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Scrape Job titles and company from LinkedIn
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{ | |
"cells": [ | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"# Scrape Job Titles from LinkedIn\n", | |
"\n", | |
"The trick is to go through Google to get the data. LinkedIn is restricting its API. The script queries Google for a name and uses the keywords _linkedin professional profile_ in addition to be sure to hot the profile data. It then extracts name, job title, and company from the first search result." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": null, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"from bs4 import BeautifulSoup\n", | |
"import requests\n", | |
"from lxml.html import html5parser\n", | |
"import re\n", | |
"\n", | |
"def decomptitle(title):\n", | |
" h = html5parser.fromstring(str(title))\n", | |
" name = h.getchildren()[0].getchildren()[0].text\n", | |
" profile = h.getchildren()[0].getchildren()[1].text\n", | |
" linkedin = h.getchildren()[0].getchildren()[2].text\n", | |
" return name, profile, linkedin\n", | |
"\n", | |
"def decompjobdesc(jobdesc):\n", | |
" h = html5parser.fromstring(str(jobdesc))\n", | |
" location, job, company = str(h.text).split('\\xa0-\\xa0')\n", | |
" job, company2 = job.split(' at ')\n", | |
" if company != company2:\n", | |
" return None, None, None\n", | |
" return location, job, company\n", | |
"\n", | |
"def scrape_job_title(firstname, lastname):\n", | |
" url = 'https://www.google.com/search?q={}+{}+linkedin+professional+profile'.format(firstname, lastname)\n", | |
" r = requests.get(url)\n", | |
" data = r.text\n", | |
" soup = BeautifulSoup(data, \"lxml\")\n", | |
" title = soup.find_all(\"h3\", {\"class\":\"r\"})[0]\n", | |
" jobdesc = soup.find_all(\"div\", {\"class\":\"slp\"})[0]\n", | |
" name, profile, linkedin = decomptitle(title)\n", | |
" location, job, company = decompjobdesc(jobdesc)\n", | |
" return job, name, company\n", | |
" " | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": null, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"scrape_job_title('John', 'Doe')" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": null, | |
"metadata": { | |
"collapsed": true | |
}, | |
"outputs": [], | |
"source": [] | |
} | |
], | |
"metadata": { | |
"kernelspec": { | |
"display_name": "Python [conda env:sumo]", | |
"language": "python", | |
"name": "conda-env-sumo-py" | |
}, | |
"language_info": { | |
"codemirror_mode": { | |
"name": "ipython", | |
"version": 3 | |
}, | |
"file_extension": ".py", | |
"mimetype": "text/x-python", | |
"name": "python", | |
"nbconvert_exporter": "python", | |
"pygments_lexer": "ipython3", | |
"version": "3.6.2" | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 2 | |
} |
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To improve this, I would add site:linkedin.com to the scrape URL, that way you'll get linkedin results.