mirror of https://github.com/Bunsly/JobSpy
refactor:organize code
Cullen Watson
parent
df70d4bc2e
commit
4ec308a302
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@ -1,50 +1,33 @@
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name: Publish Python 🐍 distributions 📦 to PyPI
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on:
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pull_request:
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types:
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- closed
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permissions:
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contents: write
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name: Publish JobSpy to PyPi
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on: push
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jobs:
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build-n-publish:
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name: Build and publish Python 🐍 distributions 📦 to PyPI
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name: Build and publish JobSpy to PyPi
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runs-on: ubuntu-latest
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if: github.event.pull_request.merged == true && github.event.pull_request.base.ref == 'main'
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steps:
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- uses: actions/checkout@v3
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- name: Set up Python
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uses: actions/setup-python@v4
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with:
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python-version: "3.10"
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- name: Install dependencies
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run: pip install toml
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- name: Increment version
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run: python increment_version.py
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- name: Commit version increment
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run: |
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git config --global user.name 'github-actions'
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git config --global user.email 'github-actions@github.com'
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git add pyproject.toml
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git commit -m 'Increment version'
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- name: Push changes
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run: git push
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- name: Install poetry
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run: pip install poetry --user
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run: >-
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python3 -m
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pip install
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poetry
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--user
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- name: Build distribution 📦
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run: poetry build
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run: >-
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python3 -m
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poetry
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build
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- name: Publish distribution 📦 to PyPI
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if: startsWith(github.ref, 'refs/tags')
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uses: pypa/gh-action-pypi-publish@release/v1
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with:
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password: ${{ secrets.PYPI_API_TOKEN }}
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@ -1,21 +0,0 @@
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import toml
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def increment_version(version):
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major, minor, patch = map(int, version.split('.'))
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patch += 1
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return f"{major}.{minor}.{patch}"
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# Load pyproject.toml
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with open('pyproject.toml', 'r') as file:
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pyproject = toml.load(file)
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# Increment the version
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current_version = pyproject['tool']['poetry']['version']
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new_version = increment_version(current_version)
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pyproject['tool']['poetry']['version'] = new_version
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# Save the updated pyproject.toml
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with open('pyproject.toml', 'w') as file:
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toml.dump(pyproject, file)
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print(f"Version updated from {current_version} to {new_version}")
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@ -1,25 +1,27 @@
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from __future__ import annotations
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import pandas as pd
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from typing import Tuple
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from concurrent.futures import ThreadPoolExecutor, as_completed
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from typing import Tuple
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from .jobs import JobType, Location
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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.bayt import BaytScraper
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from .scrapers import SalarySource, ScraperInput, Site, JobResponse, Country
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from .scrapers.exceptions import (
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LinkedInException,
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IndeedException,
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ZipRecruiterException,
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GlassdoorException,
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GoogleJobsException,
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import pandas as pd
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from jobspy.bayt import BaytScraper
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from jobspy.glassdoor import Glassdoor
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from jobspy.google import Google
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from jobspy.indeed import Indeed
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from jobspy.linkedin import LinkedIn
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from jobspy.model import JobType, Location, JobResponse, Country
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from jobspy.model import SalarySource, ScraperInput, Site
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from jobspy.util import (
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set_logger_level,
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extract_salary,
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create_logger,
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get_enum_from_value,
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map_str_to_site,
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convert_to_annual,
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desired_order,
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)
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from jobspy.ziprecruiter import ZipRecruiter
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def scrape_jobs(
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@ -33,7 +35,6 @@ def scrape_jobs(
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easy_apply: bool | None = None,
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results_wanted: int = 15,
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country_indeed: str = "usa",
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hyperlinks: bool = False,
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proxies: list[str] | str | None = None,
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ca_cert: str | None = None,
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description_format: str = "markdown",
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@ -46,28 +47,18 @@ def scrape_jobs(
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**kwargs,
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) -> pd.DataFrame:
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"""
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Simultaneously scrapes job data from multiple job sites.
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:return: pandas dataframe containing job data
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Scrapes job data from job boards concurrently
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:return: Pandas DataFrame containing job data
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"""
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SCRAPER_MAPPING = {
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Site.LINKEDIN: LinkedInScraper,
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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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Site.LINKEDIN: LinkedIn,
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Site.INDEED: Indeed,
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Site.ZIP_RECRUITER: ZipRecruiter,
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Site.GLASSDOOR: Glassdoor,
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Site.GOOGLE: Google,
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Site.BAYT: BaytScraper,
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}
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set_logger_level(verbose)
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def map_str_to_site(site_name: str) -> Site:
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return Site[site_name.upper()]
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def get_enum_from_value(value_str):
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for job_type in JobType:
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if value_str in job_type.value:
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return job_type
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raise Exception(f"Invalid job type: {value_str}")
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job_type = get_enum_from_value(job_type) if job_type else None
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def get_site_type():
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@ -127,28 +118,12 @@ def scrape_jobs(
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site_value, scraped_data = future.result()
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site_to_jobs_dict[site_value] = scraped_data
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def convert_to_annual(job_data: dict):
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if job_data["interval"] == "hourly":
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job_data["min_amount"] *= 2080
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job_data["max_amount"] *= 2080
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if job_data["interval"] == "monthly":
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job_data["min_amount"] *= 12
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job_data["max_amount"] *= 12
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if job_data["interval"] == "weekly":
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job_data["min_amount"] *= 52
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job_data["max_amount"] *= 52
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if job_data["interval"] == "daily":
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job_data["min_amount"] *= 260
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job_data["max_amount"] *= 260
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job_data["interval"] = "yearly"
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jobs_dfs: list[pd.DataFrame] = []
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for site, job_response in site_to_jobs_dict.items():
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for job in job_response.jobs:
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job_data = job.dict()
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job_url = job_data["job_url"]
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job_data["job_url_hyper"] = f'<a href="{job_url}">{job_url}</a>'
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job_data["site"] = site
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job_data["company"] = job_data["company_name"]
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job_data["job_type"] = (
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@ -211,38 +186,6 @@ def scrape_jobs(
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# Step 2: Concatenate the filtered DataFrames
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jobs_df = pd.concat(filtered_dfs, ignore_index=True)
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# Desired column order
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desired_order = [
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"id",
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"site",
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"job_url_hyper" if hyperlinks else "job_url",
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"job_url_direct",
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"title",
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"company",
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"location",
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"date_posted",
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"job_type",
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"salary_source",
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"interval",
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"min_amount",
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"max_amount",
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"currency",
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"is_remote",
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"job_level",
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"job_function",
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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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"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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"company_revenue",
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"company_description",
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]
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# Step 3: Ensure all desired columns are present, adding missing ones as empty
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for column in desired_order:
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if column not in jobs_df.columns:
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@ -1,10 +1,3 @@
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"""
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jobspy.scrapers.bayt
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~~~~~~~~~~~~~~~~~~~
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This module contains routines to scrape Bayt.
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"""
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from __future__ import annotations
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import random
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@ -12,9 +5,16 @@ import time
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from bs4 import BeautifulSoup
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from .. import Scraper, ScraperInput, Site
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from ..utils import create_logger, create_session
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from ...jobs import JobPost, JobResponse, Location, Country
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from jobspy.model import (
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Scraper,
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ScraperInput,
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Site,
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JobPost,
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JobResponse,
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Location,
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Country,
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)
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from jobspy.util import create_logger, create_session
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log = create_logger("Bayt")
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@ -1,5 +1,5 @@
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"""
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jobspy.scrapers.exceptions
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jobspy.jobboard.exceptions
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~~~~~~~~~~~~~~~~~~~
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This module contains the set of Scrapers' exceptions.
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"""
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jobspy.scrapers.glassdoor
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~~~~~~~~~~~~~~~~~~~
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This module contains routines to scrape Glassdoor.
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"""
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from __future__ import annotations
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import re
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import json
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import requests
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from typing import Optional, Tuple
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from typing import Tuple
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from datetime import datetime, timedelta
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from concurrent.futures import ThreadPoolExecutor, as_completed
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from .constants import fallback_token, query_template, headers
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from .. import Scraper, ScraperInput, Site
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from ..utils import extract_emails_from_text, create_logger
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from ..exceptions import GlassdoorException
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from ..utils import (
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from jobspy.glassdoor.constant import fallback_token, query_template, headers
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from jobspy.glassdoor.util import (
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get_cursor_for_page,
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parse_compensation,
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parse_location,
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)
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from jobspy.util import (
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extract_emails_from_text,
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create_logger,
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create_session,
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markdown_converter,
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)
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from ...jobs import (
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from jobspy.exception import GlassdoorException
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from jobspy.model import (
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JobPost,
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Compensation,
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CompensationInterval,
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Location,
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JobResponse,
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JobType,
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DescriptionFormat,
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Scraper,
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ScraperInput,
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Site,
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)
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log = create_logger("Glassdoor")
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class GlassdoorScraper(Scraper):
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class Glassdoor(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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@ -146,7 +143,7 @@ class GlassdoorScraper(Scraper):
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except Exception as exc:
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raise GlassdoorException(f"Glassdoor generated an exception: {exc}")
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return jobs, self.get_cursor_for_page(
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return jobs, get_cursor_for_page(
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res_json["data"]["jobListings"]["paginationCursors"], page_num + 1
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)
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@ -185,9 +182,9 @@ class GlassdoorScraper(Scraper):
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if location_type == "S":
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is_remote = True
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else:
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location = self.parse_location(location_name)
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location = parse_location(location_name)
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compensation = self.parse_compensation(job["header"])
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compensation = parse_compensation(job["header"])
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try:
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description = self._fetch_job_description(job_id)
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except:
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@ -321,44 +318,3 @@ class GlassdoorScraper(Scraper):
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{"filterKey": "jobType", "values": self.scraper_input.job_type.value[0]}
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)
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return json.dumps([payload])
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@staticmethod
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def parse_compensation(data: dict) -> Optional[Compensation]:
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pay_period = data.get("payPeriod")
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adjusted_pay = data.get("payPeriodAdjustedPay")
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currency = data.get("payCurrency", "USD")
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if not pay_period or not adjusted_pay:
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return None
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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:
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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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return Compensation(
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interval=interval,
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min_amount=min_amount,
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max_amount=max_amount,
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currency=currency,
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)
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@staticmethod
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def get_job_type_enum(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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@staticmethod
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def parse_location(location_name: str) -> Location | None:
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if not location_name or location_name == "Remote":
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return
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city, _, state = location_name.partition(", ")
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return Location(city=city, state=state)
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@staticmethod
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def get_cursor_for_page(pagination_cursors, page_num):
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for cursor_data in pagination_cursors:
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if cursor_data["pageNumber"] == page_num:
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return cursor_data["cursor"]
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@ -0,0 +1,42 @@
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from jobspy.model import Compensation, CompensationInterval, Location, JobType
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def parse_compensation(data: dict) -> Compensation | None:
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pay_period = data.get("payPeriod")
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adjusted_pay = data.get("payPeriodAdjustedPay")
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currency = data.get("payCurrency", "USD")
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if not pay_period or not adjusted_pay:
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return None
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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:
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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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return Compensation(
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interval=interval,
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min_amount=min_amount,
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max_amount=max_amount,
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currency=currency,
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)
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def get_job_type_enum(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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def parse_location(location_name: str) -> Location | None:
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if not location_name or location_name == "Remote":
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return
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city, _, state = location_name.partition(", ")
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return Location(city=city, state=state)
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def get_cursor_for_page(pagination_cursors, page_num):
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for cursor_data in pagination_cursors:
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if cursor_data["pageNumber"] == page_num:
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return cursor_data["cursor"]
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|
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@ -1,10 +1,3 @@
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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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@ -13,23 +6,21 @@ 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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from jobspy.google.constant import headers_jobs, headers_initial, async_param
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from jobspy.model import (
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Scraper,
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ScraperInput,
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Site,
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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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log = create_logger("Google")
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from jobspy.util import extract_emails_from_text, extract_job_type, create_session
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from jobspy.google.util import log, find_job_info_initial_page, find_job_info
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class GoogleJobsScraper(Scraper):
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class Google(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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@ -135,7 +126,7 @@ class GoogleJobsScraper(Scraper):
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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)
|
||||
data_async_fc = match_fc.group(1) if match_fc else None
|
||||
jobs_raw = self._find_job_info_initial_page(response.text)
|
||||
jobs_raw = find_job_info_initial_page(response.text)
|
||||
jobs = []
|
||||
for job_raw in jobs_raw:
|
||||
job_post = self._parse_job(job_raw)
|
||||
|
|
@ -167,7 +158,7 @@ class GoogleJobsScraper(Scraper):
|
|||
continue
|
||||
job_d = json.loads(job_data)
|
||||
|
||||
job_info = self._find_job_info(job_d)
|
||||
job_info = find_job_info(job_d)
|
||||
job_post = self._parse_job(job_info)
|
||||
if job_post:
|
||||
jobs_on_page.append(job_post)
|
||||
|
|
@ -209,39 +200,3 @@ class GoogleJobsScraper(Scraper):
|
|||
job_type=extract_job_type(description),
|
||||
)
|
||||
return job_post
|
||||
|
||||
@staticmethod
|
||||
def _find_job_info(jobs_data: list | dict) -> list | None:
|
||||
"""Iterates through the JSON data to find the job listings"""
|
||||
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
|
||||
|
||||
@staticmethod
|
||||
def _find_job_info_initial_page(html_text: str):
|
||||
pattern = f'520084652":(' + r"\[.*?\]\s*])\s*}\s*]\s*]\s*]\s*]\s*]"
|
||||
results = []
|
||||
matches = re.finditer(pattern, html_text)
|
||||
|
||||
import json
|
||||
|
||||
for match in matches:
|
||||
try:
|
||||
parsed_data = json.loads(match.group(1))
|
||||
results.append(parsed_data)
|
||||
|
||||
except json.JSONDecodeError as e:
|
||||
log.error(f"Failed to parse match: {str(e)}")
|
||||
results.append({"raw_match": match.group(0), "error": str(e)})
|
||||
return results
|
||||
|
|
@ -0,0 +1,41 @@
|
|||
import re
|
||||
|
||||
from jobspy.util import create_logger
|
||||
|
||||
log = create_logger("Google")
|
||||
|
||||
|
||||
def find_job_info(jobs_data: list | dict) -> list | None:
|
||||
"""Iterates through the JSON data to find the job listings"""
|
||||
if isinstance(jobs_data, dict):
|
||||
for key, value in jobs_data.items():
|
||||
if key == "520084652" and isinstance(value, list):
|
||||
return value
|
||||
else:
|
||||
result = find_job_info(value)
|
||||
if result:
|
||||
return result
|
||||
elif isinstance(jobs_data, list):
|
||||
for item in jobs_data:
|
||||
result = find_job_info(item)
|
||||
if result:
|
||||
return result
|
||||
return None
|
||||
|
||||
|
||||
def find_job_info_initial_page(html_text: str):
|
||||
pattern = f'520084652":(' + r"\[.*?\]\s*])\s*}\s*]\s*]\s*]\s*]\s*]"
|
||||
results = []
|
||||
matches = re.finditer(pattern, html_text)
|
||||
|
||||
import json
|
||||
|
||||
for match in matches:
|
||||
try:
|
||||
parsed_data = json.loads(match.group(1))
|
||||
results.append(parsed_data)
|
||||
|
||||
except json.JSONDecodeError as e:
|
||||
log.error(f"Failed to parse match: {str(e)}")
|
||||
results.append({"raw_match": match.group(0), "error": str(e)})
|
||||
return results
|
||||
|
|
@ -1,39 +1,32 @@
|
|||
"""
|
||||
jobspy.scrapers.indeed
|
||||
~~~~~~~~~~~~~~~~~~~
|
||||
|
||||
This module contains routines to scrape Indeed.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import math
|
||||
from typing import Tuple
|
||||
from datetime import datetime
|
||||
from typing import Tuple
|
||||
|
||||
from .constants import job_search_query, api_headers
|
||||
from .. import Scraper, ScraperInput, Site
|
||||
from ..utils import (
|
||||
extract_emails_from_text,
|
||||
get_enum_from_job_type,
|
||||
markdown_converter,
|
||||
create_session,
|
||||
create_logger,
|
||||
)
|
||||
from ...jobs import (
|
||||
from jobspy.indeed.constant import job_search_query, api_headers
|
||||
from jobspy.indeed.util import is_job_remote, get_compensation, get_job_type
|
||||
from jobspy.model import (
|
||||
Scraper,
|
||||
ScraperInput,
|
||||
Site,
|
||||
JobPost,
|
||||
Compensation,
|
||||
CompensationInterval,
|
||||
Location,
|
||||
JobResponse,
|
||||
JobType,
|
||||
DescriptionFormat,
|
||||
)
|
||||
from jobspy.util import (
|
||||
extract_emails_from_text,
|
||||
markdown_converter,
|
||||
create_session,
|
||||
create_logger,
|
||||
)
|
||||
|
||||
log = create_logger("Indeed")
|
||||
|
||||
|
||||
class IndeedScraper(Scraper):
|
||||
class Indeed(Scraper):
|
||||
def __init__(
|
||||
self, proxies: list[str] | str | None = None, ca_cert: str | None = None
|
||||
):
|
||||
|
|
@ -213,7 +206,7 @@ class IndeedScraper(Scraper):
|
|||
if self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
|
||||
description = markdown_converter(description)
|
||||
|
||||
job_type = self._get_job_type(job["attributes"])
|
||||
job_type = get_job_type(job["attributes"])
|
||||
timestamp_seconds = job["datePublished"] / 1000
|
||||
date_posted = datetime.fromtimestamp(timestamp_seconds).strftime("%Y-%m-%d")
|
||||
employer = job["employer"].get("dossier") if job["employer"] else None
|
||||
|
|
@ -234,14 +227,14 @@ class IndeedScraper(Scraper):
|
|||
country=job.get("location", {}).get("countryCode"),
|
||||
),
|
||||
job_type=job_type,
|
||||
compensation=self._get_compensation(job["compensation"]),
|
||||
compensation=get_compensation(job["compensation"]),
|
||||
date_posted=date_posted,
|
||||
job_url=job_url,
|
||||
job_url_direct=(
|
||||
job["recruit"].get("viewJobUrl") if job.get("recruit") else None
|
||||
),
|
||||
emails=extract_emails_from_text(description) if description else None,
|
||||
is_remote=self._is_job_remote(job, description),
|
||||
is_remote=is_job_remote(job, description),
|
||||
company_addresses=(
|
||||
employer_details["addresses"][0]
|
||||
if employer_details.get("addresses")
|
||||
|
|
@ -265,86 +258,3 @@ class IndeedScraper(Scraper):
|
|||
else None
|
||||
),
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def _get_job_type(attributes: list) -> list[JobType]:
|
||||
"""
|
||||
Parses the attributes to get list of job types
|
||||
:param attributes:
|
||||
:return: list of JobType
|
||||
"""
|
||||
job_types: list[JobType] = []
|
||||
for attribute in attributes:
|
||||
job_type_str = attribute["label"].replace("-", "").replace(" ", "").lower()
|
||||
job_type = get_enum_from_job_type(job_type_str)
|
||||
if job_type:
|
||||
job_types.append(job_type)
|
||||
return job_types
|
||||
|
||||
@staticmethod
|
||||
def _get_compensation(compensation: dict) -> Compensation | None:
|
||||
"""
|
||||
Parses the job to get compensation
|
||||
:param job:
|
||||
:return: compensation object
|
||||
"""
|
||||
if not compensation["baseSalary"] and not compensation["estimated"]:
|
||||
return None
|
||||
comp = (
|
||||
compensation["baseSalary"]
|
||||
if compensation["baseSalary"]
|
||||
else compensation["estimated"]["baseSalary"]
|
||||
)
|
||||
if not comp:
|
||||
return None
|
||||
interval = IndeedScraper._get_compensation_interval(comp["unitOfWork"])
|
||||
if not interval:
|
||||
return None
|
||||
min_range = comp["range"].get("min")
|
||||
max_range = comp["range"].get("max")
|
||||
return Compensation(
|
||||
interval=interval,
|
||||
min_amount=int(min_range) if min_range is not None else None,
|
||||
max_amount=int(max_range) if max_range is not None else None,
|
||||
currency=(
|
||||
compensation["estimated"]["currencyCode"]
|
||||
if compensation["estimated"]
|
||||
else compensation["currencyCode"]
|
||||
),
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def _is_job_remote(job: dict, description: str) -> bool:
|
||||
"""
|
||||
Searches the description, location, and attributes to check if job is remote
|
||||
"""
|
||||
remote_keywords = ["remote", "work from home", "wfh"]
|
||||
is_remote_in_attributes = any(
|
||||
any(keyword in attr["label"].lower() for keyword in remote_keywords)
|
||||
for attr in job["attributes"]
|
||||
)
|
||||
is_remote_in_description = any(
|
||||
keyword in description.lower() for keyword in remote_keywords
|
||||
)
|
||||
is_remote_in_location = any(
|
||||
keyword in job["location"]["formatted"]["long"].lower()
|
||||
for keyword in remote_keywords
|
||||
)
|
||||
return (
|
||||
is_remote_in_attributes or is_remote_in_description or is_remote_in_location
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def _get_compensation_interval(interval: str) -> CompensationInterval:
|
||||
interval_mapping = {
|
||||
"DAY": "DAILY",
|
||||
"YEAR": "YEARLY",
|
||||
"HOUR": "HOURLY",
|
||||
"WEEK": "WEEKLY",
|
||||
"MONTH": "MONTHLY",
|
||||
}
|
||||
mapped_interval = interval_mapping.get(interval.upper(), None)
|
||||
if mapped_interval and mapped_interval in CompensationInterval.__members__:
|
||||
return CompensationInterval[mapped_interval]
|
||||
else:
|
||||
raise ValueError(f"Unsupported interval: {interval}")
|
||||
|
|
@ -0,0 +1,83 @@
|
|||
from jobspy.model import CompensationInterval, JobType, Compensation
|
||||
from jobspy.util import get_enum_from_job_type
|
||||
|
||||
|
||||
def get_job_type(attributes: list) -> list[JobType]:
|
||||
"""
|
||||
Parses the attributes to get list of job types
|
||||
:param attributes:
|
||||
:return: list of JobType
|
||||
"""
|
||||
job_types: list[JobType] = []
|
||||
for attribute in attributes:
|
||||
job_type_str = attribute["label"].replace("-", "").replace(" ", "").lower()
|
||||
job_type = get_enum_from_job_type(job_type_str)
|
||||
if job_type:
|
||||
job_types.append(job_type)
|
||||
return job_types
|
||||
|
||||
|
||||
def get_compensation(compensation: dict) -> Compensation | None:
|
||||
"""
|
||||
Parses the job to get compensation
|
||||
:param sssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrompensation:
|
||||
:return: compensation object
|
||||
"""
|
||||
if not compensation["baseSalary"] and not compensation["estimated"]:
|
||||
return None
|
||||
comp = (
|
||||
compensation["baseSalary"]
|
||||
if compensation["baseSalary"]
|
||||
else compensation["estimated"]["baseSalary"]
|
||||
)
|
||||
if not comp:
|
||||
return None
|
||||
interval = get_compensation_interval(comp["unitOfWork"])
|
||||
if not interval:
|
||||
return None
|
||||
min_range = comp["range"].get("min")
|
||||
max_range = comp["range"].get("max")
|
||||
return Compensation(
|
||||
interval=interval,
|
||||
min_amount=int(min_range) if min_range is not None else None,
|
||||
max_amount=int(max_range) if max_range is not None else None,
|
||||
currency=(
|
||||
compensation["estimated"]["currencyCode"]
|
||||
if compensation["estimated"]
|
||||
else compensation["currencyCode"]
|
||||
),
|
||||
)
|
||||
|
||||
|
||||
def is_job_remote(job: dict, description: str) -> bool:
|
||||
"""
|
||||
Searches the description, location, and attributes to check if job is remote
|
||||
"""
|
||||
remote_keywords = ["remote", "work from home", "wfh"]
|
||||
is_remote_in_attributes = any(
|
||||
any(keyword in attr["label"].lower() for keyword in remote_keywords)
|
||||
for attr in job["attributes"]
|
||||
)
|
||||
is_remote_in_description = any(
|
||||
keyword in description.lower() for keyword in remote_keywords
|
||||
)
|
||||
is_remote_in_location = any(
|
||||
keyword in job["location"]["formatted"]["long"].lower()
|
||||
for keyword in remote_keywords
|
||||
)
|
||||
return is_remote_in_attributes or is_remote_in_description or is_remote_in_location
|
||||
|
||||
|
||||
def get_compensation_interval(interval: str) -> CompensationInterval:
|
||||
interval_mapping = {
|
||||
"DAY": "DAILY",
|
||||
"YEAR": "YEARLY",
|
||||
"HOUR": "HOURLY",
|
||||
"WEEK": "WEEKLY",
|
||||
"MONTH": "MONTHLY",
|
||||
}
|
||||
mapped_interval = interval_mapping.get(interval.upper(), None)
|
||||
if mapped_interval and mapped_interval in CompensationInterval.__members__:
|
||||
return CompensationInterval[mapped_interval]
|
||||
else:
|
||||
raise ValueError(f"Unsupported interval: {interval}")
|
||||
|
|
@ -1,47 +1,48 @@
|
|||
"""
|
||||
jobspy.scrapers.linkedin
|
||||
~~~~~~~~~~~~~~~~~~~
|
||||
|
||||
This module contains routines to scrape LinkedIn.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import math
|
||||
import time
|
||||
import random
|
||||
import regex as re
|
||||
from typing import Optional
|
||||
import time
|
||||
from datetime import datetime
|
||||
|
||||
from bs4.element import Tag
|
||||
from bs4 import BeautifulSoup
|
||||
from typing import Optional
|
||||
from urllib.parse import urlparse, urlunparse, unquote
|
||||
|
||||
from .constants import headers
|
||||
from .. import Scraper, ScraperInput, Site
|
||||
from ..exceptions import LinkedInException
|
||||
from ..utils import create_session, remove_attributes, create_logger
|
||||
from ...jobs import (
|
||||
import regex as re
|
||||
from bs4 import BeautifulSoup
|
||||
from bs4.element import Tag
|
||||
|
||||
from jobspy.exception import LinkedInException
|
||||
from jobspy.linkedin.constant import headers
|
||||
from jobspy.linkedin.util import (
|
||||
job_type_code,
|
||||
parse_job_type,
|
||||
parse_job_level,
|
||||
parse_company_industry,
|
||||
)
|
||||
from jobspy.model import (
|
||||
JobPost,
|
||||
Location,
|
||||
JobResponse,
|
||||
JobType,
|
||||
Country,
|
||||
Compensation,
|
||||
DescriptionFormat,
|
||||
Scraper,
|
||||
ScraperInput,
|
||||
Site,
|
||||
)
|
||||
from ..utils import (
|
||||
from jobspy.util import (
|
||||
extract_emails_from_text,
|
||||
get_enum_from_job_type,
|
||||
currency_parser,
|
||||
markdown_converter,
|
||||
create_session,
|
||||
remove_attributes,
|
||||
create_logger,
|
||||
)
|
||||
|
||||
log = create_logger("LinkedIn")
|
||||
|
||||
|
||||
class LinkedInScraper(Scraper):
|
||||
class LinkedIn(Scraper):
|
||||
base_url = "https://www.linkedin.com"
|
||||
delay = 3
|
||||
band_delay = 4
|
||||
|
|
@ -95,7 +96,7 @@ class LinkedInScraper(Scraper):
|
|||
"distance": scraper_input.distance,
|
||||
"f_WT": 2 if scraper_input.is_remote else None,
|
||||
"f_JT": (
|
||||
self.job_type_code(scraper_input.job_type)
|
||||
job_type_code(scraper_input.job_type)
|
||||
if scraper_input.job_type
|
||||
else None
|
||||
),
|
||||
|
|
@ -282,9 +283,9 @@ class LinkedInScraper(Scraper):
|
|||
)
|
||||
return {
|
||||
"description": description,
|
||||
"job_level": self._parse_job_level(soup),
|
||||
"company_industry": self._parse_company_industry(soup),
|
||||
"job_type": self._parse_job_type(soup),
|
||||
"job_level": parse_job_level(soup),
|
||||
"company_industry": parse_company_industry(soup),
|
||||
"job_type": parse_job_type(soup),
|
||||
"job_url_direct": self._parse_job_url_direct(soup),
|
||||
"company_logo": company_logo,
|
||||
"job_function": job_function,
|
||||
|
|
@ -316,77 +317,6 @@ class LinkedInScraper(Scraper):
|
|||
location = Location(city=city, state=state, country=country)
|
||||
return location
|
||||
|
||||
@staticmethod
|
||||
def _parse_job_type(soup_job_type: BeautifulSoup) -> list[JobType] | None:
|
||||
"""
|
||||
Gets the job type from job page
|
||||
:param soup_job_type:
|
||||
:return: JobType
|
||||
"""
|
||||
h3_tag = soup_job_type.find(
|
||||
"h3",
|
||||
class_="description__job-criteria-subheader",
|
||||
string=lambda text: "Employment type" in text,
|
||||
)
|
||||
employment_type = None
|
||||
if h3_tag:
|
||||
employment_type_span = h3_tag.find_next_sibling(
|
||||
"span",
|
||||
class_="description__job-criteria-text description__job-criteria-text--criteria",
|
||||
)
|
||||
if employment_type_span:
|
||||
employment_type = employment_type_span.get_text(strip=True)
|
||||
employment_type = employment_type.lower()
|
||||
employment_type = employment_type.replace("-", "")
|
||||
|
||||
return [get_enum_from_job_type(employment_type)] if employment_type else []
|
||||
|
||||
@staticmethod
|
||||
def _parse_job_level(soup_job_level: BeautifulSoup) -> str | None:
|
||||
"""
|
||||
Gets the job level from job page
|
||||
:param soup_job_level:
|
||||
:return: str
|
||||
"""
|
||||
h3_tag = soup_job_level.find(
|
||||
"h3",
|
||||
class_="description__job-criteria-subheader",
|
||||
string=lambda text: "Seniority level" in text,
|
||||
)
|
||||
job_level = None
|
||||
if h3_tag:
|
||||
job_level_span = h3_tag.find_next_sibling(
|
||||
"span",
|
||||
class_="description__job-criteria-text description__job-criteria-text--criteria",
|
||||
)
|
||||
if job_level_span:
|
||||
job_level = job_level_span.get_text(strip=True)
|
||||
|
||||
return job_level
|
||||
|
||||
@staticmethod
|
||||
def _parse_company_industry(soup_industry: BeautifulSoup) -> str | None:
|
||||
"""
|
||||
Gets the company industry from job page
|
||||
:param soup_industry:
|
||||
:return: str
|
||||
"""
|
||||
h3_tag = soup_industry.find(
|
||||
"h3",
|
||||
class_="description__job-criteria-subheader",
|
||||
string=lambda text: "Industries" in text,
|
||||
)
|
||||
industry = None
|
||||
if h3_tag:
|
||||
industry_span = h3_tag.find_next_sibling(
|
||||
"span",
|
||||
class_="description__job-criteria-text description__job-criteria-text--criteria",
|
||||
)
|
||||
if industry_span:
|
||||
industry = industry_span.get_text(strip=True)
|
||||
|
||||
return industry
|
||||
|
||||
def _parse_job_url_direct(self, soup: BeautifulSoup) -> str | None:
|
||||
"""
|
||||
Gets the job url direct from job page
|
||||
|
|
@ -403,13 +333,3 @@ class LinkedInScraper(Scraper):
|
|||
job_url_direct = unquote(job_url_direct_match.group())
|
||||
|
||||
return job_url_direct
|
||||
|
||||
@staticmethod
|
||||
def job_type_code(job_type_enum: JobType) -> str:
|
||||
return {
|
||||
JobType.FULL_TIME: "F",
|
||||
JobType.PART_TIME: "P",
|
||||
JobType.INTERNSHIP: "I",
|
||||
JobType.CONTRACT: "C",
|
||||
JobType.TEMPORARY: "T",
|
||||
}.get(job_type_enum, "")
|
||||
|
|
@ -0,0 +1,85 @@
|
|||
from bs4 import BeautifulSoup
|
||||
|
||||
from jobspy.model import JobType
|
||||
from jobspy.util import get_enum_from_job_type
|
||||
|
||||
|
||||
def job_type_code(job_type_enum: JobType) -> str:
|
||||
return {
|
||||
JobType.FULL_TIME: "F",
|
||||
JobType.PART_TIME: "P",
|
||||
JobType.INTERNSHIP: "I",
|
||||
JobType.CONTRACT: "C",
|
||||
JobType.TEMPORARY: "T",
|
||||
}.get(job_type_enum, "")
|
||||
|
||||
|
||||
def parse_job_type(soup_job_type: BeautifulSoup) -> list[JobType] | None:
|
||||
"""
|
||||
Gets the job type from job page
|
||||
:param soup_job_type:
|
||||
:return: JobType
|
||||
"""
|
||||
h3_tag = soup_job_type.find(
|
||||
"h3",
|
||||
class_="description__job-criteria-subheader",
|
||||
string=lambda text: "Employment type" in text,
|
||||
)
|
||||
employment_type = None
|
||||
if h3_tag:
|
||||
employment_type_span = h3_tag.find_next_sibling(
|
||||
"span",
|
||||
class_="description__job-criteria-text description__job-criteria-text--criteria",
|
||||
)
|
||||
if employment_type_span:
|
||||
employment_type = employment_type_span.get_text(strip=True)
|
||||
employment_type = employment_type.lower()
|
||||
employment_type = employment_type.replace("-", "")
|
||||
|
||||
return [get_enum_from_job_type(employment_type)] if employment_type else []
|
||||
|
||||
|
||||
def parse_job_level(soup_job_level: BeautifulSoup) -> str | None:
|
||||
"""
|
||||
Gets the job level from job page
|
||||
:param soup_job_level:
|
||||
:return: str
|
||||
"""
|
||||
h3_tag = soup_job_level.find(
|
||||
"h3",
|
||||
class_="description__job-criteria-subheader",
|
||||
string=lambda text: "Seniority level" in text,
|
||||
)
|
||||
job_level = None
|
||||
if h3_tag:
|
||||
job_level_span = h3_tag.find_next_sibling(
|
||||
"span",
|
||||
class_="description__job-criteria-text description__job-criteria-text--criteria",
|
||||
)
|
||||
if job_level_span:
|
||||
job_level = job_level_span.get_text(strip=True)
|
||||
|
||||
return job_level
|
||||
|
||||
|
||||
def parse_company_industry(soup_industry: BeautifulSoup) -> str | None:
|
||||
"""
|
||||
Gets the company industry from job page
|
||||
:param soup_industry:
|
||||
:return: str
|
||||
"""
|
||||
h3_tag = soup_industry.find(
|
||||
"h3",
|
||||
class_="description__job-criteria-subheader",
|
||||
string=lambda text: "Industries" in text,
|
||||
)
|
||||
industry = None
|
||||
if h3_tag:
|
||||
industry_span = h3_tag.find_next_sibling(
|
||||
"span",
|
||||
class_="description__job-criteria-text description__job-criteria-text--criteria",
|
||||
)
|
||||
if industry_span:
|
||||
industry = industry_span.get_text(strip=True)
|
||||
|
||||
return industry
|
||||
|
|
@ -1,5 +1,6 @@
|
|||
from __future__ import annotations
|
||||
|
||||
from abc import ABC, abstractmethod
|
||||
from typing import Optional
|
||||
from datetime import date
|
||||
from enum import Enum
|
||||
|
|
@ -265,3 +266,49 @@ class JobPost(BaseModel):
|
|||
|
||||
class JobResponse(BaseModel):
|
||||
jobs: list[JobPost] = []
|
||||
|
||||
|
||||
class Site(Enum):
|
||||
LINKEDIN = "linkedin"
|
||||
INDEED = "indeed"
|
||||
ZIP_RECRUITER = "zip_recruiter"
|
||||
GLASSDOOR = "glassdoor"
|
||||
GOOGLE = "google"
|
||||
BAYT = "bayt"
|
||||
|
||||
|
||||
class SalarySource(Enum):
|
||||
DIRECT_DATA = "direct_data"
|
||||
DESCRIPTION = "description"
|
||||
|
||||
|
||||
class ScraperInput(BaseModel):
|
||||
site_type: list[Site]
|
||||
search_term: str | None = None
|
||||
google_search_term: str | None = None
|
||||
|
||||
location: str | None = None
|
||||
country: Country | None = Country.USA
|
||||
distance: int | None = None
|
||||
is_remote: bool = False
|
||||
job_type: JobType | None = None
|
||||
easy_apply: bool | None = None
|
||||
offset: int = 0
|
||||
linkedin_fetch_description: bool = False
|
||||
linkedin_company_ids: list[int] | None = None
|
||||
description_format: DescriptionFormat | None = DescriptionFormat.MARKDOWN
|
||||
|
||||
results_wanted: int = 15
|
||||
hours_old: int | None = None
|
||||
|
||||
|
||||
class Scraper(ABC):
|
||||
def __init__(
|
||||
self, site: Site, proxies: list[str] | None = None, ca_cert: str | None = None
|
||||
):
|
||||
self.site = site
|
||||
self.proxies = proxies
|
||||
self.ca_cert = ca_cert
|
||||
|
||||
@abstractmethod
|
||||
def scrape(self, scraper_input: ScraperInput) -> JobResponse: ...
|
||||
|
|
@ -11,7 +11,7 @@ import urllib3
|
|||
from markdownify import markdownify as md
|
||||
from requests.adapters import HTTPAdapter, Retry
|
||||
|
||||
from ..jobs import CompensationInterval, JobType
|
||||
from jobspy.model import CompensationInterval, JobType, Site
|
||||
|
||||
urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
|
||||
|
||||
|
|
@ -286,3 +286,62 @@ def extract_job_type(description: str):
|
|||
listing_types.append(key)
|
||||
|
||||
return listing_types if listing_types else None
|
||||
|
||||
|
||||
def map_str_to_site(site_name: str) -> Site:
|
||||
return Site[site_name.upper()]
|
||||
|
||||
|
||||
def get_enum_from_value(value_str):
|
||||
for job_type in JobType:
|
||||
if value_str in job_type.value:
|
||||
return job_type
|
||||
raise Exception(f"Invalid job type: {value_str}")
|
||||
|
||||
|
||||
def convert_to_annual(job_data: dict):
|
||||
if job_data["interval"] == "hourly":
|
||||
job_data["min_amount"] *= 2080
|
||||
job_data["max_amount"] *= 2080
|
||||
if job_data["interval"] == "monthly":
|
||||
job_data["min_amount"] *= 12
|
||||
job_data["max_amount"] *= 12
|
||||
if job_data["interval"] == "weekly":
|
||||
job_data["min_amount"] *= 52
|
||||
job_data["max_amount"] *= 52
|
||||
if job_data["interval"] == "daily":
|
||||
job_data["min_amount"] *= 260
|
||||
job_data["max_amount"] *= 260
|
||||
job_data["interval"] = "yearly"
|
||||
|
||||
|
||||
desired_order = [
|
||||
"id",
|
||||
"site",
|
||||
"job_url",
|
||||
"job_url_direct",
|
||||
"title",
|
||||
"company",
|
||||
"location",
|
||||
"date_posted",
|
||||
"job_type",
|
||||
"salary_source",
|
||||
"interval",
|
||||
"min_amount",
|
||||
"max_amount",
|
||||
"currency",
|
||||
"is_remote",
|
||||
"job_level",
|
||||
"job_function",
|
||||
"listing_type",
|
||||
"emails",
|
||||
"description",
|
||||
"company_industry",
|
||||
"company_url",
|
||||
"company_logo",
|
||||
"company_url_direct",
|
||||
"company_addresses",
|
||||
"company_num_employees",
|
||||
"company_revenue",
|
||||
"company_description",
|
||||
]
|
||||
|
|
@ -1,10 +1,3 @@
|
|||
"""
|
||||
jobspy.scrapers.ziprecruiter
|
||||
~~~~~~~~~~~~~~~~~~~
|
||||
|
||||
This module contains routines to scrape ZipRecruiter.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
|
|
@ -13,33 +6,34 @@ import re
|
|||
import time
|
||||
from concurrent.futures import ThreadPoolExecutor
|
||||
from datetime import datetime
|
||||
from typing import Optional, Tuple, Any
|
||||
|
||||
from bs4 import BeautifulSoup
|
||||
|
||||
from .constants import headers
|
||||
from .. import Scraper, ScraperInput, Site
|
||||
from ..utils import (
|
||||
from jobspy.ziprecruiter.constant import headers, get_cookie_data
|
||||
from jobspy.util import (
|
||||
extract_emails_from_text,
|
||||
create_session,
|
||||
markdown_converter,
|
||||
remove_attributes,
|
||||
create_logger,
|
||||
)
|
||||
from ...jobs import (
|
||||
from jobspy.model import (
|
||||
JobPost,
|
||||
Compensation,
|
||||
Location,
|
||||
JobResponse,
|
||||
JobType,
|
||||
Country,
|
||||
DescriptionFormat,
|
||||
Scraper,
|
||||
ScraperInput,
|
||||
Site,
|
||||
)
|
||||
from jobspy.ziprecruiter.util import get_job_type_enum, add_params
|
||||
|
||||
log = create_logger("ZipRecruiter")
|
||||
|
||||
|
||||
class ZipRecruiterScraper(Scraper):
|
||||
class ZipRecruiter(Scraper):
|
||||
base_url = "https://www.ziprecruiter.com"
|
||||
api_url = "https://api.ziprecruiter.com"
|
||||
|
||||
|
|
@ -90,7 +84,7 @@ class ZipRecruiterScraper(Scraper):
|
|||
|
||||
def _find_jobs_in_page(
|
||||
self, scraper_input: ScraperInput, continue_token: str | None = None
|
||||
) -> Tuple[list[JobPost], Optional[str]]:
|
||||
) -> tuple[list[JobPost], str | None]:
|
||||
"""
|
||||
Scrapes a page of ZipRecruiter for jobs with scraper_input criteria
|
||||
:param scraper_input:
|
||||
|
|
@ -98,7 +92,7 @@ class ZipRecruiterScraper(Scraper):
|
|||
:return: jobs found on page
|
||||
"""
|
||||
jobs_list = []
|
||||
params = self._add_params(scraper_input)
|
||||
params = add_params(scraper_input)
|
||||
if continue_token:
|
||||
params["continue_from"] = continue_token
|
||||
try:
|
||||
|
|
@ -151,7 +145,7 @@ class ZipRecruiterScraper(Scraper):
|
|||
location = Location(
|
||||
city=job.get("job_city"), state=job.get("job_state"), country=country_enum
|
||||
)
|
||||
job_type = self._get_job_type_enum(
|
||||
job_type = get_job_type_enum(
|
||||
job.get("employment_type", "").replace("_", "").lower()
|
||||
)
|
||||
date_posted = datetime.fromisoformat(job["posted_time"].rstrip("Z")).date()
|
||||
|
|
@ -200,13 +194,17 @@ class ZipRecruiterScraper(Scraper):
|
|||
else ""
|
||||
)
|
||||
description_full = job_description_clean + company_description_clean
|
||||
script_tag = soup.find("script", type="application/json")
|
||||
if script_tag:
|
||||
job_json = json.loads(script_tag.string)
|
||||
job_url_val = job_json["model"].get("saveJobURL", "")
|
||||
m = re.search(r"job_url=(.+)", job_url_val)
|
||||
if m:
|
||||
job_url_direct = m.group(1)
|
||||
|
||||
try:
|
||||
script_tag = soup.find("script", type="application/json")
|
||||
if script_tag:
|
||||
job_json = json.loads(script_tag.string)
|
||||
job_url_val = job_json["model"].get("saveJobURL", "")
|
||||
m = re.search(r"job_url=(.+)", job_url_val)
|
||||
if m:
|
||||
job_url_direct = m.group(1)
|
||||
except:
|
||||
job_url_direct = None
|
||||
|
||||
if self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
|
||||
description_full = markdown_converter(description_full)
|
||||
|
|
@ -217,51 +215,5 @@ class ZipRecruiterScraper(Scraper):
|
|||
"""
|
||||
Sends a session event to the API with device properties.
|
||||
"""
|
||||
data = [
|
||||
("event_type", "session"),
|
||||
("logged_in", "false"),
|
||||
("number_of_retry", "1"),
|
||||
("property", "model:iPhone"),
|
||||
("property", "os:iOS"),
|
||||
("property", "locale:en_us"),
|
||||
("property", "app_build_number:4734"),
|
||||
("property", "app_version:91.0"),
|
||||
("property", "manufacturer:Apple"),
|
||||
("property", "timestamp:2025-01-12T12:04:42-06:00"),
|
||||
("property", "screen_height:852"),
|
||||
("property", "os_version:16.6.1"),
|
||||
("property", "source:install"),
|
||||
("property", "screen_width:393"),
|
||||
("property", "device_model:iPhone 14 Pro"),
|
||||
("property", "brand:Apple"),
|
||||
]
|
||||
|
||||
url = f"{self.api_url}/jobs-app/event"
|
||||
self.session.post(url, data=data)
|
||||
|
||||
@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
|
||||
|
||||
@staticmethod
|
||||
def _add_params(scraper_input) -> dict[str, str | Any]:
|
||||
params = {
|
||||
"search": scraper_input.search_term,
|
||||
"location": scraper_input.location,
|
||||
}
|
||||
if scraper_input.hours_old:
|
||||
params["days"] = max(scraper_input.hours_old // 24, 1)
|
||||
job_type_map = {JobType.FULL_TIME: "full_time", JobType.PART_TIME: "part_time"}
|
||||
if scraper_input.job_type:
|
||||
job_type = scraper_input.job_type
|
||||
params["employment_type"] = job_type_map.get(job_type, job_type.value[0])
|
||||
if scraper_input.easy_apply:
|
||||
params["zipapply"] = 1
|
||||
if scraper_input.is_remote:
|
||||
params["remote"] = 1
|
||||
if scraper_input.distance:
|
||||
params["radius"] = scraper_input.distance
|
||||
return {k: v for k, v in params.items() if v is not None}
|
||||
self.session.post(url, data=get_cookie_data)
|
||||
|
|
@ -0,0 +1,29 @@
|
|||
headers = {
|
||||
"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",
|
||||
}
|
||||
|
||||
get_cookie_data = [
|
||||
("event_type", "session"),
|
||||
("logged_in", "false"),
|
||||
("number_of_retry", "1"),
|
||||
("property", "model:iPhone"),
|
||||
("property", "os:iOS"),
|
||||
("property", "locale:en_us"),
|
||||
("property", "app_build_number:4734"),
|
||||
("property", "app_version:91.0"),
|
||||
("property", "manufacturer:Apple"),
|
||||
("property", "timestamp:2025-01-12T12:04:42-06:00"),
|
||||
("property", "screen_height:852"),
|
||||
("property", "os_version:16.6.1"),
|
||||
("property", "source:install"),
|
||||
("property", "screen_width:393"),
|
||||
("property", "device_model:iPhone 14 Pro"),
|
||||
("property", "brand:Apple"),
|
||||
]
|
||||
|
|
@ -0,0 +1,31 @@
|
|||
from jobspy.model import JobType
|
||||
|
||||
|
||||
def add_params(scraper_input) -> dict[str, str | int]:
|
||||
params: dict[str, str | int] = {
|
||||
"search": scraper_input.search_term,
|
||||
"location": scraper_input.location,
|
||||
}
|
||||
if scraper_input.hours_old:
|
||||
params["days"] = max(scraper_input.hours_old // 24, 1)
|
||||
|
||||
job_type_map = {JobType.FULL_TIME: "full_time", JobType.PART_TIME: "part_time"}
|
||||
if scraper_input.job_type:
|
||||
job_type = scraper_input.job_type
|
||||
params["employment_type"] = job_type_map.get(job_type, job_type.value[0])
|
||||
|
||||
if scraper_input.easy_apply:
|
||||
params["zipapply"] = 1
|
||||
if scraper_input.is_remote:
|
||||
params["remote"] = 1
|
||||
if scraper_input.distance:
|
||||
params["radius"] = scraper_input.distance
|
||||
|
||||
return {k: v for k, v in params.items() if v is not None}
|
||||
|
||||
|
||||
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
|
||||
|
|
@ -4,15 +4,14 @@ build-backend = "poetry.core.masonry.api"
|
|||
|
||||
[tool.poetry]
|
||||
name = "python-jobspy"
|
||||
version = "1.1.76"
|
||||
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"
|
||||
version = "1.1.77"
|
||||
description = "Job scraper for LinkedIn, Indeed, Glassdoor, ZipRecruiter & Bayt"
|
||||
authors = ["Cullen Watson <cullen@cullenwatson.com>", "Zachary Hampton <zachary@zacharysproducts.com>"]
|
||||
homepage = "https://github.com/cullenwatson/JobSpy"
|
||||
readme = "README.md"
|
||||
keywords = [ "jobs-scraper", "linkedin", "indeed", "glassdoor", "ziprecruiter",]
|
||||
keywords = [ "jobs-scraper", "linkedin", "indeed", "glassdoor", "ziprecruiter", "bayt"]
|
||||
[[tool.poetry.packages]]
|
||||
include = "jobspy"
|
||||
from = "src"
|
||||
|
||||
[tool.black]
|
||||
line-length = 88
|
||||
|
|
@ -29,7 +28,6 @@ markdownify = "^0.13.1"
|
|||
regex = "^2024.4.28"
|
||||
|
||||
[tool.poetry.group.dev.dependencies]
|
||||
pytest = "^7.4.1"
|
||||
jupyter = "^1.0.0"
|
||||
black = "*"
|
||||
pre-commit = "*"
|
||||
|
|
|
|||
|
|
@ -1,58 +0,0 @@
|
|||
from __future__ import annotations
|
||||
|
||||
from abc import ABC, abstractmethod
|
||||
|
||||
from ..jobs import (
|
||||
Enum,
|
||||
BaseModel,
|
||||
JobType,
|
||||
JobResponse,
|
||||
Country,
|
||||
DescriptionFormat,
|
||||
)
|
||||
|
||||
|
||||
class Site(Enum):
|
||||
LINKEDIN = "linkedin"
|
||||
INDEED = "indeed"
|
||||
ZIP_RECRUITER = "zip_recruiter"
|
||||
GLASSDOOR = "glassdoor"
|
||||
GOOGLE = "google"
|
||||
BAYT = "bayt"
|
||||
|
||||
|
||||
class SalarySource(Enum):
|
||||
DIRECT_DATA = "direct_data"
|
||||
DESCRIPTION = "description"
|
||||
|
||||
|
||||
class ScraperInput(BaseModel):
|
||||
site_type: list[Site]
|
||||
search_term: str | None = None
|
||||
google_search_term: str | None = None
|
||||
|
||||
location: str | None = None
|
||||
country: Country | None = Country.USA
|
||||
distance: int | None = None
|
||||
is_remote: bool = False
|
||||
job_type: JobType | None = None
|
||||
easy_apply: bool | None = None
|
||||
offset: int = 0
|
||||
linkedin_fetch_description: bool = False
|
||||
linkedin_company_ids: list[int] | None = None
|
||||
description_format: DescriptionFormat | None = DescriptionFormat.MARKDOWN
|
||||
|
||||
results_wanted: int = 15
|
||||
hours_old: int | None = None
|
||||
|
||||
|
||||
class Scraper(ABC):
|
||||
def __init__(
|
||||
self, site: Site, proxies: list[str] | None = None, ca_cert: str | None = None
|
||||
):
|
||||
self.site = site
|
||||
self.proxies = proxies
|
||||
self.ca_cert = ca_cert
|
||||
|
||||
@abstractmethod
|
||||
def scrape(self, scraper_input: ScraperInput) -> JobResponse: ...
|
||||
|
|
@ -1,10 +0,0 @@
|
|||
headers = {
|
||||
"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",
|
||||
}
|
||||
Loading…
Reference in New Issue