research_findr.py

from selenium import webdriver
import argparse
import pandas as pd
from scrape_scholar import scrape 
from selenium.webdriver.common.by import By

#selenium start guide : http://selenium-python.readthedocs.io/getting-started.html
#download chrome webdriver from https://sites.google.com/a/chromium.org/chromedriver/downloads
def search_results(first_name, last_name, display=None):
  #driver = webdriver.Chrome()
  base_url = 'https://www.linkedin.com/search/results/index/?keywords=firstname%3A{0}%20AND%20lastname%3A{1}&origin=GLOBAL_SEARCH_HEADER'.format(first_name, last_name)
  base_url= base_url.replace(' ', '%20')

  #print driver.find_element_by_class_name("search-no-results__tips Sans-15px-black-70%")
  if display:
    driver = webdriver.Chrome()
    driver.get(base_url)
    print driver.find_element_by_class_name("search-no-results__tips Sans-15px-black-70%")
  return base_url

  

if __name__ == '__main__':
  #parser = argparse.ArgumentParser()

  #dict = {'machine learning': ['John,Doe', 'Bob,Smith']}
  #input is {key: [A-first, A-last], [B-first, B-last], ...}
  dict = scrape()
  print dict 
  csv_dict = {'name':[], 'url':[], 'keyword':[]}

  for key in dict:
    for i in range(len(dict[key])):
      name = dict[key][i].split(',')
      csv_dict['url'].append(search_results(name[1], name[0]))
      csv_dict['name'].append( [name[1], name[0]])
      csv_dict['keyword'].append(key)

  pd.DataFrame(csv_dict).to_csv('tmp.csv', index=False)