- Sync and async clients (
hirebase.Client/hirebase.AsyncClient). - Typed by default — responses come back as Pydantic models; pass
return_type=dictanywhere for raw dicts. - Streaming exports — kick off an export, poll it, download it, and stream millions of jobs without loading them into memory.
- Self-contained — the SDK ships its own types and depends only on
requests,httpx, andpydantic.
Guides: Getting started · Jobs · Companies · Resumes · Tasks · Errors · Examples
pip install hirebase
# Optional extras
pip install "hirebase[streaming]" # ijson, for streaming JSON-array exports
pip install "hirebase[cli]" # the bundled `hirebase` command-line toolPass your API key directly, or set it via the environment:
import hirebase
client = hirebase.Client(api_key="sk_live_...")export HIREBASE_API_KEY="sk_live_..."
export HIREBASE_BASE_URL="https://api.hirebase.org" # optional, this is the defaultResolution order for every setting is argument → environment variable →
default. The base URL defaults to https://api.hirebase.org.
import hirebase
client = hirebase.Client(api_key="sk_live_...")
# Search jobs — results are typed and iterable
result = client.jobs.search({
"job_titles": ["Software Engineer", "Product Engineer"],
"locations": [{"city": "San Francisco", "region": "California",
"country": "United States"}],
"limit": 20,
})
print(result.total_count, "matches")
for job in result:
print(job.job_title, "@", job.company_name, "—", job.salary_range)Booleans are accepted natively (visa=True), and locations is a friendly
alias for the API's geo_locations. Unknown filter keys are passed through
untouched, so new API features work before the SDK is updated.
import asyncio, hirebase
async def main():
async with hirebase.AsyncClient(api_key="sk_live_...") as client:
result = await client.jobs.search({"job_titles": ["Engineer"]})
for job in result:
print(job.job_title)
asyncio.run(main())Every method has the same signature on both clients — the async versions are awaitable.
# Search
result = client.jobs.search(query, page=1, limit=20)
# Fetch one job
job = client.jobs.get("6958cfd211e2763c3491ef8b")
# Market insights for a cohort (same filter shape as search)
insights = client.jobs.insights({"job_titles": ["Data Scientist"]})
print(insights.headline.median_salary, insights.salary.p90)You can pass a plain dict or build a typed query:
from hirebase import JobQuery, SalaryRange
query = JobQuery(
job_titles=["Backend Engineer"],
salary=SalaryRange(min=150_000, currency="USD"),
location_types=["Remote"],
visa=True,
)
result = client.jobs.search(query)Exports are processed server-side and returned as a downloadable file.
query = {
"job_titles": ["Software Engineer", "Product Engineer", "Fullstack Engineer"],
"locations": [{"city": "San Francisco", "region": "California",
"country": "United States"}],
}
# 1. Start the export -> returns a Task
task = client.jobs.export(query, format="json") # or format="csv"
# 2. Poll until it finishes -> (success, result)
success, result = client.tasks.poll(task)
if not success:
raise RuntimeError(f"Export failed: {result.error}")
# 3. Download the file (streamed to disk)
client.stream_file(result["download_url"], file_path="./jobs.json")
# 4. Stream jobs from the file (typed by default; uses constant memory)
for job in client.jobs.stream_file("./jobs.json"):
print(job.job_title)
# ...or get raw dicts
for row in client.jobs.stream_file("./jobs.json", return_type=dict):
...poll() accepts a Task, a task dict, or a task id, plus interval,
timeout, and an on_progress callback. The result dict contains
download_url, file_size, record_count, and expiry_time.
You can also stream directly from the export URL without saving to disk (JSON Lines exports only):
for job in client.jobs.stream_url(result["download_url"]):
print(job.job_title)Requires the hiring_manager_api feature on your key (email spencer@hirebase.org).
Research returns name, role and LinkedIn profile per contact; email and phone are
optional reveals billed only when found.
task = client.jobs.contacts("6ab32db8f1c329e432f72994") # LinkedIn only
task = client.tasks.poll(task.id, timeout=600)
for c in task.result["contacts"]:
print(c["name"], c["role"], c["profile_url"])
# Reveal one contact you picked (work email by default, phone on request)
reveal = client.jobs.reveal_contact(c["profile_url"], name=c["name"], reveal_phone=True)
reveal = client.tasks.poll(reveal.id, timeout=300)
print(reveal.result["email"], reveal.result["phone_number"])
# Or reveal every contact of a posting up front
task = client.jobs.contacts("6ab32db8f1c329e432f72994", reveal_email=True, reveal_phone=True)# Search
companies = client.companies.search({"company_name": "Stripe"})
for company in companies:
print(company.company_name, company.company_slug)
# Get a company by slug — optionally with its jobs and live insights
company = client.companies.get("stripe", return_jobs=True, return_insights=True)
print(company.description_summary)
print(company.insights_data.headline.total_count)
# Bound helpers (the object remembers its client)
insights = company.insights()
jobs = company.get_jobs(limit=10)
# Company-scoped insights directly
insights = client.companies.insights("stripe", query={"days_ago": 30})Every method returns typed models by default. Pass return_type=dict to get
the raw API payload instead:
data = client.jobs.search(query, return_type=dict) # -> dict
job = client.jobs.get(job_id, return_type=dict) # -> dictAll errors subclass hirebase.HirebaseError:
| Exception | Meaning |
|---|---|
ConfigurationError |
No API key / bad config |
AuthenticationError |
401 — invalid API key |
PaymentRequiredError |
402 — plan/credits required |
PermissionError_ |
403 — not allowed |
NotFoundError |
404 |
RateLimitError |
429 from the request limiter (100 requests / 60 s per key); check err.retry_after |
QuotaExceededError |
429 with X-Billing-Code: limit_exceeded: the plan's included allowance is used up. Subclass of RateLimitError; err.usage holds the quota snapshot |
ServerError |
5xx |
APIError |
any other non-2xx (.status_code, .message, .body) |
TaskFailed / TaskTimeout |
export task failed or timed out |
import hirebase
try:
client.jobs.search(query)
except hirebase.RateLimitError:
...
except hirebase.APIError as e:
print(e.status_code, e.message)Every metered response carries Hirebase-Usage-* headers. Pass
return_meta=True to any metered method (jobs and companies, sync or async)
to get them back with the result as a ResponseMeta:
jobs, meta = client.jobs.search({"job_titles": ["Software Engineer"]}, limit=50, return_meta=True)
usage = meta.usage # None on un-metered endpoints
print(usage.meter, usage.total_used, "/", usage.included_limit, "remaining:", usage.included_remaining)
if usage.is_meter_mode and usage.overage_used:
print("billing overage units:", usage.overage_used)
print(meta.status_code, meta.request_id) # transport details for the same callWithout the flag the return shape is unchanged, so existing code keeps working.
When a block-mode plan is at its cap the API refuses the call with a 429 that is not a rate limit, so backing off will not help:
try:
client.jobs.search(query, limit=100)
except hirebase.QuotaExceededError as err:
remaining = err.usage.included_remaining # e.g. 2 -> retry with limit=2
except hirebase.RateLimitError as err:
time.sleep(err.retry_after or 5) # the 100 req / 60 s limiterpip install -e ".[dev]"
# Offline unit tests (no network)
pytest
# Live integration tests against the real API
HIREBASE_API_KEY=sk_live_... pytest tests/test_integration.py -vIf your environment preloads conflicting pytest plugins, run with
PYTEST_DISABLE_PLUGIN_AUTOLOAD=1 pytest.
MIT — see LICENSE.