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8 Commits
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eed7fca300 |
@@ -7,9 +7,6 @@
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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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||||
|
||||
Check out another project we wrote: ***[HomeHarvest](https://github.com/Bunsly/HomeHarvest)** – a Python package
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for real estate scraping*
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## Features
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- Scrapes job postings from **LinkedIn**, **Indeed**, **Glassdoor**, & **ZipRecruiter** simultaneously
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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 = "1.1.28"
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version = "1.1.33"
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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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@@ -55,18 +55,24 @@ class JobType(Enum):
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class Country(Enum):
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ARGENTINA = ("argentina", "com.ar")
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"""
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Gets the subdomain for Indeed and Glassdoor.
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The second item in the tuple is the subdomain for Indeed
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The third item in the tuple is the subdomain (and tld if there's a ':' separator) for Glassdoor
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"""
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ARGENTINA = ("argentina", "ar", "com.ar")
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AUSTRALIA = ("australia", "au", "com.au")
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AUSTRIA = ("austria", "at", "at")
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BAHRAIN = ("bahrain", "bh")
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BELGIUM = ("belgium", "be", "nl:be")
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BELGIUM = ("belgium", "be", "fr:be")
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BRAZIL = ("brazil", "br", "com.br")
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CANADA = ("canada", "ca", "ca")
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CHILE = ("chile", "cl")
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CHINA = ("china", "cn")
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COLOMBIA = ("colombia", "co")
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COSTARICA = ("costa rica", "cr")
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CZECHREPUBLIC = ("czech republic", "cz")
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CZECHREPUBLIC = ("czech republic,czechia", "cz")
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DENMARK = ("denmark", "dk")
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ECUADOR = ("ecuador", "ec")
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EGYPT = ("egypt", "eg")
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@@ -112,8 +118,8 @@ class Country(Enum):
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TURKEY = ("turkey", "tr")
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UKRAINE = ("ukraine", "ua")
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UNITEDARABEMIRATES = ("united arab emirates", "ae")
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UK = ("uk", "uk", "co.uk")
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USA = ("usa", "www", "com")
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UK = ("uk,united kingdom", "uk", "co.uk")
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USA = ("usa,us,united states", "www", "com")
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URUGUAY = ("uruguay", "uy")
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VENEZUELA = ("venezuela", "ve")
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VIETNAM = ("vietnam", "vn")
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@@ -121,7 +127,7 @@ class Country(Enum):
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# internal for ziprecruiter
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US_CANADA = ("usa/ca", "www")
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# internal for linkeind
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# internal for linkedin
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WORLDWIDE = ("worldwide", "www")
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@property
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@@ -147,7 +153,8 @@ class Country(Enum):
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"""Convert a string to the corresponding Country enum."""
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country_str = country_str.strip().lower()
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for country in cls:
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if country.value[0] == country_str:
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country_names = country.value[0].split(',')
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if country_str in country_names:
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return country
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valid_countries = [country.value for country in cls]
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raise ValueError(
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@@ -167,10 +174,13 @@ class Location(BaseModel):
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if self.state:
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location_parts.append(self.state)
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if self.country and self.country not in (Country.US_CANADA, Country.WORLDWIDE):
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if self.country.value[0] in ("usa", "uk"):
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location_parts.append(self.country.value[0].upper())
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country_name = self.country.value[0]
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if "," in country_name:
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country_name = country_name.split(",")[0]
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if country_name in ("usa", "uk"):
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location_parts.append(country_name.upper())
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else:
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location_parts.append(self.country.value[0].title())
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location_parts.append(country_name.title())
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return ", ".join(location_parts)
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@@ -181,6 +191,10 @@ class CompensationInterval(Enum):
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DAILY = "daily"
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HOURLY = "hourly"
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@classmethod
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def get_interval(cls, pay_period):
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return cls[pay_period].value if pay_period in cls.__members__ else None
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class Compensation(BaseModel):
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interval: Optional[CompensationInterval] = None
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@@ -4,17 +4,13 @@ jobspy.scrapers.glassdoor
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This module contains routines to scrape Glassdoor.
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"""
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import math
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import time
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import re
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import json
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from datetime import datetime, date
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from typing import Optional, Tuple, Any
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from bs4 import BeautifulSoup
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from typing import Optional, Any
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from datetime import datetime, timedelta
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from .. import Scraper, ScraperInput, Site
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from ..exceptions import GlassdoorException
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from ..utils import count_urgent_words, extract_emails_from_text, create_session
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from ..utils import create_session
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from ...jobs import (
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JobPost,
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Compensation,
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@@ -22,7 +18,6 @@ from ...jobs import (
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Location,
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JobResponse,
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JobType,
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Country,
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)
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@@ -31,7 +26,7 @@ class GlassdoorScraper(Scraper):
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"""
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Initializes GlassdoorScraper with the Glassdoor job search url
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"""
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site = Site(Site.ZIP_RECRUITER)
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site = Site(Site.GLASSDOOR)
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super().__init__(site, proxy=proxy)
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self.url = None
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@@ -49,15 +44,12 @@ class GlassdoorScraper(Scraper):
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) -> (list[JobPost], str | None):
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"""
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Scrapes a page of Glassdoor for jobs with scraper_input criteria
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:param scraper_input:
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:return: jobs found on page
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:return: cursor for next page
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"""
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try:
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payload = self.add_payload(
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scraper_input, location_id, location_type, page_num, cursor
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)
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session = create_session(self.proxy, is_tls=False)
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session = create_session(self.proxy, is_tls=False, has_retry=True)
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response = session.post(
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f"{self.url}/graph", headers=self.headers(), timeout=10, data=payload
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)
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@@ -86,8 +78,9 @@ class GlassdoorScraper(Scraper):
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company_name = job["header"]["employerNameFromSearch"]
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location_name = job["header"].get("locationName", "")
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location_type = job["header"].get("locationType", "")
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is_remote = False
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location = None
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age_in_days = job["header"].get("ageInDays")
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is_remote, location = False, None
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date_posted = (datetime.now() - timedelta(days=age_in_days)).date() if age_in_days else None
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if location_type == "S":
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is_remote = True
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@@ -99,10 +92,11 @@ class GlassdoorScraper(Scraper):
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job = JobPost(
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title=title,
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company_name=company_name,
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date_posted=date_posted,
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job_url=job_url,
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location=location,
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compensation=compensation,
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is_remote=is_remote,
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is_remote=is_remote
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)
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jobs.append(job)
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@@ -161,15 +155,8 @@ class GlassdoorScraper(Scraper):
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interval = None
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if pay_period == "ANNUAL":
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interval = CompensationInterval.YEARLY
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elif pay_period == "MONTHLY":
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interval = CompensationInterval.MONTHLY
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elif pay_period == "WEEKLY":
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interval = CompensationInterval.WEEKLY
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elif pay_period == "DAILY":
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interval = CompensationInterval.DAILY
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elif pay_period == "HOURLY":
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interval = CompensationInterval.HOURLY
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elif pay_period:
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interval = CompensationInterval.get_interval(pay_period)
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min_amount = int(adjusted_pay.get("p10") // 1)
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max_amount = int(adjusted_pay.get("p90") // 1)
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@@ -180,17 +167,11 @@ class GlassdoorScraper(Scraper):
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currency=currency,
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)
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def get_job_type_enum(self, job_type_str: str) -> list[JobType] | None:
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for job_type in JobType:
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if job_type_str in job_type.value:
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return [job_type]
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return None
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||||
def get_location(self, location: str, is_remote: bool) -> (int, str):
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if not location or is_remote:
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return "11047", "STATE" # remote options
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url = f"{self.url}/findPopularLocationAjax.htm?maxLocationsToReturn=10&term={location}"
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session = create_session(self.proxy)
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session = create_session(self.proxy, has_retry=True)
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response = session.get(url)
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if response.status_code != 200:
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raise GlassdoorException(
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@@ -213,7 +194,7 @@ class GlassdoorScraper(Scraper):
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location_type: str,
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||||
page_num: int,
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||||
cursor: str | None = None,
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||||
) -> dict[str, str | Any]:
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||||
) -> str:
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payload = {
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"operationName": "JobSearchResultsQuery",
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"variables": {
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||||
@@ -243,10 +224,17 @@ class GlassdoorScraper(Scraper):
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payload["variables"]["filterParams"].append(
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{"filterKey": "jobType", "values": filter_value}
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||||
)
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return json.dumps([payload])
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||||
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||||
def parse_location(self, location_name: str) -> Location:
|
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@staticmethod
|
||||
def get_job_type_enum(job_type_str: str) -> list[JobType] | None:
|
||||
for job_type in JobType:
|
||||
if job_type_str in job_type.value:
|
||||
return [job_type]
|
||||
return None
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||||
|
||||
@staticmethod
|
||||
def parse_location(location_name: str) -> Location:
|
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if not location_name or location_name == "Remote":
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return None
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city, _, state = location_name.partition(", ")
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||||
@@ -64,6 +64,7 @@ class IndeedScraper(Scraper):
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"l": scraper_input.location,
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"filter": 0,
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"start": scraper_input.offset + page * 10,
|
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"sort": "date"
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||||
}
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if scraper_input.distance:
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params["radius"] = scraper_input.distance
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||||
@@ -150,6 +151,7 @@ class IndeedScraper(Scraper):
|
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title=job["normTitle"],
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description=description,
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company_name=job["company"],
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company_url=self.url + job["companyOverviewLink"] if "companyOverviewLink" in job else None,
|
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location=Location(
|
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city=job.get("jobLocationCity"),
|
||||
state=job.get("jobLocationState"),
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||||
@@ -235,24 +237,9 @@ class IndeedScraper(Scraper):
|
||||
if response.status_code not in range(200, 400):
|
||||
return None
|
||||
|
||||
soup = BeautifulSoup(response.text, "html.parser")
|
||||
script_tag = soup.find(
|
||||
"script", text=lambda x: x and "window._initialData" in x
|
||||
)
|
||||
|
||||
if not script_tag:
|
||||
return None
|
||||
|
||||
script_code = script_tag.string
|
||||
match = re.search(r"window\._initialData\s*=\s*({.*?})\s*;", script_code, re.S)
|
||||
|
||||
if not match:
|
||||
return None
|
||||
|
||||
json_string = match.group(1)
|
||||
data = json.loads(json_string)
|
||||
try:
|
||||
job_description = data["jobInfoWrapperModel"]["jobInfoModel"][
|
||||
data = json.loads(response.text)
|
||||
job_description = data["body"]["jobInfoWrapperModel"]["jobInfoModel"][
|
||||
"sanitizedJobDescription"
|
||||
]
|
||||
except (KeyError, TypeError, IndexError):
|
||||
@@ -320,7 +307,7 @@ class IndeedScraper(Scraper):
|
||||
raise IndeedException("Could not find mosaic provider job cards data")
|
||||
else:
|
||||
raise IndeedException(
|
||||
"Could not find a script tag containing mosaic provider data"
|
||||
"Could not find any results for the search"
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
|
||||
@@ -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'
|
||||
}
|
||||
|
||||
@@ -1,8 +1,10 @@
|
||||
import re
|
||||
import numpy as np
|
||||
|
||||
import requests
|
||||
import tls_client
|
||||
import requests
|
||||
from requests.adapters import HTTPAdapter, Retry
|
||||
|
||||
from ..jobs import JobType
|
||||
|
||||
|
||||
@@ -27,11 +29,11 @@ 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):
|
||||
def create_session(proxy: dict | None = None, is_tls: bool = True, has_retry: bool = False, delay: int = 1) -> requests.Session:
|
||||
"""
|
||||
Creates a tls client session
|
||||
Creates a requests session with optional tls, proxy, and retry settings.
|
||||
|
||||
:return: A session object with or without proxies.
|
||||
:return: A session object
|
||||
"""
|
||||
if is_tls:
|
||||
session = tls_client.Session(
|
||||
@@ -39,17 +41,21 @@ def create_session(proxy: dict | None = None, is_tls: bool = True):
|
||||
random_tls_extension_order=True,
|
||||
)
|
||||
session.proxies = proxy
|
||||
# TODO multiple proxies
|
||||
# if self.proxies:
|
||||
# session.proxies = {
|
||||
# "http": random.choice(self.proxies),
|
||||
# "https": random.choice(self.proxies),
|
||||
# }
|
||||
else:
|
||||
session = requests.Session()
|
||||
session.allow_redirects = True
|
||||
if proxy:
|
||||
session.proxies.update(proxy)
|
||||
if has_retry:
|
||||
retries = Retry(total=3,
|
||||
connect=3,
|
||||
status=3,
|
||||
status_forcelist=[500, 502, 503, 504, 429],
|
||||
backoff_factor=delay)
|
||||
adapter = HTTPAdapter(max_retries=retries)
|
||||
|
||||
session.mount('http://', adapter)
|
||||
session.mount('https://', adapter)
|
||||
|
||||
return session
|
||||
|
||||
|
||||
@@ -44,12 +44,12 @@ class ZipRecruiterScraper(Scraper):
|
||||
if continue_token:
|
||||
params["continue"] = continue_token
|
||||
try:
|
||||
session = create_session(self.proxy, is_tls=False)
|
||||
session = create_session(self.proxy, is_tls=True)
|
||||
response = session.get(
|
||||
f"https://api.ziprecruiter.com/jobs-app/jobs",
|
||||
headers=self.headers(),
|
||||
params=self.add_params(scraper_input),
|
||||
timeout=10,
|
||||
timeout_seconds=10,
|
||||
)
|
||||
if response.status_code != 200:
|
||||
raise ZipRecruiterException(
|
||||
@@ -195,17 +195,12 @@ class ZipRecruiterScraper(Scraper):
|
||||
@staticmethod
|
||||
def headers() -> dict:
|
||||
"""
|
||||
Returns headers needed for requests
|
||||
Returns headers needed for ZipRecruiter API requests
|
||||
:return: dict - Dictionary containing headers
|
||||
"""
|
||||
return {
|
||||
"Host": "api.ziprecruiter.com",
|
||||
"Cookie": "ziprecruiter_browser=018188e0-045b-4ad7-aa50-627a6c3d43aa; ziprecruiter_session=5259b2219bf95b6d2299a1417424bc2edc9f4b38; SplitSV=2016-10-19%3AU2FsdGVkX19f9%2Bx70knxc%2FeR3xXR8lWoTcYfq5QjmLU%3D%0A; __cf_bm=qXim3DtLPbOL83GIp.ddQEOFVFTc1OBGPckiHYxcz3o-1698521532-0-AfUOCkgCZyVbiW1ziUwyefCfzNrJJTTKPYnif1FZGQkT60dMowmSU/Y/lP+WiygkFPW/KbYJmyc+MQSkkad5YygYaARflaRj51abnD+SyF9V; zglobalid=68d49bd5-0326-428e-aba8-8a04b64bc67c.af2d99ff7c03.653d61bb; ziprecruiter_browser=018188e0-045b-4ad7-aa50-627a6c3d43aa; ziprecruiter_session=5259b2219bf95b6d2299a1417424bc2edc9f4b38",
|
||||
"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",
|
||||
'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'
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user