FEAT: Allow LinkedIn scraper to get external job apply url (#140)

pull/141/head^2
Lluís Salord Quetglas 2024-04-30 18:36:01 +02:00 committed by GitHub
parent 5d3df732e6
commit 8dd08ed9fd
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
6 changed files with 134 additions and 11 deletions

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@ -38,7 +38,8 @@ jobs = scrape_jobs(
location="Dallas, TX",
results_wanted=20,
hours_old=72, # (only Linkedin/Indeed is hour specific, others round up to days old)
country_indeed='USA' # only needed for indeed / glassdoor
country_indeed='USA', # only needed for indeed / glassdoor
# linkedin_fetch_description=True # get full description and direct job url for linkedin (slower)
)
print(f"Found {len(jobs)} jobs")
print(jobs.head())
@ -70,7 +71,7 @@ Optional
├── is_remote (bool)
├── results_wanted (int): number of job results to retrieve for each site specified in 'site_name'
├── easy_apply (bool): filters for jobs that are hosted on the job board site (LinkedIn & Indeed do not allow pairing this with hours_old)
├── linkedin_fetch_description (bool): fetches full description for LinkedIn (slower)
├── linkedin_fetch_description (bool): fetches full description and direct job url for LinkedIn (slower)
├── linkedin_company_ids (list[int]): searches for linkedin jobs with specific company ids
├── description_format (str): markdown, html (Format type of the job descriptions. Default is markdown.)
├── country_indeed (str): filters the country on Indeed (see below for correct spelling)

103
poetry.lock generated
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@ -1,4 +1,4 @@
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]
[[package]]
name = "requests"
version = "2.31.0"
@ -2652,4 +2751,4 @@ files = [
[metadata]
lock-version = "2.0"
python-versions = "^3.10"
content-hash = "6ee18819a726314f61f20f0ed93b2db2a26c232269f045146d9a8f4e3f31eb01"
content-hash = "39b730e5efb856178111bc6ca4bc68ad61e201e654a60c58fec2ecf8d77fc054"

View File

@ -1,6 +1,6 @@
[tool.poetry]
name = "python-jobspy"
version = "1.1.51"
version = "1.1.52"
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"
@ -19,6 +19,7 @@ NUMPY = "1.24.2"
pydantic = "^2.3.0"
tls-client = "^1.0.1"
markdownify = "^0.11.6"
regex = "^2024.4.28"
[tool.poetry.group.dev.dependencies]

View File

@ -119,7 +119,7 @@ class IndeedScraper(Scraper):
)
if response.status_code != 200:
logger.info(
f"Indeed responded with status code: {response.status_code} (submit GitHub issue if this appears to be a beg)"
f"Indeed responded with status code: {response.status_code} (submit GitHub issue if this appears to be a bug)"
)
return jobs, new_cursor
data = response.json()

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@ -9,6 +9,8 @@ from __future__ import annotations
import time
import random
import regex as re
import urllib.parse
from typing import Optional
from datetime import datetime
@ -51,6 +53,7 @@ class LinkedInScraper(Scraper):
super().__init__(Site(Site.LINKEDIN), proxy=proxy)
self.scraper_input = None
self.country = "worldwide"
self.job_url_direct_regex = re.compile(r'(?<=\?url=)[^"]+')
def scrape(self, scraper_input: ScraperInput) -> JobResponse:
"""
@ -194,16 +197,15 @@ class LinkedInScraper(Scraper):
if metadata_card
else None
)
date_posted = description = job_type = None
date_posted = description = job_type = job_url_direct = None
if datetime_tag and "datetime" in datetime_tag.attrs:
datetime_str = datetime_tag["datetime"]
try:
date_posted = datetime.strptime(datetime_str, "%Y-%m-%d")
except:
date_posted = None
benefits_tag = job_card.find("span", class_="result-benefits__text")
if full_descr:
description, job_type = self._get_job_description(job_url)
description, job_type, job_url_direct = self._get_job_description(job_url)
return JobPost(
title=title,
@ -212,6 +214,7 @@ class LinkedInScraper(Scraper):
location=location,
date_posted=date_posted,
job_url=job_url,
job_url_direct=job_url_direct,
compensation=compensation,
job_type=job_type,
description=description,
@ -220,7 +223,9 @@ class LinkedInScraper(Scraper):
def _get_job_description(
self, job_page_url: str
) -> tuple[None, None] | tuple[str | None, tuple[str | None, JobType | None]]:
) -> tuple[None, None, None] | tuple[
str | None, tuple[str | None, JobType | None], str | None
]:
"""
Retrieves job description by going to the job page url
:param job_page_url:
@ -253,7 +258,7 @@ class LinkedInScraper(Scraper):
description = div_content.prettify(formatter="html")
if self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
description = markdown_converter(description)
return description, self._parse_job_type(soup)
return description, self._parse_job_type(soup), self._parse_job_url_direct(soup)
def _get_location(self, metadata_card: Optional[Tag]) -> Location:
"""
@ -306,6 +311,23 @@ class LinkedInScraper(Scraper):
return [get_enum_from_job_type(employment_type)] if employment_type else []
def _parse_job_url_direct(self, soup: BeautifulSoup) -> str | None:
"""
Gets the job url direct from job page
:param soup:
:return: str
"""
job_url_direct = None
job_url_direct_content = soup.find("code", id="applyUrl")
if job_url_direct_content:
job_url_direct_match = self.job_url_direct_regex.search(
job_url_direct_content.decode_contents().strip()
)
if job_url_direct_match:
job_url_direct = urllib.parse.unquote(job_url_direct_match.group())
return job_url_direct
@staticmethod
def job_type_code(job_type_enum: JobType) -> str:
return {

0
test.py Normal file
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