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14 Commits

Author SHA1 Message Date
Cullen Watson
aeb1a50d2c fix job type search (#106) 2024-02-12 11:02:48 -06:00
VitaminB16
91b137ef86 feat: Ability to query by time posted for linkedin, indeed, glassdoor, ziprecruiter (#103) 2024-02-09 14:02:03 -06:00
Cullen Watson
2563c5ca08 enh: Indeed company url (#104) 2024-02-09 12:05:10 -06:00
Cullen Watson
32282305c8 docs: readme 2024-02-08 18:13:19 -06:00
Cullen Watson
ccbea51f3c docs: readme 2024-02-04 09:25:10 -06:00
Cullen Watson
6ec7c24f7f enh(linkedin): search by company ids (#99) 2024-02-04 09:21:45 -06:00
Cullen Watson
02caf1b38d fix(zr): date posted (#98) 2024-02-03 07:20:53 -06:00
Cullen Watson
8e2ab277da fix(ziprecruiter): pagination (#97)
* fix(ziprecruiter): pagination

* chore: version
2024-02-02 20:48:28 -06:00
Cullen Watson
ce3bd84ee5 fix: indeed parse description bug (#96)
* fix(indeed): full descr

* chore: version
2024-02-02 18:21:55 -06:00
Cullen Watson
1ccf2290fe docs: readme 2024-02-02 17:59:24 -06:00
Cullen Watson
ec2eefc58a docs: readme 2024-02-02 17:58:15 -06:00
Cullen Watson
13c7694474 Easy apply (#95)
* enh(glassdoor): easy apply filter

* enh(ziprecruiter): easy apply

* enh(indeed): use mobile headers

* chore: version
2024-02-02 17:47:15 -06:00
Cullen Watson
bbe46fe3f4 enh(glassdoor): easy apply filter (#92) 2024-02-01 19:42:24 -06:00
Cullen Watson
b97c73ffd6 fix: clean description (#88) 2024-01-28 21:50:41 -06:00
11 changed files with 591 additions and 316 deletions

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@@ -29,18 +29,20 @@ _Python version >= [3.10](https://www.python.org/downloads/release/python-3100/)
### Usage ### Usage
```python ```python
import csv
from jobspy import scrape_jobs from jobspy import scrape_jobs
jobs = scrape_jobs( jobs = scrape_jobs(
site_name=["indeed", "linkedin", "zip_recruiter", "glassdoor"], site_name=["indeed", "linkedin", "zip_recruiter", "glassdoor"],
search_term="software engineer", search_term="software engineer",
location="Dallas, TX", location="Dallas, TX",
results_wanted=10, results_wanted=20,
hours_old=72, # (only linkedin 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
) )
print(f"Found {len(jobs)} jobs") print(f"Found {len(jobs)} jobs")
print(jobs.head()) print(jobs.head())
jobs.to_csv("jobs.csv", index=False) # to_xlsx jobs.to_csv("jobs.csv", quoting=csv.QUOTE_NONNUMERIC, escapechar="\\", index=False) # to_xlsx
``` ```
### Output ### Output
@@ -67,11 +69,13 @@ Optional
├── job_type (enum): fulltime, parttime, internship, contract ├── job_type (enum): fulltime, parttime, internship, contract
├── proxy (str): in format 'http://user:pass@host:port' or [https, socks] ├── proxy (str): in format 'http://user:pass@host:port' or [https, socks]
├── is_remote (bool) ├── is_remote (bool)
├── full_description (bool): fetches full description for Indeed / LinkedIn (much slower) ├── full_description (bool): fetches full description for LinkedIn (slower)
├── results_wanted (int): number of job results to retrieve for each site specified in 'site_type' ├── 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 LinkedIn ├── easy_apply (bool): filters for jobs that are hosted on the job board site
├── linkedin_company_ids (list[int): searches for linkedin jobs with specific company ids
├── country_indeed (enum): filters the country on Indeed (see below for correct spelling) ├── country_indeed (enum): filters the country on Indeed (see below for correct spelling)
├── offset (num): starts the search from an offset (e.g. 25 will start the search from the 25th result) ├── offset (num): starts the search from an offset (e.g. 25 will start the search from the 25th result)
├── hours_old (int): filters jobs by the number of hours since the job was posted (all but LinkedIn rounds up to next day)
``` ```
### JobPost Schema ### JobPost Schema
@@ -80,6 +84,7 @@ Optional
JobPost JobPost
├── title (str) ├── title (str)
├── company (str) ├── company (str)
├── company_url (str)
├── job_url (str) ├── job_url (str)
├── location (object) ├── location (object)
│ ├── country (str) │ ├── country (str)
@@ -158,16 +163,11 @@ persist, [submit an issue](https://github.com/Bunsly/JobSpy/issues).
**Q: Received a response code 429?** **Q: Received a response code 429?**
**A:** This indicates that you have been blocked by the job board site for sending too many requests. All of the job board sites are aggressive with blocking. We recommend: **A:** This indicates that you have been blocked by the job board site for sending too many requests. All of the job board sites are aggressive with blocking. We recommend:
- Waiting a few seconds between requests. - Waiting some time between scrapes (site-dependent).
- Trying a VPN or proxy to change your IP address. - Trying a VPN or proxy to change your IP address.
--- ---
**Q: Experiencing a "Segmentation fault: 11" on macOS Catalina?**
**A:** This is due to `tls_client` dependency not supporting your architecture. Solutions and workarounds include:
- Upgrade to a newer version of MacOS
- Reach out to the maintainers of [tls_client](https://github.com/bogdanfinn/tls-client) for fixes

18
poetry.lock generated
View File

@@ -1053,16 +1053,6 @@ files = [
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{file = "MarkupSafe-2.1.3-cp311-cp311-win32.whl", hash = "sha256:dd15ff04ffd7e05ffcb7fe79f1b98041b8ea30ae9234aed2a9168b5797c3effb"}, {file = "MarkupSafe-2.1.3-cp311-cp311-win32.whl", hash = "sha256:dd15ff04ffd7e05ffcb7fe79f1b98041b8ea30ae9234aed2a9168b5797c3effb"},
{file = "MarkupSafe-2.1.3-cp311-cp311-win_amd64.whl", hash = "sha256:134da1eca9ec0ae528110ccc9e48041e0828d79f24121a1a146161103c76e686"}, {file = "MarkupSafe-2.1.3-cp311-cp311-win_amd64.whl", hash = "sha256:134da1eca9ec0ae528110ccc9e48041e0828d79f24121a1a146161103c76e686"},
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@@ -2270,13 +2260,13 @@ test = ["flake8", "isort", "pytest"]
[[package]] [[package]]
name = "tls-client" name = "tls-client"
version = "0.2.1" version = "1.0"
description = "Advanced Python HTTP Client." description = "Advanced Python HTTP Client."
optional = false optional = false
python-versions = "*" python-versions = "*"
files = [ files = [
{file = "tls_client-0.2.1-py3-none-any.whl", hash = "sha256:124a710952b979d5e20b4e2b7879b7958d6e48a259d0f5b83101055eb173f0bd"}, {file = "tls_client-1.0-py3-none-any.whl", hash = "sha256:f1183f5e18cb31914bd62d11b350a33ea0293ea80fb91d69a3072821dece3e66"},
{file = "tls_client-0.2.1.tar.gz", hash = "sha256:473fb4c671d9d4ca6b818548ab6e955640dd589767bfce520830c5618c2f2e2b"}, {file = "tls_client-1.0.tar.gz", hash = "sha256:7f6de48ad4a0ef69b72682c76ce604155971e07b4bfb2148a36276194ae3e7a0"},
] ]
[[package]] [[package]]
@@ -2445,4 +2435,4 @@ files = [
[metadata] [metadata]
lock-version = "2.0" lock-version = "2.0"
python-versions = "^3.10" python-versions = "^3.10"
content-hash = "f966f3979873eec2c3b13460067f5aa414c69aa8ab5cd3239c1cfa564fcb5deb" content-hash = "404a77d78066cbb2ef71015562baf44aa11d12aac29a191c1ccc7758bfda598a"

View File

@@ -1,6 +1,6 @@
[tool.poetry] [tool.poetry]
name = "python-jobspy" name = "python-jobspy"
version = "1.1.35" version = "1.1.44"
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"
@@ -13,7 +13,7 @@ packages = [
[tool.poetry.dependencies] [tool.poetry.dependencies]
python = "^3.10" python = "^3.10"
requests = "^2.31.0" requests = "^2.31.0"
tls-client = "^0.2.1" 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"

View File

@@ -1,7 +1,6 @@
import pandas as pd import pandas as pd
import concurrent.futures from typing import Tuple
from concurrent.futures import ThreadPoolExecutor from concurrent.futures import ThreadPoolExecutor, as_completed
from typing import Tuple, Optional
from .jobs import JobType, Location from .jobs import JobType, Location
from .scrapers.indeed import IndeedScraper from .scrapers.indeed import IndeedScraper
@@ -29,19 +28,22 @@ def _map_str_to_site(site_name: str) -> Site:
def scrape_jobs( def scrape_jobs(
site_name: str | list[str] | Site | list[Site], site_name: str | list[str] | Site | list[Site] | None = None,
search_term: str, search_term: str | None = None,
location: str = "", location: str | None = None,
distance: int = None, distance: int | None = None,
is_remote: bool = False, is_remote: bool = False,
job_type: str = None, job_type: str | None = None,
easy_apply: bool = False, # linkedin easy_apply: bool | None = None,
results_wanted: int = 15, results_wanted: int = 15,
country_indeed: str = "usa", country_indeed: str = "usa",
hyperlinks: bool = False, hyperlinks: bool = False,
proxy: Optional[str] = None, proxy: str | None = None,
full_description: Optional[bool] = False, full_description: bool | None = False,
offset: Optional[int] = 0, linkedin_company_ids: list[int] | None = None,
offset: int | None = 0,
hours_old: int = None,
**kwargs,
) -> pd.DataFrame: ) -> pd.DataFrame:
""" """
Simultaneously scrapes job data from multiple job sites. Simultaneously scrapes job data from multiple job sites.
@@ -56,18 +58,23 @@ def scrape_jobs(
job_type = get_enum_from_value(job_type) if job_type else None job_type = get_enum_from_value(job_type) if job_type else None
if type(site_name) == str: def get_site_type():
site_type = [_map_str_to_site(site_name)] site_types = list(Site)
else: #: if type(site_name) == list if isinstance(site_name, str):
site_type = [ site_types = [_map_str_to_site(site_name)]
_map_str_to_site(site) if type(site) == str else site_name elif isinstance(site_name, Site):
for site in site_name site_types = [site_name]
] elif isinstance(site_name, list):
site_types = [
_map_str_to_site(site) if isinstance(site, str) else site
for site in site_name
]
return site_types
country_enum = Country.from_string(country_indeed) country_enum = Country.from_string(country_indeed)
scraper_input = ScraperInput( scraper_input = ScraperInput(
site_type=site_type, site_type=get_site_type(),
country=country_enum, country=country_enum,
search_term=search_term, search_term=search_term,
location=location, location=location,
@@ -77,7 +84,9 @@ def scrape_jobs(
easy_apply=easy_apply, easy_apply=easy_apply,
full_description=full_description, full_description=full_description,
results_wanted=results_wanted, results_wanted=results_wanted,
linkedin_company_ids=linkedin_company_ids,
offset=offset, offset=offset,
hours_old=hours_old
) )
def scrape_site(site: Site) -> Tuple[str, JobResponse]: def scrape_site(site: Site) -> Tuple[str, JobResponse]:
@@ -112,7 +121,7 @@ def scrape_jobs(
executor.submit(worker, site): site for site in scraper_input.site_type executor.submit(worker, site): site for site in scraper_input.site_type
} }
for future in concurrent.futures.as_completed(future_to_site): for future in as_completed(future_to_site):
site_value, scraped_data = future.result() site_value, scraped_data = future.result()
site_to_jobs_dict[site_value] = scraped_data site_to_jobs_dict[site_value] = scraped_data
@@ -183,4 +192,4 @@ def scrape_jobs(
else: else:
jobs_formatted_df = pd.DataFrame() jobs_formatted_df = pd.DataFrame()
return jobs_formatted_df return jobs_formatted_df.sort_values(by=['site', 'date_posted'], ascending=[True, False])

View File

@@ -1,7 +1,7 @@
from typing import Union, Optional from typing import Optional
from datetime import date from datetime import date
from enum import Enum from enum import Enum
from pydantic import BaseModel, validator from pydantic import BaseModel
class JobType(Enum): class JobType(Enum):
@@ -193,13 +193,20 @@ class CompensationInterval(Enum):
@classmethod @classmethod
def get_interval(cls, pay_period): def get_interval(cls, pay_period):
return cls[pay_period].value if pay_period in cls.__members__ else None interval_mapping = {
"YEAR": cls.YEARLY,
"HOUR": cls.HOURLY,
}
if pay_period in interval_mapping:
return interval_mapping[pay_period].value
else:
return cls[pay_period].value if pay_period in cls.__members__ else None
class Compensation(BaseModel): class Compensation(BaseModel):
interval: Optional[CompensationInterval] = None interval: Optional[CompensationInterval] = None
min_amount: int | None = None min_amount: float | None = None
max_amount: int | None = None max_amount: float | None = None
currency: Optional[str] = "USD" currency: Optional[str] = "USD"

View File

@@ -1,5 +1,4 @@
from ..jobs import Enum, BaseModel, JobType, JobResponse, Country from ..jobs import Enum, BaseModel, JobType, JobResponse, Country
from typing import List, Optional, Any
class Site(Enum): class Site(Enum):
@@ -10,25 +9,26 @@ class Site(Enum):
class ScraperInput(BaseModel): class ScraperInput(BaseModel):
site_type: List[Site] site_type: list[Site]
search_term: str search_term: str | None = None
location: str = None location: str | None = None
country: Optional[Country] = Country.USA country: Country | None = Country.USA
distance: Optional[int] = None distance: int | None = None
is_remote: bool = False is_remote: bool = False
job_type: Optional[JobType] = None job_type: JobType | None = None
easy_apply: bool = None # linkedin easy_apply: bool | None = None
full_description: bool = False full_description: bool = False
offset: int = 0 offset: int = 0
linkedin_company_ids: list[int] | None = None
results_wanted: int = 15 results_wanted: int = 15
hours_old: int | None = None
class Scraper: class Scraper:
def __init__(self, site: Site, proxy: Optional[List[str]] = 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)
def scrape(self, scraper_input: ScraperInput) -> JobResponse: def scrape(self, scraper_input: ScraperInput) -> JobResponse: ...
...

View File

@@ -6,7 +6,6 @@ This module contains routines to scrape Glassdoor.
""" """
import json import json
import requests import requests
from bs4 import BeautifulSoup
from typing import Optional from typing import Optional
from datetime import datetime, timedelta from datetime import datetime, timedelta
from concurrent.futures import ThreadPoolExecutor, as_completed from concurrent.futures import ThreadPoolExecutor, as_completed
@@ -35,6 +34,7 @@ class GlassdoorScraper(Scraper):
self.url = None self.url = None
self.country = None self.country = None
self.session = None
self.jobs_per_page = 30 self.jobs_per_page = 30
self.seen_urls = set() self.seen_urls = set()
@@ -53,8 +53,7 @@ class GlassdoorScraper(Scraper):
payload = self.add_payload( payload = self.add_payload(
scraper_input, location_id, location_type, page_num, cursor scraper_input, location_id, location_type, page_num, cursor
) )
session = create_session(self.proxy, is_tls=False, has_retry=True) response = self.session.post(
response = session.post(
f"{self.url}/graph", headers=self.headers(), timeout=10, data=payload f"{self.url}/graph", headers=self.headers(), timeout=10, data=payload
) )
if response.status_code != 200: if response.status_code != 200:
@@ -73,7 +72,6 @@ class GlassdoorScraper(Scraper):
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):
job_data = future_to_job_data[future]
try: try:
job_post = future.result() job_post = future.result()
if job_post: if job_post:
@@ -88,18 +86,19 @@ class GlassdoorScraper(Scraper):
def process_job(self, job_data): def process_job(self, job_data):
"""Processes a single job and fetches its description.""" """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/?jl={job_id}' job_url = f'{self.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']
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 else None date_posted = (datetime.now() - timedelta(days=age_in_days)).date() if age_in_days is not None else None
if location_type == "S": if location_type == "S":
is_remote = True is_remote = True
@@ -110,11 +109,12 @@ class GlassdoorScraper(Scraper):
try: try:
description = self.fetch_job_description(job_id) description = self.fetch_job_description(job_id)
except Exception as e : except:
description = None description = None
job_post = JobPost( job_post = JobPost(
title=title, title=title,
company_url=f"{self.url}Overview/W-EI_IE{company_id}.htm" 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,
@@ -143,6 +143,8 @@ class GlassdoorScraper(Scraper):
all_jobs: list[JobPost] = [] all_jobs: list[JobPost] = []
cursor = None cursor = None
max_pages = 30 max_pages = 30
self.session = create_session(self.proxy, is_tls=False, has_retry=True)
self.session.get(self.url)
try: try:
for page in range( for page in range(
@@ -199,10 +201,7 @@ class GlassdoorScraper(Scraper):
return None return None
data = response.json()[0] data = response.json()[0]
desc = data['data']['jobview']['job']['description'] desc = data['data']['jobview']['job']['description']
soup = BeautifulSoup(desc, 'html.parser') return desc
description = soup.get_text(separator='\n')
return description
@staticmethod @staticmethod
def parse_compensation(data: dict) -> Optional[Compensation]: def parse_compensation(data: dict) -> Optional[Compensation]:
@@ -246,6 +245,8 @@ class GlassdoorScraper(Scraper):
location_type = "CITY" location_type = "CITY"
elif location_type == "S": elif location_type == "S":
location_type = "STATE" location_type = "STATE"
elif location_type == 'N':
location_type = "COUNTRY"
return int(items[0]["locationId"]), location_type return int(items[0]["locationId"]), location_type
@staticmethod @staticmethod
@@ -256,11 +257,18 @@ class GlassdoorScraper(Scraper):
page_num: int, page_num: int,
cursor: str | None = None, cursor: str | None = None,
) -> str: ) -> str:
# `fromage` is the posting time filter in days
fromage = max(scraper_input.hours_old // 24, 1) if scraper_input.hours_old else None
filter_params = []
if scraper_input.easy_apply:
filter_params.append({"filterKey": "applicationType", "values": "1"})
if fromage:
filter_params.append({"filterKey": "fromAge", "values": str(fromage)})
payload = { payload = {
"operationName": "JobSearchResultsQuery", "operationName": "JobSearchResultsQuery",
"variables": { "variables": {
"excludeJobListingIds": [], "excludeJobListingIds": [],
"filterParams": [], "filterParams": filter_params,
"keyword": scraper_input.search_term, "keyword": scraper_input.search_term,
"numJobsToShow": 30, "numJobsToShow": 30,
"locationType": location_type, "locationType": location_type,
@@ -268,22 +276,180 @@ class GlassdoorScraper(Scraper):
"parameterUrlInput": f"IL.0,12_I{location_type}{location_id}", "parameterUrlInput": f"IL.0,12_I{location_type}{location_id}",
"pageNumber": page_num, "pageNumber": page_num,
"pageCursor": cursor, "pageCursor": cursor,
"fromage": fromage,
"sort": "date"
}, },
"query": "query JobSearchResultsQuery($excludeJobListingIds: [Long!], $keyword: String, $locationId: Int, $locationType: LocationTypeEnum, $numJobsToShow: Int!, $pageCursor: String, $pageNumber: Int, $filterParams: [FilterParams], $originalPageUrl: String, $seoFriendlyUrlInput: String, $parameterUrlInput: String, $seoUrl: Boolean) {\n jobListings(\n contextHolder: {searchParams: {excludeJobListingIds: $excludeJobListingIds, keyword: $keyword, locationId: $locationId, locationType: $locationType, numPerPage: $numJobsToShow, pageCursor: $pageCursor, pageNumber: $pageNumber, filterParams: $filterParams, originalPageUrl: $originalPageUrl, seoFriendlyUrlInput: $seoFriendlyUrlInput, parameterUrlInput: $parameterUrlInput, seoUrl: $seoUrl, searchType: SR}}\n ) {\n companyFilterOptions {\n id\n shortName\n __typename\n }\n filterOptions\n indeedCtk\n jobListings {\n ...JobView\n __typename\n }\n jobListingSeoLinks {\n linkItems {\n position\n url\n __typename\n }\n __typename\n }\n jobSearchTrackingKey\n jobsPageSeoData {\n pageMetaDescription\n pageTitle\n __typename\n }\n paginationCursors {\n cursor\n pageNumber\n __typename\n }\n indexablePageForSeo\n searchResultsMetadata {\n searchCriteria {\n implicitLocation {\n id\n localizedDisplayName\n type\n __typename\n }\n keyword\n location {\n id\n shortName\n localizedShortName\n localizedDisplayName\n type\n __typename\n }\n __typename\n }\n footerVO {\n countryMenu {\n childNavigationLinks {\n id\n link\n textKey\n __typename\n }\n __typename\n }\n __typename\n }\n helpCenterDomain\n helpCenterLocale\n jobAlert {\n jobAlertExists\n __typename\n }\n jobSerpFaq {\n questions {\n answer\n question\n __typename\n }\n __typename\n }\n jobSerpJobOutlook {\n occupation\n paragraph\n __typename\n }\n showMachineReadableJobs\n __typename\n }\n serpSeoLinksVO {\n relatedJobTitlesResults\n searchedJobTitle\n searchedKeyword\n searchedLocationIdAsString\n searchedLocationSeoName\n searchedLocationType\n topCityIdsToNameResults {\n key\n value\n __typename\n }\n topEmployerIdsToNameResults {\n key\n value\n __typename\n }\n topEmployerNameResults\n topOccupationResults\n __typename\n }\n totalJobsCount\n __typename\n }\n}\n\nfragment JobView on JobListingSearchResult {\n jobview {\n header {\n adOrderId\n advertiserType\n adOrderSponsorshipLevel\n ageInDays\n divisionEmployerName\n easyApply\n employer {\n id\n name\n shortName\n __typename\n }\n employerNameFromSearch\n goc\n gocConfidence\n gocId\n jobCountryId\n jobLink\n jobResultTrackingKey\n jobTitleText\n locationName\n locationType\n locId\n needsCommission\n payCurrency\n payPeriod\n payPeriodAdjustedPay {\n p10\n p50\n p90\n __typename\n }\n rating\n salarySource\n savedJobId\n sponsored\n __typename\n }\n job {\n descriptionFragments\n importConfigId\n jobTitleId\n jobTitleText\n listingId\n __typename\n }\n jobListingAdminDetails {\n cpcVal\n importConfigId\n jobListingId\n jobSourceId\n userEligibleForAdminJobDetails\n __typename\n }\n overview {\n shortName\n squareLogoUrl\n __typename\n }\n __typename\n }\n __typename\n}\n", "query": """
query JobSearchResultsQuery(
$excludeJobListingIds: [Long!],
$keyword: String,
$locationId: Int,
$locationType: LocationTypeEnum,
$numJobsToShow: Int!,
$pageCursor: String,
$pageNumber: Int,
$filterParams: [FilterParams],
$originalPageUrl: String,
$seoFriendlyUrlInput: String,
$parameterUrlInput: String,
$seoUrl: Boolean
) {
jobListings(
contextHolder: {
searchParams: {
excludeJobListingIds: $excludeJobListingIds,
keyword: $keyword,
locationId: $locationId,
locationType: $locationType,
numPerPage: $numJobsToShow,
pageCursor: $pageCursor,
pageNumber: $pageNumber,
filterParams: $filterParams,
originalPageUrl: $originalPageUrl,
seoFriendlyUrlInput: $seoFriendlyUrlInput,
parameterUrlInput: $parameterUrlInput,
seoUrl: $seoUrl,
searchType: SR
}
}
) {
companyFilterOptions {
id
shortName
__typename
}
filterOptions
indeedCtk
jobListings {
...JobView
__typename
}
jobListingSeoLinks {
linkItems {
position
url
__typename
}
__typename
}
jobSearchTrackingKey
jobsPageSeoData {
pageMetaDescription
pageTitle
__typename
}
paginationCursors {
cursor
pageNumber
__typename
}
indexablePageForSeo
searchResultsMetadata {
searchCriteria {
implicitLocation {
id
localizedDisplayName
type
__typename
}
keyword
location {
id
shortName
localizedShortName
localizedDisplayName
type
__typename
}
__typename
}
helpCenterDomain
helpCenterLocale
jobSerpJobOutlook {
occupation
paragraph
__typename
}
showMachineReadableJobs
__typename
}
totalJobsCount
__typename
}
}
fragment JobView on JobListingSearchResult {
jobview {
header {
adOrderId
advertiserType
adOrderSponsorshipLevel
ageInDays
divisionEmployerName
easyApply
employer {
id
name
shortName
__typename
}
employerNameFromSearch
goc
gocConfidence
gocId
jobCountryId
jobLink
jobResultTrackingKey
jobTitleText
locationName
locationType
locId
needsCommission
payCurrency
payPeriod
payPeriodAdjustedPay {
p10
p50
p90
__typename
}
rating
salarySource
savedJobId
sponsored
__typename
}
job {
description
importConfigId
jobTitleId
jobTitleText
listingId
__typename
}
jobListingAdminDetails {
cpcVal
importConfigId
jobListingId
jobSourceId
userEligibleForAdminJobDetails
__typename
}
overview {
shortName
squareLogoUrl
__typename
}
__typename
}
__typename
}
"""
} }
job_type_filters = { if scraper_input.job_type:
JobType.FULL_TIME: "fulltime",
JobType.PART_TIME: "parttime",
JobType.CONTRACT: "contract",
JobType.INTERNSHIP: "internship",
JobType.TEMPORARY: "temporary",
}
if scraper_input.job_type in job_type_filters:
filter_value = job_type_filters[scraper_input.job_type]
payload["variables"]["filterParams"].append( payload["variables"]["filterParams"].append(
{"filterKey": "jobType", "values": filter_value} {"filterKey": "jobType", "values": scraper_input.job_type.value[0]}
) )
return json.dumps([payload]) return json.dumps([payload])
@@ -292,12 +458,11 @@ class GlassdoorScraper(Scraper):
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
@staticmethod @staticmethod
def parse_location(location_name: str) -> Location: def parse_location(location_name: str) -> Location | None:
if not location_name or location_name == "Remote": if not location_name or location_name == "Remote":
return None return
city, _, state = location_name.partition(", ") city, _, state = location_name.partition(", ")
return Location(city=city, state=state) return Location(city=city, state=state)
@@ -306,7 +471,6 @@ class GlassdoorScraper(Scraper):
for cursor_data in pagination_cursors: for cursor_data in pagination_cursors:
if cursor_data["pageNumber"] == page_num: if cursor_data["pageNumber"] == page_num:
return cursor_data["cursor"] return cursor_data["cursor"]
return None
@staticmethod @staticmethod
def headers() -> dict: def headers() -> dict:
@@ -321,7 +485,6 @@ class GlassdoorScraper(Scraper):
"apollographql-client-name": "job-search-next", "apollographql-client-name": "job-search-next",
"apollographql-client-version": "4.65.5", "apollographql-client-version": "4.65.5",
"content-type": "application/json", "content-type": "application/json",
"cookie": 'gdId=91e2dfc4-c8b5-4fa7-83d0-11512b80262c; G_ENABLED_IDPS=google; trs=https%3A%2F%2Fwww.redhat.com%2F:referral:referral:2023-07-05+09%3A50%3A14.862:undefined:undefined; g_state={"i_p":1688587331651,"i_l":1}; _cfuvid=.7llazxhYFZWi6EISSPdVjtqF0NMVwzxr_E.cB1jgLs-1697828392979-0-604800000; GSESSIONID=undefined; JSESSIONID=F03DD1B5EE02DB6D842FE42B142F88F3; cass=1; jobsClicked=true; indeedCtk=1hd77b301k79i801; asst=1697829114.2; G_AUTHUSER_H=0; uc=8013A8318C98C517FE6DD0024636DFDEF978FC33266D93A2FAFEF364EACA608949D8B8FA2DC243D62DE271D733EB189D809ABE5B08D7B1AE865D217BD4EEBB97C282F5DA5FEFE79C937E3F6110B2A3A0ADBBA3B4B6DF5A996FEE00516100A65FCB11DA26817BE8D1C1BF6CFE36B5B68A3FDC2CFEC83AB797F7841FBB157C202332FC7E077B56BD39B167BDF3D9866E3B; AWSALB=zxc/Yk1nbWXXT6HjNyn3H4h4950ckVsFV/zOrq5LSoChYLE1qV+hDI8Axi3fUa9rlskndcO0M+Fw+ZnJ+AQ2afBFpyOd1acouLMYgkbEpqpQaWhY6/Gv4QH1zBcJ; AWSALBCORS=zxc/Yk1nbWXXT6HjNyn3H4h4950ckVsFV/zOrq5LSoChYLE1qV+hDI8Axi3fUa9rlskndcO0M+Fw+ZnJ+AQ2afBFpyOd1acouLMYgkbEpqpQaWhY6/Gv4QH1zBcJ; gdsid=1697828393025:1697830776351:668396EDB9E6A832022D34414128093D; at=HkH8Hnqi9uaMC7eu0okqyIwqp07ht9hBvE1_St7E_hRqPvkO9pUeJ1Jcpds4F3g6LL5ADaCNlxrPn0o6DumGMfog8qI1-zxaV_jpiFs3pugntw6WpVyYWdfioIZ1IDKupyteeLQEM1AO4zhGjY_rPZynpsiZBPO_B1au94sKv64rv23yvP56OiWKKfI-8_9hhLACEwWvM-Az7X-4aE2QdFt93VJbXbbGVf07bdDZfimsIkTtgJCLSRhU1V0kEM1Efyu66vo3m77gFFaMW7lxyYnb36I5PdDtEXBm3aL-zR7-qa5ywd94ISEivgqQOA4FPItNhqIlX4XrfD1lxVz6rfPaoTIDi4DI6UMCUjwyPsuv8mn0rYqDfRnmJpZ97fJ5AnhrknAd_6ZWN5v1OrxJczHzcXd8LO820QPoqxzzG13bmSTXLwGSxMUCtSrVsq05hicimQ3jpRt0c1dA4OkTNqF7_770B9JfcHcM8cr8-C4IL56dnOjr9KBGfN1Q2IvZM2cOBRbV7okiNOzKVZ3qJ24AE34WA2F3U6Whiu6H8nIuGG5hSNkVygY6CtglNZfFF9p8pJAZm79PngrrBv-CXFBZmhYLFo46lmFetDkiJ6mirtez4tKpzTIYjIp4_JAkiZFwbLJ2QGH4mK8kyyW0lZiX1DTuQec50N_5wvRo0Gt7nlKxzLsApMnaNhuQeH5ygh_pa381ORo9mQGi0EYF9zk00pa2--z4PtjfQ8KFq36GgpxKy5-o4qgqygZj8F01L8r-FiX2G4C7PREMIpAyHX2A4-_JxA1IS2j12EyqKTLqE9VcP06qm2Z-YuIW3ctmpMxy5G9_KiEiGv17weizhSFnl6SbpAEY-2VSmQ5V6jm3hoMp2jemkuGCRkZeFstLDEPxlzFN7WM; __cf_bm=zGaVjIJw4irf40_7UVw54B6Ohm271RUX4Tc8KVScrbs-1697830777-0-AYv2GnKTnnCU+cY9xHbJunO0DwlLDO6SIBnC/s/qldpKsGK0rRAjD6y8lbyATT/KlS7g29OZaN4fbd0lrJg0KmWbIybZIzfWVLHSYePVuOhu; asst=1697829114.2; at=dFhXf64wsf2TlnWy41xLs7skJkuxgKToEGcjGtDfUvW4oEAJ4tTIR5dKQ8wbwT75aIaGgdCfvcb-da7vwrCGWscCncmfLFQpJ9l-LLwoRfk-pMsxHhd77wvf-W7I0HSm7-Q5lQJqI9WyNGRxOa-RpzBTf4L8_Et4-3FzjPaAoYY5pY1FhuwXbN5asGOAMW-p8cjpbfn3PumlIYuckguWnjrcY2F31YJ_1noeoHM9tCGpymANbqGXRkG6aXY7yCfVXtdgZU1K5SMeaSPZIuF_iLUxjc_corzpNiH6qq7BIAmh-e5Aa-g7cwpZcln1fmwTVw4uTMZf1eLIMTa9WzgqZNkvG-sGaq_XxKA_Wai6xTTkOHfRgm4632Ba2963wdJvkGmUUa3tb_L4_wTgk3eFnHp5JhghLfT2Pe3KidP-yX__vx8JOsqe3fndCkKXgVz7xQKe1Dur-sMNlGwi4LXfguTT2YUI8C5Miq3pj2IHc7dC97eyyAiAM4HvyGWfaXWZcei6oIGrOwMvYgy0AcwFry6SIP2SxLT5TrxinRRuem1r1IcOTJsMJyUPp1QsZ7bOyq9G_0060B4CPyovw5523hEuqLTM-R5e5yavY6C_1DHUyE15C3mrh7kdvmlGZeflnHqkFTEKwwOftm-Mv-CKD5Db9ABFGNxKB2FH7nDH67hfOvm4tGNMzceBPKYJ3wciTt9jK3wy39_7cOYVywfrZ-oLhw_XtsbGSSeGn3HytrfgSADAh2sT0Gg6eCC9Xy1vh-Za337SVLUDXZ73W2xJxxUHBkFzZs8L_Xndo5DsbpWhVs9IYUGyraJdqB3SLgDbAppIBCJl4fx6_DG8-xOQPBvuFMlTROe1JVdHOzXI1GElwFDTuH1pjkg4I2G0NhAbE06Y-1illQE; gdsid=1697828393025:1697831731408:99C30D94108AC3030D61C736DDCDF11C',
"gd-csrf-token": "Ft6oHEWlRZrxDww95Cpazw:0pGUrkb2y3TyOpAIqF2vbPmUXoXVkD3oEGDVkvfeCerceQ5-n8mBg3BovySUIjmCPHCaW0H2nQVdqzbtsYqf4Q:wcqRqeegRUa9MVLJGyujVXB7vWFPjdaS1CtrrzJq-ok", "gd-csrf-token": "Ft6oHEWlRZrxDww95Cpazw:0pGUrkb2y3TyOpAIqF2vbPmUXoXVkD3oEGDVkvfeCerceQ5-n8mBg3BovySUIjmCPHCaW0H2nQVdqzbtsYqf4Q:wcqRqeegRUa9MVLJGyujVXB7vWFPjdaS1CtrrzJq-ok",
"origin": "https://www.glassdoor.com", "origin": "https://www.glassdoor.com",
"referer": "https://www.glassdoor.com/", "referer": "https://www.glassdoor.com/",

View File

@@ -6,11 +6,11 @@ This module contains routines to scrape Indeed.
""" """
import re import re
import math import math
import io
import json import json
import requests
from typing import Any
from datetime import datetime from datetime import datetime
import urllib.parse
from bs4 import BeautifulSoup from bs4 import BeautifulSoup
from bs4.element import Tag from bs4.element import Tag
from concurrent.futures import ThreadPoolExecutor, Future from concurrent.futures import ThreadPoolExecutor, Future
@@ -21,6 +21,7 @@ from ..utils import (
extract_emails_from_text, extract_emails_from_text,
create_session, create_session,
get_enum_from_job_type, get_enum_from_job_type,
logger
) )
from ...jobs import ( from ...jobs import (
JobPost, JobPost,
@@ -43,46 +44,29 @@ class IndeedScraper(Scraper):
site = Site(Site.INDEED) site = Site(Site.INDEED)
super().__init__(site, proxy=proxy) super().__init__(site, proxy=proxy)
self.jobs_per_page = 15 self.jobs_per_page = 25
self.seen_urls = set() self.seen_urls = set()
def scrape_page( def scrape_page(
self, scraper_input: ScraperInput, page: int self, scraper_input: ScraperInput, page: int
) -> tuple[list[JobPost], int]: ) -> list[JobPost]:
""" """
Scrapes a page of Indeed for jobs with scraper_input criteria Scrapes a page of Indeed for jobs with scraper_input criteria
:param scraper_input: :param scraper_input:
:param page: :param page:
:return: jobs found on page, total number of jobs found for search :return: jobs found on page, total number of jobs found for search
""" """
job_list = []
self.country = scraper_input.country self.country = scraper_input.country
domain = self.country.indeed_domain_value domain = self.country.indeed_domain_value
self.url = f"https://{domain}.indeed.com" self.url = f"https://{domain}.indeed.com"
params = {
"q": scraper_input.search_term,
"l": scraper_input.location,
"filter": 0,
"start": scraper_input.offset + page * 10,
"sort": "date"
}
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))
if sc_values:
params["sc"] = "0kf:" + "".join(sc_values) + ";"
try: try:
session = create_session(self.proxy) session = create_session(self.proxy)
response = session.get( response = session.get(
f"{self.url}/jobs", f"{self.url}/m/jobs",
headers=self.get_headers(), headers=self.get_headers(),
params=params, params=self.add_params(scraper_input, page),
allow_redirects=True, allow_redirects=True,
timeout_seconds=10, timeout_seconds=10,
) )
@@ -92,17 +76,18 @@ class IndeedScraper(Scraper):
) )
except Exception as e: except Exception as e:
if "Proxy responded with" in str(e): if "Proxy responded with" in str(e):
raise IndeedException("bad proxy") logger.error(f'Indeed: Bad proxy')
raise IndeedException(str(e)) else:
logger.error(f'Indeed: {str(e)}')
return job_list
soup = BeautifulSoup(response.content, "html.parser") soup = BeautifulSoup(response.content, "html.parser")
if "did not match any jobs" in response.text: if "did not match any jobs" in response.text:
raise IndeedException("Parsing exception: Search did not match any jobs") return job_list
jobs = IndeedScraper.parse_jobs( jobs = IndeedScraper.parse_jobs(
soup soup
) #: can raise exception, handled by main scrape function ) #: can raise exception, handled by main scrape function
total_num_jobs = IndeedScraper.total_jobs(soup)
if ( if (
not jobs.get("metaData", {}) not jobs.get("metaData", {})
@@ -111,74 +96,56 @@ class IndeedScraper(Scraper):
): ):
raise IndeedException("No jobs found.") raise IndeedException("No jobs found.")
def process_job(job) -> JobPost | None: def process_job(job: dict, job_detailed: dict) -> JobPost | None:
job_url = f'{self.url}/jobs/viewjob?jk={job["jobkey"]}' job_url = f'{self.url}/m/jobs/viewjob?jk={job["jobkey"]}'
job_url_client = f'{self.url}/viewjob?jk={job["jobkey"]}' job_url_client = f'{self.url}/viewjob?jk={job["jobkey"]}'
if job_url in self.seen_urls: if job_url in self.seen_urls:
return None return None
self.seen_urls.add(job_url)
description = job_detailed['description']['html']
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,
)
job_type = IndeedScraper.get_job_type(job) job_type = IndeedScraper.get_job_type(job)
timestamp_seconds = job["pubDate"] / 1000 timestamp_seconds = job["pubDate"] / 1000
date_posted = datetime.fromtimestamp(timestamp_seconds) date_posted = datetime.fromtimestamp(timestamp_seconds)
date_posted = date_posted.strftime("%Y-%m-%d") date_posted = date_posted.strftime("%Y-%m-%d")
description = self.get_description(job_url) if scraper_input.full_description else None
with io.StringIO(job["snippet"]) as f:
soup_io = BeautifulSoup(f, "html.parser")
li_elements = soup_io.find_all("li")
if description is None and li_elements:
description = " ".join(li.text for li in li_elements)
job_post = JobPost( job_post = JobPost(
title=job["normTitle"], title=job["normTitle"],
description=description, description=description,
company_name=job["company"], company_name=job["company"],
company_url=self.url + job["companyOverviewLink"] if "companyOverviewLink" in job else None, company_url=f"{self.url}{job_detailed['employer']['relativeCompanyPageUrl']}" if job_detailed['employer'] else None,
location=Location( location=Location(
city=job.get("jobLocationCity"), city=job.get("jobLocationCity"),
state=job.get("jobLocationState"), state=job.get("jobLocationState"),
country=self.country, country=self.country,
), ),
job_type=job_type, job_type=job_type,
compensation=compensation, compensation=self.get_compensation(job, job_detailed),
date_posted=date_posted, date_posted=date_posted,
job_url=job_url_client, job_url=job_url_client,
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) num_urgent_words=count_urgent_words(description)
if description if description
else None, else None,
is_remote=self.is_remote_job(job), is_remote=IndeedScraper.is_job_remote(job, job_detailed, description)
) )
return job_post return job_post
workers = 10
jobs = jobs["metaData"]["mosaicProviderJobCardsModel"]["results"] jobs = jobs["metaData"]["mosaicProviderJobCardsModel"]["results"]
with ThreadPoolExecutor(max_workers=1) as executor: 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] = [ job_results: list[Future] = [
executor.submit(process_job, job) for job in jobs 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()] job_list = [result.result() for result in job_results if result.result()]
return job_list, total_num_jobs return job_list
def scrape(self, scraper_input: ScraperInput) -> JobResponse: def scrape(self, scraper_input: ScraperInput) -> JobResponse:
""" """
@@ -186,70 +153,36 @@ class IndeedScraper(Scraper):
:param scraper_input: :param scraper_input:
:return: job_response :return: job_response
""" """
pages_to_process = ( job_list = self.scrape_page(scraper_input, 0)
math.ceil(scraper_input.results_wanted / self.jobs_per_page) - 1 pages_processed = 1
)
#: get first page to initialize session while len(self.seen_urls) < scraper_input.results_wanted:
job_list, total_results = self.scrape_page(scraper_input, 0) pages_to_process = math.ceil((scraper_input.results_wanted - len(self.seen_urls)) / self.jobs_per_page)
new_jobs = False
with ThreadPoolExecutor(max_workers=1) as executor: with ThreadPoolExecutor(max_workers=10) as executor:
futures: list[Future] = [ futures: list[Future] = [
executor.submit(self.scrape_page, scraper_input, page) executor.submit(self.scrape_page, scraper_input, page + pages_processed)
for page in range(1, pages_to_process + 1) for page in range(pages_to_process)
] ]
for future in futures: for future in futures:
jobs, _ = future.result() jobs = future.result()
if jobs:
job_list += jobs
new_jobs = True
if len(self.seen_urls) >= scraper_input.results_wanted:
break
job_list += jobs pages_processed += pages_to_process
if not new_jobs:
break
if len(job_list) > scraper_input.results_wanted:
job_list = job_list[: scraper_input.results_wanted]
job_response = JobResponse( if len(self.seen_urls) > scraper_input.results_wanted:
jobs=job_list, job_list = job_list[:scraper_input.results_wanted]
total_results=total_results,
)
return job_response
def get_description(self, job_page_url: str) -> str | None: return JobResponse(jobs=job_list)
"""
Retrieves job description by going to the job page url
:param job_page_url:
:return: description
"""
parsed_url = urllib.parse.urlparse(job_page_url)
params = urllib.parse.parse_qs(parsed_url.query)
jk_value = params.get("jk", [None])[0]
formatted_url = f"{self.url}/viewjob?jk={jk_value}&spa=1"
session = create_session(self.proxy)
try:
response = session.get(
formatted_url,
headers=self.get_headers(),
allow_redirects=True,
timeout_seconds=5,
)
except Exception as e:
return None
if response.status_code not in range(200, 400):
return None
try:
data = json.loads(response.text)
job_description = data["body"]["jobInfoWrapperModel"]["jobInfoModel"][
"sanitizedJobDescription"
]
except (KeyError, TypeError, IndexError):
return None
soup = BeautifulSoup(job_description, "html.parser")
text_content = "\n".join(soup.stripped_strings)
return text_content
@staticmethod @staticmethod
def get_job_type(job: dict) -> list[JobType] | None: def get_job_type(job: dict) -> list[JobType] | None:
@@ -270,6 +203,44 @@ class IndeedScraper(Scraper):
job_types.append(job_type) job_types.append(job_type)
return job_types return job_types
@staticmethod
def get_compensation(job: dict, job_detailed: dict) -> Compensation:
"""
Parses the job to get
:param job:
:param job_detailed:
:return: compensation object
"""
comp = job_detailed['compensation']['baseSalary']
if comp:
interval = IndeedScraper.get_correct_interval(comp['unitOfWork'])
if interval:
return Compensation(
interval=interval,
min_amount=round(comp['range'].get('min'), 2) if comp['range'].get('min') is not None else None,
max_amount=round(comp['range'].get('max'), 2) if comp['range'].get('max') is not None else None,
currency=job_detailed['compensation']['currencyCode']
)
extracted_salary = job.get("extractedSalary")
compensation = None
if extracted_salary:
salary_snippet = job.get("salarySnippet")
currency = salary_snippet.get("currency") if salary_snippet else None
interval = (extracted_salary.get("type"),)
if isinstance(interval, tuple):
interval = interval[0]
interval = interval.upper()
if interval in CompensationInterval.__members__:
compensation = Compensation(
interval=CompensationInterval[interval],
min_amount=int(extracted_salary.get("min")),
max_amount=int(extracted_salary.get("max")),
currency=currency,
)
return compensation
@staticmethod @staticmethod
def parse_jobs(soup: BeautifulSoup) -> dict: def parse_jobs(soup: BeautifulSoup) -> dict:
""" """
@@ -311,47 +282,155 @@ class IndeedScraper(Scraper):
"Could not find any results for the search" "Could not find any results for the search"
) )
@staticmethod
def total_jobs(soup: BeautifulSoup) -> int:
"""
Parses the total jobs for that search from soup object
:param soup:
:return: total_num_jobs
"""
script = soup.find("script", string=lambda t: t and "window._initialData" in t)
pattern = re.compile(r"window._initialData\s*=\s*({.*})\s*;", re.DOTALL)
match = pattern.search(script.string)
total_num_jobs = 0
if match:
json_str = match.group(1)
data = json.loads(json_str)
total_num_jobs = int(data["searchTitleBarModel"]["totalNumResults"])
return total_num_jobs
@staticmethod @staticmethod
def get_headers(): def get_headers():
return { return {
"authority": "www.indeed.com", 'Host': 'www.indeed.com',
"accept": "*/*", 'accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
"accept-language": "en-US,en;q=0.9", 'sec-fetch-site': 'same-origin',
"referer": "https://www.indeed.com/viewjob?jk=fe6182337d72c7b1&tk=1hcbfcmd0k62t802&from=serp&vjs=3&advn=8132938064490989&adid=408692607&ad=-6NYlbfkN0A3Osc99MJFDKjquSk4WOGT28ALb_ad4QMtrHreCb9ICg6MiSVy9oDAp3evvOrI7Q-O9qOtQTg1EPbthP9xWtBN2cOuVeHQijxHjHpJC65TjDtftH3AXeINjBvAyDrE8DrRaAXl8LD3Fs1e_xuDHQIssdZ2Mlzcav8m5jHrA0fA64ZaqJV77myldaNlM7-qyQpy4AsJQfvg9iR2MY7qeC5_FnjIgjKIy_lNi9OPMOjGRWXA94CuvC7zC6WeiJmBQCHISl8IOBxf7EdJZlYdtzgae3593TFxbkd6LUwbijAfjax39aAuuCXy3s9C4YgcEP3TwEFGQoTpYu9Pmle-Ae1tHGPgsjxwXkgMm7Cz5mBBdJioglRCj9pssn-1u1blHZM4uL1nK9p1Y6HoFgPUU9xvKQTHjKGdH8d4y4ETyCMoNF4hAIyUaysCKdJKitC8PXoYaWhDqFtSMR4Jys8UPqUV&xkcb=SoDD-_M3JLQfWnQTDh0LbzkdCdPP&xpse=SoBa6_I3JLW9FlWZlB0PbzkdCdPP&sjdu=i6xVERweJM_pVUvgf-MzuaunBTY7G71J5eEX6t4DrDs5EMPQdODrX7Nn-WIPMezoqr5wA_l7Of-3CtoiUawcHw", 'sec-fetch-dest': 'document',
"sec-ch-ua": '"Google Chrome";v="119", "Chromium";v="119", "Not?A_Brand";v="24"', 'accept-language': 'en-US,en;q=0.9',
"sec-ch-ua-mobile": "?0", 'sec-fetch-mode': 'navigate',
"sec-ch-ua-platform": '"Windows"', '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',
"sec-fetch-dest": "empty", 'referer': 'https://www.indeed.com/m/jobs?q=software%20intern&l=Dallas%2C%20TX&from=serpso&rq=1&rsIdx=3',
"sec-fetch-mode": "cors",
"sec-fetch-site": "same-origin",
"user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36",
} }
@staticmethod @staticmethod
def is_remote_job(job: dict) -> bool: 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(
any(keyword in attr['label'].lower() for keyword in remote_keywords)
for attr in job_detailed['attributes']
)
is_remote_in_description = any(keyword in description.lower() for keyword in remote_keywords)
is_remote_in_location = any(
keyword in job_detailed['location']['formatted']['long'].lower()
for keyword in remote_keywords
)
is_remote_in_taxonomy = any(
taxonomy["label"] == "remote" and len(taxonomy["attributes"]) > 0
for taxonomy in job.get("taxonomyAttributes", [])
)
return is_remote_in_attributes or is_remote_in_description or is_remote_in_location or is_remote_in_taxonomy
def get_job_details(self, job_keys: list[str]) -> dict:
""" """
:param job: Queries the GraphQL endpoint for detailed job information for the given job keys.
:return: bool
""" """
for taxonomy in job.get("taxonomyAttributes", []): url = "https://apis.indeed.com/graphql"
if taxonomy["label"] == "remote" and len(taxonomy["attributes"]) > 0: headers = {
return True 'Host': 'apis.indeed.com',
return False 'content-type': 'application/json',
'indeed-api-key': '161092c2017b5bbab13edb12461a62d5a833871e7cad6d9d475304573de67ac8',
'accept': 'application/json',
'indeed-locale': 'en-US',
'accept-language': 'en-US,en;q=0.9',
'user-agent': 'Mozilla/5.0 (iPhone; CPU iPhone OS 16_6_1 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) Mobile/15E148 Indeed App 193.1',
'indeed-app-info': 'appv=193.1; appid=com.indeed.jobsearch; osv=16.6.1; os=ios; dtype=phone',
'indeed-co': 'US',
}
job_keys_gql = '[' + ', '.join(f'"{key}"' for key in job_keys) + ']'
payload = {
"query": f"""
query GetJobData {{
jobData(input: {{
jobKeys: {job_keys_gql}
}}) {{
results {{
job {{
key
title
description {{
html
}}
location {{
countryName
countryCode
city
postalCode
streetAddress
formatted {{
short
long
}}
}}
compensation {{
baseSalary {{
unitOfWork
range {{
... on Range {{
min
max
}}
}}
}}
currencyCode
}}
attributes {{
label
}}
employer {{
relativeCompanyPageUrl
}}
recruit {{
viewJobUrl
detailedSalary
workSchedule
}}
}}
}}
}}
}}
"""
}
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

@@ -4,23 +4,35 @@ jobspy.scrapers.linkedin
This module contains routines to scrape LinkedIn. This module contains routines to scrape LinkedIn.
""" """
import time
import random import random
from typing import Optional from typing import Optional
from datetime import datetime from datetime import datetime
import requests import requests
import time
from requests.exceptions import ProxyError from requests.exceptions import ProxyError
from bs4 import BeautifulSoup
from bs4.element import Tag
from threading import Lock from threading import Lock
from bs4.element import Tag
from bs4 import BeautifulSoup
from urllib.parse import urlparse, urlunparse from urllib.parse import urlparse, urlunparse
from .. import Scraper, ScraperInput, Site from .. import Scraper, ScraperInput, Site
from ..exceptions import LinkedInException from ..exceptions import LinkedInException
from ..utils import create_session from ..utils import create_session
from ...jobs import JobPost, Location, JobResponse, JobType, Country, Compensation from ...jobs import (
from ..utils import count_urgent_words, extract_emails_from_text, get_enum_from_job_type, currency_parser JobPost,
Location,
JobResponse,
JobType,
Country,
Compensation
)
from ..utils import (
count_urgent_words,
extract_emails_from_text,
get_enum_from_job_type,
currency_parser
)
class LinkedInScraper(Scraper): class LinkedInScraper(Scraper):
@@ -46,6 +58,12 @@ class LinkedInScraper(Scraper):
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 = (
scraper_input.hours_old * 3600
if scraper_input.hours_old
else None
)
def job_type_code(job_type_enum): def job_type_code(job_type_enum):
mapping = { mapping = {
JobType.FULL_TIME: "F", JobType.FULL_TIME: "F",
@@ -57,7 +75,9 @@ class LinkedInScraper(Scraper):
return mapping.get(job_type_enum, "") return mapping.get(job_type_enum, "")
while len(job_list) < scraper_input.results_wanted and page < 1000: continue_search = lambda: len(job_list) < scraper_input.results_wanted and page < 1000
while continue_search():
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,
@@ -70,6 +90,8 @@ class LinkedInScraper(Scraper):
"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_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}
@@ -85,7 +107,9 @@ class LinkedInScraper(Scraper):
response.raise_for_status() response.raise_for_status()
except requests.HTTPError as e: except requests.HTTPError as e:
raise LinkedInException(f"bad response status code: {e.response.status_code}") raise LinkedInException(
f"bad response status code: {e.response.status_code}"
)
except ProxyError as e: except ProxyError as e:
raise LinkedInException("bad proxy") raise LinkedInException("bad proxy")
except Exception as e: except Exception as e:
@@ -117,8 +141,9 @@ class LinkedInScraper(Scraper):
except Exception as e: except Exception as e:
raise LinkedInException("Exception occurred while processing jobs") raise LinkedInException("Exception occurred while processing jobs")
page += 25 if continue_search():
time.sleep(random.uniform(LinkedInScraper.DELAY, LinkedInScraper.DELAY + 2)) time.sleep(random.uniform(LinkedInScraper.DELAY, LinkedInScraper.DELAY + 2))
page += 25
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)
@@ -128,11 +153,11 @@ class LinkedInScraper(Scraper):
compensation = None compensation = None
if salary_tag: if salary_tag:
salary_text = salary_tag.get_text(separator=' ').strip() salary_text = salary_tag.get_text(separator=" ").strip()
salary_values = [currency_parser(value) for value in salary_text.split('-')] salary_values = [currency_parser(value) for value in salary_text.split("-")]
salary_min = salary_values[0] salary_min = salary_values[0]
salary_max = salary_values[1] salary_max = salary_values[1]
currency = salary_text[0] if salary_text[0] != '$' else 'USD' currency = salary_text[0] if salary_text[0] != "$" else "USD"
compensation = Compensation( compensation = Compensation(
min_amount=int(salary_min), min_amount=int(salary_min),
@@ -210,10 +235,15 @@ class LinkedInScraper(Scraper):
div_content = soup.find( div_content = soup.find(
"div", class_=lambda x: x and "show-more-less-html__markup" in x "div", class_=lambda x: x and "show-more-less-html__markup" in x
) )
description = None description = None
if div_content: if div_content is not None:
description = "\n".join(line.strip() for line in div_content.get_text(separator="\n").splitlines() if line.strip()) def remove_attributes(tag):
for attr in list(tag.attrs):
del tag[attr]
return tag
div_content = remove_attributes(div_content)
description = div_content.prettify(formatter="html")
def get_job_type( def get_job_type(
soup_job_type: BeautifulSoup, soup_job_type: BeautifulSoup,
@@ -277,17 +307,17 @@ class LinkedInScraper(Scraper):
@staticmethod @staticmethod
def headers() -> dict: def headers() -> dict:
return { return {
'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": '"Not_A Brand";v="8", "Chromium";v="120", "Google Chrome";v="120"',
# 'sec-ch-ua-mobile': '?0', # 'sec-ch-ua-mobile': '?0',
# 'sec-ch-ua-platform': '"macOS"', # 'sec-ch-ua-platform': '"macOS"',
# 'sec-fetch-dest': 'document', # 'sec-fetch-dest': 'document',
# 'sec-fetch-mode': 'navigate', # 'sec-fetch-mode': 'navigate',
# 'sec-fetch-site': 'none', # 'sec-fetch-site': 'none',
# 'sec-fetch-user': '?1', # '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

@@ -1,4 +1,5 @@
import re import re
import logging
import numpy as np import numpy as np
import tls_client import tls_client
@@ -7,6 +8,15 @@ from requests.adapters import HTTPAdapter, Retry
from ..jobs import JobType from ..jobs import JobType
logger = logging.getLogger("JobSpy")
if not logger.handlers:
logger.setLevel(logging.ERROR)
console_handler = logging.StreamHandler()
console_handler.setLevel(logging.ERROR)
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
console_handler.setFormatter(formatter)
logger.addHandler(console_handler)
def count_urgent_words(description: str) -> int: def count_urgent_words(description: str) -> int:
""" """
@@ -70,6 +80,7 @@ def get_enum_from_job_type(job_type_str: str) -> JobType | None:
res = job_type res = job_type
return res return res
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)
@@ -85,3 +96,5 @@ def currency_parser(cur_str):
num = float(cur_str) num = float(cur_str)
return np.round(num, 2) return np.round(num, 2)

View File

@@ -6,18 +6,15 @@ This module contains routines to scrape ZipRecruiter.
""" """
import math import math
import time import time
import re from datetime import datetime, timezone
from datetime import datetime, date
from typing import Optional, Tuple, Any from typing import Optional, Tuple, Any
import requests
from bs4 import BeautifulSoup
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 ..exceptions import ZipRecruiterException
from ..utils import count_urgent_words, extract_emails_from_text, create_session
from ...jobs import JobPost, Compensation, Location, JobResponse, JobType, Country from ...jobs import JobPost, Compensation, Location, JobResponse, JobType, Country
from ..utils import count_urgent_words, extract_emails_from_text, create_session
class ZipRecruiterScraper(Scraper): class ZipRecruiterScraper(Scraper):
@@ -33,6 +30,7 @@ class ZipRecruiterScraper(Scraper):
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 find_jobs_in_page(
self, scraper_input: ScraperInput, continue_token: str | None = None self, scraper_input: ScraperInput, continue_token: str | None = None
@@ -45,12 +43,12 @@ class ZipRecruiterScraper(Scraper):
""" """
params = self.add_params(scraper_input) params = self.add_params(scraper_input)
if continue_token: if continue_token:
params["continue"] = continue_token params["continue_from"] = continue_token
try: try:
response = self.session.get( response = self.session.get(
f"https://api.ziprecruiter.com/jobs-app/jobs", f"https://api.ziprecruiter.com/jobs-app/jobs",
headers=self.headers(), headers=self.headers(),
params=self.add_params(scraper_input), params=params
) )
if response.status_code != 200: if response.status_code != 200:
raise ZipRecruiterException( raise ZipRecruiterException(
@@ -61,7 +59,6 @@ class ZipRecruiterScraper(Scraper):
raise ZipRecruiterException("bad proxy") raise ZipRecruiterException("bad proxy")
raise ZipRecruiterException(str(e)) raise ZipRecruiterException(str(e))
time.sleep(5)
response_data = response.json() response_data = response.json()
jobs_list = response_data.get("jobs", []) jobs_list = response_data.get("jobs", [])
next_continue_token = response_data.get("continue", None) next_continue_token = response_data.get("continue", None)
@@ -69,7 +66,7 @@ class ZipRecruiterScraper(Scraper):
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 = [result.result() for result in job_results if result.result()] 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 scrape(self, scraper_input: ScraperInput) -> JobResponse:
@@ -87,6 +84,9 @@ class ZipRecruiterScraper(Scraper):
if len(job_list) >= scraper_input.results_wanted: if len(job_list) >= scraper_input.results_wanted:
break break
if page > 1:
time.sleep(self.delay)
jobs_on_page, continue_token = self.find_jobs_in_page( jobs_on_page, continue_token = self.find_jobs_in_page(
scraper_input, continue_token scraper_input, continue_token
) )
@@ -96,22 +96,19 @@ class ZipRecruiterScraper(Scraper):
if not continue_token: if not continue_token:
break break
if len(job_list) > scraper_input.results_wanted: return JobResponse(jobs=job_list[: scraper_input.results_wanted])
job_list = job_list[: scraper_input.results_wanted]
return JobResponse(jobs=job_list) def process_job(self, job: dict) -> JobPost | None:
@staticmethod
def process_job(job: dict) -> JobPost:
"""Processes an individual job dict from the response""" """Processes an individual job dict from the response"""
title = job.get("name") title = job.get("name")
job_url = job.get("job_url") job_url = f"https://www.ziprecruiter.com/jobs//j?lvk={job['listing_key']}"
if job_url in self.seen_urls:
return
self.seen_urls.add(job_url)
description = BeautifulSoup( description = job.get("job_description", "").strip()
job.get("job_description", "").strip(), "html.parser"
).get_text(separator="\n")
company = job["hiring_company"].get("name") if "hiring_company" in job else None 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)
@@ -121,17 +118,7 @@ class ZipRecruiterScraper(Scraper):
job_type = ZipRecruiterScraper.get_job_type_enum( job_type = ZipRecruiterScraper.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()
save_job_url = job.get("SaveJobURL", "")
posted_time_match = re.search(
r"posted_time=(\d{4}-\d{2}-\d{2}T\d{2}:\d{2}:\d{2}Z)", save_job_url
)
if posted_time_match:
date_time_str = posted_time_match.group(1)
date_posted_obj = datetime.strptime(date_time_str, "%Y-%m-%dT%H:%M:%SZ")
date_posted = date_posted_obj.date()
else:
date_posted = date.today()
return JobPost( return JobPost(
title=title, title=title,
@@ -174,28 +161,25 @@ class ZipRecruiterScraper(Scraper):
params = { params = {
"search": scraper_input.search_term, "search": scraper_input.search_term,
"location": scraper_input.location, "location": scraper_input.location,
"form": "jobs-landing",
} }
job_type_value = None if scraper_input.hours_old:
fromage = max(scraper_input.hours_old // 24, 1) if scraper_input.hours_old else None
params['days'] = fromage
job_type_map = {
JobType.FULL_TIME: 'full_time',
JobType.PART_TIME: 'part_time'
}
if scraper_input.job_type: if scraper_input.job_type:
if scraper_input.job_type.value == "fulltime": 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_value = "full_time" if scraper_input.easy_apply:
elif scraper_input.job_type.value == "parttime": params['zipapply'] = 1
job_type_value = "part_time"
else:
job_type_value = scraper_input.job_type.value
if job_type_value:
params[
"refine_by_employment"
] = f"employment_type:employment_type:{job_type_value}"
if scraper_input.is_remote: if scraper_input.is_remote:
params["refine_by_location_type"] = "only_remote" params["remote"] = 1
if scraper_input.distance: if scraper_input.distance:
params["radius"] = scraper_input.distance params["radius"] = scraper_input.distance
params = {k: v for k, v in params.items() if v is not None}
return params return params
@staticmethod @staticmethod