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|
%global _empty_manifest_terminate_build 0
Name: python-django-apscheduler
Version: 0.6.2
Release: 1
Summary: APScheduler for Django
License: MIT
URL: http://github.com/jcass77/django-apscheduler
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/37/a2/3815e39c3ec7c83c721d9330380b2afad97b8fee9e83d19b23d4a47235f8/django-apscheduler-0.6.2.tar.gz
BuildArch: noarch
Requires: python3-django
Requires: python3-apscheduler
%description
[](https://pypi.org/project/django-apscheduler/)
[](https://pypi.org/project/django-apscheduler/)
[](https://pypi.org/project/django-apscheduler/)
[](https://github.com/jcass77/django-apscheduler/actions?query=workflow%3A%22Python+package%22)
[](https://codecov.io/gh/jcass77/django-apscheduler)
[](https://pypi.org/project/black)
[APScheduler](https://github.com/agronholm/apscheduler) for [Django](https://github.com/django/django).
This is a Django app that adds a lightweight wrapper around APScheduler. It enables storing persistent jobs in the
database using Django's ORM.
django-apscheduler is a great choice for quickly and easily adding basic scheduling features to your Django applications
with minimal dependencies and very little additional configuration. The ideal use case probably involves running a
handful of tasks on a fixed execution schedule.
**PLEASE NOTE:** the trade-off of this simplicity is that you need to **be careful to ensure that you have only ONE
scheduler actively running at a particular point in time**.
This limitation is due to the fact that APScheduler does not currently have
any [interprocess synchronization and signalling scheme](https://apscheduler.readthedocs.io/en/latest/faq.html#how-do-i-share-a-single-job-store-among-one-or-more-worker-processes)
that would enable the scheduler to be notified when a job has been added, modified, or removed from a job store (in
other words, different schedulers won't be able to tell if a job has already been run by another scheduler, and changing
a job's scheduled run time directly in the database does nothing unless you also restart the scheduler).
Depending on how you are currently doing your
Django [deployments](https://docs.djangoproject.com/en/dev/howto/deployment/#deploying-django), working with this
limitation might require a bit of thought. It is quite common to start up many webserver worker process in production
environments in order to scale and handle large volumes of user traffic. If each of these worker processes end up
running their own scheduler then this can result in jobs being missed or executed multiple times, as well as duplicate
entries being created in the `DjangoJobExecution` table.
Support for sharing a persistent job store between multiple schedulers appears to be planned for
an [upcoming APScheduler 4.0 release](https://github.com/agronholm/apscheduler/issues/465).
So for now your options are to either:
1. Use a custom Django management command to start a single scheduler in its own dedicated process (**recommended** -
see the `runapscheduler.py` example below); or
2. Implement your
own [remote processing](https://apscheduler.readthedocs.io/en/latest/faq.html#how-do-i-share-a-single-job-store-among-one-or-more-worker-processes)
logic to ensure that a single `DjangoJobStore` can be used by all of the webserver's worker processes in a
coordinated and synchronized way (might not be worth the extra effort and increased complexity for most use cases);
or
3. Select an alternative task processing library that *does* support inter-process communication using some sort of
shared message broker like Redis, RabbitMQ, Amazon SQS or the like (see:
https://djangopackages.org/grids/g/workers-queues-tasks/ for popular options).
%package -n python3-django-apscheduler
Summary: APScheduler for Django
Provides: python-django-apscheduler
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-django-apscheduler
[](https://pypi.org/project/django-apscheduler/)
[](https://pypi.org/project/django-apscheduler/)
[](https://pypi.org/project/django-apscheduler/)
[](https://github.com/jcass77/django-apscheduler/actions?query=workflow%3A%22Python+package%22)
[](https://codecov.io/gh/jcass77/django-apscheduler)
[](https://pypi.org/project/black)
[APScheduler](https://github.com/agronholm/apscheduler) for [Django](https://github.com/django/django).
This is a Django app that adds a lightweight wrapper around APScheduler. It enables storing persistent jobs in the
database using Django's ORM.
django-apscheduler is a great choice for quickly and easily adding basic scheduling features to your Django applications
with minimal dependencies and very little additional configuration. The ideal use case probably involves running a
handful of tasks on a fixed execution schedule.
**PLEASE NOTE:** the trade-off of this simplicity is that you need to **be careful to ensure that you have only ONE
scheduler actively running at a particular point in time**.
This limitation is due to the fact that APScheduler does not currently have
any [interprocess synchronization and signalling scheme](https://apscheduler.readthedocs.io/en/latest/faq.html#how-do-i-share-a-single-job-store-among-one-or-more-worker-processes)
that would enable the scheduler to be notified when a job has been added, modified, or removed from a job store (in
other words, different schedulers won't be able to tell if a job has already been run by another scheduler, and changing
a job's scheduled run time directly in the database does nothing unless you also restart the scheduler).
Depending on how you are currently doing your
Django [deployments](https://docs.djangoproject.com/en/dev/howto/deployment/#deploying-django), working with this
limitation might require a bit of thought. It is quite common to start up many webserver worker process in production
environments in order to scale and handle large volumes of user traffic. If each of these worker processes end up
running their own scheduler then this can result in jobs being missed or executed multiple times, as well as duplicate
entries being created in the `DjangoJobExecution` table.
Support for sharing a persistent job store between multiple schedulers appears to be planned for
an [upcoming APScheduler 4.0 release](https://github.com/agronholm/apscheduler/issues/465).
So for now your options are to either:
1. Use a custom Django management command to start a single scheduler in its own dedicated process (**recommended** -
see the `runapscheduler.py` example below); or
2. Implement your
own [remote processing](https://apscheduler.readthedocs.io/en/latest/faq.html#how-do-i-share-a-single-job-store-among-one-or-more-worker-processes)
logic to ensure that a single `DjangoJobStore` can be used by all of the webserver's worker processes in a
coordinated and synchronized way (might not be worth the extra effort and increased complexity for most use cases);
or
3. Select an alternative task processing library that *does* support inter-process communication using some sort of
shared message broker like Redis, RabbitMQ, Amazon SQS or the like (see:
https://djangopackages.org/grids/g/workers-queues-tasks/ for popular options).
%package help
Summary: Development documents and examples for django-apscheduler
Provides: python3-django-apscheduler-doc
%description help
[](https://pypi.org/project/django-apscheduler/)
[](https://pypi.org/project/django-apscheduler/)
[](https://pypi.org/project/django-apscheduler/)
[](https://github.com/jcass77/django-apscheduler/actions?query=workflow%3A%22Python+package%22)
[](https://codecov.io/gh/jcass77/django-apscheduler)
[](https://pypi.org/project/black)
[APScheduler](https://github.com/agronholm/apscheduler) for [Django](https://github.com/django/django).
This is a Django app that adds a lightweight wrapper around APScheduler. It enables storing persistent jobs in the
database using Django's ORM.
django-apscheduler is a great choice for quickly and easily adding basic scheduling features to your Django applications
with minimal dependencies and very little additional configuration. The ideal use case probably involves running a
handful of tasks on a fixed execution schedule.
**PLEASE NOTE:** the trade-off of this simplicity is that you need to **be careful to ensure that you have only ONE
scheduler actively running at a particular point in time**.
This limitation is due to the fact that APScheduler does not currently have
any [interprocess synchronization and signalling scheme](https://apscheduler.readthedocs.io/en/latest/faq.html#how-do-i-share-a-single-job-store-among-one-or-more-worker-processes)
that would enable the scheduler to be notified when a job has been added, modified, or removed from a job store (in
other words, different schedulers won't be able to tell if a job has already been run by another scheduler, and changing
a job's scheduled run time directly in the database does nothing unless you also restart the scheduler).
Depending on how you are currently doing your
Django [deployments](https://docs.djangoproject.com/en/dev/howto/deployment/#deploying-django), working with this
limitation might require a bit of thought. It is quite common to start up many webserver worker process in production
environments in order to scale and handle large volumes of user traffic. If each of these worker processes end up
running their own scheduler then this can result in jobs being missed or executed multiple times, as well as duplicate
entries being created in the `DjangoJobExecution` table.
Support for sharing a persistent job store between multiple schedulers appears to be planned for
an [upcoming APScheduler 4.0 release](https://github.com/agronholm/apscheduler/issues/465).
So for now your options are to either:
1. Use a custom Django management command to start a single scheduler in its own dedicated process (**recommended** -
see the `runapscheduler.py` example below); or
2. Implement your
own [remote processing](https://apscheduler.readthedocs.io/en/latest/faq.html#how-do-i-share-a-single-job-store-among-one-or-more-worker-processes)
logic to ensure that a single `DjangoJobStore` can be used by all of the webserver's worker processes in a
coordinated and synchronized way (might not be worth the extra effort and increased complexity for most use cases);
or
3. Select an alternative task processing library that *does* support inter-process communication using some sort of
shared message broker like Redis, RabbitMQ, Amazon SQS or the like (see:
https://djangopackages.org/grids/g/workers-queues-tasks/ for popular options).
%prep
%autosetup -n django-apscheduler-0.6.2
%build
%py3_build
%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .
%files -n python3-django-apscheduler -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Tue Apr 11 2023 Python_Bot <Python_Bot@openeuler.org> - 0.6.2-1
- Package Spec generated
|
