fix: indeed empty search term

format: Apply Black formatter to the codebase (#127 )
docs: readme
2026-03-05 12:04:33 -08:00 · 2024-03-11 09:21:11 -05:00 · 2024-03-10 23:36:27 -05:00 · 2024-03-09 13:40:34 -06:00 · 2024-03-09 01:49:05 -06:00 · 2024-03-09 01:40:01 -06:00
12 changed files with 1417 additions and 853 deletions
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -0,0 +1,7 @@
 repos:
 - repo: https://github.com/psf/black
  rev: 24.2.0
  hooks:
  - id: black
    language_version: python
    args: [--line-length=88, --quiet]
--- a/README.md
+++ b/README.md
@@ -11,7 +11,7 @@ work with us.*
 - Scrapes job postings from **LinkedIn**, **Indeed**, **Glassdoor**, & **ZipRecruiter** simultaneously
 - Aggregates the job postings in a Pandas DataFrame
- Proxy support (HTTP/S, SOCKS)
+- Proxy support
 [Video Guide for JobSpy](https://www.youtube.com/watch?v=RuP1HrAZnxs&pp=ygUgam9icyBzY3JhcGVyIGJvdCBsaW5rZWRpbiBpbmRlZWQ%3D) -
 Updated for release v1.1.3
@@ -21,7 +21,7 @@ Updated for release v1.1.3
 ### Installation
 ```
-pip install python-jobspy
+pip install -U python-jobspy
 ```
 _Python version >= [3.10](https://www.python.org/downloads/release/python-3100/) required_
@@ -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/Indeed 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
@@ -62,17 +64,19 @@ Required
 ├── site_type (List[enum]): linkedin, zip_recruiter, indeed, glassdoor
 └── search_term (str)
 Optional
-├── location (int)
+├── location (str)
-├── distance (int): in miles
+├── distance (int): in miles, default 50
 ├── job_type (enum): fulltime, parttime, internship, contract
-├── proxy (str): in format 'http://user:pass@host:port' or [https, socks]
+├── proxy (str): in format 'http://user:pass@host:port'
 ├── is_remote (bool)
-├── full_description (bool): fetches full description for Indeed / LinkedIn (much slower)
+├── linkedin_fetch_description (bool): fetches full description for LinkedIn (slower)
 ├── results_wanted (int): number of job results to retrieve for each site specified in 'site_type'
-├── easy_apply (bool): filters for jobs that are hosted on the job board site
+├── easy_apply (bool): filters for jobs that are hosted on the job board site (not supported on Indeed)
 ├── linkedin_company_ids (list[int): searches for linkedin jobs with specific company ids
 ├── description_format (enum): markdown, html (format type of the job descriptions)
 ├── 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 (ZipRecruiter and Glassdoor round up to next day. If you use this on Indeed, it will not filter by job_type or is_remote)
 ```
 ### JobPost Schema
@@ -96,24 +100,26 @@ JobPost
 │   └── currency (enum)
 └── date_posted (date)
 └── emails (str)
 └── num_urgent_words (int)
 └── is_remote (bool)
 Indeed specific
 ├── company_country (str)
 └── company_addresses (str)
 └── company_industry (str)
 └── company_employees_label (str)
 └── company_revenue_label (str)
 └── company_description (str)
 └── ceo_name (str)
 └── ceo_photo_url (str)
 └── logo_photo_url (str)
 └── banner_photo_url (str)
 ```
 ### Exceptions
 The following exceptions may be raised when using JobSpy:
 * `LinkedInException`
 * `IndeedException`
 * `ZipRecruiterException`
 * `GlassdoorException`
 ## Supported Countries for Job Searching
 ### **LinkedIn**
-LinkedIn searches globally & uses only the `location` parameter. You can only fetch 1000 jobs max from the LinkedIn endpoint we're using
+LinkedIn searches globally & uses only the `location` parameter. You can only fetch 1000 jobs max from the LinkedIn endpoint we are using
 ### **ZipRecruiter**
@@ -143,10 +149,14 @@ You can specify the following countries when searching on Indeed (use the exact
 | South Korea          | Spain*       | Sweden     | Switzerland*   |
 | Taiwan               | Thailand     | Turkey     | Ukraine        |
 | United Arab Emirates | UK*          | USA*       | Uruguay        |
-| Venezuela            | Vietnam      |            |                |
+| Venezuela            | Vietnam*     |            |                |
-Glassdoor can only fetch 900 jobs from the endpoint we're using on a given search.
+## Notes
 * Indeed is the best scraper currently with no rate limiting.  
 * Glassdoor/Ziprecruiter can only fetch 900/1000 jobs from the endpoints we are using on a given search.  
 * LinkedIn is the most restrictive and usually rate limits around the 10th page.
 ## Frequently Asked Questions
 ---
@@ -164,7 +174,3 @@ persist, [submit an issue](https://github.com/Bunsly/JobSpy/issues).
 - Trying a VPN or proxy to change your IP address.
 ---
--- a/poetry.lock
+++ b/poetry.lock
@@ -203,6 +203,52 @@ soupsieve = ">1.2"
 html5lib = ["html5lib"]
 lxml = ["lxml"]
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@@ -308,6 +354,17 @@ files = [
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@@ -392,6 +449,20 @@ files = [
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@@ -471,6 +542,17 @@ files = [
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@@ -513,6 +595,22 @@ files = [
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@@ -1026,6 +1138,21 @@ files = [
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@@ -1387,6 +1539,17 @@ files = [
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@@ -1442,6 +1605,24 @@ files = [
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@@ -2168,6 +2349,22 @@ nativelib = ["pyobjc-framework-Cocoa", "pywin32"]
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 name = "six"
 version = "1.16.0"
@@ -2260,13 +2457,13 @@ test = ["flake8", "isort", "pytest"]
 [[package]]
 name = "tls-client"
-version = "1.0"
+version = "1.0.1"
 description = "Advanced Python HTTP Client."
 optional = false
 python-versions = "*"
 files = [
-    {file = "tls_client-1.0-py3-none-any.whl", hash = "sha256:f1183f5e18cb31914bd62d11b350a33ea0293ea80fb91d69a3072821dece3e66"},
+    {file = "tls_client-1.0.1-py3-none-any.whl", hash = "sha256:2f8915c0642c2226c9e33120072a2af082812f6310d32f4ea4da322db7d3bb1c"},
-    {file = "tls_client-1.0.tar.gz", hash = "sha256:7f6de48ad4a0ef69b72682c76ce604155971e07b4bfb2148a36276194ae3e7a0"},
+    {file = "tls_client-1.0.1.tar.gz", hash = "sha256:dad797f3412bb713606e0765d489f547ffb580c5ffdb74aed47a183ce8505ff5"},
 ]
 [[package]]
@@ -2368,6 +2565,26 @@ secure = ["certifi", "cryptography (>=1.9)", "idna (>=2.0.0)", "pyopenssl (>=17.
 socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
 zstd = ["zstandard (>=0.18.0)"]
 [[package]]
 name = "virtualenv"
 version = "20.25.1"
 description = "Virtual Python Environment builder"
 optional = false
 python-versions = ">=3.7"
 files = [
    {file = "virtualenv-20.25.1-py3-none-any.whl", hash = "sha256:961c026ac520bac5f69acb8ea063e8a4f071bcc9457b9c1f28f6b085c511583a"},
    {file = "virtualenv-20.25.1.tar.gz", hash = "sha256:e08e13ecdca7a0bd53798f356d5831434afa5b07b93f0abdf0797b7a06ffe197"},
 ]
 [package.dependencies]
 distlib = ">=0.3.7,<1"
 filelock = ">=3.12.2,<4"
 platformdirs = ">=3.9.1,<5"
 [package.extras]
 docs = ["furo (>=2023.7.26)", "proselint (>=0.13)", "sphinx (>=7.1.2)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.6)"]
 test = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=23.1)", "pytest (>=7.4)", "pytest-env (>=0.8.2)", "pytest-freezer (>=0.4.8)", "pytest-mock (>=3.11.1)", "pytest-randomly (>=3.12)", "pytest-timeout (>=2.1)", "setuptools (>=68)", "time-machine (>=2.10)"]
 [[package]]
 name = "wcwidth"
 version = "0.2.6"
@@ -2435,4 +2652,4 @@ files = [
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10"
-content-hash = "404a77d78066cbb2ef71015562baf44aa11d12aac29a191c1ccc7758bfda598a"
+content-hash = "6ee18819a726314f61f20f0ed93b2db2a26c232269f045146d9a8f4e3f31eb01"
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "python-jobspy"
-version = "1.1.42"
+version = "1.1.49"
 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"
@@ -13,17 +13,23 @@ packages = [
 [tool.poetry.dependencies]
 python = "^3.10"
 requests = "^2.31.0"
 tls-client = "*"
 beautifulsoup4 = "^4.12.2"
 pandas = "^2.1.0"
 NUMPY = "1.24.2"
 pydantic = "^2.3.0"
 tls-client = "^1.0.1"
 markdownify = "^0.11.6"
 [tool.poetry.group.dev.dependencies]
 pytest = "^7.4.1"
 jupyter = "^1.0.0"
 black = "^24.2.0"
 pre-commit = "^3.6.2"
 [build-system]
 requires = ["poetry-core"]
 build-backend = "poetry.core.masonry.api"
 [tool.black]
 line-length = 88
--- a/src/jobspy/init.py
+++ b/src/jobspy/init.py
@@ -1,9 +1,11 @@
 from __future__ import annotations
 import pandas as pd
 from typing import Tuple
-import concurrent.futures
+from concurrent.futures import ThreadPoolExecutor, as_completed
 from concurrent.futures import ThreadPoolExecutor
 from .jobs import JobType, Location
 from .scrapers.utils import logger
 from .scrapers.indeed import IndeedScraper
 from .scrapers.ziprecruiter import ZipRecruiterScraper
 from .scrapers.glassdoor import GlassdoorScraper
@@ -16,23 +18,12 @@ from .scrapers.exceptions import (
    GlassdoorException,
 )
 SCRAPER_MAPPING = {
    Site.LINKEDIN: LinkedInScraper,
    Site.INDEED: IndeedScraper,
    Site.ZIP_RECRUITER: ZipRecruiterScraper,
    Site.GLASSDOOR: GlassdoorScraper,
 }
 def _map_str_to_site(site_name: str) -> Site:
    return Site[site_name.upper()]
 def scrape_jobs(
    site_name: str | list[str] | Site | list[Site] | None = None,
    search_term: str | None = None,
    location: str | None = None,
-    distance: int | None = None,
+    distance: int | None = 50,
    is_remote: bool = False,
    job_type: str | None = None,
    easy_apply: bool | None = None,
@@ -40,14 +31,26 @@ def scrape_jobs(
    country_indeed: str = "usa",
    hyperlinks: bool = False,
    proxy: str | None = None,
-    full_description: bool | None = False,
+    description_format: str = "markdown",
    linkedin_fetch_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.
    :return: results_wanted: pandas dataframe containing job data
    """
    SCRAPER_MAPPING = {
        Site.LINKEDIN: LinkedInScraper,
        Site.INDEED: IndeedScraper,
        Site.ZIP_RECRUITER: ZipRecruiterScraper,
        Site.GLASSDOOR: GlassdoorScraper,
    }
    def map_str_to_site(site_name: str) -> Site:
        return Site[site_name.upper()]
    def get_enum_from_value(value_str):
        for job_type in JobType:
@@ -60,12 +63,12 @@ def scrape_jobs(
    def get_site_type():
        site_types = list(Site)
        if isinstance(site_name, str):
-            site_types = [_map_str_to_site(site_name)]
+            site_types = [map_str_to_site(site_name)]
        elif isinstance(site_name, Site):
            site_types = [site_name]
        elif isinstance(site_name, list):
            site_types = [
-                _map_str_to_site(site) if isinstance(site, str) else site
+                map_str_to_site(site) if isinstance(site, str) else site
                for site in site_name
            ]
        return site_types
@@ -81,31 +84,21 @@ def scrape_jobs(
        is_remote=is_remote,
        job_type=job_type,
        easy_apply=easy_apply,
-        full_description=full_description,
+        description_format=description_format,
        linkedin_fetch_description=linkedin_fetch_description,
        results_wanted=results_wanted,
        linkedin_company_ids=linkedin_company_ids,
        offset=offset,
        hours_old=hours_old,
    )
    def scrape_site(site: Site) -> Tuple[str, JobResponse]:
        scraper_class = SCRAPER_MAPPING[site]
        scraper = scraper_class(proxy=proxy)
-
+        scraped_data: JobResponse = scraper.scrape(scraper_input)
-        try:
+        cap_name = site.value.capitalize()
-            scraped_data: JobResponse = scraper.scrape(scraper_input)
+        site_name = "ZipRecruiter" if cap_name == "Zip_recruiter" else cap_name
-        except (LinkedInException, IndeedException, ZipRecruiterException) as lie:
+        logger.info(f"{site_name} finished scraping")
            raise lie
        except Exception as e:
            if site == Site.LINKEDIN:
                raise LinkedInException(str(e))
            if site == Site.INDEED:
                raise IndeedException(str(e))
            if site == Site.ZIP_RECRUITER:
                raise ZipRecruiterException(str(e))
            if site == Site.GLASSDOOR:
                raise GlassdoorException(str(e))
            else:
                raise e
        return site.value, scraped_data
    site_to_jobs_dict = {}
@@ -119,7 +112,7 @@ def scrape_jobs(
            executor.submit(worker, site): site for site in scraper_input.site_type
        }
-        for future in concurrent.futures.as_completed(future_to_site):
+        for future in as_completed(future_to_site):
            site_value, scraped_data = future.result()
            site_to_jobs_dict[site_value] = scraped_data
@@ -128,9 +121,8 @@ def scrape_jobs(
    for site, job_response in site_to_jobs_dict.items():
        for job in job_response.jobs:
            job_data = job.dict()
-            job_data[
+            job_url = job_data["job_url"]
-                "job_url_hyper"
+            job_data["job_url_hyper"] = f'<a href="{job_url}">{job_url}</a>'
            ] = f'<a href="{job_data["job_url"]}">{job_data["job_url"]}</a>'
            job_data["site"] = site
            job_data["company"] = job_data["company_name"]
            job_data["job_type"] = (
@@ -166,13 +158,19 @@ def scrape_jobs(
            jobs_dfs.append(job_df)
    if jobs_dfs:
-        jobs_df = pd.concat(jobs_dfs, ignore_index=True)
+        # Step 1: Filter out all-NA columns from each DataFrame before concatenation
-        desired_order: list[str] = [
+        filtered_dfs = [df.dropna(axis=1, how="all") for df in jobs_dfs]
-            "job_url_hyper" if hyperlinks else "job_url",
+
        # Step 2: Concatenate the filtered DataFrames
        jobs_df = pd.concat(filtered_dfs, ignore_index=True)
        # Desired column order
        desired_order = [
            "site",
            "job_url_hyper" if hyperlinks else "job_url",
            "job_url_direct",
            "title",
            "company",
            "company_url",
            "location",
            "job_type",
            "date_posted",
@@ -181,13 +179,30 @@ def scrape_jobs(
            "max_amount",
            "currency",
            "is_remote",
            "num_urgent_words",
            "benefits",
            "emails",
            "description",
            "company_url",
            "company_url_direct",
            "company_addresses",
            "company_industry",
            "company_num_employees",
            "company_revenue",
            "company_description",
            "logo_photo_url",
            "banner_photo_url",
            "ceo_name",
            "ceo_photo_url",
        ]
        jobs_formatted_df = jobs_df[desired_order]
    else:
        jobs_formatted_df = pd.DataFrame()
-    return jobs_formatted_df
+        # Step 3: Ensure all desired columns are present, adding missing ones as empty
        for column in desired_order:
            if column not in jobs_df.columns:
                jobs_df[column] = None  # Add missing columns as empty
        # Reorder the DataFrame according to the desired order
        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])
    else:
        return pd.DataFrame()
--- a/src/jobspy/jobs/init.py
+++ b/src/jobspy/jobs/init.py
@@ -1,3 +1,5 @@
 from __future__ import annotations
 from typing import Optional
 from datetime import date
 from enum import Enum
@@ -57,7 +59,7 @@ class JobType(Enum):
 class Country(Enum):
    """
    Gets the subdomain for Indeed and Glassdoor.
-    The second item in the tuple is the subdomain for Indeed
+    The second item in the tuple is the subdomain (and API country code if there's a ':' separator) for Indeed
    The third item in the tuple is the subdomain (and tld if there's a ':' separator) for Glassdoor
    """
@@ -118,11 +120,11 @@ class Country(Enum):
    TURKEY = ("turkey", "tr")
    UKRAINE = ("ukraine", "ua")
    UNITEDARABEMIRATES = ("united arab emirates", "ae")
-    UK = ("uk,united kingdom", "uk", "co.uk")
+    UK = ("uk,united kingdom", "uk:gb", "co.uk")
-    USA = ("usa,us,united states", "www", "com")
+    USA = ("usa,us,united states", "www:us", "com")
    URUGUAY = ("uruguay", "uy")
    VENEZUELA = ("venezuela", "ve")
-    VIETNAM = ("vietnam", "vn")
+    VIETNAM = ("vietnam", "vn", "com")
    # internal for ziprecruiter
    US_CANADA = ("usa/ca", "www")
@@ -132,7 +134,10 @@ class Country(Enum):
    @property
    def indeed_domain_value(self):
-        return self.value[1]
+        subdomain, _, api_country_code = self.value[1].partition(":")
        if subdomain and api_country_code:
            return subdomain, api_country_code.upper()
        return self.value[1], self.value[1].upper()
    @property
    def glassdoor_domain_value(self):
@@ -145,7 +150,7 @@ class Country(Enum):
        else:
            raise Exception(f"Glassdoor is not available for {self.name}")
-    def get_url(self):
+    def get_glassdoor_url(self):
        return f"https://{self.glassdoor_domain_value}/"
    @classmethod
@@ -153,7 +158,7 @@ class Country(Enum):
        """Convert a string to the corresponding Country enum."""
        country_str = country_str.strip().lower()
        for country in cls:
-            country_names = country.value[0].split(',')
+            country_names = country.value[0].split(",")
            if country_str in country_names:
                return country
        valid_countries = [country.value for country in cls]
@@ -163,7 +168,7 @@ class Country(Enum):
 class Location(BaseModel):
-    country: Country | None = None
+    country: Country | str | None = None
    city: Optional[str] = None
    state: Optional[str] = None
@@ -173,7 +178,12 @@ class Location(BaseModel):
            location_parts.append(self.city)
        if self.state:
            location_parts.append(self.state)
-        if self.country and self.country not in (Country.US_CANADA, Country.WORLDWIDE):
+        if isinstance(self.country, str):
            location_parts.append(self.country)
        elif self.country and self.country not in (
            Country.US_CANADA,
            Country.WORLDWIDE,
        ):
            country_name = self.country.value[0]
            if "," in country_name:
                country_name = country_name.split(",")[0]
@@ -193,33 +203,55 @@ class CompensationInterval(Enum):
    @classmethod
    def get_interval(cls, pay_period):
-        return cls[pay_period].value if pay_period in cls.__members__ else None
+        interval_mapping = {
            "YEAR": cls.YEARLY,
            "HOUR": cls.HOURLY,
        }
        if pay_period in interval_mapping:
            return interval_mapping[pay_period].value
        else:
            return cls[pay_period].value if pay_period in cls.__members__ else None
 class Compensation(BaseModel):
    interval: Optional[CompensationInterval] = None
-    min_amount: int | None = None
+    min_amount: float | None = None
-    max_amount: int | None = None
+    max_amount: float | None = None
    currency: Optional[str] = "USD"
 class DescriptionFormat(Enum):
    MARKDOWN = "markdown"
    HTML = "html"
 class JobPost(BaseModel):
    title: str
-    company_name: str
+    company_name: str | None
    job_url: str
    job_url_direct: str | None = None
    location: Optional[Location]
    description: str | None = None
    company_url: str | None = None
    company_url_direct: str | None = None
    job_type: list[JobType] | None = None
    compensation: Compensation | None = None
    date_posted: date | None = None
    benefits: str | None = None
    emails: list[str] | None = None
    num_urgent_words: int | None = None
    is_remote: bool | None = None
-    # company_industry: str | None = None
+
    # indeed specific
    company_addresses: str | None = None
    company_industry: str | None = None
    company_num_employees: str | None = None
    company_revenue: str | None = None
    company_description: str | None = None
    ceo_name: str | None = None
    ceo_photo_url: str | None = None
    logo_photo_url: str | None = None
    banner_photo_url: str | None = None
 class JobResponse(BaseModel):
--- a/src/jobspy/scrapers/init.py
+++ b/src/jobspy/scrapers/init.py
@@ -1,4 +1,13 @@
-from ..jobs import Enum, BaseModel, JobType, JobResponse, Country
+from __future__ import annotations
 from ..jobs import (
    Enum,
    BaseModel,
    JobType,
    JobResponse,
    Country,
    DescriptionFormat,
 )
 class Site(Enum):
@@ -18,11 +27,13 @@ class ScraperInput(BaseModel):
    is_remote: bool = False
    job_type: JobType | None = None
    easy_apply: bool | None = None
    full_description: bool = False
    offset: int = 0
    linkedin_fetch_description: bool = False
    linkedin_company_ids: list[int] | None = None
    description_format: DescriptionFormat | None = DescriptionFormat.MARKDOWN
    results_wanted: int = 15
    hours_old: int | None = None
 class Scraper:
@@ -30,5 +41,4 @@ 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: ...
        ...
--- a/src/jobspy/scrapers/glassdoor/init.py
+++ b/src/jobspy/scrapers/glassdoor/init.py
@@ -4,17 +4,24 @@ jobspy.scrapers.glassdoor
 This module contains routines to scrape Glassdoor.
 """
 from __future__ import annotations
 import re
 import json
 import requests
-from bs4 import BeautifulSoup
+from typing import Optional, Tuple
 from typing import Optional
 from datetime import datetime, timedelta
 from concurrent.futures import ThreadPoolExecutor, as_completed
 from ..utils import count_urgent_words, extract_emails_from_text
 from .. import Scraper, ScraperInput, Site
 from ..utils import extract_emails_from_text
 from ..exceptions import GlassdoorException
-from ..utils import create_session, modify_and_get_description
+from ..utils import (
    create_session,
    markdown_converter,
    logger,
 )
 from ...jobs import (
    JobPost,
    Compensation,
@@ -22,6 +29,7 @@ from ...jobs import (
    Location,
    JobResponse,
    JobType,
    DescriptionFormat,
 )
@@ -33,74 +41,142 @@ class GlassdoorScraper(Scraper):
        site = Site(Site.GLASSDOOR)
        super().__init__(site, proxy=proxy)
-        self.url = None
+        self.base_url = None
        self.country = None
        self.session = None
        self.scraper_input = None
        self.jobs_per_page = 30
        self.max_pages = 30
        self.seen_urls = set()
-    def fetch_jobs_page(
+    def scrape(self, scraper_input: ScraperInput) -> JobResponse:
        """
        Scrapes Glassdoor for jobs with scraper_input criteria.
        :param scraper_input: Information about job search criteria.
        :return: JobResponse containing a list of jobs.
        """
        self.scraper_input = scraper_input
        self.scraper_input.results_wanted = min(900, scraper_input.results_wanted)
        self.base_url = self.scraper_input.country.get_glassdoor_url()
        self.session = create_session(self.proxy, is_tls=True, has_retry=True)
        token = self._get_csrf_token()
        self.headers["gd-csrf-token"] = token if token else self.fallback_token
        location_id, location_type = self._get_location(
            scraper_input.location, scraper_input.is_remote
        )
        if location_type is None:
            logger.error("Glassdoor: location not parsed")
            return JobResponse(jobs=[])
        all_jobs: list[JobPost] = []
        cursor = None
        range_start = 1 + (scraper_input.offset // self.jobs_per_page)
        tot_pages = (scraper_input.results_wanted // self.jobs_per_page) + 2
        range_end = min(tot_pages, self.max_pages + 1)
        for page in range(range_start, range_end):
            logger.info(f"Glassdoor search page: {page}")
            try:
                jobs, cursor = self._fetch_jobs_page(
                    scraper_input, location_id, location_type, page, cursor
                )
                all_jobs.extend(jobs)
                if not jobs or len(all_jobs) >= scraper_input.results_wanted:
                    all_jobs = all_jobs[: scraper_input.results_wanted]
                    break
            except Exception as e:
                logger.error(f"Glassdoor: {str(e)}")
                break
        return JobResponse(jobs=all_jobs)
    def _fetch_jobs_page(
        self,
        scraper_input: ScraperInput,
        location_id: int,
        location_type: str,
        page_num: int,
        cursor: str | None,
-    ) -> (list[JobPost], str | None):
+    ) -> Tuple[list[JobPost], str | None]:
        """
        Scrapes a page of Glassdoor for jobs with scraper_input criteria
        """
        jobs = []
        self.scraper_input = scraper_input
        try:
-            payload = self.add_payload(
+            payload = self._add_payload(location_id, location_type, page_num, cursor)
-                scraper_input, location_id, location_type, page_num, cursor
+            response = self.session.post(
-            )
+                f"{self.base_url}/graph",
-            session = create_session(self.proxy, is_tls=False, has_retry=True)
+                headers=self.headers,
-            response = session.post(
+                timeout_seconds=15,
-                f"{self.url}/graph", headers=self.headers(), timeout=10, data=payload
+                data=payload,
            )
            if response.status_code != 200:
-                raise GlassdoorException(
+                exc_msg = f"bad response status code: {response.status_code}"
-                    f"bad response status code: {response.status_code}"
+                raise GlassdoorException(exc_msg)
                )
            res_json = response.json()[0]
            if "errors" in res_json:
                raise ValueError("Error encountered in API response")
-        except Exception as e:
+        except (
-            raise GlassdoorException(str(e))
+            requests.exceptions.ReadTimeout,
            GlassdoorException,
            ValueError,
            Exception,
        ) as e:
            logger.error(f"Glassdoor: {str(e)}")
            return jobs, None
        jobs_data = res_json["data"]["jobListings"]["jobListings"]
        jobs = []
        with ThreadPoolExecutor(max_workers=self.jobs_per_page) as executor:
-            future_to_job_data = {executor.submit(self.process_job, job): job for job in jobs_data}
+            future_to_job_data = {
                executor.submit(self._process_job, job): job for job in jobs_data
            }
            for future in as_completed(future_to_job_data):
                job_data = future_to_job_data[future]
                try:
                    job_post = future.result()
                    if job_post:
                        jobs.append(job_post)
                except Exception as exc:
-                    raise GlassdoorException(f'Glassdoor generated an exception: {exc}')
+                    raise GlassdoorException(f"Glassdoor generated an exception: {exc}")
        return jobs, self.get_cursor_for_page(
            res_json["data"]["jobListings"]["paginationCursors"], page_num + 1
        )
-    def process_job(self, job_data):
+    def _get_csrf_token(self):
-        """Processes a single job and fetches its description."""
+        """
        Fetches csrf token needed for API by visiting a generic page
        """
        res = self.session.get(
            f"{self.base_url}/Job/computer-science-jobs.htm", headers=self.headers
        )
        pattern = r'"token":\s*"([^"]+)"'
        matches = re.findall(pattern, res.text)
        token = None
        if matches:
            token = matches[0]
        return token
    def _process_job(self, job_data):
        """
        Processes a single job and fetches its description.
        """
        job_id = job_data["jobview"]["job"]["listingId"]
-        job_url = f'{self.url}job-listing/j?jl={job_id}'
+        job_url = f"{self.base_url}job-listing/j?jl={job_id}"
        if job_url in self.seen_urls:
            return None
        self.seen_urls.add(job_url)
        job = job_data["jobview"]
        title = job["job"]["jobTitleText"]
        company_name = job["header"]["employerNameFromSearch"]
-        company_id = job_data['jobview']['header']['employer']['id']
+        company_id = job_data["jobview"]["header"]["employer"]["id"]
        location_name = job["header"].get("locationName", "")
        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_diff = (datetime.now() - timedelta(days=age_in_days)).date()
        date_posted = date_diff if age_in_days is not None else None
        if location_type == "S":
            is_remote = True
@@ -108,15 +184,14 @@ class GlassdoorScraper(Scraper):
            location = self.parse_location(location_name)
        compensation = self.parse_compensation(job["header"])
        try:
-            description = self.fetch_job_description(job_id)
+            description = self._fetch_job_description(job_id)
-        except Exception as e :
+        except:
            description = None
-
+        company_url = f"{self.base_url}Overview/W-EI_IE{company_id}.htm"
-        job_post = JobPost(
+        return JobPost(
            title=title,
-            company_url=f"{self.url}Overview/W-EI_IE{company_id}.htm" if company_id else None,
+            company_url=company_url if company_id else None,
            company_name=company_name,
            date_posted=date_posted,
            job_url=job_url,
@@ -125,60 +200,20 @@ class GlassdoorScraper(Scraper):
            is_remote=is_remote,
            description=description,
            emails=extract_emails_from_text(description) if description else None,
            num_urgent_words=count_urgent_words(description) if description else None,
        )
        return job_post
-    def scrape(self, scraper_input: ScraperInput) -> JobResponse:
+    def _fetch_job_description(self, job_id):
        """
-        Scrapes Glassdoor for jobs with scraper_input criteria.
+        Fetches the job description for a single job ID.
        :param scraper_input: Information about job search criteria.
        :return: JobResponse containing a list of jobs.
        """
-        scraper_input.results_wanted = min(900, scraper_input.results_wanted)
+        url = f"{self.base_url}/graph"
        self.country = scraper_input.country
        self.url = self.country.get_url()
        location_id, location_type = self.get_location(
            scraper_input.location, scraper_input.is_remote
        )
        all_jobs: list[JobPost] = []
        cursor = None
        max_pages = 30
        try:
            for page in range(
                1 + (scraper_input.offset // self.jobs_per_page),
                min(
                    (scraper_input.results_wanted // self.jobs_per_page) + 2,
                    max_pages + 1,
                ),
            ):
                try:
                    jobs, cursor = self.fetch_jobs_page(
                        scraper_input, location_id, location_type, page, cursor
                    )
                    all_jobs.extend(jobs)
                    if len(all_jobs) >= scraper_input.results_wanted:
                        all_jobs = all_jobs[: scraper_input.results_wanted]
                        break
                except Exception as e:
                    raise GlassdoorException(str(e))
        except Exception as e:
            raise GlassdoorException(str(e))
        return JobResponse(jobs=all_jobs)
    def fetch_job_description(self, job_id):
        """Fetches the job description for a single job ID."""
        url = f"{self.url}/graph"
        body = [
            {
                "operationName": "JobDetailQuery",
                "variables": {
                    "jl": job_id,
                    "queryString": "q",
-                    "pageTypeEnum": "SERP"
+                    "pageTypeEnum": "SERP",
                },
                "query": """
                query JobDetailQuery($jl: Long!, $queryString: String, $pageTypeEnum: PageTypeEnum) {
@@ -193,23 +228,90 @@ class GlassdoorScraper(Scraper):
                        __typename
                    }
                }
-                """
+                """,
            }
        ]
-        response = requests.post(url, json=body, headers=GlassdoorScraper.headers())
+        res = requests.post(url, json=body, headers=self.headers)
-        if response.status_code != 200:
+        if res.status_code != 200:
            return None
-        data = response.json()[0]
+        data = res.json()[0]
-        desc = data['data']['jobview']['job']['description']
+        desc = data["data"]["jobview"]["job"]["description"]
-        soup = BeautifulSoup(desc, 'html.parser')
+        if self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
-        return modify_and_get_description(soup)
+            desc = markdown_converter(desc)
        return desc
    def _get_location(self, location: str, is_remote: bool) -> (int, str):
        if not location or is_remote:
            return "11047", "STATE"  # remote options
        url = f"{self.base_url}/findPopularLocationAjax.htm?maxLocationsToReturn=10&term={location}"
        session = create_session(self.proxy, has_retry=True)
        res = self.session.get(url, headers=self.headers)
        if res.status_code != 200:
            if res.status_code == 429:
                err = f"429 Response - Blocked by Glassdoor for too many requests"
                logger.error(err)
                return None, None
            else:
                err = f"Glassdoor response status code {res.status_code}"
                err += f" - {res.text}"
                logger.error(f"Glassdoor response status code {res.status_code}")
                return None, None
        items = res.json()
        if not items:
            raise ValueError(f"Location '{location}' not found on Glassdoor")
        location_type = items[0]["locationType"]
        if location_type == "C":
            location_type = "CITY"
        elif location_type == "S":
            location_type = "STATE"
        elif location_type == "N":
            location_type = "COUNTRY"
        return int(items[0]["locationId"]), location_type
    def _add_payload(
        self,
        location_id: int,
        location_type: str,
        page_num: int,
        cursor: str | None = None,
    ) -> str:
        fromage = None
        if self.scraper_input.hours_old:
            fromage = max(self.scraper_input.hours_old // 24, 1)
        filter_params = []
        if self.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": filter_params,
                "keyword": self.scraper_input.search_term,
                "numJobsToShow": 30,
                "locationType": location_type,
                "locationId": int(location_id),
                "parameterUrlInput": f"IL.0,12_I{location_type}{location_id}",
                "pageNumber": page_num,
                "pageCursor": cursor,
                "fromage": fromage,
                "sort": "date",
            },
            "query": self.query_template,
        }
        if self.scraper_input.job_type:
            payload["variables"]["filterParams"].append(
                {"filterKey": "jobType", "values": self.scraper_input.job_type.value[0]}
            )
        return json.dumps([payload])
    @staticmethod
    def parse_compensation(data: dict) -> Optional[Compensation]:
        pay_period = data.get("payPeriod")
        adjusted_pay = data.get("payPeriodAdjustedPay")
        currency = data.get("payCurrency", "USD")
        if not pay_period or not adjusted_pay:
            return None
@@ -220,7 +322,6 @@ class GlassdoorScraper(Scraper):
            interval = CompensationInterval.get_interval(pay_period)
        min_amount = int(adjusted_pay.get("p10") // 1)
        max_amount = int(adjusted_pay.get("p90") // 1)
        return Compensation(
            interval=interval,
            min_amount=min_amount,
@@ -228,67 +329,6 @@ class GlassdoorScraper(Scraper):
            currency=currency,
        )
    def get_location(self, location: str, is_remote: bool) -> (int, str):
        if not location or is_remote:
            return "11047", "STATE"  # remote options
        url = f"{self.url}/findPopularLocationAjax.htm?maxLocationsToReturn=10&term={location}"
        session = create_session(self.proxy, has_retry=True)
        response = session.get(url)
        if response.status_code != 200:
            raise GlassdoorException(
                f"bad response status code: {response.status_code}"
            )
        items = response.json()
        if not items:
            raise ValueError(f"Location '{location}' not found on Glassdoor")
        location_type = items[0]["locationType"]
        if location_type == "C":
            location_type = "CITY"
        elif location_type == "S":
            location_type = "STATE"
        elif location_type == 'N':
            location_type = "COUNTRY"
        return int(items[0]["locationId"]), location_type
    @staticmethod
    def add_payload(
        scraper_input,
        location_id: int,
        location_type: str,
        page_num: int,
        cursor: str | None = None,
    ) -> str:
        payload = {
            "operationName": "JobSearchResultsQuery",
            "variables": {
                "excludeJobListingIds": [],
                "filterParams": [{"filterKey": "applicationType", "values": "1"}] if scraper_input.easy_apply else [],
                "keyword": scraper_input.search_term,
                "numJobsToShow": 30,
                "locationType": location_type,
                "locationId": int(location_id),
                "parameterUrlInput": f"IL.0,12_I{location_type}{location_id}",
                "pageNumber": page_num,
                "pageCursor": cursor,
            },
            "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",
        }
        job_type_filters = {
            JobType.FULL_TIME: "fulltime",
            JobType.PART_TIME: "parttime",
            JobType.CONTRACT: "contract",
            JobType.INTERNSHIP: "internship",
            JobType.TEMPORARY: "temporary",
        }
        if scraper_input.job_type in job_type_filters:
            filter_value = job_type_filters[scraper_input.job_type]
            payload["variables"]["filterParams"].append(
                {"filterKey": "jobType", "values": filter_value}
            )
        return json.dumps([payload])
    @staticmethod
    def get_job_type_enum(job_type_str: str) -> list[JobType] | None:
        for job_type in JobType:
@@ -308,28 +348,187 @@ class GlassdoorScraper(Scraper):
            if cursor_data["pageNumber"] == page_num:
                return cursor_data["cursor"]
-    @staticmethod
+    fallback_token = "Ft6oHEWlRZrxDww95Cpazw:0pGUrkb2y3TyOpAIqF2vbPmUXoXVkD3oEGDVkvfeCerceQ5-n8mBg3BovySUIjmCPHCaW0H2nQVdqzbtsYqf4Q:wcqRqeegRUa9MVLJGyujVXB7vWFPjdaS1CtrrzJq-ok"
-    def headers() -> dict:
+    headers = {
-        """
+        "authority": "www.glassdoor.com",
-        Returns headers needed for requests
+        "accept": "*/*",
-        :return: dict - Dictionary containing headers
+        "accept-language": "en-US,en;q=0.9",
-        """
+        "apollographql-client-name": "job-search-next",
-        return {
+        "apollographql-client-version": "4.65.5",
-            "authority": "www.glassdoor.com",
+        "content-type": "application/json",
-            "accept": "*/*",
+        "origin": "https://www.glassdoor.com",
-            "accept-language": "en-US,en;q=0.9",
+        "referer": "https://www.glassdoor.com/",
-            "apollographql-client-name": "job-search-next",
+        "sec-ch-ua": '"Chromium";v="118", "Google Chrome";v="118", "Not=A?Brand";v="99"',
-            "apollographql-client-version": "4.65.5",
+        "sec-ch-ua-mobile": "?0",
-            "content-type": "application/json",
+        "sec-ch-ua-platform": '"macOS"',
-            "cookie": 'gdId=91e2dfc4-c8b5-4fa7-83d0-11512b80262c; G_ENABLED_IDPS=google; trs=https%3A%2F%2Fwww.redhat.com%2F:referral:referral:2023-07-05+09%3A50%3A14.862:undefined:undefined; g_state={"i_p":1688587331651,"i_l":1}; _cfuvid=.7llazxhYFZWi6EISSPdVjtqF0NMVwzxr_E.cB1jgLs-1697828392979-0-604800000; GSESSIONID=undefined; JSESSIONID=F03DD1B5EE02DB6D842FE42B142F88F3; cass=1; jobsClicked=true; indeedCtk=1hd77b301k79i801; asst=1697829114.2; G_AUTHUSER_H=0; uc=8013A8318C98C517FE6DD0024636DFDEF978FC33266D93A2FAFEF364EACA608949D8B8FA2DC243D62DE271D733EB189D809ABE5B08D7B1AE865D217BD4EEBB97C282F5DA5FEFE79C937E3F6110B2A3A0ADBBA3B4B6DF5A996FEE00516100A65FCB11DA26817BE8D1C1BF6CFE36B5B68A3FDC2CFEC83AB797F7841FBB157C202332FC7E077B56BD39B167BDF3D9866E3B; AWSALB=zxc/Yk1nbWXXT6HjNyn3H4h4950ckVsFV/zOrq5LSoChYLE1qV+hDI8Axi3fUa9rlskndcO0M+Fw+ZnJ+AQ2afBFpyOd1acouLMYgkbEpqpQaWhY6/Gv4QH1zBcJ; AWSALBCORS=zxc/Yk1nbWXXT6HjNyn3H4h4950ckVsFV/zOrq5LSoChYLE1qV+hDI8Axi3fUa9rlskndcO0M+Fw+ZnJ+AQ2afBFpyOd1acouLMYgkbEpqpQaWhY6/Gv4QH1zBcJ; gdsid=1697828393025:1697830776351:668396EDB9E6A832022D34414128093D; at=HkH8Hnqi9uaMC7eu0okqyIwqp07ht9hBvE1_St7E_hRqPvkO9pUeJ1Jcpds4F3g6LL5ADaCNlxrPn0o6DumGMfog8qI1-zxaV_jpiFs3pugntw6WpVyYWdfioIZ1IDKupyteeLQEM1AO4zhGjY_rPZynpsiZBPO_B1au94sKv64rv23yvP56OiWKKfI-8_9hhLACEwWvM-Az7X-4aE2QdFt93VJbXbbGVf07bdDZfimsIkTtgJCLSRhU1V0kEM1Efyu66vo3m77gFFaMW7lxyYnb36I5PdDtEXBm3aL-zR7-qa5ywd94ISEivgqQOA4FPItNhqIlX4XrfD1lxVz6rfPaoTIDi4DI6UMCUjwyPsuv8mn0rYqDfRnmJpZ97fJ5AnhrknAd_6ZWN5v1OrxJczHzcXd8LO820QPoqxzzG13bmSTXLwGSxMUCtSrVsq05hicimQ3jpRt0c1dA4OkTNqF7_770B9JfcHcM8cr8-C4IL56dnOjr9KBGfN1Q2IvZM2cOBRbV7okiNOzKVZ3qJ24AE34WA2F3U6Whiu6H8nIuGG5hSNkVygY6CtglNZfFF9p8pJAZm79PngrrBv-CXFBZmhYLFo46lmFetDkiJ6mirtez4tKpzTIYjIp4_JAkiZFwbLJ2QGH4mK8kyyW0lZiX1DTuQec50N_5wvRo0Gt7nlKxzLsApMnaNhuQeH5ygh_pa381ORo9mQGi0EYF9zk00pa2--z4PtjfQ8KFq36GgpxKy5-o4qgqygZj8F01L8r-FiX2G4C7PREMIpAyHX2A4-_JxA1IS2j12EyqKTLqE9VcP06qm2Z-YuIW3ctmpMxy5G9_KiEiGv17weizhSFnl6SbpAEY-2VSmQ5V6jm3hoMp2jemkuGCRkZeFstLDEPxlzFN7WM; __cf_bm=zGaVjIJw4irf40_7UVw54B6Ohm271RUX4Tc8KVScrbs-1697830777-0-AYv2GnKTnnCU+cY9xHbJunO0DwlLDO6SIBnC/s/qldpKsGK0rRAjD6y8lbyATT/KlS7g29OZaN4fbd0lrJg0KmWbIybZIzfWVLHSYePVuOhu; asst=1697829114.2; at=dFhXf64wsf2TlnWy41xLs7skJkuxgKToEGcjGtDfUvW4oEAJ4tTIR5dKQ8wbwT75aIaGgdCfvcb-da7vwrCGWscCncmfLFQpJ9l-LLwoRfk-pMsxHhd77wvf-W7I0HSm7-Q5lQJqI9WyNGRxOa-RpzBTf4L8_Et4-3FzjPaAoYY5pY1FhuwXbN5asGOAMW-p8cjpbfn3PumlIYuckguWnjrcY2F31YJ_1noeoHM9tCGpymANbqGXRkG6aXY7yCfVXtdgZU1K5SMeaSPZIuF_iLUxjc_corzpNiH6qq7BIAmh-e5Aa-g7cwpZcln1fmwTVw4uTMZf1eLIMTa9WzgqZNkvG-sGaq_XxKA_Wai6xTTkOHfRgm4632Ba2963wdJvkGmUUa3tb_L4_wTgk3eFnHp5JhghLfT2Pe3KidP-yX__vx8JOsqe3fndCkKXgVz7xQKe1Dur-sMNlGwi4LXfguTT2YUI8C5Miq3pj2IHc7dC97eyyAiAM4HvyGWfaXWZcei6oIGrOwMvYgy0AcwFry6SIP2SxLT5TrxinRRuem1r1IcOTJsMJyUPp1QsZ7bOyq9G_0060B4CPyovw5523hEuqLTM-R5e5yavY6C_1DHUyE15C3mrh7kdvmlGZeflnHqkFTEKwwOftm-Mv-CKD5Db9ABFGNxKB2FH7nDH67hfOvm4tGNMzceBPKYJ3wciTt9jK3wy39_7cOYVywfrZ-oLhw_XtsbGSSeGn3HytrfgSADAh2sT0Gg6eCC9Xy1vh-Za337SVLUDXZ73W2xJxxUHBkFzZs8L_Xndo5DsbpWhVs9IYUGyraJdqB3SLgDbAppIBCJl4fx6_DG8-xOQPBvuFMlTROe1JVdHOzXI1GElwFDTuH1pjkg4I2G0NhAbE06Y-1illQE; gdsid=1697828393025:1697831731408:99C30D94108AC3030D61C736DDCDF11C',
+        "sec-fetch-dest": "empty",
-            "gd-csrf-token": "Ft6oHEWlRZrxDww95Cpazw:0pGUrkb2y3TyOpAIqF2vbPmUXoXVkD3oEGDVkvfeCerceQ5-n8mBg3BovySUIjmCPHCaW0H2nQVdqzbtsYqf4Q:wcqRqeegRUa9MVLJGyujVXB7vWFPjdaS1CtrrzJq-ok",
+        "sec-fetch-mode": "cors",
-            "origin": "https://www.glassdoor.com",
+        "sec-fetch-site": "same-origin",
-            "referer": "https://www.glassdoor.com/",
+        "user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/118.0.0.0 Safari/537.36",
-            "sec-ch-ua": '"Chromium";v="118", "Google Chrome";v="118", "Not=A?Brand";v="99"',
+    }
-            "sec-ch-ua-mobile": "?0",
+    query_template = """
-            "sec-ch-ua-platform": '"macOS"',
+            query JobSearchResultsQuery(
-            "sec-fetch-dest": "empty",
+                $excludeJobListingIds: [Long!], 
-            "sec-fetch-mode": "cors",
+                $keyword: String, 
-            "sec-fetch-site": "same-origin",
+                $locationId: Int, 
-            "user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/118.0.0.0 Safari/537.36",
+                $locationType: LocationTypeEnum, 
-        }
+                $numJobsToShow: Int!, 
                $pageCursor: String, 
                $pageNumber: Int, 
                $filterParams: [FilterParams], 
                $originalPageUrl: String, 
                $seoFriendlyUrlInput: String, 
                $parameterUrlInput: String, 
                $seoUrl: Boolean
            ) {
                jobListings(
                    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
                        }
                    }
                ) {
                    companyFilterOptions {
                        id
                        shortName
                        __typename
                    }
                    filterOptions
                    indeedCtk
                    jobListings {
                        ...JobView
                        __typename
                    }
                    jobListingSeoLinks {
                        linkItems {
                            position
                            url
                            __typename
                        }
                        __typename
                    }
                    jobSearchTrackingKey
                    jobsPageSeoData {
                        pageMetaDescription
                        pageTitle
                        __typename
                    }
                    paginationCursors {
                        cursor
                        pageNumber
                        __typename
                    }
                    indexablePageForSeo
                    searchResultsMetadata {
                        searchCriteria {
                            implicitLocation {
                                id
                                localizedDisplayName
                                type
                                __typename
                            }
                            keyword
                            location {
                                id
                                shortName
                                localizedShortName
                                localizedDisplayName
                                type
                                __typename
                            }
                            __typename
                        }
                        helpCenterDomain
                        helpCenterLocale
                        jobSerpJobOutlook {
                            occupation
                            paragraph
                            __typename
                        }
                        showMachineReadableJobs
                        __typename
                    }
                    totalJobsCount
                    __typename
                }
            }
            fragment JobView on JobListingSearchResult {
                jobview {
                    header {
                        adOrderId
                        advertiserType
                        adOrderSponsorshipLevel
                        ageInDays
                        divisionEmployerName
                        easyApply
                        employer {
                            id
                            name
                            shortName
                            __typename
                        }
                        employerNameFromSearch
                        goc
                        gocConfidence
                        gocId
                        jobCountryId
                        jobLink
                        jobResultTrackingKey
                        jobTitleText
                        locationName
                        locationType
                        locId
                        needsCommission
                        payCurrency
                        payPeriod
                        payPeriodAdjustedPay {
                            p10
                            p50
                            p90
                            __typename
                        }
                        rating
                        salarySource
                        savedJobId
                        sponsored
                        __typename
                    }
                    job {
                        description
                        importConfigId
                        jobTitleId
                        jobTitleText
                        listingId
                        __typename
                    }
                    jobListingAdminDetails {
                        cpcVal
                        importConfigId
                        jobListingId
                        jobSourceId
                        userEligibleForAdminJobDetails
                        __typename
                    }
                    overview {
                        shortName
                        squareLogoUrl
                        __typename
                    }
                    __typename
                }
                __typename
            }
    """
--- a/src/jobspy/scrapers/indeed/init.py
+++ b/src/jobspy/scrapers/indeed/init.py
@@ -4,25 +4,22 @@ jobspy.scrapers.indeed
 This module contains routines to scrape Indeed.
 """
 import re
 import math
 import io
 import json
 from typing import Any
 from datetime import datetime
-import urllib.parse
+from __future__ import annotations
-from bs4 import BeautifulSoup
+
-from bs4.element import Tag
+import math
 from typing import Tuple
 from datetime import datetime
 from concurrent.futures import ThreadPoolExecutor, Future
-from ..exceptions import IndeedException
+import requests
 from .. import Scraper, ScraperInput, Site
 from ..utils import (
    count_urgent_words,
    extract_emails_from_text,
    create_session,
    get_enum_from_job_type,
-    modify_and_get_description
+    markdown_converter,
    logger,
 )
 from ...jobs import (
    JobPost,
@@ -31,341 +28,398 @@ from ...jobs import (
    Location,
    JobResponse,
    JobType,
    DescriptionFormat,
 )
 from .. import Scraper, ScraperInput, Site
 class IndeedScraper(Scraper):
    def __init__(self, proxy: str | None = None):
        """
-        Initializes IndeedScraper with the Indeed job search url
+        Initializes IndeedScraper with the Indeed API url
        """
-        self.url = None
+        self.scraper_input = None
-        self.country = None
+        self.jobs_per_page = 100
        self.num_workers = 10
        self.seen_urls = set()
        self.headers = None
        self.api_country_code = None
        self.base_url = None
        self.api_url = "https://apis.indeed.com/graphql"
        site = Site(Site.INDEED)
        super().__init__(site, proxy=proxy)
        self.jobs_per_page = 25
        self.seen_urls = set()
    def scrape_page(
        self, scraper_input: ScraperInput, page: int
    ) -> tuple[list[JobPost], int]:
        """
        Scrapes a page of Indeed for jobs with scraper_input criteria
        :param scraper_input:
        :param page:
        :return: jobs found on page, total number of jobs found for search
        """
        self.country = scraper_input.country
        domain = self.country.indeed_domain_value
        self.url = f"https://{domain}.indeed.com"
        try:
            session = create_session(self.proxy)
            response = session.get(
                f"{self.url}/m/jobs",
                headers=self.get_headers(),
                params=self.add_params(scraper_input, page),
                allow_redirects=True,
                timeout_seconds=10,
            )
            if response.status_code not in range(200, 400):
                raise IndeedException(
                    f"bad response with status code: {response.status_code}"
                )
        except Exception as e:
            if "Proxy responded with" in str(e):
                raise IndeedException("bad proxy")
            raise IndeedException(str(e))
        soup = BeautifulSoup(response.content, "html.parser")
        if "did not match any jobs" in response.text:
            raise IndeedException("Parsing exception: Search did not match any jobs")
        jobs = IndeedScraper.parse_jobs(
            soup
        )  #: can raise exception, handled by main scrape function
        total_num_jobs = IndeedScraper.total_jobs(soup)
        if (
            not jobs.get("metaData", {})
            .get("mosaicProviderJobCardsModel", {})
            .get("results")
        ):
            raise IndeedException("No jobs found.")
        def process_job(job: dict) -> JobPost | None:
            job_url = f'{self.url}/m/jobs/viewjob?jk={job["jobkey"]}'
            job_url_client = f'{self.url}/viewjob?jk={job["jobkey"]}'
            if job_url in self.seen_urls:
                return None
            extracted_salary = job.get("extractedSalary")
            compensation = None
            if extracted_salary:
                salary_snippet = job.get("salarySnippet")
                currency = salary_snippet.get("currency") if salary_snippet else None
                interval = (extracted_salary.get("type"),)
                if isinstance(interval, tuple):
                    interval = interval[0]
                interval = interval.upper()
                if interval in CompensationInterval.__members__:
                    compensation = Compensation(
                        interval=CompensationInterval[interval],
                        min_amount=int(extracted_salary.get("min")),
                        max_amount=int(extracted_salary.get("max")),
                        currency=currency,
                    )
            job_type = IndeedScraper.get_job_type(job)
            timestamp_seconds = job["pubDate"] / 1000
            date_posted = datetime.fromtimestamp(timestamp_seconds)
            date_posted = date_posted.strftime("%Y-%m-%d")
            description = self.get_description(job_url) if scraper_input.full_description else None
            with io.StringIO(job["snippet"]) as f:
                soup_io = BeautifulSoup(f, "html.parser")
                li_elements = soup_io.find_all("li")
                if description is None and li_elements:
                    description = " ".join(li.text for li in li_elements)
            job_post = JobPost(
                title=job["normTitle"],
                description=description,
                company_name=job["company"],
                company_url=self.url + job["companyOverviewLink"] if "companyOverviewLink" in job else None,
                location=Location(
                    city=job.get("jobLocationCity"),
                    state=job.get("jobLocationState"),
                    country=self.country,
                ),
                job_type=job_type,
                compensation=compensation,
                date_posted=date_posted,
                job_url=job_url_client,
                emails=extract_emails_from_text(description) if description else None,
                num_urgent_words=count_urgent_words(description)
                if description
                else None,
                is_remote=self.is_remote_job(job),
            )
            return job_post
        workers = 10 if scraper_input.full_description else 10  # possibly lessen 10 when fetching desc based on feedback
        jobs = jobs["metaData"]["mosaicProviderJobCardsModel"]["results"]
        with ThreadPoolExecutor(max_workers=workers) as executor:
            job_results: list[Future] = [
                executor.submit(process_job, job) for job in jobs
            ]
        job_list = [result.result() for result in job_results if result.result()]
        return job_list, total_num_jobs
    def scrape(self, scraper_input: ScraperInput) -> JobResponse:
        """
        Scrapes Indeed for jobs with scraper_input criteria
        :param scraper_input:
        :return: job_response
        """
-        pages_to_process = (
+        self.scraper_input = scraper_input
-            math.ceil(scraper_input.results_wanted / self.jobs_per_page) - 1
+        domain, self.api_country_code = self.scraper_input.country.indeed_domain_value
-        )
+        self.base_url = f"https://{domain}.indeed.com"
        self.headers = self.api_headers.copy()
        self.headers["indeed-co"] = self.scraper_input.country.indeed_domain_value
        job_list = []
        page = 1
-        #: get first page to initialize session
+        cursor = None
-        job_list, total_results = self.scrape_page(scraper_input, 0)
+        offset_pages = math.ceil(self.scraper_input.offset / 100)
        for _ in range(offset_pages):
            logger.info(f"Indeed skipping search page: {page}")
            __, cursor = self._scrape_page(cursor)
            if not __:
                logger.info(f"Indeed found no jobs on page: {page}")
                break
-        with ThreadPoolExecutor(max_workers=10) as executor:
+        while len(self.seen_urls) < scraper_input.results_wanted:
-            futures: list[Future] = [
+            logger.info(f"Indeed search page: {page}")
-                executor.submit(self.scrape_page, scraper_input, page)
+            jobs, cursor = self._scrape_page(cursor)
-                for page in range(1, pages_to_process + 1)
+            if not jobs:
-            ]
+                logger.info(f"Indeed found no jobs on page: {page}")
                break
            job_list += jobs
            page += 1
        return JobResponse(jobs=job_list[: scraper_input.results_wanted])
-            for future in futures:
+    def _scrape_page(self, cursor: str | None) -> Tuple[list[JobPost], str | None]:
                jobs, _ = future.result()
                job_list += jobs
        if len(job_list) > scraper_input.results_wanted:
            job_list = job_list[: scraper_input.results_wanted]
        job_response = JobResponse(
            jobs=job_list,
            total_results=total_results,
        )
        return job_response
    def get_description(self, job_page_url: str) -> str | None:
        """
-        Retrieves job description by going to the job page url
+        Scrapes a page of Indeed for jobs with scraper_input criteria
-        :param job_page_url:
+        :param cursor:
-        :return: description
+        :return: jobs found on page, next page cursor
        """
-        parsed_url = urllib.parse.urlparse(job_page_url)
+        jobs = []
-        params = urllib.parse.parse_qs(parsed_url.query)
+        new_cursor = None
-        jk_value = params.get("jk", [None])[0]
+        filters = self._build_filters()
-        formatted_url = f"{self.url}/m/viewjob?jk={jk_value}&spa=1"
+        location = (
-        session = create_session(self.proxy)
+            self.scraper_input.location
-
+            or self.scraper_input.country.value[0].split(",")[-1]
-        try:
+        )
-            response = session.get(
+        query = self.job_search_query.format(
-                formatted_url,
+            what=(
-                headers=self.get_headers(),
+                f'what: "{self.scraper_input.search_term}"'
-                allow_redirects=True,
+                if self.scraper_input.search_term
-                timeout_seconds=5,
+                else ""
            ),
            location=location,
            radius=self.scraper_input.distance,
            dateOnIndeed=self.scraper_input.hours_old,
            cursor=f'cursor: "{cursor}"' if cursor else "",
            filters=filters,
        )
        payload = {
            "query": query,
        }
        api_headers = self.api_headers.copy()
        api_headers["indeed-co"] = self.api_country_code
        response = requests.post(
            self.api_url,
            headers=api_headers,
            json=payload,
            proxies=self.proxy,
            timeout=10,
        )
        if response.status_code != 200:
            logger.info(
                f"Indeed responded with status code: {response.status_code} (submit GitHub issue if this appears to be a beg)"
            )
-        except Exception as e:
+            return jobs, new_cursor
-            return None
+        data = response.json()
        jobs = data["data"]["jobSearch"]["results"]
        new_cursor = data["data"]["jobSearch"]["pageInfo"]["nextCursor"]
-        if response.status_code not in range(200, 400):
+        with ThreadPoolExecutor(max_workers=self.num_workers) as executor:
-            return None
+            job_results: list[Future] = [
                executor.submit(self._process_job, job["job"]) for job in jobs
            ]
        job_list = [result.result() for result in job_results if result.result()]
        return job_list, new_cursor
-        try:
+    def _build_filters(self):
-            soup = BeautifulSoup(response.text, 'html.parser')
+        """
-            script_tags = soup.find_all('script')
+        Builds the filters dict for job type/is_remote. If hours_old is provided, composite filter for job_type/is_remote is not possible.
        IndeedApply: filters: { keyword: { field: "indeedApplyScope", keys: ["DESKTOP"] } }
        """
        filters_str = ""
        if self.scraper_input.hours_old:
            filters_str = """
            filters: {{
                date: {{
                  field: "dateOnIndeed",
                  start: "{start}h"
                }}
            }}
            """.format(
                start=self.scraper_input.hours_old
            )
        elif self.scraper_input.job_type or self.scraper_input.is_remote:
            job_type_key_mapping = {
                JobType.FULL_TIME: "CF3CP",
                JobType.PART_TIME: "75GKK",
                JobType.CONTRACT: "NJXCK",
                JobType.INTERNSHIP: "VDTG7",
            }
-            job_description = ''
+            keys = []
-            for tag in script_tags:
+            if self.scraper_input.job_type:
-                if 'window._initialData' in tag.text:
+                key = job_type_key_mapping[self.scraper_input.job_type]
-                    json_str = tag.text
+                keys.append(key)
                    json_str = json_str.split('window._initialData=')[1]
                    json_str = json_str.rsplit(';', 1)[0]
                    data = json.loads(json_str)
                    job_description = data["jobInfoWrapperModel"]["jobInfoModel"]["sanitizedJobDescription"]
                    break
        except (KeyError, TypeError, IndexError):
            return None
-        soup = BeautifulSoup(job_description, "html.parser")
+            if self.scraper_input.is_remote:
-        return modify_and_get_description(soup)
+                keys.append("DSQF7")
            if keys:
                keys_str = '", "'.join(keys)  # Prepare your keys string
                filters_str = f"""
                filters: {{
                  composite: {{
                    filters: [{{
                      keyword: {{
                        field: "attributes",
                        keys: ["{keys_str}"]
                      }}
                    }}]
                  }}
                }}
                """
        return filters_str
    def _process_job(self, job: dict) -> JobPost | None:
        """
        Parses the job dict into JobPost model
        :param job: dict to parse
        :return: JobPost if it's a new job
        """
        job_url = f'{self.base_url}/viewjob?jk={job["key"]}'
        if job_url in self.seen_urls:
            return
        self.seen_urls.add(job_url)
        description = job["description"]["html"]
        if self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
            description = markdown_converter(description)
        job_type = self._get_job_type(job["attributes"])
        timestamp_seconds = job["datePublished"] / 1000
        date_posted = datetime.fromtimestamp(timestamp_seconds).strftime("%Y-%m-%d")
        employer = job["employer"].get("dossier") if job["employer"] else None
        employer_details = employer.get("employerDetails", {}) if employer else {}
        rel_url = job["employer"]["relativeCompanyPageUrl"] if job["employer"] else None
        return JobPost(
            title=job["title"],
            description=description,
            company_name=job["employer"].get("name") if job.get("employer") else None,
            company_url=(f"{self.base_url}{rel_url}" if job["employer"] else None),
            company_url_direct=(
                employer["links"]["corporateWebsite"] if employer else None
            ),
            location=Location(
                city=job.get("location", {}).get("city"),
                state=job.get("location", {}).get("admin1Code"),
                country=job.get("location", {}).get("countryCode"),
            ),
            job_type=job_type,
            compensation=self._get_compensation(job),
            date_posted=date_posted,
            job_url=job_url,
            job_url_direct=(
                job["recruit"].get("viewJobUrl") if job.get("recruit") else None
            ),
            emails=extract_emails_from_text(description) if description else None,
            is_remote=self._is_job_remote(job, description),
            company_addresses=(
                employer_details["addresses"][0]
                if employer_details.get("addresses")
                else None
            ),
            company_industry=(
                employer_details["industry"]
                .replace("Iv1", "")
                .replace("_", " ")
                .title()
                if employer_details.get("industry")
                else None
            ),
            company_num_employees=employer_details.get("employeesLocalizedLabel"),
            company_revenue=employer_details.get("revenueLocalizedLabel"),
            company_description=employer_details.get("briefDescription"),
            ceo_name=employer_details.get("ceoName"),
            ceo_photo_url=employer_details.get("ceoPhotoUrl"),
            logo_photo_url=(
                employer["images"].get("squareLogoUrl")
                if employer and employer.get("images")
                else None
            ),
            banner_photo_url=(
                employer["images"].get("headerImageUrl")
                if employer and employer.get("images")
                else None
            ),
        )
    @staticmethod
-    def get_job_type(job: dict) -> list[JobType] | None:
+    def _get_job_type(attributes: list) -> list[JobType]:
        """
-        Parses the job to get list of job types
+        Parses the attributes to get list of job types
-        :param job:
+        :param attributes:
-        :return:
+        :return: list of JobType
        """
        job_types: list[JobType] = []
-        for taxonomy in job["taxonomyAttributes"]:
+        for attribute in attributes:
-            if taxonomy["label"] == "job-types":
+            job_type_str = attribute["label"].replace("-", "").replace(" ", "").lower()
-                for i in range(len(taxonomy["attributes"])):
+            job_type = get_enum_from_job_type(job_type_str)
-                    label = taxonomy["attributes"][i].get("label")
+            if job_type:
-                    if label:
+                job_types.append(job_type)
                        job_type_str = label.replace("-", "").replace(" ", "").lower()
                        job_type = get_enum_from_job_type(job_type_str)
                        if job_type:
                            job_types.append(job_type)
        return job_types
    @staticmethod
-    def parse_jobs(soup: BeautifulSoup) -> dict:
+    def _get_compensation(job: dict) -> Compensation | None:
        """
        Parses the jobs from the soup object
        :param soup:
        :return: jobs
        """
        def find_mosaic_script() -> Tag | None:
            """
            Finds jobcards script tag
            :return: script_tag
            """
            script_tags = soup.find_all("script")
            for tag in script_tags:
                if (
                    tag.string
                    and "mosaic.providerData" in tag.string
                    and "mosaic-provider-jobcards" in tag.string
                ):
                    return tag
            return None
        script_tag = find_mosaic_script()
        if script_tag:
            script_str = script_tag.string
            pattern = r'window.mosaic.providerData\["mosaic-provider-jobcards"\]\s*=\s*({.*?});'
            p = re.compile(pattern, re.DOTALL)
            m = p.search(script_str)
            if m:
                jobs = json.loads(m.group(1).strip())
                return jobs
            else:
                raise IndeedException("Could not find mosaic provider job cards data")
        else:
            raise IndeedException(
                "Could not find any results for the search"
            )
    @staticmethod
    def total_jobs(soup: BeautifulSoup) -> int:
        """
        Parses the total jobs for that search from soup object
        :param soup:
        :return: total_num_jobs
        """
        script = soup.find("script", string=lambda t: t and "window._initialData" in t)
        pattern = re.compile(r"window._initialData\s*=\s*({.*})\s*;", re.DOTALL)
        match = pattern.search(script.string)
        total_num_jobs = 0
        if match:
            json_str = match.group(1)
            data = json.loads(json_str)
            total_num_jobs = int(data["searchTitleBarModel"]["totalNumResults"])
        return total_num_jobs
    @staticmethod
    def get_headers():
        return {
          'Host': 'www.indeed.com',
          'accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
          'sec-fetch-site': 'same-origin',
          'sec-fetch-dest': 'document',
          'accept-language': 'en-US,en;q=0.9',
          'sec-fetch-mode': 'navigate',
          'user-agent': 'Mozilla/5.0 (iPhone; CPU iPhone OS 16_6_1 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) Mobile/15E148 Indeed App 192.0',
          'referer': 'https://www.indeed.com/m/jobs?q=software%20intern&l=Dallas%2C%20TX&from=serpso&rq=1&rsIdx=3',
        }
    @staticmethod
    def is_remote_job(job: dict) -> bool:
        """
        Parses the job to get compensation
        :param job:
-        :return: bool
+        :param job:
        :return: compensation object
        """
-        for taxonomy in job.get("taxonomyAttributes", []):
+        comp = job["compensation"]["baseSalary"]
-            if taxonomy["label"] == "remote" and len(taxonomy["attributes"]) > 0:
+        if not comp:
-                return True
+            return None
-        return False
+        interval = IndeedScraper._get_compensation_interval(comp["unitOfWork"])
        if not interval:
            return None
        min_range = comp["range"].get("min")
        max_range = comp["range"].get("max")
        return Compensation(
            interval=interval,
            min_amount=round(min_range, 2) if min_range is not None else None,
            max_amount=round(max_range, 2) if max_range is not None else None,
            currency=job["compensation"]["currencyCode"],
        )
    @staticmethod
-    def add_params(scraper_input: ScraperInput, page: int) -> dict[str, str | Any]:
+    def _is_job_remote(job: dict, description: str) -> bool:
-        params = {
+        """
-            "q": scraper_input.search_term,
+        Searches the description, location, and attributes to check if job is remote
-            "l": scraper_input.location if scraper_input.location else scraper_input.country.value[0].split(',')[-1],
+        """
-            "filter": 0,
+        remote_keywords = ["remote", "work from home", "wfh"]
-            "start": scraper_input.offset + page * 10,
+        is_remote_in_attributes = any(
-            "sort": "date"
+            any(keyword in attr["label"].lower() for keyword in remote_keywords)
            for attr in job["attributes"]
        )
        is_remote_in_description = any(
            keyword in description.lower() for keyword in remote_keywords
        )
        is_remote_in_location = any(
            keyword in job["location"]["formatted"]["long"].lower()
            for keyword in remote_keywords
        )
        return (
            is_remote_in_attributes or is_remote_in_description or is_remote_in_location
        )
    @staticmethod
    def _get_compensation_interval(interval: str) -> CompensationInterval:
        interval_mapping = {
            "DAY": "DAILY",
            "YEAR": "YEARLY",
            "HOUR": "HOURLY",
            "WEEK": "WEEKLY",
            "MONTH": "MONTHLY",
        }
-        if scraper_input.distance:
+        mapped_interval = interval_mapping.get(interval.upper(), None)
-            params["radius"] = scraper_input.distance
+        if mapped_interval and mapped_interval in CompensationInterval.__members__:
            return CompensationInterval[mapped_interval]
        else:
            raise ValueError(f"Unsupported interval: {interval}")
-        sc_values = []
+    api_headers = {
-        if scraper_input.is_remote:
+        "Host": "apis.indeed.com",
-            sc_values.append("attr(DSQF7)")
+        "content-type": "application/json",
-        if scraper_input.job_type:
+        "indeed-api-key": "161092c2017b5bbab13edb12461a62d5a833871e7cad6d9d475304573de67ac8",
-            sc_values.append("jt({})".format(scraper_input.job_type.value))
+        "accept": "application/json",
-
+        "indeed-locale": "en-US",
-        if sc_values:
+        "accept-language": "en-US,en;q=0.9",
-            params["sc"] = "0kf:" + "".join(sc_values) + ";"
+        "user-agent": "Mozilla/5.0 (iPhone; CPU iPhone OS 16_6_1 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) Mobile/15E148 Indeed App 193.1",
-
+        "indeed-app-info": "appv=193.1; appid=com.indeed.jobsearch; osv=16.6.1; os=ios; dtype=phone",
-        if scraper_input.easy_apply:
+    }
-            params['iafilter'] = 1
+    job_search_query = """
-
+        query GetJobData {{
-        return params
+          jobSearch(
            {what}
            location: {{ where: "{location}", radius: {radius}, radiusUnit: MILES }}
            includeSponsoredResults: NONE
            limit: 100
            sort: DATE
            {cursor}
            {filters}
          ) {{
            pageInfo {{
              nextCursor
            }}
            results {{
              trackingKey
              job {{
                key
                title
                datePublished
                dateOnIndeed
                description {{
                  html
                }}
                location {{
                  countryName
                  countryCode
                  admin1Code
                  city
                  postalCode
                  streetAddress
                  formatted {{
                    short
                    long
                  }}
                }}
                compensation {{
                  baseSalary {{
                    unitOfWork
                    range {{
                      ... on Range {{
                        min
                        max
                      }}
                    }}
                  }}
                  currencyCode
                }}
                attributes {{
                  key
                  label
                }}
                employer {{
                  relativeCompanyPageUrl
                  name
                  dossier {{
                      employerDetails {{
                        addresses
                        industry
                        employeesLocalizedLabel
                        revenueLocalizedLabel
                        briefDescription
                        ceoName
                        ceoPhotoUrl
                      }}
                      images {{
                            headerImageUrl
                            squareLogoUrl
                      }}
                      links {{
                        corporateWebsite
                    }}
                  }}
                }}
                recruit {{
                  viewJobUrl
                  detailedSalary
                  workSchedule
                }}
              }}
            }}
          }}
        }}
        """
--- a/src/jobspy/scrapers/linkedin/init.py
+++ b/src/jobspy/scrapers/linkedin/init.py
@@ -4,13 +4,14 @@ jobspy.scrapers.linkedin
 This module contains routines to scrape LinkedIn.
 """
 from __future__ import annotations
 import time
 import random
 from typing import Optional
 from datetime import datetime
 import requests
 from requests.exceptions import ProxyError
 from threading import Lock
 from bs4.element import Tag
 from bs4 import BeautifulSoup
@@ -25,28 +26,31 @@ from ...jobs import (
    JobResponse,
    JobType,
    Country,
-    Compensation
+    Compensation,
    DescriptionFormat,
 )
 from ..utils import (
-    count_urgent_words,
+    logger,
    extract_emails_from_text,
    get_enum_from_job_type,
    currency_parser,
-    modify_and_get_description
+    markdown_converter,
 )
 class LinkedInScraper(Scraper):
-    DELAY = 3
+    base_url = "https://www.linkedin.com"
    delay = 3
    band_delay = 4
    jobs_per_page = 25
    def __init__(self, proxy: Optional[str] = None):
        """
        Initializes LinkedInScraper with the LinkedIn job search url
        """
-        site = Site(Site.LINKEDIN)
+        super().__init__(Site(Site.LINKEDIN), proxy=proxy)
        self.scraper_input = None
        self.country = "worldwide"
        self.url = "https://www.linkedin.com"
        super().__init__(site, proxy=proxy)
    def scrape(self, scraper_input: ScraperInput) -> JobResponse:
        """
@@ -54,58 +58,68 @@ class LinkedInScraper(Scraper):
        :param scraper_input:
        :return: job_response
        """
        self.scraper_input = scraper_input
        job_list: list[JobPost] = []
        seen_urls = set()
        url_lock = Lock()
        page = scraper_input.offset // 25 + 25 if scraper_input.offset else 0
-
+        seconds_old = (
-        def job_type_code(job_type_enum):
+            scraper_input.hours_old * 3600 if scraper_input.hours_old else None
-            mapping = {
+        )
-                JobType.FULL_TIME: "F",
+        continue_search = (
-                JobType.PART_TIME: "P",
+            lambda: len(job_list) < scraper_input.results_wanted and page < 1000
-                JobType.INTERNSHIP: "I",
+        )
                JobType.CONTRACT: "C",
                JobType.TEMPORARY: "T",
            }
            return mapping.get(job_type_enum, "")
        continue_search = lambda: len(job_list) < scraper_input.results_wanted and page < 1000
        while continue_search():
            logger.info(f"LinkedIn search page: {page // 25 + 1}")
            session = create_session(is_tls=False, has_retry=True, delay=5)
            params = {
                "keywords": scraper_input.search_term,
                "location": scraper_input.location,
                "distance": scraper_input.distance,
                "f_WT": 2 if scraper_input.is_remote else None,
-                "f_JT": job_type_code(scraper_input.job_type)
+                "f_JT": (
-                if scraper_input.job_type
+                    self.job_type_code(scraper_input.job_type)
-                else None,
+                    if scraper_input.job_type
                    else None
                ),
                "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
                ),
            }
            if seconds_old is not None:
                params["f_TPR"] = f"r{seconds_old}"
            params = {k: v for k, v in params.items() if v is not None}
            try:
                response = session.get(
-                    f"{self.url}/jobs-guest/jobs/api/seeMoreJobPostings/search?",
+                    f"{self.base_url}/jobs-guest/jobs/api/seeMoreJobPostings/search?",
                    params=params,
                    allow_redirects=True,
                    proxies=self.proxy,
-                    headers=self.headers(),
+                    headers=self.headers,
                    timeout=10,
                )
-                response.raise_for_status()
+                if response.status_code not in range(200, 400):
-
+                    if response.status_code == 429:
-            except requests.HTTPError as e:
+                        err = (
-                raise LinkedInException(f"bad response status code: {e.response.status_code}")
+                            f"429 Response - Blocked by LinkedIn for too many requests"
-            except ProxyError as e:
+                        )
-                raise LinkedInException("bad proxy")
+                    else:
                        err = f"LinkedIn response status code {response.status_code}"
                        err += f" - {response.text}"
                    logger.error(err)
                    return JobResponse(jobs=job_list)
            except Exception as e:
-                raise LinkedInException(str(e))
+                if "Proxy responded with" in str(e):
                    logger.error(f"LinkedIn: Bad proxy")
                else:
                    logger.error(f"LinkedIn: {str(e)}")
                return JobResponse(jobs=job_list)
            soup = BeautifulSoup(response.text, "html.parser")
            job_cards = soup.find_all("div", class_="base-search-card")
@@ -118,38 +132,41 @@ class LinkedInScraper(Scraper):
                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.url}/jobs/view/{job_id}"
+                    job_url = f"{self.base_url}/jobs/view/{job_id}"
                with url_lock:
                    if job_url in seen_urls:
                        continue
                    seen_urls.add(job_url)
                # Call process_job directly without threading
                try:
-                    job_post = self.process_job(job_card, job_url, scraper_input.full_description)
+                    fetch_desc = scraper_input.linkedin_fetch_description
                    job_post = self._process_job(job_card, job_url, fetch_desc)
                    if job_post:
                        job_list.append(job_post)
                    if not continue_search():
                        break
                except Exception as e:
-                    raise LinkedInException("Exception occurred while processing jobs")
+                    raise LinkedInException(str(e))
            if continue_search():
-                time.sleep(random.uniform(LinkedInScraper.DELAY, LinkedInScraper.DELAY + 2))
+                time.sleep(random.uniform(self.delay, self.delay + self.band_delay))
-                page += 25
+                page += self.jobs_per_page
        job_list = job_list[: scraper_input.results_wanted]
        return JobResponse(jobs=job_list)
-    def process_job(self, job_card: Tag, job_url: str, full_descr: bool) -> Optional[JobPost]:
+    def _process_job(
-        salary_tag = job_card.find('span', class_='job-search-card__salary-info')
+        self, job_card: Tag, job_url: str, full_descr: bool
    ) -> Optional[JobPost]:
        salary_tag = job_card.find("span", class_="job-search-card__salary-info")
        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),
@@ -170,7 +187,7 @@ class LinkedInScraper(Scraper):
        company = company_a_tag.get_text(strip=True) if company_a_tag else "N/A"
        metadata_card = job_card.find("div", class_="base-search-card__metadata")
-        location = self.get_location(metadata_card)
+        location = self._get_location(metadata_card)
        datetime_tag = (
            metadata_card.find("time", class_="job-search-card__listdate")
@@ -182,12 +199,11 @@ class LinkedInScraper(Scraper):
            datetime_str = datetime_tag["datetime"]
            try:
                date_posted = datetime.strptime(datetime_str, "%Y-%m-%d")
-            except Exception as e:
+            except:
                date_posted = None
        benefits_tag = job_card.find("span", class_="result-benefits__text")
        benefits = " ".join(benefits_tag.get_text().split()) if benefits_tag else None
        if full_descr:
-            description, job_type = self.get_job_description(job_url)
+            description, job_type = self._get_job_description(job_url)
        return JobPost(
            title=title,
@@ -197,14 +213,12 @@ class LinkedInScraper(Scraper):
            date_posted=date_posted,
            job_url=job_url,
            compensation=compensation,
            benefits=benefits,
            job_type=job_type,
            description=description,
            emails=extract_emails_from_text(description) if description else None,
            num_urgent_words=count_urgent_words(description) if description else None,
        )
-    def get_job_description(
+    def _get_job_description(
        self, job_page_url: str
    ) -> tuple[None, None] | tuple[str | None, tuple[str | None, JobType | None]]:
        """
@@ -214,11 +228,11 @@ class LinkedInScraper(Scraper):
        """
        try:
            session = create_session(is_tls=False, has_retry=True)
-            response = session.get(job_page_url, timeout=5, proxies=self.proxy)
+            response = session.get(
                job_page_url, headers=self.headers, timeout=5, proxies=self.proxy
            )
            response.raise_for_status()
-        except requests.HTTPError as e:
+        except:
            return None, None
        except Exception as e:
            return None, None
        if response.url == "https://www.linkedin.com/signup":
            return None, None
@@ -227,41 +241,21 @@ class LinkedInScraper(Scraper):
        div_content = soup.find(
            "div", class_=lambda x: x and "show-more-less-html__markup" in x
        )
        description = None
-        if div_content:
+        if div_content is not None:
            description = modify_and_get_description(div_content)
-        def get_job_type(
+            def remove_attributes(tag):
-            soup_job_type: BeautifulSoup,
+                for attr in list(tag.attrs):
-        ) -> list[JobType] | None:
+                    del tag[attr]
-            """
+                return tag
            Gets the job type from job page
            :param soup_job_type:
            :return: JobType
            """
            h3_tag = soup_job_type.find(
                "h3",
                class_="description__job-criteria-subheader",
                string=lambda text: "Employment type" in text,
            )
-            employment_type = None
+            div_content = remove_attributes(div_content)
-            if h3_tag:
+            description = div_content.prettify(formatter="html")
-                employment_type_span = h3_tag.find_next_sibling(
+            if self.scraper_input.description_format == DescriptionFormat.MARKDOWN:
-                    "span",
+                description = markdown_converter(description)
-                    class_="description__job-criteria-text description__job-criteria-text--criteria",
+        return description, self._parse_job_type(soup)
                )
                if employment_type_span:
                    employment_type = employment_type_span.get_text(strip=True)
                    employment_type = employment_type.lower()
                    employment_type = employment_type.replace("-", "")
-            return [get_enum_from_job_type(employment_type)] if employment_type else []
+    def _get_location(self, metadata_card: Optional[Tag]) -> Location:
        return description, get_job_type(soup)
    def get_location(self, metadata_card: Optional[Tag]) -> Location:
        """
        Extracts the location data from the job metadata card.
        :param metadata_card
@@ -283,28 +277,50 @@ class LinkedInScraper(Scraper):
                )
            elif len(parts) == 3:
                city, state, country = parts
-                location = Location(
+                country = Country.from_string(country)
-                    city=city,
+                location = Location(city=city, state=state, country=country)
                    state=state,
                    country=Country.from_string(country),
                )
        return location
    @staticmethod
-    def headers() -> dict:
+    def _parse_job_type(soup_job_type: BeautifulSoup) -> list[JobType] | None:
        """
        Gets the job type from job page
        :param soup_job_type:
        :return: JobType
        """
        h3_tag = soup_job_type.find(
            "h3",
            class_="description__job-criteria-subheader",
            string=lambda text: "Employment type" in text,
        )
        employment_type = None
        if h3_tag:
            employment_type_span = h3_tag.find_next_sibling(
                "span",
                class_="description__job-criteria-text description__job-criteria-text--criteria",
            )
            if employment_type_span:
                employment_type = employment_type_span.get_text(strip=True)
                employment_type = employment_type.lower()
                employment_type = employment_type.replace("-", "")
        return [get_enum_from_job_type(employment_type)] if employment_type else []
    @staticmethod
    def job_type_code(job_type_enum: JobType) -> str:
        return {
-            'authority': 'www.linkedin.com',
+            JobType.FULL_TIME: "F",
-            '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',
+            JobType.PART_TIME: "P",
-            'accept-language': 'en-US,en;q=0.9',
+            JobType.INTERNSHIP: "I",
-            'cache-control': 'max-age=0',
+            JobType.CONTRACT: "C",
-            'sec-ch-ua': '"Not_A Brand";v="8", "Chromium";v="120", "Google Chrome";v="120"',
+            JobType.TEMPORARY: "T",
-            # 'sec-ch-ua-mobile': '?0',
+        }.get(job_type_enum, "")
-            # 'sec-ch-ua-platform': '"macOS"',
+
-            # 'sec-fetch-dest': 'document',
+    headers = {
-            # 'sec-fetch-mode': 'navigate',
+        "authority": "www.linkedin.com",
-            # 'sec-fetch-site': 'none',
+        "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",
-            # 'sec-fetch-user': '?1',
+        "accept-language": "en-US,en;q=0.9",
-            'upgrade-insecure-requests': '1',
+        "cache-control": "max-age=0",
-            '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'
+        "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",
    }
--- a/src/jobspy/scrapers/utils.py
+++ b/src/jobspy/scrapers/utils.py
@@ -1,34 +1,31 @@
-import re
+from __future__ import annotations
 import numpy as np
-import tls_client
+import re
 import logging
 import requests
 import tls_client
 import numpy as np
 from markdownify import markdownify as md
 from requests.adapters import HTTPAdapter, Retry
 from ..jobs import JobType
-
+logger = logging.getLogger("JobSpy")
-def modify_and_get_description(soup):
+logger.propagate = False
-    for li in soup.find_all('li'):
+if not logger.handlers:
-        li.string = "- " + li.get_text()
+    logger.setLevel(logging.INFO)
-
+    console_handler = logging.StreamHandler()
-    description = soup.get_text(separator='\n').strip()
+    format = "%(asctime)s - %(name)s - %(levelname)s - %(message)s"
-    description = re.sub(r'\n+', '\n', description)
+    formatter = logging.Formatter(format)
-    return description
+    console_handler.setFormatter(formatter)
    logger.addHandler(console_handler)
-def count_urgent_words(description: str) -> int:
+def markdown_converter(description_html: str):
-    """
+    if description_html is None:
-    Count the number of urgent words or phrases in a job description.
+        return None
-    """
+    markdown = md(description_html)
-    urgent_patterns = re.compile(
+    return markdown.strip()
        r"\burgen(t|cy)|\bimmediate(ly)?\b|start asap|\bhiring (now|immediate(ly)?)\b",
        re.IGNORECASE,
    )
    matches = re.findall(urgent_patterns, description)
    count = len(matches)
    return count
 def extract_emails_from_text(text: str) -> list[str] | None:
@@ -38,17 +35,18 @@ def extract_emails_from_text(text: str) -> list[str] | None:
    return email_regex.findall(text)
-def create_session(proxy: dict | None = None, is_tls: bool = True, has_retry: bool = False, delay: int = 1) -> requests.Session:
+def create_session(
    proxy: dict | None = None,
    is_tls: bool = True,
    has_retry: bool = False,
    delay: int = 1,
 ) -> requests.Session:
    """
    Creates a requests session with optional tls, proxy, and retry settings.
    :return: A session object
    """
    if is_tls:
-        session = tls_client.Session(
+        session = tls_client.Session(random_tls_extension_order=True)
            client_identifier="chrome112",
            random_tls_extension_order=True,
        )
        session.proxies = proxy
    else:
        session = requests.Session()
@@ -56,16 +54,17 @@ def create_session(proxy: dict | None = None, is_tls: bool = True, has_retry: bo
        if proxy:
            session.proxies.update(proxy)
        if has_retry:
-            retries = Retry(total=3,
+            retries = Retry(
-                            connect=3,
+                total=3,
-                            status=3,
+                connect=3,
-                            status_forcelist=[500, 502, 503, 504, 429],
+                status=3,
-                            backoff_factor=delay)
+                status_forcelist=[500, 502, 503, 504, 429],
                backoff_factor=delay,
            )
            adapter = HTTPAdapter(max_retries=retries)
-            session.mount('http://', adapter)
+            session.mount("http://", adapter)
-            session.mount('https://', adapter)
+            session.mount("https://", adapter)
    return session
@@ -79,17 +78,18 @@ def get_enum_from_job_type(job_type_str: str) -> JobType | None:
            res = job_type
    return res
 def currency_parser(cur_str):
    # Remove any non-numerical characters
    # except for ',' '.' or '-' (e.g. EUR)
-    cur_str = re.sub("[^-0-9.,]", '', cur_str)
+    cur_str = re.sub("[^-0-9.,]", "", cur_str)
    # Remove any 000s separators (either , or .)
-    cur_str = re.sub("[.,]", '', cur_str[:-3]) + cur_str[-3:]
+    cur_str = re.sub("[.,]", "", cur_str[:-3]) + cur_str[-3:]
-    if '.' in list(cur_str[-3:]):
+    if "." in list(cur_str[-3:]):
        num = float(cur_str)
-    elif ',' in list(cur_str[-3:]):
+    elif "," in list(cur_str[-3:]):
-        num = float(cur_str.replace(',', '.'))
+        num = float(cur_str.replace(",", "."))
    else:
        num = float(cur_str)
--- a/src/jobspy/scrapers/ziprecruiter/init.py
+++ b/src/jobspy/scrapers/ziprecruiter/init.py
@@ -4,36 +4,80 @@ jobspy.scrapers.ziprecruiter
 This module contains routines to scrape ZipRecruiter.
 """
 from __future__ import annotations
 import math
 import time
-from datetime import datetime, timezone
+from datetime import datetime
 from typing import Optional, Tuple, Any
 from bs4 import BeautifulSoup
 from concurrent.futures import ThreadPoolExecutor
 from .. import Scraper, ScraperInput, Site
-from ..exceptions import ZipRecruiterException
+from ..utils import (
-from ...jobs import JobPost, Compensation, Location, JobResponse, JobType, Country
+    logger,
-from ..utils import count_urgent_words, extract_emails_from_text, create_session, modify_and_get_description
+    extract_emails_from_text,
    create_session,
    markdown_converter,
 )
 from ...jobs import (
    JobPost,
    Compensation,
    Location,
    JobResponse,
    JobType,
    Country,
    DescriptionFormat,
 )
 class ZipRecruiterScraper(Scraper):
    base_url = "https://www.ziprecruiter.com"
    api_url = "https://api.ziprecruiter.com"
    def __init__(self, proxy: Optional[str] = None):
        """
        Initializes ZipRecruiterScraper with the ZipRecruiter job search url
        """
-        site = Site(Site.ZIP_RECRUITER)
+        self.scraper_input = None
        self.url = "https://www.ziprecruiter.com"
        self.session = create_session(proxy)
-        self.get_cookies()
+        self._get_cookies()
-        super().__init__(site, proxy=proxy)
+        super().__init__(Site.ZIP_RECRUITER, proxy=proxy)
        self.delay = 5
        self.jobs_per_page = 20
        self.seen_urls = set()
        self.delay = 5
-    def find_jobs_in_page(
+    def scrape(self, scraper_input: ScraperInput) -> JobResponse:
        """
        Scrapes ZipRecruiter for jobs with scraper_input criteria.
        :param scraper_input: Information about job search criteria.
        :return: JobResponse containing a list of jobs.
        """
        self.scraper_input = scraper_input
        job_list: list[JobPost] = []
        continue_token = None
        max_pages = math.ceil(scraper_input.results_wanted / self.jobs_per_page)
        for page in range(1, max_pages + 1):
            if len(job_list) >= scraper_input.results_wanted:
                break
            if page > 1:
                time.sleep(self.delay)
            logger.info(f"ZipRecruiter search page: {page}")
            jobs_on_page, continue_token = self._find_jobs_in_page(
                scraper_input, continue_token
            )
            if jobs_on_page:
                job_list.extend(jobs_on_page)
            else:
                break
            if not continue_token:
                break
        return JobResponse(jobs=job_list[: scraper_input.results_wanted])
    def _find_jobs_in_page(
        self, scraper_input: ScraperInput, continue_token: str | None = None
    ) -> Tuple[list[JobPost], Optional[str]]:
        """
@@ -42,75 +86,54 @@ class ZipRecruiterScraper(Scraper):
        :param continue_token:
        :return: jobs found on page
        """
-        params = self.add_params(scraper_input)
+        jobs_list = []
        params = self._add_params(scraper_input)
        if continue_token:
            params["continue_from"] = continue_token
        try:
-            response = self.session.get(
+            res = self.session.get(
-                f"https://api.ziprecruiter.com/jobs-app/jobs",
+                f"{self.api_url}/jobs-app/jobs", headers=self.headers, params=params
                headers=self.headers(),
                params=params
            )
-            if response.status_code != 200:
+            if res.status_code not in range(200, 400):
-                raise ZipRecruiterException(
+                if res.status_code == 429:
-                    f"bad response status code: {response.status_code}"
+                    err = "429 Response - Blocked by ZipRecruiter for too many requests"
-                )
+                else:
                    err = f"ZipRecruiter response status code {res.status_code}"
                    err += f" with response: {res.text}"  # ZipRecruiter likely not available in EU
                logger.error(err)
                return jobs_list, ""
        except Exception as e:
-            if "Proxy responded with non 200 code" in str(e):
+            if "Proxy responded with" in str(e):
-                raise ZipRecruiterException("bad proxy")
+                logger.error(f"Indeed: Bad proxy")
-            raise ZipRecruiterException(str(e))
+            else:
-
+                logger.error(f"Indeed: {str(e)}")
-        response_data = response.json()
+            return jobs_list, ""
        jobs_list = response_data.get("jobs", [])
        next_continue_token = response_data.get("continue", None)
        res_data = res.json()
        jobs_list = res_data.get("jobs", [])
        next_continue_token = res_data.get("continue", None)
        with ThreadPoolExecutor(max_workers=self.jobs_per_page) as executor:
-            job_results = [executor.submit(self.process_job, job) for job in jobs_list]
+            job_results = [executor.submit(self._process_job, job) for job in jobs_list]
        job_list = list(filter(None, (result.result() for result in job_results)))
        return job_list, next_continue_token
-    def scrape(self, scraper_input: ScraperInput) -> JobResponse:
+    def _process_job(self, job: dict) -> JobPost | None:
        """
-        Scrapes ZipRecruiter for jobs with scraper_input criteria.
+        Processes an individual job dict from the response
        :param scraper_input: Information about job search criteria.
        :return: JobResponse containing a list of jobs.
        """
        job_list: list[JobPost] = []
        continue_token = None
        max_pages = math.ceil(scraper_input.results_wanted / self.jobs_per_page)
        for page in range(1, max_pages + 1):
            if len(job_list) >= scraper_input.results_wanted:
                break
            if page > 1:
                time.sleep(self.delay)
            jobs_on_page, continue_token = self.find_jobs_in_page(
                scraper_input, continue_token
            )
            if jobs_on_page:
                job_list.extend(jobs_on_page)
            if not continue_token:
                break
        return JobResponse(jobs=job_list[: scraper_input.results_wanted])
    def process_job(self, job: dict) -> JobPost | None:
        """Processes an individual job dict from the response"""
        title = job.get("name")
-        job_url = f"https://www.ziprecruiter.com/jobs//j?lvk={job['listing_key']}"
+        job_url = f"{self.base_url}/jobs//j?lvk={job['listing_key']}"
        if job_url in self.seen_urls:
            return
        self.seen_urls.add(job_url)
-        job_description_html = job.get("job_description", "").strip()
+        description = job.get("job_description", "").strip()
-        description_soup = BeautifulSoup(job_description_html, "html.parser")
+        description = (
-        description = modify_and_get_description(description_soup)
+            markdown_converter(description)
-
+            if self.scraper_input.description_format == DescriptionFormat.MARKDOWN
            else description
        )
        company = job.get("hiring_company", {}).get("name")
        country_value = "usa" if job.get("job_country") == "US" else "canada"
        country_enum = Country.from_string(country_value)
@@ -118,92 +141,71 @@ class ZipRecruiterScraper(Scraper):
        location = Location(
            city=job.get("job_city"), state=job.get("job_state"), country=country_enum
        )
-        job_type = ZipRecruiterScraper.get_job_type_enum(
+        job_type = self._get_job_type_enum(
            job.get("employment_type", "").replace("_", "").lower()
        )
-        date_posted = datetime.fromisoformat(job['posted_time'].rstrip("Z")).date()
+        date_posted = datetime.fromisoformat(job["posted_time"].rstrip("Z")).date()
-
+        comp_interval = job.get("compensation_interval")
        comp_interval = "yearly" if comp_interval == "annual" else comp_interval
        comp_min = int(job["compensation_min"]) if "compensation_min" in job else None
        comp_max = int(job["compensation_max"]) if "compensation_max" in job else None
        comp_currency = job.get("compensation_currency")
        return JobPost(
            title=title,
            company_name=company,
            location=location,
            job_type=job_type,
            compensation=Compensation(
-                interval="yearly"
+                interval=comp_interval,
-                if job.get("compensation_interval") == "annual"
+                min_amount=comp_min,
-                else job.get("compensation_interval"),
+                max_amount=comp_max,
-                min_amount=int(job["compensation_min"])
+                currency=comp_currency,
                if "compensation_min" in job
                else None,
                max_amount=int(job["compensation_max"])
                if "compensation_max" in job
                else None,
                currency=job.get("compensation_currency"),
            ),
            date_posted=date_posted,
            job_url=job_url,
            description=description,
            emails=extract_emails_from_text(description) if description else None,
            num_urgent_words=count_urgent_words(description) if description else None,
        )
-    def get_cookies(self):
+    def _get_cookies(self):
-        url="https://api.ziprecruiter.com/jobs-app/event"
+        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"
-        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"
+        url = f"{self.api_url}/jobs-app/event"
-        self.session.post(url, data=data, headers=ZipRecruiterScraper.headers())
+        self.session.post(url, data=data, headers=self.headers)
    @staticmethod
-    def get_job_type_enum(job_type_str: str) -> list[JobType] | None:
+    def _get_job_type_enum(job_type_str: str) -> list[JobType] | None:
        for job_type in JobType:
            if job_type_str in job_type.value:
                return [job_type]
        return None
    @staticmethod
-    def add_params(scraper_input) -> dict[str, str | Any]:
+    def _add_params(scraper_input) -> dict[str, str | Any]:
        params = {
            "search": scraper_input.search_term,
            "location": scraper_input.location,
        }
-        job_type_value = None
+        if scraper_input.hours_old:
            params["days"] = max(scraper_input.hours_old // 24, 1)
        job_type_map = {JobType.FULL_TIME: "full_time", JobType.PART_TIME: "part_time"}
        if scraper_input.job_type:
-            if scraper_input.job_type.value == "fulltime":
+            job_type = scraper_input.job_type
-                job_type_value = "full_time"
+            params["employment_type"] = job_type_map.get(job_type, job_type.value[0])
            elif scraper_input.job_type.value == "parttime":
                job_type_value = "part_time"
            else:
                job_type_value = scraper_input.job_type.value
        if scraper_input.easy_apply:
-            params['zipapply'] = 1
+            params["zipapply"] = 1
        if job_type_value:
            params[
                "refine_by_employment"
            ] = f"employment_type:employment_type:{job_type_value}"
        if scraper_input.is_remote:
-            params["refine_by_location_type"] = "only_remote"
+            params["remote"] = 1
        if scraper_input.distance:
            params["radius"] = scraper_input.distance
        return {k: v for k, v in params.items() if v is not None}
-        params = {k: v for k, v in params.items() if v is not None}
+    headers = {
-
+        "Host": "api.ziprecruiter.com",
-        return params
+        "accept": "*/*",
-
+        "x-zr-zva-override": "100000000;vid:ZT1huzm_EQlDTVEc",
-    @staticmethod
+        "x-pushnotificationid": "0ff4983d38d7fc5b3370297f2bcffcf4b3321c418f5c22dd152a0264707602a0",
-    def headers() -> dict:
+        "x-deviceid": "D77B3A92-E589-46A4-8A39-6EF6F1D86006",
-        """
+        "user-agent": "Job Search/87.0 (iPhone; CPU iOS 16_6_1 like Mac OS X)",
-        Returns headers needed for requests
+        "authorization": "Basic YTBlZjMyZDYtN2I0Yy00MWVkLWEyODMtYTI1NDAzMzI0YTcyOg==",
-        :return: dict - Dictionary containing headers
+        "accept-language": "en-US,en;q=0.9",
-        """
+    }
        return {
            "Host": "api.ziprecruiter.com",
            "accept": "*/*",
            "x-zr-zva-override": "100000000;vid:ZT1huzm_EQlDTVEc",
            "x-pushnotificationid": "0ff4983d38d7fc5b3370297f2bcffcf4b3321c418f5c22dd152a0264707602a0",
            "x-deviceid": "D77B3A92-E589-46A4-8A39-6EF6F1D86006",
            "user-agent": "Job Search/87.0 (iPhone; CPU iOS 16_6_1 like Mac OS X)",
            "authorization": "Basic YTBlZjMyZDYtN2I0Yy00MWVkLWEyODMtYTI1NDAzMzI0YTcyOg==",
            "accept-language": "en-US,en;q=0.9",
        }
Author	SHA1	Message	Date
Cullen Watson	3b0017964c	fix: indeed empty search term	2024-03-11 09:21:11 -05:00
VitaminB16	94d8f555fd	format: Apply Black formatter to the codebase (#127 )	2024-03-10 23:36:27 -05:00
Cullen Watson	e8b4b376b8	docs: readme	2024-03-09 13:40:34 -06:00
Cullen Watson	54ac1bad16	docs: readme	2024-03-09 01:49:05 -06:00
Cullen Watson	0a669e9ba8	enh: indeed more fields (#126 )	2024-03-09 01:40:01 -06:00
gigaSec	a4f6851c32	Fix GlassDoor Country Vietnam(#122 )	2024-03-04 17:35:57 -06:00
troy-conte	db01bc6bbb	log search updates, fix glassdoor (#120 )	2024-03-04 16:39:38 -06:00
Cullen Watson	f8a4eccc6b	Remove pandas warning (#118 )	2024-02-29 21:30:56 -06:00
Cullen Watson	ba3a16b228	Description format (#107 )	2024-02-14 16:04:23 -06:00
Cullen Watson	aeb1a50d2c	fix job type search (#106 )	2024-02-12 11:02:48 -06:00
VitaminB16	91b137ef86	feat: Ability to query by time posted for linkedin, indeed, glassdoor, ziprecruiter (#103 )	2024-02-09 14:02:03 -06:00
Cullen Watson	2563c5ca08	enh: Indeed company url (#104 )	2024-02-09 12:05:10 -06:00
Cullen Watson	32282305c8	docs: readme	2024-02-08 18:13:19 -06:00