Compare commits

..

51 Commits

Author SHA1 Message Date
Cullen Watson
7cb0c518fc docs:readme 2025-02-21 12:53:59 -06:00
Cullen Watson
df70d4bc2e minor 2025-02-21 12:35:31 -06:00
Cullen Watson
3006063875 enh:remove log by default 2025-02-21 12:31:04 -06:00
Abdulrahman Hisham
1be009b8bc Adding Bayt.com Scraper to current codebase (#246) 2025-02-21 12:29:54 -06:00
Cullen Watson
81ed9b3ddf enh:remove log by default 2025-02-21 12:29:28 -06:00
Abdulrahman Al Muaitah
11a9e9a56a Fixed Bayt scraper integration 2025-02-21 20:10:02 +04:00
Abdulrahman Al Muaitah
c6ade14784 Added Bayt Scraper integration 2025-02-21 15:31:29 +04:00
Cullen Watson
13c74a0fed docs:readme 2025-02-09 13:42:18 -06:00
Cullen Watson
333e9e6760 docs:readme 2025-01-17 21:44:49 -06:00
github-actions
04032a0f91 Increment version 2024-12-04 22:55:06 +00:00
Cullen Watson
496896d0b5 enh:fix yml (#225) 2024-12-04 16:54:52 -06:00
Cullen Watson
87ba1ad1bf fix yml 2024-12-04 16:52:15 -06:00
Jason Geffner
4e7ac9a583 Fix Google job search (#223)
The previous regex did not capture all expected matches in the returned content
2024-12-04 16:45:59 -06:00
Cullen Watson
e44d13e1cf enh:auto update version 2024-12-04 16:29:38 -06:00
Cullen Watson
d52e366ef7 docs:readme 2024-11-26 15:51:26 -06:00
Cullen Watson
395ebf0017 docs:readme 2024-11-26 15:49:12 -06:00
Cullen Watson
63fddd9b7f docs:readme 2024-11-26 15:48:22 -06:00
Cullen Watson
58956868ae docs:readme 2024-11-26 15:47:10 -06:00
Cullen Watson
4fce836222 docs:readme 2024-10-28 03:53:59 -05:00
Cullen Watson
5ba25e7a7c docs:readme 2024-10-28 03:42:19 -05:00
Cullen Watson
f7cb3e9206 docs:readme 2024-10-28 03:36:21 -05:00
Cullen Watson
3ad3f121f7 docs:readme 2024-10-28 03:34:52 -05:00
Cullen Watson
ff3c782912 docs:readme 2024-10-25 18:12:08 -05:00
Cullen Watson
338d854b96 fix(google): search (#216) 2024-10-25 14:54:14 -05:00
Cullen Watson
811d4c40b4 chore:version 2024-10-24 15:28:25 -05:00
Cullen Watson
dba92d22c2 chore:version 2024-10-24 15:27:16 -05:00
Cullen Watson
10a3592a0f docs:file 2024-10-24 15:26:49 -05:00
Cullen Watson
b7905cc756 docs:file 2024-10-24 15:24:18 -05:00
Cullen Watson
6867d58829 docs:readme 2024-10-24 15:22:31 -05:00
Cullen Watson
f6248c8386 enh: google jobs (#214) 2024-10-24 15:19:40 -05:00
Cullen Watson
f395597fdd fix(indeed): offset 2024-10-22 19:25:07 -05:00
Cullen Watson
6372e41bd9 chore:version 2024-10-20 00:19:31 -05:00
Olzhas Arystanov
6c869decb8 build(deps): bump markdownify to 0.13.1 (#211) 2024-10-20 00:18:44 -05:00
Cullen Watson
9f4083380d indeed:remove tpe (#210) 2024-10-19 18:01:59 -05:00
Olzhas Arystanov
9207ab56f6 fix: extract tests out of src (#209) 2024-10-19 16:56:38 -05:00
Cullen Watson
757a94853e chore:version 2024-10-08 17:49:06 -05:00
Marcel Gozalbo Baró
6bc191d5c7 FEATURE: Add the "ca_cert" setting for providing a Certification Authority certificate in order to use proxies requiring it. (#204) 2024-10-08 17:46:46 -05:00
Cullen Watson
0cc34287f7 fix:turkey 2024-10-02 01:31:00 -05:00
Anton Pikhteryev
923979093b Add Malta for linkedin country support (#198) 2024-09-19 20:41:22 -05:00
Cullen Watson
286f0e4487 docs:readme 2024-09-18 18:49:41 -05:00
Cullen Watson
f7b29d43a2 fix(indeed):sort relevance not date (#197) 2024-09-18 18:42:25 -05:00
Cullen Watson
6f1490458c fix key error (#186) 2024-08-14 02:54:40 -05:00
Cullen Watson
6bb7d81ba8 change linkedin ep (#185) 2024-08-14 02:39:43 -05:00
Cullen Watson
0e046432d1 fix:variable bug (#181) 2024-08-05 12:47:55 -05:00
Cullen Watson
209e0e65b6 fix:malaysia indeed (#180) 2024-08-03 22:48:53 -05:00
Cullen Watson
8570c0651e fix:key error (#176) 2024-07-21 13:05:18 -05:00
Cullen Watson
8678b0bbe4 enh: test on pr (#174) 2024-07-19 14:25:25 -05:00
Cullen Watson
60d4d911c9 lock file (#173) 2024-07-17 21:21:22 -05:00
Lluís Salord Quetglas
2a0cba8c7e FEAT: Optional convertion to annual and know salary source (#170) 2024-07-17 21:05:33 -05:00
Mason DePalma
de70189fa2 Update pyproject.toml (#172)
Changed Numpy to the most recent version so the package can properly install
2024-07-17 20:54:08 -05:00
Cullen Watson
b55c0eb86d docs:readme 2024-07-16 19:24:38 -05:00
28 changed files with 2273 additions and 1683 deletions

View File

@@ -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 }}

149
README.md
View File

@@ -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
![jobspy](https://github.com/cullenwatson/JobSpy/assets/78247585/ec7ef355-05f6-4fd3-8161-a817e31c5c57)
@@ -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 full description , direct job url , company industry and job level (seniority level) 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)
@@ -79,14 +77,14 @@ Optional
├── proxies (list):
| in format ['user:pass@host:port', 'localhost']
| each job board scraper will round robin through the 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.)
@@ -110,6 +108,12 @@ Optional
|
├── country_indeed (str):
| filters the country on Indeed & Glassdoor (see below for correct spelling)
|
├── enforce_annual_salary (bool):
| converts wages to annual salary
|
├── ca_cert (str)
| path to CA Certificate file for proxies
```
```
@@ -125,49 +129,6 @@ Optional
| - easy_apply
```
### JobPost Schema
```plaintext
JobPost
├── title (str)
├── company (str)
├── company_url (str)
├── job_url (str)
├── location (object)
│ ├── country (str)
│ ├── city (str)
│ ├── state (str)
├── description (str)
├── job_type (str): fulltime, parttime, internship, contract
├── job_function (str)
├── compensation (object)
│ ├── interval (str): yearly, monthly, weekly, daily, hourly
│ ├── min_amount (int)
│ ├── max_amount (int)
│ └── currency (enum)
├── date_posted (date)
├── emails (str)
└── is_remote (bool)
Linkedin specific
└── job_level (str)
Linkedin & Indeed specific
└── company_industry (str)
Indeed specific
├── company_country (str)
└── company_addresses (str)
└── company_employees_label (str)
└── company_revenue_label (str)
└── company_description (str)
└── ceo_name (str)
└── ceo_photo_url (str)
└── logo_photo_url (str)
└── banner_photo_url (str)
```
## Supported Countries for Job Searching
### **LinkedIn**
@@ -204,6 +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.
@@ -213,10 +179,24 @@ You can specify the following countries when searching on Indeed (use the exact
## Frequently Asked Questions
---
**Q: Why is Indeed giving unrelated roles?**
**A:** Indeed searches the description too.
**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).
- 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.
---
@@ -227,3 +207,42 @@ persist, [submit an issue](https://github.com/Bunsly/JobSpy/issues).
- Try using the proxies param to change your IP address.
---
### 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
View 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}")

2183
poetry.lock generated

File diff suppressed because it is too large Load Diff

View File

@@ -1,36 +1,35 @@
[build-system]
requires = [ "poetry-core",]
build-backend = "poetry.core.masonry.api"
[tool.poetry]
name = "python-jobspy"
version = "1.1.59"
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",]
[[tool.poetry.packages]]
include = "jobspy"
from = "src"
packages = [
{ include = "jobspy", from = "src" }
]
[tool.black]
line-length = 88
[tool.poetry.dependencies]
python = "^3.10"
requests = "^2.31.0"
beautifulsoup4 = "^4.12.2"
pandas = "^2.1.0"
NUMPY = "1.24.2"
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

View File

View File

@@ -5,23 +5,27 @@ from typing import Tuple
from concurrent.futures import ThreadPoolExecutor, as_completed
from .jobs import JobType, Location
from .scrapers.utils import logger, set_logger_level, extract_salary
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 ScraperInput, Site, JobResponse, Country
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,
@@ -31,12 +35,14 @@ def scrape_jobs(
country_indeed: str = "usa",
hyperlinks: bool = False,
proxies: list[str] | str | None = None,
ca_cert: str | None = None,
description_format: str = "markdown",
linkedin_fetch_description: bool | None = False,
linkedin_company_ids: list[int] | None = None,
offset: int | None = 0,
hours_old: int = None,
verbose: int = 2,
enforce_annual_salary: bool = False,
verbose: int = 0,
**kwargs,
) -> pd.DataFrame:
"""
@@ -48,6 +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)
@@ -81,6 +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,
@@ -96,11 +105,11 @@ def scrape_jobs(
def scrape_site(site: Site) -> Tuple[str, JobResponse]:
scraper_class = SCRAPER_MAPPING[site]
scraper = scraper_class(proxies=proxies)
scraper = scraper_class(proxies=proxies, ca_cert=ca_cert)
scraped_data: JobResponse = scraper.scrape(scraper_input)
cap_name = site.value.capitalize()
site_name = "ZipRecruiter" if cap_name == "Zip_recruiter" else cap_name
logger.info(f"{site_name} finished scraping")
create_logger(site_name).info(f"finished scraping")
return site.value, scraped_data
site_to_jobs_dict = {}
@@ -165,7 +174,8 @@ def scrape_jobs(
job_data["min_amount"] = compensation_obj.get("min_amount")
job_data["max_amount"] = compensation_obj.get("max_amount")
job_data["currency"] = compensation_obj.get("currency", "USD")
if (
job_data["salary_source"] = SalarySource.DIRECT_DATA.value
if enforce_annual_salary and (
job_data["interval"]
and job_data["interval"] != "yearly"
and job_data["min_amount"]
@@ -180,8 +190,17 @@ def scrape_jobs(
job_data["min_amount"],
job_data["max_amount"],
job_data["currency"],
) = extract_salary(job_data["description"])
) = extract_salary(
job_data["description"],
enforce_annual_salary=enforce_annual_salary,
)
job_data["salary_source"] = SalarySource.DESCRIPTION.value
job_data["salary_source"] = (
job_data["salary_source"]
if "min_amount" in job_data and job_data["min_amount"]
else None
)
job_df = pd.DataFrame([job_data])
jobs_dfs.append(job_df)
@@ -201,8 +220,9 @@ def scrape_jobs(
"title",
"company",
"location",
"job_type",
"date_posted",
"job_type",
"salary_source",
"interval",
"min_amount",
"max_amount",
@@ -210,20 +230,17 @@ def scrape_jobs(
"is_remote",
"job_level",
"job_function",
"company_industry",
"listing_type",
"emails",
"description",
"company_industry",
"company_url",
"company_logo",
"company_url_direct",
"company_addresses",
"company_num_employees",
"company_revenue",
"company_description",
"logo_photo_url",
"banner_photo_url",
"ceo_name",
"ceo_photo_url",
]
# Step 3: Ensure all desired columns are present, adding missing ones as empty
@@ -235,6 +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()

View File

@@ -92,7 +92,8 @@ class Country(Enum):
JAPAN = ("japan", "jp")
KUWAIT = ("kuwait", "kw")
LUXEMBOURG = ("luxembourg", "lu")
MALAYSIA = ("malaysia", "malaysia")
MALAYSIA = ("malaysia", "malaysia:my", "com")
MALTA = ("malta", "malta:mt", "mt")
MEXICO = ("mexico", "mx", "com.mx")
MOROCCO = ("morocco", "ma")
NETHERLANDS = ("netherlands", "nl", "nl")
@@ -117,7 +118,7 @@ class Country(Enum):
SWITZERLAND = ("switzerland", "ch", "de:ch")
TAIWAN = ("taiwan", "tw")
THAILAND = ("thailand", "th")
TURKEY = ("turkey", "tr")
TURKEY = ("türkiye,turkey", "tr")
UKRAINE = ("ukraine", "ua")
UNITEDARABEMIRATES = ("united arab emirates", "ae")
UK = ("uk,united kingdom", "uk:gb", "co.uk")
@@ -255,9 +256,7 @@ class JobPost(BaseModel):
company_num_employees: str | None = None
company_revenue: str | None = None
company_description: str | None = None
ceo_name: str | None = None
ceo_photo_url: str | None = None
logo_photo_url: str | None = None
company_logo: str | None = None
banner_photo_url: str | None = None
# linkedin only atm

View File

@@ -17,11 +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
@@ -39,9 +47,12 @@ class ScraperInput(BaseModel):
class Scraper(ABC):
def __init__(self, site: Site, proxies: list[str] | None = None):
self.proxies = proxies
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: ...

View 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()

View File

@@ -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")

View File

@@ -14,13 +14,13 @@ from typing import Optional, Tuple
from datetime import datetime, timedelta
from concurrent.futures import ThreadPoolExecutor, as_completed
from .constants import fallback_token, query_template, headers
from .. import Scraper, ScraperInput, Site
from ..utils import extract_emails_from_text
from ..utils import extract_emails_from_text, create_logger
from ..exceptions import GlassdoorException
from ..utils import (
create_session,
markdown_converter,
logger,
)
from ...jobs import (
JobPost,
@@ -32,14 +32,18 @@ from ...jobs import (
DescriptionFormat,
)
log = create_logger("Glassdoor")
class GlassdoorScraper(Scraper):
def __init__(self, proxies: list[str] | str | None = None):
def __init__(
self, proxies: list[str] | str | None = None, ca_cert: str | None = None
):
"""
Initializes GlassdoorScraper with the Glassdoor job search url
"""
site = Site(Site.GLASSDOOR)
super().__init__(site, proxies=proxies)
super().__init__(site, proxies=proxies, ca_cert=ca_cert)
self.base_url = None
self.country = None
@@ -59,15 +63,18 @@ class GlassdoorScraper(Scraper):
self.scraper_input.results_wanted = min(900, scraper_input.results_wanted)
self.base_url = self.scraper_input.country.get_glassdoor_url()
self.session = create_session(proxies=self.proxies, is_tls=True, has_retry=True)
self.session = create_session(
proxies=self.proxies, ca_cert=self.ca_cert, has_retry=True
)
token = self._get_csrf_token()
self.headers["gd-csrf-token"] = token if token else self.fallback_token
headers["gd-csrf-token"] = token if token else fallback_token
self.session.headers.update(headers)
location_id, location_type = self._get_location(
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
@@ -76,7 +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"Glassdoor search page: {page}")
log.info(f"search page: {page} / {range_end - 1}")
try:
jobs, cursor = self._fetch_jobs_page(
scraper_input, location_id, location_type, page, cursor
@@ -86,7 +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)
@@ -107,7 +114,6 @@ class GlassdoorScraper(Scraper):
payload = self._add_payload(location_id, location_type, page_num, cursor)
response = self.session.post(
f"{self.base_url}/graph",
headers=self.headers,
timeout_seconds=15,
data=payload,
)
@@ -123,7 +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"]
@@ -148,9 +154,7 @@ class GlassdoorScraper(Scraper):
"""
Fetches csrf token needed for API by visiting a generic page
"""
res = self.session.get(
f"{self.base_url}/Job/computer-science-jobs.htm", headers=self.headers
)
res = self.session.get(f"{self.base_url}/Job/computer-science-jobs.htm")
pattern = r'"token":\s*"([^"]+)"'
matches = re.findall(pattern, res.text)
token = None
@@ -199,7 +203,7 @@ class GlassdoorScraper(Scraper):
.lower()
)
return JobPost(
id=str(job_id),
id=f"gd-{job_id}",
title=title,
company_url=company_url if company_id else None,
company_name=company_name,
@@ -210,7 +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,
)
@@ -243,7 +247,7 @@ class GlassdoorScraper(Scraper):
""",
}
]
res = requests.post(url, json=body, headers=self.headers)
res = requests.post(url, json=body, headers=headers)
if res.status_code != 200:
return None
data = res.json()[0]
@@ -256,16 +260,16 @@ class GlassdoorScraper(Scraper):
if not location or is_remote:
return "11047", "STATE" # remote options
url = f"{self.base_url}/findPopularLocationAjax.htm?maxLocationsToReturn=10&term={location}"
res = self.session.get(url, headers=self.headers)
res = self.session.get(url)
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()
@@ -310,7 +314,7 @@ class GlassdoorScraper(Scraper):
"fromage": fromage,
"sort": "date",
},
"query": self.query_template,
"query": query_template,
}
if self.scraper_input.job_type:
payload["variables"]["filterParams"].append(
@@ -358,188 +362,3 @@ class GlassdoorScraper(Scraper):
for cursor_data in pagination_cursors:
if cursor_data["pageNumber"] == page_num:
return cursor_data["cursor"]
fallback_token = "Ft6oHEWlRZrxDww95Cpazw:0pGUrkb2y3TyOpAIqF2vbPmUXoXVkD3oEGDVkvfeCerceQ5-n8mBg3BovySUIjmCPHCaW0H2nQVdqzbtsYqf4Q:wcqRqeegRUa9MVLJGyujVXB7vWFPjdaS1CtrrzJq-ok"
headers = {
"authority": "www.glassdoor.com",
"accept": "*/*",
"accept-language": "en-US,en;q=0.9",
"apollographql-client-name": "job-search-next",
"apollographql-client-version": "4.65.5",
"content-type": "application/json",
"origin": "https://www.glassdoor.com",
"referer": "https://www.glassdoor.com/",
"sec-ch-ua": '"Chromium";v="118", "Google Chrome";v="118", "Not=A?Brand";v="99"',
"sec-ch-ua-mobile": "?0",
"sec-ch-ua-platform": '"macOS"',
"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/118.0.0.0 Safari/537.36",
}
query_template = """
query JobSearchResultsQuery(
$excludeJobListingIds: [Long!],
$keyword: String,
$locationId: Int,
$locationType: LocationTypeEnum,
$numJobsToShow: Int!,
$pageCursor: String,
$pageNumber: Int,
$filterParams: [FilterParams],
$originalPageUrl: String,
$seoFriendlyUrlInput: String,
$parameterUrlInput: String,
$seoUrl: Boolean
) {
jobListings(
contextHolder: {
searchParams: {
excludeJobListingIds: $excludeJobListingIds,
keyword: $keyword,
locationId: $locationId,
locationType: $locationType,
numPerPage: $numJobsToShow,
pageCursor: $pageCursor,
pageNumber: $pageNumber,
filterParams: $filterParams,
originalPageUrl: $originalPageUrl,
seoFriendlyUrlInput: $seoFriendlyUrlInput,
parameterUrlInput: $parameterUrlInput,
seoUrl: $seoUrl,
searchType: SR
}
}
) {
companyFilterOptions {
id
shortName
__typename
}
filterOptions
indeedCtk
jobListings {
...JobView
__typename
}
jobListingSeoLinks {
linkItems {
position
url
__typename
}
__typename
}
jobSearchTrackingKey
jobsPageSeoData {
pageMetaDescription
pageTitle
__typename
}
paginationCursors {
cursor
pageNumber
__typename
}
indexablePageForSeo
searchResultsMetadata {
searchCriteria {
implicitLocation {
id
localizedDisplayName
type
__typename
}
keyword
location {
id
shortName
localizedShortName
localizedDisplayName
type
__typename
}
__typename
}
helpCenterDomain
helpCenterLocale
jobSerpJobOutlook {
occupation
paragraph
__typename
}
showMachineReadableJobs
__typename
}
totalJobsCount
__typename
}
}
fragment JobView on JobListingSearchResult {
jobview {
header {
adOrderId
advertiserType
adOrderSponsorshipLevel
ageInDays
divisionEmployerName
easyApply
employer {
id
name
shortName
__typename
}
employerNameFromSearch
goc
gocConfidence
gocId
jobCountryId
jobLink
jobResultTrackingKey
jobTitleText
locationName
locationType
locId
needsCommission
payCurrency
payPeriod
payPeriodAdjustedPay {
p10
p50
p90
__typename
}
rating
salarySource
savedJobId
sponsored
__typename
}
job {
description
importConfigId
jobTitleId
jobTitleText
listingId
__typename
}
jobListingAdminDetails {
cpcVal
importConfigId
jobListingId
jobSourceId
userEligibleForAdminJobDetails
__typename
}
overview {
shortName
squareLogoUrl
__typename
}
__typename
}
__typename
}
"""

View File

@@ -0,0 +1,184 @@
headers = {
"authority": "www.glassdoor.com",
"accept": "*/*",
"accept-language": "en-US,en;q=0.9",
"apollographql-client-name": "job-search-next",
"apollographql-client-version": "4.65.5",
"content-type": "application/json",
"origin": "https://www.glassdoor.com",
"referer": "https://www.glassdoor.com/",
"sec-ch-ua": '"Chromium";v="118", "Google Chrome";v="118", "Not=A?Brand";v="99"',
"sec-ch-ua-mobile": "?0",
"sec-ch-ua-platform": '"macOS"',
"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/118.0.0.0 Safari/537.36",
}
query_template = """
query JobSearchResultsQuery(
$excludeJobListingIds: [Long!],
$keyword: String,
$locationId: Int,
$locationType: LocationTypeEnum,
$numJobsToShow: Int!,
$pageCursor: String,
$pageNumber: Int,
$filterParams: [FilterParams],
$originalPageUrl: String,
$seoFriendlyUrlInput: String,
$parameterUrlInput: String,
$seoUrl: Boolean
) {
jobListings(
contextHolder: {
searchParams: {
excludeJobListingIds: $excludeJobListingIds,
keyword: $keyword,
locationId: $locationId,
locationType: $locationType,
numPerPage: $numJobsToShow,
pageCursor: $pageCursor,
pageNumber: $pageNumber,
filterParams: $filterParams,
originalPageUrl: $originalPageUrl,
seoFriendlyUrlInput: $seoFriendlyUrlInput,
parameterUrlInput: $parameterUrlInput,
seoUrl: $seoUrl,
searchType: SR
}
}
) {
companyFilterOptions {
id
shortName
__typename
}
filterOptions
indeedCtk
jobListings {
...JobView
__typename
}
jobListingSeoLinks {
linkItems {
position
url
__typename
}
__typename
}
jobSearchTrackingKey
jobsPageSeoData {
pageMetaDescription
pageTitle
__typename
}
paginationCursors {
cursor
pageNumber
__typename
}
indexablePageForSeo
searchResultsMetadata {
searchCriteria {
implicitLocation {
id
localizedDisplayName
type
__typename
}
keyword
location {
id
shortName
localizedShortName
localizedDisplayName
type
__typename
}
__typename
}
helpCenterDomain
helpCenterLocale
jobSerpJobOutlook {
occupation
paragraph
__typename
}
showMachineReadableJobs
__typename
}
totalJobsCount
__typename
}
}
fragment JobView on JobListingSearchResult {
jobview {
header {
adOrderId
advertiserType
adOrderSponsorshipLevel
ageInDays
divisionEmployerName
easyApply
employer {
id
name
shortName
__typename
}
employerNameFromSearch
goc
gocConfidence
gocId
jobCountryId
jobLink
jobResultTrackingKey
jobTitleText
locationName
locationType
locId
needsCommission
payCurrency
payPeriod
payPeriodAdjustedPay {
p10
p50
p90
__typename
}
rating
salarySource
savedJobId
sponsored
__typename
}
job {
description
importConfigId
jobTitleId
jobTitleText
listingId
__typename
}
jobListingAdminDetails {
cpcVal
importConfigId
jobListingId
jobSourceId
userEligibleForAdminJobDetails
__typename
}
overview {
shortName
squareLogoUrl
__typename
}
__typename
}
__typename
}
"""
fallback_token = "Ft6oHEWlRZrxDww95Cpazw:0pGUrkb2y3TyOpAIqF2vbPmUXoXVkD3oEGDVkvfeCerceQ5-n8mBg3BovySUIjmCPHCaW0H2nQVdqzbtsYqf4Q:wcqRqeegRUa9MVLJGyujVXB7vWFPjdaS1CtrrzJq-ok"

View 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

View 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"

View File

@@ -10,15 +10,15 @@ from __future__ import annotations
import math
from typing import Tuple
from datetime import datetime
from concurrent.futures import ThreadPoolExecutor, Future
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,
logger,
create_session,
create_logger,
)
from ...jobs import (
JobPost,
@@ -30,15 +30,21 @@ from ...jobs import (
DescriptionFormat,
)
log = create_logger("Indeed")
class IndeedScraper(Scraper):
def __init__(self, proxies: list[str] | str | None = None):
def __init__(
self, proxies: list[str] | str | None = None, ca_cert: str | None = None
):
"""
Initializes IndeedScraper with the Indeed API url
"""
super().__init__(Site.INDEED, proxies=proxies)
self.session = create_session(proxies=self.proxies, is_tls=False)
self.session = create_session(
proxies=self.proxies, ca_cert=ca_cert, is_tls=False
)
self.scraper_input = None
self.jobs_per_page = 100
self.num_workers = 10
@@ -57,29 +63,29 @@ class IndeedScraper(Scraper):
self.scraper_input = scraper_input
domain, self.api_country_code = self.scraper_input.country.indeed_domain_value
self.base_url = f"https://{domain}.indeed.com"
self.headers = self.api_headers.copy()
self.headers = api_headers.copy()
self.headers["indeed-co"] = self.scraper_input.country.indeed_domain_value
job_list = []
page = 1
cursor = None
offset_pages = math.ceil(self.scraper_input.offset / 100)
for _ in range(offset_pages):
logger.info(f"Indeed skipping search page: {page}")
__, cursor = self._scrape_page(cursor)
if not __:
logger.info(f"Indeed found no jobs on page: {page}")
break
while len(self.seen_urls) < scraper_input.results_wanted:
logger.info(f"Indeed search page: {page}")
while len(self.seen_urls) < scraper_input.results_wanted + scraper_input.offset:
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"Indeed found no jobs on page: {page}")
log.info(f"found no jobs on page: {page}")
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]:
"""
@@ -95,7 +101,7 @@ class IndeedScraper(Scraper):
if self.scraper_input.search_term
else ""
)
query = self.job_search_query.format(
query = job_search_query.format(
what=(f'what: "{search_term}"' if search_term else ""),
location=(
f'location: {{where: "{self.scraper_input.location}", radius: {self.scraper_input.distance}, radiusUnit: MILES}}'
@@ -109,28 +115,30 @@ class IndeedScraper(Scraper):
payload = {
"query": query,
}
api_headers = self.api_headers.copy()
api_headers["indeed-co"] = self.api_country_code
api_headers_temp = api_headers.copy()
api_headers_temp["indeed-co"] = self.api_country_code
response = self.session.post(
self.api_url,
headers=api_headers,
headers=api_headers_temp,
json=payload,
timeout=10,
verify=False,
)
if response.status_code != 200:
logger.info(
f"Indeed responded with status code: {response.status_code} (submit GitHub issue if this appears to be a bug)"
if not response.ok:
log.info(
f"responded with status code: {response.status_code} (submit GitHub issue if this appears to be a bug)"
)
return jobs, new_cursor
data = response.json()
jobs = data["data"]["jobSearch"]["results"]
new_cursor = data["data"]["jobSearch"]["pageInfo"]["nextCursor"]
with ThreadPoolExecutor(max_workers=self.num_workers) as executor:
job_results: list[Future] = [
executor.submit(self._process_job, job["job"]) for job in jobs
]
job_list = [result.result() for result in job_results if result.result()]
job_list = []
for job in jobs:
processed_job = self._process_job(job["job"])
if processed_job:
job_list.append(processed_job)
return job_list, new_cursor
def _build_filters(self):
@@ -212,7 +220,7 @@ class IndeedScraper(Scraper):
employer_details = employer.get("employerDetails", {}) if employer else {}
rel_url = job["employer"]["relativeCompanyPageUrl"] if job["employer"] else None
return JobPost(
id=str(job["key"]),
id=f'in-{job["key"]}',
title=job["title"],
description=description,
company_name=job["employer"].get("name") if job.get("employer") else None,
@@ -251,18 +259,11 @@ class IndeedScraper(Scraper):
company_num_employees=employer_details.get("employeesLocalizedLabel"),
company_revenue=employer_details.get("revenueLocalizedLabel"),
company_description=employer_details.get("briefDescription"),
ceo_name=employer_details.get("ceoName"),
ceo_photo_url=employer_details.get("ceoPhotoUrl"),
logo_photo_url=(
company_logo=(
employer["images"].get("squareLogoUrl")
if employer and employer.get("images")
else None
),
banner_photo_url=(
employer["images"].get("headerImageUrl")
if employer and employer.get("images")
else None
),
)
@staticmethod
@@ -347,112 +348,3 @@ class IndeedScraper(Scraper):
return CompensationInterval[mapped_interval]
else:
raise ValueError(f"Unsupported interval: {interval}")
api_headers = {
"Host": "apis.indeed.com",
"content-type": "application/json",
"indeed-api-key": "161092c2017b5bbab13edb12461a62d5a833871e7cad6d9d475304573de67ac8",
"accept": "application/json",
"indeed-locale": "en-US",
"accept-language": "en-US,en;q=0.9",
"user-agent": "Mozilla/5.0 (iPhone; CPU iPhone OS 16_6_1 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) Mobile/15E148 Indeed App 193.1",
"indeed-app-info": "appv=193.1; appid=com.indeed.jobsearch; osv=16.6.1; os=ios; dtype=phone",
}
job_search_query = """
query GetJobData {{
jobSearch(
{what}
{location}
limit: 100
sort: DATE
{cursor}
{filters}
) {{
pageInfo {{
nextCursor
}}
results {{
trackingKey
job {{
source {{
name
}}
key
title
datePublished
dateOnIndeed
description {{
html
}}
location {{
countryName
countryCode
admin1Code
city
postalCode
streetAddress
formatted {{
short
long
}}
}}
compensation {{
estimated {{
currencyCode
baseSalary {{
unitOfWork
range {{
... on Range {{
min
max
}}
}}
}}
}}
baseSalary {{
unitOfWork
range {{
... on Range {{
min
max
}}
}}
}}
currencyCode
}}
attributes {{
key
label
}}
employer {{
relativeCompanyPageUrl
name
dossier {{
employerDetails {{
addresses
industry
employeesLocalizedLabel
revenueLocalizedLabel
briefDescription
ceoName
ceoPhotoUrl
}}
images {{
headerImageUrl
squareLogoUrl
}}
links {{
corporateWebsite
}}
}}
}}
recruit {{
viewJobUrl
detailedSalary
workSchedule
}}
}}
}}
}}
}}
"""

View File

@@ -0,0 +1,109 @@
job_search_query = """
query GetJobData {{
jobSearch(
{what}
{location}
limit: 100
{cursor}
sort: RELEVANCE
{filters}
) {{
pageInfo {{
nextCursor
}}
results {{
trackingKey
job {{
source {{
name
}}
key
title
datePublished
dateOnIndeed
description {{
html
}}
location {{
countryName
countryCode
admin1Code
city
postalCode
streetAddress
formatted {{
short
long
}}
}}
compensation {{
estimated {{
currencyCode
baseSalary {{
unitOfWork
range {{
... on Range {{
min
max
}}
}}
}}
}}
baseSalary {{
unitOfWork
range {{
... on Range {{
min
max
}}
}}
}}
currencyCode
}}
attributes {{
key
label
}}
employer {{
relativeCompanyPageUrl
name
dossier {{
employerDetails {{
addresses
industry
employeesLocalizedLabel
revenueLocalizedLabel
briefDescription
ceoName
ceoPhotoUrl
}}
images {{
headerImageUrl
squareLogoUrl
}}
links {{
corporateWebsite
}}
}}
}}
recruit {{
viewJobUrl
detailedSalary
workSchedule
}}
}}
}}
}}
}}
"""
api_headers = {
"Host": "apis.indeed.com",
"content-type": "application/json",
"indeed-api-key": "161092c2017b5bbab13edb12461a62d5a833871e7cad6d9d475304573de67ac8",
"accept": "application/json",
"indeed-locale": "en-US",
"accept-language": "en-US,en;q=0.9",
"user-agent": "Mozilla/5.0 (iPhone; CPU iPhone OS 16_6_1 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) Mobile/15E148 Indeed App 193.1",
"indeed-app-info": "appv=193.1; appid=com.indeed.jobsearch; osv=16.6.1; os=ios; dtype=phone",
}

View File

@@ -7,6 +7,7 @@ This module contains routines to scrape LinkedIn.
from __future__ import annotations
import math
import time
import random
import regex as re
@@ -17,9 +18,10 @@ from bs4.element import Tag
from bs4 import BeautifulSoup
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
from ..utils import create_session, remove_attributes, create_logger
from ...jobs import (
JobPost,
Location,
@@ -30,13 +32,14 @@ from ...jobs import (
DescriptionFormat,
)
from ..utils import (
logger,
extract_emails_from_text,
get_enum_from_job_type,
currency_parser,
markdown_converter,
)
log = create_logger("LinkedIn")
class LinkedInScraper(Scraper):
base_url = "https://www.linkedin.com"
@@ -44,19 +47,22 @@ class LinkedInScraper(Scraper):
band_delay = 4
jobs_per_page = 25
def __init__(self, proxies: list[str] | str | None = None):
def __init__(
self, proxies: list[str] | str | None = None, ca_cert: str | None = None
):
"""
Initializes LinkedInScraper with the LinkedIn job search url
"""
super().__init__(Site.LINKEDIN, proxies=proxies)
super().__init__(Site.LINKEDIN, proxies=proxies, ca_cert=ca_cert)
self.session = create_session(
proxies=self.proxies,
ca_cert=ca_cert,
is_tls=False,
has_retry=True,
delay=5,
clear_cookies=True,
)
self.session.headers.update(self.headers)
self.session.headers.update(headers)
self.scraper_input = None
self.country = "worldwide"
self.job_url_direct_regex = re.compile(r'(?<=\?url=)[^"]+')
@@ -70,17 +76,19 @@ class LinkedInScraper(Scraper):
self.scraper_input = scraper_input
job_list: list[JobPost] = []
seen_ids = set()
page = scraper_input.offset // 10 * 10 if scraper_input.offset else 0
start = scraper_input.offset // 10 * 10 if scraper_input.offset else 0
request_count = 0
seconds_old = (
scraper_input.hours_old * 3600 if scraper_input.hours_old else None
)
continue_search = (
lambda: len(job_list) < scraper_input.results_wanted and page < 1000
lambda: len(job_list) < scraper_input.results_wanted and start < 1000
)
while continue_search():
request_count += 1
logger.info(f"LinkedIn search page: {request_count}")
log.info(
f"search page: {request_count} / {math.ceil(scraper_input.results_wanted / 10)}"
)
params = {
"keywords": scraper_input.search_term,
"location": scraper_input.location,
@@ -92,7 +100,7 @@ class LinkedInScraper(Scraper):
else None
),
"pageNum": 0,
"start": page,
"start": start,
"f_AL": "true" if scraper_input.easy_apply else None,
"f_C": (
",".join(map(str, scraper_input.linkedin_company_ids))
@@ -118,13 +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")
@@ -154,7 +162,7 @@ class LinkedInScraper(Scraper):
if continue_search():
time.sleep(random.uniform(self.delay, self.delay + self.band_delay))
page += len(job_list)
start += len(job_list)
job_list = job_list[: scraper_input.results_wanted]
return JobResponse(jobs=job_list)
@@ -210,7 +218,7 @@ class LinkedInScraper(Scraper):
job_details = self._get_job_details(job_id)
return JobPost(
id=job_id,
id=f"li-{job_id}",
title=title,
company_name=company,
company_url=company_url,
@@ -224,7 +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"),
)
@@ -236,7 +244,7 @@ class LinkedInScraper(Scraper):
"""
try:
response = self.session.get(
f"{self.base_url}/jobs-guest/jobs/api/jobPosting/{job_id}", timeout=5
f"{self.base_url}/jobs/view/{job_id}", timeout=5
)
response.raise_for_status()
except:
@@ -266,15 +274,19 @@ class LinkedInScraper(Scraper):
)
if job_function_span:
job_function = job_function_span.text.strip()
company_logo = (
logo_image.get("data-delayed-url")
if (logo_image := soup.find("img", {"class": "artdeco-entity-image"}))
else None
)
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_url_direct": self._parse_job_url_direct(soup),
"logo_photo_url": soup.find("img", {"class": "artdeco-entity-image"}).get(
"data-delayed-url"
),
"company_logo": company_logo,
"job_function": job_function,
}
@@ -401,12 +413,3 @@ class LinkedInScraper(Scraper):
JobType.CONTRACT: "C",
JobType.TEMPORARY: "T",
}.get(job_type_enum, "")
headers = {
"authority": "www.linkedin.com",
"accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7",
"accept-language": "en-US,en;q=0.9",
"cache-control": "max-age=0",
"upgrade-insecure-requests": "1",
"user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36",
}

View File

@@ -0,0 +1,8 @@
headers = {
"authority": "www.linkedin.com",
"accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7",
"accept-language": "en-US,en;q=0.9",
"cache-control": "max-age=0",
"upgrade-insecure-requests": "1",
"user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36",
}

View File

@@ -1,26 +1,32 @@
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 JobType
from ..jobs import CompensationInterval, JobType
logger = logging.getLogger("JobSpy")
logger.propagate = False
if not logger.handlers:
logger.setLevel(logging.INFO)
console_handler = logging.StreamHandler()
format = "%(asctime)s - %(name)s - %(levelname)s - %(message)s"
formatter = logging.Formatter(format)
console_handler.setFormatter(formatter)
logger.addHandler(console_handler)
urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
def create_logger(name: str):
logger = logging.getLogger(f"JobSpy:{name}")
logger.propagate = False
if not logger.handlers:
logger.setLevel(logging.INFO)
console_handler = logging.StreamHandler()
format = "%(asctime)s - %(levelname)s - %(name)s - %(message)s"
formatter = logging.Formatter(format)
console_handler.setFormatter(formatter)
logger.addHandler(console_handler)
return logger
class RotatingProxySession:
@@ -100,6 +106,7 @@ class TLSRotating(RotatingProxySession, tls_client.Session):
def create_session(
*,
proxies: dict | str | None = None,
ca_cert: str | None = None,
is_tls: bool = True,
has_retry: bool = False,
delay: int = 1,
@@ -119,10 +126,13 @@ def create_session(
clear_cookies=clear_cookies,
)
if ca_cert:
session.verify = ca_cert
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.
@@ -134,7 +144,9 @@ def set_logger_level(verbose: int = 2):
level_name = {2: "INFO", 1: "WARNING", 0: "ERROR"}.get(verbose, "INFO")
level = getattr(logging, level_name.upper(), None)
if level is not None:
logger.setLevel(level)
for logger_name in logging.root.manager.loggerDict:
if logger_name.startswith("JobSpy:"):
logging.getLogger(logger_name).setLevel(level)
else:
raise ValueError(f"Invalid log level: {level_name}")
@@ -193,10 +205,16 @@ def extract_salary(
upper_limit=700000,
hourly_threshold=350,
monthly_threshold=30000,
enforce_annual_salary=False,
):
"""
Extracts salary information from a string and returns the salary interval, min and max salary values, and currency.
(TODO: Needs test cases as the regex is complicated and may not cover all edge cases)
"""
if not salary_str:
return None, None, None, None
annual_max_salary = None
min_max_pattern = r"\$(\d+(?:,\d+)?(?:\.\d+)?)([kK]?)\s*[-—–]\s*(?:\$)?(\d+(?:,\d+)?(?:\.\d+)?)([kK]?)"
def to_int(s):
@@ -220,20 +238,51 @@ def extract_salary(
# Convert to annual if less than the hourly threshold
if min_salary < hourly_threshold:
min_salary = convert_hourly_to_annual(min_salary)
interval = CompensationInterval.HOURLY.value
annual_min_salary = convert_hourly_to_annual(min_salary)
if max_salary < hourly_threshold:
max_salary = convert_hourly_to_annual(max_salary)
annual_max_salary = convert_hourly_to_annual(max_salary)
elif min_salary < monthly_threshold:
min_salary = convert_monthly_to_annual(min_salary)
interval = CompensationInterval.MONTHLY.value
annual_min_salary = convert_monthly_to_annual(min_salary)
if max_salary < monthly_threshold:
max_salary = convert_monthly_to_annual(max_salary)
annual_max_salary = convert_monthly_to_annual(max_salary)
else:
interval = CompensationInterval.YEARLY.value
annual_min_salary = min_salary
annual_max_salary = max_salary
# Ensure salary range is within specified limits
if not annual_max_salary:
return None, None, None, None
if (
lower_limit <= min_salary <= upper_limit
and lower_limit <= max_salary <= upper_limit
and min_salary < max_salary
lower_limit <= annual_min_salary <= upper_limit
and lower_limit <= annual_max_salary <= upper_limit
and annual_min_salary < annual_max_salary
):
return "yearly", min_salary, max_salary, "USD"
if enforce_annual_salary:
return interval, annual_min_salary, annual_max_salary, "USD"
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

View File

@@ -11,20 +11,20 @@ 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
from .. import Scraper, ScraperInput, Site
from ..utils import (
logger,
extract_emails_from_text,
create_session,
markdown_converter,
remove_attributes,
create_logger,
)
from ...jobs import (
JobPost,
@@ -36,19 +36,24 @@ from ...jobs import (
DescriptionFormat,
)
log = create_logger("ZipRecruiter")
class ZipRecruiterScraper(Scraper):
base_url = "https://www.ziprecruiter.com"
api_url = "https://api.ziprecruiter.com"
def __init__(self, proxies: list[str] | str | None = None):
def __init__(
self, proxies: list[str] | str | None = None, ca_cert: str | None = None
):
"""
Initializes ZipRecruiterScraper with the ZipRecruiter job search url
"""
super().__init__(Site.ZIP_RECRUITER, proxies=proxies)
self.scraper_input = None
self.session = create_session(proxies=proxies)
self.session = create_session(proxies=proxies, ca_cert=ca_cert)
self.session.headers.update(headers)
self._get_cookies()
self.delay = 5
@@ -71,7 +76,7 @@ class ZipRecruiterScraper(Scraper):
break
if page > 1:
time.sleep(self.delay)
logger.info(f"ZipRecruiter search page: {page}")
log.info(f"search page: {page} / {max_pages}")
jobs_on_page, continue_token = self._find_jobs_in_page(
scraper_input, continue_token
)
@@ -97,22 +102,20 @@ class ZipRecruiterScraper(Scraper):
if continue_token:
params["continue_from"] = continue_token
try:
res = self.session.get(
f"{self.api_url}/jobs-app/jobs", headers=self.headers, params=params
)
res = self.session.get(f"{self.api_url}/jobs-app/jobs", params=params)
if res.status_code not in range(200, 400):
if res.status_code == 429:
err = "429 Response - Blocked by ZipRecruiter for too many requests"
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()
@@ -160,7 +163,7 @@ class ZipRecruiterScraper(Scraper):
description_full, job_url_direct = self._get_descr(job_url)
return JobPost(
id=str(job["listing_key"]),
id=f'zr-{job["listing_key"]}',
title=title,
company_name=company,
location=location,
@@ -180,7 +183,7 @@ class ZipRecruiterScraper(Scraper):
)
def _get_descr(self, job_url):
res = self.session.get(job_url, headers=self.headers, allow_redirects=True)
res = self.session.get(job_url, allow_redirects=True)
description_full = job_url_direct = None
if res.ok:
soup = BeautifulSoup(res.text, "html.parser")
@@ -200,7 +203,7 @@ class ZipRecruiterScraper(Scraper):
script_tag = soup.find("script", type="application/json")
if script_tag:
job_json = json.loads(script_tag.string)
job_url_val = job_json["model"]["saveJobURL"]
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)
@@ -211,9 +214,30 @@ 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, headers=self.headers)
self.session.post(url, data=data)
@staticmethod
def _get_job_type_enum(job_type_str: str) -> list[JobType] | None:
@@ -241,14 +265,3 @@ class ZipRecruiterScraper(Scraper):
if scraper_input.distance:
params["radius"] = scraper_input.distance
return {k: v for k, v in params.items() if v is not None}
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",
}

View File

@@ -0,0 +1,10 @@
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",
}

View File

View File

@@ -1,14 +0,0 @@
from ..jobspy import scrape_jobs
import pandas as pd
def test_all():
result = scrape_jobs(
site_name=["linkedin", "indeed", "zip_recruiter", "glassdoor"],
search_term="software engineer",
results_wanted=5,
)
assert (
isinstance(result, pd.DataFrame) and not result.empty
), "Result should be a non-empty DataFrame"

View File

@@ -1,11 +0,0 @@
from ..jobspy import scrape_jobs
import pandas as pd
def test_indeed():
result = scrape_jobs(
site_name="glassdoor", search_term="software engineer", country_indeed="USA"
)
assert (
isinstance(result, pd.DataFrame) and not result.empty
), "Result should be a non-empty DataFrame"

View File

@@ -1,11 +0,0 @@
from ..jobspy import scrape_jobs
import pandas as pd
def test_indeed():
result = scrape_jobs(
site_name="indeed", search_term="software engineer", country_indeed="usa"
)
assert (
isinstance(result, pd.DataFrame) and not result.empty
), "Result should be a non-empty DataFrame"

View File

@@ -1,12 +0,0 @@
from ..jobspy import scrape_jobs
import pandas as pd
def test_linkedin():
result = scrape_jobs(
site_name="linkedin",
search_term="software engineer",
)
assert (
isinstance(result, pd.DataFrame) and not result.empty
), "Result should be a non-empty DataFrame"

View File

@@ -1,13 +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",
)
assert (
isinstance(result, pd.DataFrame) and not result.empty
), "Result should be a non-empty DataFrame"