mirror of https://github.com/Bunsly/JobSpy
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Author | SHA1 | Date |
---|---|---|
Cullen Watson | 811d4c40b4 | |
Cullen Watson | dba92d22c2 | |
Cullen Watson | 10a3592a0f | |
Cullen Watson | b7905cc756 | |
Cullen Watson | 6867d58829 | |
Cullen Watson | f6248c8386 |
24
README.md
24
README.md
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@ -2,14 +2,12 @@
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**JobSpy** is a simple, yet comprehensive, job scraping library.
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**Not technical?** Try out the web scraping tool on our site at [usejobspy.com](https://usejobspy.com).
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*Looking to build a data-focused software product?* **[Book a call](https://bunsly.com/)** *to
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work with us.*
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## Features
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- Scrapes job postings from **LinkedIn**, **Indeed**, **Glassdoor**, & **ZipRecruiter** simultaneously
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- Scrapes job postings from **LinkedIn**, **Indeed**, **Glassdoor**, **Google**, & **ZipRecruiter** simultaneously
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- Aggregates the job postings in a Pandas DataFrame
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- Proxies support
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@ -30,9 +28,9 @@ import csv
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from jobspy import scrape_jobs
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jobs = scrape_jobs(
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site_name=["indeed", "linkedin", "zip_recruiter", "glassdoor"],
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site_name=["indeed", "linkedin", "zip_recruiter", "glassdoor", "google"],
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search_term="software engineer",
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location="Dallas, TX",
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location="San Francisco, CA",
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results_wanted=20,
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hours_old=72, # (only Linkedin/Indeed is hour specific, others round up to days old)
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country_indeed='USA', # only needed for indeed / glassdoor
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@ -63,8 +61,8 @@ zip_recruiter Software Developer TEKsystems Phoenix
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```plaintext
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Optional
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├── site_name (list|str):
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| linkedin, zip_recruiter, indeed, glassdoor
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| (default is all four)
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| linkedin, zip_recruiter, indeed, glassdoor, google
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| (default is all)
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│
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├── search_term (str)
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│
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@ -80,9 +78,6 @@ Optional
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| in format ['user:pass@host:port', 'localhost']
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| each job board scraper will round robin through the proxies
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|
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├── ca_cert (str)
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| path to CA Certificate file for proxies
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│
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├── is_remote (bool)
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│
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├── results_wanted (int):
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@ -116,6 +111,9 @@ Optional
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|
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├── enforce_annual_salary (bool):
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| converts wages to annual salary
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|
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├── ca_cert (str)
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| path to CA Certificate file for proxies
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```
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```
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@ -168,14 +166,14 @@ Indeed specific
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├── company_employees_label
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├── company_revenue_label
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├── company_description
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└── logo_photo_url
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└── company_logo
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```
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## Supported Countries for Job Searching
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### **LinkedIn**
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### **LinkedIn / Google**
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LinkedIn searches globally & uses only the `location` parameter.
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LinkedIn & Google searches globally & uses only the `location` parameter.
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### **ZipRecruiter**
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|
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@ -1,6 +1,6 @@
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[tool.poetry]
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name = "python-jobspy"
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version = "1.1.72"
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version = "1.1.74"
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description = "Job scraper for LinkedIn, Indeed, Glassdoor & ZipRecruiter"
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authors = ["Zachary Hampton <zachary@bunsly.com>", "Cullen Watson <cullen@bunsly.com>"]
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homepage = "https://github.com/Bunsly/JobSpy"
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@ -9,6 +9,7 @@ from .scrapers.utils import set_logger_level, extract_salary, create_logger
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from .scrapers.indeed import IndeedScraper
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from .scrapers.ziprecruiter import ZipRecruiterScraper
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from .scrapers.glassdoor import GlassdoorScraper
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from .scrapers.google import GoogleJobsScraper
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from .scrapers.linkedin import LinkedInScraper
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from .scrapers import SalarySource, ScraperInput, Site, JobResponse, Country
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from .scrapers.exceptions import (
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@ -16,6 +17,7 @@ from .scrapers.exceptions import (
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IndeedException,
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ZipRecruiterException,
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GlassdoorException,
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GoogleJobsException,
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)
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@ -50,6 +52,7 @@ def scrape_jobs(
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Site.INDEED: IndeedScraper,
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Site.ZIP_RECRUITER: ZipRecruiterScraper,
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Site.GLASSDOOR: GlassdoorScraper,
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Site.GOOGLE: GoogleJobsScraper,
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}
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set_logger_level(verbose)
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@ -223,12 +226,12 @@ def scrape_jobs(
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"is_remote",
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"job_level",
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"job_function",
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"company_industry",
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"listing_type",
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"emails",
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"description",
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"company_industry",
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"company_url",
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"logo_photo_url",
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"company_logo",
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"company_url_direct",
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"company_addresses",
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"company_num_employees",
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|
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@ -256,7 +256,7 @@ class JobPost(BaseModel):
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company_num_employees: str | None = None
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company_revenue: str | None = None
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company_description: str | None = None
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logo_photo_url: str | None = None
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company_logo: str | None = None
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banner_photo_url: str | None = None
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# linkedin only atm
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|
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@ -17,11 +17,14 @@ class Site(Enum):
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INDEED = "indeed"
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ZIP_RECRUITER = "zip_recruiter"
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GLASSDOOR = "glassdoor"
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GOOGLE = "google"
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class SalarySource(Enum):
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DIRECT_DATA = "direct_data"
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DESCRIPTION = "description"
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class ScraperInput(BaseModel):
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site_type: list[Site]
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search_term: str | None = None
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@ -42,7 +45,9 @@ class ScraperInput(BaseModel):
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class Scraper(ABC):
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def __init__(self, site: Site, proxies: list[str] | None = None, ca_cert: str | None = None):
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def __init__(
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self, site: Site, proxies: list[str] | None = None, ca_cert: str | None = None
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):
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self.site = site
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self.proxies = proxies
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self.ca_cert = ca_cert
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|
|
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@ -24,3 +24,8 @@ class ZipRecruiterException(Exception):
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class GlassdoorException(Exception):
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def __init__(self, message=None):
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super().__init__(message or "An error occurred with Glassdoor")
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class GoogleJobsException(Exception):
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def __init__(self, message=None):
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super().__init__(message or "An error occurred with Google Jobs")
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|
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@ -214,7 +214,7 @@ class GlassdoorScraper(Scraper):
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is_remote=is_remote,
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description=description,
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emails=extract_emails_from_text(description) if description else None,
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logo_photo_url=company_logo,
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company_logo=company_logo,
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listing_type=listing_type,
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)
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|
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@ -0,0 +1,215 @@
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"""
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jobspy.scrapers.google
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~~~~~~~~~~~~~~~~~~~
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This module contains routines to scrape Google.
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"""
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from __future__ import annotations
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import math
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import re
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import json
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from typing import Tuple
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from datetime import datetime, timedelta
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from .constants import headers_jobs, headers_initial, async_param
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from .. import Scraper, ScraperInput, Site
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from ..utils import extract_emails_from_text, create_logger, extract_job_type
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from ..utils import (
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create_session,
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)
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from ...jobs import (
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JobPost,
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JobResponse,
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Location,
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JobType,
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)
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logger = create_logger("Google")
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class GoogleJobsScraper(Scraper):
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def __init__(
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self, proxies: list[str] | str | None = None, ca_cert: str | None = None
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):
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"""
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Initializes Google Scraper with the Goodle jobs search url
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"""
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site = Site(Site.GOOGLE)
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super().__init__(site, proxies=proxies, ca_cert=ca_cert)
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self.country = None
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self.session = None
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self.scraper_input = None
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self.jobs_per_page = 10
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self.seen_urls = set()
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self.url = "https://www.google.com/search"
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self.jobs_url = "https://www.google.com/async/callback:550"
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def scrape(self, scraper_input: ScraperInput) -> JobResponse:
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"""
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Scrapes Google for jobs with scraper_input criteria.
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:param scraper_input: Information about job search criteria.
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:return: JobResponse containing a list of jobs.
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"""
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self.scraper_input = scraper_input
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self.scraper_input.results_wanted = min(900, scraper_input.results_wanted)
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self.session = create_session(
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proxies=self.proxies, ca_cert=self.ca_cert, is_tls=False, has_retry=True
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)
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forward_cursor = self._get_initial_cursor()
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if forward_cursor is None:
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logger.error("initial cursor not found")
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return JobResponse(jobs=[])
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page = 1
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job_list: list[JobPost] = []
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while (
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len(self.seen_urls) < scraper_input.results_wanted + scraper_input.offset
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and forward_cursor
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):
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logger.info(
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f"search page: {page} / {math.ceil(scraper_input.results_wanted / self.jobs_per_page)}"
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)
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jobs, forward_cursor = self._get_jobs_next_page(forward_cursor)
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if not jobs:
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logger.info(f"found no jobs on page: {page}")
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break
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job_list += jobs
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page += 1
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return JobResponse(
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jobs=job_list[
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scraper_input.offset : scraper_input.offset
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+ scraper_input.results_wanted
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]
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)
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def _get_initial_cursor(self):
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"""Gets initial cursor to paginate through job listings"""
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query = f"{self.scraper_input.search_term} jobs"
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def get_time_range(hours_old):
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if hours_old <= 24:
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return "since yesterday"
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elif hours_old <= 72:
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return "in the last 3 days"
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elif hours_old <= 168:
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return "in the last week"
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else:
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return "in the last month"
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job_type_mapping = {
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JobType.FULL_TIME: "Full time",
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JobType.PART_TIME: "Part time",
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JobType.INTERNSHIP: "Internship",
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JobType.CONTRACT: "Contract",
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}
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if self.scraper_input.job_type in job_type_mapping:
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query += f" {job_type_mapping[self.scraper_input.job_type]}"
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if self.scraper_input.location:
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query += f" near {self.scraper_input.location}"
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if self.scraper_input.hours_old:
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time_filter = get_time_range(self.scraper_input.hours_old)
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query += f" {time_filter}"
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if self.scraper_input.is_remote:
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query += " remote"
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params = {"q": query, "udm": "8"}
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response = self.session.get(self.url, headers=headers_initial, params=params)
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pattern_fc = r'<div jsname="Yust4d"[^>]+data-async-fc="([^"]+)"'
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match_fc = re.search(pattern_fc, response.text)
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data_async_fc = match_fc.group(1) if match_fc else None
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return data_async_fc
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def _get_jobs_next_page(self, forward_cursor: str) -> Tuple[list[JobPost], str]:
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params = {"fc": [forward_cursor], "fcv": ["3"], "async": [async_param]}
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response = self.session.get(self.jobs_url, headers=headers_jobs, params=params)
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return self._parse_jobs(response.text)
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def _parse_jobs(self, job_data: str) -> Tuple[list[JobPost], str]:
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"""
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Parses jobs on a page with next page cursor
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"""
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start_idx = job_data.find("[[[")
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end_idx = job_data.rindex("]]]") + 3
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s = job_data[start_idx:end_idx]
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parsed = json.loads(s)[0]
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pattern_fc = r'data-async-fc="([^"]+)"'
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match_fc = re.search(pattern_fc, job_data)
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data_async_fc = match_fc.group(1) if match_fc else None
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jobs_on_page = []
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for array in parsed:
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_, job_data = array
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if not job_data.startswith("[[["):
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continue
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job_d = json.loads(job_data)
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job_info = self._find_job_info(job_d)
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job_url = job_info[3][0][0] if job_info[3] and job_info[3][0] else None
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if job_url in self.seen_urls:
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continue
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self.seen_urls.add(job_url)
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title = job_info[0]
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company_name = job_info[1]
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location = city = job_info[2]
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state = country = date_posted = None
|
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if location and "," in location:
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city, state, *country = [*map(lambda x: x.strip(), location.split(","))]
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|
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days_ago_str = job_info[12]
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if type(days_ago_str) == str:
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match = re.search(r"\d+", days_ago_str)
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days_ago = int(match.group()) if match else None
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date_posted = (datetime.now() - timedelta(days=days_ago)).date()
|
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description = job_info[19]
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job_post = JobPost(
|
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id=f"go-{job_info[28]}",
|
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title=title,
|
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company_name=company_name,
|
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location=Location(
|
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city=city, state=state, country=country[0] if country else None
|
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),
|
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job_url=job_url,
|
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job_url_direct=job_url,
|
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date_posted=date_posted,
|
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is_remote="remote" in description.lower()
|
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or "wfh" in description.lower(),
|
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description=description,
|
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emails=extract_emails_from_text(description),
|
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job_type=extract_job_type(description),
|
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)
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jobs_on_page.append(job_post)
|
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return jobs_on_page, data_async_fc
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|
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@staticmethod
|
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def _find_job_info(jobs_data: list | dict) -> list | None:
|
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"""Iterates through the JSON data to find the job listings"""
|
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if isinstance(jobs_data, dict):
|
||||
for key, value in jobs_data.items():
|
||||
if key == "520084652" and isinstance(value, list):
|
||||
return value
|
||||
else:
|
||||
result = GoogleJobsScraper._find_job_info(value)
|
||||
if result:
|
||||
return result
|
||||
elif isinstance(jobs_data, list):
|
||||
for item in jobs_data:
|
||||
result = GoogleJobsScraper._find_job_info(item)
|
||||
if result:
|
||||
return result
|
||||
return None
|
|
@ -0,0 +1,52 @@
|
|||
headers_initial = {
|
||||
"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",
|
||||
"priority": "u=0, i",
|
||||
"referer": "https://www.google.com/",
|
||||
"sec-ch-prefers-color-scheme": "dark",
|
||||
"sec-ch-ua": '"Chromium";v="130", "Google Chrome";v="130", "Not?A_Brand";v="99"',
|
||||
"sec-ch-ua-arch": '"arm"',
|
||||
"sec-ch-ua-bitness": '"64"',
|
||||
"sec-ch-ua-form-factors": '"Desktop"',
|
||||
"sec-ch-ua-full-version": '"130.0.6723.58"',
|
||||
"sec-ch-ua-full-version-list": '"Chromium";v="130.0.6723.58", "Google Chrome";v="130.0.6723.58", "Not?A_Brand";v="99.0.0.0"',
|
||||
"sec-ch-ua-mobile": "?0",
|
||||
"sec-ch-ua-model": '""',
|
||||
"sec-ch-ua-platform": '"macOS"',
|
||||
"sec-ch-ua-platform-version": '"15.0.1"',
|
||||
"sec-ch-ua-wow64": "?0",
|
||||
"sec-fetch-dest": "document",
|
||||
"sec-fetch-mode": "navigate",
|
||||
"sec-fetch-site": "same-origin",
|
||||
"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/130.0.0.0 Safari/537.36",
|
||||
"x-browser-channel": "stable",
|
||||
"x-browser-copyright": "Copyright 2024 Google LLC. All rights reserved.",
|
||||
"x-browser-year": "2024",
|
||||
}
|
||||
|
||||
headers_jobs = {
|
||||
"accept": "*/*",
|
||||
"accept-language": "en-US,en;q=0.9",
|
||||
"priority": "u=1, i",
|
||||
"referer": "https://www.google.com/",
|
||||
"sec-ch-prefers-color-scheme": "dark",
|
||||
"sec-ch-ua": '"Chromium";v="130", "Google Chrome";v="130", "Not?A_Brand";v="99"',
|
||||
"sec-ch-ua-arch": '"arm"',
|
||||
"sec-ch-ua-bitness": '"64"',
|
||||
"sec-ch-ua-form-factors": '"Desktop"',
|
||||
"sec-ch-ua-full-version": '"130.0.6723.58"',
|
||||
"sec-ch-ua-full-version-list": '"Chromium";v="130.0.6723.58", "Google Chrome";v="130.0.6723.58", "Not?A_Brand";v="99.0.0.0"',
|
||||
"sec-ch-ua-mobile": "?0",
|
||||
"sec-ch-ua-model": '""',
|
||||
"sec-ch-ua-platform": '"macOS"',
|
||||
"sec-ch-ua-platform-version": '"15.0.1"',
|
||||
"sec-ch-ua-wow64": "?0",
|
||||
"sec-fetch-dest": "empty",
|
||||
"sec-fetch-mode": "cors",
|
||||
"sec-fetch-site": "same-origin",
|
||||
"user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Safari/537.36",
|
||||
}
|
||||
|
||||
async_param = "_basejs:/xjs/_/js/k=xjs.s.en_US.JwveA-JiKmg.2018.O/am=AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAIAAAAAAAAACAAAoICAAAAAAAKMAfAAAAIAQAAAAAAAAAAAAACCAAAEJDAAACAAAAAGABAIAAARBAAABAAAAAgAgQAABAASKAfv8JAAABAAAAAAwAQAQACQAAAAAAcAEAQABoCAAAABAAAIABAACAAAAEAAAAFAAAAAAAAAAAAAAAAAAAAAAAAACAQADoBwAAAAAAAAAAAAAQBAAAAATQAAoACOAHAAAAAAAAAQAAAIIAAAA_ZAACAAAAAAAAcB8APB4wHFJ4AAAAAAAAAAAAAAAACECCYA5If0EACAAAAAAAAAAAAAAAAAAAUgRNXG4AMAE/dg=0/br=1/rs=ACT90oGxMeaFMCopIHq5tuQM-6_3M_VMjQ,_basecss:/xjs/_/ss/k=xjs.s.IwsGu62EDtU.L.B1.O/am=QOoQIAQAAAQAREADEBAAAAAAAAAAAAAAAAAAAAAgAQAAIAAAgAQAAAIAIAIAoEwCAADIC8AfsgEAawwAPkAAjgoAGAAAAAAAAEADAAAAAAIgAECHAAAAAAAAAAABAQAggAARQAAAQCEAAAAAIAAAABgAAAAAIAQIACCAAfB-AAFIQABoCEA_CgEAAIABAACEgHAEwwAEFQAM4CgAAAAAAAAAAAAACABCAAAAQEAAABAgAMCPAAA4AoE2BAEAggSAAIoAQAAAAAgAAAAACCAQAAAxEwA_ZAACAAAAAAAAAAkAAAAAAAAgAAAAAAAAAAAAAAAAAAAAAAAAQAEAAAAAAAAAAAAAAAAAAAAAQA/br=1/rs=ACT90oGZc36t3uUQkj0srnIvvbHjO2hgyg,_basecomb:/xjs/_/js/k=xjs.s.en_US.JwveA-JiKmg.2018.O/ck=xjs.s.IwsGu62EDtU.L.B1.O/am=QOoQIAQAAAQAREADEBAAAAAAAAAAAAAAAAAAAAAgAQAAIAAAgAQAAAKAIAoIqEwCAADIK8AfsgEAawwAPkAAjgoAGAAACCAAAEJDAAACAAIgAGCHAIAAARBAAABBAQAggAgRQABAQSOAfv8JIAABABgAAAwAYAQICSCAAfB-cAFIQABoCEA_ChEAAIABAACEgHAEwwAEFQAM4CgAAAAAAAAAAAAACABCAACAQEDoBxAgAMCPAAA4AoE2BAEAggTQAIoASOAHAAgAAAAACSAQAIIxEwA_ZAACAAAAAAAAcB8APB4wHFJ4AAAAAAAAAAAAAAAACECCYA5If0EACAAAAAAAAAAAAAAAAAAAUgRNXG4AMAE/d=1/ed=1/dg=0/br=1/ujg=1/rs=ACT90oFNLTjPzD_OAqhhtXwe2pg1T3WpBg,_fmt:prog,_id:fc_5FwaZ86OKsfdwN4P4La3yA4_2"
|
|
@ -72,7 +72,7 @@ class IndeedScraper(Scraper):
|
|||
|
||||
while len(self.seen_urls) < scraper_input.results_wanted + scraper_input.offset:
|
||||
logger.info(
|
||||
f"search page: {page} / {math.ceil(scraper_input.results_wanted / 100)}"
|
||||
f"search page: {page} / {math.ceil(scraper_input.results_wanted / self.jobs_per_page)}"
|
||||
)
|
||||
jobs, cursor = self._scrape_page(cursor)
|
||||
if not jobs:
|
||||
|
@ -258,7 +258,7 @@ class IndeedScraper(Scraper):
|
|||
company_num_employees=employer_details.get("employeesLocalizedLabel"),
|
||||
company_revenue=employer_details.get("revenueLocalizedLabel"),
|
||||
company_description=employer_details.get("briefDescription"),
|
||||
logo_photo_url=(
|
||||
company_logo=(
|
||||
employer["images"].get("squareLogoUrl")
|
||||
if employer and employer.get("images")
|
||||
else None
|
||||
|
|
|
@ -232,7 +232,7 @@ class LinkedInScraper(Scraper):
|
|||
description=job_details.get("description"),
|
||||
job_url_direct=job_details.get("job_url_direct"),
|
||||
emails=extract_emails_from_text(job_details.get("description")),
|
||||
logo_photo_url=job_details.get("logo_photo_url"),
|
||||
company_logo=job_details.get("company_logo"),
|
||||
job_function=job_details.get("job_function"),
|
||||
)
|
||||
|
||||
|
@ -275,7 +275,7 @@ class LinkedInScraper(Scraper):
|
|||
if job_function_span:
|
||||
job_function = job_function_span.text.strip()
|
||||
|
||||
logo_photo_url = (
|
||||
company_logo = (
|
||||
logo_image.get("data-delayed-url")
|
||||
if (logo_image := soup.find("img", {"class": "artdeco-entity-image"}))
|
||||
else None
|
||||
|
@ -286,7 +286,7 @@ class LinkedInScraper(Scraper):
|
|||
"company_industry": self._parse_company_industry(soup),
|
||||
"job_type": self._parse_job_type(soup),
|
||||
"job_url_direct": self._parse_job_url_direct(soup),
|
||||
"logo_photo_url": logo_photo_url,
|
||||
"company_logo": company_logo,
|
||||
"job_function": job_function,
|
||||
}
|
||||
|
||||
|
|
|
@ -264,3 +264,22 @@ def extract_salary(
|
|||
else:
|
||||
return interval, min_salary, max_salary, "USD"
|
||||
return None, None, None, None
|
||||
|
||||
|
||||
def extract_job_type(description: str):
|
||||
if not description:
|
||||
return []
|
||||
|
||||
keywords = {
|
||||
JobType.FULL_TIME: r"full\s?time",
|
||||
JobType.PART_TIME: r"part\s?time",
|
||||
JobType.INTERNSHIP: r"internship",
|
||||
JobType.CONTRACT: r"contract",
|
||||
}
|
||||
|
||||
listing_types = []
|
||||
for key, pattern in keywords.items():
|
||||
if re.search(pattern, description, re.IGNORECASE):
|
||||
listing_types.append(key)
|
||||
|
||||
return listing_types if listing_types else None
|
||||
|
|
|
@ -0,0 +1,12 @@
|
|||
from jobspy import scrape_jobs
|
||||
import pandas as pd
|
||||
|
||||
|
||||
def test_google():
|
||||
result = scrape_jobs(
|
||||
site_name="google", search_term="software engineer", results_wanted=5
|
||||
)
|
||||
|
||||
assert (
|
||||
isinstance(result, pd.DataFrame) and len(result) == 5
|
||||
), "Result should be a non-empty DataFrame"
|
Loading…
Reference in New Issue