Spooled Python SDK
Official Python SDK for Spooled Cloud — a modern, scalable job queue and task scheduler.
Live Demo (SpriteForge) • Documentation
Features
- Full API Coverage — Access all Spooled API endpoints
- Type Safety — Full type hints and Pydantic models
- Sync & Async — Both synchronous and asynchronous clients
- Worker Runtime — Process jobs with a decorator-based API
- Real-time Events — WebSocket and SSE support
- gRPC Support — High-performance gRPC client (optional)
- Resilience — Retry logic with exponential backoff and circuit breaker
- Production Ready — Comprehensive error handling and logging
Installation
pip install spooled
Optional Extras
# For real-time events (WebSocket/SSE)
pip install spooled[realtime]
# For gRPC support
pip install spooled[grpc]
# All features
pip install spooled[all]
Quick Start
Create a Job
from spooled import SpooledClient
client = SpooledClient(api_key="sp_live_...")
# Create a job
result = client.jobs.create({
"queue_name": "emails",
"payload": {
"to": "user@example.com",
"subject": "Welcome!",
"template": "welcome_email",
},
"priority": 5,
})
print(f"Job created: {result.id}")
# Get job details
job = client.jobs.get(result.id)
print(f"Status: {job.status}")
client.close()
Process Jobs with a Worker
from spooled import SpooledClient
from spooled.worker import SpooledWorker
client = SpooledClient(api_key="sp_live_...")
worker = SpooledWorker(client, queue_name="emails", concurrency=10)
@worker.process
def handle_job(ctx):
"""Process an email job."""
print(f"Processing job {ctx.job_id}")
# Access payload
to = ctx.payload["to"]
subject = ctx.payload["subject"]
# Send the email (your logic here)
send_email(to, subject)
# Return result
return {"sent": True}
@worker.on("job:completed")
def on_completed(event):
print(f"Job {event.job_id} completed!")
worker.start() # Blocking
Real-world examples (beginner friendly)
If you want 5 copy/paste “real life” setups (Stripe → jobs, GitHub Actions → jobs, cron schedules, CSV import, website signup), see:
https://github.com/spooled-cloud/spooled-backend/blob/main/docs/guides/real-world-examples.md
Async Client
import asyncio
from spooled import AsyncSpooledClient
async def main():
async with AsyncSpooledClient(api_key="sp_live_...") as client:
# Create multiple jobs concurrently
tasks = [
client.jobs.create({"queue_name": "tasks", "payload": {"n": i}})
for i in range(10)
]
results = await asyncio.gather(*tasks)
print(f"Created {len(results)} jobs")
asyncio.run(main())
Workflows (Job Dependencies)
from spooled import SpooledClient
client = SpooledClient(api_key="sp_live_...")
# Create a workflow with dependencies
workflow = client.workflows.create({
"name": "Order Processing",
"jobs": [
{
"key": "validate",
"queue_name": "orders",
"payload": {"action": "validate"},
},
{
"key": "charge",
"queue_name": "payments",
"payload": {"action": "charge"},
"depends_on": ["validate"],
},
{
"key": "ship",
"queue_name": "fulfillment",
"payload": {"action": "ship"},
"depends_on": ["charge"],
},
],
})
print(f"Workflow created: {workflow.workflow_id}")
Schedules (Cron Jobs)
from spooled import SpooledClient
client = SpooledClient(api_key="sp_live_...")
# Create a scheduled job
schedule = client.schedules.create({
"name": "Daily Report",
"cron_expression": "0 9 * * *", # 9 AM daily
"timezone": "America/New_York",
"queue_name": "reports",
"payload_template": {"report_type": "daily"},
})
print(f"Schedule created: {schedule.id}")
print(f"Next run: {schedule.next_run_at}")
gRPC Support (High Performance)
The SDK includes a high-performance gRPC client for high-throughput worker scenarios.
from spooled.grpc import SpooledGrpcClient
# Connect to Spooled Cloud gRPC (TLS required for Cloudflare Tunnel)
client = SpooledGrpcClient(
address="grpc.spooled.cloud:443",
api_key="sp_live_...",
use_tls=True # Required for production (Cloudflare Tunnel needs HTTPS for HTTP/2)
)
# Enqueue a job
response = client.queue.enqueue(
queue_name="high-throughput",
payload={"data": "value"}
)
print(f"Job enqueued: {response.job_id}")
# Get queue stats
stats = client.queue.get_queue_stats("high-throughput")
print(f"Pending jobs: {stats.pending}")
client.close()
When to use gRPC?
- High Throughput: Persistent HTTP/2 and Protobuf can reduce overhead; benchmark your workload and network path.
- Streaming: Supports real-time job streaming.
- Efficiency: Uses persistent HTTP/2 connections with keepalives.
Real-time Events (SSE/WebSocket)
Listen for real-time updates:
from spooled import SpooledClient
from spooled.realtime.unified import SubscriptionFilter
client = SpooledClient(api_key="sp_live_...")
# Subscribe to job updates for a queue, then iterate events
realtime = client.realtime(type="websocket")
realtime.connect()
realtime.subscribe(SubscriptionFilter(queue="my-queue"))
for event in realtime.events():
print(f"Event: {event.type} - {event.data}")
Configuration
from spooled import SpooledClient, SpooledClientConfig, RetryConfig
# Full configuration
config = SpooledClientConfig(
api_key="sp_live_...",
base_url="https://api.spooled.cloud",
timeout=30.0,
retry=RetryConfig(
max_retries=3,
base_delay=1.0,
max_delay=30.0,
),
debug=True,
)
client = SpooledClient(config=config)
Error Handling
from spooled import SpooledClient
from spooled.errors import (
SpooledError,
NotFoundError,
ValidationError,
RateLimitError,
)
client = SpooledClient(api_key="sp_live_...")
try:
job = client.jobs.get("nonexistent")
except NotFoundError:
print("Job not found")
except RateLimitError as e:
# 429 covers both per-second rate limiting and plan-quota errors.
# A plan quota carries code == "QUOTA_EXCEEDED" (with resource/current/limit/plan details).
if e.code == "QUOTA_EXCEEDED":
print(f"Plan quota exceeded: {e.message}")
else:
print(f"Rate limited. Retry after {e.retry_after}s")
except SpooledError as e:
print(f"API error: {e.code} - {e.message}")
API Reference
Client Resources
| Resource | Description |
|---|---|
client.jobs |
Job CRUD, claim, complete, fail, DLQ |
client.queues |
Queue config, stats, pause/resume |
client.workers |
Worker registration, heartbeat |
client.schedules |
Cron job scheduling |
client.workflows |
Multi-job workflows with dependencies |
client.webhooks |
Outgoing webhook management |
client.api_keys |
API key management |
client.organizations |
Organization settings, usage |
client.billing |
Billing status, portal |
client.auth |
Authentication, token management |
client.health |
Health checks |
client.admin |
Admin operations (requires admin_key) |
Worker Events
| Event | Description |
|---|---|
started |
Worker started processing |
stopped |
Worker stopped |
error |
Worker error occurred |
job:claimed |
Job claimed from queue |
job:started |
Job handler started |
job:completed |
Job completed successfully |
job:failed |
Job failed |
Environment Variables
| Variable | Description |
|---|---|
SPOOLED_API_KEY |
API key for authentication |
SPOOLED_BASE_URL |
API base URL (default: https://api.spooled.cloud) |
Requirements
- Python 3.10+
- Core:
httpx>=0.25.0,pydantic>=2.0.0 - gRPC extra:
grpcio>=1.80.0,grpcio-tools>=1.80.0,protobuf>=6.33.5 - Realtime extra:
websockets>=12.0,sseclient-py>=1.8.0
The package version is defined in pyproject.toml. At runtime, spooled.__version__, the default REST User-Agent, worker options, and REST/gRPC worker registration read installed package metadata; source-only imports fall back to 1.2.0.
Release maintainers should follow the publishing checklist before creating a tag or publishing to PyPI.
License
Apache 2.0
Metadata
Release files for spooled 1.2.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| spooled-1.2.2.tar.gz | 83.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| spooled-1.2.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 201.7 kB
Release files / spooled-1.2.2.tar.gz
| Download URL | spooled-1.2.2.tar.gz |
|---|---|
| Size | 83.0 kB |
| Tags | Source |
|
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| Tags | Python 3 |
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Yes |
| Uploaded via |
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|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 26, 2026.
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