Compare commits

...

10 Commits

Author SHA1 Message Date
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 173 additions and 146 deletions

View File

@@ -69,7 +69,8 @@ Optional
├── is_remote (bool)
├── full_description (bool): fetches full description for Indeed / LinkedIn (much slower)
├── results_wanted (int): number of job results to retrieve for each site specified in 'site_type'
├── easy_apply (bool): filters for jobs that are hosted on 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)
├── offset (num): starts the search from an offset (e.g. 25 will start the search from the 25th result)
```
@@ -80,6 +81,7 @@ Optional
JobPost
├── title (str)
├── company (str)
├── company_url (str)
├── job_url (str)
├── location (object)
│ ├── country (str)
@@ -158,16 +160,11 @@ persist, [submit an issue](https://github.com/Bunsly/JobSpy/issues).
**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:
- Waiting a few seconds between requests.
- Waiting some time between scrapes (site-dependent).
- 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 = [
{file = "MarkupSafe-2.1.3-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:5bbe06f8eeafd38e5d0a4894ffec89378b6c6a625ff57e3028921f8ff59318ac"},
{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-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:f698de3fd0c4e6972b92290a45bd9b1536bffe8c6759c62471efaa8acb4c37bc"},
{file = "MarkupSafe-2.1.3-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:aa57bd9cf8ae831a362185ee444e15a93ecb2e344c8e52e4d721ea3ab6ef1823"},
{file = "MarkupSafe-2.1.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ffcc3f7c66b5f5b7931a5aa68fc9cecc51e685ef90282f4a82f0f5e9b704ad11"},
{file = "MarkupSafe-2.1.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:47d4f1c5f80fc62fdd7777d0d40a2e9dda0a05883ab11374334f6c4de38adffd"},
{file = "MarkupSafe-2.1.3-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:1f67c7038d560d92149c060157d623c542173016c4babc0c1913cca0564b9939"},
{file = "MarkupSafe-2.1.3-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:9aad3c1755095ce347e26488214ef77e0485a3c34a50c5a5e2471dff60b9dd9c"},
{file = "MarkupSafe-2.1.3-cp312-cp312-musllinux_1_1_i686.whl", hash = "sha256:14ff806850827afd6b07a5f32bd917fb7f45b046ba40c57abdb636674a8b559c"},
{file = "MarkupSafe-2.1.3-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:8f9293864fe09b8149f0cc42ce56e3f0e54de883a9de90cd427f191c346eb2e1"},
{file = "MarkupSafe-2.1.3-cp312-cp312-win32.whl", hash = "sha256:715d3562f79d540f251b99ebd6d8baa547118974341db04f5ad06d5ea3eb8007"},
{file = "MarkupSafe-2.1.3-cp312-cp312-win_amd64.whl", hash = "sha256:1b8dd8c3fd14349433c79fa8abeb573a55fc0fdd769133baac1f5e07abf54aeb"},
{file = "MarkupSafe-2.1.3-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:8e254ae696c88d98da6555f5ace2279cf7cd5b3f52be2b5cf97feafe883b58d2"},
{file = "MarkupSafe-2.1.3-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:cb0932dc158471523c9637e807d9bfb93e06a95cbf010f1a38b98623b929ef2b"},
{file = "MarkupSafe-2.1.3-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9402b03f1a1b4dc4c19845e5c749e3ab82d5078d16a2a4c2cd2df62d57bb0707"},
@@ -2270,13 +2260,13 @@ test = ["flake8", "isort", "pytest"]
[[package]]
name = "tls-client"
version = "0.2.1"
version = "1.0"
description = "Advanced Python HTTP Client."
optional = false
python-versions = "*"
files = [
{file = "tls_client-0.2.1-py3-none-any.whl", hash = "sha256:124a710952b979d5e20b4e2b7879b7958d6e48a259d0f5b83101055eb173f0bd"},
{file = "tls_client-0.2.1.tar.gz", hash = "sha256:473fb4c671d9d4ca6b818548ab6e955640dd589767bfce520830c5618c2f2e2b"},
{file = "tls_client-1.0-py3-none-any.whl", hash = "sha256:f1183f5e18cb31914bd62d11b350a33ea0293ea80fb91d69a3072821dece3e66"},
{file = "tls_client-1.0.tar.gz", hash = "sha256:7f6de48ad4a0ef69b72682c76ce604155971e07b4bfb2148a36276194ae3e7a0"},
]
[[package]]
@@ -2445,4 +2435,4 @@ files = [
[metadata]
lock-version = "2.0"
python-versions = "^3.10"
content-hash = "f966f3979873eec2c3b13460067f5aa414c69aa8ab5cd3239c1cfa564fcb5deb"
content-hash = "404a77d78066cbb2ef71015562baf44aa11d12aac29a191c1ccc7758bfda598a"

View File

@@ -1,6 +1,6 @@
[tool.poetry]
name = "python-jobspy"
version = "1.1.35"
version = "1.1.42"
description = "Job scraper for LinkedIn, Indeed, Glassdoor & ZipRecruiter"
authors = ["Zachary Hampton <zachary@bunsly.com>", "Cullen Watson <cullen@bunsly.com>"]
homepage = "https://github.com/Bunsly/JobSpy"
@@ -13,7 +13,7 @@ packages = [
[tool.poetry.dependencies]
python = "^3.10"
requests = "^2.31.0"
tls-client = "^0.2.1"
tls-client = "*"
beautifulsoup4 = "^4.12.2"
pandas = "^2.1.0"
NUMPY = "1.24.2"

View File

@@ -1,7 +1,7 @@
import pandas as pd
from typing import Tuple
import concurrent.futures
from concurrent.futures import ThreadPoolExecutor
from typing import Tuple, Optional
from .jobs import JobType, Location
from .scrapers.indeed import IndeedScraper
@@ -29,19 +29,20 @@ def _map_str_to_site(site_name: str) -> Site:
def scrape_jobs(
site_name: str | list[str] | Site | list[Site],
search_term: str,
location: str = "",
distance: int = None,
site_name: str | list[str] | Site | list[Site] | None = None,
search_term: str | None = None,
location: str | None = None,
distance: int | None = None,
is_remote: bool = False,
job_type: str = None,
easy_apply: bool = False, # linkedin
job_type: str | None = None,
easy_apply: bool | None = None,
results_wanted: int = 15,
country_indeed: str = "usa",
hyperlinks: bool = False,
proxy: Optional[str] = None,
full_description: Optional[bool] = False,
offset: Optional[int] = 0,
proxy: str | None = None,
full_description: bool | None = False,
linkedin_company_ids: list[int] | None = None,
offset: int | None = 0,
) -> pd.DataFrame:
"""
Simultaneously scrapes job data from multiple job sites.
@@ -56,18 +57,23 @@ def scrape_jobs(
job_type = get_enum_from_value(job_type) if job_type else None
if type(site_name) == str:
site_type = [_map_str_to_site(site_name)]
else: #: if type(site_name) == list
site_type = [
_map_str_to_site(site) if type(site) == str else site_name
for site in site_name
]
def get_site_type():
site_types = list(Site)
if isinstance(site_name, str):
site_types = [_map_str_to_site(site_name)]
elif isinstance(site_name, Site):
site_types = [site_name]
elif isinstance(site_name, list):
site_types = [
_map_str_to_site(site) if isinstance(site, str) else site
for site in site_name
]
return site_types
country_enum = Country.from_string(country_indeed)
scraper_input = ScraperInput(
site_type=site_type,
site_type=get_site_type(),
country=country_enum,
search_term=search_term,
location=location,
@@ -77,6 +83,7 @@ def scrape_jobs(
easy_apply=easy_apply,
full_description=full_description,
results_wanted=results_wanted,
linkedin_company_ids=linkedin_company_ids,
offset=offset,
)

View File

@@ -1,7 +1,7 @@
from typing import Union, Optional
from typing import Optional
from datetime import date
from enum import Enum
from pydantic import BaseModel, validator
from pydantic import BaseModel
class JobType(Enum):

View File

@@ -1,5 +1,4 @@
from ..jobs import Enum, BaseModel, JobType, JobResponse, Country
from typing import List, Optional, Any
class Site(Enum):
@@ -10,23 +9,24 @@ class Site(Enum):
class ScraperInput(BaseModel):
site_type: List[Site]
search_term: str
site_type: list[Site]
search_term: str | None = None
location: str = None
country: Optional[Country] = Country.USA
distance: Optional[int] = None
location: str | None = None
country: Country | None = Country.USA
distance: int | None = None
is_remote: bool = False
job_type: Optional[JobType] = None
easy_apply: bool = None # linkedin
job_type: JobType | None = None
easy_apply: bool | None = None
full_description: bool = False
offset: int = 0
linkedin_company_ids: list[int] | None = None
results_wanted: int = 15
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.proxy = (lambda p: {"http": p, "https": p} if p else None)(proxy)

View File

@@ -14,7 +14,7 @@ from ..utils import count_urgent_words, extract_emails_from_text
from .. import Scraper, ScraperInput, Site
from ..exceptions import GlassdoorException
from ..utils import create_session
from ..utils import create_session, modify_and_get_description
from ...jobs import (
JobPost,
Compensation,
@@ -88,13 +88,14 @@ class GlassdoorScraper(Scraper):
def process_job(self, job_data):
"""Processes a single job and fetches its description."""
job_id = job_data["jobview"]["job"]["listingId"]
job_url = f'{self.url}/job-listing/?jl={job_id}'
job_url = f'{self.url}job-listing/j?jl={job_id}'
if job_url in self.seen_urls:
return None
self.seen_urls.add(job_url)
job = job_data["jobview"]
title = job["job"]["jobTitleText"]
company_name = job["header"]["employerNameFromSearch"]
company_id = job_data['jobview']['header']['employer']['id']
location_name = job["header"].get("locationName", "")
location_type = job["header"].get("locationType", "")
age_in_days = job["header"].get("ageInDays")
@@ -115,6 +116,7 @@ class GlassdoorScraper(Scraper):
job_post = JobPost(
title=title,
company_url=f"{self.url}Overview/W-EI_IE{company_id}.htm" if company_id else None,
company_name=company_name,
date_posted=date_posted,
job_url=job_url,
@@ -200,9 +202,7 @@ class GlassdoorScraper(Scraper):
data = response.json()[0]
desc = data['data']['jobview']['job']['description']
soup = BeautifulSoup(desc, 'html.parser')
description = soup.get_text(separator='\n')
return description
return modify_and_get_description(soup)
@staticmethod
def parse_compensation(data: dict) -> Optional[Compensation]:
@@ -246,6 +246,8 @@ class GlassdoorScraper(Scraper):
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
@@ -260,7 +262,7 @@ class GlassdoorScraper(Scraper):
"operationName": "JobSearchResultsQuery",
"variables": {
"excludeJobListingIds": [],
"filterParams": [],
"filterParams": [{"filterKey": "applicationType", "values": "1"}] if scraper_input.easy_apply else [],
"keyword": scraper_input.search_term,
"numJobsToShow": 30,
"locationType": location_type,
@@ -292,12 +294,11 @@ class GlassdoorScraper(Scraper):
for job_type in JobType:
if job_type_str in job_type.value:
return [job_type]
return None
@staticmethod
def parse_location(location_name: str) -> Location:
def parse_location(location_name: str) -> Location | None:
if not location_name or location_name == "Remote":
return None
return
city, _, state = location_name.partition(", ")
return Location(city=city, state=state)
@@ -306,7 +307,6 @@ class GlassdoorScraper(Scraper):
for cursor_data in pagination_cursors:
if cursor_data["pageNumber"] == page_num:
return cursor_data["cursor"]
return None
@staticmethod
def headers() -> dict:

View File

@@ -8,6 +8,7 @@ import re
import math
import io
import json
from typing import Any
from datetime import datetime
import urllib.parse
@@ -21,6 +22,7 @@ from ..utils import (
extract_emails_from_text,
create_session,
get_enum_from_job_type,
modify_and_get_description
)
from ...jobs import (
JobPost,
@@ -43,7 +45,7 @@ class IndeedScraper(Scraper):
site = Site(Site.INDEED)
super().__init__(site, proxy=proxy)
self.jobs_per_page = 15
self.jobs_per_page = 25
self.seen_urls = set()
def scrape_page(
@@ -59,30 +61,12 @@ class IndeedScraper(Scraper):
domain = self.country.indeed_domain_value
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:
session = create_session(self.proxy)
response = session.get(
f"{self.url}/jobs",
f"{self.url}/m/jobs",
headers=self.get_headers(),
params=params,
params=self.add_params(scraper_input, page),
allow_redirects=True,
timeout_seconds=10,
)
@@ -111,8 +95,8 @@ class IndeedScraper(Scraper):
):
raise IndeedException("No jobs found.")
def process_job(job) -> JobPost | None:
job_url = f'{self.url}/jobs/viewjob?jk={job["jobkey"]}'
def process_job(job: 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
@@ -170,8 +154,9 @@ class IndeedScraper(Scraper):
)
return job_post
workers = 10 if scraper_input.full_description else 10 # possibly lessen 10 when fetching desc based on feedback
jobs = jobs["metaData"]["mosaicProviderJobCardsModel"]["results"]
with ThreadPoolExecutor(max_workers=1) as executor:
with ThreadPoolExecutor(max_workers=workers) as executor:
job_results: list[Future] = [
executor.submit(process_job, job) for job in jobs
]
@@ -193,7 +178,7 @@ class IndeedScraper(Scraper):
#: get first page to initialize session
job_list, total_results = self.scrape_page(scraper_input, 0)
with ThreadPoolExecutor(max_workers=1) as executor:
with ThreadPoolExecutor(max_workers=10) as executor:
futures: list[Future] = [
executor.submit(self.scrape_page, scraper_input, page)
for page in range(1, pages_to_process + 1)
@@ -222,7 +207,7 @@ class IndeedScraper(Scraper):
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"
formatted_url = f"{self.url}/m/viewjob?jk={jk_value}&spa=1"
session = create_session(self.proxy)
try:
@@ -239,17 +224,23 @@ class IndeedScraper(Scraper):
return None
try:
data = json.loads(response.text)
job_description = data["body"]["jobInfoWrapperModel"]["jobInfoModel"][
"sanitizedJobDescription"
]
soup = BeautifulSoup(response.text, 'html.parser')
script_tags = soup.find_all('script')
job_description = ''
for tag in script_tags:
if 'window._initialData' in tag.text:
json_str = tag.text
json_str = json_str.split('window._initialData=')[1]
json_str = json_str.rsplit(';', 1)[0]
data = json.loads(json_str)
job_description = data["jobInfoWrapperModel"]["jobInfoModel"]["sanitizedJobDescription"]
break
except (KeyError, TypeError, IndexError):
return None
soup = BeautifulSoup(job_description, "html.parser")
text_content = "\n".join(soup.stripped_strings)
return text_content
return modify_and_get_description(soup)
@staticmethod
def get_job_type(job: dict) -> list[JobType] | None:
@@ -332,17 +323,14 @@ class IndeedScraper(Scraper):
@staticmethod
def get_headers():
return {
"authority": "www.indeed.com",
"accept": "*/*",
"accept-language": "en-US,en;q=0.9",
"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-ch-ua": '"Google Chrome";v="119", "Chromium";v="119", "Not?A_Brand";v="24"',
"sec-ch-ua-mobile": "?0",
"sec-ch-ua-platform": '"Windows"',
"sec-fetch-dest": "empty",
"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",
'Host': 'www.indeed.com',
'accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
'sec-fetch-site': 'same-origin',
'sec-fetch-dest': 'document',
'accept-language': 'en-US,en;q=0.9',
'sec-fetch-mode': 'navigate',
'user-agent': 'Mozilla/5.0 (iPhone; CPU iPhone OS 16_6_1 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) Mobile/15E148 Indeed App 192.0',
'referer': 'https://www.indeed.com/m/jobs?q=software%20intern&l=Dallas%2C%20TX&from=serpso&rq=1&rsIdx=3',
}
@staticmethod
@@ -355,3 +343,29 @@ class IndeedScraper(Scraper):
if taxonomy["label"] == "remote" and len(taxonomy["attributes"]) > 0:
return True
return False
@staticmethod
def add_params(scraper_input: ScraperInput, page: int) -> dict[str, str | Any]:
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"
}
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) + ";"
if scraper_input.easy_apply:
params['iafilter'] = 1
return params

View File

@@ -4,23 +4,36 @@ jobspy.scrapers.linkedin
This module contains routines to scrape LinkedIn.
"""
import time
import random
from typing import Optional
from datetime import datetime
import requests
import time
from requests.exceptions import ProxyError
from bs4 import BeautifulSoup
from bs4.element import Tag
from threading import Lock
from bs4.element import Tag
from bs4 import BeautifulSoup
from urllib.parse import urlparse, urlunparse
from .. import Scraper, ScraperInput, Site
from ..exceptions import LinkedInException
from ..utils import create_session
from ...jobs import JobPost, Location, JobResponse, JobType, Country, Compensation
from ..utils import count_urgent_words, extract_emails_from_text, get_enum_from_job_type, currency_parser
from ...jobs import (
JobPost,
Location,
JobResponse,
JobType,
Country,
Compensation
)
from ..utils import (
count_urgent_words,
extract_emails_from_text,
get_enum_from_job_type,
currency_parser,
modify_and_get_description
)
class LinkedInScraper(Scraper):
@@ -57,7 +70,9 @@ class LinkedInScraper(Scraper):
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)
params = {
"keywords": scraper_input.search_term,
@@ -70,6 +85,7 @@ class LinkedInScraper(Scraper):
"pageNum": 0,
"start": page + scraper_input.offset,
"f_AL": "true" if scraper_input.easy_apply else None,
"f_C": ','.join(map(str, scraper_input.linkedin_company_ids)) if scraper_input.linkedin_company_ids else None
}
params = {k: v for k, v in params.items() if v is not None}
@@ -117,8 +133,9 @@ class LinkedInScraper(Scraper):
except Exception as e:
raise LinkedInException("Exception occurred while processing jobs")
page += 25
time.sleep(random.uniform(LinkedInScraper.DELAY, LinkedInScraper.DELAY + 2))
if continue_search():
time.sleep(random.uniform(LinkedInScraper.DELAY, LinkedInScraper.DELAY + 2))
page += 25
job_list = job_list[: scraper_input.results_wanted]
return JobResponse(jobs=job_list)
@@ -213,7 +230,7 @@ class LinkedInScraper(Scraper):
description = None
if div_content:
description = "\n".join(line.strip() for line in div_content.get_text(separator="\n").splitlines() if line.strip())
description = modify_and_get_description(div_content)
def get_job_type(
soup_job_type: BeautifulSoup,

View File

@@ -8,6 +8,15 @@ from requests.adapters import HTTPAdapter, Retry
from ..jobs import JobType
def modify_and_get_description(soup):
for li in soup.find_all('li'):
li.string = "- " + li.get_text()
description = soup.get_text(separator='\n').strip()
description = re.sub(r'\n+', '\n', description)
return description
def count_urgent_words(description: str) -> int:
"""
Count the number of urgent words or phrases in a job description.

View File

@@ -6,18 +6,16 @@ This module contains routines to scrape ZipRecruiter.
"""
import math
import time
import re
from datetime import datetime, date
from datetime import datetime, timezone
from typing import Optional, Tuple, Any
import requests
from bs4 import BeautifulSoup
from concurrent.futures import ThreadPoolExecutor
from .. import Scraper, ScraperInput, Site
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 ..utils import count_urgent_words, extract_emails_from_text, create_session, modify_and_get_description
class ZipRecruiterScraper(Scraper):
@@ -33,6 +31,7 @@ class ZipRecruiterScraper(Scraper):
self.jobs_per_page = 20
self.seen_urls = set()
self.delay = 5
def find_jobs_in_page(
self, scraper_input: ScraperInput, continue_token: str | None = None
@@ -45,12 +44,12 @@ class ZipRecruiterScraper(Scraper):
"""
params = self.add_params(scraper_input)
if continue_token:
params["continue"] = continue_token
params["continue_from"] = continue_token
try:
response = self.session.get(
f"https://api.ziprecruiter.com/jobs-app/jobs",
headers=self.headers(),
params=self.add_params(scraper_input),
params=params
)
if response.status_code != 200:
raise ZipRecruiterException(
@@ -61,7 +60,6 @@ class ZipRecruiterScraper(Scraper):
raise ZipRecruiterException("bad proxy")
raise ZipRecruiterException(str(e))
time.sleep(5)
response_data = response.json()
jobs_list = response_data.get("jobs", [])
next_continue_token = response_data.get("continue", None)
@@ -69,7 +67,7 @@ class ZipRecruiterScraper(Scraper):
with ThreadPoolExecutor(max_workers=self.jobs_per_page) as executor:
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
def scrape(self, scraper_input: ScraperInput) -> JobResponse:
@@ -87,6 +85,9 @@ class ZipRecruiterScraper(Scraper):
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
)
@@ -96,22 +97,21 @@ class ZipRecruiterScraper(Scraper):
if not continue_token:
break
if len(job_list) > scraper_input.results_wanted:
job_list = job_list[: scraper_input.results_wanted]
return JobResponse(jobs=job_list[: scraper_input.results_wanted])
return JobResponse(jobs=job_list)
@staticmethod
def process_job(job: dict) -> JobPost:
def process_job(self, job: dict) -> JobPost | None:
"""Processes an individual job dict from the response"""
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(
job.get("job_description", "").strip(), "html.parser"
).get_text(separator="\n")
job_description_html = job.get("job_description", "").strip()
description_soup = BeautifulSoup(job_description_html, "html.parser")
description = modify_and_get_description(description_soup)
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_enum = Country.from_string(country_value)
@@ -121,17 +121,7 @@ class ZipRecruiterScraper(Scraper):
job_type = ZipRecruiterScraper.get_job_type_enum(
job.get("employment_type", "").replace("_", "").lower()
)
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()
date_posted = datetime.fromisoformat(job['posted_time'].rstrip("Z")).date()
return JobPost(
title=title,
@@ -174,7 +164,6 @@ class ZipRecruiterScraper(Scraper):
params = {
"search": scraper_input.search_term,
"location": scraper_input.location,
"form": "jobs-landing",
}
job_type_value = None
if scraper_input.job_type:
@@ -184,6 +173,8 @@ class ZipRecruiterScraper(Scraper):
job_type_value = "part_time"
else:
job_type_value = scraper_input.job_type.value
if scraper_input.easy_apply:
params['zipapply'] = 1
if job_type_value:
params[
@@ -196,6 +187,8 @@ class ZipRecruiterScraper(Scraper):
if scraper_input.distance:
params["radius"] = scraper_input.distance
params = {k: v for k, v in params.items() if v is not None}
return params
@staticmethod