docs:readme

README.md

@@ -8,8 +8,8 @@ work with us.*
 ## Features
 
 - Scrapes job postings from **LinkedIn**, **Indeed**, **Glassdoor**, **Google**, & **ZipRecruiter** simultaneously
-- Aggregates the job postings in a Pandas DataFrame
-- Proxies support
+- Aggregates the job postings in a dataframe
+- Proxies support to bypass blocking
 
 ![jobspy](https://github.com/cullenwatson/JobSpy/assets/78247585/ec7ef355-05f6-4fd3-8161-a817e31c5c57)
 
@@ -30,14 +30,14 @@ from jobspy import scrape_jobs
 jobs = scrape_jobs(
     site_name=["indeed", "linkedin", "zip_recruiter", "glassdoor", "google"],
     search_term="software engineer",
+    google_search_term="software engineer jobs near San Francisco, CA since yesterday",
     location="San Francisco, CA",
     results_wanted=20,
-    hours_old=72, # (only Linkedin/Indeed is hour specific, others round up to days old)
-    country_indeed='USA',  # only needed for indeed / glassdoor
+    hours_old=72,
+    country_indeed='USA',
     
-    # linkedin_fetch_description=True # get more info such as full description, direct job url for linkedin (slower)
+    # linkedin_fetch_description=True # gets more info such as description, direct job url (slower)
     # proxies=["208.195.175.46:65095", "208.195.175.45:65095", "localhost"],
-    
 )
 print(f"Found {len(jobs)} jobs")
 print(jobs.head())
@@ -65,6 +65,9 @@ Optional
 |    (default is all)
 │
 ├── search_term (str)
+|
+├── google_search_term (str)
+|     search term for google jobs. This is the only param for filtering google jobs.
 │
 ├── location (str)
 │
@@ -84,7 +87,7 @@ Optional
 |    number of job results to retrieve for each site specified in 'site_name'
 │
 ├── easy_apply (bool): 
-|    filters for jobs that are hosted on the job board site
+|    filters for jobs that are hosted on the job board site (LinkedIn easy apply filter no longer works)
 │
 ├── description_format (str): 
 |    markdown, html (Format type of the job descriptions. Default is markdown.)
@@ -129,51 +132,11 @@ Optional
 |    - easy_apply
 ```
 
-
-### JobPost Schema
-
-```plaintext
-JobPost
-├── title
-├── company
-├── company_url
-├── job_url
-├── location
-│   ├── country
-│   ├── city
-│   ├── state
-├── description
-├── job_type: fulltime, parttime, internship, contract
-├── job_function
-│   ├── interval: yearly, monthly, weekly, daily, hourly
-│   ├── min_amount
-│   ├── max_amount
-│   ├── currency
-│   └── salary_source: direct_data, description (parsed from posting)
-├── date_posted
-├── emails
-└── is_remote
-
-Linkedin specific
-└── job_level
-
-Linkedin & Indeed specific
-└── company_industry
-
-Indeed specific
-├── company_country
-├── company_addresses
-├── company_employees_label
-├── company_revenue_label
-├── company_description
-└── company_logo
-```
-
 ## Supported Countries for Job Searching
 
-### **LinkedIn / Google**
+### **LinkedIn**
 
-LinkedIn & Google searches globally & uses only the `location` parameter. 
+LinkedIn searches globally & uses only the `location` parameter. 
 
 ### **ZipRecruiter**
 
@@ -215,7 +178,18 @@ You can specify the following countries when searching on Indeed (use the exact
 
 ---
 **Q: Why is Indeed giving unrelated roles?**  
-**A:** Indeed is searching each one of your terms e.g. software intern, it searches software OR intern. Try search_term='"software intern"' in quotes for stricter searching
+**A:** Indeed searches the description too.
+
+- use - to remove words
+- "" for exact match
+
+Example of a good Indeed query
+
+```py
+search_term='"engineering intern" software summer (java OR python OR c++) 2025 -tax -marketing'
+```
+
+This searches the description/title and must include software, summer, 2025, one of the languages, engineering intern exactly, no tax, no marketing.
 
 ---
 
@@ -227,8 +201,41 @@ You can specify the following countries when searching on Indeed (use the exact
 
 ---
 
-**Q: Encountering issues with your queries?**  
-**A:** Try reducing the number of `results_wanted` and/or broadening the filters. If problems
-persist, [submit an issue](https://github.com/Bunsly/JobSpy/issues).
+### JobPost Schema
 
----
+```plaintext
+JobPost
+├── title
+├── company
+├── company_url
+├── job_url
+├── location
+│   ├── country
+│   ├── city
+│   ├── state
+├── description
+├── job_type: fulltime, parttime, internship, contract
+├── job_function
+│   ├── interval: yearly, monthly, weekly, daily, hourly
+│   ├── min_amount
+│   ├── max_amount
+│   ├── currency
+│   └── salary_source: direct_data, description (parsed from posting)
+├── date_posted
+├── emails
+└── is_remote
+
+Linkedin specific
+└── job_level
+
+Linkedin & Indeed specific
+└── company_industry
+
+Indeed specific
+├── company_country
+├── company_addresses
+├── company_employees_label
+├── company_revenue_label
+├── company_description
+└── company_logo
+```

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "python-jobspy"
-version = "1.1.74"
+version = "1.1.75"
 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

@@ -24,6 +24,7 @@ from .scrapers.exceptions import (
 def scrape_jobs(
     site_name: str | list[str] | Site | list[Site] | None = None,
     search_term: str | None = None,
+    google_search_term: str | None = None,
     location: str | None = None,
     distance: int | None = 50,
     is_remote: bool = False,
@@ -86,6 +87,7 @@ def scrape_jobs(
         site_type=get_site_type(),
         country=country_enum,
         search_term=search_term,
+        google_search_term=google_search_term,
         location=location,
         distance=distance,
         is_remote=is_remote,
@@ -216,8 +218,8 @@ def scrape_jobs(
             "title",
             "company",
             "location",
-            "job_type",
             "date_posted",
+            "job_type",
             "salary_source",
             "interval",
             "min_amount",
@@ -248,6 +250,8 @@ def scrape_jobs(
         jobs_df = jobs_df[desired_order]
 
         # Step 4: Sort the DataFrame as required
-        return jobs_df.sort_values(by=["site", "date_posted"], ascending=[True, False])
+        return jobs_df.sort_values(
+            by=["site", "date_posted"], ascending=[True, False]
+        ).reset_index(drop=True)
     else:
         return pd.DataFrame()

src/jobspy/scrapers/__init__.py

@@ -28,6 +28,7 @@ class SalarySource(Enum):
 class ScraperInput(BaseModel):
     site_type: list[Site]
     search_term: str | None = None
+    google_search_term: str | None = None
 
     location: str | None = None
     country: Country | None = Country.USA

src/jobspy/scrapers/google/__init__.py

@@ -59,13 +59,14 @@ class GoogleJobsScraper(Scraper):
         self.session = create_session(
             proxies=self.proxies, ca_cert=self.ca_cert, is_tls=False, has_retry=True
         )
-        forward_cursor = self._get_initial_cursor()
+        forward_cursor, job_list = self._get_initial_cursor_and_jobs()
         if forward_cursor is None:
-            logger.error("initial cursor not found")
-            return JobResponse(jobs=[])
+            logger.warning(
+                "initial cursor not found, try changing your query or there was at most 10 results"
+            )
+            return JobResponse(jobs=job_list)
 
         page = 1
-        job_list: list[JobPost] = []
 
         while (
             len(self.seen_urls) < scraper_input.results_wanted + scraper_input.offset
@@ -74,7 +75,11 @@ class GoogleJobsScraper(Scraper):
             logger.info(
                 f"search page: {page} / {math.ceil(scraper_input.results_wanted / self.jobs_per_page)}"
             )
-            jobs, forward_cursor = self._get_jobs_next_page(forward_cursor)
+            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}")
+                break
             if not jobs:
                 logger.info(f"found no jobs on page: {page}")
                 break
@@ -87,8 +92,8 @@ class GoogleJobsScraper(Scraper):
             ]
         )
 
-    def _get_initial_cursor(self):
-        """Gets initial cursor to paginate through job listings"""
+    def _get_initial_cursor_and_jobs(self) -> Tuple[str, list[JobPost]]:
+        """Gets initial cursor and jobs to paginate through job listings"""
         query = f"{self.scraper_input.search_term} jobs"
 
         def get_time_range(hours_old):
@@ -121,13 +126,22 @@ class GoogleJobsScraper(Scraper):
         if self.scraper_input.is_remote:
             query += " remote"
 
+        if self.scraper_input.google_search_term:
+            query = self.scraper_input.google_search_term
+
         params = {"q": query, "udm": "8"}
         response = self.session.get(self.url, headers=headers_initial, params=params)
 
         pattern_fc = r'<div jsname="Yust4d"[^>]+data-async-fc="([^"]+)"'
         match_fc = re.search(pattern_fc, response.text)
         data_async_fc = match_fc.group(1) if match_fc else None
-        return data_async_fc
+        jobs_raw = self._find_job_info_initial_page(response.text)
+        jobs = []
+        for job_raw in jobs_raw:
+            job_post = self._parse_job(job_raw)
+            if job_post:
+                jobs.append(job_post)
+        return data_async_fc, jobs
 
     def _get_jobs_next_page(self, forward_cursor: str) -> Tuple[list[JobPost], str]:
         params = {"fc": [forward_cursor], "fcv": ["3"], "async": [async_param]}
@@ -147,55 +161,55 @@ class GoogleJobsScraper(Scraper):
         match_fc = re.search(pattern_fc, job_data)
         data_async_fc = match_fc.group(1) if match_fc else None
         jobs_on_page = []
-
         for array in parsed:
-
             _, job_data = array
             if not job_data.startswith("[[["):
                 continue
             job_d = json.loads(job_data)
 
             job_info = self._find_job_info(job_d)
-
-            job_url = job_info[3][0][0] if job_info[3] and job_info[3][0] else None
-            if job_url in self.seen_urls:
-                continue
-            self.seen_urls.add(job_url)
-
-            title = job_info[0]
-            company_name = job_info[1]
-            location = city = job_info[2]
-            state = country = date_posted = None
-            if location and "," in location:
-                city, state, *country = [*map(lambda x: x.strip(), location.split(","))]
-
-            days_ago_str = job_info[12]
-            if type(days_ago_str) == str:
-                match = re.search(r"\d+", days_ago_str)
-                days_ago = int(match.group()) if match else None
-                date_posted = (datetime.now() - timedelta(days=days_ago)).date()
-
-            description = job_info[19]
-
-            job_post = JobPost(
-                id=f"go-{job_info[28]}",
-                title=title,
-                company_name=company_name,
-                location=Location(
-                    city=city, state=state, country=country[0] if country else None
-                ),
-                job_url=job_url,
-                job_url_direct=job_url,
-                date_posted=date_posted,
-                is_remote="remote" in description.lower()
-                or "wfh" in description.lower(),
-                description=description,
-                emails=extract_emails_from_text(description),
-                job_type=extract_job_type(description),
-            )
-            jobs_on_page.append(job_post)
+            job_post = self._parse_job(job_info)
+            if job_post:
+                jobs_on_page.append(job_post)
         return jobs_on_page, data_async_fc
 
+    def _parse_job(self, job_info: list):
+        job_url = job_info[3][0][0] if job_info[3] and job_info[3][0] else None
+        if job_url in self.seen_urls:
+            return
+        self.seen_urls.add(job_url)
+
+        title = job_info[0]
+        company_name = job_info[1]
+        location = city = job_info[2]
+        state = country = date_posted = None
+        if location and "," in location:
+            city, state, *country = [*map(lambda x: x.strip(), location.split(","))]
+
+        days_ago_str = job_info[12]
+        if type(days_ago_str) == str:
+            match = re.search(r"\d+", days_ago_str)
+            days_ago = int(match.group()) if match else None
+            date_posted = (datetime.now() - timedelta(days=days_ago)).date()
+
+        description = job_info[19]
+
+        job_post = JobPost(
+            id=f"go-{job_info[28]}",
+            title=title,
+            company_name=company_name,
+            location=Location(
+                city=city, state=state, country=country[0] if country else None
+            ),
+            job_url=job_url,
+            date_posted=date_posted,
+            is_remote="remote" in description.lower() or "wfh" in description.lower(),
+            description=description,
+            emails=extract_emails_from_text(description),
+            job_type=extract_job_type(description),
+        )
+        return job_post
+
     @staticmethod
     def _find_job_info(jobs_data: list | dict) -> list | None:
         """Iterates through the JSON data to find the job listings"""
@@ -213,3 +227,24 @@ class GoogleJobsScraper(Scraper):
                 if result:
                     return result
         return None
+
+    @staticmethod
+    def _find_job_info_initial_page(html_text: str):
+        pattern = (
+            f'520084652":('
+            + r"\[(?:[^\[\]]|\[(?:[^\[\]]|\[(?:[^\[\]]|\[[^\[\]]*\])*\])*\])*\])"
+        )
+        results = []
+        matches = re.finditer(pattern, html_text)
+
+        import json
+
+        for match in matches:
+            try:
+                parsed_data = json.loads(match.group(1))
+                results.append(parsed_data)
+
+            except json.JSONDecodeError as e:
+                logger.error(f"Failed to parse match: {str(e)}")
+                results.append({"raw_match": match.group(0), "error": str(e)})
+        return results