omniq 1.6.0

OmniQ v1 - Redis+Lua queue Python SDK

OmniQ (Python)

OmniQ is a Redis + Lua, language-agnostic job queue.
This package is the Python client for OmniQ v1.

Core project / docs: https://github.com/not-empty/omniq

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Key Ideas

• Hybrid lanes
  • Ungrouped jobs by default
  • Optional grouped jobs (FIFO per group + per-group concurrency)
• Lease-based execution
  • Workers reserve a job with a time-limited lease
• Token-gated ACK / heartbeat
  • reserve() returns a lease_token
  • heartbeat() and ack_*() must include the same token
• Pause / resume (flag-only)
  • Pausing prevents new reserves
  • Running jobs are not interrupted
  • Jobs are not moved
• Admin-safe operations
  • Strict retry, retry_batch, remove, remove_batch
• Handler-driven execution layer
  • ctx.exec exposes internal OmniQ operations safely inside handlers

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Install

pip install omniq

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Quick Start

Publish

# importing the lib
from omniq.client import OmniqClient

# creating OmniQ passing redis information
omniq = OmniqClient(
    host="omniq-redis",
    port=6379,
)

# publishing the job
job_id = omniq.publish(
    queue="demo",
    payload={"hello": "world"},
    timeout_ms=30_000
)

print("OK", job_id)

---

Publish Structured JSON

from dataclasses import dataclass
from typing import List, Optional

# importing the lib
from omniq.client import OmniqClient


# Nested structure
@dataclass
class Customer:
    id: str
    email: str
    vip: bool


# Main payload
@dataclass
class OrderCreated:
    order_id: str
    customer: Customer
    amount: int
    currency: str
    items: List[str]
    processed: bool
    retry_count: int
    tags: Optional[List[str]] = None


# creating OmniQ passing redis information
omniq = OmniqClient(
    host="omniq-redis",
    port=6379,
)

# creating structured payload
payload = OrderCreated(
    order_id="ORD-2026-0001",
    customer=Customer(
        id="CUST-99",
        email="[e-mail]",
        vip=True,
    ),
    amount=1500,
    currency="USD",
    items=["keyboard", "mouse"],
    processed=False,
    retry_count=0,
    tags=["priority", "online"],
)

# publish using publish_json
job_id = omniq.publish_json(
    queue="deno",
    payload=payload,
    max_attempts=5,
    timeout_ms=60_000,
)

print("OK", job_id)

---

Consume

import time

# importing the lib
from omniq.client import OmniqClient

# creating your handler (ctx will have all the job information and actions)
def my_actions(ctx):
    print("Waiting 2 seconds")
    time.sleep(2)
    print("Done")

# creating OmniQ passing redis information
omniq = OmniqClient(
    host="omniq-redis",
    port=6379,
)

# creating the consumer that will listen and execute the actions in your handler
omniq.consume(
    queue="demo",
    handler=my_actions,
    verbose=True,
    drain=False,
)

---

Handler Context

Inside handler(ctx):

• queue
• job_id
• payload_raw
• payload
• attempt
• lock_until_ms
• lease_token
• gid
• exec → execution layer (ctx.exec)

---

Administrative Operations

All admin operations are Lua-backed and atomic.

retry_failed()

omniq.retry_failed(queue="demo", job_id="01ABC...")

• Works only if job state is failed
• Resets attempt counter
• Respects grouping rules

---

retry_failed_batch()

results = omniq.retry_failed_batch(
    queue="demo",
    job_ids=["01A...", "01B...", "01C..."]
)

for job_id, status, reason in results:
    print(job_id, status, reason)

• Max 100 jobs per call
• Atomic batch
• Per-job result returned

---

remove_job()

omniq.remove_job(
    queue="demo",
    job_id="01ABC...",
    lane="failed",  # wait | delayed | failed | completed | gwait
)

Rules:

• Cannot remove active jobs
• Lane must match job state
• Group safety preserved

---

remove_jobs_batch()

results = omniq.remove_jobs_batch(
    queue="demo",
    lane="failed",
    job_ids=["01A...", "01B...", "01C..."]
)

• Max 100 per call
• Strict lane validation
• Atomic per batch

---

pause()

pause_result = omniq.pause(
    queue="demo",
)

resume_result = omniq.resume(
    queue="demo",
)

is_paused = omniq.is_paused(
    queue="demo",
)

---

Handler Context

Inside handler(ctx):

• queue
• job_id
• payload_raw
• payload
• attempt
• lock_until_ms
• lease_token
• gid
• exec

---

Child Ack Control (Parent / Child Workflows)

A handler-driven primitive for fan-out workflows.

No TTL. Cleanup happens only when counter reaches zero.

Parent Example

The first queue will receive a document with 5 pages

# importing the lib
from omniq.client import OmniqClient

# creating OmniQ passing redis information
omniq = OmniqClient(
    host="omniq-redis",
    port=6379,
)

# publishing the job
job_id = omniq.publish(
    queue="documents",
    payload={
        "document_id": "doc-123", # this will be our unique key to initiate childs and tracking then until completion
        "pages": 5, # each page must be completed before something happen
    },
)
print("OK", job_id)

The first consumer will publish a job for each page passing the unique key for childs tracking

# importing the lib
from omniq.client import OmniqClient

# creating OmniQ passing redis information
omniq = OmniqClient(
    host="omniq-redis",
    port=6379,
)

# publishing the job
job_id = omniq.publish(
    queue="documents",
    payload={
        "document_id": "doc-123", # this will be our unique key to initiate childs and tracking then until completion
        "pages": 5, # each page must be completed before something happen
    },
)
print("OK", job_id)

Child Example

The second consumer will deal with each page and ack each child (alerting when the last page was processed)

import time

# importing the lib
from omniq.client import OmniqClient

# creating your handler (ctx will have all the job information and actions)
def page_worker(ctx):

    page = ctx.payload["page"]
    # getting the unique key to track the childs
    completion_key = ctx.payload["completion_key"]

    print(f"[page_worker] Processing page {page} (job_id={ctx.job_id})")
    time.sleep(1.5)

    # acking itself as a child the number of remaining jobs are returned so we can say when the last job was executed
    remaining = ctx.exec.child_ack(completion_key)

    print(f"[page_worker] Page {page} done. Remaining={remaining}")
    

    # remaining will be 0 ONLY when this is the last job
    # will return > 0 when are still jobs to process
    # and -1 if something goes wrong with the counter
    if remaining == 0:
        print("[page_worker] Last page finished.")

# creating OmniQ passing redis information
omniq = OmniqClient(
    host="omniq-redis",
    port=6379,
)

# creating the consumer that will listen and execute the actions in your handler
omniq.consume(
    queue="pages",
    handler=page_worker,
    verbose=True,
    drain=False,
)

Properties:

• Idempotent decrement
• Safe under retries
• Cross-queue safe
• Fully business-logic driven

---

Grouped Jobs

# if you provide a gid (group_id) you can limit the parallel execution for jobs in the same group
omniq.publish(queue="demo", payload={"i": 1}, gid="company:acme", group_limit=1)

# you can also publis ungrouped jobs that will also be executed (fairness by round-robin algorithm)
omniq.publish(queue="demo", payload={"i": 2})

• FIFO inside group
• Groups execute in parallel
• Concurrency limited per group

---

Pause and Resume inside the consumer

You publish your job as usual

# importing the lib
from omniq.client import OmniqClient

# creating OmniQ passing redis information
uq = OmniqClient(
    host="omniq-redis",
    port=6379,
)

# publishing the job
job_id = uq.publish(
    queue="test",
    payload={"hello": "world"},
    timeout_ms=30_000
)
print("OK", job_id)

Inside your consumer you can pause/resume your queue (or another one)

import time

# importing the lib
from omniq.client import OmniqClient

# creating your handler (ctx will have all the job information and actions)
def pause_unpause_example(ctx):
    print("Waiting 2 seconds")

    # checking if this queue it is paused (spoiler: it's not)
    is_paused = ctx.exec.is_paused(
        queue="test"
    )
    print("Is paused", is_paused)
    time.sleep(2)


    print("Pausing")

    # pausing this queue (this job it's and others active jobs will be not affected but not new job will be start until queue is resumed)
    ctx.exec.pause(
        queue="test"
    )

    # checking again now is suposed to be paused
    is_paused = ctx.exec.is_paused(
        queue="test"
    )
    print("Is paused", is_paused)
    time.sleep(2)

    print("Resuming")

    # resuming this queue (all other workers can process jobs again)
    ctx.exec.resume(
        queue="test"
    )

    # checking again and is suposed to be resumed
    is_paused = ctx.exec.is_paused(
        queue="test"
    )
    print("Is paused", is_paused)
    time.sleep(2)

    print("Done")

# creating OmniQ passing redis information
omniq = OmniqClient(
    host="omniq-redis",
    port=6379,
)

# creating the consumer that will listen and execute the actions in your handler
omniq.consume(
    queue="test",
    handler=pause_unpause_example,
    verbose=True,
    drain=False,
)

Examples

All examples can be found in the ./examples folder.

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License

See the repository license.