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6 Commits
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14
README.md
14
README.md
@@ -13,9 +13,6 @@ work with us.*
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- Aggregates the job postings in a Pandas DataFrame
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- Proxies support
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[Video Guide for JobSpy](https://www.youtube.com/watch?v=RuP1HrAZnxs&pp=ygUgam9icyBzY3JhcGVyIGJvdCBsaW5rZWRpbiBpbmRlZWQ%3D) -
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Updated for release v1.1.3
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### Installation
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@@ -41,12 +38,12 @@ jobs = scrape_jobs(
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country_indeed='USA', # only needed for indeed / glassdoor
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# linkedin_fetch_description=True # get full description and direct job url for linkedin (slower)
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# proxies=["Efb5EA8OIk0BQb:wifi;us;@proxy.soax.com:9000", "localhost"],
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# proxies=["208.195.175.46:65095", "208.195.175.45:65095", "localhost"],
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)
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print(f"Found {len(jobs)} jobs")
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print(jobs.head())
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jobs.to_csv("jobs.csv", quoting=csv.QUOTE_NONNUMERIC, escapechar="\\", index=False) # to_xlsx
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jobs.to_csv("jobs.csv", quoting=csv.QUOTE_NONNUMERIC, escapechar="\\", index=False) # to_excel
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```
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### Output
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@@ -79,7 +76,7 @@ Optional
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├── job_type (str):
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| fulltime, parttime, internship, contract
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│
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├── proxies ():
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├── proxies (list):
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| in format ['user:pass@host:port', 'localhost']
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| each job board will round robin through the proxies
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│
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@@ -143,13 +140,14 @@ JobPost
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│ ├── state (str)
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├── description (str)
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├── job_type (str): fulltime, parttime, internship, contract
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├── job_function (str)
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├── compensation (object)
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│ ├── interval (str): yearly, monthly, weekly, daily, hourly
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│ ├── min_amount (int)
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│ ├── max_amount (int)
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│ └── currency (enum)
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└── date_posted (date)
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└── emails (str)
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├── date_posted (date)
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├── emails (str)
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└── is_remote (bool)
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Indeed specific
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@@ -1,6 +1,6 @@
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[tool.poetry]
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name = "python-jobspy"
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version = "1.1.54"
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version = "1.1.56"
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description = "Job scraper for LinkedIn, Indeed, Glassdoor & ZipRecruiter"
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authors = ["Zachary Hampton <zachary@bunsly.com>", "Cullen Watson <cullen@bunsly.com>"]
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homepage = "https://github.com/Bunsly/JobSpy"
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@@ -182,6 +182,7 @@ def scrape_jobs(
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"max_amount",
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"currency",
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"is_remote",
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"job_function",
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"emails",
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"description",
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"company_url",
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@@ -254,6 +254,9 @@ class JobPost(BaseModel):
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logo_photo_url: str | None = None
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banner_photo_url: str | None = None
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# linkedin only atm
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job_function: str | None = None
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class JobResponse(BaseModel):
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jobs: list[JobPost] = []
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@@ -13,14 +13,13 @@ import regex as re
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from typing import Optional
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from datetime import datetime
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from threading import Lock
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from bs4.element import Tag
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from bs4 import BeautifulSoup
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from urllib.parse import urlparse, urlunparse, unquote
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from .. import Scraper, ScraperInput, Site
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from ..exceptions import LinkedInException
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from ..utils import create_session
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from ..utils import create_session, remove_attributes
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from ...jobs import (
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JobPost,
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Location,
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@@ -71,8 +70,8 @@ class LinkedInScraper(Scraper):
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self.scraper_input = scraper_input
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job_list: list[JobPost] = []
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seen_urls = set()
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url_lock = Lock()
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page = scraper_input.offset // 25 + 25 if scraper_input.offset else 0
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page = scraper_input.offset // 10 * 10 if scraper_input.offset else 0
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request_count = 0
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seconds_old = (
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scraper_input.hours_old * 3600 if scraper_input.hours_old else None
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)
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@@ -80,7 +79,8 @@ class LinkedInScraper(Scraper):
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lambda: len(job_list) < scraper_input.results_wanted and page < 1000
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)
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while continue_search():
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logger.info(f"LinkedIn search page: {page // 25 + 1}")
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request_count += 1
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logger.info(f"LinkedIn search page: {request_count}")
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params = {
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"keywords": scraper_input.search_term,
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"location": scraper_input.location,
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@@ -92,7 +92,7 @@ class LinkedInScraper(Scraper):
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else None
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),
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"pageNum": 0,
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"start": page + scraper_input.offset,
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"start": page,
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"f_AL": "true" if scraper_input.easy_apply else None,
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"f_C": (
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",".join(map(str, scraper_input.linkedin_company_ids))
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@@ -140,10 +140,9 @@ class LinkedInScraper(Scraper):
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job_id = href.split("-")[-1]
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job_url = f"{self.base_url}/jobs/view/{job_id}"
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with url_lock:
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if job_url in seen_urls:
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continue
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seen_urls.add(job_url)
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if job_url in seen_urls:
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continue
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seen_urls.add(job_url)
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try:
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fetch_desc = scraper_input.linkedin_fetch_description
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job_post = self._process_job(job_card, job_url, fetch_desc)
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@@ -156,7 +155,7 @@ class LinkedInScraper(Scraper):
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if continue_search():
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time.sleep(random.uniform(self.delay, self.delay + self.band_delay))
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page += self.jobs_per_page
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page += len(job_list)
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job_list = job_list[: scraper_input.results_wanted]
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return JobResponse(jobs=job_list)
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@@ -225,6 +224,7 @@ class LinkedInScraper(Scraper):
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job_url_direct=job_details.get("job_url_direct"),
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emails=extract_emails_from_text(job_details.get("description")),
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logo_photo_url=job_details.get("logo_photo_url"),
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job_function=job_details.get("job_function"),
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)
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def _get_id(self, url: str):
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@@ -248,7 +248,7 @@ class LinkedInScraper(Scraper):
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response.raise_for_status()
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except:
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return {}
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if response.url == "https://www.linkedin.com/signup":
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if "linkedin.com/signup" in response.url:
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return {}
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soup = BeautifulSoup(response.text, "html.parser")
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@@ -257,16 +257,22 @@ class LinkedInScraper(Scraper):
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)
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description = None
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if div_content is not None:
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def remove_attributes(tag):
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for attr in list(tag.attrs):
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del tag[attr]
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return tag
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div_content = remove_attributes(div_content)
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description = div_content.prettify(formatter="html")
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if self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
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description = markdown_converter(description)
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h3_tag = soup.find(
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"h3", text=lambda text: text and "Job function" in text.strip()
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)
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job_function = None
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if h3_tag:
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job_function_span = h3_tag.find_next(
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"span", class_="description__job-criteria-text"
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)
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if job_function_span:
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job_function = job_function_span.text.strip()
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return {
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"description": description,
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"job_type": self._parse_job_type(soup),
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@@ -274,6 +280,7 @@ class LinkedInScraper(Scraper):
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"logo_photo_url": soup.find("img", {"class": "artdeco-entity-image"}).get(
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"data-delayed-url"
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),
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"job_function": job_function,
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}
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def _get_location(self, metadata_card: Optional[Tag]) -> Location:
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@@ -93,6 +93,7 @@ class TLSRotating(RotatingProxySession, tls_client.Session):
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else:
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self.proxies = {}
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response = tls_client.Session.execute_request(self, *args, **kwargs)
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response.ok = response.status_code in range(200, 400)
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return response
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@@ -178,3 +179,9 @@ def currency_parser(cur_str):
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num = float(cur_str)
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return np.round(num, 2)
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def remove_attributes(tag):
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for attr in list(tag.attrs):
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del tag[attr]
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return tag
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@@ -7,19 +7,24 @@ This module contains routines to scrape ZipRecruiter.
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from __future__ import annotations
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import json
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import math
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import re
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import time
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from datetime import datetime
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from typing import Optional, Tuple, Any
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from concurrent.futures import ThreadPoolExecutor
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from bs4 import BeautifulSoup
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from .. import Scraper, ScraperInput, Site
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from ..utils import (
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logger,
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extract_emails_from_text,
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create_session,
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markdown_converter,
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remove_attributes,
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)
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from ...jobs import (
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JobPost,
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@@ -151,6 +156,8 @@ class ZipRecruiterScraper(Scraper):
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comp_min = int(job["compensation_min"]) if "compensation_min" in job else None
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comp_max = int(job["compensation_max"]) if "compensation_max" in job else None
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comp_currency = job.get("compensation_currency")
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description_full, job_url_direct = self._get_descr(job_url)
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return JobPost(
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id=str(job["listing_key"]),
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title=title,
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@@ -165,10 +172,42 @@ class ZipRecruiterScraper(Scraper):
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),
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date_posted=date_posted,
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job_url=job_url,
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description=description,
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description=description_full if description_full else description,
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emails=extract_emails_from_text(description) if description else None,
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job_url_direct=job_url_direct,
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)
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def _get_descr(self, job_url):
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res = self.session.get(job_url, headers=self.headers, allow_redirects=True)
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description_full = job_url_direct = None
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if res.ok:
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soup = BeautifulSoup(res.text, "html.parser")
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job_descr_div = soup.find("div", class_="job_description")
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company_descr_section = soup.find("section", class_="company_description")
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job_description_clean = (
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remove_attributes(job_descr_div).prettify(formatter="html")
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if job_descr_div
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else ""
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)
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company_description_clean = (
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remove_attributes(company_descr_section).prettify(formatter="html")
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if company_descr_section
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else ""
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)
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description_full = job_description_clean + company_description_clean
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script_tag = soup.find("script", type="application/json")
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if script_tag:
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job_json = json.loads(script_tag.string)
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job_url_val = job_json["model"]["saveJobURL"]
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m = re.search(r"job_url=(.+)", job_url_val)
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if m:
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job_url_direct = m.group(1)
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if self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
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description_full = markdown_converter(description_full)
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return description_full, job_url_direct
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def _get_cookies(self):
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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"
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url = f"{self.api_url}/jobs-app/event"
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