Skip to main content

kicker

Lightweight job runner built on FastAPI and APScheduler with a simple web UI.

Features

  • FastAPI-style developer experience
    • app = Kicker()
    • @app.kick(...)
    • standard uvicorn module:app
  • Schedule jobs with APScheduler using decorators
  • Run jobs manually from UI
  • Pause/resume scheduler and individual jobs
  • Supports both sync and async functions
  • Simple HTML interface
  • Use multiple log outputs
  • Save execution state between job runs
  • Supports multiple named instances of the same job

Installation

uv add kicker

Usage

Create a project and define your jobs:

# main.py
from kicker import Kicker, JobContext

app = Kicker(logger_fmt="%(prefix)s[%(levelname)s] %(message)s at %(asctime)s")


@app.kick(day_of_week="mon-fri", hour="9-20/2", minute=0)
async def job_echo(ctx: JobContext):
    ctx.logger.info("job_echo executed")


# run the app
# uv run uvicorn package.module:app --reload

To see logs in the UI, declare a logger parameter — kicker injects it automatically. Jobs without it work fine but won't produce UI logs.

Splitting jobs across files

Like FastAPI's APIRouter, Coworker lets you define jobs in separate files and include them in the main app — no circular imports, no shared app instance.

# jobs/weekly_report.py
from kicker import Coworker, JobContext

worker = Coworker()


@worker.kick(hour=8, minute=0)
async def weekly_report(ctx: JobContext):
    ctx.logger.info("weekly_report executed")
# main.py
from kicker import Kicker
from jobs.weekly_report import worker

app = Kicker()
app.include_coworker(worker)

Adding multiple log outputs

It is possible to have multiple visual log output "containers". By default, the default output container is used. To see logs in a different output container, use the standatd extra keyword argument of the logger method you use (error in this example) with a output key and some string value as a new output container name:

from kicker import Kicker, JobContext

app = Kicker()


@app.kick(second="*/5")
def sync_job(ctx: JobContext):
    try:
        ...
    except:
        ctx.logger.error(
            "error in a sync job executed in the thread pool",
            extra={"output": "errors"},
        )

or, cleaner with partial:

from functools import partial

from kicker import Kicker, JobContext

app = Kicker()


@app.kick(second="*/5")
def sync_job(ctx: JobContext):
    log_error = partial(ctx.logger.error, extra={"output": "errors"})
    try:
        ...
    except:
        log_error("error in a sync job executed in the thread pool")

Getting access to the scheduler and the job

Along with the logger parameter, kicker also injects the scheduler object and a job_id of the current job object. This is useful for managing jobs — for example, we can change the next run time of the current job:

from datetime import datetime, timedelta
from functools import partial

from kicker import Kicker, JobContext

app = Kicker()


@app.kick(second="*/5")
def sync_job(ctx: JobContext):
    log_debug = partial(ctx.logger.debug, extra={"output": "debug"})
    slowdown_interval_minutes = 10
    try:
        ...
    except Exception as e:
        ctx.scheduler.modify_job(
            ctx.job_id,
            next_run_time=datetime.now() + timedelta(minutes=slowdown_interval_minutes),
        )
        log_debug(f"error: {e} - slowing down for {slowdown_interval_minutes} minutes")

Save execution state between job runs

You can save arbitrary data in ctx.storage between job runs.

from kicker import Coworker, JobContext

worker = Coworker()


@worker.kick(second="*/6")
async def very_important_job_with_runs_counter(ctx: JobContext):
    counter = ctx.storage.get("counter", 0)
    ctx.logger.info(f"important job executed ({counter}) times")
    ctx.storage["counter"] = counter + 1

Run multiple named instances of the same job

It is possible to specify an instance name when including a coworker:

from kicker import Kicker
from jobs.weekly_report import worker

app = Kicker()
app.include_coworker(worker)  # default instance
app.include_coworker(worker, instance="v2")

or just directly in the job decorator:

from datetime import datetime, timedelta
from functools import partial

from kicker import Kicker, JobContext

app = Kicker()


def same_business_logic(ctx: JobContext):
    ctx.logger.info(
        f"sync job {ctx.instance} executed in the thread pool with a very long message",
        extra={"output": "sync_job"},
    )


@app.kick(second="*/5")
def sync_job1(ctx: JobContext):
    same_business_logic(ctx)


@app.kick(second="*/4", instance="v2")
def sync_job2(ctx: JobContext):
    same_business_logic(ctx)

Visible last job execution status

You can report failure or success job execution status to the UI. The status will be displayed with a green or red dot next to the job name.

from kicker import Coworker, JobContext

worker = Coworker()


@worker.kick(second="*/30")
async def some_job(ctx: JobContext):
    try:
        ...
    except Exception:
        ctx.report_execution_status("failure")
    else:
        ctx.report_execution_status("success")

Notes

  • Scheduler runs in-process (not distributed)
  • Running with multiple workers will duplicate job execution
  • Designed for simple internal tools and automation

License

MIT

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

kicker-1.3.0.tar.gz (8.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

kicker-1.3.0-py3-none-any.whl (10.9 kB view details)

Uploaded Python 3

File details

Details for the file kicker-1.3.0.tar.gz.

File metadata

  • Download URL: kicker-1.3.0.tar.gz
  • Upload date:
  • Size: 8.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.10.4 {"installer":{"name":"uv","version":"0.10.4","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Linux Mint","version":"22.3","id":"zena","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":null}

File hashes

Hashes for kicker-1.3.0.tar.gz
Algorithm Hash digest
SHA256 c326ad92970b00c934f1fcf2ed14254286439485e0188a466f7a3a154df7ab3b
MD5 f30ba87610c6b08254c28df73c9f2f05
BLAKE2b-256 4010d2868d41f5a0d5a60ecf027ed4256b1c1e75d64ec3939bf717459b385129

See more details on using hashes here.

File details

Details for the file kicker-1.3.0-py3-none-any.whl.

File metadata

  • Download URL: kicker-1.3.0-py3-none-any.whl
  • Upload date:
  • Size: 10.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.10.4 {"installer":{"name":"uv","version":"0.10.4","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Linux Mint","version":"22.3","id":"zena","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":null}

File hashes

Hashes for kicker-1.3.0-py3-none-any.whl
Algorithm Hash digest
SHA256 9b9e58247708b864e5a0765285c4488afe7b539886bc00e6609740bb011e6c08
MD5 026cdf088e14b4179c5d13b29e1537f0
BLAKE2b-256 7b3314eceab392898cb1655f9049fe42cbb354c60d0c7be90a40dd158b2bac49

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page