Best Flask open-source libraries and packages

Flask_Production

Cherrypy server for Flask + scheduler
Updated 1 year ago

flask-production

Cherrypy prod server for Flask + parallel task scheduler

|Python 3.7| |license| |pytest|

Installation

.. code:: sh

pip install flask_production

Usage example

CherryFlask

``Cherrypy`` server on top of ``Flask`` app

.. code:: python

   CherryFlask(app, scheduler=None, silent=False)


Parameters:

- **app** *(Flask)*: ``Flask`` application

- **scheduler** *(TaskScheduler)*: task scheduler to run in parallel with ``Flask`` app

- **silent** *(bool)*: don't print logs
      - default False



.. code:: python

   from flask import Flask
   from flask_production import CherryFlask

   app = Flask(__name__)
   ...

   cherry = CherryFlask(app)
   cherry.run(host="0.0.0.0", port=8080, threads=5, debug=False)

|


TaskScheduler

| Main class to setup, run and manage jobs

.. code:: python

TaskScheduler(check_interval=5, holidays_calendar=None, tzname=None, on_job_error=None, log_filepath=None, log_maxsize=510241024, # 5 MB log_backups=1, startup_grace_mins=0, # minutes persist_states=True, state_handler=None)

Parameters:

  • check_interval (int): how often to check for pending jobs - default 5 seconds

  • holidays_calendar (holidays.HolidayBase): calendar to use for intervals like businessday - default US holidays

  • tzname (str): name of timezone as supported by dateutil.tz

  • on_job_error (func(e)): function to call if any job fails

  • log_filepath (path): file to write logs to

  • log_maxsize (int): byte limit per log file - default 5 mb (only effective if log_filepath is provided)

  • log_backups (int): number of backups of logs to retain - default 1 (only effective if log_filepath is provided)

  • startup_grace_mins (int): grace period for tasks in case a schedule was missed because of app restart - default 0

  • persist_states (bool): store job logs and read back on app restart - default True (logs will be stored)

  • state_handler (.state.BaseStateHandler): different handler backends to store job logs - default .state.FileSystemState (logs will be stored in a unique data directory)

Standalone usage

.. code:: python

from flask_production import TaskScheduler

sched = TaskScheduler(check_interval=2)

Run every minute

sched.every(60).do(foo)

Run on end of every month (with strict_date False)

sched.every("31st").strict_date(False).at("08:00").do(foo)

Run every weekday

sched.every("weekday").at("08:00").do(lambda:bar()) sched.every("weekday").at("08:00").timezone("Europe/London").do(lambda:bar())

catch() will run on job error

example_job = sched.every("weekday").at("09:00").do(lambda:failing()).catch(lambda e: print(e))

access job information and status as dict

print(example_job.to_dict()) print(sched.jobs[-1].to_dict()) # same job

sched.start() # starts the task scheduler and blocks ..

Instead of sched.start(), TaskScheduler can be run in parallel with a Flask application using CherryFlask

.. code:: python

from flask import Flask from flask_production import TaskScheduler, CherryFlask

app = Flask(name) ...

sched = TaskScheduler() ...

cherry = CherryFlask(app, scheduler=sched) cherry.run(host="0.0.0.0", port=8080, threads=5, debug=False)

..

|

TaskMonitor


| The TaskScheduler exposes a list of Job objects through the ``.jobs`` attribute
| Job information and logs from the last execution are available using the ``.to_dict()`` method
| TaskMonitor uses these features to provide a web interface to view and rerun tasks



.. code:: python

   TaskMonitor(
      app,
      sched,
      display_name=None,
      endpoint="@taskmonitor",
      homepage_refresh=30,
      taskpage_refresh=5,
      can_rerun=True,
      can_disable=True)

Parameters:

- **app** *(int)*: ``Flask`` application
- **sched** *(TaskScheduler)*: task scheduler with task definitions
- **display_name** *(str)*: name of the application to be displayed
      - default app.name

- **endpoint** *(str)*: URL endpoint where the taskmonitor can be viewed
      - default "@taskmonitor"
- **homepage_refresh** *(int)*: home page auto refresh interval (in seconds)
      - default 30
- **taskpage_refresh** *(int)*: task page auto refresh interval (in seconds)
      - default 5
- **can_rerun** *(bool)*: if True adds rerun button to job page
      - default True
- **can_disable** *(bool)*: if True adds disable button to job page
      - default True


.. code:: python

   from flask import Flask
   from flask_production import CherryFlask, TaskScheduler
   from flask_production.plugins import TaskMonitor

   app = Flask(__name__)
   sched = TaskScheduler(check_interval=2)

   monitor = TaskMonitor(app, sched)
   print(monitor._endpoint) # /@taskmonitor

   # Run every minute
   sched.every(60).do(foo)

   cherry = CherryFlask(app, scheduler=sched)
   cherry.run(host="0.0.0.0", port=8080) # localhost:8080/@taskmonitor

`Example Gist
here <https://gist.github.com/shashfrankenstien/5cfa8821d74c24fb0a01b979d434e5bb>`__


TODO:

| scheduler - function argument validation

.. |Python 3.7| image:: https://img.shields.io/badge/python-3.7+-blue.svg .. |license| image:: https://img.shields.io/github/license/shashfrankenstien/flask_production .. |pytest| image:: https://github.com/shashfrankenstien/Flask_Production/workflows/pytest/badge.svg