Automatically Get Top 10 Jobs from LinkedIn Using Python

from clicknium import clicknium as cc, locator

# Create a browser instance with
# "cc.chrome", for edge browser using "cc.edge"
# Open browser with specified url and
# get browser tab For default, it will
# wait the page load completely. You do
# not need to add extra time.sleep()
_tab = cc.chrome.open("https://www.linkedin.com/", is_wait_complete=True)

# Find input box for username
# Fill in with the key value 'linkedin_login_name'
# in setting.json
_tab.find_element(locator.chrome.linkedin.login.login_email).set_text(
    Setting.login_name)

# Find input box for password
# Fill in with the key value 'linkedin_login_password'
# in setting.json
_tab.find_element(locator.chrome.linkedin.login.login_password).set_text(
    Setting.login_password)

# Find submit button, and click it to login
_tab.find_element(locator.chrome.linkedin.login.signin).click()

# Wait skip add phone button appears in 5 seconds,
# if it exists, click the 'skip' button
_tab.wait_appear(locator.chrome.linkedin.login.skip_add_phone,
                 wait_timeout=5).click()

# Wait the page load completely
# after submitting login information
# Find job channel and click it
# to switch to job channel
_tab.wait_appear(locator.chrome.linkedin.job.jobs_channel,
                 wait_timeout=5).click()

# Wait job search keyword input
# box exists in 10 seconds
# If exists fill in with the key
# value 'linkedin_search_job_key'
# in setting.json
_tab.wait_appear(locator.chrome.linkedin.job.job_search_key,
                 wait_timeout=10).set_text(Setting.search_job_key)

# Find job search location input box
# Fill in with the key value
# 'linkedin_search_job_location' in setting.json
_tab.find_element(locator.chrome.linkedin.job.job_search_location).set_text(
    Setting.search_job_location)

# Find the search button, and click
# it to search
_tab.find_element(locator.chrome.linkedin.job.job_search).click()

# Here we set range(1,11) to get top
# 10 jobs, it can be set with any value
for i in range(1, 11):

    # Wait the job item appears in 5 second,
    # and get the element with index value
    ele = _tab.wait_appear(locator.chrome.linkedin.jobitem.job_listitem, {
                           "index": i}, wait_timeout=5)

# Initial job item search dict
details = {}

# Click job item
ele.click()

# Wait job item's title appears in 5 seconds
job_title_ele = _tab.wait_appear(
    locator.chrome.linkedin.jobitem.job_title, wait_timeout=5)

# If job item's title exists, get the title
# string and save into result object 'details'
if job_title_ele:
details["Job Title"] = job_title_ele.get_text().strip()

# Wait job item's company name appears in 5 seconds
job_company_ele = _tab.wait_appear(
    locator.chrome.linkedin.jobitem.job_company, wait_timeout=2)

# If job item's company name exists, get the company
# name string and save into result object 'details'
if job_company_ele:
    details["Company Name"] = job_company_ele.get_text().strip()

# Wait job item's company scale appears in 5 seconds
company_size_ele = _tab.wait_appear(
    locator.chrome.linkedin.jobitem.company_size, wait_timeout=2)

# If job item's company scale exists, get the
# company scale string and save into result
# object 'details'
if company_size_ele:
    scale = company_size_ele.get_text().strip(
    ) if "employees" in company_size_ele.get_text() else ""
    details["Company Size"] = scale

# Wait job item's post date appears in 5 seconds  
job_post_date_ele = _tab.wait_appear(locator.chrome.linkedin.jobitem.job_post_date, 
                                     wait_timeout = 2)

# If job item's post date exists, get 
# the post date string and save into 
# result object 'details'
if job_post_date_ele:
    post_date = job_post_date_ele.get_text().strip() \
    if "ago" in job_post_date_ele.get_text() else ""
    details["Post Date"] = post_date
            
# Wait job item's type appears in 5 seconds  
job_type_ele = _tab.wait_appear(locator.chrome.linkedin.jobitem.job_type,
                                wait_timeout = 2)

# If job item's type exists, get the type string
# and save into result object 'details'
if job_type_ele:
    details["Job Type"] = job_type_ele.get_text().strip()

# Library for win32 clipboard api
import win32clipboard

# Get clipboard data
def get_clipboard_data():
    try:
      
        # Call open clipboard api
        win32clipboard.OpenClipboard()

        # Call get clipboard data api, and return the data
        data = win32clipboard.GetClipboardData()
        return data
    except:
      
        # If it got exception, return empty string
        return ""
    finally:
      
        # Call close clipboard api
        win32clipboard.CloseClipboard()

# Wait job item's share button appears
# in 5 seconds
job_share_btn_ele = _tab.wait_appear(
    locator.chrome.linkedin.jobitem.share_button, wait_timeout=2)

# If job item's share button exists, click
# the share button
if job_share_btn_ele:
    job_share_btn_ele.click()

    # Wait the copy link button appears in 5 seconds
    copy_link = _tab.wait_appear(
        locator.chrome.linkedin.jobitem.copy_link, wait_timeout=2)
    
    # If the copy link exists, click the copy
    # link to set clipboard data
    if copy_link:
        copy_link.click()

        # Sleep 0.2 second to wait the clipboard 
        # in ready state
        sleep(0.2)

        # Get the job link string and save into 
        # result object 'details'
        details["Job Link"] = get_clipboard_data()

# Library for csv operations api
import csv

# Save the list of dicts info csv file
def list_dict_to_csv(dicts, filename="test.csv"):

    # Open csv file and get file object
    with open(filename, 'w', newline='') as output_file:
      
        # Get csv header with the dicts keys
        keys = dicts[0].keys()

        # Initial DictWriter object
        dict_writer = csv.DictWriter(output_file, keys)

        # Write header into csv
        dict_writer.writeheader()

        # Write row datas into csv
        dict_writer.writerows(dicts)

# Library for web automation apis
# Locator used for selector reference
from clicknium import clicknium as cc, locator

# Library for delay function
from time import sleep

# Library for save dict list data into csv file
from csvutils import list_dict_to_csv

# Library for clear clipboard and get clipboard data
from clipboard import get_clipboard_data, clear_clipboard_data

# Library for get setting in 'setting.json' file
from setting import Setting

# Login to LinkedIn page
# Find input box for username and password,
# and fill in with the value in setting.json
# Find submit button, and click it to login
# Wait 'skip add phone' button if it needs,
# and click the 'skip' button
def login():
  
    # Find input box for username
    # Fill in with the key value
    # 'linkedin_login_name' in setting.json
    _tab.find_element(locator.chrome.linkedin.login.login_email).set_text(
        Setting.login_name)

    # Find input box for password
    # Fill in with the key value
    # 'linkedin_login_password' in setting.json
    _tab.find_element(locator.chrome.linkedin.login.login_password).set_text(
        Setting.login_password)

    # Find submit button, and click it to login
    _tab.find_element(locator.chrome.linkedin.login.signin).click()

    # Wait skip add phone button appears in 5
    # seconds, if it exists, click the 'skip' button
    _tab.wait_appear(
        locator.chrome.linkedin.login.skip_add_phone, wait_timeout=5).click()


def search_jobs():
  
    # Wait the page load completely after 
    # submitting login information
    # Find job channel and click it to
    # switch to job channel
    _tab.wait_appear(locator.chrome.linkedin.job.jobs_channel,
                     wait_timeout=5).click()

    # Wait job search keyword input box exists
    # in 10 seconds If exists fill in with
    # the key value 'linkedin_search_job_key' 
    # in setting.json
    _tab.wait_appear(locator.chrome.linkedin.job.job_search_key,
                     wait_timeout=10).set_text(Setting.search_job_key)

    # Find job search location input box
    # Fill in with the key value
    # 'linkedin_search_job_location' in setting.json
    _tab.find_element(locator.chrome.linkedin.job.job_search_location).set_text(
        Setting.search_job_location)

    # Find the search button, and click it to search
    _tab.find_element(locator.chrome.linkedin.job.job_search).click()

# Scrape the information of the top 10 jobs
# For each job item, get the title,
# the company name, the size of the company,
# the post date, the job type
# Save search results into csv file
def get_job_top10_list():
    # Initial search result list
    job_list = []

    # Clear clipboard data first
    clear_clipboard_data()

    # Here we set range(1,11) to get top 10 jobs,
    # it can be set with any value
    for i in range(1, 11):

        # Wait the job item appears in 5 second,
        # and get the element with index value
        ele = _tab.wait_appear(locator.chrome.linkedin.jobitem.job_listitem, {
                               "index": i}, wait_timeout=5)

        # If job item exists, click the job
        # item to get detail information
        if ele:
            # Initial job item search dict
            details = {}

            # Click job item
            ele.click()

            # Wait job item's title appears in 5 seconds
            job_title_ele = _tab.wait_appear(
                locator.chrome.linkedin.jobitem.job_title, wait_timeout=5)
            
            # If job item's title exists, get
            # the title string and save into 
            # result object 'details'
            if job_title_ele:
                details["Job Title"] = job_title_ele.get_text().strip()

            # Wait job item's company name appears in 5 seconds
            job_company_ele = _tab.wait_appear(
                locator.chrome.linkedin.jobitem.job_company, wait_timeout=2)
            
            # If job item's company name exists
            #, get the company name string and
            # save into result object 'details'
            if job_company_ele:
                details["Company Name"] = job_company_ele.get_text().strip()

            # Wait job item's company scale appears in 5 seconds
            company_size_ele = _tab.wait_appear(
                locator.chrome.linkedin.jobitem.company_size, wait_timeout=2)
            
            # If job item's company scale exists,
            # get the company scale string and
            # save into result object 'details'
            if company_size_ele:
                scale = company_size_ele.get_text().strip(
                ) if "employees" in company_size_ele.get_text() else ""
                details["Company Size"] = scale

            # Wait job item's post date appears in 5 seconds
            job_post_date_ele = _tab.wait_appear(
                locator.chrome.linkedin.jobitem.job_post_date, wait_timeout=2)
            
            # If job item's post date exists,
            # get the post date string and save
            # into result object 'details'
            if job_post_date_ele:
                post_date = job_post_date_ele.get_text().strip(
                ) if "ago" in job_post_date_ele.get_text() else ""
                details["Post Date"] = post_date

            # Wait job item's type appears in 5 seconds
            job_type_ele = _tab.wait_appear(
                locator.chrome.linkedin.jobitem.job_type, wait_timeout=2)
            
            # If job item's type exists, get the
            # type string and save into result
            # object 'details'
            if job_type_ele:
                details["Job Type"] = job_type_ele.get_text().strip()

            # Wait job item's share button appears in 5 seconds
            job_share_btn_ele = _tab.wait_appear(
                locator.chrome.linkedin.jobitem.share_button, wait_timeout=2)
            
            # If job item's share button exists,
            # click the share button
            if job_share_btn_ele:
                job_share_btn_ele.click()

                # Wait the copy link button appears in 5 seconds
                copy_link = _tab.wait_appear(
                    locator.chrome.linkedin.jobitem.copy_link, wait_timeout=2)
                
                # If the copy link exists, click the copy
                # link to set clipboard data
                if copy_link:
                    copy_link.click()

                    # Sleep 0.2 second to wait the clipboard in ready state
                    sleep(0.2)

                    # Get the job link string and save
                    # into result object 'details'
                    details["Job Link"] = get_clipboard_data()

            # Save job item's result to list object
            job_list.append(details)

    # If it has any results, save into the csv file,
    # set the file path with the key
    # value 'result_csv_file' in setting.json
    if job_list:
        list_dict_to_csv(job_list, Setting.result_csv_file)


if __name__ == "__main__":
  
    # Create a browser instance with "cc.chrome",
    # for edge browser using "cc.edge"
    # Open browser with specified url and get browser tab
    # For default, it will wait the page load
    # completely. You do not need to add extra time.sleep()
    _tab = cc.chrome.open("https://www.linkedin.com/", is_wait_complete=True)

    # Check whether it needs to login in with username and password
    # True: means it needs to login in with username and password
    # False: means the website has remember authentication information
    if _tab.is_existing(locator.chrome.linkedin.login.login_email):
        # Login to LinkedIn
        login()

    # Search jobs with the keyword and location
    search_jobs()

    # Get top 10 jobs information from search
    # results and save into csv file
    get_job_top10_list()

# Library for csv operations api
import csv

# Save the list of dicts info csv file
def list_dict_to_csv(dicts, filename="test.csv"):

    # Open csv file and get file object
    with open(filename, 'w', newline='') as output_file:
        # Get csv header with the dicts keys
        keys = dicts[0].keys()

        # Initial DictWriter object
        dict_writer = csv.DictWriter(output_file, keys)

        # Write header into csv
        dict_writer.writeheader()

        # Write row datas into csv
        dict_writer.writerows(dicts)

# Library for win32 clipboard api
import win32clipboard

# Clear clipboard data
def clear_clipboard_data():
    try:
        # Call open clipboard api
        win32clipboard.OpenClipboard()

        # Call empty clipboard api
        win32clipboard.EmptyClipboard()
    finally:
        # Call close clipboard api
        win32clipboard.CloseClipboard()

# Get clipboard data
def get_clipboard_data():
    try:
        # Call open clipboard api
        win32clipboard.OpenClipboard()

        # Call get clipboard data api, and return the data
        data = win32clipboard.GetClipboardData()
        return data
    except:
        # If it got exception, return empty string
        return ""
    finally:
        # Call close clipboard api
        win32clipboard.CloseClipboard()

# Library for json operations api
import json

class Setting(object):
         
    # Open json file and get file object
    # Load json data
    with open("setting.json") as f:
        data = json.load(f)

    # Value set for LinkedIn login username
    login_name = data['linkedin_login_name']

    # Value set for LinkedIn login password
    login_password = data['linkedin_login_password']

    # Value set for LinkedIn job search keyword
    search_job_key = data['linkedin_search_job_key']

    # Value set for LinkedIn job search location
    search_job_location = data['linkedin_search_job_location']

    # Value set for csv file path to save search results
    result_csv_file = data['result_csv_file']

{
    "linkedin_login_name": "your account username",
    "linkedin_login_password": "your account password",
    "linkedin_search_job_key": "your desired job title",
    "linkedin_search_job_location": "your desired job location",
    "result_csv_file": "C:\\test\\test.csv"
}