_positions_data_ranges = js['job_positions_data_ranges']
Jobs_array = js['Jobs_array']
last_job = Jobs_array[0]
if len(education_positions) > 0:
eds = self.parsing_educations(education_positions)
return ScrapingResult(
Profile(
profile_name, email, skills, last_job,
JobHistorySummary(profile_known_graduation_date,
job_positions_data_ranges),
Jobs_array, eds))
else:
return ScrapingResult(
Profile(
profile_name, email, skills, last_job,
JobHistorySummary(profile_known_graduation_date,
job_positions_data_ranges),
Jobs_array))
else:
return ScrapingResult(Profile(profile_name, email, skills))
except HumanCheckException:
if self.headless_option:
raise CannotProceedScrapingException
linkedin_logout(self.browser)
linkedin_login(self.browser,
self.config.get('linkedin', 'username'),
self.config.get('linkedin', 'password'))
while self.browser.current_url != 'https://www.linkedin.com/feed/':
message_to_user('Please execute manual check', self.config)
time.sleep(30)
return self.scrap_profile(profile_linkedin_url,
profile_known_graduation_date)
import time
import xlsxwriter
from selenium import webdriver
from utils import linkedin_login, linkedin_logout, load_configurations
waiting_time_to_load_page = 2
waiting_time_to_load_results = 5
# Loading of configurations
username, password, driver_bin = load_configurations()
# Creation of a new instance of Chrome
browser = webdriver.Chrome(executable_path=driver_bin)
# Doing login on LinkedIn
linkedin_login(browser, username, password)
time.sleep(120)
results = []
for query in open("profiles_names.txt", "r"):
best_solution = ['N/A', '', '']
query = query.split(':::')
name = query[0]
graduation_date = query[1]
try:
# Clears the search box