Salary parse (#163)

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "python-jobspy"
-version = "1.1.56"
+version = "1.1.57"
 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"

src/jobspy/__init__.py

@@ -5,7 +5,7 @@ from typing import Tuple
 from concurrent.futures import ThreadPoolExecutor, as_completed
 
 from .jobs import JobType, Location
-from .scrapers.utils import logger, set_logger_level
+from .scrapers.utils import logger, set_logger_level, extract_salary
 from .scrapers.indeed import IndeedScraper
 from .scrapers.ziprecruiter import ZipRecruiterScraper
 from .scrapers.glassdoor import GlassdoorScraper
@@ -118,6 +118,21 @@ def scrape_jobs(
             site_value, scraped_data = future.result()
             site_to_jobs_dict[site_value] = scraped_data
 
+    def convert_to_annual(job_data: dict):
+        if job_data["interval"] == "hourly":
+            job_data["min_amount"] *= 2080
+            job_data["max_amount"] *= 2080
+        if job_data["interval"] == "monthly":
+            job_data["min_amount"] *= 12
+            job_data["max_amount"] *= 12
+        if job_data["interval"] == "weekly":
+            job_data["min_amount"] *= 52
+            job_data["max_amount"] *= 52
+        if job_data["interval"] == "daily":
+            job_data["min_amount"] *= 260
+            job_data["max_amount"] *= 260
+        job_data["interval"] = "yearly"
+
     jobs_dfs: list[pd.DataFrame] = []
 
     for site, job_response in site_to_jobs_dict.items():
@@ -150,11 +165,22 @@ def scrape_jobs(
                 job_data["min_amount"] = compensation_obj.get("min_amount")
                 job_data["max_amount"] = compensation_obj.get("max_amount")
                 job_data["currency"] = compensation_obj.get("currency", "USD")
+                if (
+                    job_data["interval"]
+                    and job_data["interval"] != "yearly"
+                    and job_data["min_amount"]
+                    and job_data["max_amount"]
+                ):
+                    convert_to_annual(job_data)
+
             else:
-                job_data["interval"] = None
+                if country_enum == Country.USA:
-                job_data["min_amount"] = None
+                    (
-                job_data["max_amount"] = None
+                        job_data["interval"],
-                job_data["currency"] = None
+                        job_data["min_amount"],
+                        job_data["max_amount"],
+                        job_data["currency"],
+                    ) = extract_salary(job_data["description"])
 
             job_df = pd.DataFrame([job_data])
             jobs_dfs.append(job_df)

src/jobspy/scrapers/glassdoor/__init__.py

@@ -69,7 +69,7 @@ class GlassdoorScraper(Scraper):
         if location_type is None:
             logger.error("Glassdoor: location not parsed")
             return JobResponse(jobs=[])
-        all_jobs: list[JobPost] = []
+        job_list: list[JobPost] = []
         cursor = None
 
         range_start = 1 + (scraper_input.offset // self.jobs_per_page)
@@ -81,14 +81,14 @@ class GlassdoorScraper(Scraper):
                 jobs, cursor = self._fetch_jobs_page(
                     scraper_input, location_id, location_type, page, cursor
                 )
-                all_jobs.extend(jobs)
+                job_list.extend(jobs)
-                if not jobs or len(all_jobs) >= scraper_input.results_wanted:
+                if not jobs or len(job_list) >= scraper_input.results_wanted:
-                    all_jobs = all_jobs[: scraper_input.results_wanted]
+                    job_list = job_list[: scraper_input.results_wanted]
                     break
             except Exception as e:
                 logger.error(f"Glassdoor: {str(e)}")
                 break
-        return JobResponse(jobs=all_jobs)
+        return JobResponse(jobs=job_list)
 
     def _fetch_jobs_page(
         self,

src/jobspy/scrapers/indeed/__init__.py

@@ -297,8 +297,8 @@ class IndeedScraper(Scraper):
         max_range = comp["range"].get("max")
         return Compensation(
             interval=interval,
-            min_amount=round(min_range, 2) if min_range is not None else None,
+            min_amount=int(min_range) if min_range is not None else None,
-            max_amount=round(max_range, 2) if max_range is not None else None,
+            max_amount=int(max_range) if max_range is not None else None,
             currency=job["compensation"]["currencyCode"],
         )
 

src/jobspy/scrapers/linkedin/__init__.py

@@ -69,7 +69,7 @@ class LinkedInScraper(Scraper):
         """
         self.scraper_input = scraper_input
         job_list: list[JobPost] = []
-        seen_urls = set()
+        seen_ids = set()
         page = scraper_input.offset // 10 * 10 if scraper_input.offset else 0
         request_count = 0
         seconds_old = (
@@ -133,19 +133,18 @@ class LinkedInScraper(Scraper):
                 return JobResponse(jobs=job_list)
 
             for job_card in job_cards:
-                job_url = None
                 href_tag = job_card.find("a", class_="base-card__full-link")
                 if href_tag and "href" in href_tag.attrs:
                     href = href_tag.attrs["href"].split("?")[0]
                     job_id = href.split("-")[-1]
-                    job_url = f"{self.base_url}/jobs/view/{job_id}"
 
-                if job_url in seen_urls:
+                    if job_id in seen_ids:
                         continue
-                seen_urls.add(job_url)
+                    seen_ids.add(job_id)
+
                     try:
                         fetch_desc = scraper_input.linkedin_fetch_description
-                    job_post = self._process_job(job_card, job_url, fetch_desc)
+                        job_post = self._process_job(job_card, job_id, fetch_desc)
                         if job_post:
                             job_list.append(job_post)
                         if not continue_search():
@@ -161,7 +160,7 @@ class LinkedInScraper(Scraper):
         return JobResponse(jobs=job_list)
 
     def _process_job(
-        self, job_card: Tag, job_url: str, full_descr: bool
+        self, job_card: Tag, job_id: str, full_descr: bool
     ) -> Optional[JobPost]:
         salary_tag = job_card.find("span", class_="job-search-card__salary-info")
 
@@ -208,16 +207,16 @@ class LinkedInScraper(Scraper):
                 date_posted = None
         job_details = {}
         if full_descr:
-            job_details = self._get_job_details(job_url)
+            job_details = self._get_job_details(job_id)
 
         return JobPost(
-            id=self._get_id(job_url),
+            id=job_id,
             title=title,
             company_name=company,
             company_url=company_url,
             location=location,
             date_posted=date_posted,
-            job_url=job_url,
+            job_url=f"{self.base_url}/jobs/view/{job_id}",
             compensation=compensation,
             job_type=job_details.get("job_type"),
             description=job_details.get("description"),
@@ -227,24 +226,16 @@ class LinkedInScraper(Scraper):
             job_function=job_details.get("job_function"),
         )
 
-    def _get_id(self, url: str):
+    def _get_job_details(self, job_id: str) -> dict:
-        """
-        Extracts the job id from the job url
-        :param url:
-        :return: str
-        """
-        if not url:
-            return None
-        return url.split("/")[-1]
-
-    def _get_job_details(self, job_page_url: str) -> dict:
         """
         Retrieves job description and other job details by going to the job page url
         :param job_page_url:
         :return: dict
         """
         try:
-            response = self.session.get(job_page_url, timeout=5)
+            response = self.session.get(
+                f"{self.base_url}/jobs-guest/jobs/api/jobPosting/{job_id}", timeout=5
+            )
             response.raise_for_status()
         except:
             return {}

src/jobspy/scrapers/utils.py

@@ -185,3 +185,55 @@ def remove_attributes(tag):
     for attr in list(tag.attrs):
         del tag[attr]
     return tag
+
+
+def extract_salary(
+    salary_str,
+    lower_limit=1000,
+    upper_limit=700000,
+    hourly_threshold=350,
+    monthly_threshold=30000,
+):
+    if not salary_str:
+        return None, None, None, None
+
+    min_max_pattern = r"\$(\d+(?:,\d+)?(?:\.\d+)?)([kK]?)\s*[-—–]\s*(?:\$)?(\d+(?:,\d+)?(?:\.\d+)?)([kK]?)"
+
+    def to_int(s):
+        return int(float(s.replace(",", "")))
+
+    def convert_hourly_to_annual(hourly_wage):
+        return hourly_wage * 2080
+
+    def convert_monthly_to_annual(monthly_wage):
+        return monthly_wage * 12
+
+    match = re.search(min_max_pattern, salary_str)
+
+    if match:
+        min_salary = to_int(match.group(1))
+        max_salary = to_int(match.group(3))
+        # Handle 'k' suffix for min and max salaries independently
+        if "k" in match.group(2).lower() or "k" in match.group(4).lower():
+            min_salary *= 1000
+            max_salary *= 1000
+
+        # Convert to annual if less than the hourly threshold
+        if min_salary < hourly_threshold:
+            min_salary = convert_hourly_to_annual(min_salary)
+            if max_salary < hourly_threshold:
+                max_salary = convert_hourly_to_annual(max_salary)
+
+        elif min_salary < monthly_threshold:
+            min_salary = convert_monthly_to_annual(min_salary)
+            if max_salary < monthly_threshold:
+                max_salary = convert_monthly_to_annual(max_salary)
+
+        # Ensure salary range is within specified limits
+        if (
+            lower_limit <= min_salary <= upper_limit
+            and lower_limit <= max_salary <= upper_limit
+            and min_salary < max_salary
+        ):
+            return "yearly", min_salary, max_salary, "USD"
+    return None, None, None, None