mirror of
https://github.com/Bunsly/JobSpy.git
synced 2026-03-05 03:54:31 -08:00
Compare commits
30 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
|
|
7cb0c518fc | ||
|
|
df70d4bc2e | ||
|
|
3006063875 | ||
|
|
1be009b8bc | ||
|
|
81ed9b3ddf | ||
|
|
11a9e9a56a | ||
|
|
c6ade14784 | ||
|
|
13c74a0fed | ||
|
|
333e9e6760 | ||
|
|
04032a0f91 | ||
|
|
496896d0b5 | ||
|
|
87ba1ad1bf | ||
|
|
4e7ac9a583 | ||
|
|
e44d13e1cf | ||
|
|
d52e366ef7 | ||
|
|
395ebf0017 | ||
|
|
63fddd9b7f | ||
|
|
58956868ae | ||
|
|
4fce836222 | ||
|
|
5ba25e7a7c | ||
|
|
f7cb3e9206 | ||
|
|
3ad3f121f7 | ||
|
|
ff3c782912 | ||
|
|
338d854b96 | ||
|
|
811d4c40b4 | ||
|
|
dba92d22c2 | ||
|
|
10a3592a0f | ||
|
|
b7905cc756 | ||
|
|
6867d58829 | ||
|
|
f6248c8386 |
39
.github/workflows/publish-to-pypi.yml
vendored
39
.github/workflows/publish-to-pypi.yml
vendored
@@ -1,33 +1,50 @@
|
||||
name: Publish Python 🐍 distributions 📦 to PyPI
|
||||
on: push
|
||||
on:
|
||||
pull_request:
|
||||
types:
|
||||
- closed
|
||||
|
||||
permissions:
|
||||
contents: write
|
||||
|
||||
jobs:
|
||||
build-n-publish:
|
||||
name: Build and publish Python 🐍 distributions 📦 to PyPI
|
||||
runs-on: ubuntu-latest
|
||||
|
||||
if: github.event.pull_request.merged == true && github.event.pull_request.base.ref == 'main'
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v3
|
||||
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@v4
|
||||
with:
|
||||
python-version: "3.10"
|
||||
|
||||
- name: Install dependencies
|
||||
run: pip install toml
|
||||
|
||||
- name: Increment version
|
||||
run: python increment_version.py
|
||||
|
||||
- name: Commit version increment
|
||||
run: |
|
||||
git config --global user.name 'github-actions'
|
||||
git config --global user.email 'github-actions@github.com'
|
||||
git add pyproject.toml
|
||||
git commit -m 'Increment version'
|
||||
|
||||
- name: Push changes
|
||||
run: git push
|
||||
|
||||
- name: Install poetry
|
||||
run: >-
|
||||
python3 -m
|
||||
pip install
|
||||
poetry
|
||||
--user
|
||||
run: pip install poetry --user
|
||||
|
||||
- name: Build distribution 📦
|
||||
run: >-
|
||||
python3 -m
|
||||
poetry
|
||||
build
|
||||
run: poetry build
|
||||
|
||||
- name: Publish distribution 📦 to PyPI
|
||||
if: startsWith(github.ref, 'refs/tags')
|
||||
uses: pypa/gh-action-pypi-publish@release/v1
|
||||
with:
|
||||
password: ${{ secrets.PYPI_API_TOKEN }}
|
||||
22
.github/workflows/python-test.yml
vendored
22
.github/workflows/python-test.yml
vendored
@@ -1,22 +0,0 @@
|
||||
name: Python Tests
|
||||
|
||||
on:
|
||||
pull_request:
|
||||
branches:
|
||||
- main
|
||||
|
||||
jobs:
|
||||
test:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v2
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@v2
|
||||
with:
|
||||
python-version: '3.8'
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
pip install poetry
|
||||
poetry install
|
||||
- name: Run tests
|
||||
run: poetry run pytest tests/test_all.py
|
||||
144
README.md
144
README.md
@@ -1,17 +1,12 @@
|
||||
<img src="https://github.com/cullenwatson/JobSpy/assets/78247585/ae185b7e-e444-4712-8bb9-fa97f53e896b" width="400">
|
||||
|
||||
**JobSpy** is a simple, yet comprehensive, job scraping library.
|
||||
|
||||
**Not technical?** Try out the web scraping tool on our site at [usejobspy.com](https://usejobspy.com).
|
||||
|
||||
*Looking to build a data-focused software product?* **[Book a call](https://bunsly.com/)** *to
|
||||
work with us.*
|
||||
**JobSpy** is a job scraping library with the goal of aggregating all the jobs from popular job boards with one tool.
|
||||
|
||||
## Features
|
||||
|
||||
- Scrapes job postings from **LinkedIn**, **Indeed**, **Glassdoor**, & **ZipRecruiter** simultaneously
|
||||
- Aggregates the job postings in a Pandas DataFrame
|
||||
- Proxies support
|
||||
- Scrapes job postings from **LinkedIn**, **Indeed**, **Glassdoor**, **Google**, **ZipRecruiter**, & **Bayt** concurrently
|
||||
- Aggregates the job postings in a dataframe
|
||||
- Proxies support to bypass blocking
|
||||
|
||||

|
||||
|
||||
@@ -30,16 +25,16 @@ import csv
|
||||
from jobspy import scrape_jobs
|
||||
|
||||
jobs = scrape_jobs(
|
||||
site_name=["indeed", "linkedin", "zip_recruiter", "glassdoor"],
|
||||
site_name=["indeed", "linkedin", "zip_recruiter", "glassdoor", "google", "bayt"],
|
||||
search_term="software engineer",
|
||||
location="Dallas, TX",
|
||||
google_search_term="software engineer jobs near San Francisco, CA since yesterday",
|
||||
location="San Francisco, CA",
|
||||
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
|
||||
hours_old=72,
|
||||
country_indeed='USA',
|
||||
|
||||
# linkedin_fetch_description=True # get more info such as full description, direct job url for linkedin (slower)
|
||||
# linkedin_fetch_description=True # gets more info such as description, direct job url (slower)
|
||||
# proxies=["208.195.175.46:65095", "208.195.175.45:65095", "localhost"],
|
||||
|
||||
)
|
||||
print(f"Found {len(jobs)} jobs")
|
||||
print(jobs.head())
|
||||
@@ -63,10 +58,13 @@ zip_recruiter Software Developer TEKsystems Phoenix
|
||||
```plaintext
|
||||
Optional
|
||||
├── site_name (list|str):
|
||||
| linkedin, zip_recruiter, indeed, glassdoor
|
||||
| (default is all four)
|
||||
| linkedin, zip_recruiter, indeed, glassdoor, google, bayt
|
||||
| (default is all)
|
||||
│
|
||||
├── search_term (str)
|
||||
|
|
||||
├── google_search_term (str)
|
||||
| search term for google jobs. This is the only param for filtering google jobs.
|
||||
│
|
||||
├── location (str)
|
||||
│
|
||||
@@ -80,16 +78,13 @@ Optional
|
||||
| in format ['user:pass@host:port', 'localhost']
|
||||
| each job board scraper will round robin through the proxies
|
||||
|
|
||||
├── ca_cert (str)
|
||||
| path to CA Certificate file for proxies
|
||||
│
|
||||
├── 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
|
||||
| filters for jobs that are hosted on the job board site (LinkedIn easy apply filter no longer works)
|
||||
│
|
||||
├── description_format (str):
|
||||
| markdown, html (Format type of the job descriptions. Default is markdown.)
|
||||
@@ -116,6 +111,9 @@ Optional
|
||||
|
|
||||
├── enforce_annual_salary (bool):
|
||||
| converts wages to annual salary
|
||||
|
|
||||
├── ca_cert (str)
|
||||
| path to CA Certificate file for proxies
|
||||
```
|
||||
|
||||
```
|
||||
@@ -131,46 +129,6 @@ Optional
|
||||
| - easy_apply
|
||||
```
|
||||
|
||||
|
||||
### JobPost Schema
|
||||
|
||||
```plaintext
|
||||
JobPost
|
||||
├── title
|
||||
├── company
|
||||
├── company_url
|
||||
├── job_url
|
||||
├── location
|
||||
│ ├── country
|
||||
│ ├── city
|
||||
│ ├── state
|
||||
├── description
|
||||
├── job_type: fulltime, parttime, internship, contract
|
||||
├── job_function
|
||||
│ ├── interval: yearly, monthly, weekly, daily, hourly
|
||||
│ ├── min_amount
|
||||
│ ├── max_amount
|
||||
│ ├── currency
|
||||
│ └── salary_source: direct_data, description (parsed from posting)
|
||||
├── date_posted
|
||||
├── emails
|
||||
└── is_remote
|
||||
|
||||
Linkedin specific
|
||||
└── job_level
|
||||
|
||||
Linkedin & Indeed specific
|
||||
└── company_industry
|
||||
|
||||
Indeed specific
|
||||
├── company_country
|
||||
├── company_addresses
|
||||
├── company_employees_label
|
||||
├── company_revenue_label
|
||||
├── company_description
|
||||
└── logo_photo_url
|
||||
```
|
||||
|
||||
## Supported Countries for Job Searching
|
||||
|
||||
### **LinkedIn**
|
||||
@@ -207,6 +165,11 @@ You can specify the following countries when searching on Indeed (use the exact
|
||||
| United Arab Emirates | UK* | USA* | Uruguay |
|
||||
| Venezuela | Vietnam* | | |
|
||||
|
||||
### **Bayt**
|
||||
|
||||
Bayt only uses the search_term parameter currently and searches internationally
|
||||
|
||||
|
||||
|
||||
## Notes
|
||||
* Indeed is the best scraper currently with no rate limiting.
|
||||
@@ -217,7 +180,23 @@ You can specify the following countries when searching on Indeed (use the exact
|
||||
|
||||
---
|
||||
**Q: Why is Indeed giving unrelated roles?**
|
||||
**A:** Indeed is searching each one of your terms e.g. software intern, it searches software OR intern. Try search_term='"software intern"' in quotes for stricter searching
|
||||
**A:** Indeed searches the description too.
|
||||
|
||||
- use - to remove words
|
||||
- "" for exact match
|
||||
|
||||
Example of a good Indeed query
|
||||
|
||||
```py
|
||||
search_term='"engineering intern" software summer (java OR python OR c++) 2025 -tax -marketing'
|
||||
```
|
||||
|
||||
This searches the description/title and must include software, summer, 2025, one of the languages, engineering intern exactly, no tax, no marketing.
|
||||
|
||||
---
|
||||
|
||||
**Q: No results when using "google"?**
|
||||
**A:** You have to use super specific syntax. Search for google jobs on your browser and then whatever pops up in the google jobs search box after applying some filters is what you need to copy & paste into the google_search_term.
|
||||
|
||||
---
|
||||
|
||||
@@ -229,8 +208,41 @@ You can specify the following countries when searching on Indeed (use the exact
|
||||
|
||||
---
|
||||
|
||||
**Q: Encountering issues with your queries?**
|
||||
**A:** Try reducing the number of `results_wanted` and/or broadening the filters. If problems
|
||||
persist, [submit an issue](https://github.com/Bunsly/JobSpy/issues).
|
||||
### JobPost Schema
|
||||
|
||||
---
|
||||
```plaintext
|
||||
JobPost
|
||||
├── title
|
||||
├── company
|
||||
├── company_url
|
||||
├── job_url
|
||||
├── location
|
||||
│ ├── country
|
||||
│ ├── city
|
||||
│ ├── state
|
||||
├── description
|
||||
├── job_type: fulltime, parttime, internship, contract
|
||||
├── job_function
|
||||
│ ├── interval: yearly, monthly, weekly, daily, hourly
|
||||
│ ├── min_amount
|
||||
│ ├── max_amount
|
||||
│ ├── currency
|
||||
│ └── salary_source: direct_data, description (parsed from posting)
|
||||
├── date_posted
|
||||
├── emails
|
||||
└── is_remote
|
||||
|
||||
Linkedin specific
|
||||
└── job_level
|
||||
|
||||
Linkedin & Indeed specific
|
||||
└── company_industry
|
||||
|
||||
Indeed specific
|
||||
├── company_country
|
||||
├── company_addresses
|
||||
├── company_employees_label
|
||||
├── company_revenue_label
|
||||
├── company_description
|
||||
└── company_logo
|
||||
```
|
||||
|
||||
21
increment_version.py
Normal file
21
increment_version.py
Normal file
@@ -0,0 +1,21 @@
|
||||
import toml
|
||||
|
||||
def increment_version(version):
|
||||
major, minor, patch = map(int, version.split('.'))
|
||||
patch += 1
|
||||
return f"{major}.{minor}.{patch}"
|
||||
|
||||
# Load pyproject.toml
|
||||
with open('pyproject.toml', 'r') as file:
|
||||
pyproject = toml.load(file)
|
||||
|
||||
# Increment the version
|
||||
current_version = pyproject['tool']['poetry']['version']
|
||||
new_version = increment_version(current_version)
|
||||
pyproject['tool']['poetry']['version'] = new_version
|
||||
|
||||
# Save the updated pyproject.toml
|
||||
with open('pyproject.toml', 'w') as file:
|
||||
toml.dump(pyproject, file)
|
||||
|
||||
print(f"Version updated from {current_version} to {new_version}")
|
||||
@@ -1,2 +0,0 @@
|
||||
[virtualenvs]
|
||||
in-project = true
|
||||
@@ -1,15 +1,21 @@
|
||||
[build-system]
|
||||
requires = [ "poetry-core",]
|
||||
build-backend = "poetry.core.masonry.api"
|
||||
|
||||
[tool.poetry]
|
||||
name = "python-jobspy"
|
||||
version = "1.1.72"
|
||||
version = "1.1.76"
|
||||
description = "Job scraper for LinkedIn, Indeed, Glassdoor & ZipRecruiter"
|
||||
authors = ["Zachary Hampton <zachary@bunsly.com>", "Cullen Watson <cullen@bunsly.com>"]
|
||||
authors = [ "Zachary Hampton <zachary@bunsly.com>", "Cullen Watson <cullen@bunsly.com>",]
|
||||
homepage = "https://github.com/Bunsly/JobSpy"
|
||||
readme = "README.md"
|
||||
keywords = ['jobs-scraper', 'linkedin', 'indeed', 'glassdoor', 'ziprecruiter']
|
||||
keywords = [ "jobs-scraper", "linkedin", "indeed", "glassdoor", "ziprecruiter",]
|
||||
[[tool.poetry.packages]]
|
||||
include = "jobspy"
|
||||
from = "src"
|
||||
|
||||
packages = [
|
||||
{ include = "jobspy", from = "src" }
|
||||
]
|
||||
[tool.black]
|
||||
line-length = 88
|
||||
|
||||
[tool.poetry.dependencies]
|
||||
python = "^3.10"
|
||||
@@ -22,16 +28,8 @@ tls-client = "^1.0.1"
|
||||
markdownify = "^0.13.1"
|
||||
regex = "^2024.4.28"
|
||||
|
||||
|
||||
[tool.poetry.group.dev.dependencies]
|
||||
pytest = "^7.4.1"
|
||||
jupyter = "^1.0.0"
|
||||
black = "*"
|
||||
pre-commit = "*"
|
||||
|
||||
[build-system]
|
||||
requires = ["poetry-core"]
|
||||
build-backend = "poetry.core.masonry.api"
|
||||
|
||||
[tool.black]
|
||||
line-length = 88
|
||||
|
||||
@@ -9,19 +9,23 @@ from .scrapers.utils import set_logger_level, extract_salary, create_logger
|
||||
from .scrapers.indeed import IndeedScraper
|
||||
from .scrapers.ziprecruiter import ZipRecruiterScraper
|
||||
from .scrapers.glassdoor import GlassdoorScraper
|
||||
from .scrapers.google import GoogleJobsScraper
|
||||
from .scrapers.linkedin import LinkedInScraper
|
||||
from .scrapers.bayt import BaytScraper
|
||||
from .scrapers import SalarySource, ScraperInput, Site, JobResponse, Country
|
||||
from .scrapers.exceptions import (
|
||||
LinkedInException,
|
||||
IndeedException,
|
||||
ZipRecruiterException,
|
||||
GlassdoorException,
|
||||
GoogleJobsException,
|
||||
)
|
||||
|
||||
|
||||
def scrape_jobs(
|
||||
site_name: str | list[str] | Site | list[Site] | None = None,
|
||||
search_term: str | None = None,
|
||||
google_search_term: str | None = None,
|
||||
location: str | None = None,
|
||||
distance: int | None = 50,
|
||||
is_remote: bool = False,
|
||||
@@ -38,7 +42,7 @@ def scrape_jobs(
|
||||
offset: int | None = 0,
|
||||
hours_old: int = None,
|
||||
enforce_annual_salary: bool = False,
|
||||
verbose: int = 2,
|
||||
verbose: int = 0,
|
||||
**kwargs,
|
||||
) -> pd.DataFrame:
|
||||
"""
|
||||
@@ -50,6 +54,8 @@ def scrape_jobs(
|
||||
Site.INDEED: IndeedScraper,
|
||||
Site.ZIP_RECRUITER: ZipRecruiterScraper,
|
||||
Site.GLASSDOOR: GlassdoorScraper,
|
||||
Site.GOOGLE: GoogleJobsScraper,
|
||||
Site.BAYT: BaytScraper,
|
||||
}
|
||||
set_logger_level(verbose)
|
||||
|
||||
@@ -83,6 +89,7 @@ def scrape_jobs(
|
||||
site_type=get_site_type(),
|
||||
country=country_enum,
|
||||
search_term=search_term,
|
||||
google_search_term=google_search_term,
|
||||
location=location,
|
||||
distance=distance,
|
||||
is_remote=is_remote,
|
||||
@@ -213,8 +220,8 @@ def scrape_jobs(
|
||||
"title",
|
||||
"company",
|
||||
"location",
|
||||
"job_type",
|
||||
"date_posted",
|
||||
"job_type",
|
||||
"salary_source",
|
||||
"interval",
|
||||
"min_amount",
|
||||
@@ -223,12 +230,12 @@ def scrape_jobs(
|
||||
"is_remote",
|
||||
"job_level",
|
||||
"job_function",
|
||||
"company_industry",
|
||||
"listing_type",
|
||||
"emails",
|
||||
"description",
|
||||
"company_industry",
|
||||
"company_url",
|
||||
"logo_photo_url",
|
||||
"company_logo",
|
||||
"company_url_direct",
|
||||
"company_addresses",
|
||||
"company_num_employees",
|
||||
@@ -245,6 +252,8 @@ def scrape_jobs(
|
||||
jobs_df = jobs_df[desired_order]
|
||||
|
||||
# Step 4: Sort the DataFrame as required
|
||||
return jobs_df.sort_values(by=["site", "date_posted"], ascending=[True, False])
|
||||
return jobs_df.sort_values(
|
||||
by=["site", "date_posted"], ascending=[True, False]
|
||||
).reset_index(drop=True)
|
||||
else:
|
||||
return pd.DataFrame()
|
||||
|
||||
@@ -256,7 +256,7 @@ class JobPost(BaseModel):
|
||||
company_num_employees: str | None = None
|
||||
company_revenue: str | None = None
|
||||
company_description: str | None = None
|
||||
logo_photo_url: str | None = None
|
||||
company_logo: str | None = None
|
||||
banner_photo_url: str | None = None
|
||||
|
||||
# linkedin only atm
|
||||
|
||||
@@ -17,14 +17,19 @@ class Site(Enum):
|
||||
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
|
||||
@@ -42,7 +47,9 @@ class ScraperInput(BaseModel):
|
||||
|
||||
|
||||
class Scraper(ABC):
|
||||
def __init__(self, site: Site, proxies: list[str] | None = None, ca_cert: str | None = None):
|
||||
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
|
||||
|
||||
145
src/jobspy/scrapers/bayt/__init__.py
Normal file
145
src/jobspy/scrapers/bayt/__init__.py
Normal file
@@ -0,0 +1,145 @@
|
||||
"""
|
||||
jobspy.scrapers.bayt
|
||||
~~~~~~~~~~~~~~~~~~~
|
||||
|
||||
This module contains routines to scrape Bayt.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import random
|
||||
import time
|
||||
|
||||
from bs4 import BeautifulSoup
|
||||
|
||||
from .. import Scraper, ScraperInput, Site
|
||||
from ..utils import create_logger, create_session
|
||||
from ...jobs import JobPost, JobResponse, Location, Country
|
||||
|
||||
log = create_logger("Bayt")
|
||||
|
||||
|
||||
class BaytScraper(Scraper):
|
||||
base_url = "https://www.bayt.com"
|
||||
delay = 2
|
||||
band_delay = 3
|
||||
|
||||
def __init__(
|
||||
self, proxies: list[str] | str | None = None, ca_cert: str | None = None
|
||||
):
|
||||
super().__init__(Site.BAYT, proxies=proxies, ca_cert=ca_cert)
|
||||
self.scraper_input = None
|
||||
self.session = None
|
||||
self.country = "worldwide"
|
||||
|
||||
def scrape(self, scraper_input: ScraperInput) -> JobResponse:
|
||||
self.scraper_input = scraper_input
|
||||
self.session = create_session(
|
||||
proxies=self.proxies, ca_cert=self.ca_cert, is_tls=False, has_retry=True
|
||||
)
|
||||
job_list: list[JobPost] = []
|
||||
page = 1
|
||||
results_wanted = (
|
||||
scraper_input.results_wanted if scraper_input.results_wanted else 10
|
||||
)
|
||||
|
||||
while len(job_list) < results_wanted:
|
||||
log.info(f"Fetching Bayt jobs page {page}")
|
||||
job_elements = self._fetch_jobs(self.scraper_input.search_term, page)
|
||||
if not job_elements:
|
||||
break
|
||||
|
||||
if job_elements:
|
||||
log.debug(
|
||||
"First job element snippet:\n" + job_elements[0].prettify()[:500]
|
||||
)
|
||||
|
||||
initial_count = len(job_list)
|
||||
for job in job_elements:
|
||||
try:
|
||||
job_post = self._extract_job_info(job)
|
||||
if job_post:
|
||||
job_list.append(job_post)
|
||||
if len(job_list) >= results_wanted:
|
||||
break
|
||||
else:
|
||||
log.debug(
|
||||
"Extraction returned None. Job snippet:\n"
|
||||
+ job.prettify()[:500]
|
||||
)
|
||||
except Exception as e:
|
||||
log.error(f"Bayt: Error extracting job info: {str(e)}")
|
||||
continue
|
||||
|
||||
if len(job_list) == initial_count:
|
||||
log.info(f"No new jobs found on page {page}. Ending pagination.")
|
||||
break
|
||||
|
||||
page += 1
|
||||
time.sleep(random.uniform(self.delay, self.delay + self.band_delay))
|
||||
|
||||
job_list = job_list[: scraper_input.results_wanted]
|
||||
return JobResponse(jobs=job_list)
|
||||
|
||||
def _fetch_jobs(self, query: str, page: int) -> list | None:
|
||||
"""
|
||||
Grabs the job results for the given query and page number.
|
||||
"""
|
||||
try:
|
||||
url = f"{self.base_url}/en/international/jobs/{query}-jobs/?page={page}"
|
||||
response = self.session.get(url)
|
||||
response.raise_for_status()
|
||||
soup = BeautifulSoup(response.text, "html.parser")
|
||||
job_listings = soup.find_all("li", attrs={"data-js-job": ""})
|
||||
log.debug(f"Found {len(job_listings)} job listing elements")
|
||||
return job_listings
|
||||
except Exception as e:
|
||||
log.error(f"Bayt: Error fetching jobs - {str(e)}")
|
||||
return None
|
||||
|
||||
def _extract_job_info(self, job: BeautifulSoup) -> JobPost | None:
|
||||
"""
|
||||
Extracts the job information from a single job listing.
|
||||
"""
|
||||
# Find the h2 element holding the title and link (no class filtering)
|
||||
job_general_information = job.find("h2")
|
||||
if not job_general_information:
|
||||
return
|
||||
|
||||
job_title = job_general_information.get_text(strip=True)
|
||||
job_url = self._extract_job_url(job_general_information)
|
||||
if not job_url:
|
||||
return
|
||||
|
||||
# Extract company name using the original approach:
|
||||
company_tag = job.find("div", class_="t-nowrap p10l")
|
||||
company_name = (
|
||||
company_tag.find("span").get_text(strip=True)
|
||||
if company_tag and company_tag.find("span")
|
||||
else None
|
||||
)
|
||||
|
||||
# Extract location using the original approach:
|
||||
location_tag = job.find("div", class_="t-mute t-small")
|
||||
location = location_tag.get_text(strip=True) if location_tag else None
|
||||
|
||||
job_id = f"bayt-{abs(hash(job_url))}"
|
||||
location_obj = Location(
|
||||
city=location,
|
||||
country=Country.from_string(self.country),
|
||||
)
|
||||
return JobPost(
|
||||
id=job_id,
|
||||
title=job_title,
|
||||
company_name=company_name,
|
||||
location=location_obj,
|
||||
job_url=job_url,
|
||||
)
|
||||
|
||||
def _extract_job_url(self, job_general_information: BeautifulSoup) -> str | None:
|
||||
"""
|
||||
Pulls the job URL from the 'a' within the h2 element.
|
||||
"""
|
||||
a_tag = job_general_information.find("a")
|
||||
if a_tag and a_tag.has_attr("href"):
|
||||
return self.base_url + a_tag["href"].strip()
|
||||
@@ -24,3 +24,13 @@ class ZipRecruiterException(Exception):
|
||||
class GlassdoorException(Exception):
|
||||
def __init__(self, message=None):
|
||||
super().__init__(message or "An error occurred with Glassdoor")
|
||||
|
||||
|
||||
class GoogleJobsException(Exception):
|
||||
def __init__(self, message=None):
|
||||
super().__init__(message or "An error occurred with Google Jobs")
|
||||
|
||||
|
||||
class BaytException(Exception):
|
||||
def __init__(self, message=None):
|
||||
super().__init__(message or "An error occurred with Bayt")
|
||||
|
||||
@@ -32,7 +32,7 @@ from ...jobs import (
|
||||
DescriptionFormat,
|
||||
)
|
||||
|
||||
logger = create_logger("Glassdoor")
|
||||
log = create_logger("Glassdoor")
|
||||
|
||||
|
||||
class GlassdoorScraper(Scraper):
|
||||
@@ -64,7 +64,7 @@ class GlassdoorScraper(Scraper):
|
||||
self.base_url = self.scraper_input.country.get_glassdoor_url()
|
||||
|
||||
self.session = create_session(
|
||||
proxies=self.proxies, ca_cert=self.ca_cert, is_tls=True, has_retry=True
|
||||
proxies=self.proxies, ca_cert=self.ca_cert, has_retry=True
|
||||
)
|
||||
token = self._get_csrf_token()
|
||||
headers["gd-csrf-token"] = token if token else fallback_token
|
||||
@@ -74,7 +74,7 @@ class GlassdoorScraper(Scraper):
|
||||
scraper_input.location, scraper_input.is_remote
|
||||
)
|
||||
if location_type is None:
|
||||
logger.error("Glassdoor: location not parsed")
|
||||
log.error("Glassdoor: location not parsed")
|
||||
return JobResponse(jobs=[])
|
||||
job_list: list[JobPost] = []
|
||||
cursor = None
|
||||
@@ -83,7 +83,7 @@ class GlassdoorScraper(Scraper):
|
||||
tot_pages = (scraper_input.results_wanted // self.jobs_per_page) + 2
|
||||
range_end = min(tot_pages, self.max_pages + 1)
|
||||
for page in range(range_start, range_end):
|
||||
logger.info(f"search page: {page} / {range_end-1}")
|
||||
log.info(f"search page: {page} / {range_end - 1}")
|
||||
try:
|
||||
jobs, cursor = self._fetch_jobs_page(
|
||||
scraper_input, location_id, location_type, page, cursor
|
||||
@@ -93,7 +93,7 @@ class GlassdoorScraper(Scraper):
|
||||
job_list = job_list[: scraper_input.results_wanted]
|
||||
break
|
||||
except Exception as e:
|
||||
logger.error(f"Glassdoor: {str(e)}")
|
||||
log.error(f"Glassdoor: {str(e)}")
|
||||
break
|
||||
return JobResponse(jobs=job_list)
|
||||
|
||||
@@ -129,7 +129,7 @@ class GlassdoorScraper(Scraper):
|
||||
ValueError,
|
||||
Exception,
|
||||
) as e:
|
||||
logger.error(f"Glassdoor: {str(e)}")
|
||||
log.error(f"Glassdoor: {str(e)}")
|
||||
return jobs, None
|
||||
|
||||
jobs_data = res_json["data"]["jobListings"]["jobListings"]
|
||||
@@ -214,7 +214,7 @@ class GlassdoorScraper(Scraper):
|
||||
is_remote=is_remote,
|
||||
description=description,
|
||||
emails=extract_emails_from_text(description) if description else None,
|
||||
logo_photo_url=company_logo,
|
||||
company_logo=company_logo,
|
||||
listing_type=listing_type,
|
||||
)
|
||||
|
||||
@@ -264,12 +264,12 @@ class GlassdoorScraper(Scraper):
|
||||
if res.status_code != 200:
|
||||
if res.status_code == 429:
|
||||
err = f"429 Response - Blocked by Glassdoor for too many requests"
|
||||
logger.error(err)
|
||||
log.error(err)
|
||||
return None, None
|
||||
else:
|
||||
err = f"Glassdoor response status code {res.status_code}"
|
||||
err += f" - {res.text}"
|
||||
logger.error(f"Glassdoor response status code {res.status_code}")
|
||||
log.error(f"Glassdoor response status code {res.status_code}")
|
||||
return None, None
|
||||
items = res.json()
|
||||
|
||||
|
||||
247
src/jobspy/scrapers/google/__init__.py
Normal file
247
src/jobspy/scrapers/google/__init__.py
Normal file
@@ -0,0 +1,247 @@
|
||||
"""
|
||||
jobspy.scrapers.google
|
||||
~~~~~~~~~~~~~~~~~~~
|
||||
|
||||
This module contains routines to scrape Google.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import math
|
||||
import re
|
||||
import json
|
||||
from typing import Tuple
|
||||
from datetime import datetime, timedelta
|
||||
|
||||
from .constants import headers_jobs, headers_initial, async_param
|
||||
from .. import Scraper, ScraperInput, Site
|
||||
from ..utils import extract_emails_from_text, create_logger, extract_job_type
|
||||
from ..utils import (
|
||||
create_session,
|
||||
)
|
||||
from ...jobs import (
|
||||
JobPost,
|
||||
JobResponse,
|
||||
Location,
|
||||
JobType,
|
||||
)
|
||||
|
||||
log = create_logger("Google")
|
||||
|
||||
|
||||
class GoogleJobsScraper(Scraper):
|
||||
def __init__(
|
||||
self, proxies: list[str] | str | None = None, ca_cert: str | None = None
|
||||
):
|
||||
"""
|
||||
Initializes Google Scraper with the Goodle jobs search url
|
||||
"""
|
||||
site = Site(Site.GOOGLE)
|
||||
super().__init__(site, proxies=proxies, ca_cert=ca_cert)
|
||||
|
||||
self.country = None
|
||||
self.session = None
|
||||
self.scraper_input = None
|
||||
self.jobs_per_page = 10
|
||||
self.seen_urls = set()
|
||||
self.url = "https://www.google.com/search"
|
||||
self.jobs_url = "https://www.google.com/async/callback:550"
|
||||
|
||||
def scrape(self, scraper_input: ScraperInput) -> JobResponse:
|
||||
"""
|
||||
Scrapes Google for jobs with scraper_input criteria.
|
||||
:param scraper_input: Information about job search criteria.
|
||||
:return: JobResponse containing a list of jobs.
|
||||
"""
|
||||
self.scraper_input = scraper_input
|
||||
self.scraper_input.results_wanted = min(900, scraper_input.results_wanted)
|
||||
|
||||
self.session = create_session(
|
||||
proxies=self.proxies, ca_cert=self.ca_cert, is_tls=False, has_retry=True
|
||||
)
|
||||
forward_cursor, job_list = self._get_initial_cursor_and_jobs()
|
||||
if forward_cursor is None:
|
||||
log.warning(
|
||||
"initial cursor not found, try changing your query or there was at most 10 results"
|
||||
)
|
||||
return JobResponse(jobs=job_list)
|
||||
|
||||
page = 1
|
||||
|
||||
while (
|
||||
len(self.seen_urls) < scraper_input.results_wanted + scraper_input.offset
|
||||
and forward_cursor
|
||||
):
|
||||
log.info(
|
||||
f"search page: {page} / {math.ceil(scraper_input.results_wanted / self.jobs_per_page)}"
|
||||
)
|
||||
try:
|
||||
jobs, forward_cursor = self._get_jobs_next_page(forward_cursor)
|
||||
except Exception as e:
|
||||
log.error(f"failed to get jobs on page: {page}, {e}")
|
||||
break
|
||||
if not jobs:
|
||||
log.info(f"found no jobs on page: {page}")
|
||||
break
|
||||
job_list += jobs
|
||||
page += 1
|
||||
return JobResponse(
|
||||
jobs=job_list[
|
||||
scraper_input.offset : scraper_input.offset
|
||||
+ scraper_input.results_wanted
|
||||
]
|
||||
)
|
||||
|
||||
def _get_initial_cursor_and_jobs(self) -> Tuple[str, list[JobPost]]:
|
||||
"""Gets initial cursor and jobs to paginate through job listings"""
|
||||
query = f"{self.scraper_input.search_term} jobs"
|
||||
|
||||
def get_time_range(hours_old):
|
||||
if hours_old <= 24:
|
||||
return "since yesterday"
|
||||
elif hours_old <= 72:
|
||||
return "in the last 3 days"
|
||||
elif hours_old <= 168:
|
||||
return "in the last week"
|
||||
else:
|
||||
return "in the last month"
|
||||
|
||||
job_type_mapping = {
|
||||
JobType.FULL_TIME: "Full time",
|
||||
JobType.PART_TIME: "Part time",
|
||||
JobType.INTERNSHIP: "Internship",
|
||||
JobType.CONTRACT: "Contract",
|
||||
}
|
||||
|
||||
if self.scraper_input.job_type in job_type_mapping:
|
||||
query += f" {job_type_mapping[self.scraper_input.job_type]}"
|
||||
|
||||
if self.scraper_input.location:
|
||||
query += f" near {self.scraper_input.location}"
|
||||
|
||||
if self.scraper_input.hours_old:
|
||||
time_filter = get_time_range(self.scraper_input.hours_old)
|
||||
query += f" {time_filter}"
|
||||
|
||||
if self.scraper_input.is_remote:
|
||||
query += " remote"
|
||||
|
||||
if self.scraper_input.google_search_term:
|
||||
query = self.scraper_input.google_search_term
|
||||
|
||||
params = {"q": query, "udm": "8"}
|
||||
response = self.session.get(self.url, headers=headers_initial, params=params)
|
||||
|
||||
pattern_fc = r'<div jsname="Yust4d"[^>]+data-async-fc="([^"]+)"'
|
||||
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 = []
|
||||
for job_raw in jobs_raw:
|
||||
job_post = self._parse_job(job_raw)
|
||||
if job_post:
|
||||
jobs.append(job_post)
|
||||
return data_async_fc, jobs
|
||||
|
||||
def _get_jobs_next_page(self, forward_cursor: str) -> Tuple[list[JobPost], str]:
|
||||
params = {"fc": [forward_cursor], "fcv": ["3"], "async": [async_param]}
|
||||
response = self.session.get(self.jobs_url, headers=headers_jobs, params=params)
|
||||
return self._parse_jobs(response.text)
|
||||
|
||||
def _parse_jobs(self, job_data: str) -> Tuple[list[JobPost], str]:
|
||||
"""
|
||||
Parses jobs on a page with next page cursor
|
||||
"""
|
||||
start_idx = job_data.find("[[[")
|
||||
end_idx = job_data.rindex("]]]") + 3
|
||||
s = job_data[start_idx:end_idx]
|
||||
parsed = json.loads(s)[0]
|
||||
|
||||
pattern_fc = r'data-async-fc="([^"]+)"'
|
||||
match_fc = re.search(pattern_fc, job_data)
|
||||
data_async_fc = match_fc.group(1) if match_fc else None
|
||||
jobs_on_page = []
|
||||
for array in parsed:
|
||||
_, job_data = array
|
||||
if not job_data.startswith("[[["):
|
||||
continue
|
||||
job_d = json.loads(job_data)
|
||||
|
||||
job_info = self._find_job_info(job_d)
|
||||
job_post = self._parse_job(job_info)
|
||||
if job_post:
|
||||
jobs_on_page.append(job_post)
|
||||
return jobs_on_page, data_async_fc
|
||||
|
||||
def _parse_job(self, job_info: list):
|
||||
job_url = job_info[3][0][0] if job_info[3] and job_info[3][0] else None
|
||||
if job_url in self.seen_urls:
|
||||
return
|
||||
self.seen_urls.add(job_url)
|
||||
|
||||
title = job_info[0]
|
||||
company_name = job_info[1]
|
||||
location = city = job_info[2]
|
||||
state = country = date_posted = None
|
||||
if location and "," in location:
|
||||
city, state, *country = [*map(lambda x: x.strip(), location.split(","))]
|
||||
|
||||
days_ago_str = job_info[12]
|
||||
if type(days_ago_str) == str:
|
||||
match = re.search(r"\d+", days_ago_str)
|
||||
days_ago = int(match.group()) if match else None
|
||||
date_posted = (datetime.now() - timedelta(days=days_ago)).date()
|
||||
|
||||
description = job_info[19]
|
||||
|
||||
job_post = JobPost(
|
||||
id=f"go-{job_info[28]}",
|
||||
title=title,
|
||||
company_name=company_name,
|
||||
location=Location(
|
||||
city=city, state=state, country=country[0] if country else None
|
||||
),
|
||||
job_url=job_url,
|
||||
date_posted=date_posted,
|
||||
is_remote="remote" in description.lower() or "wfh" in description.lower(),
|
||||
description=description,
|
||||
emails=extract_emails_from_text(description),
|
||||
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
|
||||
52
src/jobspy/scrapers/google/constants.py
Normal file
52
src/jobspy/scrapers/google/constants.py
Normal file
@@ -0,0 +1,52 @@
|
||||
headers_initial = {
|
||||
"accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7",
|
||||
"accept-language": "en-US,en;q=0.9",
|
||||
"priority": "u=0, i",
|
||||
"referer": "https://www.google.com/",
|
||||
"sec-ch-prefers-color-scheme": "dark",
|
||||
"sec-ch-ua": '"Chromium";v="130", "Google Chrome";v="130", "Not?A_Brand";v="99"',
|
||||
"sec-ch-ua-arch": '"arm"',
|
||||
"sec-ch-ua-bitness": '"64"',
|
||||
"sec-ch-ua-form-factors": '"Desktop"',
|
||||
"sec-ch-ua-full-version": '"130.0.6723.58"',
|
||||
"sec-ch-ua-full-version-list": '"Chromium";v="130.0.6723.58", "Google Chrome";v="130.0.6723.58", "Not?A_Brand";v="99.0.0.0"',
|
||||
"sec-ch-ua-mobile": "?0",
|
||||
"sec-ch-ua-model": '""',
|
||||
"sec-ch-ua-platform": '"macOS"',
|
||||
"sec-ch-ua-platform-version": '"15.0.1"',
|
||||
"sec-ch-ua-wow64": "?0",
|
||||
"sec-fetch-dest": "document",
|
||||
"sec-fetch-mode": "navigate",
|
||||
"sec-fetch-site": "same-origin",
|
||||
"sec-fetch-user": "?1",
|
||||
"upgrade-insecure-requests": "1",
|
||||
"user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Safari/537.36",
|
||||
"x-browser-channel": "stable",
|
||||
"x-browser-copyright": "Copyright 2024 Google LLC. All rights reserved.",
|
||||
"x-browser-year": "2024",
|
||||
}
|
||||
|
||||
headers_jobs = {
|
||||
"accept": "*/*",
|
||||
"accept-language": "en-US,en;q=0.9",
|
||||
"priority": "u=1, i",
|
||||
"referer": "https://www.google.com/",
|
||||
"sec-ch-prefers-color-scheme": "dark",
|
||||
"sec-ch-ua": '"Chromium";v="130", "Google Chrome";v="130", "Not?A_Brand";v="99"',
|
||||
"sec-ch-ua-arch": '"arm"',
|
||||
"sec-ch-ua-bitness": '"64"',
|
||||
"sec-ch-ua-form-factors": '"Desktop"',
|
||||
"sec-ch-ua-full-version": '"130.0.6723.58"',
|
||||
"sec-ch-ua-full-version-list": '"Chromium";v="130.0.6723.58", "Google Chrome";v="130.0.6723.58", "Not?A_Brand";v="99.0.0.0"',
|
||||
"sec-ch-ua-mobile": "?0",
|
||||
"sec-ch-ua-model": '""',
|
||||
"sec-ch-ua-platform": '"macOS"',
|
||||
"sec-ch-ua-platform-version": '"15.0.1"',
|
||||
"sec-ch-ua-wow64": "?0",
|
||||
"sec-fetch-dest": "empty",
|
||||
"sec-fetch-mode": "cors",
|
||||
"sec-fetch-site": "same-origin",
|
||||
"user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Safari/537.36",
|
||||
}
|
||||
|
||||
async_param = "_basejs:/xjs/_/js/k=xjs.s.en_US.JwveA-JiKmg.2018.O/am=AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAIAAAAAAAAACAAAoICAAAAAAAKMAfAAAAIAQAAAAAAAAAAAAACCAAAEJDAAACAAAAAGABAIAAARBAAABAAAAAgAgQAABAASKAfv8JAAABAAAAAAwAQAQACQAAAAAAcAEAQABoCAAAABAAAIABAACAAAAEAAAAFAAAAAAAAAAAAAAAAAAAAAAAAACAQADoBwAAAAAAAAAAAAAQBAAAAATQAAoACOAHAAAAAAAAAQAAAIIAAAA_ZAACAAAAAAAAcB8APB4wHFJ4AAAAAAAAAAAAAAAACECCYA5If0EACAAAAAAAAAAAAAAAAAAAUgRNXG4AMAE/dg=0/br=1/rs=ACT90oGxMeaFMCopIHq5tuQM-6_3M_VMjQ,_basecss:/xjs/_/ss/k=xjs.s.IwsGu62EDtU.L.B1.O/am=QOoQIAQAAAQAREADEBAAAAAAAAAAAAAAAAAAAAAgAQAAIAAAgAQAAAIAIAIAoEwCAADIC8AfsgEAawwAPkAAjgoAGAAAAAAAAEADAAAAAAIgAECHAAAAAAAAAAABAQAggAARQAAAQCEAAAAAIAAAABgAAAAAIAQIACCAAfB-AAFIQABoCEA_CgEAAIABAACEgHAEwwAEFQAM4CgAAAAAAAAAAAAACABCAAAAQEAAABAgAMCPAAA4AoE2BAEAggSAAIoAQAAAAAgAAAAACCAQAAAxEwA_ZAACAAAAAAAAAAkAAAAAAAAgAAAAAAAAAAAAAAAAAAAAAAAAQAEAAAAAAAAAAAAAAAAAAAAAQA/br=1/rs=ACT90oGZc36t3uUQkj0srnIvvbHjO2hgyg,_basecomb:/xjs/_/js/k=xjs.s.en_US.JwveA-JiKmg.2018.O/ck=xjs.s.IwsGu62EDtU.L.B1.O/am=QOoQIAQAAAQAREADEBAAAAAAAAAAAAAAAAAAAAAgAQAAIAAAgAQAAAKAIAoIqEwCAADIK8AfsgEAawwAPkAAjgoAGAAACCAAAEJDAAACAAIgAGCHAIAAARBAAABBAQAggAgRQABAQSOAfv8JIAABABgAAAwAYAQICSCAAfB-cAFIQABoCEA_ChEAAIABAACEgHAEwwAEFQAM4CgAAAAAAAAAAAAACABCAACAQEDoBxAgAMCPAAA4AoE2BAEAggTQAIoASOAHAAgAAAAACSAQAIIxEwA_ZAACAAAAAAAAcB8APB4wHFJ4AAAAAAAAAAAAAAAACECCYA5If0EACAAAAAAAAAAAAAAAAAAAUgRNXG4AMAE/d=1/ed=1/dg=0/br=1/ujg=1/rs=ACT90oFNLTjPzD_OAqhhtXwe2pg1T3WpBg,_fmt:prog,_id:fc_5FwaZ86OKsfdwN4P4La3yA4_2"
|
||||
@@ -30,7 +30,7 @@ from ...jobs import (
|
||||
DescriptionFormat,
|
||||
)
|
||||
|
||||
logger = create_logger("Indeed")
|
||||
log = create_logger("Indeed")
|
||||
|
||||
|
||||
class IndeedScraper(Scraper):
|
||||
@@ -71,12 +71,12 @@ class IndeedScraper(Scraper):
|
||||
cursor = None
|
||||
|
||||
while len(self.seen_urls) < scraper_input.results_wanted + scraper_input.offset:
|
||||
logger.info(
|
||||
f"search page: {page} / {math.ceil(scraper_input.results_wanted / 100)}"
|
||||
log.info(
|
||||
f"search page: {page} / {math.ceil(scraper_input.results_wanted / self.jobs_per_page)}"
|
||||
)
|
||||
jobs, cursor = self._scrape_page(cursor)
|
||||
if not jobs:
|
||||
logger.info(f"found no jobs on page: {page}")
|
||||
log.info(f"found no jobs on page: {page}")
|
||||
break
|
||||
job_list += jobs
|
||||
page += 1
|
||||
@@ -122,9 +122,10 @@ class IndeedScraper(Scraper):
|
||||
headers=api_headers_temp,
|
||||
json=payload,
|
||||
timeout=10,
|
||||
verify=False,
|
||||
)
|
||||
if not response.ok:
|
||||
logger.info(
|
||||
log.info(
|
||||
f"responded with status code: {response.status_code} (submit GitHub issue if this appears to be a bug)"
|
||||
)
|
||||
return jobs, new_cursor
|
||||
@@ -258,7 +259,7 @@ class IndeedScraper(Scraper):
|
||||
company_num_employees=employer_details.get("employeesLocalizedLabel"),
|
||||
company_revenue=employer_details.get("revenueLocalizedLabel"),
|
||||
company_description=employer_details.get("briefDescription"),
|
||||
logo_photo_url=(
|
||||
company_logo=(
|
||||
employer["images"].get("squareLogoUrl")
|
||||
if employer and employer.get("images")
|
||||
else None
|
||||
|
||||
@@ -38,7 +38,7 @@ from ..utils import (
|
||||
markdown_converter,
|
||||
)
|
||||
|
||||
logger = create_logger("LinkedIn")
|
||||
log = create_logger("LinkedIn")
|
||||
|
||||
|
||||
class LinkedInScraper(Scraper):
|
||||
@@ -86,7 +86,7 @@ class LinkedInScraper(Scraper):
|
||||
)
|
||||
while continue_search():
|
||||
request_count += 1
|
||||
logger.info(
|
||||
log.info(
|
||||
f"search page: {request_count} / {math.ceil(scraper_input.results_wanted / 10)}"
|
||||
)
|
||||
params = {
|
||||
@@ -126,13 +126,13 @@ class LinkedInScraper(Scraper):
|
||||
else:
|
||||
err = f"LinkedIn response status code {response.status_code}"
|
||||
err += f" - {response.text}"
|
||||
logger.error(err)
|
||||
log.error(err)
|
||||
return JobResponse(jobs=job_list)
|
||||
except Exception as e:
|
||||
if "Proxy responded with" in str(e):
|
||||
logger.error(f"LinkedIn: Bad proxy")
|
||||
log.error(f"LinkedIn: Bad proxy")
|
||||
else:
|
||||
logger.error(f"LinkedIn: {str(e)}")
|
||||
log.error(f"LinkedIn: {str(e)}")
|
||||
return JobResponse(jobs=job_list)
|
||||
|
||||
soup = BeautifulSoup(response.text, "html.parser")
|
||||
@@ -232,7 +232,7 @@ class LinkedInScraper(Scraper):
|
||||
description=job_details.get("description"),
|
||||
job_url_direct=job_details.get("job_url_direct"),
|
||||
emails=extract_emails_from_text(job_details.get("description")),
|
||||
logo_photo_url=job_details.get("logo_photo_url"),
|
||||
company_logo=job_details.get("company_logo"),
|
||||
job_function=job_details.get("job_function"),
|
||||
)
|
||||
|
||||
@@ -275,7 +275,7 @@ class LinkedInScraper(Scraper):
|
||||
if job_function_span:
|
||||
job_function = job_function_span.text.strip()
|
||||
|
||||
logo_photo_url = (
|
||||
company_logo = (
|
||||
logo_image.get("data-delayed-url")
|
||||
if (logo_image := soup.find("img", {"class": "artdeco-entity-image"}))
|
||||
else None
|
||||
@@ -286,7 +286,7 @@ class LinkedInScraper(Scraper):
|
||||
"company_industry": self._parse_company_industry(soup),
|
||||
"job_type": self._parse_job_type(soup),
|
||||
"job_url_direct": self._parse_job_url_direct(soup),
|
||||
"logo_photo_url": logo_photo_url,
|
||||
"company_logo": company_logo,
|
||||
"job_function": job_function,
|
||||
}
|
||||
|
||||
|
||||
@@ -1,17 +1,20 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import re
|
||||
import logging
|
||||
import re
|
||||
from itertools import cycle
|
||||
|
||||
import numpy as np
|
||||
import requests
|
||||
import tls_client
|
||||
import numpy as np
|
||||
import urllib3
|
||||
from markdownify import markdownify as md
|
||||
from requests.adapters import HTTPAdapter, Retry
|
||||
|
||||
from ..jobs import CompensationInterval, JobType
|
||||
|
||||
urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
|
||||
|
||||
|
||||
def create_logger(name: str):
|
||||
logger = logging.getLogger(f"JobSpy:{name}")
|
||||
@@ -129,7 +132,7 @@ def create_session(
|
||||
return session
|
||||
|
||||
|
||||
def set_logger_level(verbose: int = 2):
|
||||
def set_logger_level(verbose: int):
|
||||
"""
|
||||
Adjusts the logger's level. This function allows the logging level to be changed at runtime.
|
||||
|
||||
@@ -264,3 +267,22 @@ def extract_salary(
|
||||
else:
|
||||
return interval, min_salary, max_salary, "USD"
|
||||
return None, None, None, None
|
||||
|
||||
|
||||
def extract_job_type(description: str):
|
||||
if not description:
|
||||
return []
|
||||
|
||||
keywords = {
|
||||
JobType.FULL_TIME: r"full\s?time",
|
||||
JobType.PART_TIME: r"part\s?time",
|
||||
JobType.INTERNSHIP: r"internship",
|
||||
JobType.CONTRACT: r"contract",
|
||||
}
|
||||
|
||||
listing_types = []
|
||||
for key, pattern in keywords.items():
|
||||
if re.search(pattern, description, re.IGNORECASE):
|
||||
listing_types.append(key)
|
||||
|
||||
return listing_types if listing_types else None
|
||||
|
||||
@@ -11,11 +11,10 @@ import json
|
||||
import math
|
||||
import re
|
||||
import time
|
||||
from concurrent.futures import ThreadPoolExecutor
|
||||
from datetime import datetime
|
||||
from typing import Optional, Tuple, Any
|
||||
|
||||
from concurrent.futures import ThreadPoolExecutor
|
||||
|
||||
from bs4 import BeautifulSoup
|
||||
|
||||
from .constants import headers
|
||||
@@ -37,7 +36,7 @@ from ...jobs import (
|
||||
DescriptionFormat,
|
||||
)
|
||||
|
||||
logger = create_logger("ZipRecruiter")
|
||||
log = create_logger("ZipRecruiter")
|
||||
|
||||
|
||||
class ZipRecruiterScraper(Scraper):
|
||||
@@ -77,7 +76,7 @@ class ZipRecruiterScraper(Scraper):
|
||||
break
|
||||
if page > 1:
|
||||
time.sleep(self.delay)
|
||||
logger.info(f"search page: {page} / {max_pages}")
|
||||
log.info(f"search page: {page} / {max_pages}")
|
||||
jobs_on_page, continue_token = self._find_jobs_in_page(
|
||||
scraper_input, continue_token
|
||||
)
|
||||
@@ -110,13 +109,13 @@ class ZipRecruiterScraper(Scraper):
|
||||
else:
|
||||
err = f"ZipRecruiter response status code {res.status_code}"
|
||||
err += f" with response: {res.text}" # ZipRecruiter likely not available in EU
|
||||
logger.error(err)
|
||||
log.error(err)
|
||||
return jobs_list, ""
|
||||
except Exception as e:
|
||||
if "Proxy responded with" in str(e):
|
||||
logger.error(f"Indeed: Bad proxy")
|
||||
log.error(f"Indeed: Bad proxy")
|
||||
else:
|
||||
logger.error(f"Indeed: {str(e)}")
|
||||
log.error(f"Indeed: {str(e)}")
|
||||
return jobs_list, ""
|
||||
|
||||
res_data = res.json()
|
||||
@@ -215,7 +214,28 @@ class ZipRecruiterScraper(Scraper):
|
||||
return description_full, job_url_direct
|
||||
|
||||
def _get_cookies(self):
|
||||
data = "event_type=session&logged_in=false&number_of_retry=1&property=model%3AiPhone&property=os%3AiOS&property=locale%3Aen_us&property=app_build_number%3A4734&property=app_version%3A91.0&property=manufacturer%3AApple&property=timestamp%3A2024-01-12T12%3A04%3A42-06%3A00&property=screen_height%3A852&property=os_version%3A16.6.1&property=source%3Ainstall&property=screen_width%3A393&property=device_model%3AiPhone%2014%20Pro&property=brand%3AApple"
|
||||
"""
|
||||
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)
|
||||
|
||||
|
||||
@@ -1,18 +0,0 @@
|
||||
from jobspy import scrape_jobs
|
||||
import pandas as pd
|
||||
|
||||
|
||||
def test_all():
|
||||
sites = [
|
||||
"indeed",
|
||||
"glassdoor",
|
||||
] # ziprecruiter/linkedin needs good ip, and temp fix to pass test on ci
|
||||
result = scrape_jobs(
|
||||
site_name=sites,
|
||||
search_term="engineer",
|
||||
results_wanted=5,
|
||||
)
|
||||
|
||||
assert (
|
||||
isinstance(result, pd.DataFrame) and len(result) == len(sites) * 5
|
||||
), "Result should be a non-empty DataFrame"
|
||||
@@ -1,13 +0,0 @@
|
||||
from jobspy import scrape_jobs
|
||||
import pandas as pd
|
||||
|
||||
|
||||
def test_glassdoor():
|
||||
result = scrape_jobs(
|
||||
site_name="glassdoor",
|
||||
search_term="engineer",
|
||||
results_wanted=5,
|
||||
)
|
||||
assert (
|
||||
isinstance(result, pd.DataFrame) and len(result) == 5
|
||||
), "Result should be a non-empty DataFrame"
|
||||
@@ -1,13 +0,0 @@
|
||||
from jobspy import scrape_jobs
|
||||
import pandas as pd
|
||||
|
||||
|
||||
def test_indeed():
|
||||
result = scrape_jobs(
|
||||
site_name="indeed",
|
||||
search_term="engineer",
|
||||
results_wanted=5,
|
||||
)
|
||||
assert (
|
||||
isinstance(result, pd.DataFrame) and len(result) == 5
|
||||
), "Result should be a non-empty DataFrame"
|
||||
@@ -1,9 +0,0 @@
|
||||
from jobspy import scrape_jobs
|
||||
import pandas as pd
|
||||
|
||||
|
||||
def test_linkedin():
|
||||
result = scrape_jobs(site_name="linkedin", search_term="engineer", results_wanted=5)
|
||||
assert (
|
||||
isinstance(result, pd.DataFrame) and len(result) == 5
|
||||
), "Result should be a non-empty DataFrame"
|
||||
@@ -1,12 +0,0 @@
|
||||
from jobspy import scrape_jobs
|
||||
import pandas as pd
|
||||
|
||||
|
||||
def test_ziprecruiter():
|
||||
result = scrape_jobs(
|
||||
site_name="zip_recruiter", search_term="software engineer", results_wanted=5
|
||||
)
|
||||
|
||||
assert (
|
||||
isinstance(result, pd.DataFrame) and len(result) == 5
|
||||
), "Result should be a non-empty DataFrame"
|
||||
Reference in New Issue
Block a user