feat: Ability to query by time posted for linkedin, indeed, glassdoor, ziprecruiter (#103)

README.md

@@ -29,18 +29,20 @@ _Python version >= [3.10](https://www.python.org/downloads/release/python-3100/)
 ### Usage
 
 ```python
+import csv
 from jobspy import scrape_jobs
 
 jobs = scrape_jobs(
     site_name=["indeed", "linkedin", "zip_recruiter", "glassdoor"],
     search_term="software engineer",
     location="Dallas, TX",
-    results_wanted=10,
+    results_wanted=20,
+    hours_old=72, # (only linkedin is hour specific, others round up to days old)
     country_indeed='USA'  # only needed for indeed / glassdoor
 )
 print(f"Found {len(jobs)} jobs")
 print(jobs.head())
-jobs.to_csv("jobs.csv", index=False) # to_xlsx
+jobs.to_csv("jobs.csv", quoting=csv.QUOTE_NONNUMERIC, escapechar="\\", index=False) # to_xlsx
 ```
 
 ### Output
@@ -73,6 +75,7 @@ Optional
 ├── 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)
+├── hours_old (int): filters jobs by the number of hours since the job was posted (all but LinkedIn rounds up to next day)
 ```
 
 ### JobPost Schema

src/jobspy/__init__.py

@@ -42,6 +42,8 @@ def scrape_jobs(
     full_description: bool | None = False,
     linkedin_company_ids: list[int] | None = None,
     offset: int | None = 0,
+    hours_old: int = None,
+    **kwargs,
 ) -> pd.DataFrame:
     """
     Simultaneously scrapes job data from multiple job sites.
@@ -84,6 +86,7 @@ def scrape_jobs(
         results_wanted=results_wanted,
         linkedin_company_ids=linkedin_company_ids,
         offset=offset,
+        hours_old=hours_old
     )
 
     def scrape_site(site: Site) -> Tuple[str, JobResponse]:
@@ -189,4 +192,4 @@ def scrape_jobs(
     else:
         jobs_formatted_df = pd.DataFrame()
 
-    return jobs_formatted_df
+    return jobs_formatted_df.sort_values(by='date_posted', ascending=False)

src/jobspy/scrapers/__init__.py

@@ -23,6 +23,7 @@ class ScraperInput(BaseModel):
     linkedin_company_ids: list[int] | None = None
 
     results_wanted: int = 15
+    hours_old: int | None = None
 
 
 class Scraper:
@@ -30,5 +31,4 @@ class Scraper:
         self.site = site
         self.proxy = (lambda p: {"http": p, "https": p} if p else None)(proxy)
 
-    def scrape(self, scraper_input: ScraperInput) -> JobResponse:
+    def scrape(self, scraper_input: ScraperInput) -> JobResponse: ...
-        ...

src/jobspy/scrapers/glassdoor/__init__.py

@@ -100,7 +100,7 @@ class GlassdoorScraper(Scraper):
         location_type = job["header"].get("locationType", "")
         age_in_days = job["header"].get("ageInDays")
         is_remote, location = False, None
-        date_posted = (datetime.now() - timedelta(days=age_in_days)).date() if age_in_days else None
+        date_posted = (datetime.now() - timedelta(days=age_in_days)).date() if age_in_days is not None else None
 
         if location_type == "S":
             is_remote = True
@@ -258,11 +258,19 @@ class GlassdoorScraper(Scraper):
         page_num: int,
         cursor: str | None = None,
     ) -> str:
+        # `fromage` is the posting time filter in days
+        fromage = max(scraper_input.hours_old // 24, 1) if scraper_input.hours_old else None
+        filter_params = []
+        if scraper_input.easy_apply:
+            filter_params.append({"filterKey": "applicationType", "values": "1"})
+        if fromage:
+            filter_params.append({"filterKey": "fromAge", "values": str(fromage)})
         payload = {
             "operationName": "JobSearchResultsQuery",
+
             "variables": {
                 "excludeJobListingIds": [],
-                "filterParams": [{"filterKey": "applicationType", "values": "1"}] if scraper_input.easy_apply else [],
+                "filterParams": filter_params,
                 "keyword": scraper_input.search_term,
                 "numJobsToShow": 30,
                 "locationType": location_type,
@@ -270,6 +278,8 @@ class GlassdoorScraper(Scraper):
                 "parameterUrlInput": f"IL.0,12_I{location_type}{location_id}",
                 "pageNumber": page_num,
                 "pageCursor": cursor,
+                "fromage": fromage,
+                "sort": "date"
             },
             "query": "query JobSearchResultsQuery($excludeJobListingIds: [Long!], $keyword: String, $locationId: Int, $locationType: LocationTypeEnum, $numJobsToShow: Int!, $pageCursor: String, $pageNumber: Int, $filterParams: [FilterParams], $originalPageUrl: String, $seoFriendlyUrlInput: String, $parameterUrlInput: String, $seoUrl: Boolean) {\n  jobListings(\n    contextHolder: {searchParams: {excludeJobListingIds: $excludeJobListingIds, keyword: $keyword, locationId: $locationId, locationType: $locationType, numPerPage: $numJobsToShow, pageCursor: $pageCursor, pageNumber: $pageNumber, filterParams: $filterParams, originalPageUrl: $originalPageUrl, seoFriendlyUrlInput: $seoFriendlyUrlInput, parameterUrlInput: $parameterUrlInput, seoUrl: $seoUrl, searchType: SR}}\n  ) {\n    companyFilterOptions {\n      id\n      shortName\n      __typename\n    }\n    filterOptions\n    indeedCtk\n    jobListings {\n      ...JobView\n      __typename\n    }\n    jobListingSeoLinks {\n      linkItems {\n        position\n        url\n        __typename\n      }\n      __typename\n    }\n    jobSearchTrackingKey\n    jobsPageSeoData {\n      pageMetaDescription\n      pageTitle\n      __typename\n    }\n    paginationCursors {\n      cursor\n      pageNumber\n      __typename\n    }\n    indexablePageForSeo\n    searchResultsMetadata {\n      searchCriteria {\n        implicitLocation {\n          id\n          localizedDisplayName\n          type\n          __typename\n        }\n        keyword\n        location {\n          id\n          shortName\n          localizedShortName\n          localizedDisplayName\n          type\n          __typename\n        }\n        __typename\n      }\n      footerVO {\n        countryMenu {\n          childNavigationLinks {\n            id\n            link\n            textKey\n            __typename\n          }\n          __typename\n        }\n        __typename\n      }\n      helpCenterDomain\n      helpCenterLocale\n      jobAlert {\n        jobAlertExists\n        __typename\n      }\n      jobSerpFaq {\n        questions {\n          answer\n          question\n          __typename\n        }\n        __typename\n      }\n      jobSerpJobOutlook {\n        occupation\n        paragraph\n        __typename\n      }\n      showMachineReadableJobs\n      __typename\n    }\n    serpSeoLinksVO {\n      relatedJobTitlesResults\n      searchedJobTitle\n      searchedKeyword\n      searchedLocationIdAsString\n      searchedLocationSeoName\n      searchedLocationType\n      topCityIdsToNameResults {\n        key\n        value\n        __typename\n      }\n      topEmployerIdsToNameResults {\n        key\n        value\n        __typename\n      }\n      topEmployerNameResults\n      topOccupationResults\n      __typename\n    }\n    totalJobsCount\n    __typename\n  }\n}\n\nfragment JobView on JobListingSearchResult {\n  jobview {\n    header {\n      adOrderId\n      advertiserType\n      adOrderSponsorshipLevel\n      ageInDays\n      divisionEmployerName\n      easyApply\n      employer {\n        id\n        name\n        shortName\n        __typename\n      }\n      employerNameFromSearch\n      goc\n      gocConfidence\n      gocId\n      jobCountryId\n      jobLink\n      jobResultTrackingKey\n      jobTitleText\n      locationName\n      locationType\n      locId\n      needsCommission\n      payCurrency\n      payPeriod\n      payPeriodAdjustedPay {\n        p10\n        p50\n        p90\n        __typename\n      }\n      rating\n      salarySource\n      savedJobId\n      sponsored\n      __typename\n    }\n    job {\n      descriptionFragments\n      importConfigId\n      jobTitleId\n      jobTitleText\n      listingId\n      __typename\n    }\n    jobListingAdminDetails {\n      cpcVal\n      importConfigId\n      jobListingId\n      jobSourceId\n      userEligibleForAdminJobDetails\n      __typename\n    }\n    overview {\n      shortName\n      squareLogoUrl\n      __typename\n    }\n    __typename\n  }\n  __typename\n}\n",
         }

src/jobspy/scrapers/indeed/__init__.py

@@ -363,12 +363,15 @@ class IndeedScraper(Scraper):
 
     @staticmethod
     def add_params(scraper_input: ScraperInput, page: int) -> dict[str, str | Any]:
+        # `fromage` is the posting time filter in days
+        fromage = max(scraper_input.hours_old // 24, 1) if scraper_input.hours_old else None
         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"
+            "sort": "date",
+            "fromage": fromage,
         }
         if scraper_input.distance:
             params["radius"] = scraper_input.distance
@@ -405,8 +408,7 @@ class IndeedScraper(Scraper):
         )
         return is_remote_in_attributes or is_remote_in_description or is_remote_in_location
 
-    @staticmethod
+    def get_job_details(self, job_keys: list[str]) -> dict:
-    def get_job_details(job_keys: list[str]) -> dict:
         """
         Queries the GraphQL endpoint for detailed job information for the given job keys.
         """
@@ -478,7 +480,7 @@ class IndeedScraper(Scraper):
             }}
             """
         }
-        response = requests.post(url, headers=headers, json=payload)
+        response = requests.post(url, headers=headers, json=payload, proxies=self.proxy)
         if response.status_code == 200:
             return response.json()['data']['jobData']['results']
         else:

src/jobspy/scrapers/linkedin/__init__.py

@@ -59,6 +59,12 @@ class LinkedInScraper(Scraper):
         url_lock = Lock()
         page = scraper_input.offset // 25 + 25 if scraper_input.offset else 0
 
+        seconds_old = (
+            scraper_input.hours_old * 3600
+            if scraper_input.hours_old
+            else None
+        )
+
         def job_type_code(job_type_enum):
             mapping = {
                 JobType.FULL_TIME: "F",
@@ -85,7 +91,8 @@ 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
+                "f_C": ','.join(map(str, scraper_input.linkedin_company_ids)) if scraper_input.linkedin_company_ids else None,
+                "f_TPR": f"r{seconds_old}",
             }
 
             params = {k: v for k, v in params.items() if v is not None}
@@ -101,7 +108,9 @@ class LinkedInScraper(Scraper):
                 response.raise_for_status()
 
             except requests.HTTPError as e:
-                raise LinkedInException(f"bad response status code: {e.response.status_code}")
+                raise LinkedInException(
+                    f"bad response status code: {e.response.status_code}"
+                )
             except ProxyError as e:
                 raise LinkedInException("bad proxy")
             except Exception as e:
@@ -145,11 +154,11 @@ class LinkedInScraper(Scraper):
 
         compensation = None
         if salary_tag:
-            salary_text = salary_tag.get_text(separator=' ').strip()
+            salary_text = salary_tag.get_text(separator=" ").strip()
-            salary_values = [currency_parser(value) for value in salary_text.split('-')]
+            salary_values = [currency_parser(value) for value in salary_text.split("-")]
             salary_min = salary_values[0]
             salary_max = salary_values[1]
-            currency = salary_text[0] if salary_text[0] != '$' else 'USD'
+            currency = salary_text[0] if salary_text[0] != "$" else "USD"
 
             compensation = Compensation(
                 min_amount=int(salary_min),
@@ -294,17 +303,17 @@ class LinkedInScraper(Scraper):
     @staticmethod
     def headers() -> dict:
         return {
-            'authority': 'www.linkedin.com',
+            "authority": "www.linkedin.com",
-            'accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7',
+            "accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7",
-            'accept-language': 'en-US,en;q=0.9',
+            "accept-language": "en-US,en;q=0.9",
-            'cache-control': 'max-age=0',
+            "cache-control": "max-age=0",
-            'sec-ch-ua': '"Not_A Brand";v="8", "Chromium";v="120", "Google Chrome";v="120"',
+            "sec-ch-ua": '"Not_A Brand";v="8", "Chromium";v="120", "Google Chrome";v="120"',
             # 'sec-ch-ua-mobile': '?0',
             # 'sec-ch-ua-platform': '"macOS"',
             # 'sec-fetch-dest': 'document',
             # 'sec-fetch-mode': 'navigate',
             # 'sec-fetch-site': 'none',
             # 'sec-fetch-user': '?1',
-            'upgrade-insecure-requests': '1',
+            "upgrade-insecure-requests": "1",
-            'user-agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36'
+            "user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36",
         }

src/jobspy/scrapers/ziprecruiter/__init__.py

@@ -165,6 +165,9 @@ class ZipRecruiterScraper(Scraper):
             "search": scraper_input.search_term,
             "location": scraper_input.location,
         }
+        if scraper_input.hours_old:
+            fromage = max(scraper_input.hours_old // 24, 1) if scraper_input.hours_old else None
+            params['days'] = fromage
         job_type_value = None
         if scraper_input.job_type:
             if scraper_input.job_type.value == "fulltime":