mirror of https://github.com/Bunsly/JobSpy
Cullen Watson
GitHub
parent
1598d4ff63
commit
1c264b8c58
1469
JobSpy_Demo.ipynb
1469
JobSpy_Demo.ipynb
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91
README.md
91
README.md
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@ -23,7 +23,11 @@ import pandas as pd
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jobs: pd.DataFrame = scrape_jobs(
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site_name=["indeed", "linkedin", "zip_recruiter"],
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search_term="software engineer",
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results_wanted=10
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location="Dallas, TX",
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results_wanted=10,
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# country: only needed for indeed
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country='USA'
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)
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if jobs.empty:
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@ -65,8 +69,10 @@ Optional
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├── is_remote (bool)
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├── results_wanted (int): number of job results to retrieve for each site specified in 'site_type'
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├── easy_apply (bool): filters for jobs on LinkedIn that have the 'Easy Apply' option
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├── country (enum): uses the corresponding subdomain on Indeed (e.g. Canada on Indeed is ca.indeed.com
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```
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### JobPost Schema
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```plaintext
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JobPost
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@ -81,12 +87,91 @@ JobPost
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├── job_type (enum)
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├── compensation (object)
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│ ├── interval (CompensationInterval): yearly, monthly, weekly, daily, hourly
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│ ├── min_amount (float)
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│ ├── max_amount (float)
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│ ├── min_amount (int)
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│ ├── max_amount (int)
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│ └── currency (str)
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└── date_posted (datetime)
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```
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## Supported Countries for Job Searching
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### **LinkedIn**
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LinkedIn searches globally. Use the `location` parameter
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### **ZipRecruiter**
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ZipRecruiter searches for jobs in US/Canada. Use the `location` parameter
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### **Indeed**
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For Indeed, you `location` along with `country` param
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You can specify the following countries when searching on Indeed (use the exact name):
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- Argentina
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- Australia
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- Austria
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- Bahrain
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- Belgium
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- Brazil
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- Canada
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- Chile
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- China
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- Colombia
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- Costa Rica
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- Czech Republic
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- Denmark
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- Ecuador
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- Egypt
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- Finland
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- France
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- Germany
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- Greece
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- Hong Kong
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- Hungary
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- India
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- Indonesia
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- Ireland
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- Israel
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- Italy
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- Japan
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- Kuwait
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- Luxembourg
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- Malaysia
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- Mexico
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- Morocco
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- Netherlands
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- New Zealand
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- Nigeria
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- Norway
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- Oman
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- Pakistan
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- Panama
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- Peru
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- Philippines
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- Poland
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- Portugal
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- Qatar
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- Romania
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- Saudi Arabia
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- Singapore
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- South Africa
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- South Korea
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- Spain
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- Sweden
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- Switzerland
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- Taiwan
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- Thailand
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- Turkey
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- Ukraine
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- United Arab Emirates
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- UK
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- USA
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- Uruguay
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- Venezuela
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- Vietnam
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## Frequently Asked Questions
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@ -1,6 +1,6 @@
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[tool.poetry]
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name = "python-jobspy"
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version = "1.0.3"
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version = "1.1.0"
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description = "Job scraper for LinkedIn, Indeed & ZipRecruiter"
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authors = ["Zachary Hampton <zachary@zacharysproducts.com>", "Cullen Watson <cullen@cullen.ai>"]
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readme = "README.md"
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@ -1,15 +1,11 @@
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import pandas as pd
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from typing import List, Tuple
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from .jobs import JobType
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from .jobs import JobType, Location
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from .scrapers.indeed import IndeedScraper
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from .scrapers.ziprecruiter import ZipRecruiterScraper
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from .scrapers.linkedin import LinkedInScraper
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from .scrapers import (
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ScraperInput,
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Site,
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JobResponse,
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)
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from .scrapers import ScraperInput, Site, JobResponse, Country
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SCRAPER_MAPPING = {
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@ -32,6 +28,7 @@ def scrape_jobs(
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job_type: JobType = None,
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easy_apply: bool = False, # linkedin
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results_wanted: int = 15,
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country: str = "usa",
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) -> pd.DataFrame:
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"""
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Asynchronously scrapes job data from multiple job sites.
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@ -41,9 +38,12 @@ def scrape_jobs(
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if type(site_name) == str:
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site_name = _map_str_to_site(site_name)
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country_enum = Country.from_string(country)
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site_type = [site_name] if type(site_name) == Site else site_name
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scraper_input = ScraperInput(
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site_type=site_type,
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country=country_enum,
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search_term=search_term,
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location=location,
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distance=distance,
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@ -71,22 +71,15 @@ def scrape_jobs(
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for job in job_response.jobs:
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data = job.dict()
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data["site"] = site
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# Formatting JobType
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data["job_type"] = data["job_type"].value if data["job_type"] else None
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# Formatting Location
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location_obj = data.get("location")
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if location_obj and isinstance(location_obj, dict):
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data["city"] = location_obj.get("city", "")
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data["state"] = location_obj.get("state", "")
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data["country"] = location_obj.get("country", "USA")
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data["company"] = data["company_name"]
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if data["job_type"]:
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# Take the first value from the job type tuple
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data["job_type"] = data["job_type"].value[0]
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else:
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data["city"] = None
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data["state"] = None
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data["country"] = None
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data["job_type"] = None
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data["location"] = Location(**data["location"]).display_location()
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# Formatting Compensation
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compensation_obj = data.get("compensation")
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if compensation_obj and isinstance(compensation_obj, dict):
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data["interval"] = (
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@ -111,13 +104,13 @@ def scrape_jobs(
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desired_order = [
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"site",
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"title",
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"company_name",
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"city",
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"state",
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"company",
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"location",
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"job_type",
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"interval",
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"min_amount",
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"max_amount",
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"currency",
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"job_url",
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"description",
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]
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@ -6,24 +6,160 @@ from pydantic import BaseModel, validator
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class JobType(Enum):
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FULL_TIME = "fulltime"
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PART_TIME = "parttime"
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CONTRACT = "contract"
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TEMPORARY = "temporary"
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INTERNSHIP = "internship"
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FULL_TIME = (
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"fulltime",
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"períodointegral",
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"estágio/trainee",
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"cunormăîntreagă",
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"tiempocompleto",
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"vollzeit",
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"voltijds",
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"tempointegral",
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"全职",
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"plnýúvazek",
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"fuldtid",
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"دوامكامل",
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"kokopäivätyö",
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"tempsplein",
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"vollzeit",
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"πλήρηςαπασχόληση",
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"teljesmunkaidő",
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"tempopieno",
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"tempsplein",
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"heltid",
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"jornadacompleta",
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"pełnyetat",
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"정규직",
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"100%",
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"全職",
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"งานประจำ",
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"tamzamanlı",
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"повназайнятість",
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"toànthờigian",
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)
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PART_TIME = ("parttime", "teilzeit")
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CONTRACT = ("contract", "contractor")
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TEMPORARY = ("temporary",)
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INTERNSHIP = ("internship", "prácticas", "ojt(onthejobtraining)", "praktikum")
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PER_DIEM = "perdiem"
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NIGHTS = "nights"
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OTHER = "other"
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SUMMER = "summer"
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VOLUNTEER = "volunteer"
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PER_DIEM = ("perdiem",)
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NIGHTS = ("nights",)
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OTHER = ("other",)
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SUMMER = ("summer",)
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VOLUNTEER = ("volunteer",)
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class Country(Enum):
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ARGENTINA = ("argentina", "ar")
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AUSTRALIA = ("australia", "au")
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AUSTRIA = ("austria", "at")
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BAHRAIN = ("bahrain", "bh")
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BELGIUM = ("belgium", "be")
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BRAZIL = ("brazil", "br")
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CANADA = ("canada", "ca")
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CHILE = ("chile", "cl")
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CHINA = ("china", "cn")
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COLOMBIA = ("colombia", "co")
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COSTARICA = ("costa rica", "cr")
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CZECHREPUBLIC = ("czech republic", "cz")
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DENMARK = ("denmark", "dk")
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ECUADOR = ("ecuador", "ec")
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EGYPT = ("egypt", "eg")
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FINLAND = ("finland", "fi")
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FRANCE = ("france", "fr")
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GERMANY = ("germany", "de")
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GREECE = ("greece", "gr")
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HONGKONG = ("hong kong", "hk")
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HUNGARY = ("hungary", "hu")
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INDIA = ("india", "in")
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INDONESIA = ("indonesia", "id")
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IRELAND = ("ireland", "ie")
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ISRAEL = ("israel", "il")
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ITALY = ("italy", "it")
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JAPAN = ("japan", "jp")
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KUWAIT = ("kuwait", "kw")
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LUXEMBOURG = ("luxembourg", "lu")
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MALAYSIA = ("malaysia", "malaysia")
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MEXICO = ("mexico", "mx")
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MOROCCO = ("morocco", "ma")
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NETHERLANDS = ("netherlands", "nl")
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NEWZEALAND = ("new zealand", "nz")
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NIGERIA = ("nigeria", "ng")
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NORWAY = ("norway", "no")
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OMAN = ("oman", "om")
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PAKISTAN = ("pakistan", "pk")
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PANAMA = ("panama", "pa")
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PERU = ("peru", "pe")
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PHILIPPINES = ("philippines", "ph")
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POLAND = ("poland", "pl")
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PORTUGAL = ("portugal", "pt")
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QATAR = ("qatar", "qa")
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ROMANIA = ("romania", "ro")
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SAUDIARABIA = ("saudi arabia", "sa")
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SINGAPORE = ("singapore", "sg")
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SOUTHAFRICA = ("south africa", "za")
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SOUTHKOREA = ("south korea", "kr")
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SPAIN = ("spain", "es")
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SWEDEN = ("sweden", "se")
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SWITZERLAND = ("switzerland", "ch")
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TAIWAN = ("taiwan", "tw")
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THAILAND = ("thailand", "th")
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TURKEY = ("turkey", "tr")
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UKRAINE = ("ukraine", "ua")
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UNITEDARABEMIRATES = ("united arab emirates", "ae")
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UK = ("uk", "uk")
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USA = ("usa", "www")
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URUGUAY = ("uruguay", "uy")
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VENEZUELA = ("venezuela", "ve")
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VIETNAM = ("vietnam", "vn")
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# internal for ziprecruiter
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US_CANADA = ("usa/ca", "www")
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# internal for linkeind
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WORLDWIDE = ("worldwide", "www")
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def __new__(cls, country, domain):
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obj = object.__new__(cls)
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obj._value_ = country
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obj.domain = domain
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return obj
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@property
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def domain_value(self):
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return self.domain
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@classmethod
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def from_string(cls, country_str: str):
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"""Convert a string to the corresponding Country enum."""
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country_str = country_str.strip().lower()
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for country in cls:
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if country.value == country_str:
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return country
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valid_countries = [country.value for country in cls]
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raise ValueError(
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f"Invalid country string: '{country_str}'. Valid countries (only include this param for Indeed) are: {', '.join(valid_countries)}"
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)
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class Location(BaseModel):
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country: str = "USA"
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city: str = None
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country: Country = None
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city: Optional[str] = None
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state: Optional[str] = None
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def display_location(self) -> str:
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location_parts = []
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if self.city:
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location_parts.append(self.city)
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if self.state:
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location_parts.append(self.state)
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if self.country and self.country not in (Country.US_CANADA, Country.WORLDWIDE):
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if self.country.value in ("usa", "uk"):
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location_parts.append(self.country.value.upper())
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else:
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location_parts.append(self.country.value.title())
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return ", ".join(location_parts)
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class CompensationInterval(Enum):
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YEARLY = "yearly"
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@ -37,7 +173,7 @@ class Compensation(BaseModel):
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interval: CompensationInterval
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min_amount: int = None
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max_amount: int = None
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currency: str = "USD"
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currency: Optional[str] = "USD"
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class JobPost(BaseModel):
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|
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@ -1,4 +1,4 @@
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from ..jobs import Enum, BaseModel, JobType, JobResponse
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from ..jobs import Enum, BaseModel, JobType, JobResponse, Country
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from typing import List, Optional, Any
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@ -18,6 +18,7 @@ class ScraperInput(BaseModel):
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search_term: str
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location: str = None
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country: Optional[Country] = Country.USA
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distance: Optional[int] = None
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is_remote: bool = False
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job_type: Optional[JobType] = None
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@ -35,9 +36,8 @@ class CommonResponse(BaseModel):
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class Scraper:
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def __init__(self, site: Site, url: str):
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def __init__(self, site: Site):
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self.site = site
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self.url = url
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def scrape(self, scraper_input: ScraperInput) -> JobResponse:
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...
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@ -1,6 +1,8 @@
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import re
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import math
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import io
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import json
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import traceback
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from datetime import datetime
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from typing import Optional
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@ -18,7 +20,7 @@ from ...jobs import (
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JobResponse,
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JobType,
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)
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from .. import Scraper, ScraperInput, Site, StatusException
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from .. import Scraper, ScraperInput, Site, Country, StatusException
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class ParsingException(Exception):
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@ -31,8 +33,7 @@ class IndeedScraper(Scraper):
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Initializes IndeedScraper with the Indeed job search url
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"""
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site = Site(Site.INDEED)
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url = "https://www.indeed.com"
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super().__init__(site, url)
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super().__init__(site)
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self.jobs_per_page = 15
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self.seen_urls = set()
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@ -47,16 +48,21 @@ class IndeedScraper(Scraper):
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:param session:
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:return: jobs found on page, total number of jobs found for search
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"""
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self.country = scraper_input.country
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domain = self.country.domain_value
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self.url = f"https://{domain}.indeed.com"
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job_list = []
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params = {
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"q": scraper_input.search_term,
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"l": scraper_input.location,
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"radius": scraper_input.distance,
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"filter": 0,
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"start": 0 + page * 10,
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}
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if scraper_input.distance:
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params["radius"] = scraper_input.distance
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sc_values = []
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if scraper_input.is_remote:
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sc_values.append("attr(DSQF7)")
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@ -65,12 +71,15 @@ class IndeedScraper(Scraper):
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if sc_values:
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params["sc"] = "0kf:" + "".join(sc_values) + ";"
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response = session.get(self.url + "/jobs", params=params)
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response = session.get(self.url + "/jobs", params=params, allow_redirects=True)
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# print(response.status_code)
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if response.status_code != 200 and response.status_code != 307:
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if response.status_code not in range(200, 400):
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raise StatusException(response.status_code)
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soup = BeautifulSoup(response.content, "html.parser")
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with open("text2.html", "w", encoding="utf-8") as f:
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f.write(str(soup))
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if "did not match any jobs" in str(soup):
|
||||
raise ParsingException("Search did not match any jobs")
|
||||
|
||||
|
|
@ -92,8 +101,6 @@ class IndeedScraper(Scraper):
|
|||
if job_url in self.seen_urls:
|
||||
return None
|
||||
|
||||
snippet_html = BeautifulSoup(job["snippet"], "html.parser")
|
||||
|
||||
extracted_salary = job.get("extractedSalary")
|
||||
compensation = None
|
||||
if extracted_salary:
|
||||
|
|
@ -118,11 +125,12 @@ class IndeedScraper(Scraper):
|
|||
date_posted = date_posted.strftime("%Y-%m-%d")
|
||||
|
||||
description = self.get_description(job_url, session)
|
||||
li_elements = snippet_html.find_all("li")
|
||||
if description is None and li_elements:
|
||||
description = " ".join(li.text for li in li_elements)
|
||||
with io.StringIO(job["snippet"]) as f:
|
||||
soup = BeautifulSoup(f, "html.parser")
|
||||
li_elements = soup.find_all("li")
|
||||
if description is None and li_elements:
|
||||
description = " ".join(li.text for li in li_elements)
|
||||
|
||||
first_li = snippet_html.find("li")
|
||||
job_post = JobPost(
|
||||
title=job["normTitle"],
|
||||
description=description,
|
||||
|
|
@ -130,6 +138,7 @@ class IndeedScraper(Scraper):
|
|||
location=Location(
|
||||
city=job.get("jobLocationCity"),
|
||||
state=job.get("jobLocationState"),
|
||||
country=self.country,
|
||||
),
|
||||
job_type=job_type,
|
||||
compensation=compensation,
|
||||
|
|
@ -138,7 +147,7 @@ class IndeedScraper(Scraper):
|
|||
)
|
||||
return job_post
|
||||
|
||||
with ThreadPoolExecutor(max_workers=10) as executor:
|
||||
with ThreadPoolExecutor(max_workers=1) as executor:
|
||||
job_results: list[Future] = [
|
||||
executor.submit(process_job, job)
|
||||
for job in jobs["metaData"]["mosaicProviderJobCardsModel"]["results"]
|
||||
|
|
@ -166,7 +175,7 @@ class IndeedScraper(Scraper):
|
|||
#: get first page to initialize session
|
||||
job_list, total_results = self.scrape_page(scraper_input, 0, session)
|
||||
|
||||
with ThreadPoolExecutor(max_workers=10) as executor:
|
||||
with ThreadPoolExecutor(max_workers=1) as executor:
|
||||
futures: list[Future] = [
|
||||
executor.submit(self.scrape_page, scraper_input, page, session)
|
||||
for page in range(1, pages_to_process + 1)
|
||||
|
|
@ -188,6 +197,7 @@ class IndeedScraper(Scraper):
|
|||
error=f"Indeed failed to parse response: {e}",
|
||||
)
|
||||
except Exception as e:
|
||||
print(f"LinkedIn failed to scrape: {e}\n{traceback.format_exc()}")
|
||||
return JobResponse(
|
||||
success=False,
|
||||
error=f"Indeed failed to scrape: {e}",
|
||||
|
|
@ -215,17 +225,25 @@ class IndeedScraper(Scraper):
|
|||
jk_value = params.get("jk", [None])[0]
|
||||
formatted_url = f"{self.url}/viewjob?jk={jk_value}&spa=1"
|
||||
|
||||
response = session.get(formatted_url, allow_redirects=True)
|
||||
try:
|
||||
response = session.get(
|
||||
formatted_url, allow_redirects=True, timeout_seconds=5
|
||||
)
|
||||
except requests.exceptions.Timeout:
|
||||
print("The request timed out.")
|
||||
return None
|
||||
|
||||
if response.status_code not in range(200, 400):
|
||||
print("status code not in range")
|
||||
return None
|
||||
|
||||
raw_description = response.json()["body"]["jobInfoWrapperModel"][
|
||||
"jobInfoModel"
|
||||
]["sanitizedJobDescription"]
|
||||
soup = BeautifulSoup(raw_description, "html.parser")
|
||||
text_content = " ".join(soup.get_text().split()).strip()
|
||||
return text_content
|
||||
with io.StringIO(raw_description) as f:
|
||||
soup = BeautifulSoup(f, "html.parser")
|
||||
text_content = " ".join(soup.get_text().split()).strip()
|
||||
return text_content
|
||||
|
||||
@staticmethod
|
||||
def get_job_type(job: dict) -> Optional[JobType]:
|
||||
|
|
@ -237,13 +255,18 @@ class IndeedScraper(Scraper):
|
|||
for taxonomy in job["taxonomyAttributes"]:
|
||||
if taxonomy["label"] == "job-types":
|
||||
if len(taxonomy["attributes"]) > 0:
|
||||
job_type_str = (
|
||||
taxonomy["attributes"][0]["label"]
|
||||
.replace("-", "_")
|
||||
.replace(" ", "_")
|
||||
.upper()
|
||||
)
|
||||
return JobType[job_type_str]
|
||||
label = taxonomy["attributes"][0].get("label")
|
||||
if label:
|
||||
job_type_str = label.replace("-", "").replace(" ", "").lower()
|
||||
# print(f"Debug: job_type_str = {job_type_str}")
|
||||
return IndeedScraper.get_enum_from_value(job_type_str)
|
||||
return None
|
||||
|
||||
@staticmethod
|
||||
def get_enum_from_value(value_str):
|
||||
for job_type in JobType:
|
||||
if value_str in job_type.value:
|
||||
return job_type
|
||||
return None
|
||||
|
||||
@staticmethod
|
||||
|
|
@ -294,7 +317,7 @@ class IndeedScraper(Scraper):
|
|||
:param soup:
|
||||
:return: total_num_jobs
|
||||
"""
|
||||
script = soup.find("script", string=lambda t: "window._initialData" in t)
|
||||
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)
|
||||
|
|
|
|||
|
|
@ -22,8 +22,8 @@ class LinkedInScraper(Scraper):
|
|||
Initializes LinkedInScraper with the LinkedIn job search url
|
||||
"""
|
||||
site = Site(Site.LINKEDIN)
|
||||
url = "https://www.linkedin.com"
|
||||
super().__init__(site, url)
|
||||
self.url = "https://www.linkedin.com"
|
||||
super().__init__(site)
|
||||
|
||||
def scrape(self, scraper_input: ScraperInput) -> JobResponse:
|
||||
"""
|
||||
|
|
@ -31,6 +31,7 @@ class LinkedInScraper(Scraper):
|
|||
:param scraper_input:
|
||||
:return: job_response
|
||||
"""
|
||||
self.country = "worldwide"
|
||||
job_list: list[JobPost] = []
|
||||
seen_urls = set()
|
||||
page, processed_jobs, job_count = 0, 0, 0
|
||||
|
|
@ -104,7 +105,7 @@ class LinkedInScraper(Scraper):
|
|||
metadata_card = job_info.find(
|
||||
"div", class_="base-search-card__metadata"
|
||||
)
|
||||
location: Location = LinkedInScraper.get_location(metadata_card)
|
||||
location: Location = self.get_location(metadata_card)
|
||||
|
||||
datetime_tag = metadata_card.find(
|
||||
"time", class_="job-search-card__listdate"
|
||||
|
|
@ -125,7 +126,7 @@ class LinkedInScraper(Scraper):
|
|||
job_url=job_url,
|
||||
job_type=job_type,
|
||||
compensation=Compensation(
|
||||
interval=CompensationInterval.YEARLY, currency="USD"
|
||||
interval=CompensationInterval.YEARLY, currency=None
|
||||
),
|
||||
)
|
||||
job_list.append(job_post)
|
||||
|
|
@ -195,17 +196,24 @@ class LinkedInScraper(Scraper):
|
|||
employment_type = employment_type.lower()
|
||||
employment_type = employment_type.replace("-", "")
|
||||
|
||||
return JobType(employment_type)
|
||||
return LinkedInScraper.get_enum_from_value(employment_type)
|
||||
|
||||
return text_content, get_job_type(soup)
|
||||
|
||||
@staticmethod
|
||||
def get_location(metadata_card: Optional[Tag]) -> Location:
|
||||
def get_enum_from_value(value_str):
|
||||
for job_type in JobType:
|
||||
if value_str in job_type.value:
|
||||
return job_type
|
||||
return None
|
||||
|
||||
def get_location(self, metadata_card: Optional[Tag]) -> Location:
|
||||
"""
|
||||
Extracts the location data from the job metadata card.
|
||||
:param metadata_card
|
||||
:return: location
|
||||
"""
|
||||
location = Location(country=self.country)
|
||||
if metadata_card is not None:
|
||||
location_tag = metadata_card.find(
|
||||
"span", class_="job-search-card__location"
|
||||
|
|
@ -217,6 +225,7 @@ class LinkedInScraper(Scraper):
|
|||
location = Location(
|
||||
city=city,
|
||||
state=state,
|
||||
country=self.country,
|
||||
)
|
||||
|
||||
return location
|
||||
|
|
|
|||
|
|
@ -1,6 +1,7 @@
|
|||
import math
|
||||
import json
|
||||
import re
|
||||
import traceback
|
||||
from datetime import datetime
|
||||
from typing import Optional, Tuple
|
||||
from urllib.parse import urlparse, parse_qs
|
||||
|
|
@ -18,6 +19,7 @@ from ...jobs import (
|
|||
Location,
|
||||
JobResponse,
|
||||
JobType,
|
||||
Country,
|
||||
)
|
||||
|
||||
|
||||
|
|
@ -27,8 +29,8 @@ class ZipRecruiterScraper(Scraper):
|
|||
Initializes LinkedInScraper with the ZipRecruiter job search url
|
||||
"""
|
||||
site = Site(Site.ZIP_RECRUITER)
|
||||
url = "https://www.ziprecruiter.com"
|
||||
super().__init__(site, url)
|
||||
self.url = "https://www.ziprecruiter.com"
|
||||
super().__init__(site)
|
||||
|
||||
self.jobs_per_page = 20
|
||||
self.seen_urls = set()
|
||||
|
|
@ -80,8 +82,10 @@ class ZipRecruiterScraper(Scraper):
|
|||
self.url + "/jobs-search",
|
||||
headers=ZipRecruiterScraper.headers(),
|
||||
params=params,
|
||||
allow_redirects=True,
|
||||
)
|
||||
|
||||
# print(response.status_code)
|
||||
if response.status_code != 200:
|
||||
raise StatusException(response.status_code)
|
||||
|
||||
|
|
@ -144,6 +148,7 @@ class ZipRecruiterScraper(Scraper):
|
|||
error=f"ZipRecruiter returned status code {e.status_code}",
|
||||
)
|
||||
except Exception as e:
|
||||
print(f"ZipRecruiter failed to scrape: {e}\n{traceback.format_exc()}")
|
||||
return JobResponse(
|
||||
success=False,
|
||||
error=f"ZipRecruiter failed to scrape: {e}",
|
||||
|
|
@ -181,15 +186,12 @@ class ZipRecruiterScraper(Scraper):
|
|||
description = job.find("p", {"class": "job_snippet"}).text.strip()
|
||||
|
||||
job_type_element = job.find("li", {"class": "perk_item perk_type"})
|
||||
job_type = None
|
||||
if job_type_element:
|
||||
job_type_text = (
|
||||
job_type_element.text.strip().lower().replace("-", "").replace(" ", "")
|
||||
)
|
||||
if job_type_text == "contractor":
|
||||
job_type_text = "contract"
|
||||
job_type = JobType(job_type_text)
|
||||
else:
|
||||
job_type = None
|
||||
job_type = ZipRecruiterScraper.get_job_type_enum(job_type_text)
|
||||
|
||||
date_posted = ZipRecruiterScraper.get_date_posted(job)
|
||||
|
||||
|
|
@ -206,16 +208,17 @@ class ZipRecruiterScraper(Scraper):
|
|||
return job_post
|
||||
|
||||
def process_job_js(self, job: dict) -> JobPost:
|
||||
# Map the job data to the expected fields by the Pydantic model
|
||||
title = job.get("Title")
|
||||
description = BeautifulSoup(
|
||||
job.get("Snippet", "").strip(), "html.parser"
|
||||
).get_text()
|
||||
|
||||
company = job.get("OrgName")
|
||||
location = Location(city=job.get("City"), state=job.get("State"))
|
||||
location = Location(
|
||||
city=job.get("City"), state=job.get("State"), country=Country.US_CANADA
|
||||
)
|
||||
try:
|
||||
job_type = ZipRecruiterScraper.job_type_from_string(
|
||||
job_type = ZipRecruiterScraper.get_job_type_enum(
|
||||
job.get("EmploymentType", "").replace("-", "_").lower()
|
||||
)
|
||||
except ValueError:
|
||||
|
|
@ -244,6 +247,7 @@ class ZipRecruiterScraper(Scraper):
|
|||
interval=CompensationInterval.YEARLY,
|
||||
min_amount=min_amount,
|
||||
max_amount=max_amount,
|
||||
currency="USD/CAD",
|
||||
)
|
||||
save_job_url = job.get("SaveJobURL", "")
|
||||
posted_time_match = re.search(
|
||||
|
|
@ -270,17 +274,18 @@ class ZipRecruiterScraper(Scraper):
|
|||
return job_post
|
||||
|
||||
@staticmethod
|
||||
def job_type_from_string(value: str) -> Optional[JobType]:
|
||||
if not value:
|
||||
return None
|
||||
def get_enum_from_value(value_str):
|
||||
for job_type in JobType:
|
||||
if value_str in job_type.value:
|
||||
return job_type
|
||||
return None
|
||||
|
||||
if value.lower() == "contractor":
|
||||
value = "contract"
|
||||
normalized_value = value.replace("_", "")
|
||||
for item in JobType:
|
||||
if item.value == normalized_value:
|
||||
return item
|
||||
raise ValueError(f"Invalid value for JobType: {value}")
|
||||
@staticmethod
|
||||
def get_job_type_enum(job_type_str: str) -> Optional[JobType]:
|
||||
for job_type in JobType:
|
||||
if job_type_str in job_type.value:
|
||||
return job_type
|
||||
return None
|
||||
|
||||
def get_description(self, job_page_url: str) -> Tuple[Optional[str], Optional[str]]:
|
||||
"""
|
||||
|
|
@ -289,11 +294,16 @@ class ZipRecruiterScraper(Scraper):
|
|||
:param session:
|
||||
:return: description or None, response url
|
||||
"""
|
||||
response = self.session.get(
|
||||
job_page_url, headers=ZipRecruiterScraper.headers(), allow_redirects=True
|
||||
)
|
||||
if response.status_code not in range(200, 400):
|
||||
return None, None
|
||||
try:
|
||||
response = self.session.get(
|
||||
job_page_url,
|
||||
headers=ZipRecruiterScraper.headers(),
|
||||
allow_redirects=True,
|
||||
timeout_seconds=5,
|
||||
)
|
||||
except requests.exceptions.Timeout:
|
||||
print("The request timed out.")
|
||||
return None
|
||||
|
||||
html_string = response.content
|
||||
soup_job = BeautifulSoup(html_string, "html.parser")
|
||||
|
|
@ -375,7 +385,10 @@ class ZipRecruiterScraper(Scraper):
|
|||
amounts.append(amount)
|
||||
|
||||
compensation = Compensation(
|
||||
interval=interval, min_amount=min(amounts), max_amount=max(amounts)
|
||||
interval=interval,
|
||||
min_amount=min(amounts),
|
||||
max_amount=max(amounts),
|
||||
currency="USD/CAD",
|
||||
)
|
||||
|
||||
return compensation
|
||||
|
|
@ -399,10 +412,7 @@ class ZipRecruiterScraper(Scraper):
|
|||
city, state = None, None
|
||||
else:
|
||||
city, state = None, None
|
||||
return Location(
|
||||
city=city,
|
||||
state=state,
|
||||
)
|
||||
return Location(city=city, state=state, country=Country.US_CANADA)
|
||||
|
||||
@staticmethod
|
||||
def headers() -> dict:
|
||||
|
|
|
|||
Loading…
Reference in New Issue