mirror of https://github.com/Bunsly/JobSpy
enh: linkedin company logo (#141)
parent
8dd08ed9fd
commit
bf73c061bd
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@ -32,17 +32,18 @@ while len(all_jobs) < results_wanted:
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search_term="software engineer",
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# New York, NY
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# Dallas, TX
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# Los Angeles, CA
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location="Los Angeles, CA",
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results_wanted=min(results_in_each_iteration, results_wanted - len(all_jobs)),
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results_wanted=min(
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results_in_each_iteration, results_wanted - len(all_jobs)
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),
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country_indeed="USA",
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offset=offset,
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# proxy="http://jobspy:5a4vpWtj8EeJ2hoYzk@ca.smartproxy.com:20001",
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)
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# Add the scraped jobs to the list
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all_jobs.extend(jobs.to_dict('records'))
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all_jobs.extend(jobs.to_dict("records"))
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# Increment the offset for the next page of results
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offset += results_in_each_iteration
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File diff suppressed because it is too large
Load Diff
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@ -25,8 +25,8 @@ regex = "^2024.4.28"
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[tool.poetry.group.dev.dependencies]
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pytest = "^7.4.1"
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jupyter = "^1.0.0"
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black = "^24.2.0"
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pre-commit = "^3.6.2"
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black = "*"
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pre-commit = "*"
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[build-system]
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requires = ["poetry-core"]
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@ -1,5 +1,7 @@
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from __future__ import annotations
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from abc import ABC, abstractmethod
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from ..jobs import (
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Enum,
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BaseModel,
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@ -36,9 +38,10 @@ class ScraperInput(BaseModel):
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hours_old: int | None = None
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class Scraper:
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class Scraper(ABC):
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def __init__(self, site: Site, proxy: list[str] | None = None):
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self.site = site
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self.proxy = (lambda p: {"http": p, "https": p} if p else None)(proxy)
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@abstractmethod
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def scrape(self, scraper_input: ScraperInput) -> JobResponse: ...
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@ -197,15 +197,16 @@ class LinkedInScraper(Scraper):
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if metadata_card
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else None
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)
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date_posted = description = job_type = job_url_direct = None
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date_posted = None
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if datetime_tag and "datetime" in datetime_tag.attrs:
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datetime_str = datetime_tag["datetime"]
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try:
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date_posted = datetime.strptime(datetime_str, "%Y-%m-%d")
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except:
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date_posted = None
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job_details = {}
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if full_descr:
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description, job_type, job_url_direct = self._get_job_description(job_url)
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job_details = self._get_job_details(job_url)
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return JobPost(
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title=title,
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@ -216,20 +217,18 @@ class LinkedInScraper(Scraper):
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job_url=job_url,
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job_url_direct=job_url_direct,
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compensation=compensation,
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job_type=job_type,
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description=description,
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emails=extract_emails_from_text(description) if description else None,
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job_type=job_details.get("job_type"),
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description=job_details.get("description"),
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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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)
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def _get_job_description(
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self, job_page_url: str
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) -> tuple[None, None, None] | tuple[
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str | None, tuple[str | None, JobType | None], str | None
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]:
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def _get_job_details(self, job_page_url: str) -> dict:
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"""
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Retrieves job description by going to the job page url
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Retrieves job description and other job details by going to the job page url
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:param job_page_url:
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:return: description or None
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:return: dict
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"""
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try:
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session = create_session(is_tls=False, has_retry=True)
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@ -238,9 +237,9 @@ class LinkedInScraper(Scraper):
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)
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response.raise_for_status()
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except:
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return None, None
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return {}
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if response.url == "https://www.linkedin.com/signup":
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return None, None
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return {}
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soup = BeautifulSoup(response.text, "html.parser")
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div_content = soup.find(
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@ -258,7 +257,14 @@ class LinkedInScraper(Scraper):
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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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return description, self._parse_job_type(soup), self._parse_job_url_direct(soup)
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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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"job_url_direct": self._parse_job_url_direct(soup),
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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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}
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def _get_location(self, metadata_card: Optional[Tag]) -> Location:
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"""
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