Metadata-Version: 2.1
Name: uwsgi-tasks
Version: 0.7.3
Summary: Asynchronous tasks management with UWSGI server
Home-page: https://github.com/Bahus/uwsgi_tasks
Author: Oleg Churkin
Author-email: bahusoff@gmail.com
License: MIT
Description: # UWSGI Tasks engine
        
        This package makes it to use [UWSGI signal framework](http://uwsgi-docs.readthedocs.org/en/latest/Signals.html)
        for asynchronous tasks management. It's more functional and flexible than [cron scheduler](https://wikipedia.org/wiki/Cron), and
        can be used as replacement for [celery](http://www.celeryproject.org/) in many cases.
        
        ## Requirements
        
        The module works only in [UWSGI web server](https://uwsgi-docs.readthedocs.org/en/latest/) environment,
        you also may have to setup some [mules](https://uwsgi-docs.readthedocs.org/en/latest/Mules.html) or\and [spooler processes](http://uwsgi-docs.readthedocs.org/en/latest/Spooler.html) as described in UWSGI documentation.
        
        ## Installation
        
        Simple execute `pip install uwsgi_tasks`
        
        ## Usage
        
        ### Mules, farms and spoolers
        
        **Use case**: you have Django project and want to send all emails asynchronously.
        
        Setup some mules with `--mule` or `--mules=<N>` parameters, or some spooler
        processes with `--spooler==<path_to_spooler_folder>`.
        
        Then write:
        
        ```python
        # myapp/__init__.py
        from django.core.mail import send_mail
        from uwsgi_tasks import task, TaskExecutor
        
        @task(executor=TaskExecutor.SPOOLER)
        def send_email_async(subject, body, email_to):
            # Execute task asynchronously on first available spooler
            return send_mail(subject, body, 'noreply@domain.com', [email_to])
        
        ...
        
        def my_view():
            # Execute tasks asynchronously on first available spooler
            send_email_async('Welcome!', 'Thank you!', 'user@domain.com')
        ```
        
        Execution of `send_email_async` will not block execution of `my_view`, since
        function will be called by first available spooler. I personally recommend to use spoolers rather than mules for several reasons:
        
        1. Task will be executed\retried even if uwsgi is crashed or restarted, since task information stored in files.
        2. Task parameters size is not limited to 64 KBytes.
        3. You may switch to external\network spoolers if required.
        4. You are able to tune task execution flow with introspection facilities.
        
        
        The following tasks execution backends are supported:
        
        * `AUTO` - default mode, spooler will be used if available, otherwise mule will be used. If mule is not available, than task is executed at runtime.
        * `MULE` - execute decorated task on first available mule
        * `SPOOLER` - execute decorated task on spooler
        * `RUNTIME` - execute task at runtime, this backend is also used in case `uwsgi` module can't be imported, e.g. tests.
        
        Common task parameters are:
        
        * `working_dir` - absolute path to execute task in. You won't typically need to provide this value, since it will be provided automatically: as soon as you execute the task current working directory will be saved and sent to spooler or mule. You may pass `None` value to disable this feature.
        
        When `SPOOLER` backend is used, the following additional parameters are supported:
        
        * `priority` - **string** related to priority of this task, larger = less important, so you can simply use digits. `spooler-ordered` uwsgi parameter must be set for this feature to work (in linux only?).
        * `at` - UNIX timestamp or Python **datetime** or Python **timedelta** object – when task must be executed.
        * `spooler_return` - boolean value, `False` by default. If `True` is passed, you can return spooler codes from function, e.g. `SPOOL_OK`, `SPOOL_RETRY` and `SPOOL_IGNORE`.
        * `retry_count` - how many times spooler should repeat the task if it returns `SPOOL_RETRY` code, implies `spooler_return=True`.
        * `retry_timeout` - how many seconds between attempts spooler should wait to execute the task. Actual timeout depends on `spooler-frequency` parameter. Python **timedelta** object is also supported.
        
        **Use case**: run task asynchronously and repeat execution 3 times at maximum if it fails, with 5 seconds timeout between attempts.
        
        ```python
        from functools import wraps
        from uwsgi_tasks import task, TaskExecutor, SPOOL_OK, SPOOL_RETRY
        
        def task_wrapper(func):
            @wraps(func)  # required!
            def _inner(*args, **kwargs):
                print 'Task started with parameters:', args, kwargs
                try:
                    func(*args, **kwargs)
                except Exception as ex:  # example
                    print 'Exception is occurred', ex, 'repeat the task'
                    return SPOOL_RETRY
        
                print 'Task ended', func
                return SPOOL_OK
        
            return _inner
        
        @task(executor=TaskExecutor.SPOOLER, retry_count=3, retry_timeout=5)
        @task_wrapper
        def spooler_task(text):
            print 'Hello, spooler! text =', text
            raise Exception('Sorry, task failed!')
        ```
        
        Raising `RetryTaskException(count=<retry_count>, timeout=<retry_timeout>)` approach can be also used to retry task execution:
        
        ```python
        import logging
        from uwsgi_tasks import RetryTaskException, task, TaskExecutor
        
        @task(executor=TaskExecutor.SPOOLER, retry_count=2)
        def process_purchase(order_id):
        
            try:
                # make something with order id
                ...
            except Exception as ex:
                logging.exception('Something bad happened')
                # retry task in 10 seconds for the last time
                raise RetryTaskException(timeout=10)
        ```
        
        Be careful when providing `count` parameter to the exception constructor - it may lead to infinite tasks execution, since the parameter replaces the value of `retry_count`.
        
        Task execution process can be also controlled via spooler options, see details [here](http://uwsgi-docs.readthedocs.org/en/latest/Spooler.html?highlight=spool_ok#options).
        
        ### Project setup
        
        There are some requirements to make asynchronous tasks work properly. Let's imagine your Django project has the following directory structure:
        
        ```
        ├── project/
        │   ├── venv/  <-- your virtual environment is placed here
        │   ├── my_project/  <-- Django project (created with "startproject" command)
        │   │   ├── apps/
        │   │   │   ├── index/  <-- Single Django application ("startapp" command)
        │   │   │   │   ├── __init__.py
        │   │   │   │   ├── admin.py
        │   │   │   │   ├── models.py
        │   │   │   │   ├── tasks.py
        │   │   │   │   ├── tests.py
        │   │   │   │   ├── views.py
        │   │   │   ├── __init__.py
        │   │   ├── __init__.py
        │   │   ├── settings.py
        │   │   ├── urls.py
        │   ├── spooler/  <-- spooler files are created here
        ```
        
        Minimum working UWSGI configuration is placed in `uwsgi.ini` file:
        
        ```ini
        [uwsgi]
        http-socket=127.0.0.1:8080
        processes=1
        workers=1
        
        # python path setup
        module=django.core.wsgi:get_wsgi_application()
        # absolute path to the virtualenv directory
        venv=<base_path>/project/venv/
        # Django project directory is placed here:
        pythonpath=<base_path>/project/
        # "importable" path for Django settings
        env=DJANGO_SETTINGS_MODULE=my_project.settings
        
        # spooler setup
        spooler=<base_path>/project/spooler
        spooler-processes=2
        spooler-frequency=10
        ```
        
        In such configuration you should put the following code into `my_project/__init__.py` file:
        
        ```python
        # my_project/__init__.py
        from uwsgi_tasks import set_uwsgi_callbacks
        
        set_uwsgi_callbacks()
        ```
        
        Task functions (decorated with `@task`) may be placed in any file where they can be imported, e.g. `apps/index/tasks.py`.
        
        If you still receive some strange errors when running asynchronous tasks, e. g.
        "uwsgi unable to find the spooler function" or "ImproperlyConfigured Django exception", you may try
        the following: add to uwsgi configuration new variable `spooler-import=my_project` - it will force spooler
        to import `my_project/__init__.py` file when starting, then add Django initialization
        into this file:
        
        ```python
        # my_project/__init__.py
        # ... set_uwsgi_callbacks code ...
        
        # if you use Django, otherwise use
        # initialization related to your framework\project
        from uwsgi_tasks import django_setup
        
        django_setup()
        ```
        
        Also make sure you **didn't override** uwsgi callbacks with this code
        `from uwsgidecorators import *` somewhere in your project.
        
        If nothing helps - please submit an issue.
        
        If you want to run some cron or timer-like tasks on project initialization you
        may import them in the same file:
        
        ```python
        # my_project/__init__.py
        # ... set_uwsgi_callbacks
        
        from my_cron_tasks import *
        from my_timer_tasks import *
        ```
        
        Keep in mind that task arguments must be [pickable](http://stackoverflow.com/questions/3603581/what-does-it-mean-for-an-object-to-be-picklable-or-pickle-able), since they are serialized and send via socket (mule) or file (spooler).
        
        ### Timers, red-black timers and cron
        
        This API is similar to uwsgi bundled Python decorators [module](http://uwsgi-docs.readthedocs.org/en/latest/PythonDecorators.html). One thing to note: you are not able to provide any arguments to timer-like or cron-like tasks. See examples below:
        
        ```python
        from uwsgi_tasks import *
        
        @timer(seconds=5)
        def print_every_5_seconds(signal_number):
            """Prints string every 5 seconds
        
            Keep in mind: task is created on initialization.
            """
            print 'Task for signal', signal_number
        
        @timer(seconds=5, iterations=3, target='workers')
        def print_every_5_seconds(signal_number):
            """Prints string every 5 seconds 3 times"""
            print 'Task with iterations for signal', signal_number
        
        @timer_lazy(seconds=5)
        def print_every_5_seconds_after_call(signal_number):
            """Prints string every 5 seconds"""
            print 'Lazy task for signal', signal_number
        
        @cron(minute=-2)
        def print_every_2_minutes(signal_number):
            print 'Cron task:', signal_number
        
        @cron_lazy(minute=-2, target='mule')
        def print_every_2_minutes_after_call(signal_number):
            print 'Cron task:', signal_number
        
        ...
        
        def my_view():
           print_every_5_seconds_after_call()
           print_every_2_minutes_after_call()
        ```
        
        Timer and cron decorators supports `target` parameter, supported values are described [here](http://uwsgi-docs.readthedocs.org/en/latest/PythonModule.html#uwsgi.register_signal).
        
        Keep in mind the maximum number of timer-like and cron-like tasks is 256 for each available worker.
        
        ### Task introspection API
        
        Using task introspection API you can get current task object inside current task function and will be able to change some task parameters. You may also use special `buffer` dict-like object to pass data between task execution attempts. Using `get_current_task` you are able to get internal representation of task object and manipulate the attributes of the task, e.g. SpoolerTask object has the following changeable properties: `at`, `retry_count`, `retry_timeout`.
        
        Here is a complex example:
        
        ```python
        from uwsgi_tasks import get_current_task
        
        @task(executor=TaskExecutor.SPOOLER, at=datetime.timedelta(seconds=10))
        def remove_files_sequentially(previous_selected_file=None):
            # get current SpoolerTask object
            current_task = get_current_task()
        
            selected_file = select_file_for_removal(previous_selected_file)
        
            # we should stop the task here
            if selected_file is None:
                logger.info('All files were removed')
                for filename, removed_at in current_task.buffer['results'].items():
                    logger.info('File "%s" was removed at "%s"', filename, removed_at)
                for filename, error_message in current_task.buffer['errors'].items():
                    logger.info('File "%s", error: "%s"', filename, error_message)
                return
        
            try:
                logger.info('Removing the file "%s"', selected_file)
                # ... remove the file ...
                del_file(selected_file)
            except IOError as ex:
                logger.exception('Cannot delete file "%s"', selected_file)
        
                # let's try to remove this one more time later
                io_errors = current_task.buffer.setdefault('errors', {}).get(selected_file)
                if not io_errors:
                    current_task.buffer['errors'][selected_file] = str(ex)
                    current_task.at = datetime.timedelta(seconds=20)
                    return current_task(previous_selected_file)
        
            # save datetime of removal
            current_task.buffer.setdefault('results', {})[selected_file] = datetime.datetime.now()
        
            # run in async mode
            return current_task(selected_file)
        ```
        
        #### Changing task configuration before execution
        
        You may use `add_setup` method to change some task-related settings before (or during) task execution process. The following example shows how to change timer's timeout and iterations amount at runtime:
        
        ```python
        from uwsgi_tasks import timer_lazy
        
        @timer_lazy(target='worker')
        def run_me_periodically(signal):
            print('Running with signal:', signal)
        
        def my_view(request):
            run_me_periodically.add_setup(seconds=10, iterations=2)
            run_me_periodically()
        ```
        
Keywords: asynchronous,tasks,uwsgi
Platform: Platform Independent
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Web Environment
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Requires: uwsgi
Requires: six
Description-Content-Type: text/markdown
