BambooHR Jobs API.

import requests

def validate_company(subdomain: str) -> dict | None:
    """Validate a BambooHR company subdomain exists."""
    url = f"https://{subdomain}.bamboohr.com/careers/company-info"
    try:
        response = requests.get(url, timeout=10)
        response.raise_for_status()
        data = response.json()
        return data.get("result")
    except requests.RequestException:
        return None

# Example usage
company = validate_company("cortina")
if company:
    print(f"Company: {company['name']}")
else:
    print("Invalid company subdomain")

import requests

def fetch_job_listings(subdomain: str) -> list[dict]:
    """Fetch all job listings from a BambooHR company."""
    url = f"https://{subdomain}.bamboohr.com/careers/list"
    response = requests.get(url, timeout=10)
    response.raise_for_status()
    data = response.json()

    jobs = data.get("result", [])
    total_count = data.get("meta", {}).get("totalCount", 0)
    print(f"Found {total_count} jobs for {subdomain}")
    return jobs

# Example usage
jobs = fetch_job_listings("cortina")
for job in jobs[:3]:
    print(f"- {job['jobOpeningName']} ({job['departmentLabel']})")

def map_workplace_type(location_type: str | None) -> str:
    """Map BambooHR location type codes to readable values."""
    workplace_map = {
        "0": "On-site",
        "1": "Remote",
        "2": "Hybrid",
    }
    return workplace_map.get(location_type, "Not Specified")

# Parse job listings with workplace type
for job in jobs:
    workplace = map_workplace_type(job.get("locationType"))
    location = job.get("atsLocation", {})
    print(f"{job['jobOpeningName']}: {workplace} - {location.get('city', 'N/A')}, {location.get('state', 'N/A')}")

import requests
import time

def fetch_job_details(subdomain: str, job_id: str) -> dict:
    """Fetch detailed information for a specific job."""
    url = f"https://{subdomain}.bamboohr.com/careers/{job_id}/detail"
    response = requests.get(url, timeout=10)
    response.raise_for_status()
    data = response.json()
    return data.get("result", {}).get("jobOpening", {})

# Fetch details for all jobs (with rate limiting)
for job in jobs[:5]:  # Limit to first 5 for example
    details = fetch_job_details("cortina", job["id"])
    print({
        "title": details.get("jobOpeningName"),
        "posted": details.get("datePosted"),
        "experience": details.get("minimumExperience"),
        "compensation": details.get("compensation"),
    })
    time.sleep(1)  # Be respectful with rate limiting

import requests
import time

def scrape_bamboohr_jobs(subdomain: str) -> list[dict]:
    """Complete BambooHR job scraper with error handling."""
    base_url = f"https://{subdomain}.bamboohr.com"

    # Validate company exists
    try:
        info_resp = requests.get(f"{base_url}/careers/company-info", timeout=10)
        info_resp.raise_for_status()
        company_name = info_resp.json().get("result", {}).get("name", subdomain)
    except requests.RequestException:
        print(f"Company '{subdomain}' not found or invalid")
        return []

    # Fetch job listings
    try:
        list_resp = requests.get(f"{base_url}/careers/list", timeout=10)
        list_resp.raise_for_status()
        listings = list_resp.json().get("result", [])
    except requests.RequestException as e:
        print(f"Error fetching listings: {e}")
        return []

    # Fetch details for each job
    results = []
    for job in listings:
        try:
            detail_url = f"{base_url}/careers/{job['id']}/detail"
            detail_resp = requests.get(detail_url, timeout=10)
            detail_resp.raise_for_status()
            details = detail_resp.json().get("result", {}).get("jobOpening", {})

            results.append({
                "external_id": f"{subdomain}:{job['id']}",
                "title": job["jobOpeningName"],
                "company": company_name,
                "department": job.get("departmentLabel"),
                "location": job.get("atsLocation", {}),
                "workplace_type": map_workplace_type(job.get("locationType")),
                "employment_type": job.get("employmentStatusLabel"),
                "description": details.get("description"),
                "posted_date": details.get("datePosted"),
                "experience": details.get("minimumExperience"),
                "compensation": details.get("compensation"),
                "url": details.get("jobOpeningShareUrl"),
            })
            time.sleep(0.5)  # Rate limiting
        except requests.RequestException as e:
            print(f"Error fetching job {job['id']}: {e}")

    return results

# Run the scraper
jobs = scrape_bamboohr_jobs("cortina")
print(f"Scraped {len(jobs)} complete job listings")