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17 Commits

Author SHA1 Message Date
Cullen Watson
aeb93b99f5 Update pyproject.toml 2024-01-03 12:04:50 -06:00
Cullen Watson
a5916edcdd fix(glassdoor): add retry adapter (#77) 2024-01-03 12:04:32 -06:00
Augusto Gunsch
33d442bf1e Add czech to Indeed (#72) 2023-12-02 02:42:54 -06:00
Zachary Hampton
6587e464fa Update README.md 2023-11-30 11:49:31 -07:00
Vincent Yan
eed7fca300 Get full indeed description (#70) 2023-11-27 15:00:36 -06:00
Faraz Khan
dfb8c18c51 include location with 3 parts (#69) 2023-11-10 16:59:42 -06:00
Faraz Khan
81f70ff8a5 added salary data for linkedin (#68) 2023-11-09 14:57:15 -06:00
Cullen Watson
cc9e7866b7 fix linkedin bug & add linkedin company url (#67) 2023-11-08 15:51:07 -06:00
Zachary Hampton
a2c8fe046e Update README.md 2023-11-06 22:13:19 -07:00
Cullen Watson
2b7fea40a5 [fix] glassdoor duplicates 2023-10-30 20:29:55 -05:00
Cullen Watson
d37f86e1b9 [fix] glassdoor location 2023-10-30 20:19:56 -05:00
Cullen Watson
0302ab14f5 glassdoor keywords 2023-10-30 20:07:31 -05:00
Cullen Watson
3f2b582445 add glassdoor (#66) 2023-10-30 19:57:36 -05:00
Cullen Watson
93223b6a38 bug fix 2023-10-30 13:57:23 -05:00
Cullen Watson
e3fc222eb5 readd proxy support for zip (#64) 2023-10-29 08:54:56 -05:00
Cullen
b303b3f841 chore: version 2023-10-28 16:58:32 -05:00
Cullen
1a0c75f323 chore: version 2023-10-28 16:54:04 -05:00
14 changed files with 544 additions and 289 deletions

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@@ -4,15 +4,12 @@
**Not technical?** Try out the web scraping tool on our site at [usejobspy.com](https://usejobspy.com).
*Looking to build a data-focused software product?* **[Book a call](https://calendly.com/bunsly/15min)** *to
work with us.*
\
Check out another project we wrote: ***[HomeHarvest](https://github.com/Bunsly/HomeHarvest)** a Python package
for real estate scraping*
*Looking to build a data-focused software product?* **[Book a call](https://bunsly.com/)** *to
work with us.*
## Features
- Scrapes job postings from **LinkedIn**, **Indeed** & **ZipRecruiter** simultaneously
- Scrapes job postings from **LinkedIn**, **Indeed**, **Glassdoor**, & **ZipRecruiter** simultaneously
- Aggregates the job postings in a Pandas DataFrame
- Proxy support (HTTP/S, SOCKS)
@@ -35,15 +32,15 @@ _Python version >= [3.10](https://www.python.org/downloads/release/python-3100/)
from jobspy import scrape_jobs
jobs = scrape_jobs(
site_name=["indeed", "linkedin", "zip_recruiter"],
site_name=["indeed", "linkedin", "zip_recruiter", "glassdoor"],
search_term="software engineer",
location="Dallas, TX",
results_wanted=10,
country_indeed='USA' # only needed for indeed
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", index=False) # to_xlsx
```
### Output
@@ -62,7 +59,7 @@ zip_recruiter Software Developer TEKsystems Phoenix
```plaintext
Required
├── site_type (List[enum]): linkedin, zip_recruiter, indeed
├── site_type (List[enum]): linkedin, zip_recruiter, indeed, glassdoor
└── search_term (str)
Optional
├── location (int)
@@ -107,43 +104,46 @@ 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.
LinkedIn searches globally & uses only the `location` parameter. You can only fetch 1000 jobs max from the LinkedIn endpoint we're using
### **ZipRecruiter**
ZipRecruiter searches for jobs in **US/Canada** & uses only the `location` parameter.
### **Indeed**
### **Indeed / Glassdoor**
Indeed supports most countries, but the `country_indeed` parameter is required. Additionally, use the `location`
parameter to narrow down the location, e.g. city & state if necessary.
Indeed & Glassdoor supports most countries, but the `country_indeed` parameter is required. Additionally, use the `location`
parameter to narrow down the location, e.g. city & state if necessary.
You can specify the following countries when searching on Indeed (use the exact name):
You can specify the following countries when searching on Indeed (use the exact name, * indicates support for Glassdoor):
| | | | |
|----------------------|--------------|------------|----------------|
| Argentina | Australia | Austria | Bahrain |
| Belgium | Brazil | Canada | Chile |
| Argentina | Australia* | Austria* | Bahrain |
| Belgium* | Brazil* | Canada* | Chile |
| China | Colombia | Costa Rica | Czech Republic |
| Denmark | Ecuador | Egypt | Finland |
| France | Germany | Greece | Hong Kong |
| Hungary | India | Indonesia | Ireland |
| Israel | Italy | Japan | Kuwait |
| Luxembourg | Malaysia | Mexico | Morocco |
| Netherlands | New Zealand | Nigeria | Norway |
| France* | Germany* | Greece | Hong Kong* |
| Hungary | India* | Indonesia | Ireland* |
| Israel | Italy* | Japan | Kuwait |
| Luxembourg | Malaysia | Mexico* | Morocco |
| Netherlands* | New Zealand* | Nigeria | Norway |
| Oman | Pakistan | Panama | Peru |
| Philippines | Poland | Portugal | Qatar |
| Romania | Saudi Arabia | Singapore | South Africa |
| South Korea | Spain | Sweden | Switzerland |
| Romania | Saudi Arabia | Singapore* | South Africa |
| South Korea | Spain* | Sweden | Switzerland* |
| Taiwan | Thailand | Turkey | Ukraine |
| United Arab Emirates | UK | USA | Uruguay |
| United Arab Emirates | UK* | USA* | Uruguay |
| Venezuela | Vietnam | | |
Glassdoor can only fetch 900 jobs from the endpoint we're using on a given search.
## Frequently Asked Questions
---

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@@ -1,7 +1,7 @@
[tool.poetry]
name = "python-jobspy"
version = "1.1.17"
description = "Job scraper for LinkedIn, Indeed & ZipRecruiter"
version = "1.1.31"
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"
readme = "README.md"

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@@ -6,18 +6,21 @@ from typing import Tuple, Optional
from .jobs import JobType, Location
from .scrapers.indeed import IndeedScraper
from .scrapers.ziprecruiter import ZipRecruiterScraper
from .scrapers.glassdoor import GlassdoorScraper
from .scrapers.linkedin import LinkedInScraper
from .scrapers import ScraperInput, Site, JobResponse, Country
from .scrapers.exceptions import (
LinkedInException,
IndeedException,
ZipRecruiterException,
GlassdoorException,
)
SCRAPER_MAPPING = {
Site.LINKEDIN: LinkedInScraper,
Site.INDEED: IndeedScraper,
Site.ZIP_RECRUITER: ZipRecruiterScraper,
Site.GLASSDOOR: GlassdoorScraper,
}
@@ -90,6 +93,8 @@ def scrape_jobs(
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
@@ -127,7 +132,10 @@ def scrape_jobs(
job_data["emails"] = (
", ".join(job_data["emails"]) if job_data["emails"] else None
)
job_data["location"] = Location(**job_data["location"]).display_location()
if job_data["location"]:
job_data["location"] = Location(
**job_data["location"]
).display_location()
compensation_obj = job_data.get("compensation")
if compensation_obj and isinstance(compensation_obj, dict):
@@ -155,6 +163,7 @@ def scrape_jobs(
"site",
"title",
"company",
"company_url",
"location",
"job_type",
"date_posted",

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@@ -1,7 +1,6 @@
from typing import Union, Optional
from datetime import date
from enum import Enum
from pydantic import BaseModel, validator
@@ -56,40 +55,46 @@ class JobType(Enum):
class Country(Enum):
ARGENTINA = ("argentina", "ar")
AUSTRALIA = ("australia", "au")
AUSTRIA = ("austria", "at")
"""
Gets the subdomain for Indeed and Glassdoor.
The second item in the tuple is the subdomain for Indeed
The third item in the tuple is the subdomain (and tld if there's a ':' separator) for Glassdoor
"""
ARGENTINA = ("argentina", "ar", "com.ar")
AUSTRALIA = ("australia", "au", "com.au")
AUSTRIA = ("austria", "at", "at")
BAHRAIN = ("bahrain", "bh")
BELGIUM = ("belgium", "be")
BRAZIL = ("brazil", "br")
CANADA = ("canada", "ca")
BELGIUM = ("belgium", "be", "fr:be")
BRAZIL = ("brazil", "br", "com.br")
CANADA = ("canada", "ca", "ca")
CHILE = ("chile", "cl")
CHINA = ("china", "cn")
COLOMBIA = ("colombia", "co")
COSTARICA = ("costa rica", "cr")
CZECHREPUBLIC = ("czech republic", "cz")
CZECHREPUBLIC = ("czech republic,czechia", "cz")
DENMARK = ("denmark", "dk")
ECUADOR = ("ecuador", "ec")
EGYPT = ("egypt", "eg")
FINLAND = ("finland", "fi")
FRANCE = ("france", "fr")
GERMANY = ("germany", "de")
FRANCE = ("france", "fr", "fr")
GERMANY = ("germany", "de", "de")
GREECE = ("greece", "gr")
HONGKONG = ("hong kong", "hk")
HONGKONG = ("hong kong", "hk", "com.hk")
HUNGARY = ("hungary", "hu")
INDIA = ("india", "in")
INDIA = ("india", "in", "co.in")
INDONESIA = ("indonesia", "id")
IRELAND = ("ireland", "ie")
IRELAND = ("ireland", "ie", "ie")
ISRAEL = ("israel", "il")
ITALY = ("italy", "it")
ITALY = ("italy", "it", "it")
JAPAN = ("japan", "jp")
KUWAIT = ("kuwait", "kw")
LUXEMBOURG = ("luxembourg", "lu")
MALAYSIA = ("malaysia", "malaysia")
MEXICO = ("mexico", "mx")
MEXICO = ("mexico", "mx", "com.mx")
MOROCCO = ("morocco", "ma")
NETHERLANDS = ("netherlands", "nl")
NEWZEALAND = ("new zealand", "nz")
NETHERLANDS = ("netherlands", "nl", "nl")
NEWZEALAND = ("new zealand", "nz", "co.nz")
NIGERIA = ("nigeria", "ng")
NORWAY = ("norway", "no")
OMAN = ("oman", "om")
@@ -102,19 +107,19 @@ class Country(Enum):
QATAR = ("qatar", "qa")
ROMANIA = ("romania", "ro")
SAUDIARABIA = ("saudi arabia", "sa")
SINGAPORE = ("singapore", "sg")
SINGAPORE = ("singapore", "sg", "sg")
SOUTHAFRICA = ("south africa", "za")
SOUTHKOREA = ("south korea", "kr")
SPAIN = ("spain", "es")
SPAIN = ("spain", "es", "es")
SWEDEN = ("sweden", "se")
SWITZERLAND = ("switzerland", "ch")
SWITZERLAND = ("switzerland", "ch", "de:ch")
TAIWAN = ("taiwan", "tw")
THAILAND = ("thailand", "th")
TURKEY = ("turkey", "tr")
UKRAINE = ("ukraine", "ua")
UNITEDARABEMIRATES = ("united arab emirates", "ae")
UK = ("uk", "uk")
USA = ("usa", "www")
UK = ("uk,united kingdom", "uk", "co.uk")
USA = ("usa,us,united states", "www", "com")
URUGUAY = ("uruguay", "uy")
VENEZUELA = ("venezuela", "ve")
VIETNAM = ("vietnam", "vn")
@@ -122,34 +127,43 @@ class Country(Enum):
# internal for ziprecruiter
US_CANADA = ("usa/ca", "www")
# internal for linkeind
# internal for linkedin
WORLDWIDE = ("worldwide", "www")
def __new__(cls, country, domain):
obj = object.__new__(cls)
obj._value_ = country
obj.domain = domain
return obj
@property
def indeed_domain_value(self):
return self.value[1]
@property
def domain_value(self):
return self.domain
def glassdoor_domain_value(self):
if len(self.value) == 3:
subdomain, _, domain = self.value[2].partition(":")
if subdomain and domain:
return f"{subdomain}.glassdoor.{domain}"
else:
return f"www.glassdoor.{self.value[2]}"
else:
raise Exception(f"Glassdoor is not available for {self.name}")
def get_url(self):
return f"https://{self.glassdoor_domain_value}/"
@classmethod
def from_string(cls, country_str: str):
"""Convert a string to the corresponding Country enum."""
country_str = country_str.strip().lower()
for country in cls:
if country.value == country_str:
country_names = country.value[0].split(',')
if country_str in country_names:
return country
valid_countries = [country.value for country in cls]
raise ValueError(
f"Invalid country string: '{country_str}'. Valid countries (only include this param for Indeed) are: {', '.join(valid_countries)}"
f"Invalid country string: '{country_str}'. Valid countries are: {', '.join([country[0] for country in valid_countries])}"
)
class Location(BaseModel):
country: Country = None
country: Country | None = None
city: Optional[str] = None
state: Optional[str] = None
@@ -160,10 +174,13 @@ class Location(BaseModel):
if self.state:
location_parts.append(self.state)
if self.country and self.country not in (Country.US_CANADA, Country.WORLDWIDE):
if self.country.value in ("usa", "uk"):
location_parts.append(self.country.value.upper())
country_name = self.country.value[0]
if "," in country_name:
country_name = country_name.split(",")[0]
if country_name in ("usa", "uk"):
location_parts.append(country_name.upper())
else:
location_parts.append(self.country.value.title())
location_parts.append(country_name.title())
return ", ".join(location_parts)
@@ -174,6 +191,10 @@ class CompensationInterval(Enum):
DAILY = "daily"
HOURLY = "hourly"
@classmethod
def get_interval(cls, pay_period):
return cls[pay_period].value if pay_period in cls.__members__ else None
class Compensation(BaseModel):
interval: Optional[CompensationInterval] = None
@@ -189,6 +210,8 @@ class JobPost(BaseModel):
location: Optional[Location]
description: str | None = None
company_url: str | None = None
job_type: list[JobType] | None = None
compensation: Compensation | None = None
date_posted: date | None = None

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@@ -6,6 +6,7 @@ class Site(Enum):
LINKEDIN = "linkedin"
INDEED = "indeed"
ZIP_RECRUITER = "zip_recruiter"
GLASSDOOR = "glassdoor"
class ScraperInput(BaseModel):

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@@ -19,3 +19,8 @@ class IndeedException(Exception):
class ZipRecruiterException(Exception):
def __init__(self, message=None):
super().__init__(message or "An error occurred with ZipRecruiter")
class GlassdoorException(Exception):
def __init__(self, message=None):
super().__init__(message or "An error occurred with Glassdoor")

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@@ -0,0 +1,274 @@
"""
jobspy.scrapers.glassdoor
~~~~~~~~~~~~~~~~~~~
This module contains routines to scrape Glassdoor.
"""
import json
from typing import Optional, Any
from datetime import datetime, timedelta
from .. import Scraper, ScraperInput, Site
from ..exceptions import GlassdoorException
from ..utils import create_session
from ...jobs import (
JobPost,
Compensation,
CompensationInterval,
Location,
JobResponse,
JobType,
)
class GlassdoorScraper(Scraper):
def __init__(self, proxy: Optional[str] = None):
"""
Initializes GlassdoorScraper with the Glassdoor job search url
"""
site = Site(Site.GLASSDOOR)
super().__init__(site, proxy=proxy)
self.url = None
self.country = None
self.jobs_per_page = 30
self.seen_urls = set()
def fetch_jobs_page(
self,
scraper_input: ScraperInput,
location_id: int,
location_type: str,
page_num: int,
cursor: str | None,
) -> (list[JobPost], str | None):
"""
Scrapes a page of Glassdoor for jobs with scraper_input criteria
"""
try:
payload = self.add_payload(
scraper_input, location_id, location_type, page_num, cursor
)
session = create_session(self.proxy, is_tls=False, has_retry=True)
response = session.post(
f"{self.url}/graph", headers=self.headers(), timeout=10, data=payload
)
if response.status_code != 200:
raise GlassdoorException(
f"bad response status code: {response.status_code}"
)
res_json = response.json()[0]
if "errors" in res_json:
raise ValueError("Error encountered in API response")
except Exception as e:
raise GlassdoorException(str(e))
jobs_data = res_json["data"]["jobListings"]["jobListings"]
jobs = []
for i, job in enumerate(jobs_data):
job_url = res_json["data"]["jobListings"]["jobListingSeoLinks"][
"linkItems"
][i]["url"]
if job_url in self.seen_urls:
continue
self.seen_urls.add(job_url)
job = job["jobview"]
title = job["job"]["jobTitleText"]
company_name = job["header"]["employerNameFromSearch"]
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
if location_type == "S":
is_remote = True
else:
location = self.parse_location(location_name)
compensation = self.parse_compensation(job["header"])
job = JobPost(
title=title,
company_name=company_name,
date_posted=date_posted,
job_url=job_url,
location=location,
compensation=compensation,
is_remote=is_remote
)
jobs.append(job)
return jobs, self.get_cursor_for_page(
res_json["data"]["jobListings"]["paginationCursors"], page_num + 1
)
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.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)
@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
interval = None
if pay_period == "ANNUAL":
interval = CompensationInterval.YEARLY
elif pay_period:
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,
max_amount=max_amount,
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"
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": [],
"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:
if job_type_str in job_type.value:
return [job_type]
return None
@staticmethod
def parse_location(location_name: str) -> Location:
if not location_name or location_name == "Remote":
return None
city, _, state = location_name.partition(", ")
return Location(city=city, state=state)
@staticmethod
def get_cursor_for_page(pagination_cursors, page_num):
for cursor_data in pagination_cursors:
if cursor_data["pageNumber"] == page_num:
return cursor_data["cursor"]
return None
@staticmethod
def headers() -> dict:
"""
Returns headers needed for requests
:return: dict - Dictionary containing headers
"""
return {
"authority": "www.glassdoor.com",
"accept": "*/*",
"accept-language": "en-US,en;q=0.9",
"apollographql-client-name": "job-search-next",
"apollographql-client-version": "4.65.5",
"content-type": "application/json",
"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',
"gd-csrf-token": "Ft6oHEWlRZrxDww95Cpazw:0pGUrkb2y3TyOpAIqF2vbPmUXoXVkD3oEGDVkvfeCerceQ5-n8mBg3BovySUIjmCPHCaW0H2nQVdqzbtsYqf4Q:wcqRqeegRUa9MVLJGyujVXB7vWFPjdaS1CtrrzJq-ok",
"origin": "https://www.glassdoor.com",
"referer": "https://www.glassdoor.com/",
"sec-ch-ua": '"Chromium";v="118", "Google Chrome";v="118", "Not=A?Brand";v="99"',
"sec-ch-ua-mobile": "?0",
"sec-ch-ua-platform": '"macOS"',
"sec-fetch-dest": "empty",
"sec-fetch-mode": "cors",
"sec-fetch-site": "same-origin",
"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",
}

View File

@@ -56,15 +56,15 @@ class IndeedScraper(Scraper):
:return: jobs found on page, total number of jobs found for search
"""
self.country = scraper_input.country
domain = self.country.domain_value
domain = self.country.indeed_domain_value
self.url = f"https://{domain}.indeed.com"
session = create_session(self.proxy)
params = {
"q": scraper_input.search_term,
"l": scraper_input.location,
"filter": 0,
"start": scraper_input.offset + page * 10,
"sort": "date"
}
if scraper_input.distance:
params["radius"] = scraper_input.distance
@@ -78,6 +78,7 @@ class IndeedScraper(Scraper):
if sc_values:
params["sc"] = "0kf:" + "".join(sc_values) + ";"
try:
session = create_session(self.proxy, is_tls=True)
response = session.get(
f"{self.url}/jobs",
headers=self.get_headers(),
@@ -150,6 +151,7 @@ class IndeedScraper(Scraper):
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"),
@@ -235,35 +237,16 @@ class IndeedScraper(Scraper):
if response.status_code not in range(200, 400):
return None
soup = BeautifulSoup(response.text, "html.parser")
script_tag = soup.find(
"script", text=lambda x: x and "window._initialData" in x
)
if not script_tag:
return None
script_code = script_tag.string
match = re.search(r"window\._initialData\s*=\s*({.*?})\s*;", script_code, re.S)
if not match:
return None
json_string = match.group(1)
data = json.loads(json_string)
try:
job_description = data["jobInfoWrapperModel"]["jobInfoModel"][
data = json.loads(response.text)
job_description = data["body"]["jobInfoWrapperModel"]["jobInfoModel"][
"sanitizedJobDescription"
]
except (KeyError, TypeError, IndexError):
return None
soup = BeautifulSoup(
job_description, "html.parser"
)
text_content = " ".join(
soup.get_text(separator=" ").split()
).strip()
soup = BeautifulSoup(job_description, "html.parser")
text_content = " ".join(soup.get_text(separator=" ").split()).strip()
return text_content
@@ -324,7 +307,7 @@ class IndeedScraper(Scraper):
raise IndeedException("Could not find mosaic provider job cards data")
else:
raise IndeedException(
"Could not find a script tag containing mosaic provider data"
"Could not find any results for the search"
)
@staticmethod

View File

@@ -10,20 +10,15 @@ from datetime import datetime
import requests
import time
from requests.exceptions import ProxyError
from concurrent.futures import ThreadPoolExecutor, as_completed
from bs4 import BeautifulSoup
from bs4.element import Tag
from threading import Lock
from urllib.parse import urlparse, urlunparse
from .. import Scraper, ScraperInput, Site
from ..utils import count_urgent_words, extract_emails_from_text, get_enum_from_job_type
from ..utils import count_urgent_words, extract_emails_from_text, get_enum_from_job_type, currency_parser
from ..exceptions import LinkedInException
from ...jobs import (
JobPost,
Location,
JobResponse,
JobType,
)
from ...jobs import JobPost, Location, JobResponse, JobType, Country, Compensation
class LinkedInScraper(Scraper):
@@ -71,12 +66,10 @@ class LinkedInScraper(Scraper):
if scraper_input.job_type
else None,
"pageNum": 0,
page: page + scraper_input.offset,
"start": page + scraper_input.offset,
"f_AL": "true" if scraper_input.easy_apply else None,
}
params = {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}
retries = 0
while retries < self.MAX_RETRIES:
@@ -93,7 +86,7 @@ class LinkedInScraper(Scraper):
break
except requests.HTTPError as e:
if hasattr(e, "response") and e.response is not None:
if e.response.status_code == 429:
if e.response.status_code in (429, 502):
time.sleep(self.DELAY)
retries += 1
continue
@@ -115,43 +108,59 @@ class LinkedInScraper(Scraper):
soup = BeautifulSoup(response.text, "html.parser")
with ThreadPoolExecutor(max_workers=5) as executor:
futures = []
for job_card in soup.find_all("div", class_="base-search-card"):
job_url = None
href_tag = job_card.find("a", class_="base-card__full-link")
if href_tag and "href" in href_tag.attrs:
href = href_tag.attrs["href"].split("?")[0]
job_id = href.split("-")[-1]
job_url = f"{self.url}/jobs/view/{job_id}"
for job_card in soup.find_all("div", class_="base-search-card"):
job_url = None
href_tag = job_card.find("a", class_="base-card__full-link")
if href_tag and "href" in href_tag.attrs:
href = href_tag.attrs["href"].split("?")[0]
job_id = href.split("-")[-1]
job_url = f"{self.url}/jobs/view/{job_id}"
with url_lock:
if job_url in seen_urls:
continue
seen_urls.add(job_url)
with url_lock:
if job_url in seen_urls:
continue
seen_urls.add(job_url)
futures.append(executor.submit(self.process_job, job_card, job_url))
# Call process_job directly without threading
try:
job_post = self.process_job(job_card, job_url)
if job_post:
job_list.append(job_post)
except Exception as e:
raise LinkedInException("Exception occurred while processing jobs")
for future in as_completed(futures):
try:
job_post = future.result()
if job_post:
job_list.append(job_post)
except Exception as e:
raise LinkedInException(
"Exception occurred while processing jobs"
)
page += 25
job_list = job_list[: scraper_input.results_wanted]
return JobResponse(jobs=job_list)
def process_job(self, job_card: Tag, job_url: str) -> 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_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'
compensation = Compensation(
min_amount=int(salary_min),
max_amount=int(salary_max),
currency=currency,
)
title_tag = job_card.find("span", class_="sr-only")
title = title_tag.get_text(strip=True) if title_tag else "N/A"
company_tag = job_card.find("h4", class_="base-search-card__subtitle")
company_a_tag = company_tag.find("a") if company_tag else None
company_url = (
urlunparse(urlparse(company_a_tag.get("href"))._replace(query=""))
if company_a_tag and company_a_tag.has_attr("href")
else ""
)
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")
@@ -173,16 +182,18 @@ class LinkedInScraper(Scraper):
benefits = " ".join(benefits_tag.get_text().split()) if benefits_tag else None
description, job_type = self.get_job_description(job_url)
# description, job_type = None, []
return JobPost(
title=title,
description=description,
company_name=company,
company_url=company_url,
location=location,
date_posted=date_posted,
job_url=job_url,
# job_type=[JobType.FULL_TIME],
job_type=job_type,
compensation=compensation,
benefits=benefits,
emails=extract_emails_from_text(description) if description else None,
num_urgent_words=count_urgent_words(description) if description else None,
@@ -199,8 +210,15 @@ class LinkedInScraper(Scraper):
try:
response = requests.get(job_page_url, timeout=5, proxies=self.proxy)
response.raise_for_status()
except requests.HTTPError as e:
if hasattr(e, "response") and e.response is not None:
if e.response.status_code in (429, 502):
time.sleep(self.DELAY)
return None, None
except Exception as e:
return None, None
if response.url == "https://www.linkedin.com/signup":
return None, None
soup = BeautifulSoup(response.text, "html.parser")
div_content = soup.find(
@@ -236,7 +254,7 @@ class LinkedInScraper(Scraper):
employment_type = employment_type.lower()
employment_type = employment_type.replace("-", "")
return [get_enum_from_job_type(employment_type)]
return [get_enum_from_job_type(employment_type)] if employment_type else []
return description, get_job_type(soup)
@@ -246,7 +264,7 @@ class LinkedInScraper(Scraper):
:param metadata_card
:return: location
"""
location = Location(country=self.country)
location = Location(country=Country.from_string(self.country))
if metadata_card is not None:
location_tag = metadata_card.find(
"span", class_="job-search-card__location"
@@ -258,7 +276,14 @@ class LinkedInScraper(Scraper):
location = Location(
city=city,
state=state,
country=self.country,
country=Country.from_string(self.country),
)
elif len(parts) == 3:
city, state, country = parts
location = Location(
city=city,
state=state,
country=Country.from_string(country),
)
return location

View File

@@ -1,5 +1,10 @@
import re
import numpy as np
import tls_client
import requests
from requests.adapters import HTTPAdapter, Retry
from ..jobs import JobType
@@ -24,23 +29,33 @@ def extract_emails_from_text(text: str) -> list[str] | None:
return email_regex.findall(text)
def create_session(proxy: str | None = None):
def create_session(proxy: dict | None = None, is_tls: bool = True, has_retry: bool = False):
"""
Creates a tls client session
Creates a requests session with optional tls, proxy, and retry settings.
:return: A session object with or without proxies.
:return: A session object
"""
session = tls_client.Session(
client_identifier="chrome112",
random_tls_extension_order=True,
)
session.proxies = proxy
# TODO multiple proxies
# if self.proxies:
# session.proxies = {
# "http": random.choice(self.proxies),
# "https": random.choice(self.proxies),
# }
if is_tls:
session = tls_client.Session(
client_identifier="chrome112",
random_tls_extension_order=True,
)
session.proxies = proxy
else:
session = requests.Session()
session.allow_redirects = True
if proxy:
session.proxies.update(proxy)
if has_retry:
retries = Retry(total=3,
connect=3,
status=3,
status_forcelist=[500, 502, 503, 504, 429],
backoff_factor=1)
adapter = HTTPAdapter(max_retries=retries)
session.mount('http://', adapter)
session.mount('https://', adapter)
return session
@@ -54,3 +69,19 @@ def get_enum_from_job_type(job_type_str: str) -> JobType | None:
if job_type_str in job_type.value:
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)
# Remove any 000s separators (either , or .)
cur_str = re.sub("[.,]", '', cur_str[:-3]) + cur_str[-3:]
if '.' in list(cur_str[-3:]):
num = float(cur_str)
elif ',' in list(cur_str[-3:]):
num = float(cur_str.replace(',', '.'))
else:
num = float(cur_str)
return np.round(num, 2)

View File

@@ -9,31 +9,20 @@ import time
import re
from datetime import datetime, date
from typing import Optional, Tuple, Any
from urllib.parse import urlparse, parse_qs, urlunparse
import requests
from bs4 import BeautifulSoup
from bs4.element import Tag
from concurrent.futures import ThreadPoolExecutor, Future
from concurrent.futures import ThreadPoolExecutor
from .. import Scraper, ScraperInput, Site
from ..exceptions import ZipRecruiterException
from ..utils import count_urgent_words, extract_emails_from_text, create_session
from ...jobs import (
JobPost,
Compensation,
CompensationInterval,
Location,
JobResponse,
JobType,
Country,
)
from ...jobs import JobPost, Compensation, Location, JobResponse, JobType, Country
class ZipRecruiterScraper(Scraper):
def __init__(self, proxy: Optional[str] = None):
"""
Initializes LinkedInScraper with the ZipRecruiter job search url
Initializes ZipRecruiterScraper with the ZipRecruiter job search url
"""
site = Site(Site.ZIP_RECRUITER)
self.url = "https://www.ziprecruiter.com"
@@ -42,22 +31,25 @@ class ZipRecruiterScraper(Scraper):
self.jobs_per_page = 20
self.seen_urls = set()
def find_jobs_in_page(self, scraper_input: ScraperInput, continue_token: Optional[str] = None) -> Tuple[list[JobPost], Optional[str]]:
def find_jobs_in_page(
self, scraper_input: ScraperInput, continue_token: str | None = None
) -> Tuple[list[JobPost], Optional[str]]:
"""
Scrapes a page of ZipRecruiter for jobs with scraper_input criteria
:param scraper_input:
:param continue_token:
:return: jobs found on page
"""
params = self.add_params(scraper_input)
if continue_token:
params['continue'] = continue_token
params["continue"] = continue_token
try:
response = requests.get(
session = create_session(self.proxy, is_tls=True)
response = session.get(
f"https://api.ziprecruiter.com/jobs-app/jobs",
headers=self.headers(),
params=self.add_params(scraper_input),
allow_redirects=True,
timeout=10,
timeout_seconds=10,
)
if response.status_code != 200:
raise ZipRecruiterException(
@@ -71,13 +63,10 @@ class ZipRecruiterScraper(Scraper):
time.sleep(5)
response_data = response.json()
jobs_list = response_data.get("jobs", [])
next_continue_token = response_data.get('continue', None)
next_continue_token = response_data.get("continue", None)
with ThreadPoolExecutor(max_workers=10) as executor:
job_results = [
executor.submit(self.process_job, job)
for job in jobs_list
]
with ThreadPoolExecutor(max_workers=self.jobs_per_page) as executor:
job_results = [executor.submit(self.process_job, job) for job in jobs_list]
job_list = [result.result() for result in job_results if result.result()]
return job_list, next_continue_token
@@ -97,7 +86,9 @@ class ZipRecruiterScraper(Scraper):
if len(job_list) >= scraper_input.results_wanted:
break
jobs_on_page, continue_token = self.find_jobs_in_page(scraper_input, continue_token)
jobs_on_page, continue_token = self.find_jobs_in_page(
scraper_input, continue_token
)
if jobs_on_page:
job_list.extend(jobs_on_page)
@@ -105,23 +96,26 @@ class ZipRecruiterScraper(Scraper):
break
if len(job_list) > scraper_input.results_wanted:
job_list = job_list[:scraper_input.results_wanted]
job_list = job_list[: scraper_input.results_wanted]
return JobResponse(jobs=job_list)
def process_job(self, job: dict) -> JobPost:
"""the most common type of jobs page on ZR"""
@staticmethod
def process_job(job: dict) -> JobPost:
"""Processes an individual job dict from the response"""
title = job.get("name")
job_url = job.get("job_url")
description = BeautifulSoup(
job.get("job_description", "").strip(), "html.parser"
).get_text()
company = job['hiring_company'].get("name") if "hiring_company" in job else None
company = job["hiring_company"].get("name") if "hiring_company" in job else None
country_value = "usa" if job.get("job_country") == "US" else "canada"
country_enum = Country.from_string(country_value)
location = Location(
city=job.get("job_city"), state=job.get("job_state"), country='usa' if job.get("job_country") == 'US' else 'canada'
city=job.get("job_city"), state=job.get("job_state"), country=country_enum
)
job_type = ZipRecruiterScraper.get_job_type_enum(
job.get("employment_type", "").replace("_", "").lower()
@@ -144,9 +138,15 @@ class ZipRecruiterScraper(Scraper):
location=location,
job_type=job_type,
compensation=Compensation(
interval="yearly" if job.get("compensation_interval") == "annual" else job.get("compensation_interval") ,
min_amount=int(job["compensation_min"]) if "compensation_min" in job else None,
max_amount=int(job["compensation_max"]) if "compensation_max" in job else None,
interval="yearly"
if job.get("compensation_interval") == "annual"
else job.get("compensation_interval"),
min_amount=int(job["compensation_min"])
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,
@@ -192,121 +192,15 @@ class ZipRecruiterScraper(Scraper):
return params
@staticmethod
def get_interval(interval_str: str):
"""
Maps the interval alias to its appropriate CompensationInterval.
:param interval_str
:return: CompensationInterval
"""
interval_alias = {"annually": CompensationInterval.YEARLY}
interval_str = interval_str.lower()
if interval_str in interval_alias:
return interval_alias[interval_str]
return CompensationInterval(interval_str)
@staticmethod
def get_date_posted(job: Tag) -> Optional[datetime.date]:
"""
Extracts the date a job was posted
:param job
:return: date the job was posted or None
"""
button = job.find(
"button", {"class": "action_input save_job zrs_btn_secondary_200"}
)
if not button:
return None
url_time = button.get("data-href", "")
url_components = urlparse(url_time)
params = parse_qs(url_components.query)
posted_time_str = params.get("posted_time", [None])[0]
if posted_time_str:
posted_date = datetime.strptime(
posted_time_str, "%Y-%m-%dT%H:%M:%SZ"
).date()
return posted_date
return None
@staticmethod
def get_compensation(job: Tag) -> Optional[Compensation]:
"""
Parses the compensation tag from the job BeautifulSoup object
:param job
:return: Compensation object or None
"""
pay_element = job.find("li", {"class": "perk_item perk_pay"})
if pay_element is None:
return None
pay = pay_element.find("div", {"class": "value"}).find("span").text.strip()
def create_compensation_object(pay_string: str) -> Compensation:
"""
Creates a Compensation object from a pay_string
:param pay_string
:return: compensation
"""
interval = ZipRecruiterScraper.get_interval(pay_string.split()[-1])
amounts = []
for amount in pay_string.split("to"):
amount = amount.replace(",", "").strip("$ ").split(" ")[0]
if "K" in amount:
amount = amount.replace("K", "")
amount = int(float(amount)) * 1000
else:
amount = int(float(amount))
amounts.append(amount)
compensation = Compensation(
interval=interval,
min_amount=min(amounts),
max_amount=max(amounts),
currency="USD/CAD",
)
return compensation
return create_compensation_object(pay)
@staticmethod
def get_location(job: Tag) -> Location:
"""
Extracts the job location from BeatifulSoup object
:param job:
:return: location
"""
location_link = job.find("a", {"class": "company_location"})
if location_link is not None:
location_string = location_link.text.strip()
parts = location_string.split(", ")
if len(parts) == 2:
city, state = parts
else:
city, state = None, None
else:
city, state = None, None
return Location(city=city, state=state, country=Country.US_CANADA)
@staticmethod
def headers() -> dict:
"""
Returns headers needed for requests
Returns headers needed for ZipRecruiter API requests
:return: dict - Dictionary containing headers
"""
return {
'Host': 'api.ziprecruiter.com',
'Cookie': 'ziprecruiter_browser=018188e0-045b-4ad7-aa50-627a6c3d43aa; ziprecruiter_session=5259b2219bf95b6d2299a1417424bc2edc9f4b38; SplitSV=2016-10-19%3AU2FsdGVkX19f9%2Bx70knxc%2FeR3xXR8lWoTcYfq5QjmLU%3D%0A; __cf_bm=qXim3DtLPbOL83GIp.ddQEOFVFTc1OBGPckiHYxcz3o-1698521532-0-AfUOCkgCZyVbiW1ziUwyefCfzNrJJTTKPYnif1FZGQkT60dMowmSU/Y/lP+WiygkFPW/KbYJmyc+MQSkkad5YygYaARflaRj51abnD+SyF9V; zglobalid=68d49bd5-0326-428e-aba8-8a04b64bc67c.af2d99ff7c03.653d61bb; ziprecruiter_browser=018188e0-045b-4ad7-aa50-627a6c3d43aa; ziprecruiter_session=5259b2219bf95b6d2299a1417424bc2edc9f4b38',
'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'
'Cookie': '__cf_bm=DZ7eJOw6lka.Bwy5jLeDqWanaZ8BJlVAwaXrmcbYnxM-1701505132-0-AfGaVIfTA2kJlmleK14o722vbVwpZ+4UxFznsWv+guvzXSpD9KVEy/+pNzvEZUx88yaEShJwGt3/EVjhHirX/ASustKxg47V/aXRd2XIO2QN; zglobalid=61f94830-1990-4130-b222-d9d0e09c7825.57da9ea9581c.656ae86b; ziprecruiter_browser=018188e0-045b-4ad7-aa50-627a6c3d43aa; ziprecruiter_session=5259b2219bf95b6d2299a1417424bc2edc9f4b38; zva=100000000%3Bvid%3AZWroa0x_F1KEeGeU'
}

View File

@@ -4,7 +4,7 @@ import pandas as pd
def test_all():
result = scrape_jobs(
site_name=["linkedin", "indeed", "zip_recruiter"],
site_name=["linkedin", "indeed", "zip_recruiter", "glassdoor"],
search_term="software engineer",
results_wanted=5,
)

View File

@@ -0,0 +1,11 @@
from ..jobspy import scrape_jobs
import pandas as pd
def test_indeed():
result = scrape_jobs(
site_name="glassdoor", search_term="software engineer", country_indeed="USA"
)
assert (
isinstance(result, pd.DataFrame) and not result.empty
), "Result should be a non-empty DataFrame"

View File

@@ -4,8 +4,7 @@ import pandas as pd
def test_indeed():
result = scrape_jobs(
site_name="indeed",
search_term="software engineer",
site_name="indeed", search_term="software engineer", country_indeed="usa"
)
assert (
isinstance(result, pd.DataFrame) and not result.empty