Francesco, MaxMind(R) produces commercial and free IP geolocation datasets. As a proof of concept I created GeoDjango-enabled models and import scripts for their CSV files:
http://www.djangosnippets.org/snippets/327/ http://www.djangosnippets.org/snippets/328/ To create this code I had to patch Django since it lacks large integer support; specifically, IP address queries require conversion to a long integer. I used Peter Nixon's latest patch to get BigIntegerField: http://code.djangoproject.com/attachment/ticket/399/django-bigint-20070712.patch I'm not sure about the utility of including it in GeoDjango. The large database size (3 million rows for LocationBlock), makes queries slower -- however, there are much fewer CountryBlock rows. I will try out their C API and compare. This may be useful for some research purposes (e.g. how many IP allocations within a political boundary, etc.). Example: >>> from geoip.models import LocationBlock, CountryBlock >>> lb = LocationBlock.objects.ipquery('72.14.207.99') >>> print unicode(lb.location) Location 2633: United States - CA, Mountain View 94043 >>> print lb.location.point POINT (-122.0574000000000012 37.4191999999999965) >>> cb = CountryBlock.objects.ipquery('66.64.46.23') >>> print unicode(cb.location) United States: 66.60.64.0 to 66.70.70.109 -Justin --~--~---------~--~----~------------~-------~--~----~ You received this message because you are subscribed to the Google Groups "Django users" group. To post to this group, send email to django-users@googlegroups.com To unsubscribe from this group, send email to [EMAIL PROTECTED] For more options, visit this group at http://groups.google.com/group/django-users?hl=en -~----------~----~----~----~------~----~------~--~---
