Metadata-Version: 1.0
Name: pywurfl
Version: 7.2.1
Summary: pywurfl - Python tools for processing and querying the Wireless Universal Resource File (WURFL)
Home-page: http://celljam.net/
Author: Armand Lynch
Author-email: lyncha@users.sourceforge.net
License: LGPL
Description: WURFL and Python
        ================
        
        #### by Armand Lynch (lyncha at users dot sourceforge dot net)
        
        **Please note: As of pywurfl v7.0.0 all textual capabilities (including WURFL
        IDs and user agents) are unicode strings and all textual parameters to the API
        functions should be given as unicode strings.**
        
        [pywurfl][1] is a [Python][3] language package that makes dealing with the
        [WURFL][2] in Python a little easier. It contains tools that allow you to
        retrieve objects that represent devices defined in the WURFL or manipulate the
        WURFL device hierarchy by using a simple set of [API][9] functions or a
        pywurfl specific [query language][4]. Also included within the package is a
        [WURFL processor][5] class that provides an event based API that can be used
        to alleviate some of the work when processing the WURFL sequentially.
        
        License
        -------
        
        pywurfl is Copyright 2004-2011, Armand Lynch (lyncha at users dot sourceforge
        dot net) The code is free software; you can redistribute it and/or modify it
        under the terms of the [LGPL][6] License (see the file LICENSE included with
        the distribution).
        
        Requires
        --------
        
        Python >= 2.6
        
        Required Modules
        ----------------
        
        [Levenshtein Module][7] >= 0.10.1 is required for the user agent similarity
        algorithms.
        
        Optional Modules
        ----------------
        
        [pyparsing][8] >= 1.5 is required if you want to use the pywurfl query language.
        
        Scripts
        -------
        
        The pywurfl package contains a wurfl2python.py script that translates a WURFL
        compatible XML file into a python class hierarchy that the pywurfl API can use
        directly. The default name for the output file is wurfl.py. Type the following
        at the command line to produce it:
        
            python wurfl2python.py wurfl.xml
        
        Patching
        --------
        
        In order to [patch][13] your wurfl.xml file, use the [WURFL XSLT Tools][14].
        Then run wurfl2python on the patched file.
        
        A quick usage example
        ---------------------
        
        After you have created the wurfl.py module, you can use the following code to
        get a device object based on a user agent and print it to stdout.
        
            from wurfl import devices
            from pywurfl.algorithms import TwoStepAnalysis
        
            user_agent = u"Nokia3350/1.0 (05.01)"
            search_algorithm = TwoStepAnalysis(devices)
        
            device = devices.select_ua(user_agent, search=search_algorithm)
        
            # Print out the specialized capabilities for this device.
            print device
        
        That's it.
        
        pywurfl API
        -----------
        
        To get an object that represents a device, you can use one of 2 methods of the
        'devices' object imported from the wurfl.py module.
        
            select_id(unicode, [actual_device_root=False], [instance=True])
        
        This method returns a device object based on the WURFL ID provided.
        
        If `actual_device_root` is `True` then the `select_id` method will return the
        requested device or a device in its fallbacks if it is an actual device.
        
        If instance is `False` then the `select_id` method will return a class object
        instead of an instance.
        
            select_ua(unicode, [actual_device_root=False], [search=False], [instance=True])
        
        This method returns a device object based on the user agent provided.
        
        If `actual_device_root` is `True` then the `select_ua` method will return the
        requested device or a device in its fallbacks if it is an actual device.
        
        The search argument takes an instance of [pywurfl.algorithms.Algorithm][12].
        At this time, only four algorithms are provided: TwoStepAnalysis, Tokenizer,
        Levenshtein distance and JaroWinkler. The TwoStepAnalysis algorithm is the
        default algorithm used in Java and PHP APIs, you can find a description of it
        [here][11]. The other three algorithms are older and probably shouldn't be
        used in new programs. 
        
        If instance is `False` then the `select_ua` method will return a class object
        instead of an instance.
        
        ### More API methods
        
        There are a few more methods that you can use on the 'devices' object to
        manipulate the device class hierarchy itself.
        
            add(parent, devid, devua, [actual_device_root=False], [capabilities=None])
        
            add_capability(group, capability, object)
        
            add_group(group)
        
            insert_after(parent, devid, devua, [actual_device_root=False], [capabilities=None])
        
            insert_before(child, devid, devua, [actual_device_root=False], [capabilities=None])
        
            remove(devid)
        
            remove_capability(capability)
        
            remove_group(group)
        
            remove_tree(devid)
        
        Here's an example
        
            from wurfl import devices
        
            # Add a new device
            devices.add(u'generic',
                        u'teledev1',
                        u'Mozilla/25.0 (X11; U; Linux i686; en-US; rv:25.0.0) Gecko/21000711 Firefox/28.1.5',
                        actual_device_root=True)
        
            # Add a new capability group
            devices.add_group(u'teleporter')
        
            # Add some capabilities to the teleporter group
            devices.add_capability(u'teleporter', u'teleportation_device', False)
            devices.add_capability(u'teleporter', u'distance', 20) # in km
            devices.add_capability(u'teleporter', u'can_recover_from_errors', False)
        
            # Add a new device overriding a default capability value
            # Note that no devices had a 'teleportation_device' attribute until we added it
            devices.add(u'teledev1',
                        u'teledev2',
                        u'Mozilla/25.0 (X11; U; Linux i686; en-US; rv:26.0.0) Gecko/21000712 Firefox/28.1.6',
                        actual_device_root=True,
                        capabilities={u'teleportation_device': True})
        
            # Add another group and capabilities
            devices.add_group(u'python')
            devices.add_capability(u'python', u'py_version', u'2.6')
            devices.add_capability(u'python', u'py_heap_size', 0)
        
            # Remove an unused group
            devices.remove_group(u'j2me')
        
            # Not interested in tiff files
            devices.remove_capability(u'tiff')
        
        Check the [documentation][9] for more information.
        
        Serialization
        -------------
        
        It's also possible to serialize changes that you make to a WURFL compatible
        XML file.
        
            from wurfl import devices
            from pywurfl.serialize import Serialize
        
            # Remove some groups and their capabilities from the WURFL hierarchy
            devices.remove_group(u'j2me')
            devices.remove_group(u'mms')
        
            Serialize(devices).to_xml("no_j2me_or_mms.xml")
        
        Search Algorithm Classes
        ------------------------
        
        The algorithms module contains four algorithm classes (TwoStepAnalysis,
        Tokenizer, JaroWinkler and LevenshteinDistance). When instantiating any of
        these classes, a callable object will be returned that can be used to search a
        'devices' object with the provided user agent.
        
            TwoStepAnalysis(devices, [use_normalized_ua=False])
        
        In order to use the TwoStepAnalysis algorithm, you must initialize it with a
        set of known devices. `use_normalized_ua` determines whether or not the search
        algorithm requires that a normalized user agent be presented to it. The
        TwoStepAnalysis algorithm does its own normalization internally, hence the
        `False` specification here.
        
            Tokenizer([devwindow], [use_normalized_ua=True])
        
        The devwindow argument determines the upper limit of device matches before the
        algorithm would return the generic device.
        
            JaroWinkler([accuracy=1.0], [weight=0.05], [use_normalized_ua=True])
        
        The accuracy argument determines the lower limit at which pywurfl will
        determine if a user agent matches another. If no device can be found that
        scores equal to or greater than accuracy, a generic device is returned. Valid
        values are between 0.0 and 1.0
        
            LevenshteinDistance([use_normalized_ua=True])
        
        The LevenshteinDistance algorithm only has an optional `use_normalized_ua` argument.
        
            from wurfl import devices
            from pywurfl.algorithms import JaroWinkler, Tokenizer, LevenshteinDistance
        
            tsa = TwoStepAnalysis(devices)
            tokenizer = Tokenizer()
            jarow = JaroWinkler()
            levdis = LevenshteinDistance()
        
            user_agent = u"Nokia3350/1.0 (05.01)"
            device1 = jarow(user_agent, devices)
            device2 = tokenizer(user_agent, devices)
            device3 = levdis(user_agent, devices)
        
            device4 = devices.select_ua(user_agent, search=tsa)
            device5 = devices.select_ua(user_agent, search=jarow)
            device6 = devices.select_ua(user_agent, search=tokenizer)
            device7 = devices.select_ua(user_agent, search=levdis)
        
        It's also very easy to define your own algorithm for use in pywurfl in case
        the algorithms provided don't serve your needs. Just subclass the
        pywurfl.algorithms.Algorithm class and follow the protocol.
        
        Device Objects
        --------------
        
        The object returned by either `select_id` or `select_ua` is usually a Device
        instance.
        
            device = devices.select_id(unicode)
        
        A device object has many attributes. The device id, user agent, `fall_back`
        and `actual_device_root` attributes are exposed with the following attributes
        of the device object:
        
            device.devid
            device.devua
            device.fall_back # All devices have a fall_back attribute
            device.actual_device_root
        
        Any capability that is defined in the WURFL becomes an attribute of the device
        object. For example:
        
            device.brand_name
            device.model_name
            device.ringtone
        
        All attributes are converted into their respective Python types. For example:
        
            device.ringtone  # Attribute is boolean
            device.preferred_markup  # Attribute is a unicode string
            device.rows  # Attribute is an integer
        
        You can iterate over a device object to select each capability and its
        corresponding value. For example, to print out all capabilities of a device
        object you can use the code below:
        
            for group, capability, value in device:
                print group, capability, value
        
        Every device has a shared groups attribute which is a Python dictionary where
        the keys are the capability group names as defined in the WURFL and the values
        are lists of the capability names for that specific group.
        
            for group in sorted(device.groups):
                print group
        
        ### Classes and Instances
        
        The API methods can also return a class object instead of an instance. What
        wurfl2python does is produce a module that creates a single inheritance class
        hierarchy of all WURFL devices. You can use this to your advantage if you want
        to change the attributes of a device at run-time and have all of its
        descendants represent that change.
        
            # get an arbitrary device instance
            device = devices.select_id(u'blackberry_generic_ver3_sub2')
        
            # get the generic device *class*
            gen = devices.select_id(u'generic', instance=False)
        
            # modify the generic class
            gen.teleportation_device = False
        
            # since all devices inherit from the generic device, this will not raise
            # an attribute error now
            device.teleportation_device # == False
        
        If you want to maintain the integrity of the class hierarchy, you should use
        the add/remove/insert API methods on the 'devices' object mentioned above.
        
        Query Language
        --------------
        
        The pywurfl package includes a query language that makes it easier to retrieve
        a list of devices, WURFL IDs or user agents based on the capabilities of a
        device. The best way to see what the query language looks like and what it can
        do is with an example.
        
            from wurfl import devices
            from pywurfl.ql import QL  # Import the query function generator
        
            # Retrieve a function that will query the devices object
            query = QL(devices)
        
            # QL also adds a query method to devices (devices.query)
        
            q1 = u"""select id where ringtone=true and rows < 5 and
                     columns > 5 and preferred_markup = 'wml_1_1'"""
        
            for wurfl_id in query(q1):
                print wurfl_id
        
            # Let's look for some nice phones
            q2 = u"""select device where all(ringtone_mp3, ringtone_aac, wallpaper_png,
                     streaming_mp4) = true"""
        
            # Notice that we can also retrieve device classes
            for device in devices.query(q2, instance=False):
                print device.brand_name, device.model_name
        
            # We can also use the methods on the capability types to refine our queries.
            # Note that you should *always* quote the strings that are passed to functions
            # and those that are used in comparisons.
            q3 = u"""select ua where brand_name.lower()='nokia'"""
            for ua in query(q3):
                print ua
        
            q4 = u"""select ua where brand_name.replace('No', 'Si').lower()='sikia'"""
            for ua in query(q4):
                print ua
        
            q5 = u"""select ua where model_name.isdigit()=true and actual_device_root=true"""
            for ua in query(q5):
                print ua
        
            # There are also a couple of regex methods (match and imatch) that were added
            # to the string type to make those kind of queries possible. Use imatch to
            # ignore case.
            q6 = u"""select ua where brand_name.match('^No')=true"""
            for ua in query(q6):
                print ua
        
            # and arbitrary nesting is supported
            q7 = u"""select ua where brand_name.replace('Nokia', brand_name.lower())='nokia'"""
            for ua in query(q7):
                print ua
        
        A full description of the query language is included in the documentation.
        
        The WURFL Processor
        -------------------
        
        The WURFL processor is a general class that walks a WURFL XML file and
        executes hooks as specific events occur in a fashion similar to SAX. The best
        way to understand the WURFL processor is to look at its [documentation][10].
        For an example of how to use use it, look at the source for wurfl2python.py.
        
        Contributors
        ------------
        
        To *Pau Aliagas*, *Gabriele Fantini* and *Michele Bariani*: Thank you for the
        many patches, bug reports and improvements.
        
        Comments and/or suggestions are appreciated.
        
        
        [1]: http://celljam.net/api/index.html "pywurfl"
        [2]: http://wurfl.sourceforge.net/ "WURFL"
        [3]: http://www.python.org/ "Python"
        [4]: http://celljam.net/#query "Query Language"
        [5]: http://celljam.net/#processor "WURFL processor"
        [6]: http://www.opensource.org/licenses/lgpl-license.php "LGPL"
        [7]: http://pypi.python.org/pypi/python-Levenshtein/0.10.2 "Levenshtein Module"
        [8]: http://pyparsing.wikispaces.com/ "pyparsing"
        [9]: http://celljam.net/api/index.html "API documentation"
        [10]: http://celljam.net/api/pywurfl.wurflprocessor-module.html "WURFL processor documentation"
        [11]: http://wurfl.sourceforge.net/newapi/ "TwoStepAnalysis description"
        [12]: http://celljam.net/api/pywurfl.algorithms.Algorithm-class.html "Algorithm class API documentation"
        [13]: http://wurfl.sourceforge.net/patchfile.php "What is a patch file"
        [14]: http://wurfl.sourceforge.net/xslt/index.php "WURFL XSLT Tools"
        
Platform: All
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Console
Classifier: Environment :: Web Environment
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Telecommunications Industry
Classifier: License :: OSI Approved :: GNU Library or Lesser General Public License (LGPL)
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Topic :: Database :: Front-Ends
Classifier: Topic :: Internet :: WAP
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Utilities
