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51
README.md
51
README.md
@@ -11,7 +11,7 @@ work with us.*
|
||||
|
||||
- Scrapes job postings from **LinkedIn**, **Indeed**, **Glassdoor**, & **ZipRecruiter** simultaneously
|
||||
- Aggregates the job postings in a Pandas DataFrame
|
||||
- Proxy support (HTTP/S, SOCKS)
|
||||
- Proxy support
|
||||
|
||||
[Video Guide for JobSpy](https://www.youtube.com/watch?v=RuP1HrAZnxs&pp=ygUgam9icyBzY3JhcGVyIGJvdCBsaW5rZWRpbiBpbmRlZWQ%3D) -
|
||||
Updated for release v1.1.3
|
||||
@@ -21,7 +21,7 @@ Updated for release v1.1.3
|
||||
### Installation
|
||||
|
||||
```
|
||||
pip install python-jobspy
|
||||
pip install -U python-jobspy
|
||||
```
|
||||
|
||||
_Python version >= [3.10](https://www.python.org/downloads/release/python-3100/) required_
|
||||
@@ -64,18 +64,19 @@ Required
|
||||
├── site_type (List[enum]): linkedin, zip_recruiter, indeed, glassdoor
|
||||
└── search_term (str)
|
||||
Optional
|
||||
├── location (int)
|
||||
├── distance (int): in miles
|
||||
├── location (str)
|
||||
├── distance (int): in miles, default 50
|
||||
├── job_type (enum): fulltime, parttime, internship, contract
|
||||
├── proxy (str): in format 'http://user:pass@host:port' or [https, socks]
|
||||
├── proxy (str): in format 'http://user:pass@host:port'
|
||||
├── is_remote (bool)
|
||||
├── full_description (bool): fetches full description for LinkedIn (slower)
|
||||
├── linkedin_fetch_description (bool): fetches full description for LinkedIn (slower)
|
||||
├── results_wanted (int): number of job results to retrieve for each site specified in 'site_type'
|
||||
├── easy_apply (bool): filters for jobs that are hosted on the job board site
|
||||
├── linkedin_company_ids (list[int): searches for linkedin jobs with specific company ids
|
||||
├── description_format (enum): markdown, html (format type of the job descriptions)
|
||||
├── country_indeed (enum): filters the country on Indeed (see below for correct spelling)
|
||||
├── offset (num): starts the search from an offset (e.g. 25 will start the search from the 25th result)
|
||||
├── hours_old (int): filters jobs by the number of hours since the job was posted (all but LinkedIn rounds up to next day)
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||||
├── hours_old (int): filters jobs by the number of hours since the job was posted (ZipRecruiter and Glassdoor round up to next day. If you use this on Indeed, it will not filter by job_type or is_remote)
|
||||
```
|
||||
|
||||
### JobPost Schema
|
||||
@@ -99,24 +100,26 @@ JobPost
|
||||
│ └── currency (enum)
|
||||
└── date_posted (date)
|
||||
└── emails (str)
|
||||
└── num_urgent_words (int)
|
||||
└── is_remote (bool)
|
||||
|
||||
Indeed specific
|
||||
├── company_country (str)
|
||||
└── company_addresses (str)
|
||||
└── company_industry (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)
|
||||
```
|
||||
|
||||
### Exceptions
|
||||
|
||||
The following exceptions may be raised when using JobSpy:
|
||||
|
||||
* `LinkedInException`
|
||||
* `IndeedException`
|
||||
* `ZipRecruiterException`
|
||||
* `GlassdoorException`
|
||||
|
||||
## Supported Countries for Job Searching
|
||||
|
||||
### **LinkedIn**
|
||||
|
||||
LinkedIn searches globally & uses only the `location` parameter. You can only fetch 1000 jobs max from the LinkedIn endpoint we're using
|
||||
LinkedIn searches globally & uses only the `location` parameter. You can only fetch 1000 jobs max from the LinkedIn endpoint we are using
|
||||
|
||||
### **ZipRecruiter**
|
||||
|
||||
@@ -146,10 +149,14 @@ You can specify the following countries when searching on Indeed (use the exact
|
||||
| South Korea | Spain* | Sweden | Switzerland* |
|
||||
| Taiwan | Thailand | Turkey | Ukraine |
|
||||
| United Arab Emirates | UK* | USA* | Uruguay |
|
||||
| Venezuela | Vietnam | | |
|
||||
| Venezuela | Vietnam* | | |
|
||||
|
||||
|
||||
Glassdoor can only fetch 900 jobs from the endpoint we're using on a given search.
|
||||
## Notes
|
||||
* Indeed is the best scraper currently with no rate limiting.
|
||||
* Glassdoor can only fetch 900 jobs from the endpoint we're using on a given search.
|
||||
* LinkedIn is the most restrictive and usually rate limits on around the 10th page
|
||||
* ZipRecruiter is okay but has a 5 second delay in between each page to avoid rate limiting.
|
||||
## Frequently Asked Questions
|
||||
|
||||
---
|
||||
@@ -167,7 +174,3 @@ persist, [submit an issue](https://github.com/Bunsly/JobSpy/issues).
|
||||
- Trying a VPN or proxy to change your IP address.
|
||||
|
||||
---
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
23
poetry.lock
generated
23
poetry.lock
generated
@@ -1026,6 +1026,21 @@ files = [
|
||||
{file = "jupyterlab_widgets-3.0.8.tar.gz", hash = "sha256:d428ab97b8d87cc7c54cbf37644d6e0f0e662f23876e05fa460a73ec3257252a"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "markdownify"
|
||||
version = "0.11.6"
|
||||
description = "Convert HTML to markdown."
|
||||
optional = false
|
||||
python-versions = "*"
|
||||
files = [
|
||||
{file = "markdownify-0.11.6-py3-none-any.whl", hash = "sha256:ba35fe289d5e9073bcd7d2cad629278fe25f1a93741fcdc0bfb4f009076d8324"},
|
||||
{file = "markdownify-0.11.6.tar.gz", hash = "sha256:009b240e0c9f4c8eaf1d085625dcd4011e12f0f8cec55dedf9ea6f7655e49bfe"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
beautifulsoup4 = ">=4.9,<5"
|
||||
six = ">=1.15,<2"
|
||||
|
||||
[[package]]
|
||||
name = "markupsafe"
|
||||
version = "2.1.3"
|
||||
@@ -2260,13 +2275,13 @@ test = ["flake8", "isort", "pytest"]
|
||||
|
||||
[[package]]
|
||||
name = "tls-client"
|
||||
version = "1.0"
|
||||
version = "1.0.1"
|
||||
description = "Advanced Python HTTP Client."
|
||||
optional = false
|
||||
python-versions = "*"
|
||||
files = [
|
||||
{file = "tls_client-1.0-py3-none-any.whl", hash = "sha256:f1183f5e18cb31914bd62d11b350a33ea0293ea80fb91d69a3072821dece3e66"},
|
||||
{file = "tls_client-1.0.tar.gz", hash = "sha256:7f6de48ad4a0ef69b72682c76ce604155971e07b4bfb2148a36276194ae3e7a0"},
|
||||
{file = "tls_client-1.0.1-py3-none-any.whl", hash = "sha256:2f8915c0642c2226c9e33120072a2af082812f6310d32f4ea4da322db7d3bb1c"},
|
||||
{file = "tls_client-1.0.1.tar.gz", hash = "sha256:dad797f3412bb713606e0765d489f547ffb580c5ffdb74aed47a183ce8505ff5"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@@ -2435,4 +2450,4 @@ files = [
|
||||
[metadata]
|
||||
lock-version = "2.0"
|
||||
python-versions = "^3.10"
|
||||
content-hash = "404a77d78066cbb2ef71015562baf44aa11d12aac29a191c1ccc7758bfda598a"
|
||||
content-hash = "ba7f7cc9b6833a4a6271981f90610395639dd8b9b3db1370cbd1149d70cc9632"
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
[tool.poetry]
|
||||
name = "python-jobspy"
|
||||
version = "1.1.44"
|
||||
version = "1.1.48"
|
||||
description = "Job scraper for LinkedIn, Indeed, Glassdoor & ZipRecruiter"
|
||||
authors = ["Zachary Hampton <zachary@bunsly.com>", "Cullen Watson <cullen@bunsly.com>"]
|
||||
homepage = "https://github.com/Bunsly/JobSpy"
|
||||
@@ -13,11 +13,12 @@ packages = [
|
||||
[tool.poetry.dependencies]
|
||||
python = "^3.10"
|
||||
requests = "^2.31.0"
|
||||
tls-client = "*"
|
||||
beautifulsoup4 = "^4.12.2"
|
||||
pandas = "^2.1.0"
|
||||
NUMPY = "1.24.2"
|
||||
pydantic = "^2.3.0"
|
||||
tls-client = "^1.0.1"
|
||||
markdownify = "^0.11.6"
|
||||
|
||||
|
||||
[tool.poetry.group.dev.dependencies]
|
||||
|
||||
@@ -3,6 +3,7 @@ from typing import Tuple
|
||||
from concurrent.futures import ThreadPoolExecutor, as_completed
|
||||
|
||||
from .jobs import JobType, Location
|
||||
from .scrapers.utils import logger
|
||||
from .scrapers.indeed import IndeedScraper
|
||||
from .scrapers.ziprecruiter import ZipRecruiterScraper
|
||||
from .scrapers.glassdoor import GlassdoorScraper
|
||||
@@ -15,23 +16,12 @@ from .scrapers.exceptions import (
|
||||
GlassdoorException,
|
||||
)
|
||||
|
||||
SCRAPER_MAPPING = {
|
||||
Site.LINKEDIN: LinkedInScraper,
|
||||
Site.INDEED: IndeedScraper,
|
||||
Site.ZIP_RECRUITER: ZipRecruiterScraper,
|
||||
Site.GLASSDOOR: GlassdoorScraper,
|
||||
}
|
||||
|
||||
|
||||
def _map_str_to_site(site_name: str) -> Site:
|
||||
return Site[site_name.upper()]
|
||||
|
||||
|
||||
def scrape_jobs(
|
||||
site_name: str | list[str] | Site | list[Site] | None = None,
|
||||
search_term: str | None = None,
|
||||
location: str | None = None,
|
||||
distance: int | None = None,
|
||||
distance: int | None = 50,
|
||||
is_remote: bool = False,
|
||||
job_type: str | None = None,
|
||||
easy_apply: bool | None = None,
|
||||
@@ -39,7 +29,8 @@ def scrape_jobs(
|
||||
country_indeed: str = "usa",
|
||||
hyperlinks: bool = False,
|
||||
proxy: str | None = None,
|
||||
full_description: bool | None = False,
|
||||
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,
|
||||
@@ -49,6 +40,15 @@ def scrape_jobs(
|
||||
Simultaneously scrapes job data from multiple job sites.
|
||||
:return: results_wanted: pandas dataframe containing job data
|
||||
"""
|
||||
SCRAPER_MAPPING = {
|
||||
Site.LINKEDIN: LinkedInScraper,
|
||||
Site.INDEED: IndeedScraper,
|
||||
Site.ZIP_RECRUITER: ZipRecruiterScraper,
|
||||
Site.GLASSDOOR: GlassdoorScraper,
|
||||
}
|
||||
|
||||
def map_str_to_site(site_name: str) -> Site:
|
||||
return Site[site_name.upper()]
|
||||
|
||||
def get_enum_from_value(value_str):
|
||||
for job_type in JobType:
|
||||
@@ -61,16 +61,15 @@ def scrape_jobs(
|
||||
def get_site_type():
|
||||
site_types = list(Site)
|
||||
if isinstance(site_name, str):
|
||||
site_types = [_map_str_to_site(site_name)]
|
||||
site_types = [map_str_to_site(site_name)]
|
||||
elif isinstance(site_name, Site):
|
||||
site_types = [site_name]
|
||||
elif isinstance(site_name, list):
|
||||
site_types = [
|
||||
_map_str_to_site(site) if isinstance(site, str) else site
|
||||
map_str_to_site(site) if isinstance(site, str) else site
|
||||
for site in site_name
|
||||
]
|
||||
return site_types
|
||||
|
||||
country_enum = Country.from_string(country_indeed)
|
||||
|
||||
scraper_input = ScraperInput(
|
||||
@@ -82,7 +81,8 @@ def scrape_jobs(
|
||||
is_remote=is_remote,
|
||||
job_type=job_type,
|
||||
easy_apply=easy_apply,
|
||||
full_description=full_description,
|
||||
description_format=description_format,
|
||||
linkedin_fetch_description=linkedin_fetch_description,
|
||||
results_wanted=results_wanted,
|
||||
linkedin_company_ids=linkedin_company_ids,
|
||||
offset=offset,
|
||||
@@ -92,22 +92,9 @@ def scrape_jobs(
|
||||
def scrape_site(site: Site) -> Tuple[str, JobResponse]:
|
||||
scraper_class = SCRAPER_MAPPING[site]
|
||||
scraper = scraper_class(proxy=proxy)
|
||||
|
||||
try:
|
||||
scraped_data: JobResponse = scraper.scrape(scraper_input)
|
||||
except (LinkedInException, IndeedException, ZipRecruiterException) as lie:
|
||||
raise lie
|
||||
except Exception as e:
|
||||
if site == Site.LINKEDIN:
|
||||
raise LinkedInException(str(e))
|
||||
if site == Site.INDEED:
|
||||
raise IndeedException(str(e))
|
||||
if site == Site.ZIP_RECRUITER:
|
||||
raise ZipRecruiterException(str(e))
|
||||
if site == Site.GLASSDOOR:
|
||||
raise GlassdoorException(str(e))
|
||||
else:
|
||||
raise e
|
||||
site_name = 'ZipRecruiter' if site.value.capitalize() == 'Zip_recruiter' else site.value.capitalize()
|
||||
logger.info(f"{site_name} finished scraping")
|
||||
return site.value, scraped_data
|
||||
|
||||
site_to_jobs_dict = {}
|
||||
@@ -168,13 +155,19 @@ def scrape_jobs(
|
||||
jobs_dfs.append(job_df)
|
||||
|
||||
if jobs_dfs:
|
||||
jobs_df = pd.concat(jobs_dfs, ignore_index=True)
|
||||
desired_order: list[str] = [
|
||||
"job_url_hyper" if hyperlinks else "job_url",
|
||||
# Step 1: Filter out all-NA columns from each DataFrame before concatenation
|
||||
filtered_dfs = [df.dropna(axis=1, how='all') for df in jobs_dfs]
|
||||
|
||||
# Step 2: Concatenate the filtered DataFrames
|
||||
jobs_df = pd.concat(filtered_dfs, ignore_index=True)
|
||||
|
||||
# Desired column order
|
||||
desired_order = [
|
||||
"site",
|
||||
"job_url_hyper" if hyperlinks else "job_url",
|
||||
"job_url_direct",
|
||||
"title",
|
||||
"company",
|
||||
"company_url",
|
||||
"location",
|
||||
"job_type",
|
||||
"date_posted",
|
||||
@@ -183,13 +176,31 @@ def scrape_jobs(
|
||||
"max_amount",
|
||||
"currency",
|
||||
"is_remote",
|
||||
"num_urgent_words",
|
||||
"benefits",
|
||||
"emails",
|
||||
"description",
|
||||
]
|
||||
jobs_formatted_df = jobs_df[desired_order]
|
||||
else:
|
||||
jobs_formatted_df = pd.DataFrame()
|
||||
|
||||
return jobs_formatted_df.sort_values(by=['site', 'date_posted'], ascending=[True, False])
|
||||
"company_url",
|
||||
"company_url_direct",
|
||||
"company_addresses",
|
||||
"company_industry",
|
||||
"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
|
||||
for column in desired_order:
|
||||
if column not in jobs_df.columns:
|
||||
jobs_df[column] = None # Add missing columns as empty
|
||||
|
||||
# Reorder the DataFrame according to the desired order
|
||||
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])
|
||||
else:
|
||||
return pd.DataFrame()
|
||||
|
||||
@@ -57,7 +57,7 @@ class JobType(Enum):
|
||||
class Country(Enum):
|
||||
"""
|
||||
Gets the subdomain for Indeed and Glassdoor.
|
||||
The second item in the tuple is the subdomain for Indeed
|
||||
The second item in the tuple is the subdomain (and API country code if there's a ':' separator) for Indeed
|
||||
The third item in the tuple is the subdomain (and tld if there's a ':' separator) for Glassdoor
|
||||
"""
|
||||
|
||||
@@ -118,11 +118,11 @@ class Country(Enum):
|
||||
TURKEY = ("turkey", "tr")
|
||||
UKRAINE = ("ukraine", "ua")
|
||||
UNITEDARABEMIRATES = ("united arab emirates", "ae")
|
||||
UK = ("uk,united kingdom", "uk", "co.uk")
|
||||
USA = ("usa,us,united states", "www", "com")
|
||||
UK = ("uk,united kingdom", "uk:gb", "co.uk")
|
||||
USA = ("usa,us,united states", "www:us", "com")
|
||||
URUGUAY = ("uruguay", "uy")
|
||||
VENEZUELA = ("venezuela", "ve")
|
||||
VIETNAM = ("vietnam", "vn")
|
||||
VIETNAM = ("vietnam", "vn", "com")
|
||||
|
||||
# internal for ziprecruiter
|
||||
US_CANADA = ("usa/ca", "www")
|
||||
@@ -132,7 +132,10 @@ class Country(Enum):
|
||||
|
||||
@property
|
||||
def indeed_domain_value(self):
|
||||
return self.value[1]
|
||||
subdomain, _, api_country_code = self.value[1].partition(":")
|
||||
if subdomain and api_country_code:
|
||||
return subdomain, api_country_code.upper()
|
||||
return self.value[1], self.value[1].upper()
|
||||
|
||||
@property
|
||||
def glassdoor_domain_value(self):
|
||||
@@ -145,7 +148,7 @@ class Country(Enum):
|
||||
else:
|
||||
raise Exception(f"Glassdoor is not available for {self.name}")
|
||||
|
||||
def get_url(self):
|
||||
def get_glassdoor_url(self):
|
||||
return f"https://{self.glassdoor_domain_value}/"
|
||||
|
||||
@classmethod
|
||||
@@ -163,7 +166,7 @@ class Country(Enum):
|
||||
|
||||
|
||||
class Location(BaseModel):
|
||||
country: Country | None = None
|
||||
country: Country | str | None = None
|
||||
city: Optional[str] = None
|
||||
state: Optional[str] = None
|
||||
|
||||
@@ -173,7 +176,9 @@ class Location(BaseModel):
|
||||
location_parts.append(self.city)
|
||||
if self.state:
|
||||
location_parts.append(self.state)
|
||||
if self.country and self.country not in (Country.US_CANADA, Country.WORLDWIDE):
|
||||
if isinstance(self.country, str):
|
||||
location_parts.append(self.country)
|
||||
elif self.country and self.country not in (Country.US_CANADA, Country.WORLDWIDE):
|
||||
country_name = self.country.value[0]
|
||||
if "," in country_name:
|
||||
country_name = country_name.split(",")[0]
|
||||
@@ -210,23 +215,38 @@ class Compensation(BaseModel):
|
||||
currency: Optional[str] = "USD"
|
||||
|
||||
|
||||
class DescriptionFormat(Enum):
|
||||
MARKDOWN = "markdown"
|
||||
HTML = "html"
|
||||
|
||||
|
||||
class JobPost(BaseModel):
|
||||
title: str
|
||||
company_name: str
|
||||
company_name: str | None
|
||||
job_url: str
|
||||
job_url_direct: str | None = None
|
||||
location: Optional[Location]
|
||||
|
||||
description: str | None = None
|
||||
company_url: str | None = None
|
||||
company_url_direct: str | None = None
|
||||
|
||||
job_type: list[JobType] | None = None
|
||||
compensation: Compensation | None = None
|
||||
date_posted: date | None = None
|
||||
benefits: str | None = None
|
||||
emails: list[str] | None = None
|
||||
num_urgent_words: int | None = None
|
||||
is_remote: bool | None = None
|
||||
# company_industry: str | None = None
|
||||
|
||||
# indeed specific
|
||||
company_addresses: str | None = None
|
||||
company_industry: str | None = None
|
||||
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
|
||||
banner_photo_url: str | None = None
|
||||
|
||||
|
||||
class JobResponse(BaseModel):
|
||||
|
||||
@@ -1,4 +1,11 @@
|
||||
from ..jobs import Enum, BaseModel, JobType, JobResponse, Country
|
||||
from ..jobs import (
|
||||
Enum,
|
||||
BaseModel,
|
||||
JobType,
|
||||
JobResponse,
|
||||
Country,
|
||||
DescriptionFormat
|
||||
)
|
||||
|
||||
|
||||
class Site(Enum):
|
||||
@@ -18,9 +25,10 @@ class ScraperInput(BaseModel):
|
||||
is_remote: bool = False
|
||||
job_type: JobType | None = None
|
||||
easy_apply: bool | None = None
|
||||
full_description: bool = False
|
||||
offset: int = 0
|
||||
linkedin_fetch_description: bool = False
|
||||
linkedin_company_ids: list[int] | None = None
|
||||
description_format: DescriptionFormat | None = DescriptionFormat.MARKDOWN
|
||||
|
||||
results_wanted: int = 15
|
||||
hours_old: int | None = None
|
||||
|
||||
@@ -5,15 +5,21 @@ jobspy.scrapers.glassdoor
|
||||
This module contains routines to scrape Glassdoor.
|
||||
"""
|
||||
import json
|
||||
import re
|
||||
|
||||
import requests
|
||||
from typing import Optional
|
||||
from datetime import datetime, timedelta
|
||||
from concurrent.futures import ThreadPoolExecutor, as_completed
|
||||
from ..utils import count_urgent_words, extract_emails_from_text
|
||||
from ..utils import extract_emails_from_text
|
||||
|
||||
from .. import Scraper, ScraperInput, Site
|
||||
from ..exceptions import GlassdoorException
|
||||
from ..utils import create_session
|
||||
from ..utils import (
|
||||
create_session,
|
||||
markdown_converter,
|
||||
logger
|
||||
)
|
||||
from ...jobs import (
|
||||
JobPost,
|
||||
Compensation,
|
||||
@@ -21,6 +27,7 @@ from ...jobs import (
|
||||
Location,
|
||||
JobResponse,
|
||||
JobType,
|
||||
DescriptionFormat
|
||||
)
|
||||
|
||||
|
||||
@@ -32,13 +39,59 @@ class GlassdoorScraper(Scraper):
|
||||
site = Site(Site.GLASSDOOR)
|
||||
super().__init__(site, proxy=proxy)
|
||||
|
||||
self.url = None
|
||||
self.base_url = None
|
||||
self.country = None
|
||||
self.session = None
|
||||
self.scraper_input = None
|
||||
self.jobs_per_page = 30
|
||||
self.max_pages = 30
|
||||
self.seen_urls = set()
|
||||
|
||||
def fetch_jobs_page(
|
||||
def scrape(self, scraper_input: ScraperInput) -> JobResponse:
|
||||
"""
|
||||
Scrapes Glassdoor 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.base_url = self.scraper_input.country.get_glassdoor_url()
|
||||
|
||||
self.session = create_session(self.proxy, is_tls=True, has_retry=True)
|
||||
token = self._get_csrf_token()
|
||||
self.headers['gd-csrf-token'] = token if token else self.fallback_token
|
||||
|
||||
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')
|
||||
return JobResponse(jobs=[])
|
||||
all_jobs: list[JobPost] = []
|
||||
cursor = None
|
||||
|
||||
for page in range(
|
||||
1 + (scraper_input.offset // self.jobs_per_page),
|
||||
min(
|
||||
(scraper_input.results_wanted // self.jobs_per_page) + 2,
|
||||
self.max_pages + 1,
|
||||
),
|
||||
):
|
||||
logger.info(f'Glassdoor search page: {page}')
|
||||
try:
|
||||
jobs, cursor = self._fetch_jobs_page(
|
||||
scraper_input, location_id, location_type, page, cursor
|
||||
)
|
||||
all_jobs.extend(jobs)
|
||||
if not jobs or len(all_jobs) >= scraper_input.results_wanted:
|
||||
all_jobs = all_jobs[: scraper_input.results_wanted]
|
||||
break
|
||||
except Exception as e:
|
||||
logger.error(f'Glassdoor: {str(e)}')
|
||||
break
|
||||
return JobResponse(jobs=all_jobs)
|
||||
|
||||
def _fetch_jobs_page(
|
||||
self,
|
||||
scraper_input: ScraperInput,
|
||||
location_id: int,
|
||||
@@ -49,28 +102,28 @@ class GlassdoorScraper(Scraper):
|
||||
"""
|
||||
Scrapes a page of Glassdoor for jobs with scraper_input criteria
|
||||
"""
|
||||
jobs = []
|
||||
self.scraper_input = scraper_input
|
||||
try:
|
||||
payload = self.add_payload(
|
||||
scraper_input, location_id, location_type, page_num, cursor
|
||||
payload = self._add_payload(
|
||||
location_id, location_type, page_num, cursor
|
||||
)
|
||||
response = self.session.post(
|
||||
f"{self.url}/graph", headers=self.headers(), timeout=10, data=payload
|
||||
f"{self.base_url}/graph", headers=self.headers, timeout_seconds=15, data=payload
|
||||
)
|
||||
if response.status_code != 200:
|
||||
raise GlassdoorException(
|
||||
f"bad response status code: {response.status_code}"
|
||||
)
|
||||
raise GlassdoorException(f"bad response status code: {response.status_code}")
|
||||
res_json = response.json()[0]
|
||||
if "errors" in res_json:
|
||||
raise ValueError("Error encountered in API response")
|
||||
except Exception as e:
|
||||
raise GlassdoorException(str(e))
|
||||
except (requests.exceptions.ReadTimeout, GlassdoorException, ValueError, Exception) as e:
|
||||
logger.error(f'Glassdoor: {str(e)}')
|
||||
return jobs, None
|
||||
|
||||
jobs_data = res_json["data"]["jobListings"]["jobListings"]
|
||||
|
||||
jobs = []
|
||||
with ThreadPoolExecutor(max_workers=self.jobs_per_page) as executor:
|
||||
future_to_job_data = {executor.submit(self.process_job, job): job for job in jobs_data}
|
||||
future_to_job_data = {executor.submit(self._process_job, job): job for job in jobs_data}
|
||||
for future in as_completed(future_to_job_data):
|
||||
try:
|
||||
job_post = future.result()
|
||||
@@ -83,10 +136,24 @@ class GlassdoorScraper(Scraper):
|
||||
res_json["data"]["jobListings"]["paginationCursors"], page_num + 1
|
||||
)
|
||||
|
||||
def process_job(self, job_data):
|
||||
"""Processes a single job and fetches its description."""
|
||||
def _get_csrf_token(self):
|
||||
"""
|
||||
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)
|
||||
pattern = r'"token":\s*"([^"]+)"'
|
||||
matches = re.findall(pattern, res.text)
|
||||
token = None
|
||||
if matches:
|
||||
token = matches[0]
|
||||
return token
|
||||
|
||||
def _process_job(self, job_data):
|
||||
"""
|
||||
Processes a single job and fetches its description.
|
||||
"""
|
||||
job_id = job_data["jobview"]["job"]["listingId"]
|
||||
job_url = f'{self.url}job-listing/j?jl={job_id}'
|
||||
job_url = f'{self.base_url}job-listing/j?jl={job_id}'
|
||||
if job_url in self.seen_urls:
|
||||
return None
|
||||
self.seen_urls.add(job_url)
|
||||
@@ -106,15 +173,13 @@ class GlassdoorScraper(Scraper):
|
||||
location = self.parse_location(location_name)
|
||||
|
||||
compensation = self.parse_compensation(job["header"])
|
||||
|
||||
try:
|
||||
description = self.fetch_job_description(job_id)
|
||||
description = self._fetch_job_description(job_id)
|
||||
except:
|
||||
description = None
|
||||
|
||||
job_post = JobPost(
|
||||
return JobPost(
|
||||
title=title,
|
||||
company_url=f"{self.url}Overview/W-EI_IE{company_id}.htm" if company_id else None,
|
||||
company_url=f"{self.base_url}Overview/W-EI_IE{company_id}.htm" if company_id else None,
|
||||
company_name=company_name,
|
||||
date_posted=date_posted,
|
||||
job_url=job_url,
|
||||
@@ -123,55 +188,13 @@ class GlassdoorScraper(Scraper):
|
||||
is_remote=is_remote,
|
||||
description=description,
|
||||
emails=extract_emails_from_text(description) if description else None,
|
||||
num_urgent_words=count_urgent_words(description) if description else None,
|
||||
)
|
||||
return job_post
|
||||
|
||||
def scrape(self, scraper_input: ScraperInput) -> JobResponse:
|
||||
def _fetch_job_description(self, job_id):
|
||||
"""
|
||||
Scrapes Glassdoor for jobs with scraper_input criteria.
|
||||
:param scraper_input: Information about job search criteria.
|
||||
:return: JobResponse containing a list of jobs.
|
||||
Fetches the job description for a single job ID.
|
||||
"""
|
||||
scraper_input.results_wanted = min(900, scraper_input.results_wanted)
|
||||
self.country = scraper_input.country
|
||||
self.url = self.country.get_url()
|
||||
|
||||
location_id, location_type = self.get_location(
|
||||
scraper_input.location, scraper_input.is_remote
|
||||
)
|
||||
all_jobs: list[JobPost] = []
|
||||
cursor = None
|
||||
max_pages = 30
|
||||
self.session = create_session(self.proxy, is_tls=False, has_retry=True)
|
||||
self.session.get(self.url)
|
||||
|
||||
try:
|
||||
for page in range(
|
||||
1 + (scraper_input.offset // self.jobs_per_page),
|
||||
min(
|
||||
(scraper_input.results_wanted // self.jobs_per_page) + 2,
|
||||
max_pages + 1,
|
||||
),
|
||||
):
|
||||
try:
|
||||
jobs, cursor = self.fetch_jobs_page(
|
||||
scraper_input, location_id, location_type, page, cursor
|
||||
)
|
||||
all_jobs.extend(jobs)
|
||||
if len(all_jobs) >= scraper_input.results_wanted:
|
||||
all_jobs = all_jobs[: scraper_input.results_wanted]
|
||||
break
|
||||
except Exception as e:
|
||||
raise GlassdoorException(str(e))
|
||||
except Exception as e:
|
||||
raise GlassdoorException(str(e))
|
||||
|
||||
return JobResponse(jobs=all_jobs)
|
||||
|
||||
def fetch_job_description(self, job_id):
|
||||
"""Fetches the job description for a single job ID."""
|
||||
url = f"{self.url}/graph"
|
||||
url = f"{self.base_url}/graph"
|
||||
body = [
|
||||
{
|
||||
"operationName": "JobDetailQuery",
|
||||
@@ -196,48 +219,28 @@ class GlassdoorScraper(Scraper):
|
||||
"""
|
||||
}
|
||||
]
|
||||
response = requests.post(url, json=body, headers=GlassdoorScraper.headers())
|
||||
if response.status_code != 200:
|
||||
res = requests.post(url, json=body, headers=self.headers)
|
||||
if res.status_code != 200:
|
||||
return None
|
||||
data = response.json()[0]
|
||||
data = res.json()[0]
|
||||
desc = data['data']['jobview']['job']['description']
|
||||
return desc
|
||||
return markdown_converter(desc) if self.scraper_input.description_format == DescriptionFormat.MARKDOWN else desc
|
||||
|
||||
@staticmethod
|
||||
def parse_compensation(data: dict) -> Optional[Compensation]:
|
||||
pay_period = data.get("payPeriod")
|
||||
adjusted_pay = data.get("payPeriodAdjustedPay")
|
||||
currency = data.get("payCurrency", "USD")
|
||||
|
||||
if not pay_period or not adjusted_pay:
|
||||
return None
|
||||
|
||||
interval = None
|
||||
if pay_period == "ANNUAL":
|
||||
interval = CompensationInterval.YEARLY
|
||||
elif pay_period:
|
||||
interval = CompensationInterval.get_interval(pay_period)
|
||||
min_amount = int(adjusted_pay.get("p10") // 1)
|
||||
max_amount = int(adjusted_pay.get("p90") // 1)
|
||||
|
||||
return Compensation(
|
||||
interval=interval,
|
||||
min_amount=min_amount,
|
||||
max_amount=max_amount,
|
||||
currency=currency,
|
||||
)
|
||||
|
||||
def get_location(self, location: str, is_remote: bool) -> (int, str):
|
||||
def _get_location(self, location: str, is_remote: bool) -> (int, str):
|
||||
if not location or is_remote:
|
||||
return "11047", "STATE" # remote options
|
||||
url = f"{self.url}/findPopularLocationAjax.htm?maxLocationsToReturn=10&term={location}"
|
||||
url = f"{self.base_url}/findPopularLocationAjax.htm?maxLocationsToReturn=10&term={location}"
|
||||
session = create_session(self.proxy, has_retry=True)
|
||||
response = session.get(url)
|
||||
if response.status_code != 200:
|
||||
raise GlassdoorException(
|
||||
f"bad response status code: {response.status_code}"
|
||||
)
|
||||
items = response.json()
|
||||
res = self.session.get(url, headers=self.headers)
|
||||
if res.status_code != 200:
|
||||
if res.status_code == 429:
|
||||
logger.error(f'429 Response - Blocked by Glassdoor for too many requests')
|
||||
return None, None
|
||||
else:
|
||||
logger.error(f'Glassdoor response status code {res.status_code}')
|
||||
return None, None
|
||||
items = res.json()
|
||||
|
||||
if not items:
|
||||
raise ValueError(f"Location '{location}' not found on Glassdoor")
|
||||
location_type = items[0]["locationType"]
|
||||
@@ -249,18 +252,16 @@ class GlassdoorScraper(Scraper):
|
||||
location_type = "COUNTRY"
|
||||
return int(items[0]["locationId"]), location_type
|
||||
|
||||
@staticmethod
|
||||
def add_payload(
|
||||
scraper_input,
|
||||
def _add_payload(
|
||||
self,
|
||||
location_id: int,
|
||||
location_type: str,
|
||||
page_num: int,
|
||||
cursor: str | None = None,
|
||||
) -> str:
|
||||
# `fromage` is the posting time filter in days
|
||||
fromage = max(scraper_input.hours_old // 24, 1) if scraper_input.hours_old else None
|
||||
fromage = max(self.scraper_input.hours_old // 24, 1) if self.scraper_input.hours_old else None
|
||||
filter_params = []
|
||||
if scraper_input.easy_apply:
|
||||
if self.scraper_input.easy_apply:
|
||||
filter_params.append({"filterKey": "applicationType", "values": "1"})
|
||||
if fromage:
|
||||
filter_params.append({"filterKey": "fromAge", "values": str(fromage)})
|
||||
@@ -269,7 +270,7 @@ class GlassdoorScraper(Scraper):
|
||||
"variables": {
|
||||
"excludeJobListingIds": [],
|
||||
"filterParams": filter_params,
|
||||
"keyword": scraper_input.search_term,
|
||||
"keyword": self.scraper_input.search_term,
|
||||
"numJobsToShow": 30,
|
||||
"locationType": location_type,
|
||||
"locationId": int(location_id),
|
||||
@@ -279,7 +280,74 @@ class GlassdoorScraper(Scraper):
|
||||
"fromage": fromage,
|
||||
"sort": "date"
|
||||
},
|
||||
"query": """
|
||||
"query": self.query_template
|
||||
}
|
||||
if self.scraper_input.job_type:
|
||||
payload["variables"]["filterParams"].append(
|
||||
{"filterKey": "jobType", "values": self.scraper_input.job_type.value[0]}
|
||||
)
|
||||
return json.dumps([payload])
|
||||
|
||||
@staticmethod
|
||||
def parse_compensation(data: dict) -> Optional[Compensation]:
|
||||
pay_period = data.get("payPeriod")
|
||||
adjusted_pay = data.get("payPeriodAdjustedPay")
|
||||
currency = data.get("payCurrency", "USD")
|
||||
if not pay_period or not adjusted_pay:
|
||||
return None
|
||||
|
||||
interval = None
|
||||
if pay_period == "ANNUAL":
|
||||
interval = CompensationInterval.YEARLY
|
||||
elif pay_period:
|
||||
interval = CompensationInterval.get_interval(pay_period)
|
||||
min_amount = int(adjusted_pay.get("p10") // 1)
|
||||
max_amount = int(adjusted_pay.get("p90") // 1)
|
||||
return Compensation(
|
||||
interval=interval,
|
||||
min_amount=min_amount,
|
||||
max_amount=max_amount,
|
||||
currency=currency,
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def get_job_type_enum(job_type_str: str) -> list[JobType] | None:
|
||||
for job_type in JobType:
|
||||
if job_type_str in job_type.value:
|
||||
return [job_type]
|
||||
|
||||
@staticmethod
|
||||
def parse_location(location_name: str) -> Location | None:
|
||||
if not location_name or location_name == "Remote":
|
||||
return
|
||||
city, _, state = location_name.partition(", ")
|
||||
return Location(city=city, state=state)
|
||||
|
||||
@staticmethod
|
||||
def get_cursor_for_page(pagination_cursors, page_num):
|
||||
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,
|
||||
@@ -445,54 +513,3 @@ class GlassdoorScraper(Scraper):
|
||||
__typename
|
||||
}
|
||||
"""
|
||||
}
|
||||
|
||||
if scraper_input.job_type:
|
||||
payload["variables"]["filterParams"].append(
|
||||
{"filterKey": "jobType", "values": scraper_input.job_type.value[0]}
|
||||
)
|
||||
return json.dumps([payload])
|
||||
|
||||
@staticmethod
|
||||
def get_job_type_enum(job_type_str: str) -> list[JobType] | None:
|
||||
for job_type in JobType:
|
||||
if job_type_str in job_type.value:
|
||||
return [job_type]
|
||||
|
||||
@staticmethod
|
||||
def parse_location(location_name: str) -> Location | None:
|
||||
if not location_name or location_name == "Remote":
|
||||
return
|
||||
city, _, state = location_name.partition(", ")
|
||||
return Location(city=city, state=state)
|
||||
|
||||
@staticmethod
|
||||
def get_cursor_for_page(pagination_cursors, page_num):
|
||||
for cursor_data in pagination_cursors:
|
||||
if cursor_data["pageNumber"] == page_num:
|
||||
return cursor_data["cursor"]
|
||||
|
||||
@staticmethod
|
||||
def headers() -> dict:
|
||||
"""
|
||||
Returns headers needed for requests
|
||||
:return: dict - Dictionary containing headers
|
||||
"""
|
||||
return {
|
||||
"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",
|
||||
"gd-csrf-token": "Ft6oHEWlRZrxDww95Cpazw:0pGUrkb2y3TyOpAIqF2vbPmUXoXVkD3oEGDVkvfeCerceQ5-n8mBg3BovySUIjmCPHCaW0H2nQVdqzbtsYqf4Q:wcqRqeegRUa9MVLJGyujVXB7vWFPjdaS1CtrrzJq-ok",
|
||||
"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",
|
||||
}
|
||||
|
||||
@@ -4,23 +4,17 @@ jobspy.scrapers.indeed
|
||||
|
||||
This module contains routines to scrape Indeed.
|
||||
"""
|
||||
import re
|
||||
import math
|
||||
import json
|
||||
import requests
|
||||
from typing import Any
|
||||
from concurrent.futures import ThreadPoolExecutor, Future
|
||||
from datetime import datetime
|
||||
|
||||
from bs4 import BeautifulSoup
|
||||
from bs4.element import Tag
|
||||
from concurrent.futures import ThreadPoolExecutor, Future
|
||||
import requests
|
||||
|
||||
from ..exceptions import IndeedException
|
||||
from .. import Scraper, ScraperInput, Site
|
||||
from ..utils import (
|
||||
count_urgent_words,
|
||||
extract_emails_from_text,
|
||||
create_session,
|
||||
get_enum_from_job_type,
|
||||
markdown_converter,
|
||||
logger
|
||||
)
|
||||
from ...jobs import (
|
||||
@@ -30,324 +24,261 @@ from ...jobs import (
|
||||
Location,
|
||||
JobResponse,
|
||||
JobType,
|
||||
DescriptionFormat
|
||||
)
|
||||
from .. import Scraper, ScraperInput, Site
|
||||
|
||||
|
||||
class IndeedScraper(Scraper):
|
||||
def __init__(self, proxy: str | None = None):
|
||||
"""
|
||||
Initializes IndeedScraper with the Indeed job search url
|
||||
Initializes IndeedScraper with the Indeed API url
|
||||
"""
|
||||
self.url = None
|
||||
self.country = None
|
||||
self.scraper_input = None
|
||||
self.jobs_per_page = 100
|
||||
self.num_workers = 10
|
||||
self.seen_urls = set()
|
||||
self.headers = None
|
||||
self.api_country_code = None
|
||||
self.base_url = None
|
||||
self.api_url = "https://apis.indeed.com/graphql"
|
||||
site = Site(Site.INDEED)
|
||||
super().__init__(site, proxy=proxy)
|
||||
|
||||
self.jobs_per_page = 25
|
||||
self.seen_urls = set()
|
||||
|
||||
def scrape_page(
|
||||
self, scraper_input: ScraperInput, page: int
|
||||
) -> list[JobPost]:
|
||||
"""
|
||||
Scrapes a page of Indeed for jobs with scraper_input criteria
|
||||
:param scraper_input:
|
||||
:param page:
|
||||
:return: jobs found on page, total number of jobs found for search
|
||||
"""
|
||||
job_list = []
|
||||
self.country = scraper_input.country
|
||||
domain = self.country.indeed_domain_value
|
||||
self.url = f"https://{domain}.indeed.com"
|
||||
|
||||
try:
|
||||
session = create_session(self.proxy)
|
||||
response = session.get(
|
||||
f"{self.url}/m/jobs",
|
||||
headers=self.get_headers(),
|
||||
params=self.add_params(scraper_input, page),
|
||||
allow_redirects=True,
|
||||
timeout_seconds=10,
|
||||
)
|
||||
if response.status_code not in range(200, 400):
|
||||
raise IndeedException(
|
||||
f"bad response with status code: {response.status_code}"
|
||||
)
|
||||
except Exception as e:
|
||||
if "Proxy responded with" in str(e):
|
||||
logger.error(f'Indeed: Bad proxy')
|
||||
else:
|
||||
logger.error(f'Indeed: {str(e)}')
|
||||
return job_list
|
||||
|
||||
soup = BeautifulSoup(response.content, "html.parser")
|
||||
if "did not match any jobs" in response.text:
|
||||
return job_list
|
||||
|
||||
jobs = IndeedScraper.parse_jobs(
|
||||
soup
|
||||
) #: can raise exception, handled by main scrape function
|
||||
|
||||
if (
|
||||
not jobs.get("metaData", {})
|
||||
.get("mosaicProviderJobCardsModel", {})
|
||||
.get("results")
|
||||
):
|
||||
raise IndeedException("No jobs found.")
|
||||
|
||||
def process_job(job: dict, job_detailed: dict) -> JobPost | None:
|
||||
job_url = f'{self.url}/m/jobs/viewjob?jk={job["jobkey"]}'
|
||||
job_url_client = f'{self.url}/viewjob?jk={job["jobkey"]}'
|
||||
if job_url in self.seen_urls:
|
||||
return None
|
||||
self.seen_urls.add(job_url)
|
||||
description = job_detailed['description']['html']
|
||||
|
||||
|
||||
job_type = IndeedScraper.get_job_type(job)
|
||||
timestamp_seconds = job["pubDate"] / 1000
|
||||
date_posted = datetime.fromtimestamp(timestamp_seconds)
|
||||
date_posted = date_posted.strftime("%Y-%m-%d")
|
||||
|
||||
job_post = JobPost(
|
||||
title=job["normTitle"],
|
||||
description=description,
|
||||
company_name=job["company"],
|
||||
company_url=f"{self.url}{job_detailed['employer']['relativeCompanyPageUrl']}" if job_detailed['employer'] else None,
|
||||
location=Location(
|
||||
city=job.get("jobLocationCity"),
|
||||
state=job.get("jobLocationState"),
|
||||
country=self.country,
|
||||
),
|
||||
job_type=job_type,
|
||||
compensation=self.get_compensation(job, job_detailed),
|
||||
date_posted=date_posted,
|
||||
job_url=job_url_client,
|
||||
emails=extract_emails_from_text(description) if description else None,
|
||||
num_urgent_words=count_urgent_words(description)
|
||||
if description
|
||||
else None,
|
||||
is_remote=IndeedScraper.is_job_remote(job, job_detailed, description)
|
||||
|
||||
)
|
||||
return job_post
|
||||
|
||||
workers = 10
|
||||
jobs = jobs["metaData"]["mosaicProviderJobCardsModel"]["results"]
|
||||
job_keys = [job['jobkey'] for job in jobs]
|
||||
jobs_detailed = self.get_job_details(job_keys)
|
||||
|
||||
with ThreadPoolExecutor(max_workers=workers) as executor:
|
||||
job_results: list[Future] = [
|
||||
executor.submit(process_job, job, job_detailed['job']) for job, job_detailed in zip(jobs, jobs_detailed)
|
||||
]
|
||||
|
||||
job_list = [result.result() for result in job_results if result.result()]
|
||||
|
||||
return job_list
|
||||
|
||||
def scrape(self, scraper_input: ScraperInput) -> JobResponse:
|
||||
"""
|
||||
Scrapes Indeed for jobs with scraper_input criteria
|
||||
:param scraper_input:
|
||||
:return: job_response
|
||||
"""
|
||||
job_list = self.scrape_page(scraper_input, 0)
|
||||
pages_processed = 1
|
||||
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['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:
|
||||
pages_to_process = math.ceil((scraper_input.results_wanted - len(self.seen_urls)) / self.jobs_per_page)
|
||||
new_jobs = False
|
||||
|
||||
with ThreadPoolExecutor(max_workers=10) as executor:
|
||||
futures: list[Future] = [
|
||||
executor.submit(self.scrape_page, scraper_input, page + pages_processed)
|
||||
for page in range(pages_to_process)
|
||||
]
|
||||
|
||||
for future in futures:
|
||||
jobs = future.result()
|
||||
if jobs:
|
||||
logger.info(f'Indeed search page: {page}')
|
||||
jobs, cursor = self._scrape_page(cursor)
|
||||
if not jobs:
|
||||
logger.info(f'Indeed found no jobs on page: {page}')
|
||||
break
|
||||
job_list += jobs
|
||||
new_jobs = True
|
||||
if len(self.seen_urls) >= scraper_input.results_wanted:
|
||||
break
|
||||
page += 1
|
||||
return JobResponse(jobs=job_list[:scraper_input.results_wanted])
|
||||
|
||||
pages_processed += pages_to_process
|
||||
if not new_jobs:
|
||||
break
|
||||
def _scrape_page(self, cursor: str | None) -> (list[JobPost], str | None):
|
||||
"""
|
||||
Scrapes a page of Indeed for jobs with scraper_input criteria
|
||||
:param cursor:
|
||||
:return: jobs found on page, next page cursor
|
||||
"""
|
||||
jobs = []
|
||||
new_cursor = None
|
||||
filters = self._build_filters()
|
||||
query = self.job_search_query.format(
|
||||
what=self.scraper_input.search_term,
|
||||
location=self.scraper_input.location if self.scraper_input.location else self.scraper_input.country.value[0].split(',')[-1],
|
||||
radius=self.scraper_input.distance,
|
||||
dateOnIndeed=self.scraper_input.hours_old,
|
||||
cursor=f'cursor: "{cursor}"' if cursor else '',
|
||||
filters=filters
|
||||
)
|
||||
payload = {
|
||||
'query': query,
|
||||
}
|
||||
api_headers = self.api_headers.copy()
|
||||
api_headers['indeed-co'] = self.api_country_code
|
||||
response = requests.post(self.api_url, headers=api_headers, json=payload, proxies=self.proxy, timeout=10)
|
||||
if response.status_code != 200:
|
||||
logger.info(f'Indeed responded with status code: {response.status_code} (submit GitHub issue if this appears to be a beg)')
|
||||
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()]
|
||||
return job_list, new_cursor
|
||||
|
||||
if len(self.seen_urls) > scraper_input.results_wanted:
|
||||
job_list = job_list[:scraper_input.results_wanted]
|
||||
def _build_filters(self):
|
||||
"""
|
||||
Builds the filters dict for job type/is_remote. If hours_old is provided, composite filter for job_type/is_remote is not possible.
|
||||
IndeedApply: filters: { keyword: { field: "indeedApplyScope", keys: ["DESKTOP"] } }
|
||||
"""
|
||||
filters_str = ""
|
||||
if self.scraper_input.hours_old:
|
||||
filters_str = """
|
||||
filters: {{
|
||||
date: {{
|
||||
field: "dateOnIndeed",
|
||||
start: "{start}h"
|
||||
}}
|
||||
}}
|
||||
""".format(start=self.scraper_input.hours_old)
|
||||
elif self.scraper_input.job_type or self.scraper_input.is_remote:
|
||||
job_type_key_mapping = {
|
||||
JobType.FULL_TIME: "CF3CP",
|
||||
JobType.PART_TIME: "75GKK",
|
||||
JobType.CONTRACT: "NJXCK",
|
||||
JobType.INTERNSHIP: "VDTG7",
|
||||
}
|
||||
|
||||
return JobResponse(jobs=job_list)
|
||||
keys = []
|
||||
if self.scraper_input.job_type:
|
||||
key = job_type_key_mapping[self.scraper_input.job_type]
|
||||
keys.append(key)
|
||||
|
||||
if self.scraper_input.is_remote:
|
||||
keys.append("DSQF7")
|
||||
|
||||
if keys:
|
||||
keys_str = '", "'.join(keys) # Prepare your keys string
|
||||
filters_str = f"""
|
||||
filters: {{
|
||||
composite: {{
|
||||
filters: [{{
|
||||
keyword: {{
|
||||
field: "attributes",
|
||||
keys: ["{keys_str}"]
|
||||
}}
|
||||
}}]
|
||||
}}
|
||||
}}
|
||||
"""
|
||||
return filters_str
|
||||
|
||||
def _process_job(self, job: dict) -> JobPost | None:
|
||||
"""
|
||||
Parses the job dict into JobPost model
|
||||
:param job: dict to parse
|
||||
:return: JobPost if it's a new job
|
||||
"""
|
||||
job_url = f'{self.base_url}/viewjob?jk={job["key"]}'
|
||||
if job_url in self.seen_urls:
|
||||
return
|
||||
self.seen_urls.add(job_url)
|
||||
description = job['description']['html']
|
||||
description = markdown_converter(description) if self.scraper_input.description_format == DescriptionFormat.MARKDOWN else description
|
||||
|
||||
job_type = self._get_job_type(job['attributes'])
|
||||
timestamp_seconds = job["datePublished"] / 1000
|
||||
date_posted = datetime.fromtimestamp(timestamp_seconds).strftime("%Y-%m-%d")
|
||||
employer = job['employer'].get('dossier') if job['employer'] else None
|
||||
employer_details = employer.get('employerDetails', {}) if employer else {}
|
||||
return JobPost(
|
||||
title=job["title"],
|
||||
description=description,
|
||||
company_name=job['employer'].get("name") if job.get('employer') else None,
|
||||
company_url=f"{self.base_url}{job['employer']['relativeCompanyPageUrl']}" if job[
|
||||
'employer'] else None,
|
||||
company_url_direct=employer['links']['corporateWebsite'] if employer else None,
|
||||
|
||||
location=Location(
|
||||
city=job.get("location", {}).get("city"),
|
||||
state=job.get("location", {}).get("admin1Code"),
|
||||
country=job.get("location", {}).get("countryCode"),
|
||||
),
|
||||
job_type=job_type,
|
||||
compensation=self._get_compensation(job),
|
||||
date_posted=date_posted,
|
||||
job_url=job_url,
|
||||
job_url_direct=job['recruit'].get('viewJobUrl') if job.get('recruit') else None,
|
||||
emails=extract_emails_from_text(description) if description else None,
|
||||
is_remote=self._is_job_remote(job, description),
|
||||
|
||||
company_addresses=employer_details['addresses'][0] if employer_details.get('addresses') else None,
|
||||
company_industry=employer_details['industry'].replace('Iv1', '').replace('_', ' ').title() if employer_details.get('industry') else None,
|
||||
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=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
|
||||
def get_job_type(job: dict) -> list[JobType] | None:
|
||||
def _get_job_type(attributes: list) -> list[JobType]:
|
||||
"""
|
||||
Parses the job to get list of job types
|
||||
:param job:
|
||||
:return:
|
||||
Parses the attributes to get list of job types
|
||||
:param attributes:
|
||||
:return: list of JobType
|
||||
"""
|
||||
job_types: list[JobType] = []
|
||||
for taxonomy in job["taxonomyAttributes"]:
|
||||
if taxonomy["label"] == "job-types":
|
||||
for i in range(len(taxonomy["attributes"])):
|
||||
label = taxonomy["attributes"][i].get("label")
|
||||
if label:
|
||||
job_type_str = label.replace("-", "").replace(" ", "").lower()
|
||||
for attribute in attributes:
|
||||
job_type_str = attribute['label'].replace("-", "").replace(" ", "").lower()
|
||||
job_type = get_enum_from_job_type(job_type_str)
|
||||
if job_type:
|
||||
job_types.append(job_type)
|
||||
return job_types
|
||||
|
||||
@staticmethod
|
||||
def get_compensation(job: dict, job_detailed: dict) -> Compensation:
|
||||
def _get_compensation(job: dict) -> Compensation | None:
|
||||
"""
|
||||
Parses the job to get
|
||||
Parses the job to get compensation
|
||||
:param job:
|
||||
:param job:
|
||||
:param job_detailed:
|
||||
:return: compensation object
|
||||
"""
|
||||
comp = job_detailed['compensation']['baseSalary']
|
||||
comp = job['compensation']['baseSalary']
|
||||
if comp:
|
||||
interval = IndeedScraper.get_correct_interval(comp['unitOfWork'])
|
||||
interval = IndeedScraper._get_compensation_interval(comp['unitOfWork'])
|
||||
if interval:
|
||||
return Compensation(
|
||||
interval=interval,
|
||||
min_amount=round(comp['range'].get('min'), 2) if comp['range'].get('min') is not None else None,
|
||||
max_amount=round(comp['range'].get('max'), 2) if comp['range'].get('max') is not None else None,
|
||||
currency=job_detailed['compensation']['currencyCode']
|
||||
)
|
||||
|
||||
extracted_salary = job.get("extractedSalary")
|
||||
compensation = None
|
||||
if extracted_salary:
|
||||
salary_snippet = job.get("salarySnippet")
|
||||
currency = salary_snippet.get("currency") if salary_snippet else None
|
||||
interval = (extracted_salary.get("type"),)
|
||||
if isinstance(interval, tuple):
|
||||
interval = interval[0]
|
||||
|
||||
interval = interval.upper()
|
||||
if interval in CompensationInterval.__members__:
|
||||
compensation = Compensation(
|
||||
interval=CompensationInterval[interval],
|
||||
min_amount=int(extracted_salary.get("min")),
|
||||
max_amount=int(extracted_salary.get("max")),
|
||||
currency=currency,
|
||||
)
|
||||
return compensation
|
||||
|
||||
@staticmethod
|
||||
def parse_jobs(soup: BeautifulSoup) -> dict:
|
||||
"""
|
||||
Parses the jobs from the soup object
|
||||
:param soup:
|
||||
:return: jobs
|
||||
"""
|
||||
|
||||
def find_mosaic_script() -> Tag | None:
|
||||
"""
|
||||
Finds jobcards script tag
|
||||
:return: script_tag
|
||||
"""
|
||||
script_tags = soup.find_all("script")
|
||||
|
||||
for tag in script_tags:
|
||||
if (
|
||||
tag.string
|
||||
and "mosaic.providerData" in tag.string
|
||||
and "mosaic-provider-jobcards" in tag.string
|
||||
):
|
||||
return tag
|
||||
return None
|
||||
|
||||
script_tag = find_mosaic_script()
|
||||
|
||||
if script_tag:
|
||||
script_str = script_tag.string
|
||||
pattern = r'window.mosaic.providerData\["mosaic-provider-jobcards"\]\s*=\s*({.*?});'
|
||||
p = re.compile(pattern, re.DOTALL)
|
||||
m = p.search(script_str)
|
||||
if m:
|
||||
jobs = json.loads(m.group(1).strip())
|
||||
return jobs
|
||||
else:
|
||||
raise IndeedException("Could not find mosaic provider job cards data")
|
||||
else:
|
||||
raise IndeedException(
|
||||
"Could not find any results for the search"
|
||||
currency=job['compensation']['currencyCode']
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def get_headers():
|
||||
return {
|
||||
'Host': 'www.indeed.com',
|
||||
'accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
|
||||
'sec-fetch-site': 'same-origin',
|
||||
'sec-fetch-dest': 'document',
|
||||
'accept-language': 'en-US,en;q=0.9',
|
||||
'sec-fetch-mode': 'navigate',
|
||||
'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 192.0',
|
||||
'referer': 'https://www.indeed.com/m/jobs?q=software%20intern&l=Dallas%2C%20TX&from=serpso&rq=1&rsIdx=3',
|
||||
}
|
||||
|
||||
@staticmethod
|
||||
def add_params(scraper_input: ScraperInput, page: int) -> dict[str, str | Any]:
|
||||
# `fromage` is the posting time filter in days
|
||||
fromage = max(scraper_input.hours_old // 24, 1) if scraper_input.hours_old else None
|
||||
params = {
|
||||
"q": scraper_input.search_term,
|
||||
"l": scraper_input.location if scraper_input.location else scraper_input.country.value[0].split(',')[-1],
|
||||
"filter": 0,
|
||||
"start": scraper_input.offset + page * 10,
|
||||
"sort": "date",
|
||||
"fromage": fromage,
|
||||
}
|
||||
if scraper_input.distance:
|
||||
params["radius"] = scraper_input.distance
|
||||
|
||||
sc_values = []
|
||||
if scraper_input.is_remote:
|
||||
sc_values.append("attr(DSQF7)")
|
||||
if scraper_input.job_type:
|
||||
sc_values.append("jt({})".format(scraper_input.job_type.value[0]))
|
||||
|
||||
if sc_values:
|
||||
params["sc"] = "0kf:" + "".join(sc_values) + ";"
|
||||
|
||||
if scraper_input.easy_apply:
|
||||
params['iafilter'] = 1
|
||||
|
||||
return params
|
||||
|
||||
@staticmethod
|
||||
def is_job_remote(job: dict, job_detailed: dict, description: str) -> bool:
|
||||
def _is_job_remote(job: dict, description: str) -> bool:
|
||||
"""
|
||||
Searches the description, location, and attributes to check if job is remote
|
||||
"""
|
||||
remote_keywords = ['remote', 'work from home', 'wfh']
|
||||
is_remote_in_attributes = any(
|
||||
any(keyword in attr['label'].lower() for keyword in remote_keywords)
|
||||
for attr in job_detailed['attributes']
|
||||
for attr in job['attributes']
|
||||
)
|
||||
is_remote_in_description = any(keyword in description.lower() for keyword in remote_keywords)
|
||||
is_remote_in_location = any(
|
||||
keyword in job_detailed['location']['formatted']['long'].lower()
|
||||
keyword in job['location']['formatted']['long'].lower()
|
||||
for keyword in remote_keywords
|
||||
)
|
||||
is_remote_in_taxonomy = any(
|
||||
taxonomy["label"] == "remote" and len(taxonomy["attributes"]) > 0
|
||||
for taxonomy in job.get("taxonomyAttributes", [])
|
||||
)
|
||||
return is_remote_in_attributes or is_remote_in_description or is_remote_in_location or is_remote_in_taxonomy
|
||||
return is_remote_in_attributes or is_remote_in_description or is_remote_in_location
|
||||
|
||||
def get_job_details(self, job_keys: list[str]) -> dict:
|
||||
"""
|
||||
Queries the GraphQL endpoint for detailed job information for the given job keys.
|
||||
"""
|
||||
url = "https://apis.indeed.com/graphql"
|
||||
headers = {
|
||||
@staticmethod
|
||||
def _get_compensation_interval(interval: str) -> CompensationInterval:
|
||||
interval_mapping = {
|
||||
"DAY": "DAILY",
|
||||
"YEAR": "YEARLY",
|
||||
"HOUR": "HOURLY",
|
||||
"WEEK": "WEEKLY",
|
||||
"MONTH": "MONTHLY"
|
||||
}
|
||||
mapped_interval = interval_mapping.get(interval.upper(), None)
|
||||
if mapped_interval and mapped_interval in CompensationInterval.__members__:
|
||||
return CompensationInterval[mapped_interval]
|
||||
else:
|
||||
raise ValueError(f"Unsupported interval: {interval}")
|
||||
|
||||
api_headers = {
|
||||
'Host': 'apis.indeed.com',
|
||||
'content-type': 'application/json',
|
||||
'indeed-api-key': '161092c2017b5bbab13edb12461a62d5a833871e7cad6d9d475304573de67ac8',
|
||||
@@ -356,27 +287,35 @@ class IndeedScraper(Scraper):
|
||||
'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',
|
||||
'indeed-co': 'US',
|
||||
}
|
||||
|
||||
job_keys_gql = '[' + ', '.join(f'"{key}"' for key in job_keys) + ']'
|
||||
|
||||
payload = {
|
||||
"query": f"""
|
||||
job_search_query = """
|
||||
query GetJobData {{
|
||||
jobData(input: {{
|
||||
jobKeys: {job_keys_gql}
|
||||
}}) {{
|
||||
jobSearch(
|
||||
what: "{what}"
|
||||
location: {{ where: "{location}", radius: {radius}, radiusUnit: MILES }}
|
||||
includeSponsoredResults: NONE
|
||||
limit: 100
|
||||
sort: DATE
|
||||
{cursor}
|
||||
{filters}
|
||||
) {{
|
||||
pageInfo {{
|
||||
nextCursor
|
||||
}}
|
||||
results {{
|
||||
trackingKey
|
||||
job {{
|
||||
key
|
||||
title
|
||||
datePublished
|
||||
dateOnIndeed
|
||||
description {{
|
||||
html
|
||||
}}
|
||||
location {{
|
||||
countryName
|
||||
countryCode
|
||||
admin1Code
|
||||
city
|
||||
postalCode
|
||||
streetAddress
|
||||
@@ -398,10 +337,30 @@ class IndeedScraper(Scraper):
|
||||
currencyCode
|
||||
}}
|
||||
attributes {{
|
||||
key
|
||||
label
|
||||
}}
|
||||
employer {{
|
||||
relativeCompanyPageUrl
|
||||
name
|
||||
dossier {{
|
||||
employerDetails {{
|
||||
addresses
|
||||
industry
|
||||
employeesLocalizedLabel
|
||||
revenueLocalizedLabel
|
||||
briefDescription
|
||||
ceoName
|
||||
ceoPhotoUrl
|
||||
}}
|
||||
images {{
|
||||
headerImageUrl
|
||||
squareLogoUrl
|
||||
}}
|
||||
links {{
|
||||
corporateWebsite
|
||||
}}
|
||||
}}
|
||||
}}
|
||||
recruit {{
|
||||
viewJobUrl
|
||||
@@ -413,24 +372,3 @@ class IndeedScraper(Scraper):
|
||||
}}
|
||||
}}
|
||||
"""
|
||||
}
|
||||
response = requests.post(url, headers=headers, json=payload, proxies=self.proxy)
|
||||
if response.status_code == 200:
|
||||
return response.json()['data']['jobData']['results']
|
||||
else:
|
||||
return {}
|
||||
|
||||
@staticmethod
|
||||
def get_correct_interval(interval: str) -> CompensationInterval:
|
||||
interval_mapping = {
|
||||
"DAY": "DAILY",
|
||||
"YEAR": "YEARLY",
|
||||
"HOUR": "HOURLY",
|
||||
"WEEK": "WEEKLY",
|
||||
"MONTH": "MONTHLY"
|
||||
}
|
||||
mapped_interval = interval_mapping.get(interval.upper(), None)
|
||||
if mapped_interval and mapped_interval in CompensationInterval.__members__:
|
||||
return CompensationInterval[mapped_interval]
|
||||
else:
|
||||
raise ValueError(f"Unsupported interval: {interval}")
|
||||
|
||||
@@ -9,8 +9,6 @@ import random
|
||||
from typing import Optional
|
||||
from datetime import datetime
|
||||
|
||||
import requests
|
||||
from requests.exceptions import ProxyError
|
||||
from threading import Lock
|
||||
from bs4.element import Tag
|
||||
from bs4 import BeautifulSoup
|
||||
@@ -25,27 +23,31 @@ from ...jobs import (
|
||||
JobResponse,
|
||||
JobType,
|
||||
Country,
|
||||
Compensation
|
||||
Compensation,
|
||||
DescriptionFormat
|
||||
)
|
||||
from ..utils import (
|
||||
count_urgent_words,
|
||||
logger,
|
||||
extract_emails_from_text,
|
||||
get_enum_from_job_type,
|
||||
currency_parser
|
||||
currency_parser,
|
||||
markdown_converter
|
||||
)
|
||||
|
||||
|
||||
class LinkedInScraper(Scraper):
|
||||
DELAY = 3
|
||||
base_url = "https://www.linkedin.com"
|
||||
delay = 3
|
||||
band_delay = 4
|
||||
jobs_per_page = 25
|
||||
|
||||
def __init__(self, proxy: Optional[str] = None):
|
||||
"""
|
||||
Initializes LinkedInScraper with the LinkedIn job search url
|
||||
"""
|
||||
site = Site(Site.LINKEDIN)
|
||||
super().__init__(Site(Site.LINKEDIN), proxy=proxy)
|
||||
self.scraper_input = None
|
||||
self.country = "worldwide"
|
||||
self.url = "https://www.linkedin.com"
|
||||
super().__init__(site, proxy=proxy)
|
||||
|
||||
def scrape(self, scraper_input: ScraperInput) -> JobResponse:
|
||||
"""
|
||||
@@ -53,67 +55,58 @@ class LinkedInScraper(Scraper):
|
||||
:param scraper_input:
|
||||
:return: job_response
|
||||
"""
|
||||
self.scraper_input = scraper_input
|
||||
job_list: list[JobPost] = []
|
||||
seen_urls = set()
|
||||
url_lock = Lock()
|
||||
page = scraper_input.offset // 25 + 25 if scraper_input.offset else 0
|
||||
|
||||
seconds_old = (
|
||||
scraper_input.hours_old * 3600
|
||||
if scraper_input.hours_old
|
||||
else None
|
||||
)
|
||||
|
||||
def job_type_code(job_type_enum):
|
||||
mapping = {
|
||||
JobType.FULL_TIME: "F",
|
||||
JobType.PART_TIME: "P",
|
||||
JobType.INTERNSHIP: "I",
|
||||
JobType.CONTRACT: "C",
|
||||
JobType.TEMPORARY: "T",
|
||||
}
|
||||
|
||||
return mapping.get(job_type_enum, "")
|
||||
|
||||
continue_search = lambda: len(job_list) < scraper_input.results_wanted and page < 1000
|
||||
|
||||
while continue_search():
|
||||
logger.info(f'LinkedIn search page: {page // 25 + 1}')
|
||||
session = create_session(is_tls=False, has_retry=True, delay=5)
|
||||
params = {
|
||||
"keywords": scraper_input.search_term,
|
||||
"location": scraper_input.location,
|
||||
"distance": scraper_input.distance,
|
||||
"f_WT": 2 if scraper_input.is_remote else None,
|
||||
"f_JT": job_type_code(scraper_input.job_type)
|
||||
"f_JT": self.job_type_code(scraper_input.job_type)
|
||||
if scraper_input.job_type
|
||||
else None,
|
||||
"pageNum": 0,
|
||||
"start": page + scraper_input.offset,
|
||||
"f_AL": "true" if scraper_input.easy_apply else None,
|
||||
"f_C": ','.join(map(str, scraper_input.linkedin_company_ids)) if scraper_input.linkedin_company_ids else None,
|
||||
"f_TPR": f"r{seconds_old}",
|
||||
}
|
||||
if seconds_old is not None:
|
||||
params["f_TPR"] = f"r{seconds_old}"
|
||||
|
||||
params = {k: v for k, v in params.items() if v is not None}
|
||||
try:
|
||||
response = session.get(
|
||||
f"{self.url}/jobs-guest/jobs/api/seeMoreJobPostings/search?",
|
||||
f"{self.base_url}/jobs-guest/jobs/api/seeMoreJobPostings/search?",
|
||||
params=params,
|
||||
allow_redirects=True,
|
||||
proxies=self.proxy,
|
||||
headers=self.headers(),
|
||||
headers=self.headers,
|
||||
timeout=10,
|
||||
)
|
||||
response.raise_for_status()
|
||||
|
||||
except requests.HTTPError as e:
|
||||
raise LinkedInException(
|
||||
f"bad response status code: {e.response.status_code}"
|
||||
)
|
||||
except ProxyError as e:
|
||||
raise LinkedInException("bad proxy")
|
||||
if response.status_code not in range(200, 400):
|
||||
if response.status_code == 429:
|
||||
logger.error(f'429 Response - Blocked by LinkedIn for too many requests')
|
||||
else:
|
||||
logger.error(f'LinkedIn response status code {response.status_code}')
|
||||
return JobResponse(jobs=job_list)
|
||||
except Exception as e:
|
||||
raise LinkedInException(str(e))
|
||||
if "Proxy responded with" in str(e):
|
||||
logger.error(f'LinkedIn: Bad proxy')
|
||||
else:
|
||||
logger.error(f'LinkedIn: {str(e)}')
|
||||
return JobResponse(jobs=job_list)
|
||||
|
||||
soup = BeautifulSoup(response.text, "html.parser")
|
||||
job_cards = soup.find_all("div", class_="base-search-card")
|
||||
@@ -126,29 +119,29 @@ class LinkedInScraper(Scraper):
|
||||
if href_tag and "href" in href_tag.attrs:
|
||||
href = href_tag.attrs["href"].split("?")[0]
|
||||
job_id = href.split("-")[-1]
|
||||
job_url = f"{self.url}/jobs/view/{job_id}"
|
||||
job_url = f"{self.base_url}/jobs/view/{job_id}"
|
||||
|
||||
with url_lock:
|
||||
if job_url in seen_urls:
|
||||
continue
|
||||
seen_urls.add(job_url)
|
||||
|
||||
# Call process_job directly without threading
|
||||
try:
|
||||
job_post = self.process_job(job_card, job_url, scraper_input.full_description)
|
||||
job_post = self._process_job(job_card, job_url, scraper_input.linkedin_fetch_description)
|
||||
if job_post:
|
||||
job_list.append(job_post)
|
||||
if not continue_search():
|
||||
break
|
||||
except Exception as e:
|
||||
raise LinkedInException("Exception occurred while processing jobs")
|
||||
raise LinkedInException(str(e))
|
||||
|
||||
if continue_search():
|
||||
time.sleep(random.uniform(LinkedInScraper.DELAY, LinkedInScraper.DELAY + 2))
|
||||
page += 25
|
||||
time.sleep(random.uniform(self.delay, self.delay + self.band_delay))
|
||||
page += self.jobs_per_page
|
||||
|
||||
job_list = job_list[: scraper_input.results_wanted]
|
||||
return JobResponse(jobs=job_list)
|
||||
|
||||
def process_job(self, job_card: Tag, job_url: str, full_descr: bool) -> Optional[JobPost]:
|
||||
def _process_job(self, job_card: Tag, job_url: str, full_descr: bool) -> Optional[JobPost]:
|
||||
salary_tag = job_card.find('span', class_='job-search-card__salary-info')
|
||||
|
||||
compensation = None
|
||||
@@ -178,7 +171,7 @@ class LinkedInScraper(Scraper):
|
||||
company = company_a_tag.get_text(strip=True) if company_a_tag else "N/A"
|
||||
|
||||
metadata_card = job_card.find("div", class_="base-search-card__metadata")
|
||||
location = self.get_location(metadata_card)
|
||||
location = self._get_location(metadata_card)
|
||||
|
||||
datetime_tag = (
|
||||
metadata_card.find("time", class_="job-search-card__listdate")
|
||||
@@ -190,12 +183,11 @@ class LinkedInScraper(Scraper):
|
||||
datetime_str = datetime_tag["datetime"]
|
||||
try:
|
||||
date_posted = datetime.strptime(datetime_str, "%Y-%m-%d")
|
||||
except Exception as e:
|
||||
except:
|
||||
date_posted = None
|
||||
benefits_tag = job_card.find("span", class_="result-benefits__text")
|
||||
benefits = " ".join(benefits_tag.get_text().split()) if benefits_tag else None
|
||||
if full_descr:
|
||||
description, job_type = self.get_job_description(job_url)
|
||||
description, job_type = self._get_job_description(job_url)
|
||||
|
||||
return JobPost(
|
||||
title=title,
|
||||
@@ -205,14 +197,12 @@ class LinkedInScraper(Scraper):
|
||||
date_posted=date_posted,
|
||||
job_url=job_url,
|
||||
compensation=compensation,
|
||||
benefits=benefits,
|
||||
job_type=job_type,
|
||||
description=description,
|
||||
emails=extract_emails_from_text(description) if description else None,
|
||||
num_urgent_words=count_urgent_words(description) if description else None,
|
||||
)
|
||||
|
||||
def get_job_description(
|
||||
def _get_job_description(
|
||||
self, job_page_url: str
|
||||
) -> tuple[None, None] | tuple[str | None, tuple[str | None, JobType | None]]:
|
||||
"""
|
||||
@@ -222,11 +212,9 @@ class LinkedInScraper(Scraper):
|
||||
"""
|
||||
try:
|
||||
session = create_session(is_tls=False, has_retry=True)
|
||||
response = session.get(job_page_url, timeout=5, proxies=self.proxy)
|
||||
response = session.get(job_page_url, headers=self.headers, timeout=5, proxies=self.proxy)
|
||||
response.raise_for_status()
|
||||
except requests.HTTPError as e:
|
||||
return None, None
|
||||
except Exception as e:
|
||||
except:
|
||||
return None, None
|
||||
if response.url == "https://www.linkedin.com/signup":
|
||||
return None, None
|
||||
@@ -241,40 +229,13 @@ class LinkedInScraper(Scraper):
|
||||
for attr in list(tag.attrs):
|
||||
del tag[attr]
|
||||
return tag
|
||||
|
||||
div_content = remove_attributes(div_content)
|
||||
description = div_content.prettify(formatter="html")
|
||||
if self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
|
||||
description = markdown_converter(description)
|
||||
return description, self._parse_job_type(soup)
|
||||
|
||||
def get_job_type(
|
||||
soup_job_type: BeautifulSoup,
|
||||
) -> list[JobType] | None:
|
||||
"""
|
||||
Gets the job type from job page
|
||||
:param soup_job_type:
|
||||
:return: JobType
|
||||
"""
|
||||
h3_tag = soup_job_type.find(
|
||||
"h3",
|
||||
class_="description__job-criteria-subheader",
|
||||
string=lambda text: "Employment type" in text,
|
||||
)
|
||||
|
||||
employment_type = None
|
||||
if h3_tag:
|
||||
employment_type_span = h3_tag.find_next_sibling(
|
||||
"span",
|
||||
class_="description__job-criteria-text description__job-criteria-text--criteria",
|
||||
)
|
||||
if employment_type_span:
|
||||
employment_type = employment_type_span.get_text(strip=True)
|
||||
employment_type = employment_type.lower()
|
||||
employment_type = employment_type.replace("-", "")
|
||||
|
||||
return [get_enum_from_job_type(employment_type)] if employment_type else []
|
||||
|
||||
return description, get_job_type(soup)
|
||||
|
||||
def get_location(self, metadata_card: Optional[Tag]) -> Location:
|
||||
def _get_location(self, metadata_card: Optional[Tag]) -> Location:
|
||||
"""
|
||||
Extracts the location data from the job metadata card.
|
||||
:param metadata_card
|
||||
@@ -299,25 +260,50 @@ class LinkedInScraper(Scraper):
|
||||
location = Location(
|
||||
city=city,
|
||||
state=state,
|
||||
country=Country.from_string(country),
|
||||
country=Country.from_string(country)
|
||||
)
|
||||
|
||||
return location
|
||||
|
||||
@staticmethod
|
||||
def headers() -> dict:
|
||||
def _parse_job_type(soup_job_type: BeautifulSoup) -> list[JobType] | None:
|
||||
"""
|
||||
Gets the job type from job page
|
||||
:param soup_job_type:
|
||||
:return: JobType
|
||||
"""
|
||||
h3_tag = soup_job_type.find(
|
||||
"h3",
|
||||
class_="description__job-criteria-subheader",
|
||||
string=lambda text: "Employment type" in text,
|
||||
)
|
||||
employment_type = None
|
||||
if h3_tag:
|
||||
employment_type_span = h3_tag.find_next_sibling(
|
||||
"span",
|
||||
class_="description__job-criteria-text description__job-criteria-text--criteria",
|
||||
)
|
||||
if employment_type_span:
|
||||
employment_type = employment_type_span.get_text(strip=True)
|
||||
employment_type = employment_type.lower()
|
||||
employment_type = employment_type.replace("-", "")
|
||||
|
||||
return [get_enum_from_job_type(employment_type)] if employment_type else []
|
||||
|
||||
@staticmethod
|
||||
def job_type_code(job_type_enum: JobType) -> str:
|
||||
return {
|
||||
JobType.FULL_TIME: "F",
|
||||
JobType.PART_TIME: "P",
|
||||
JobType.INTERNSHIP: "I",
|
||||
JobType.CONTRACT: "C",
|
||||
JobType.TEMPORARY: "T",
|
||||
}.get(job_type_enum, "")
|
||||
|
||||
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",
|
||||
"sec-ch-ua": '"Not_A Brand";v="8", "Chromium";v="120", "Google Chrome";v="120"',
|
||||
# 'sec-ch-ua-mobile': '?0',
|
||||
# 'sec-ch-ua-platform': '"macOS"',
|
||||
# 'sec-fetch-dest': 'document',
|
||||
# 'sec-fetch-mode': 'navigate',
|
||||
# 'sec-fetch-site': 'none',
|
||||
# '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/120.0.0.0 Safari/537.36",
|
||||
}
|
||||
|
||||
@@ -1,35 +1,29 @@
|
||||
import re
|
||||
import logging
|
||||
import numpy as np
|
||||
import re
|
||||
|
||||
import tls_client
|
||||
import numpy as np
|
||||
import requests
|
||||
import tls_client
|
||||
from markdownify import markdownify as md
|
||||
from requests.adapters import HTTPAdapter, Retry
|
||||
|
||||
from ..jobs import JobType
|
||||
|
||||
logger = logging.getLogger("JobSpy")
|
||||
logger.propagate = False
|
||||
if not logger.handlers:
|
||||
logger.setLevel(logging.ERROR)
|
||||
logger.setLevel(logging.INFO)
|
||||
console_handler = logging.StreamHandler()
|
||||
console_handler.setLevel(logging.ERROR)
|
||||
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
|
||||
console_handler.setFormatter(formatter)
|
||||
logger.addHandler(console_handler)
|
||||
|
||||
|
||||
def count_urgent_words(description: str) -> int:
|
||||
"""
|
||||
Count the number of urgent words or phrases in a job description.
|
||||
"""
|
||||
urgent_patterns = re.compile(
|
||||
r"\burgen(t|cy)|\bimmediate(ly)?\b|start asap|\bhiring (now|immediate(ly)?)\b",
|
||||
re.IGNORECASE,
|
||||
)
|
||||
matches = re.findall(urgent_patterns, description)
|
||||
count = len(matches)
|
||||
|
||||
return count
|
||||
def markdown_converter(description_html: str):
|
||||
if description_html is None:
|
||||
return None
|
||||
markdown = md(description_html)
|
||||
return markdown.strip()
|
||||
|
||||
|
||||
def extract_emails_from_text(text: str) -> list[str] | None:
|
||||
@@ -42,14 +36,10 @@ def extract_emails_from_text(text: str) -> list[str] | None:
|
||||
def create_session(proxy: dict | None = None, is_tls: bool = True, has_retry: bool = False, delay: int = 1) -> requests.Session:
|
||||
"""
|
||||
Creates a requests session with optional tls, proxy, and retry settings.
|
||||
|
||||
:return: A session object
|
||||
"""
|
||||
if is_tls:
|
||||
session = tls_client.Session(
|
||||
client_identifier="chrome112",
|
||||
random_tls_extension_order=True,
|
||||
)
|
||||
session = tls_client.Session(random_tls_extension_order=True)
|
||||
session.proxies = proxy
|
||||
else:
|
||||
session = requests.Session()
|
||||
@@ -66,7 +56,6 @@ def create_session(proxy: dict | None = None, is_tls: bool = True, has_retry: bo
|
||||
|
||||
session.mount('http://', adapter)
|
||||
session.mount('https://', adapter)
|
||||
|
||||
return session
|
||||
|
||||
|
||||
|
||||
@@ -6,33 +6,75 @@ This module contains routines to scrape ZipRecruiter.
|
||||
"""
|
||||
import math
|
||||
import time
|
||||
from datetime import datetime, timezone
|
||||
from datetime import datetime
|
||||
from typing import Optional, Tuple, Any
|
||||
|
||||
from concurrent.futures import ThreadPoolExecutor
|
||||
|
||||
from .. import Scraper, ScraperInput, Site
|
||||
from ..exceptions import ZipRecruiterException
|
||||
from ...jobs import JobPost, Compensation, Location, JobResponse, JobType, Country
|
||||
from ..utils import count_urgent_words, extract_emails_from_text, create_session
|
||||
from ..utils import (
|
||||
logger,
|
||||
extract_emails_from_text,
|
||||
create_session,
|
||||
markdown_converter
|
||||
)
|
||||
from ...jobs import (
|
||||
JobPost,
|
||||
Compensation,
|
||||
Location,
|
||||
JobResponse,
|
||||
JobType,
|
||||
Country,
|
||||
DescriptionFormat
|
||||
)
|
||||
|
||||
|
||||
class ZipRecruiterScraper(Scraper):
|
||||
base_url = "https://www.ziprecruiter.com"
|
||||
api_url = "https://api.ziprecruiter.com"
|
||||
|
||||
def __init__(self, proxy: Optional[str] = None):
|
||||
"""
|
||||
Initializes ZipRecruiterScraper with the ZipRecruiter job search url
|
||||
"""
|
||||
site = Site(Site.ZIP_RECRUITER)
|
||||
self.url = "https://www.ziprecruiter.com"
|
||||
self.scraper_input = None
|
||||
self.session = create_session(proxy)
|
||||
self.get_cookies()
|
||||
super().__init__(site, proxy=proxy)
|
||||
self._get_cookies()
|
||||
super().__init__(Site.ZIP_RECRUITER, proxy=proxy)
|
||||
|
||||
self.delay = 5
|
||||
self.jobs_per_page = 20
|
||||
self.seen_urls = set()
|
||||
self.delay = 5
|
||||
|
||||
def find_jobs_in_page(
|
||||
def scrape(self, scraper_input: ScraperInput) -> JobResponse:
|
||||
"""
|
||||
Scrapes ZipRecruiter 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
|
||||
job_list: list[JobPost] = []
|
||||
continue_token = None
|
||||
|
||||
max_pages = math.ceil(scraper_input.results_wanted / self.jobs_per_page)
|
||||
for page in range(1, max_pages + 1):
|
||||
if len(job_list) >= scraper_input.results_wanted:
|
||||
break
|
||||
if page > 1:
|
||||
time.sleep(self.delay)
|
||||
logger.info(f'ZipRecruiter search page: {page}')
|
||||
jobs_on_page, continue_token = self._find_jobs_in_page(
|
||||
scraper_input, continue_token
|
||||
)
|
||||
if jobs_on_page:
|
||||
job_list.extend(jobs_on_page)
|
||||
else:
|
||||
break
|
||||
if not continue_token:
|
||||
break
|
||||
return JobResponse(jobs=job_list[: scraper_input.results_wanted])
|
||||
|
||||
def _find_jobs_in_page(
|
||||
self, scraper_input: ScraperInput, continue_token: str | None = None
|
||||
) -> Tuple[list[JobPost], Optional[str]]:
|
||||
"""
|
||||
@@ -41,73 +83,51 @@ class ZipRecruiterScraper(Scraper):
|
||||
:param continue_token:
|
||||
:return: jobs found on page
|
||||
"""
|
||||
params = self.add_params(scraper_input)
|
||||
jobs_list = []
|
||||
params = self._add_params(scraper_input)
|
||||
if continue_token:
|
||||
params["continue_from"] = continue_token
|
||||
try:
|
||||
response = self.session.get(
|
||||
f"https://api.ziprecruiter.com/jobs-app/jobs",
|
||||
headers=self.headers(),
|
||||
res= self.session.get(
|
||||
f"{self.api_url}/jobs-app/jobs",
|
||||
headers=self.headers,
|
||||
params=params
|
||||
)
|
||||
if response.status_code != 200:
|
||||
raise ZipRecruiterException(
|
||||
f"bad response status code: {response.status_code}"
|
||||
)
|
||||
if res.status_code not in range(200, 400):
|
||||
if res.status_code == 429:
|
||||
logger.error(f'429 Response - Blocked by ZipRecruiter for too many requests')
|
||||
else:
|
||||
logger.error(f'ZipRecruiter response status code {res.status_code}')
|
||||
return jobs_list, ""
|
||||
except Exception as e:
|
||||
if "Proxy responded with non 200 code" in str(e):
|
||||
raise ZipRecruiterException("bad proxy")
|
||||
raise ZipRecruiterException(str(e))
|
||||
if "Proxy responded with" in str(e):
|
||||
logger.error(f'Indeed: Bad proxy')
|
||||
else:
|
||||
logger.error(f'Indeed: {str(e)}')
|
||||
return jobs_list, ""
|
||||
|
||||
response_data = response.json()
|
||||
jobs_list = response_data.get("jobs", [])
|
||||
next_continue_token = response_data.get("continue", None)
|
||||
|
||||
res_data = res.json()
|
||||
jobs_list = res_data.get("jobs", [])
|
||||
next_continue_token = res_data.get("continue", None)
|
||||
with ThreadPoolExecutor(max_workers=self.jobs_per_page) as executor:
|
||||
job_results = [executor.submit(self.process_job, job) for job in jobs_list]
|
||||
job_results = [executor.submit(self._process_job, job) for job in jobs_list]
|
||||
|
||||
job_list = list(filter(None, (result.result() for result in job_results)))
|
||||
return job_list, next_continue_token
|
||||
|
||||
def scrape(self, scraper_input: ScraperInput) -> JobResponse:
|
||||
def _process_job(self, job: dict) -> JobPost | None:
|
||||
"""
|
||||
Scrapes ZipRecruiter for jobs with scraper_input criteria.
|
||||
:param scraper_input: Information about job search criteria.
|
||||
:return: JobResponse containing a list of jobs.
|
||||
Processes an individual job dict from the response
|
||||
"""
|
||||
job_list: list[JobPost] = []
|
||||
continue_token = None
|
||||
|
||||
max_pages = math.ceil(scraper_input.results_wanted / self.jobs_per_page)
|
||||
|
||||
for page in range(1, max_pages + 1):
|
||||
if len(job_list) >= scraper_input.results_wanted:
|
||||
break
|
||||
|
||||
if page > 1:
|
||||
time.sleep(self.delay)
|
||||
|
||||
jobs_on_page, continue_token = self.find_jobs_in_page(
|
||||
scraper_input, continue_token
|
||||
)
|
||||
if jobs_on_page:
|
||||
job_list.extend(jobs_on_page)
|
||||
|
||||
if not continue_token:
|
||||
break
|
||||
|
||||
return JobResponse(jobs=job_list[: scraper_input.results_wanted])
|
||||
|
||||
def process_job(self, job: dict) -> JobPost | None:
|
||||
"""Processes an individual job dict from the response"""
|
||||
title = job.get("name")
|
||||
job_url = f"https://www.ziprecruiter.com/jobs//j?lvk={job['listing_key']}"
|
||||
job_url = f"{self.base_url}/jobs//j?lvk={job['listing_key']}"
|
||||
if job_url in self.seen_urls:
|
||||
return
|
||||
self.seen_urls.add(job_url)
|
||||
|
||||
description = job.get("job_description", "").strip()
|
||||
|
||||
description = markdown_converter(description) if self.scraper_input.description_format == DescriptionFormat.MARKDOWN else description
|
||||
company = job.get("hiring_company", {}).get("name")
|
||||
country_value = "usa" if job.get("job_country") == "US" else "canada"
|
||||
country_enum = Country.from_string(country_value)
|
||||
@@ -115,11 +135,10 @@ class ZipRecruiterScraper(Scraper):
|
||||
location = Location(
|
||||
city=job.get("job_city"), state=job.get("job_state"), country=country_enum
|
||||
)
|
||||
job_type = ZipRecruiterScraper.get_job_type_enum(
|
||||
job_type = self._get_job_type_enum(
|
||||
job.get("employment_type", "").replace("_", "").lower()
|
||||
)
|
||||
date_posted = datetime.fromisoformat(job['posted_time'].rstrip("Z")).date()
|
||||
|
||||
return JobPost(
|
||||
title=title,
|
||||
company_name=company,
|
||||
@@ -141,23 +160,21 @@ class ZipRecruiterScraper(Scraper):
|
||||
job_url=job_url,
|
||||
description=description,
|
||||
emails=extract_emails_from_text(description) if description else None,
|
||||
num_urgent_words=count_urgent_words(description) if description else None,
|
||||
)
|
||||
|
||||
def get_cookies(self):
|
||||
url="https://api.ziprecruiter.com/jobs-app/event"
|
||||
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"
|
||||
self.session.post(url, data=data, headers=ZipRecruiterScraper.headers())
|
||||
self.session.post(f"{self.api_url}/jobs-app/event", data=data, headers=self.headers)
|
||||
|
||||
@staticmethod
|
||||
def get_job_type_enum(job_type_str: str) -> list[JobType] | None:
|
||||
def _get_job_type_enum(job_type_str: str) -> list[JobType] | None:
|
||||
for job_type in JobType:
|
||||
if job_type_str in job_type.value:
|
||||
return [job_type]
|
||||
return None
|
||||
|
||||
@staticmethod
|
||||
def add_params(scraper_input) -> dict[str, str | Any]:
|
||||
def _add_params(scraper_input) -> dict[str, str | Any]:
|
||||
params = {
|
||||
"search": scraper_input.search_term,
|
||||
"location": scraper_input.location,
|
||||
@@ -177,18 +194,9 @@ class ZipRecruiterScraper(Scraper):
|
||||
params["remote"] = 1
|
||||
if scraper_input.distance:
|
||||
params["radius"] = scraper_input.distance
|
||||
return {k: v for k, v in params.items() if v is not None}
|
||||
|
||||
params = {k: v for k, v in params.items() if v is not None}
|
||||
|
||||
return params
|
||||
|
||||
@staticmethod
|
||||
def headers() -> dict:
|
||||
"""
|
||||
Returns headers needed for requests
|
||||
:return: dict - Dictionary containing headers
|
||||
"""
|
||||
return {
|
||||
headers = {
|
||||
"Host": "api.ziprecruiter.com",
|
||||
"accept": "*/*",
|
||||
"x-zr-zva-override": "100000000;vid:ZT1huzm_EQlDTVEc",
|
||||
|
||||
Reference in New Issue
Block a user