Metadata-Version: 1.1
Name: backoff
Version: 1.0.1
Summary: Function decoration for pluggable backoff and retry
Home-page: https://github.com/litl/backoff
Author: Bob Green
Author-email: bgreen@litl.com
License: MIT
Description: 
        Function decoration for pluggable backoff and retry
        
        This module provides function decorators which can be used to wrap a
        function such that it will be retried until some condition is met. It
        is meant to be of use when accessing unreliable resources with the
        potential for intermittent failures i.e. network resources and external
        APIs. Somewhat more generally, it may also be of use for dynamically
        polling resources for externally generated content.
        
        ## Examples
        
        *Since Kenneth Reitz's [requests](http://python-requests.org) module
        has become a defacto standard for HTTP clients in python, networking
        examples below are written using it, but it is in no way required by
        the backoff module.*
        
        ### @backoff.on_exception
        
        The on_exception decorator is used to retry when a specified exception
        is raised. Here's an example using exponential backoff when any
        requests exception is raised:
        
            @backoff.on_exception(backoff.expo,
                                  requests.exceptions.RequestException,
                                  max_tries=8)
            def get_url(url):
                return requests.get(url)
        
        ### @backoff.on_predicate
        
        The on_predicate decorator is used to retry when a particular condition
        is true of the return value of the target function.  This may be useful
        when polling a resource for externally generated content.
        
        Here's an example which uses a fibonacci sequence backoff when the
        return value of the target function is the empty list:
        
            @backoff.on_predicate(backoff.fibo, lambda x: x == [], max_value=13)
            def poll_for_messages(queue):
                return queue.get()
        
        Extra keyword arguments are passed when initializing the
        wait_generator, so the max_value param above is used to initialize the
        fibo generator.
        
        When not specified, the predicate param defaults to the falsey test,
        so the above can more concisely be written:
        
            @backoff.on_predicate(backoff.fibo, max_value=13)
            def poll_for_message(queue)
                return queue.get()
        
        More simply, function which continues polling every second until it
        gets a non falsey result could be defined like like this:
        
            @backoff.on_predicate(backoff.constant, interval=1)
            def poll_for_message(queue)
                return queue.get()
        
        ### Using multiple decorators
        
        It can also be useful to combine backoff decorators to define
        different backoff behavior for different cases:
        
            @backoff.on_predicate(backoff.fibo, max_value=13)
            @backoff.on_exception(backoff.expo,
                                  requests.exceptions.HTTPError,
                                  max_tries=4)
            @backoff.on_exception(backoff.expo,
                                  requests.exceptions.TimeoutError,
                                  max_tries=8)
            def poll_for_message(queue):
                return queue.get()
        
        ### Logging configuration
        
        Errors and backoff/retry attempts are logged to the 'backoff' logger.
        By default, this logger is configured with a NullHandler, so there will
        be nothing output unless you configure a handler. Programmatically,
        this might be accomplished with something as simple as:
        
            logging.getLogger('backoff').addHandler(logging.StreamHandler())
        
        The default logging level is ERROR, which correponds to logging anytime
        max_tries is exceeded as well as any time a retryable exception is
        raised. If you would instead like to log any type of retry, you can
        instead set the logger level to INFO:
        
            logging.getLogger('backoff').setLevel(logging.INFO)
        
Keywords: backoff function decorator
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Operating System :: MacOS
Classifier: Operating System :: POSIX
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: Implementation
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Topic :: Internet :: WWW/HTTP
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Utilities
