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v1.1.76
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22
.github/workflows/python-test.yml
vendored
22
.github/workflows/python-test.yml
vendored
@@ -1,22 +0,0 @@
|
||||
name: Python Tests
|
||||
|
||||
on:
|
||||
pull_request:
|
||||
branches:
|
||||
- main
|
||||
|
||||
jobs:
|
||||
test:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v2
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@v2
|
||||
with:
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||||
python-version: '3.8'
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
pip install poetry
|
||||
poetry install
|
||||
- name: Run tests
|
||||
run: poetry run pytest tests/test_all.py
|
||||
13
README.md
13
README.md
@@ -1,10 +1,10 @@
|
||||
<img src="https://github.com/cullenwatson/JobSpy/assets/78247585/ae185b7e-e444-4712-8bb9-fa97f53e896b" width="400">
|
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|
||||
**JobSpy** is a simple, yet comprehensive, job scraping library.
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**JobSpy** is a job scraping library with the goal of aggregating all the jobs from popular job boards with one tool.
|
||||
|
||||
## Features
|
||||
|
||||
- Scrapes job postings from **LinkedIn**, **Indeed**, **Glassdoor**, **Google**, & **ZipRecruiter** simultaneously
|
||||
- Scrapes job postings from **LinkedIn**, **Indeed**, **Glassdoor**, **Google**, **ZipRecruiter**, & **Bayt** concurrently
|
||||
- Aggregates the job postings in a dataframe
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- Proxies support to bypass blocking
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||||
|
||||
@@ -25,7 +25,7 @@ import csv
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from jobspy import scrape_jobs
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|
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jobs = scrape_jobs(
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site_name=["indeed", "linkedin", "zip_recruiter", "glassdoor", "google"],
|
||||
site_name=["indeed", "linkedin", "zip_recruiter", "glassdoor", "google", "bayt"],
|
||||
search_term="software engineer",
|
||||
google_search_term="software engineer jobs near San Francisco, CA since yesterday",
|
||||
location="San Francisco, CA",
|
||||
@@ -58,7 +58,7 @@ zip_recruiter Software Developer TEKsystems Phoenix
|
||||
```plaintext
|
||||
Optional
|
||||
├── site_name (list|str):
|
||||
| linkedin, zip_recruiter, indeed, glassdoor, google
|
||||
| linkedin, zip_recruiter, indeed, glassdoor, google, bayt
|
||||
| (default is all)
|
||||
│
|
||||
├── search_term (str)
|
||||
@@ -165,6 +165,11 @@ You can specify the following countries when searching on Indeed (use the exact
|
||||
| United Arab Emirates | UK* | USA* | Uruguay |
|
||||
| Venezuela | Vietnam* | | |
|
||||
|
||||
### **Bayt**
|
||||
|
||||
Bayt only uses the search_term parameter currently and searches internationally
|
||||
|
||||
|
||||
|
||||
## Notes
|
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* Indeed is the best scraper currently with no rate limiting.
|
||||
|
||||
@@ -11,6 +11,7 @@ from .scrapers.ziprecruiter import ZipRecruiterScraper
|
||||
from .scrapers.glassdoor import GlassdoorScraper
|
||||
from .scrapers.google import GoogleJobsScraper
|
||||
from .scrapers.linkedin import LinkedInScraper
|
||||
from .scrapers.bayt import BaytScraper
|
||||
from .scrapers import SalarySource, ScraperInput, Site, JobResponse, Country
|
||||
from .scrapers.exceptions import (
|
||||
LinkedInException,
|
||||
@@ -41,7 +42,7 @@ def scrape_jobs(
|
||||
offset: int | None = 0,
|
||||
hours_old: int = None,
|
||||
enforce_annual_salary: bool = False,
|
||||
verbose: int = 2,
|
||||
verbose: int = 0,
|
||||
**kwargs,
|
||||
) -> pd.DataFrame:
|
||||
"""
|
||||
@@ -54,6 +55,7 @@ def scrape_jobs(
|
||||
Site.ZIP_RECRUITER: ZipRecruiterScraper,
|
||||
Site.GLASSDOOR: GlassdoorScraper,
|
||||
Site.GOOGLE: GoogleJobsScraper,
|
||||
Site.BAYT: BaytScraper,
|
||||
}
|
||||
set_logger_level(verbose)
|
||||
|
||||
|
||||
@@ -18,6 +18,7 @@ class Site(Enum):
|
||||
ZIP_RECRUITER = "zip_recruiter"
|
||||
GLASSDOOR = "glassdoor"
|
||||
GOOGLE = "google"
|
||||
BAYT = "bayt"
|
||||
|
||||
|
||||
class SalarySource(Enum):
|
||||
|
||||
145
src/jobspy/scrapers/bayt/__init__.py
Normal file
145
src/jobspy/scrapers/bayt/__init__.py
Normal file
@@ -0,0 +1,145 @@
|
||||
"""
|
||||
jobspy.scrapers.bayt
|
||||
~~~~~~~~~~~~~~~~~~~
|
||||
|
||||
This module contains routines to scrape Bayt.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import random
|
||||
import time
|
||||
|
||||
from bs4 import BeautifulSoup
|
||||
|
||||
from .. import Scraper, ScraperInput, Site
|
||||
from ..utils import create_logger, create_session
|
||||
from ...jobs import JobPost, JobResponse, Location, Country
|
||||
|
||||
log = create_logger("Bayt")
|
||||
|
||||
|
||||
class BaytScraper(Scraper):
|
||||
base_url = "https://www.bayt.com"
|
||||
delay = 2
|
||||
band_delay = 3
|
||||
|
||||
def __init__(
|
||||
self, proxies: list[str] | str | None = None, ca_cert: str | None = None
|
||||
):
|
||||
super().__init__(Site.BAYT, proxies=proxies, ca_cert=ca_cert)
|
||||
self.scraper_input = None
|
||||
self.session = None
|
||||
self.country = "worldwide"
|
||||
|
||||
def scrape(self, scraper_input: ScraperInput) -> JobResponse:
|
||||
self.scraper_input = scraper_input
|
||||
self.session = create_session(
|
||||
proxies=self.proxies, ca_cert=self.ca_cert, is_tls=False, has_retry=True
|
||||
)
|
||||
job_list: list[JobPost] = []
|
||||
page = 1
|
||||
results_wanted = (
|
||||
scraper_input.results_wanted if scraper_input.results_wanted else 10
|
||||
)
|
||||
|
||||
while len(job_list) < results_wanted:
|
||||
log.info(f"Fetching Bayt jobs page {page}")
|
||||
job_elements = self._fetch_jobs(self.scraper_input.search_term, page)
|
||||
if not job_elements:
|
||||
break
|
||||
|
||||
if job_elements:
|
||||
log.debug(
|
||||
"First job element snippet:\n" + job_elements[0].prettify()[:500]
|
||||
)
|
||||
|
||||
initial_count = len(job_list)
|
||||
for job in job_elements:
|
||||
try:
|
||||
job_post = self._extract_job_info(job)
|
||||
if job_post:
|
||||
job_list.append(job_post)
|
||||
if len(job_list) >= results_wanted:
|
||||
break
|
||||
else:
|
||||
log.debug(
|
||||
"Extraction returned None. Job snippet:\n"
|
||||
+ job.prettify()[:500]
|
||||
)
|
||||
except Exception as e:
|
||||
log.error(f"Bayt: Error extracting job info: {str(e)}")
|
||||
continue
|
||||
|
||||
if len(job_list) == initial_count:
|
||||
log.info(f"No new jobs found on page {page}. Ending pagination.")
|
||||
break
|
||||
|
||||
page += 1
|
||||
time.sleep(random.uniform(self.delay, self.delay + self.band_delay))
|
||||
|
||||
job_list = job_list[: scraper_input.results_wanted]
|
||||
return JobResponse(jobs=job_list)
|
||||
|
||||
def _fetch_jobs(self, query: str, page: int) -> list | None:
|
||||
"""
|
||||
Grabs the job results for the given query and page number.
|
||||
"""
|
||||
try:
|
||||
url = f"{self.base_url}/en/international/jobs/{query}-jobs/?page={page}"
|
||||
response = self.session.get(url)
|
||||
response.raise_for_status()
|
||||
soup = BeautifulSoup(response.text, "html.parser")
|
||||
job_listings = soup.find_all("li", attrs={"data-js-job": ""})
|
||||
log.debug(f"Found {len(job_listings)} job listing elements")
|
||||
return job_listings
|
||||
except Exception as e:
|
||||
log.error(f"Bayt: Error fetching jobs - {str(e)}")
|
||||
return None
|
||||
|
||||
def _extract_job_info(self, job: BeautifulSoup) -> JobPost | None:
|
||||
"""
|
||||
Extracts the job information from a single job listing.
|
||||
"""
|
||||
# Find the h2 element holding the title and link (no class filtering)
|
||||
job_general_information = job.find("h2")
|
||||
if not job_general_information:
|
||||
return
|
||||
|
||||
job_title = job_general_information.get_text(strip=True)
|
||||
job_url = self._extract_job_url(job_general_information)
|
||||
if not job_url:
|
||||
return
|
||||
|
||||
# Extract company name using the original approach:
|
||||
company_tag = job.find("div", class_="t-nowrap p10l")
|
||||
company_name = (
|
||||
company_tag.find("span").get_text(strip=True)
|
||||
if company_tag and company_tag.find("span")
|
||||
else None
|
||||
)
|
||||
|
||||
# Extract location using the original approach:
|
||||
location_tag = job.find("div", class_="t-mute t-small")
|
||||
location = location_tag.get_text(strip=True) if location_tag else None
|
||||
|
||||
job_id = f"bayt-{abs(hash(job_url))}"
|
||||
location_obj = Location(
|
||||
city=location,
|
||||
country=Country.from_string(self.country),
|
||||
)
|
||||
return JobPost(
|
||||
id=job_id,
|
||||
title=job_title,
|
||||
company_name=company_name,
|
||||
location=location_obj,
|
||||
job_url=job_url,
|
||||
)
|
||||
|
||||
def _extract_job_url(self, job_general_information: BeautifulSoup) -> str | None:
|
||||
"""
|
||||
Pulls the job URL from the 'a' within the h2 element.
|
||||
"""
|
||||
a_tag = job_general_information.find("a")
|
||||
if a_tag and a_tag.has_attr("href"):
|
||||
return self.base_url + a_tag["href"].strip()
|
||||
@@ -29,3 +29,8 @@ class GlassdoorException(Exception):
|
||||
class GoogleJobsException(Exception):
|
||||
def __init__(self, message=None):
|
||||
super().__init__(message or "An error occurred with Google Jobs")
|
||||
|
||||
|
||||
class BaytException(Exception):
|
||||
def __init__(self, message=None):
|
||||
super().__init__(message or "An error occurred with Bayt")
|
||||
|
||||
@@ -32,7 +32,7 @@ from ...jobs import (
|
||||
DescriptionFormat,
|
||||
)
|
||||
|
||||
logger = create_logger("Glassdoor")
|
||||
log = create_logger("Glassdoor")
|
||||
|
||||
|
||||
class GlassdoorScraper(Scraper):
|
||||
@@ -64,7 +64,7 @@ class GlassdoorScraper(Scraper):
|
||||
self.base_url = self.scraper_input.country.get_glassdoor_url()
|
||||
|
||||
self.session = create_session(
|
||||
proxies=self.proxies, ca_cert=self.ca_cert, is_tls=True, has_retry=True
|
||||
proxies=self.proxies, ca_cert=self.ca_cert, has_retry=True
|
||||
)
|
||||
token = self._get_csrf_token()
|
||||
headers["gd-csrf-token"] = token if token else fallback_token
|
||||
@@ -74,7 +74,7 @@ class GlassdoorScraper(Scraper):
|
||||
scraper_input.location, scraper_input.is_remote
|
||||
)
|
||||
if location_type is None:
|
||||
logger.error("Glassdoor: location not parsed")
|
||||
log.error("Glassdoor: location not parsed")
|
||||
return JobResponse(jobs=[])
|
||||
job_list: list[JobPost] = []
|
||||
cursor = None
|
||||
@@ -83,7 +83,7 @@ class GlassdoorScraper(Scraper):
|
||||
tot_pages = (scraper_input.results_wanted // self.jobs_per_page) + 2
|
||||
range_end = min(tot_pages, self.max_pages + 1)
|
||||
for page in range(range_start, range_end):
|
||||
logger.info(f"search page: {page} / {range_end-1}")
|
||||
log.info(f"search page: {page} / {range_end - 1}")
|
||||
try:
|
||||
jobs, cursor = self._fetch_jobs_page(
|
||||
scraper_input, location_id, location_type, page, cursor
|
||||
@@ -93,7 +93,7 @@ class GlassdoorScraper(Scraper):
|
||||
job_list = job_list[: scraper_input.results_wanted]
|
||||
break
|
||||
except Exception as e:
|
||||
logger.error(f"Glassdoor: {str(e)}")
|
||||
log.error(f"Glassdoor: {str(e)}")
|
||||
break
|
||||
return JobResponse(jobs=job_list)
|
||||
|
||||
@@ -129,7 +129,7 @@ class GlassdoorScraper(Scraper):
|
||||
ValueError,
|
||||
Exception,
|
||||
) as e:
|
||||
logger.error(f"Glassdoor: {str(e)}")
|
||||
log.error(f"Glassdoor: {str(e)}")
|
||||
return jobs, None
|
||||
|
||||
jobs_data = res_json["data"]["jobListings"]["jobListings"]
|
||||
@@ -264,12 +264,12 @@ class GlassdoorScraper(Scraper):
|
||||
if res.status_code != 200:
|
||||
if res.status_code == 429:
|
||||
err = f"429 Response - Blocked by Glassdoor for too many requests"
|
||||
logger.error(err)
|
||||
log.error(err)
|
||||
return None, None
|
||||
else:
|
||||
err = f"Glassdoor response status code {res.status_code}"
|
||||
err += f" - {res.text}"
|
||||
logger.error(f"Glassdoor response status code {res.status_code}")
|
||||
log.error(f"Glassdoor response status code {res.status_code}")
|
||||
return None, None
|
||||
items = res.json()
|
||||
|
||||
|
||||
@@ -26,7 +26,7 @@ from ...jobs import (
|
||||
JobType,
|
||||
)
|
||||
|
||||
logger = create_logger("Google")
|
||||
log = create_logger("Google")
|
||||
|
||||
|
||||
class GoogleJobsScraper(Scraper):
|
||||
@@ -61,7 +61,7 @@ class GoogleJobsScraper(Scraper):
|
||||
)
|
||||
forward_cursor, job_list = self._get_initial_cursor_and_jobs()
|
||||
if forward_cursor is None:
|
||||
logger.warning(
|
||||
log.warning(
|
||||
"initial cursor not found, try changing your query or there was at most 10 results"
|
||||
)
|
||||
return JobResponse(jobs=job_list)
|
||||
@@ -72,16 +72,16 @@ class GoogleJobsScraper(Scraper):
|
||||
len(self.seen_urls) < scraper_input.results_wanted + scraper_input.offset
|
||||
and forward_cursor
|
||||
):
|
||||
logger.info(
|
||||
log.info(
|
||||
f"search page: {page} / {math.ceil(scraper_input.results_wanted / self.jobs_per_page)}"
|
||||
)
|
||||
try:
|
||||
jobs, forward_cursor = self._get_jobs_next_page(forward_cursor)
|
||||
except Exception as e:
|
||||
logger.error(f"failed to get jobs on page: {page}, {e}")
|
||||
log.error(f"failed to get jobs on page: {page}, {e}")
|
||||
break
|
||||
if not jobs:
|
||||
logger.info(f"found no jobs on page: {page}")
|
||||
log.info(f"found no jobs on page: {page}")
|
||||
break
|
||||
job_list += jobs
|
||||
page += 1
|
||||
@@ -230,10 +230,7 @@ class GoogleJobsScraper(Scraper):
|
||||
|
||||
@staticmethod
|
||||
def _find_job_info_initial_page(html_text: str):
|
||||
pattern = (
|
||||
f'520084652":('
|
||||
+ r"\[.*?\]\s*])\s*}\s*]\s*]\s*]\s*]\s*]"
|
||||
)
|
||||
pattern = f'520084652":(' + r"\[.*?\]\s*])\s*}\s*]\s*]\s*]\s*]\s*]"
|
||||
results = []
|
||||
matches = re.finditer(pattern, html_text)
|
||||
|
||||
@@ -245,6 +242,6 @@ class GoogleJobsScraper(Scraper):
|
||||
results.append(parsed_data)
|
||||
|
||||
except json.JSONDecodeError as e:
|
||||
logger.error(f"Failed to parse match: {str(e)}")
|
||||
log.error(f"Failed to parse match: {str(e)}")
|
||||
results.append({"raw_match": match.group(0), "error": str(e)})
|
||||
return results
|
||||
|
||||
@@ -30,7 +30,7 @@ from ...jobs import (
|
||||
DescriptionFormat,
|
||||
)
|
||||
|
||||
logger = create_logger("Indeed")
|
||||
log = create_logger("Indeed")
|
||||
|
||||
|
||||
class IndeedScraper(Scraper):
|
||||
@@ -71,12 +71,12 @@ class IndeedScraper(Scraper):
|
||||
cursor = None
|
||||
|
||||
while len(self.seen_urls) < scraper_input.results_wanted + scraper_input.offset:
|
||||
logger.info(
|
||||
log.info(
|
||||
f"search page: {page} / {math.ceil(scraper_input.results_wanted / self.jobs_per_page)}"
|
||||
)
|
||||
jobs, cursor = self._scrape_page(cursor)
|
||||
if not jobs:
|
||||
logger.info(f"found no jobs on page: {page}")
|
||||
log.info(f"found no jobs on page: {page}")
|
||||
break
|
||||
job_list += jobs
|
||||
page += 1
|
||||
@@ -122,9 +122,10 @@ class IndeedScraper(Scraper):
|
||||
headers=api_headers_temp,
|
||||
json=payload,
|
||||
timeout=10,
|
||||
verify=False,
|
||||
)
|
||||
if not response.ok:
|
||||
logger.info(
|
||||
log.info(
|
||||
f"responded with status code: {response.status_code} (submit GitHub issue if this appears to be a bug)"
|
||||
)
|
||||
return jobs, new_cursor
|
||||
|
||||
@@ -38,7 +38,7 @@ from ..utils import (
|
||||
markdown_converter,
|
||||
)
|
||||
|
||||
logger = create_logger("LinkedIn")
|
||||
log = create_logger("LinkedIn")
|
||||
|
||||
|
||||
class LinkedInScraper(Scraper):
|
||||
@@ -86,7 +86,7 @@ class LinkedInScraper(Scraper):
|
||||
)
|
||||
while continue_search():
|
||||
request_count += 1
|
||||
logger.info(
|
||||
log.info(
|
||||
f"search page: {request_count} / {math.ceil(scraper_input.results_wanted / 10)}"
|
||||
)
|
||||
params = {
|
||||
@@ -126,13 +126,13 @@ class LinkedInScraper(Scraper):
|
||||
else:
|
||||
err = f"LinkedIn response status code {response.status_code}"
|
||||
err += f" - {response.text}"
|
||||
logger.error(err)
|
||||
log.error(err)
|
||||
return JobResponse(jobs=job_list)
|
||||
except Exception as e:
|
||||
if "Proxy responded with" in str(e):
|
||||
logger.error(f"LinkedIn: Bad proxy")
|
||||
log.error(f"LinkedIn: Bad proxy")
|
||||
else:
|
||||
logger.error(f"LinkedIn: {str(e)}")
|
||||
log.error(f"LinkedIn: {str(e)}")
|
||||
return JobResponse(jobs=job_list)
|
||||
|
||||
soup = BeautifulSoup(response.text, "html.parser")
|
||||
|
||||
@@ -1,17 +1,20 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import re
|
||||
import logging
|
||||
import re
|
||||
from itertools import cycle
|
||||
|
||||
import numpy as np
|
||||
import requests
|
||||
import tls_client
|
||||
import numpy as np
|
||||
import urllib3
|
||||
from markdownify import markdownify as md
|
||||
from requests.adapters import HTTPAdapter, Retry
|
||||
|
||||
from ..jobs import CompensationInterval, JobType
|
||||
|
||||
urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
|
||||
|
||||
|
||||
def create_logger(name: str):
|
||||
logger = logging.getLogger(f"JobSpy:{name}")
|
||||
@@ -129,7 +132,7 @@ def create_session(
|
||||
return session
|
||||
|
||||
|
||||
def set_logger_level(verbose: int = 2):
|
||||
def set_logger_level(verbose: int):
|
||||
"""
|
||||
Adjusts the logger's level. This function allows the logging level to be changed at runtime.
|
||||
|
||||
|
||||
@@ -11,11 +11,10 @@ import json
|
||||
import math
|
||||
import re
|
||||
import time
|
||||
from concurrent.futures import ThreadPoolExecutor
|
||||
from datetime import datetime
|
||||
from typing import Optional, Tuple, Any
|
||||
|
||||
from concurrent.futures import ThreadPoolExecutor
|
||||
|
||||
from bs4 import BeautifulSoup
|
||||
|
||||
from .constants import headers
|
||||
@@ -37,7 +36,7 @@ from ...jobs import (
|
||||
DescriptionFormat,
|
||||
)
|
||||
|
||||
logger = create_logger("ZipRecruiter")
|
||||
log = create_logger("ZipRecruiter")
|
||||
|
||||
|
||||
class ZipRecruiterScraper(Scraper):
|
||||
@@ -77,7 +76,7 @@ class ZipRecruiterScraper(Scraper):
|
||||
break
|
||||
if page > 1:
|
||||
time.sleep(self.delay)
|
||||
logger.info(f"search page: {page} / {max_pages}")
|
||||
log.info(f"search page: {page} / {max_pages}")
|
||||
jobs_on_page, continue_token = self._find_jobs_in_page(
|
||||
scraper_input, continue_token
|
||||
)
|
||||
@@ -110,13 +109,13 @@ class ZipRecruiterScraper(Scraper):
|
||||
else:
|
||||
err = f"ZipRecruiter response status code {res.status_code}"
|
||||
err += f" with response: {res.text}" # ZipRecruiter likely not available in EU
|
||||
logger.error(err)
|
||||
log.error(err)
|
||||
return jobs_list, ""
|
||||
except Exception as e:
|
||||
if "Proxy responded with" in str(e):
|
||||
logger.error(f"Indeed: Bad proxy")
|
||||
log.error(f"Indeed: Bad proxy")
|
||||
else:
|
||||
logger.error(f"Indeed: {str(e)}")
|
||||
log.error(f"Indeed: {str(e)}")
|
||||
return jobs_list, ""
|
||||
|
||||
res_data = res.json()
|
||||
@@ -215,7 +214,28 @@ class ZipRecruiterScraper(Scraper):
|
||||
return description_full, job_url_direct
|
||||
|
||||
def _get_cookies(self):
|
||||
data = "event_type=session&logged_in=false&number_of_retry=1&property=model%3AiPhone&property=os%3AiOS&property=locale%3Aen_us&property=app_build_number%3A4734&property=app_version%3A91.0&property=manufacturer%3AApple&property=timestamp%3A2024-01-12T12%3A04%3A42-06%3A00&property=screen_height%3A852&property=os_version%3A16.6.1&property=source%3Ainstall&property=screen_width%3A393&property=device_model%3AiPhone%2014%20Pro&property=brand%3AApple"
|
||||
"""
|
||||
Sends a session event to the API with device properties.
|
||||
"""
|
||||
data = [
|
||||
("event_type", "session"),
|
||||
("logged_in", "false"),
|
||||
("number_of_retry", "1"),
|
||||
("property", "model:iPhone"),
|
||||
("property", "os:iOS"),
|
||||
("property", "locale:en_us"),
|
||||
("property", "app_build_number:4734"),
|
||||
("property", "app_version:91.0"),
|
||||
("property", "manufacturer:Apple"),
|
||||
("property", "timestamp:2025-01-12T12:04:42-06:00"),
|
||||
("property", "screen_height:852"),
|
||||
("property", "os_version:16.6.1"),
|
||||
("property", "source:install"),
|
||||
("property", "screen_width:393"),
|
||||
("property", "device_model:iPhone 14 Pro"),
|
||||
("property", "brand:Apple"),
|
||||
]
|
||||
|
||||
url = f"{self.api_url}/jobs-app/event"
|
||||
self.session.post(url, data=data)
|
||||
|
||||
|
||||
@@ -1,18 +0,0 @@
|
||||
from jobspy import scrape_jobs
|
||||
import pandas as pd
|
||||
|
||||
|
||||
def test_all():
|
||||
sites = [
|
||||
"indeed",
|
||||
"glassdoor",
|
||||
] # ziprecruiter/linkedin needs good ip, and temp fix to pass test on ci
|
||||
result = scrape_jobs(
|
||||
site_name=sites,
|
||||
search_term="engineer",
|
||||
results_wanted=5,
|
||||
)
|
||||
|
||||
assert (
|
||||
isinstance(result, pd.DataFrame) and len(result) == len(sites) * 5
|
||||
), "Result should be a non-empty DataFrame"
|
||||
@@ -1,13 +0,0 @@
|
||||
from jobspy import scrape_jobs
|
||||
import pandas as pd
|
||||
|
||||
|
||||
def test_glassdoor():
|
||||
result = scrape_jobs(
|
||||
site_name="glassdoor",
|
||||
search_term="engineer",
|
||||
results_wanted=5,
|
||||
)
|
||||
assert (
|
||||
isinstance(result, pd.DataFrame) and len(result) == 5
|
||||
), "Result should be a non-empty DataFrame"
|
||||
@@ -1,12 +0,0 @@
|
||||
from jobspy import scrape_jobs
|
||||
import pandas as pd
|
||||
|
||||
|
||||
def test_google():
|
||||
result = scrape_jobs(
|
||||
site_name="google", search_term="software engineer", results_wanted=5
|
||||
)
|
||||
|
||||
assert (
|
||||
isinstance(result, pd.DataFrame) and len(result) == 5
|
||||
), "Result should be a non-empty DataFrame"
|
||||
@@ -1,13 +0,0 @@
|
||||
from jobspy import scrape_jobs
|
||||
import pandas as pd
|
||||
|
||||
|
||||
def test_indeed():
|
||||
result = scrape_jobs(
|
||||
site_name="indeed",
|
||||
search_term="engineer",
|
||||
results_wanted=5,
|
||||
)
|
||||
assert (
|
||||
isinstance(result, pd.DataFrame) and len(result) == 5
|
||||
), "Result should be a non-empty DataFrame"
|
||||
@@ -1,9 +0,0 @@
|
||||
from jobspy import scrape_jobs
|
||||
import pandas as pd
|
||||
|
||||
|
||||
def test_linkedin():
|
||||
result = scrape_jobs(site_name="linkedin", search_term="engineer", results_wanted=5)
|
||||
assert (
|
||||
isinstance(result, pd.DataFrame) and len(result) == 5
|
||||
), "Result should be a non-empty DataFrame"
|
||||
@@ -1,12 +0,0 @@
|
||||
from jobspy import scrape_jobs
|
||||
import pandas as pd
|
||||
|
||||
|
||||
def test_ziprecruiter():
|
||||
result = scrape_jobs(
|
||||
site_name="zip_recruiter", search_term="software engineer", results_wanted=5
|
||||
)
|
||||
|
||||
assert (
|
||||
isinstance(result, pd.DataFrame) and len(result) == 5
|
||||
), "Result should be a non-empty DataFrame"
|
||||
Reference in New Issue
Block a user