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26 Commits

Author SHA1 Message Date
Cullen Watson
65d2e5e707 Update pyproject.toml 2024-05-20 11:46:36 -05:00
fasih hussain
08d63a87a2 chore: id added for JobPost schema (#152) 2024-05-20 11:45:52 -05:00
Cullen
1ffdb1756f fix: dup line 2024-04-30 12:11:48 -05:00
Cullen Watson
1185693422 delete empty file 2024-04-30 12:06:20 -05:00
Lluís Salord Quetglas
dcd7144318 FIX: Allow Indeed search term with complex syntax (#139) 2024-04-30 12:05:43 -05:00
Cullen Watson
bf73c061bd enh: linkedin company logo (#141) 2024-04-30 12:03:10 -05:00
Lluís Salord Quetglas
8dd08ed9fd FEAT: Allow LinkedIn scraper to get external job apply url (#140) 2024-04-30 11:36:01 -05:00
Cullen Watson
5d3df732e6 docs: readme 2024-03-12 20:46:25 -05:00
Kellen Mace
86f858e06d Update scrape_jobs() parameters info in readme (#130) 2024-03-12 20:45:13 -05:00
Cullen
1089d1f0a5 docs: readme 2024-03-11 21:30:57 -05:00
Cullen
3e93454738 fix(indeed): readd param 2024-03-11 21:23:20 -05:00
Cullen Watson
0d150d519f docs: readme 2024-03-11 14:52:20 -05:00
Cullen Watson
cc3497f929 docs: readme 2024-03-11 14:45:17 -05:00
Cullen Watson
5986f75346 docs: readme 2024-03-11 14:41:12 -05:00
VitaminB16
4b7bdb9313 feat: Adjust log verbosity via verbose arg (#128) 2024-03-11 14:38:44 -05:00
Cullen Watson
80213f28d2 chore: version 2024-03-11 09:43:12 -05:00
Cullen Watson
ada38532c3 fix: indeed empty location term 2024-03-11 09:42:43 -05:00
Cullen Watson
3b0017964c fix: indeed empty search term 2024-03-11 09:21:11 -05:00
VitaminB16
94d8f555fd format: Apply Black formatter to the codebase (#127) 2024-03-10 23:36:27 -05:00
Cullen Watson
e8b4b376b8 docs: readme 2024-03-09 13:40:34 -06:00
Cullen Watson
54ac1bad16 docs: readme 2024-03-09 01:49:05 -06:00
Cullen Watson
0a669e9ba8 enh: indeed more fields (#126) 2024-03-09 01:40:01 -06:00
gigaSec
a4f6851c32 Fix GlassDoor Country Vietnam(#122) 2024-03-04 17:35:57 -06:00
troy-conte
db01bc6bbb log search updates, fix glassdoor (#120) 2024-03-04 16:39:38 -06:00
Cullen Watson
f8a4eccc6b Remove pandas warning (#118) 2024-02-29 21:30:56 -06:00
Cullen Watson
ba3a16b228 Description format (#107) 2024-02-14 16:04:23 -06:00
14 changed files with 2405 additions and 1819 deletions

7
.pre-commit-config.yaml Normal file
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@@ -0,0 +1,7 @@
repos:
- repo: https://github.com/psf/black
rev: 24.2.0
hooks:
- id: black
language_version: python
args: [--line-length=88, --quiet]

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@@ -11,7 +11,7 @@ work with us.*
- Scrapes job postings from **LinkedIn**, **Indeed**, **Glassdoor**, & **ZipRecruiter** simultaneously - Scrapes job postings from **LinkedIn**, **Indeed**, **Glassdoor**, & **ZipRecruiter** simultaneously
- Aggregates the job postings in a Pandas DataFrame - 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) - [Video Guide for JobSpy](https://www.youtube.com/watch?v=RuP1HrAZnxs&pp=ygUgam9icyBzY3JhcGVyIGJvdCBsaW5rZWRpbiBpbmRlZWQ%3D) -
Updated for release v1.1.3 Updated for release v1.1.3
@@ -21,7 +21,7 @@ Updated for release v1.1.3
### Installation ### Installation
``` ```
pip install python-jobspy pip install -U python-jobspy
``` ```
_Python version >= [3.10](https://www.python.org/downloads/release/python-3100/) required_ _Python version >= [3.10](https://www.python.org/downloads/release/python-3100/) required_
@@ -37,8 +37,9 @@ jobs = scrape_jobs(
search_term="software engineer", search_term="software engineer",
location="Dallas, TX", location="Dallas, TX",
results_wanted=20, results_wanted=20,
hours_old=72, # (only linkedin is hour specific, others round up to days old) hours_old=72, # (only Linkedin/Indeed is hour specific, others round up to days old)
country_indeed='USA' # only needed for indeed / glassdoor country_indeed='USA', # only needed for indeed / glassdoor
# linkedin_fetch_description=True # get full description and direct job url for linkedin (slower)
) )
print(f"Found {len(jobs)} jobs") print(f"Found {len(jobs)} jobs")
print(jobs.head()) print(jobs.head())
@@ -48,7 +49,7 @@ jobs.to_csv("jobs.csv", quoting=csv.QUOTE_NONNUMERIC, escapechar="\\", index=Fal
### Output ### Output
``` ```
SITE TITLE COMPANY_NAME CITY STATE JOB_TYPE INTERVAL MIN_AMOUNT MAX_AMOUNT JOB_URL DESCRIPTION SITE TITLE COMPANY CITY STATE JOB_TYPE INTERVAL MIN_AMOUNT MAX_AMOUNT JOB_URL DESCRIPTION
indeed Software Engineer AMERICAN SYSTEMS Arlington VA None yearly 200000 150000 https://www.indeed.com/viewjob?jk=5e409e577046... THIS POSITION COMES WITH A 10K SIGNING BONUS!... indeed Software Engineer AMERICAN SYSTEMS Arlington VA None yearly 200000 150000 https://www.indeed.com/viewjob?jk=5e409e577046... THIS POSITION COMES WITH A 10K SIGNING BONUS!...
indeed Senior Software Engineer TherapyNotes.com Philadelphia PA fulltime yearly 135000 110000 https://www.indeed.com/viewjob?jk=da39574a40cb... About Us TherapyNotes is the national leader i... indeed Senior Software Engineer TherapyNotes.com Philadelphia PA fulltime yearly 135000 110000 https://www.indeed.com/viewjob?jk=da39574a40cb... About Us TherapyNotes is the national leader i...
linkedin Software Engineer - Early Career Lockheed Martin Sunnyvale CA fulltime yearly None None https://www.linkedin.com/jobs/view/3693012711 Description:By bringing together people that u... linkedin Software Engineer - Early Career Lockheed Martin Sunnyvale CA fulltime yearly None None https://www.linkedin.com/jobs/view/3693012711 Description:By bringing together people that u...
@@ -60,22 +61,24 @@ zip_recruiter Software Developer TEKsystems Phoenix
### Parameters for `scrape_jobs()` ### Parameters for `scrape_jobs()`
```plaintext ```plaintext
Required
├── site_type (List[enum]): linkedin, zip_recruiter, indeed, glassdoor
└── search_term (str)
Optional Optional
├── location (int) ├── site_name (list|str): linkedin, zip_recruiter, indeed, glassdoor (default is all four)
├── distance (int): in miles ├── search_term (str)
├── job_type (enum): fulltime, parttime, internship, contract ├── location (str)
├── proxy (str): in format 'http://user:pass@host:port' or [https, socks] ├── distance (int): in miles, default 50
├── job_type (str): fulltime, parttime, internship, contract
├── proxy (str): in format 'http://user:pass@host:port'
├── is_remote (bool) ├── is_remote (bool)
├── full_description (bool): fetches full description for LinkedIn (slower) ├── results_wanted (int): number of job results to retrieve for each site specified in 'site_name'
├── 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 & Indeed do not allow pairing this with hours_old)
├── easy_apply (bool): filters for jobs that are hosted on the job board site ├── linkedin_fetch_description (bool): fetches full description and direct job url for LinkedIn (slower)
├── linkedin_company_ids (list[int): searches for linkedin jobs with specific company ids ├── linkedin_company_ids (list[int]): searches for linkedin jobs with specific company ids
├── country_indeed (enum): filters the country on Indeed (see below for correct spelling) ├── description_format (str): markdown, html (Format type of the job descriptions. Default is markdown.)
├── offset (num): starts the search from an offset (e.g. 25 will start the search from the 25th result) ├── country_indeed (str): filters the country on Indeed (see below for correct spelling)
├── hours_old (int): filters jobs by the number of hours since the job was posted (all but LinkedIn rounds up to next day) ├── offset (int): 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 (ZipRecruiter and Glassdoor round up to next day. If you use this on Indeed, it will not filter by job_type/is_remote/easy_apply)
├── verbose (int) {0, 1, 2}: Controls the verbosity of the runtime printouts (0 prints only errors, 1 is errors+warnings, 2 is all logs. Default is 2.)
├── hyperlinks (bool): Whether to turn `job_url`s into hyperlinks. Default is false.
``` ```
### JobPost Schema ### JobPost Schema
@@ -99,24 +102,26 @@ JobPost
│ └── currency (enum) │ └── currency (enum)
└── date_posted (date) └── date_posted (date)
└── emails (str) └── emails (str)
└── num_urgent_words (int)
└── is_remote (bool) └── 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 ## Supported Countries for Job Searching
### **LinkedIn** ### **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.
### **ZipRecruiter** ### **ZipRecruiter**
@@ -146,10 +151,14 @@ You can specify the following countries when searching on Indeed (use the exact
| South Korea | Spain* | Sweden | Switzerland* | | South Korea | Spain* | Sweden | Switzerland* |
| Taiwan | Thailand | Turkey | Ukraine | | Taiwan | Thailand | Turkey | Ukraine |
| United Arab Emirates | UK* | USA* | Uruguay | | 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.
* All the job board endpoints are capped at around 1000 jobs on a given search.
* LinkedIn is the most restrictive and usually rate limits around the 10th page.
## Frequently Asked Questions ## Frequently Asked Questions
--- ---
@@ -167,7 +176,3 @@ persist, [submit an issue](https://github.com/Bunsly/JobSpy/issues).
- Trying a VPN or proxy to change your IP address. - Trying a VPN or proxy to change your IP address.
--- ---

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@@ -32,17 +32,18 @@ while len(all_jobs) < results_wanted:
search_term="software engineer", search_term="software engineer",
# New York, NY # New York, NY
# Dallas, TX # Dallas, TX
# Los Angeles, CA # Los Angeles, CA
location="Los Angeles, CA", location="Los Angeles, CA",
results_wanted=min(results_in_each_iteration, results_wanted - len(all_jobs)), results_wanted=min(
results_in_each_iteration, results_wanted - len(all_jobs)
),
country_indeed="USA", country_indeed="USA",
offset=offset, offset=offset,
# proxy="http://jobspy:5a4vpWtj8EeJ2hoYzk@ca.smartproxy.com:20001", # proxy="http://jobspy:5a4vpWtj8EeJ2hoYzk@ca.smartproxy.com:20001",
) )
# Add the scraped jobs to the list # Add the scraped jobs to the list
all_jobs.extend(jobs.to_dict('records')) all_jobs.extend(jobs.to_dict("records"))
# Increment the offset for the next page of results # Increment the offset for the next page of results
offset += results_in_each_iteration offset += results_in_each_iteration

2205
poetry.lock generated

File diff suppressed because it is too large Load Diff

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@@ -1,6 +1,6 @@
[tool.poetry] [tool.poetry]
name = "python-jobspy" name = "python-jobspy"
version = "1.1.44" version = "1.1.53"
description = "Job scraper for LinkedIn, Indeed, Glassdoor & ZipRecruiter" 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" homepage = "https://github.com/Bunsly/JobSpy"
@@ -13,17 +13,24 @@ packages = [
[tool.poetry.dependencies] [tool.poetry.dependencies]
python = "^3.10" python = "^3.10"
requests = "^2.31.0" requests = "^2.31.0"
tls-client = "*"
beautifulsoup4 = "^4.12.2" beautifulsoup4 = "^4.12.2"
pandas = "^2.1.0" pandas = "^2.1.0"
NUMPY = "1.24.2" NUMPY = "1.24.2"
pydantic = "^2.3.0" pydantic = "^2.3.0"
tls-client = "^1.0.1"
markdownify = "^0.11.6"
regex = "^2024.4.28"
[tool.poetry.group.dev.dependencies] [tool.poetry.group.dev.dependencies]
pytest = "^7.4.1" pytest = "^7.4.1"
jupyter = "^1.0.0" jupyter = "^1.0.0"
black = "*"
pre-commit = "*"
[build-system] [build-system]
requires = ["poetry-core"] requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api" build-backend = "poetry.core.masonry.api"
[tool.black]
line-length = 88

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@@ -1,8 +1,11 @@
from __future__ import annotations
import pandas as pd import pandas as pd
from typing import Tuple from typing import Tuple
from concurrent.futures import ThreadPoolExecutor, as_completed from concurrent.futures import ThreadPoolExecutor, as_completed
from .jobs import JobType, Location from .jobs import JobType, Location
from .scrapers.utils import logger, set_logger_level
from .scrapers.indeed import IndeedScraper from .scrapers.indeed import IndeedScraper
from .scrapers.ziprecruiter import ZipRecruiterScraper from .scrapers.ziprecruiter import ZipRecruiterScraper
from .scrapers.glassdoor import GlassdoorScraper from .scrapers.glassdoor import GlassdoorScraper
@@ -15,23 +18,12 @@ from .scrapers.exceptions import (
GlassdoorException, 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( def scrape_jobs(
site_name: str | list[str] | Site | list[Site] | None = None, site_name: str | list[str] | Site | list[Site] | None = None,
search_term: str | None = None, search_term: str | None = None,
location: str | None = None, location: str | None = None,
distance: int | None = None, distance: int | None = 50,
is_remote: bool = False, is_remote: bool = False,
job_type: str | None = None, job_type: str | None = None,
easy_apply: bool | None = None, easy_apply: bool | None = None,
@@ -39,16 +31,28 @@ def scrape_jobs(
country_indeed: str = "usa", country_indeed: str = "usa",
hyperlinks: bool = False, hyperlinks: bool = False,
proxy: str | None = None, 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, linkedin_company_ids: list[int] | None = None,
offset: int | None = 0, offset: int | None = 0,
hours_old: int = None, hours_old: int = None,
verbose: int = 2,
**kwargs, **kwargs,
) -> pd.DataFrame: ) -> pd.DataFrame:
""" """
Simultaneously scrapes job data from multiple job sites. Simultaneously scrapes job data from multiple job sites.
:return: results_wanted: pandas dataframe containing job data :return: pandas dataframe containing job data
""" """
SCRAPER_MAPPING = {
Site.LINKEDIN: LinkedInScraper,
Site.INDEED: IndeedScraper,
Site.ZIP_RECRUITER: ZipRecruiterScraper,
Site.GLASSDOOR: GlassdoorScraper,
}
set_logger_level(verbose)
def map_str_to_site(site_name: str) -> Site:
return Site[site_name.upper()]
def get_enum_from_value(value_str): def get_enum_from_value(value_str):
for job_type in JobType: for job_type in JobType:
@@ -61,12 +65,12 @@ def scrape_jobs(
def get_site_type(): def get_site_type():
site_types = list(Site) site_types = list(Site)
if isinstance(site_name, str): 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): elif isinstance(site_name, Site):
site_types = [site_name] site_types = [site_name]
elif isinstance(site_name, list): elif isinstance(site_name, list):
site_types = [ 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 for site in site_name
] ]
return site_types return site_types
@@ -82,32 +86,21 @@ def scrape_jobs(
is_remote=is_remote, is_remote=is_remote,
job_type=job_type, job_type=job_type,
easy_apply=easy_apply, easy_apply=easy_apply,
full_description=full_description, description_format=description_format,
linkedin_fetch_description=linkedin_fetch_description,
results_wanted=results_wanted, results_wanted=results_wanted,
linkedin_company_ids=linkedin_company_ids, linkedin_company_ids=linkedin_company_ids,
offset=offset, offset=offset,
hours_old=hours_old hours_old=hours_old,
) )
def scrape_site(site: Site) -> Tuple[str, JobResponse]: def scrape_site(site: Site) -> Tuple[str, JobResponse]:
scraper_class = SCRAPER_MAPPING[site] scraper_class = SCRAPER_MAPPING[site]
scraper = scraper_class(proxy=proxy) scraper = scraper_class(proxy=proxy)
try:
scraped_data: JobResponse = scraper.scrape(scraper_input) scraped_data: JobResponse = scraper.scrape(scraper_input)
except (LinkedInException, IndeedException, ZipRecruiterException) as lie: cap_name = site.value.capitalize()
raise lie site_name = "ZipRecruiter" if cap_name == "Zip_recruiter" else cap_name
except Exception as e: logger.info(f"{site_name} finished scraping")
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
return site.value, scraped_data return site.value, scraped_data
site_to_jobs_dict = {} site_to_jobs_dict = {}
@@ -130,9 +123,8 @@ def scrape_jobs(
for site, job_response in site_to_jobs_dict.items(): for site, job_response in site_to_jobs_dict.items():
for job in job_response.jobs: for job in job_response.jobs:
job_data = job.dict() job_data = job.dict()
job_data[ job_url = job_data["job_url"]
"job_url_hyper" job_data["job_url_hyper"] = f'<a href="{job_url}">{job_url}</a>'
] = f'<a href="{job_data["job_url"]}">{job_data["job_url"]}</a>'
job_data["site"] = site job_data["site"] = site
job_data["company"] = job_data["company_name"] job_data["company"] = job_data["company_name"]
job_data["job_type"] = ( job_data["job_type"] = (
@@ -168,13 +160,20 @@ def scrape_jobs(
jobs_dfs.append(job_df) jobs_dfs.append(job_df)
if jobs_dfs: if jobs_dfs:
jobs_df = pd.concat(jobs_dfs, ignore_index=True) # Step 1: Filter out all-NA columns from each DataFrame before concatenation
desired_order: list[str] = [ filtered_dfs = [df.dropna(axis=1, how="all") for df in jobs_dfs]
"job_url_hyper" if hyperlinks else "job_url",
# Step 2: Concatenate the filtered DataFrames
jobs_df = pd.concat(filtered_dfs, ignore_index=True)
# Desired column order
desired_order = [
"id",
"site", "site",
"job_url_hyper" if hyperlinks else "job_url",
"job_url_direct",
"title", "title",
"company", "company",
"company_url",
"location", "location",
"job_type", "job_type",
"date_posted", "date_posted",
@@ -183,13 +182,30 @@ def scrape_jobs(
"max_amount", "max_amount",
"currency", "currency",
"is_remote", "is_remote",
"num_urgent_words",
"benefits",
"emails", "emails",
"description", "description",
"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",
] ]
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]) # 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()

View File

@@ -1,3 +1,5 @@
from __future__ import annotations
from typing import Optional from typing import Optional
from datetime import date from datetime import date
from enum import Enum from enum import Enum
@@ -57,7 +59,7 @@ class JobType(Enum):
class Country(Enum): class Country(Enum):
""" """
Gets the subdomain for Indeed and Glassdoor. 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 The third item in the tuple is the subdomain (and tld if there's a ':' separator) for Glassdoor
""" """
@@ -118,11 +120,11 @@ class Country(Enum):
TURKEY = ("turkey", "tr") TURKEY = ("turkey", "tr")
UKRAINE = ("ukraine", "ua") UKRAINE = ("ukraine", "ua")
UNITEDARABEMIRATES = ("united arab emirates", "ae") UNITEDARABEMIRATES = ("united arab emirates", "ae")
UK = ("uk,united kingdom", "uk", "co.uk") UK = ("uk,united kingdom", "uk:gb", "co.uk")
USA = ("usa,us,united states", "www", "com") USA = ("usa,us,united states", "www:us", "com")
URUGUAY = ("uruguay", "uy") URUGUAY = ("uruguay", "uy")
VENEZUELA = ("venezuela", "ve") VENEZUELA = ("venezuela", "ve")
VIETNAM = ("vietnam", "vn") VIETNAM = ("vietnam", "vn", "com")
# internal for ziprecruiter # internal for ziprecruiter
US_CANADA = ("usa/ca", "www") US_CANADA = ("usa/ca", "www")
@@ -132,7 +134,10 @@ class Country(Enum):
@property @property
def indeed_domain_value(self): 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 @property
def glassdoor_domain_value(self): def glassdoor_domain_value(self):
@@ -145,7 +150,7 @@ class Country(Enum):
else: else:
raise Exception(f"Glassdoor is not available for {self.name}") 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}/" return f"https://{self.glassdoor_domain_value}/"
@classmethod @classmethod
@@ -153,7 +158,7 @@ class Country(Enum):
"""Convert a string to the corresponding Country enum.""" """Convert a string to the corresponding Country enum."""
country_str = country_str.strip().lower() country_str = country_str.strip().lower()
for country in cls: for country in cls:
country_names = country.value[0].split(',') country_names = country.value[0].split(",")
if country_str in country_names: if country_str in country_names:
return country return country
valid_countries = [country.value for country in cls] valid_countries = [country.value for country in cls]
@@ -163,7 +168,7 @@ class Country(Enum):
class Location(BaseModel): class Location(BaseModel):
country: Country | None = None country: Country | str | None = None
city: Optional[str] = None city: Optional[str] = None
state: Optional[str] = None state: Optional[str] = None
@@ -173,7 +178,12 @@ class Location(BaseModel):
location_parts.append(self.city) location_parts.append(self.city)
if self.state: if self.state:
location_parts.append(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] country_name = self.country.value[0]
if "," in country_name: if "," in country_name:
country_name = country_name.split(",")[0] country_name = country_name.split(",")[0]
@@ -210,23 +220,39 @@ class Compensation(BaseModel):
currency: Optional[str] = "USD" currency: Optional[str] = "USD"
class DescriptionFormat(Enum):
MARKDOWN = "markdown"
HTML = "html"
class JobPost(BaseModel): class JobPost(BaseModel):
id: str | None = None
title: str title: str
company_name: str company_name: str | None
job_url: str job_url: str
job_url_direct: str | None = None
location: Optional[Location] location: Optional[Location]
description: str | None = None description: str | None = None
company_url: str | None = None company_url: str | None = None
company_url_direct: str | None = None
job_type: list[JobType] | None = None job_type: list[JobType] | None = None
compensation: Compensation | None = None compensation: Compensation | None = None
date_posted: date | None = None date_posted: date | None = None
benefits: str | None = None
emails: list[str] | None = None emails: list[str] | None = None
num_urgent_words: int | None = None
is_remote: bool | 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): class JobResponse(BaseModel):

View File

@@ -1,4 +1,15 @@
from ..jobs import Enum, BaseModel, JobType, JobResponse, Country from __future__ import annotations
from abc import ABC, abstractmethod
from ..jobs import (
Enum,
BaseModel,
JobType,
JobResponse,
Country,
DescriptionFormat,
)
class Site(Enum): class Site(Enum):
@@ -18,17 +29,19 @@ class ScraperInput(BaseModel):
is_remote: bool = False is_remote: bool = False
job_type: JobType | None = None job_type: JobType | None = None
easy_apply: bool | None = None easy_apply: bool | None = None
full_description: bool = False
offset: int = 0 offset: int = 0
linkedin_fetch_description: bool = False
linkedin_company_ids: list[int] | None = None linkedin_company_ids: list[int] | None = None
description_format: DescriptionFormat | None = DescriptionFormat.MARKDOWN
results_wanted: int = 15 results_wanted: int = 15
hours_old: int | None = None hours_old: int | None = None
class Scraper: class Scraper(ABC):
def __init__(self, site: Site, proxy: list[str] | None = None): def __init__(self, site: Site, proxy: list[str] | None = None):
self.site = site self.site = site
self.proxy = (lambda p: {"http": p, "https": p} if p else None)(proxy) self.proxy = (lambda p: {"http": p, "https": p} if p else None)(proxy)
@abstractmethod
def scrape(self, scraper_input: ScraperInput) -> JobResponse: ... def scrape(self, scraper_input: ScraperInput) -> JobResponse: ...

View File

@@ -4,16 +4,24 @@ jobspy.scrapers.glassdoor
This module contains routines to scrape Glassdoor. This module contains routines to scrape Glassdoor.
""" """
from __future__ import annotations
import re
import json import json
import requests import requests
from typing import Optional from typing import Optional, Tuple
from datetime import datetime, timedelta from datetime import datetime, timedelta
from concurrent.futures import ThreadPoolExecutor, as_completed from concurrent.futures import ThreadPoolExecutor, as_completed
from ..utils import count_urgent_words, extract_emails_from_text
from .. import Scraper, ScraperInput, Site from .. import Scraper, ScraperInput, Site
from ..utils import extract_emails_from_text
from ..exceptions import GlassdoorException from ..exceptions import GlassdoorException
from ..utils import create_session from ..utils import (
create_session,
markdown_converter,
logger,
)
from ...jobs import ( from ...jobs import (
JobPost, JobPost,
Compensation, Compensation,
@@ -21,6 +29,7 @@ from ...jobs import (
Location, Location,
JobResponse, JobResponse,
JobType, JobType,
DescriptionFormat,
) )
@@ -32,73 +41,142 @@ class GlassdoorScraper(Scraper):
site = Site(Site.GLASSDOOR) site = Site(Site.GLASSDOOR)
super().__init__(site, proxy=proxy) super().__init__(site, proxy=proxy)
self.url = None self.base_url = None
self.country = None self.country = None
self.session = None self.session = None
self.scraper_input = None
self.jobs_per_page = 30 self.jobs_per_page = 30
self.max_pages = 30
self.seen_urls = set() 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
range_start = 1 + (scraper_input.offset // self.jobs_per_page)
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}")
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, self,
scraper_input: ScraperInput, scraper_input: ScraperInput,
location_id: int, location_id: int,
location_type: str, location_type: str,
page_num: int, page_num: int,
cursor: str | None, cursor: str | None,
) -> (list[JobPost], str | None): ) -> Tuple[list[JobPost], str | None]:
""" """
Scrapes a page of Glassdoor for jobs with scraper_input criteria Scrapes a page of Glassdoor for jobs with scraper_input criteria
""" """
jobs = []
self.scraper_input = scraper_input
try: try:
payload = self.add_payload( payload = self._add_payload(location_id, location_type, page_num, cursor)
scraper_input, location_id, location_type, page_num, cursor
)
response = self.session.post( 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: if response.status_code != 200:
raise GlassdoorException( exc_msg = f"bad response status code: {response.status_code}"
f"bad response status code: {response.status_code}" raise GlassdoorException(exc_msg)
)
res_json = response.json()[0] res_json = response.json()[0]
if "errors" in res_json: if "errors" in res_json:
raise ValueError("Error encountered in API response") raise ValueError("Error encountered in API response")
except Exception as e: except (
raise GlassdoorException(str(e)) 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_data = res_json["data"]["jobListings"]["jobListings"]
jobs = []
with ThreadPoolExecutor(max_workers=self.jobs_per_page) as executor: 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): for future in as_completed(future_to_job_data):
try: try:
job_post = future.result() job_post = future.result()
if job_post: if job_post:
jobs.append(job_post) jobs.append(job_post)
except Exception as exc: except Exception as exc:
raise GlassdoorException(f'Glassdoor generated an exception: {exc}') raise GlassdoorException(f"Glassdoor generated an exception: {exc}")
return jobs, self.get_cursor_for_page( return jobs, self.get_cursor_for_page(
res_json["data"]["jobListings"]["paginationCursors"], page_num + 1 res_json["data"]["jobListings"]["paginationCursors"], page_num + 1
) )
def process_job(self, job_data): def _get_csrf_token(self):
"""Processes a single job and fetches its description.""" """
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_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: if job_url in self.seen_urls:
return None return None
self.seen_urls.add(job_url) self.seen_urls.add(job_url)
job = job_data["jobview"] job = job_data["jobview"]
title = job["job"]["jobTitleText"] title = job["job"]["jobTitleText"]
company_name = job["header"]["employerNameFromSearch"] company_name = job["header"]["employerNameFromSearch"]
company_id = job_data['jobview']['header']['employer']['id'] company_id = job_data["jobview"]["header"]["employer"]["id"]
location_name = job["header"].get("locationName", "") location_name = job["header"].get("locationName", "")
location_type = job["header"].get("locationType", "") location_type = job["header"].get("locationType", "")
age_in_days = job["header"].get("ageInDays") age_in_days = job["header"].get("ageInDays")
is_remote, location = False, None is_remote, location = False, None
date_posted = (datetime.now() - timedelta(days=age_in_days)).date() if age_in_days is not None else None date_diff = (datetime.now() - timedelta(days=age_in_days)).date()
date_posted = date_diff if age_in_days is not None else None
if location_type == "S": if location_type == "S":
is_remote = True is_remote = True
@@ -106,15 +184,15 @@ class GlassdoorScraper(Scraper):
location = self.parse_location(location_name) location = self.parse_location(location_name)
compensation = self.parse_compensation(job["header"]) compensation = self.parse_compensation(job["header"])
try: try:
description = self.fetch_job_description(job_id) description = self._fetch_job_description(job_id)
except: except:
description = None description = None
company_url = f"{self.base_url}Overview/W-EI_IE{company_id}.htm"
job_post = JobPost( return JobPost(
id=str(job_id),
title=title, title=title,
company_url=f"{self.url}Overview/W-EI_IE{company_id}.htm" if company_id else None, company_url=company_url if company_id else None,
company_name=company_name, company_name=company_name,
date_posted=date_posted, date_posted=date_posted,
job_url=job_url, job_url=job_url,
@@ -123,62 +201,20 @@ class GlassdoorScraper(Scraper):
is_remote=is_remote, is_remote=is_remote,
description=description, description=description,
emails=extract_emails_from_text(description) if description else None, 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. Fetches the job description for a single job ID.
:param scraper_input: Information about job search criteria.
:return: JobResponse containing a list of jobs.
""" """
scraper_input.results_wanted = min(900, scraper_input.results_wanted) url = f"{self.base_url}/graph"
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"
body = [ body = [
{ {
"operationName": "JobDetailQuery", "operationName": "JobDetailQuery",
"variables": { "variables": {
"jl": job_id, "jl": job_id,
"queryString": "q", "queryString": "q",
"pageTypeEnum": "SERP" "pageTypeEnum": "SERP",
}, },
"query": """ "query": """
query JobDetailQuery($jl: Long!, $queryString: String, $pageTypeEnum: PageTypeEnum) { query JobDetailQuery($jl: Long!, $queryString: String, $pageTypeEnum: PageTypeEnum) {
@@ -193,22 +229,90 @@ class GlassdoorScraper(Scraper):
__typename __typename
} }
} }
""" """,
} }
] ]
response = requests.post(url, json=body, headers=GlassdoorScraper.headers()) res = requests.post(url, json=body, headers=self.headers)
if response.status_code != 200: if res.status_code != 200:
return None return None
data = response.json()[0] data = res.json()[0]
desc = data['data']['jobview']['job']['description'] desc = data["data"]["jobview"]["job"]["description"]
if self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
desc = markdown_converter(desc)
return desc return desc
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.base_url}/findPopularLocationAjax.htm?maxLocationsToReturn=10&term={location}"
session = create_session(self.proxy, has_retry=True)
res = self.session.get(url, headers=self.headers)
if res.status_code != 200:
if res.status_code == 429:
err = f"429 Response - Blocked by Glassdoor for too many requests"
logger.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}")
return None, None
items = res.json()
if not items:
raise ValueError(f"Location '{location}' not found on Glassdoor")
location_type = items[0]["locationType"]
if location_type == "C":
location_type = "CITY"
elif location_type == "S":
location_type = "STATE"
elif location_type == "N":
location_type = "COUNTRY"
return int(items[0]["locationId"]), location_type
def _add_payload(
self,
location_id: int,
location_type: str,
page_num: int,
cursor: str | None = None,
) -> str:
fromage = None
if self.scraper_input.hours_old:
fromage = max(self.scraper_input.hours_old // 24, 1)
filter_params = []
if self.scraper_input.easy_apply:
filter_params.append({"filterKey": "applicationType", "values": "1"})
if fromage:
filter_params.append({"filterKey": "fromAge", "values": str(fromage)})
payload = {
"operationName": "JobSearchResultsQuery",
"variables": {
"excludeJobListingIds": [],
"filterParams": filter_params,
"keyword": self.scraper_input.search_term,
"numJobsToShow": 30,
"locationType": location_type,
"locationId": int(location_id),
"parameterUrlInput": f"IL.0,12_I{location_type}{location_id}",
"pageNumber": page_num,
"pageCursor": cursor,
"fromage": fromage,
"sort": "date",
},
"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 @staticmethod
def parse_compensation(data: dict) -> Optional[Compensation]: def parse_compensation(data: dict) -> Optional[Compensation]:
pay_period = data.get("payPeriod") pay_period = data.get("payPeriod")
adjusted_pay = data.get("payPeriodAdjustedPay") adjusted_pay = data.get("payPeriodAdjustedPay")
currency = data.get("payCurrency", "USD") currency = data.get("payCurrency", "USD")
if not pay_period or not adjusted_pay: if not pay_period or not adjusted_pay:
return None return None
@@ -219,7 +323,6 @@ class GlassdoorScraper(Scraper):
interval = CompensationInterval.get_interval(pay_period) interval = CompensationInterval.get_interval(pay_period)
min_amount = int(adjusted_pay.get("p10") // 1) min_amount = int(adjusted_pay.get("p10") // 1)
max_amount = int(adjusted_pay.get("p90") // 1) max_amount = int(adjusted_pay.get("p90") // 1)
return Compensation( return Compensation(
interval=interval, interval=interval,
min_amount=min_amount, min_amount=min_amount,
@@ -227,59 +330,44 @@ class GlassdoorScraper(Scraper):
currency=currency, currency=currency,
) )
def get_location(self, location: str, is_remote: bool) -> (int, str): @staticmethod
if not location or is_remote: def get_job_type_enum(job_type_str: str) -> list[JobType] | None:
return "11047", "STATE" # remote options for job_type in JobType:
url = f"{self.url}/findPopularLocationAjax.htm?maxLocationsToReturn=10&term={location}" if job_type_str in job_type.value:
session = create_session(self.proxy, has_retry=True) return [job_type]
response = session.get(url)
if response.status_code != 200:
raise GlassdoorException(
f"bad response status code: {response.status_code}"
)
items = response.json()
if not items:
raise ValueError(f"Location '{location}' not found on Glassdoor")
location_type = items[0]["locationType"]
if location_type == "C":
location_type = "CITY"
elif location_type == "S":
location_type = "STATE"
elif location_type == 'N':
location_type = "COUNTRY"
return int(items[0]["locationId"]), location_type
@staticmethod @staticmethod
def add_payload( def parse_location(location_name: str) -> Location | None:
scraper_input, if not location_name or location_name == "Remote":
location_id: int, return
location_type: str, city, _, state = location_name.partition(", ")
page_num: int, return Location(city=city, state=state)
cursor: str | None = None,
) -> str: @staticmethod
# `fromage` is the posting time filter in days def get_cursor_for_page(pagination_cursors, page_num):
fromage = max(scraper_input.hours_old // 24, 1) if scraper_input.hours_old else None for cursor_data in pagination_cursors:
filter_params = [] if cursor_data["pageNumber"] == page_num:
if scraper_input.easy_apply: return cursor_data["cursor"]
filter_params.append({"filterKey": "applicationType", "values": "1"})
if fromage: fallback_token = "Ft6oHEWlRZrxDww95Cpazw:0pGUrkb2y3TyOpAIqF2vbPmUXoXVkD3oEGDVkvfeCerceQ5-n8mBg3BovySUIjmCPHCaW0H2nQVdqzbtsYqf4Q:wcqRqeegRUa9MVLJGyujVXB7vWFPjdaS1CtrrzJq-ok"
filter_params.append({"filterKey": "fromAge", "values": str(fromage)}) headers = {
payload = { "authority": "www.glassdoor.com",
"operationName": "JobSearchResultsQuery", "accept": "*/*",
"variables": { "accept-language": "en-US,en;q=0.9",
"excludeJobListingIds": [], "apollographql-client-name": "job-search-next",
"filterParams": filter_params, "apollographql-client-version": "4.65.5",
"keyword": scraper_input.search_term, "content-type": "application/json",
"numJobsToShow": 30, "origin": "https://www.glassdoor.com",
"locationType": location_type, "referer": "https://www.glassdoor.com/",
"locationId": int(location_id), "sec-ch-ua": '"Chromium";v="118", "Google Chrome";v="118", "Not=A?Brand";v="99"',
"parameterUrlInput": f"IL.0,12_I{location_type}{location_id}", "sec-ch-ua-mobile": "?0",
"pageNumber": page_num, "sec-ch-ua-platform": '"macOS"',
"pageCursor": cursor, "sec-fetch-dest": "empty",
"fromage": fromage, "sec-fetch-mode": "cors",
"sort": "date" "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": """ }
query_template = """
query JobSearchResultsQuery( query JobSearchResultsQuery(
$excludeJobListingIds: [Long!], $excludeJobListingIds: [Long!],
$keyword: String, $keyword: String,
@@ -445,54 +533,3 @@ class GlassdoorScraper(Scraper):
__typename __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",
}

View File

@@ -4,24 +4,22 @@ jobspy.scrapers.indeed
This module contains routines to scrape Indeed. This module contains routines to scrape Indeed.
""" """
import re
import math
import json
import requests
from typing import Any
from datetime import datetime
from bs4 import BeautifulSoup from __future__ import annotations
from bs4.element import Tag
import math
from typing import Tuple
from datetime import datetime
from concurrent.futures import ThreadPoolExecutor, Future from concurrent.futures import ThreadPoolExecutor, Future
from ..exceptions import IndeedException import requests
from .. import Scraper, ScraperInput, Site
from ..utils import ( from ..utils import (
count_urgent_words,
extract_emails_from_text, extract_emails_from_text,
create_session,
get_enum_from_job_type, get_enum_from_job_type,
logger markdown_converter,
logger,
) )
from ...jobs import ( from ...jobs import (
JobPost, JobPost,
@@ -30,353 +28,355 @@ from ...jobs import (
Location, Location,
JobResponse, JobResponse,
JobType, JobType,
DescriptionFormat,
) )
from .. import Scraper, ScraperInput, Site
class IndeedScraper(Scraper): class IndeedScraper(Scraper):
def __init__(self, proxy: str | None = None): 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.scraper_input = None
self.country = 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) site = Site(Site.INDEED)
super().__init__(site, proxy=proxy) 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: def scrape(self, scraper_input: ScraperInput) -> JobResponse:
""" """
Scrapes Indeed for jobs with scraper_input criteria Scrapes Indeed for jobs with scraper_input criteria
:param scraper_input: :param scraper_input:
:return: job_response :return: job_response
""" """
job_list = self.scrape_page(scraper_input, 0) self.scraper_input = scraper_input
pages_processed = 1 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: 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) logger.info(f"Indeed search page: {page}")
new_jobs = False jobs, cursor = self._scrape_page(cursor)
if not jobs:
with ThreadPoolExecutor(max_workers=10) as executor: logger.info(f"Indeed found no jobs on page: {page}")
futures: list[Future] = [ break
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:
job_list += jobs job_list += jobs
new_jobs = True page += 1
if len(self.seen_urls) >= scraper_input.results_wanted: return JobResponse(jobs=job_list[: scraper_input.results_wanted])
break
pages_processed += pages_to_process def _scrape_page(self, cursor: str | None) -> Tuple[list[JobPost], str | None]:
if not new_jobs: """
break 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()
search_term = self.scraper_input.search_term.replace('"', '\\"') if self.scraper_input.search_term else ""
query = self.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}}'
if self.scraper_input.location
else ""
),
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 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()]
return job_list, new_cursor
if len(self.seen_urls) > scraper_input.results_wanted: def _build_filters(self):
job_list = job_list[:scraper_input.results_wanted] """
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.easy_apply:
filters_str = """
filters: {
keyword: {
field: "indeedApplyScope",
keys: ["DESKTOP"]
}
}
"""
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"]
if self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
description = markdown_converter(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 {}
rel_url = job["employer"]["relativeCompanyPageUrl"] if job["employer"] else None
return JobPost(
id=str(job["key"]),
title=job["title"],
description=description,
company_name=job["employer"].get("name") if job.get("employer") else None,
company_url=(f"{self.base_url}{rel_url}" 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 @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 Parses the attributes to get list of job types
:param job: :param attributes:
:return: :return: list of JobType
""" """
job_types: list[JobType] = [] job_types: list[JobType] = []
for taxonomy in job["taxonomyAttributes"]: for attribute in attributes:
if taxonomy["label"] == "job-types": job_type_str = attribute["label"].replace("-", "").replace(" ", "").lower()
for i in range(len(taxonomy["attributes"])):
label = taxonomy["attributes"][i].get("label")
if label:
job_type_str = label.replace("-", "").replace(" ", "").lower()
job_type = get_enum_from_job_type(job_type_str) job_type = get_enum_from_job_type(job_type_str)
if job_type: if job_type:
job_types.append(job_type) job_types.append(job_type)
return job_types return job_types
@staticmethod @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:
:param job_detailed:
:return: compensation object :return: compensation object
""" """
comp = job_detailed['compensation']['baseSalary'] comp = job["compensation"]["baseSalary"]
if comp: if not comp:
interval = IndeedScraper.get_correct_interval(comp['unitOfWork']) return None
if interval: interval = IndeedScraper._get_compensation_interval(comp["unitOfWork"])
if not interval:
return None
min_range = comp["range"].get("min")
max_range = comp["range"].get("max")
return Compensation( return Compensation(
interval=interval, interval=interval,
min_amount=round(comp['range'].get('min'), 2) if comp['range'].get('min') is not None else None, min_amount=round(min_range, 2) if min_range is not None else None,
max_amount=round(comp['range'].get('max'), 2) if comp['range'].get('max') is not None else None, max_amount=round(max_range, 2) if max_range is not None else None,
currency=job_detailed['compensation']['currencyCode'] currency=job["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"
) )
@staticmethod @staticmethod
def get_headers(): def _is_job_remote(job: dict, description: str) -> bool:
return { """
'Host': 'www.indeed.com', Searches the description, location, and attributes to check if job is remote
'accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8', """
'sec-fetch-site': 'same-origin', remote_keywords = ["remote", "work from home", "wfh"]
'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:
remote_keywords = ['remote', 'work from home', 'wfh']
is_remote_in_attributes = any( is_remote_in_attributes = any(
any(keyword in attr['label'].lower() for keyword in remote_keywords) 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_description = any(keyword in description.lower() for keyword in remote_keywords)
is_remote_in_location = any( 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 for keyword in remote_keywords
) )
is_remote_in_taxonomy = any( return (
taxonomy["label"] == "remote" and len(taxonomy["attributes"]) > 0 is_remote_in_attributes or is_remote_in_description or is_remote_in_location
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
def get_job_details(self, job_keys: list[str]) -> dict: @staticmethod
""" def _get_compensation_interval(interval: str) -> CompensationInterval:
Queries the GraphQL endpoint for detailed job information for the given job keys. interval_mapping = {
""" "DAY": "DAILY",
url = "https://apis.indeed.com/graphql" "YEAR": "YEARLY",
headers = { "HOUR": "HOURLY",
'Host': 'apis.indeed.com', "WEEK": "WEEKLY",
'content-type': 'application/json', "MONTH": "MONTHLY",
'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',
'indeed-co': 'US',
} }
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}")
job_keys_gql = '[' + ', '.join(f'"{key}"' for key in job_keys) + ']' api_headers = {
"Host": "apis.indeed.com",
payload = { "content-type": "application/json",
"query": f""" "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 {{ query GetJobData {{
jobData(input: {{ jobSearch(
jobKeys: {job_keys_gql} {what}
}}) {{ {location}
includeSponsoredResults: NONE
limit: 100
sort: DATE
{cursor}
{filters}
) {{
pageInfo {{
nextCursor
}}
results {{ results {{
trackingKey
job {{ job {{
key key
title title
datePublished
dateOnIndeed
description {{ description {{
html html
}} }}
location {{ location {{
countryName countryName
countryCode countryCode
admin1Code
city city
postalCode postalCode
streetAddress streetAddress
@@ -398,10 +398,30 @@ class IndeedScraper(Scraper):
currencyCode currencyCode
}} }}
attributes {{ attributes {{
key
label label
}} }}
employer {{ employer {{
relativeCompanyPageUrl relativeCompanyPageUrl
name
dossier {{
employerDetails {{
addresses
industry
employeesLocalizedLabel
revenueLocalizedLabel
briefDescription
ceoName
ceoPhotoUrl
}}
images {{
headerImageUrl
squareLogoUrl
}}
links {{
corporateWebsite
}}
}}
}} }}
recruit {{ recruit {{
viewJobUrl viewJobUrl
@@ -413,24 +433,3 @@ 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}")

View File

@@ -4,13 +4,16 @@ jobspy.scrapers.linkedin
This module contains routines to scrape LinkedIn. This module contains routines to scrape LinkedIn.
""" """
from __future__ import annotations
import time import time
import random import random
import regex as re
import urllib.parse
from typing import Optional from typing import Optional
from datetime import datetime from datetime import datetime
import requests
from requests.exceptions import ProxyError
from threading import Lock from threading import Lock
from bs4.element import Tag from bs4.element import Tag
from bs4 import BeautifulSoup from bs4 import BeautifulSoup
@@ -25,27 +28,32 @@ from ...jobs import (
JobResponse, JobResponse,
JobType, JobType,
Country, Country,
Compensation Compensation,
DescriptionFormat,
) )
from ..utils import ( from ..utils import (
count_urgent_words, logger,
extract_emails_from_text, extract_emails_from_text,
get_enum_from_job_type, get_enum_from_job_type,
currency_parser currency_parser,
markdown_converter,
) )
class LinkedInScraper(Scraper): 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): def __init__(self, proxy: Optional[str] = None):
""" """
Initializes LinkedInScraper with the LinkedIn job search url 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.country = "worldwide"
self.url = "https://www.linkedin.com" self.job_url_direct_regex = re.compile(r'(?<=\?url=)[^"]+')
super().__init__(site, proxy=proxy)
def scrape(self, scraper_input: ScraperInput) -> JobResponse: def scrape(self, scraper_input: ScraperInput) -> JobResponse:
""" """
@@ -53,67 +61,68 @@ class LinkedInScraper(Scraper):
:param scraper_input: :param scraper_input:
:return: job_response :return: job_response
""" """
self.scraper_input = scraper_input
job_list: list[JobPost] = [] job_list: list[JobPost] = []
seen_urls = set() seen_urls = set()
url_lock = Lock() url_lock = Lock()
page = scraper_input.offset // 25 + 25 if scraper_input.offset else 0 page = scraper_input.offset // 25 + 25 if scraper_input.offset else 0
seconds_old = ( seconds_old = (
scraper_input.hours_old * 3600 scraper_input.hours_old * 3600 if scraper_input.hours_old else None
if scraper_input.hours_old )
else None continue_search = (
lambda: len(job_list) < scraper_input.results_wanted and page < 1000
) )
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(): while continue_search():
logger.info(f"LinkedIn search page: {page // 25 + 1}")
session = create_session(is_tls=False, has_retry=True, delay=5) session = create_session(is_tls=False, has_retry=True, delay=5)
params = { params = {
"keywords": scraper_input.search_term, "keywords": scraper_input.search_term,
"location": scraper_input.location, "location": scraper_input.location,
"distance": scraper_input.distance, "distance": scraper_input.distance,
"f_WT": 2 if scraper_input.is_remote else None, "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 if scraper_input.job_type
else None, else None
),
"pageNum": 0, "pageNum": 0,
"start": page + scraper_input.offset, "start": page + scraper_input.offset,
"f_AL": "true" if scraper_input.easy_apply else None, "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_C": (
"f_TPR": f"r{seconds_old}", ",".join(map(str, scraper_input.linkedin_company_ids))
if scraper_input.linkedin_company_ids
else None
),
} }
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} params = {k: v for k, v in params.items() if v is not None}
try: try:
response = session.get( response = session.get(
f"{self.url}/jobs-guest/jobs/api/seeMoreJobPostings/search?", f"{self.base_url}/jobs-guest/jobs/api/seeMoreJobPostings/search?",
params=params, params=params,
allow_redirects=True, allow_redirects=True,
proxies=self.proxy, proxies=self.proxy,
headers=self.headers(), headers=self.headers,
timeout=10, timeout=10,
) )
response.raise_for_status() if response.status_code not in range(200, 400):
if response.status_code == 429:
except requests.HTTPError as e: err = (
raise LinkedInException( f"429 Response - Blocked by LinkedIn for too many requests"
f"bad response status code: {e.response.status_code}"
) )
except ProxyError as e: else:
raise LinkedInException("bad proxy") err = f"LinkedIn response status code {response.status_code}"
err += f" - {response.text}"
logger.error(err)
return JobResponse(jobs=job_list)
except Exception as e: 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") soup = BeautifulSoup(response.text, "html.parser")
job_cards = soup.find_all("div", class_="base-search-card") job_cards = soup.find_all("div", class_="base-search-card")
@@ -126,30 +135,33 @@ class LinkedInScraper(Scraper):
if href_tag and "href" in href_tag.attrs: if href_tag and "href" in href_tag.attrs:
href = href_tag.attrs["href"].split("?")[0] href = href_tag.attrs["href"].split("?")[0]
job_id = href.split("-")[-1] 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: with url_lock:
if job_url in seen_urls: if job_url in seen_urls:
continue continue
seen_urls.add(job_url) seen_urls.add(job_url)
# Call process_job directly without threading
try: try:
job_post = self.process_job(job_card, job_url, scraper_input.full_description) fetch_desc = scraper_input.linkedin_fetch_description
job_post = self._process_job(job_card, job_url, fetch_desc)
if job_post: if job_post:
job_list.append(job_post) job_list.append(job_post)
if not continue_search():
break
except Exception as e: except Exception as e:
raise LinkedInException("Exception occurred while processing jobs") raise LinkedInException(str(e))
if continue_search(): if continue_search():
time.sleep(random.uniform(LinkedInScraper.DELAY, LinkedInScraper.DELAY + 2)) time.sleep(random.uniform(self.delay, self.delay + self.band_delay))
page += 25 page += self.jobs_per_page
job_list = job_list[: scraper_input.results_wanted] job_list = job_list[: scraper_input.results_wanted]
return JobResponse(jobs=job_list) return JobResponse(jobs=job_list)
def process_job(self, job_card: Tag, job_url: str, full_descr: bool) -> Optional[JobPost]: def _process_job(
salary_tag = job_card.find('span', class_='job-search-card__salary-info') 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 compensation = None
if salary_tag: if salary_tag:
@@ -178,26 +190,26 @@ class LinkedInScraper(Scraper):
company = company_a_tag.get_text(strip=True) if company_a_tag else "N/A" 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") 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 = ( datetime_tag = (
metadata_card.find("time", class_="job-search-card__listdate") metadata_card.find("time", class_="job-search-card__listdate")
if metadata_card if metadata_card
else None else None
) )
date_posted = description = job_type = None date_posted = None
if datetime_tag and "datetime" in datetime_tag.attrs: if datetime_tag and "datetime" in datetime_tag.attrs:
datetime_str = datetime_tag["datetime"] datetime_str = datetime_tag["datetime"]
try: try:
date_posted = datetime.strptime(datetime_str, "%Y-%m-%d") date_posted = datetime.strptime(datetime_str, "%Y-%m-%d")
except Exception as e: except:
date_posted = None date_posted = None
benefits_tag = job_card.find("span", class_="result-benefits__text") job_details = {}
benefits = " ".join(benefits_tag.get_text().split()) if benefits_tag else None
if full_descr: if full_descr:
description, job_type = self.get_job_description(job_url) job_details = self._get_job_details(job_url)
return JobPost( return JobPost(
id=self._get_id(job_url),
title=title, title=title,
company_name=company, company_name=company,
company_url=company_url, company_url=company_url,
@@ -205,31 +217,39 @@ class LinkedInScraper(Scraper):
date_posted=date_posted, date_posted=date_posted,
job_url=job_url, job_url=job_url,
compensation=compensation, compensation=compensation,
benefits=benefits, job_type=job_details.get("job_type"),
job_type=job_type, description=job_details.get("description"),
description=description, job_url_direct=job_details.get("job_url_direct"),
emails=extract_emails_from_text(description) if description else None, emails=extract_emails_from_text(job_details.get("description")),
num_urgent_words=count_urgent_words(description) if description else None, logo_photo_url=job_details.get("logo_photo_url"),
) )
def get_job_description( def _get_id(self, url: str):
self, job_page_url: str
) -> tuple[None, None] | tuple[str | None, tuple[str | None, JobType | None]]:
""" """
Retrieves job description by going to the job page url Extracts the job id from the job url
:param url:
:return: str
"""
if not url:
return None
return url.split("/")[-1]
def _get_job_details(self, job_page_url: str) -> dict:
"""
Retrieves job description and other job details by going to the job page url
:param job_page_url: :param job_page_url:
:return: description or None :return: dict
""" """
try: try:
session = create_session(is_tls=False, has_retry=True) 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() response.raise_for_status()
except requests.HTTPError as e: except:
return None, None return {}
except Exception as e:
return None, None
if response.url == "https://www.linkedin.com/signup": if response.url == "https://www.linkedin.com/signup":
return None, None return {}
soup = BeautifulSoup(response.text, "html.parser") soup = BeautifulSoup(response.text, "html.parser")
div_content = soup.find( div_content = soup.find(
@@ -237,6 +257,7 @@ class LinkedInScraper(Scraper):
) )
description = None description = None
if div_content is not None: if div_content is not None:
def remove_attributes(tag): def remove_attributes(tag):
for attr in list(tag.attrs): for attr in list(tag.attrs):
del tag[attr] del tag[attr]
@@ -244,37 +265,18 @@ class LinkedInScraper(Scraper):
div_content = remove_attributes(div_content) div_content = remove_attributes(div_content)
description = div_content.prettify(formatter="html") description = div_content.prettify(formatter="html")
if self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
description = markdown_converter(description)
return {
"description": description,
"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"
),
}
def get_job_type( def _get_location(self, metadata_card: Optional[Tag]) -> Location:
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:
""" """
Extracts the location data from the job metadata card. Extracts the location data from the job metadata card.
:param metadata_card :param metadata_card
@@ -296,28 +298,67 @@ class LinkedInScraper(Scraper):
) )
elif len(parts) == 3: elif len(parts) == 3:
city, state, country = parts city, state, country = parts
location = Location( country = Country.from_string(country)
city=city, location = Location(city=city, state=state, country=country)
state=state,
country=Country.from_string(country),
)
return location return location
@staticmethod @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 []
def _parse_job_url_direct(self, soup: BeautifulSoup) -> str | None:
"""
Gets the job url direct from job page
:param soup:
:return: str
"""
job_url_direct = None
job_url_direct_content = soup.find("code", id="applyUrl")
if job_url_direct_content:
job_url_direct_match = self.job_url_direct_regex.search(
job_url_direct_content.decode_contents().strip()
)
if job_url_direct_match:
job_url_direct = urllib.parse.unquote(job_url_direct_match.group())
return job_url_direct
@staticmethod
def job_type_code(job_type_enum: JobType) -> str:
return { 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", "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": "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", "accept-language": "en-US,en;q=0.9",
"cache-control": "max-age=0", "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", "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", "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

@@ -1,35 +1,48 @@
from __future__ import annotations
import re import re
import logging import logging
import numpy as np
import tls_client
import requests import requests
import tls_client
import numpy as np
from markdownify import markdownify as md
from requests.adapters import HTTPAdapter, Retry from requests.adapters import HTTPAdapter, Retry
from ..jobs import JobType from ..jobs import JobType
logger = logging.getLogger("JobSpy") logger = logging.getLogger("JobSpy")
logger.propagate = False
if not logger.handlers: if not logger.handlers:
logger.setLevel(logging.ERROR) logger.setLevel(logging.INFO)
console_handler = logging.StreamHandler() console_handler = logging.StreamHandler()
console_handler.setLevel(logging.ERROR) format = "%(asctime)s - %(name)s - %(levelname)s - %(message)s"
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s') formatter = logging.Formatter(format)
console_handler.setFormatter(formatter) console_handler.setFormatter(formatter)
logger.addHandler(console_handler) logger.addHandler(console_handler)
def count_urgent_words(description: str) -> int: def set_logger_level(verbose: int = 2):
""" """
Count the number of urgent words or phrases in a job description. Adjusts the logger's level. This function allows the logging level to be changed at runtime.
"""
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 Parameters:
- verbose: int {0, 1, 2} (default=2, all logs)
"""
if verbose is None:
return
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)
else:
raise ValueError(f"Invalid log level: {level_name}")
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: def extract_emails_from_text(text: str) -> list[str] | None:
@@ -39,17 +52,18 @@ def extract_emails_from_text(text: str) -> list[str] | None:
return email_regex.findall(text) return email_regex.findall(text)
def create_session(proxy: dict | None = None, is_tls: bool = True, has_retry: bool = False, delay: int = 1) -> requests.Session: 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. Creates a requests session with optional tls, proxy, and retry settings.
:return: A session object :return: A session object
""" """
if is_tls: if is_tls:
session = tls_client.Session( session = tls_client.Session(random_tls_extension_order=True)
client_identifier="chrome112",
random_tls_extension_order=True,
)
session.proxies = proxy session.proxies = proxy
else: else:
session = requests.Session() session = requests.Session()
@@ -57,16 +71,17 @@ def create_session(proxy: dict | None = None, is_tls: bool = True, has_retry: bo
if proxy: if proxy:
session.proxies.update(proxy) session.proxies.update(proxy)
if has_retry: if has_retry:
retries = Retry(total=3, retries = Retry(
total=3,
connect=3, connect=3,
status=3, status=3,
status_forcelist=[500, 502, 503, 504, 429], status_forcelist=[500, 502, 503, 504, 429],
backoff_factor=delay) backoff_factor=delay,
)
adapter = HTTPAdapter(max_retries=retries) adapter = HTTPAdapter(max_retries=retries)
session.mount('http://', adapter) session.mount("http://", adapter)
session.mount('https://', adapter) session.mount("https://", adapter)
return session return session
@@ -84,17 +99,15 @@ def get_enum_from_job_type(job_type_str: str) -> JobType | None:
def currency_parser(cur_str): def currency_parser(cur_str):
# Remove any non-numerical characters # Remove any non-numerical characters
# except for ',' '.' or '-' (e.g. EUR) # except for ',' '.' or '-' (e.g. EUR)
cur_str = re.sub("[^-0-9.,]", '', cur_str) cur_str = re.sub("[^-0-9.,]", "", cur_str)
# Remove any 000s separators (either , or .) # Remove any 000s separators (either , or .)
cur_str = re.sub("[.,]", '', cur_str[:-3]) + cur_str[-3:] cur_str = re.sub("[.,]", "", cur_str[:-3]) + cur_str[-3:]
if '.' in list(cur_str[-3:]): if "." in list(cur_str[-3:]):
num = float(cur_str) num = float(cur_str)
elif ',' in list(cur_str[-3:]): elif "," in list(cur_str[-3:]):
num = float(cur_str.replace(',', '.')) num = float(cur_str.replace(",", "."))
else: else:
num = float(cur_str) num = float(cur_str)
return np.round(num, 2) return np.round(num, 2)

View File

@@ -4,35 +4,80 @@ jobspy.scrapers.ziprecruiter
This module contains routines to scrape ZipRecruiter. This module contains routines to scrape ZipRecruiter.
""" """
from __future__ import annotations
import math import math
import time import time
from datetime import datetime, timezone from datetime import datetime
from typing import Optional, Tuple, Any from typing import Optional, Tuple, Any
from concurrent.futures import ThreadPoolExecutor from concurrent.futures import ThreadPoolExecutor
from .. import Scraper, ScraperInput, Site from .. import Scraper, ScraperInput, Site
from ..exceptions import ZipRecruiterException from ..utils import (
from ...jobs import JobPost, Compensation, Location, JobResponse, JobType, Country logger,
from ..utils import count_urgent_words, extract_emails_from_text, create_session extract_emails_from_text,
create_session,
markdown_converter,
)
from ...jobs import (
JobPost,
Compensation,
Location,
JobResponse,
JobType,
Country,
DescriptionFormat,
)
class ZipRecruiterScraper(Scraper): class ZipRecruiterScraper(Scraper):
base_url = "https://www.ziprecruiter.com"
api_url = "https://api.ziprecruiter.com"
def __init__(self, proxy: Optional[str] = None): def __init__(self, proxy: Optional[str] = None):
""" """
Initializes ZipRecruiterScraper with the ZipRecruiter job search url Initializes ZipRecruiterScraper with the ZipRecruiter job search url
""" """
site = Site(Site.ZIP_RECRUITER) self.scraper_input = None
self.url = "https://www.ziprecruiter.com"
self.session = create_session(proxy) self.session = create_session(proxy)
self.get_cookies() self._get_cookies()
super().__init__(site, proxy=proxy) super().__init__(Site.ZIP_RECRUITER, proxy=proxy)
self.delay = 5
self.jobs_per_page = 20 self.jobs_per_page = 20
self.seen_urls = set() 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 self, scraper_input: ScraperInput, continue_token: str | None = None
) -> Tuple[list[JobPost], Optional[str]]: ) -> Tuple[list[JobPost], Optional[str]]:
""" """
@@ -41,73 +86,54 @@ class ZipRecruiterScraper(Scraper):
:param continue_token: :param continue_token:
:return: jobs found on page :return: jobs found on page
""" """
params = self.add_params(scraper_input) jobs_list = []
params = self._add_params(scraper_input)
if continue_token: if continue_token:
params["continue_from"] = continue_token params["continue_from"] = continue_token
try: try:
response = self.session.get( res = self.session.get(
f"https://api.ziprecruiter.com/jobs-app/jobs", f"{self.api_url}/jobs-app/jobs", headers=self.headers, params=params
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:
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)
return jobs_list, ""
except Exception as e: except Exception as e:
if "Proxy responded with non 200 code" in str(e): if "Proxy responded with" in str(e):
raise ZipRecruiterException("bad proxy") logger.error(f"Indeed: Bad proxy")
raise ZipRecruiterException(str(e)) else:
logger.error(f"Indeed: {str(e)}")
response_data = response.json() return jobs_list, ""
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: 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))) job_list = list(filter(None, (result.result() for result in job_results)))
return job_list, next_continue_token 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. Processes an individual job dict from the response
:param scraper_input: Information about job search criteria.
:return: JobResponse containing a list of jobs.
""" """
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") 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: if job_url in self.seen_urls:
return return
self.seen_urls.add(job_url) self.seen_urls.add(job_url)
description = job.get("job_description", "").strip() 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") company = job.get("hiring_company", {}).get("name")
country_value = "usa" if job.get("job_country") == "US" else "canada" country_value = "usa" if job.get("job_country") == "US" else "canada"
country_enum = Country.from_string(country_value) country_enum = Country.from_string(country_value)
@@ -115,80 +141,66 @@ class ZipRecruiterScraper(Scraper):
location = Location( location = Location(
city=job.get("job_city"), state=job.get("job_state"), country=country_enum 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() job.get("employment_type", "").replace("_", "").lower()
) )
date_posted = datetime.fromisoformat(job['posted_time'].rstrip("Z")).date() date_posted = datetime.fromisoformat(job["posted_time"].rstrip("Z")).date()
comp_interval = job.get("compensation_interval")
comp_interval = "yearly" if comp_interval == "annual" else comp_interval
comp_min = int(job["compensation_min"]) if "compensation_min" in job else None
comp_max = int(job["compensation_max"]) if "compensation_max" in job else None
comp_currency = job.get("compensation_currency")
return JobPost( return JobPost(
id=str(job['listing_key']),
title=title, title=title,
company_name=company, company_name=company,
location=location, location=location,
job_type=job_type, job_type=job_type,
compensation=Compensation( compensation=Compensation(
interval="yearly" interval=comp_interval,
if job.get("compensation_interval") == "annual" min_amount=comp_min,
else job.get("compensation_interval"), max_amount=comp_max,
min_amount=int(job["compensation_min"]) currency=comp_currency,
if "compensation_min" in job
else None,
max_amount=int(job["compensation_max"])
if "compensation_max" in job
else None,
currency=job.get("compensation_currency"),
), ),
date_posted=date_posted, date_posted=date_posted,
job_url=job_url, job_url=job_url,
description=description, description=description,
emails=extract_emails_from_text(description) if description else None, 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): def _get_cookies(self):
url="https://api.ziprecruiter.com/jobs-app/event" 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"
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" url = f"{self.api_url}/jobs-app/event"
self.session.post(url, data=data, headers=ZipRecruiterScraper.headers()) self.session.post(url, data=data, headers=self.headers)
@staticmethod @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: for job_type in JobType:
if job_type_str in job_type.value: if job_type_str in job_type.value:
return [job_type] return [job_type]
return None return None
@staticmethod @staticmethod
def add_params(scraper_input) -> dict[str, str | Any]: def _add_params(scraper_input) -> dict[str, str | Any]:
params = { params = {
"search": scraper_input.search_term, "search": scraper_input.search_term,
"location": scraper_input.location, "location": scraper_input.location,
} }
if scraper_input.hours_old: if scraper_input.hours_old:
fromage = max(scraper_input.hours_old // 24, 1) if scraper_input.hours_old else None params["days"] = max(scraper_input.hours_old // 24, 1)
params['days'] = fromage job_type_map = {JobType.FULL_TIME: "full_time", JobType.PART_TIME: "part_time"}
job_type_map = {
JobType.FULL_TIME: 'full_time',
JobType.PART_TIME: 'part_time'
}
if scraper_input.job_type: if scraper_input.job_type:
params['employment_type'] = job_type_map[scraper_input.job_type] if scraper_input.job_type in job_type_map else scraper_input.job_type.value[0] job_type = scraper_input.job_type
params["employment_type"] = job_type_map.get(job_type, job_type.value[0])
if scraper_input.easy_apply: if scraper_input.easy_apply:
params['zipapply'] = 1 params["zipapply"] = 1
if scraper_input.is_remote: if scraper_input.is_remote:
params["remote"] = 1 params["remote"] = 1
if scraper_input.distance: if scraper_input.distance:
params["radius"] = 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} headers = {
return params
@staticmethod
def headers() -> dict:
"""
Returns headers needed for requests
:return: dict - Dictionary containing headers
"""
return {
"Host": "api.ziprecruiter.com", "Host": "api.ziprecruiter.com",
"accept": "*/*", "accept": "*/*",
"x-zr-zva-override": "100000000;vid:ZT1huzm_EQlDTVEc", "x-zr-zva-override": "100000000;vid:ZT1huzm_EQlDTVEc",