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5 Commits

Author SHA1 Message Date
Cullen Watson
2ec3b04777 fix(ziprecruiter): init cookies (#82) 2024-01-12 12:28:35 -06:00
Harish Vadaparty
89a5264391 add long scrape example (#81) 2024-01-12 12:24:00 -06:00
Cullen Watson
a7ad616567 fix: linkedin no results (#80) 2024-01-10 14:01:10 -06:00
cullenwatson
53bc33a43a chore: version 2024-01-09 19:33:56 -06:00
Cullen Watson
22870438c7 linkedin fix delays (#79) 2024-01-09 19:32:51 -06:00
6 changed files with 153 additions and 62 deletions

View File

@@ -2,12 +2,11 @@ from jobspy import scrape_jobs
import pandas as pd
jobs: pd.DataFrame = scrape_jobs(
site_name=["indeed", "linkedin", "zip_recruiter"],
site_name=["indeed", "linkedin", "zip_recruiter", "glassdoor"],
search_term="software engineer",
location="Dallas, TX",
results_wanted=50, # be wary the higher it is, the more likey you'll get blocked (rotating proxy should work tho)
results_wanted=25, # be wary the higher it is, the more likey you'll get blocked (rotating proxy can help tho)
country_indeed="USA",
offset=25 # start jobs from an offset (use if search failed and want to continue)
# proxy="http://jobspy:5a4vpWtj8EeJ2hoYzk@ca.smartproxy.com:20001",
)

View File

@@ -0,0 +1,77 @@
from jobspy import scrape_jobs
import pandas as pd
import os
import time
# creates csv a new filename if the jobs.csv already exists.
csv_filename = "jobs.csv"
counter = 1
while os.path.exists(csv_filename):
csv_filename = f"jobs_{counter}.csv"
counter += 1
# results wanted and offset
results_wanted = 1000
offset = 0
all_jobs = []
# max retries
max_retries = 3
# nuumber of results at each iteration
results_in_each_iteration = 30
while len(all_jobs) < results_wanted:
retry_count = 0
while retry_count < max_retries:
print("Doing from", offset, "to", offset + results_in_each_iteration, "jobs")
try:
jobs = scrape_jobs(
site_name=["indeed"],
search_term="software engineer",
# New York, NY
# Dallas, TX
# Los Angeles, CA
location="Los Angeles, CA",
results_wanted=min(results_in_each_iteration, results_wanted - len(all_jobs)),
country_indeed="USA",
offset=offset,
# proxy="http://jobspy:5a4vpWtj8EeJ2hoYzk@ca.smartproxy.com:20001",
)
# Add the scraped jobs to the list
all_jobs.extend(jobs.to_dict('records'))
# Increment the offset for the next page of results
offset += results_in_each_iteration
# Add a delay to avoid rate limiting (you can adjust the delay time as needed)
print(f"Scraped {len(all_jobs)} jobs")
print("Sleeping secs", 100 * (retry_count + 1))
time.sleep(100 * (retry_count + 1)) # Sleep for 2 seconds between requests
break # Break out of the retry loop if successful
except Exception as e:
print(f"Error: {e}")
retry_count += 1
print("Sleeping secs before retry", 100 * (retry_count + 1))
time.sleep(100 * (retry_count + 1))
if retry_count >= max_retries:
print("Max retries reached. Exiting.")
break
# DataFrame from the collected job data
jobs_df = pd.DataFrame(all_jobs)
# Formatting
pd.set_option("display.max_columns", None)
pd.set_option("display.max_rows", None)
pd.set_option("display.width", None)
pd.set_option("display.max_colwidth", 50)
print(jobs_df)
jobs_df.to_csv(csv_filename, index=False)
print(f"Outputted to {csv_filename}")

View File

@@ -1,6 +1,6 @@
[tool.poetry]
name = "python-jobspy"
version = "1.1.31"
version = "1.1.34"
description = "Job scraper for LinkedIn, Indeed, Glassdoor & ZipRecruiter"
authors = ["Zachary Hampton <zachary@bunsly.com>", "Cullen Watson <cullen@bunsly.com>"]
homepage = "https://github.com/Bunsly/JobSpy"

View File

@@ -4,6 +4,7 @@ jobspy.scrapers.linkedin
This module contains routines to scrape LinkedIn.
"""
import random
from typing import Optional
from datetime import datetime
@@ -16,14 +17,14 @@ from threading import Lock
from urllib.parse import urlparse, urlunparse
from .. import Scraper, ScraperInput, Site
from ..utils import count_urgent_words, extract_emails_from_text, get_enum_from_job_type, currency_parser
from ..exceptions import LinkedInException
from ..utils import create_session
from ...jobs import JobPost, Location, JobResponse, JobType, Country, Compensation
from ..utils import count_urgent_words, extract_emails_from_text, get_enum_from_job_type, currency_parser
class LinkedInScraper(Scraper):
MAX_RETRIES = 3
DELAY = 10
DELAY = 3
def __init__(self, proxy: Optional[str] = None):
"""
@@ -57,6 +58,7 @@ class LinkedInScraper(Scraper):
return mapping.get(job_type_enum, "")
while len(job_list) < scraper_input.results_wanted and page < 1000:
session = create_session(is_tls=False, has_retry=True, delay=5)
params = {
"keywords": scraper_input.search_term,
"location": scraper_input.location,
@@ -71,44 +73,30 @@ class LinkedInScraper(Scraper):
}
params = {k: v for k, v in params.items() if v is not None}
retries = 0
while retries < self.MAX_RETRIES:
try:
response = requests.get(
f"{self.url}/jobs-guest/jobs/api/seeMoreJobPostings/search?",
params=params,
allow_redirects=True,
proxies=self.proxy,
timeout=10,
)
response.raise_for_status()
break
except requests.HTTPError as e:
if hasattr(e, "response") and e.response is not None:
if e.response.status_code in (429, 502):
time.sleep(self.DELAY)
retries += 1
continue
else:
raise LinkedInException(
f"bad response status code: {e.response.status_code}"
)
else:
raise
except ProxyError as e:
raise LinkedInException("bad proxy")
except Exception as e:
raise LinkedInException(str(e))
else:
# Raise an exception if the maximum number of retries is reached
raise LinkedInException(
"Max retries reached, failed to get a valid response"
try:
response = session.get(
f"{self.url}/jobs-guest/jobs/api/seeMoreJobPostings/search?",
params=params,
allow_redirects=True,
proxies=self.proxy,
headers=self.headers(),
timeout=10,
)
response.raise_for_status()
except requests.HTTPError as e:
raise LinkedInException(f"bad response status code: {e.response.status_code}")
except ProxyError as e:
raise LinkedInException("bad proxy")
except Exception as e:
raise LinkedInException(str(e))
soup = BeautifulSoup(response.text, "html.parser")
job_cards = soup.find_all("div", class_="base-search-card")
if len(job_cards) == 0:
return JobResponse(jobs=job_list)
for job_card in soup.find_all("div", class_="base-search-card"):
for job_card in job_cards:
job_url = None
href_tag = job_card.find("a", class_="base-card__full-link")
if href_tag and "href" in href_tag.attrs:
@@ -130,6 +118,7 @@ class LinkedInScraper(Scraper):
raise LinkedInException("Exception occurred while processing jobs")
page += 25
time.sleep(random.uniform(LinkedInScraper.DELAY, LinkedInScraper.DELAY + 2))
job_list = job_list[: scraper_input.results_wanted]
return JobResponse(jobs=job_list)
@@ -181,22 +170,22 @@ class LinkedInScraper(Scraper):
benefits_tag = job_card.find("span", class_="result-benefits__text")
benefits = " ".join(benefits_tag.get_text().split()) if benefits_tag else None
description, job_type = self.get_job_description(job_url)
# description, job_type = None, []
# removed to speed up scraping
# description, job_type = self.get_job_description(job_url)
return JobPost(
title=title,
description=description,
company_name=company,
company_url=company_url,
location=location,
date_posted=date_posted,
job_url=job_url,
job_type=job_type,
compensation=compensation,
benefits=benefits,
emails=extract_emails_from_text(description) if description else None,
num_urgent_words=count_urgent_words(description) if description else None,
# job_type=job_type,
# description=description,
# emails=extract_emails_from_text(description) if description else None,
# num_urgent_words=count_urgent_words(description) if description else None,
)
def get_job_description(
@@ -208,12 +197,10 @@ class LinkedInScraper(Scraper):
:return: description or None
"""
try:
response = requests.get(job_page_url, timeout=5, proxies=self.proxy)
session = create_session(is_tls=False, has_retry=True)
response = session.get(job_page_url, timeout=5, proxies=self.proxy)
response.raise_for_status()
except requests.HTTPError as e:
if hasattr(e, "response") and e.response is not None:
if e.response.status_code in (429, 502):
time.sleep(self.DELAY)
return None, None
except Exception as e:
return None, None
@@ -287,3 +274,21 @@ class LinkedInScraper(Scraper):
)
return location
@staticmethod
def headers() -> dict:
return {
'authority': 'www.linkedin.com',
'accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7',
'accept-language': 'en-US,en;q=0.9',
'cache-control': 'max-age=0',
'sec-ch-ua': '"Not_A Brand";v="8", "Chromium";v="120", "Google Chrome";v="120"',
# 'sec-ch-ua-mobile': '?0',
# 'sec-ch-ua-platform': '"macOS"',
# 'sec-fetch-dest': 'document',
# 'sec-fetch-mode': 'navigate',
# 'sec-fetch-site': 'none',
# 'sec-fetch-user': '?1',
'upgrade-insecure-requests': '1',
'user-agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36'
}

View File

@@ -29,7 +29,7 @@ def extract_emails_from_text(text: str) -> list[str] | None:
return email_regex.findall(text)
def create_session(proxy: dict | None = None, is_tls: bool = True, has_retry: bool = False):
def create_session(proxy: dict | None = None, is_tls: bool = True, has_retry: bool = False, delay: int = 1) -> requests.Session:
"""
Creates a requests session with optional tls, proxy, and retry settings.
@@ -51,7 +51,7 @@ def create_session(proxy: dict | None = None, is_tls: bool = True, has_retry: bo
connect=3,
status=3,
status_forcelist=[500, 502, 503, 504, 429],
backoff_factor=1)
backoff_factor=delay)
adapter = HTTPAdapter(max_retries=retries)
session.mount('http://', adapter)

View File

@@ -10,6 +10,7 @@ import re
from datetime import datetime, date
from typing import Optional, Tuple, Any
import requests
from bs4 import BeautifulSoup
from concurrent.futures import ThreadPoolExecutor
@@ -26,6 +27,8 @@ class ZipRecruiterScraper(Scraper):
"""
site = Site(Site.ZIP_RECRUITER)
self.url = "https://www.ziprecruiter.com"
self.session = create_session(proxy)
self.get_cookies()
super().__init__(site, proxy=proxy)
self.jobs_per_page = 20
@@ -44,12 +47,10 @@ class ZipRecruiterScraper(Scraper):
if continue_token:
params["continue"] = continue_token
try:
session = create_session(self.proxy, is_tls=True)
response = session.get(
response = self.session.get(
f"https://api.ziprecruiter.com/jobs-app/jobs",
headers=self.headers(),
params=self.add_params(scraper_input),
timeout_seconds=10,
)
if response.status_code != 200:
raise ZipRecruiterException(
@@ -156,6 +157,11 @@ class ZipRecruiterScraper(Scraper):
num_urgent_words=count_urgent_words(description) if description else None,
)
def get_cookies(self):
url="https://api.ziprecruiter.com/jobs-app/event"
data="event_type=session&logged_in=false&number_of_retry=1&property=model%3AiPhone&property=os%3AiOS&property=locale%3Aen_us&property=app_build_number%3A4734&property=app_version%3A91.0&property=manufacturer%3AApple&property=timestamp%3A2024-01-12T12%3A04%3A42-06%3A00&property=screen_height%3A852&property=os_version%3A16.6.1&property=source%3Ainstall&property=screen_width%3A393&property=device_model%3AiPhone%2014%20Pro&property=brand%3AApple"
self.session.post(url, data=data, headers=ZipRecruiterScraper.headers())
@staticmethod
def get_job_type_enum(job_type_str: str) -> list[JobType] | None:
for job_type in JobType:
@@ -195,12 +201,16 @@ class ZipRecruiterScraper(Scraper):
@staticmethod
def headers() -> dict:
"""
Returns headers needed for ZipRecruiter API requests
Returns headers needed for requests
:return: dict - Dictionary containing headers
"""
return {
'Host': 'api.ziprecruiter.com',
'accept': '*/*',
'authorization': 'Basic YTBlZjMyZDYtN2I0Yy00MWVkLWEyODMtYTI1NDAzMzI0YTcyOg==',
'Cookie': '__cf_bm=DZ7eJOw6lka.Bwy5jLeDqWanaZ8BJlVAwaXrmcbYnxM-1701505132-0-AfGaVIfTA2kJlmleK14o722vbVwpZ+4UxFznsWv+guvzXSpD9KVEy/+pNzvEZUx88yaEShJwGt3/EVjhHirX/ASustKxg47V/aXRd2XIO2QN; zglobalid=61f94830-1990-4130-b222-d9d0e09c7825.57da9ea9581c.656ae86b; ziprecruiter_browser=018188e0-045b-4ad7-aa50-627a6c3d43aa; ziprecruiter_session=5259b2219bf95b6d2299a1417424bc2edc9f4b38; zva=100000000%3Bvid%3AZWroa0x_F1KEeGeU'
"Host": "api.ziprecruiter.com",
"accept": "*/*",
"x-zr-zva-override": "100000000;vid:ZT1huzm_EQlDTVEc",
"x-pushnotificationid": "0ff4983d38d7fc5b3370297f2bcffcf4b3321c418f5c22dd152a0264707602a0",
"x-deviceid": "D77B3A92-E589-46A4-8A39-6EF6F1D86006",
"user-agent": "Job Search/87.0 (iPhone; CPU iOS 16_6_1 like Mac OS X)",
"authorization": "Basic YTBlZjMyZDYtN2I0Yy00MWVkLWEyODMtYTI1NDAzMzI0YTcyOg==",
"accept-language": "en-US,en;q=0.9",
}