Mobile.sniffer is a project mainly written in Python, it's free.
mobile.sniffer is Python framework for abstracting mobile handset detection and feature database access.
When rendering web pages for mobile phones one must deal with varying handset features: different screen sizes and shapes, different supported file formats, different sets of web browser features. Also, the fact that you know the user is browsing on a mobile phone is most critical for building successful mobile web user experience.
mobile.sniffer provides two phase mobile phone detection (a.k.a sniffing)
mobile detection - this simply detects whether a browser is a mobile phone based or not.
This is done in mobile/sniffer/detect.py module. This is useful to redirect to your
visitors from a web site to a mobile site if they are using a mobile phone to arrive on your web site.
mobile handset feature extraction - the handset database is looked for a mobile web browser user agent match. Since there might be version changes, local varieties, etc. in user agent strings, heurestics are applied to the string matching. If a database entry is found, with certain match accuracy, it's records like device screen width and height are made available to the web server so that it can tailor HTML, image and video output suitable for this particular mobile phone.
Mobile detection can be done with a fast regular expression match. Mobile handset feature extraction always requires a some sort of database of mobile phone entries and mobile.sniffer framework provides abstraction of these databases.
Easily plug-in mobile redirects to your Python based web sites
Able to source data from multiple sniffing backends leading better handset coverage
Automatically download, parse and cache complex RDF based WAP profiles
Very convenient Python API designed by professionals
Open source
Unit test coverage
The code is Django, WSGI and Zope/Plone compatible.
Wurfl <http://wurfl.sourceforge.net/>_
ApexVertex. Commercially available from mFabrik <http://mfabrik.com>_.
DeviceAtlas. Commercially available.
WAP profiles. User agents post a link to their WAP profile data, which is an XML file and maintained by the handset manufacturer. (note: as WAP is deprecating protocol these are not supported on newer smartphones)
mobile.sniffer is distributed as Python egg in PyPi repository.
The usual method to install Python eggs is easy_install command.
Simple (Unix version)::
sudo easy_install mobile.sniffer.. note::
Python package comes with a copy of Wurfl database which dates around the release.
You might want to update this.You might need to install additional libraries depending on what handset database you use
Wurfl: pywurlf library <http://wurfl.sourceforge.net/python/index.php> and
python-Levenshtein <http://pypi.python.org/pypi/python-Levenshtein/>
WAP profiles: Django (for database abstraction) and rdflib
Apex Vertex: Django (for database abstraction)
There is no single standard to name properties queried from the handset database. For legacy reasons, we use DeviceAtlas database column names (keys) and then map them to database-dependent keys.
detect_mobile_browser(user_agent) will return True of False
whether the HTTP request was made by a mobile phone.
Example::
from mobile.sniffer.detect import detect_mobile_browser
from mobile.sniffer.utilities import get_user_agent
# Get HTTP_USER_AGENT from HTTP request object
ua = get_user_agent(self.request)
if ua:
# Apply reg
if detect_mobile_browser(ua):
# Redirect the visitor from a web site to a mobile site
pass
else:
# A regular web site visitor
pass
else:
# User agent header is missing from HTTP request
return FalseThis example will work out of the box with the included pywurlf database.
Example::
try:
from mobile.sniffer.wurlf.sniffer import WurlfSniffer
# Wrapper sniffer instance
# All start-up delay goes on this line
sniffer = WurlfSniffer()
except ImportError, e:
import traceback
traceback.print_exc()
logger.exception(e)
logger.error("Could not import Wurlf sniffer... add pywurfl and python-Lehvenstein to buildout.cfg eggs section")
sniffer = None
def sniff_request(request):
"""
@param request: Request can be Django, WSGI or Zope HTTPRequest object
"""
if not sniffer:
# We failed to initialize Wurfl
return None
user_agent = sniffer.sniff(request)
if user_agent == None:
# No match in the handset database,
return None
else:
return user_agent # mobile.sniffer.wurlf.sniffer.UserAgent object
def web_or_mobile(request)
ua = sniff_request(request)
# How certain we must be about UA
# match to make decisions
# float 0...1, the actual value is UA search algorithm specific
# We use JaroWinkler as the default algorithm
certainty_threshold = 0.7
if ua.get("is_wireless_device") and ua.getCertainty() > certainty_threshold:
# Mobile code
pass
else:
# Webby code
passSince Wurfl is the default backend the process of finding UA record is explained more carefully
Wurlf database is usually loaded during the start-up (slow operation) - it is possible to make this to use lazy initialization pattern
The search algorithm is initialized with certain match threshold - all matches below this threshold will be ignored. The default search algorithm is JaroWinkler from Lehvenstein Python package.
When the user agent is searched
* Take in HTTP request User-Agent header
* Go through all entries in database
* Match this entry against incoming User-Agent using the search algorithm
* First search pass is doing using exact string matches (no algorithm involved). In this
case exposed certainty will be 1.1.
* If there was no match in the first pass, do the second pass using the search algorithm
* If match is found and threshold is exceed return this user agent record
* User agent record is retrofitted with the information how accurate the match was
(ua.getCertainty() method exposes this)Use all available handset information sources to accurately get device data. Matching is done on property level - if one data source lacks the property information the next data source is tried. Finally if the handset is unknown, but it publishes WAP profile information, the profile is downloaded and analyzed and saved for further requests.
Example::
from mobile.sniffer.chain import ChainedSniffer
from mobile.sniffer.apexvertex.sniffer import ApexVertexSniffer
from mobile.sniffer.wapprofile.sniffer import WAPProfileSniffer
from mobile.sniffer.deviceatlas.sniffer import DeviceAtlasSniffer
# Create all supported sniffers
da = DeviceAtlasSniffer(da_api_file)
apex = ApexVertexSniffer()
wap = WAPProfileSniffer()
# Preferred order of sniffers
sniffer = ChainedSniffer([apex, da, wap])
ua = sniffer.sniff(request) # Sniff HTTP_USER_AGENT, HTTP_PROFILE and many other fields
property = ua.get("usableDisplayWidth") # This will look up data from all the databases in the chainProprietary handset databases do not publicly distribute their APIs or data. mobile.sniffer deals with the problem by automatic installation wrappers. Also, these handset database APIs are not open source compatible which makes it further difficult to use them in open source projects. Instead of manually download and set up bunch of files each time you deploy your code on a new server, just make call to one magical Python function which will take care of all of this for you.
Source code is available via Google Code.
This software is still in much development and aimed for advanced Python developers only.
mFabrik Research Oy <mailto:[email protected]>_ - Python and Plone professionals for hire.
mFabrik web site <http://mfabrik.com>_
mFabrik mobile site <http://mfabrik.mobi>_
Blog <http://blog.mfabrik.com>_
About Plone CMS <http://mfabrik.com/technology/technologies/content-management-cms/plone>_