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A multi-platform cron-like job runner in Python

Project description

Pycroner

Pycroner

Pycroner is a lightweight cron style job runner implemented in Python. Jobs are configured via a YAML file and executed by the runner once their cron schedule matches the current time.

Features

  • Parses standard five field cron expressions (minute, hour, day, month, weekday) using a small built in parser.
  • Jobs can optionally be fanned out into multiple processes. Fanout may be an integer (repeat the job N times) or a list of argument strings that will be appended to the base command.
  • Configuration lives in pycroner.yml by default. The exact format is described in pycroner/spec.md.

Installation

From PyPI:

pip install pycroner

Usage

From code

  1. Create a pycroner.yml file describing your jobs. A simple example is shown below.
  2. Run the job runner from a Python script:
from pycroner.runner import Runner

Runner("pycroner.yml").run()

The runner checks schedules every minute and spawns each job as a subprocess when its cron expression matches the current time.

From CLI

You can also invoke the runner directly from the command line using the pycroner command. By default it looks for pycroner.yml in the current directory:

pycroner

Specify an alternative working directory with --at or a specific configuration file with --config:

pycroner --at /path/to/project
pycroner --config custom.yml

Example Configuration

jobs:
  - id: "index_articles"
    schedule: "*/15 * * * *"
    command: "python index.py"
    fanout: 4

  - id: "daily_etl"
    schedule: "0 2 * * *"
    command: "python etl.py"
    fanout:
      - "--source=internal --mode=full"
      - "--source=external --mode=delta"

  - id: "ping"
    schedule: "* * * * *"
    command: "python ping.py"

Jobs run independently, and any output or error handling is left to your commands. For full details see pycroner/spec.md.

If the configuration file changes while the runner is active, it will be reloaded automatically so updates take effect without restarting.

Output from each job is streamed with a colored prefix containing the job id, and if fanned out, the fannout numeric id is attached.

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