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41
.github/workflows/publish-to-pypi.yml
vendored
41
.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 }}
|
||||
password: ${{ secrets.PYPI_API_TOKEN }}
|
||||
|
||||
137
README.md
137
README.md
@@ -2,16 +2,11 @@
|
||||
|
||||
**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.*
|
||||
|
||||
## 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** simultaneously
|
||||
- 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"],
|
||||
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
|
||||
| (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**
|
||||
@@ -217,7 +175,23 @@ 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 +203,41 @@ 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}")
|
||||
1901
poetry.lock
generated
1901
poetry.lock
generated
File diff suppressed because it is too large
Load Diff
@@ -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 = "1.1.70"
|
||||
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"
|
||||
@@ -19,19 +25,11 @@ pandas = "^2.1.0"
|
||||
NUMPY = "1.26.3"
|
||||
pydantic = "^2.3.0"
|
||||
tls-client = "^1.0.1"
|
||||
markdownify = "^0.11.6"
|
||||
markdownify = "^0.13.1"
|
||||
regex = "^2024.4.28"
|
||||
|
||||
|
||||
[tool.poetry.group.dev.dependencies]
|
||||
pytest = "^7.4.1"
|
||||
jupyter = "^1.0.0"
|
||||
black = "*"
|
||||
pre-commit = "*"
|
||||
|
||||
[build-system]
|
||||
requires = ["poetry-core"]
|
||||
build-backend = "poetry.core.masonry.api"
|
||||
|
||||
[tool.black]
|
||||
line-length = 88
|
||||
|
||||
@@ -9,6 +9,7 @@ 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 import SalarySource, ScraperInput, Site, JobResponse, Country
|
||||
from .scrapers.exceptions import (
|
||||
@@ -16,12 +17,14 @@ from .scrapers.exceptions import (
|
||||
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,
|
||||
@@ -50,6 +53,7 @@ def scrape_jobs(
|
||||
Site.INDEED: IndeedScraper,
|
||||
Site.ZIP_RECRUITER: ZipRecruiterScraper,
|
||||
Site.GLASSDOOR: GlassdoorScraper,
|
||||
Site.GOOGLE: GoogleJobsScraper,
|
||||
}
|
||||
set_logger_level(verbose)
|
||||
|
||||
@@ -83,6 +87,7 @@ 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 +218,8 @@ def scrape_jobs(
|
||||
"title",
|
||||
"company",
|
||||
"location",
|
||||
"job_type",
|
||||
"date_posted",
|
||||
"job_type",
|
||||
"salary_source",
|
||||
"interval",
|
||||
"min_amount",
|
||||
@@ -223,12 +228,12 @@ 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 +250,8 @@ 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 +17,18 @@ class Site(Enum):
|
||||
INDEED = "indeed"
|
||||
ZIP_RECRUITER = "zip_recruiter"
|
||||
GLASSDOOR = "glassdoor"
|
||||
GOOGLE = "google"
|
||||
|
||||
|
||||
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 +46,9 @@ 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
|
||||
|
||||
@@ -24,3 +24,8 @@ 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")
|
||||
|
||||
@@ -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,
|
||||
)
|
||||
|
||||
|
||||
250
src/jobspy/scrapers/google/__init__.py
Normal file
250
src/jobspy/scrapers/google/__init__.py
Normal file
@@ -0,0 +1,250 @@
|
||||
"""
|
||||
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,
|
||||
)
|
||||
|
||||
logger = 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:
|
||||
logger.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
|
||||
):
|
||||
logger.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:
|
||||
logger.error(f"failed to get jobs on page: {page}, {e}")
|
||||
break
|
||||
if not jobs:
|
||||
logger.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:
|
||||
logger.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"
|
||||
@@ -69,17 +69,10 @@ class IndeedScraper(Scraper):
|
||||
page = 1
|
||||
|
||||
cursor = None
|
||||
offset_pages = math.ceil(self.scraper_input.offset / 100)
|
||||
for _ in range(offset_pages):
|
||||
logger.info(f"skipping search page: {page}")
|
||||
__, cursor = self._scrape_page(cursor)
|
||||
if not __:
|
||||
logger.info(f"found no jobs on page: {page}")
|
||||
break
|
||||
|
||||
while len(self.seen_urls) < scraper_input.results_wanted:
|
||||
while len(self.seen_urls) < scraper_input.results_wanted + scraper_input.offset:
|
||||
logger.info(
|
||||
f"search page: {page} / {math.ceil(scraper_input.results_wanted / 100)}"
|
||||
f"search page: {page} / {math.ceil(scraper_input.results_wanted / self.jobs_per_page)}"
|
||||
)
|
||||
jobs, cursor = self._scrape_page(cursor)
|
||||
if not jobs:
|
||||
@@ -87,7 +80,12 @@ class IndeedScraper(Scraper):
|
||||
break
|
||||
job_list += jobs
|
||||
page += 1
|
||||
return JobResponse(jobs=job_list[: scraper_input.results_wanted])
|
||||
return JobResponse(
|
||||
jobs=job_list[
|
||||
scraper_input.offset : scraper_input.offset
|
||||
+ scraper_input.results_wanted
|
||||
]
|
||||
)
|
||||
|
||||
def _scrape_page(self, cursor: str | None) -> Tuple[list[JobPost], str | None]:
|
||||
"""
|
||||
@@ -260,7 +258,7 @@ class IndeedScraper(Scraper):
|
||||
company_num_employees=employer_details.get("employeesLocalizedLabel"),
|
||||
company_revenue=employer_details.get("revenueLocalizedLabel"),
|
||||
company_description=employer_details.get("briefDescription"),
|
||||
logo_photo_url=(
|
||||
company_logo=(
|
||||
employer["images"].get("squareLogoUrl")
|
||||
if employer and employer.get("images")
|
||||
else None
|
||||
|
||||
@@ -232,7 +232,7 @@ class LinkedInScraper(Scraper):
|
||||
description=job_details.get("description"),
|
||||
job_url_direct=job_details.get("job_url_direct"),
|
||||
emails=extract_emails_from_text(job_details.get("description")),
|
||||
logo_photo_url=job_details.get("logo_photo_url"),
|
||||
company_logo=job_details.get("company_logo"),
|
||||
job_function=job_details.get("job_function"),
|
||||
)
|
||||
|
||||
@@ -275,7 +275,7 @@ class LinkedInScraper(Scraper):
|
||||
if job_function_span:
|
||||
job_function = job_function_span.text.strip()
|
||||
|
||||
logo_photo_url = (
|
||||
company_logo = (
|
||||
logo_image.get("data-delayed-url")
|
||||
if (logo_image := soup.find("img", {"class": "artdeco-entity-image"}))
|
||||
else None
|
||||
@@ -286,7 +286,7 @@ class LinkedInScraper(Scraper):
|
||||
"company_industry": self._parse_company_industry(soup),
|
||||
"job_type": self._parse_job_type(soup),
|
||||
"job_url_direct": self._parse_job_url_direct(soup),
|
||||
"logo_photo_url": logo_photo_url,
|
||||
"company_logo": company_logo,
|
||||
"job_function": job_function,
|
||||
}
|
||||
|
||||
|
||||
@@ -264,3 +264,22 @@ def extract_salary(
|
||||
else:
|
||||
return interval, min_salary, max_salary, "USD"
|
||||
return None, None, None, None
|
||||
|
||||
|
||||
def extract_job_type(description: str):
|
||||
if not description:
|
||||
return []
|
||||
|
||||
keywords = {
|
||||
JobType.FULL_TIME: r"full\s?time",
|
||||
JobType.PART_TIME: r"part\s?time",
|
||||
JobType.INTERNSHIP: r"internship",
|
||||
JobType.CONTRACT: r"contract",
|
||||
}
|
||||
|
||||
listing_types = []
|
||||
for key, pattern in keywords.items():
|
||||
if re.search(pattern, description, re.IGNORECASE):
|
||||
listing_types.append(key)
|
||||
|
||||
return listing_types if listing_types else None
|
||||
|
||||
12
tests/test_google.py
Normal file
12
tests/test_google.py
Normal file
@@ -0,0 +1,12 @@
|
||||
from jobspy import scrape_jobs
|
||||
import pandas as pd
|
||||
|
||||
|
||||
def test_google():
|
||||
result = scrape_jobs(
|
||||
site_name="google", search_term="software engineer", results_wanted=5
|
||||
)
|
||||
|
||||
assert (
|
||||
isinstance(result, pd.DataFrame) and len(result) == 5
|
||||
), "Result should be a non-empty DataFrame"
|
||||
Reference in New Issue
Block a user