Where am I? Django & Location Services

Slides from my talk at JSPyConf in Istanbul. I talked about Django and different location database and search solutions you can use with it, as well as some visualization and mapping options.

Style and colour theme was totally ripped off from Chris Coyier's (http://chriscoyier.net) excellent slide deck designs with his gracious approval.

Transcript

1. Where am I? Django & Location Services
2. Taylan Pinçe @taylanpince Tech Lead @
3. APIs & Web Services
4. APPS!
5. Django + Location 1 2 3 4 Technologies Storing Data Searching Visualizing
6. Technologies 1 2 3 geodjango mongoDB elasticsearch
8. geodjango 1 2 3 Easy installation Integrated with Django Support: GEOS & GDAL 4 Low performance!
9. geodjango How to install? sudo apt-get install libgdal1-1.7.0 postgresql-9.1-postgis postgresql-server-dev-9.1 proj That’s it!
10. geodjango Model Integration from django.db import models from django.contrib.gis.db import models class Restaurant(models.Model): location = models.PointField() objects = models.GeoManager()
11. geodjango from django.contrib.gis.measure import D Restaurant.objects.filter( location__distance_lte=( point, D(m=radius) ) ).distance(point)
12. Where did that point come from?
13. geodjango GEOS Geometry Engine Open Source
14. geodjango GEOS from django.contrib.gis.geos import GEOSGeometry, Point point = GEOSGeometry(“POINT(20.391 46.556)”) point = Point(20.391, 46.556)
15. geodjango GEOS Point LineString Polygon
16. If all you have is a hammer, everything looks like a nail. - Abraham Maslow
17. geodjango 1 2 3 Good for complex data Not performance oriented 95% simple data is OK 4 Simple queries are enough
19. mongoDB 1 2 3 Hard to install & deploy Only simple queries Good performance
20. mongoDB is web scale ha ha
21. “It is, if you set it up properly.”
22. mongoDB app server app server mongoDB config mongoDB config mongoDB config mongoDB shard mongoDB replica mongoDB shard mongoDB replica mongoDB shard mongoDB replica Simple Production Deployment
23. mongoDB Data Insertion with PyMongo db.restaurants.insert({ “name”: “Mano Burger”, “location”: { “lat”: 41.029, “lng”: 28.974 } })
24. mongoDB Search with PyMongo db.restaurants.ensureIndex({ “location”: “2d” }) db.restaurants.find({ “location”: { “$within”: { “$centerSphere”: { [[lat, lng], radius], }}}})
25. mongoDB 1 2 3 Limited to simple data Only simple search queries High performance 4 Easy to scale
27. elasticsearch 1 2 3 Easy installation Simple search queries Amazing performance 4 Not a database
28. elasticsearch Installation * openjdk-6-jre-headless * elasticsearch * elasticsearch-servicewrapper sudo elasticsearch install sudo elasticsearch start pip install haystack
29. elasticsearch Haystack Integration from haystack import indexes class RestaurantIndex( indexes.SearchIndex, indexes.Indexable): location = indexes.LocationField( model_attr="location" )
30. elasticsearch Haystack Search from haystack.query import SearchQuerySet SearchQuerySet().dwithin( “location”, Point(longitude, latitude), D(m=radius) )
32. elasticsearch app server app server elastic search elastic search elastic search Simple Production Deployment Can detect other instances automatically!
33. elasticsearch 1 2 3 AWS focused deployment haystack Integration Excellent performance 4 Scaling is super easy
34. Visualization 1 2 3 Google Maps Open Layers MapBox
35. Google Maps
36. Open Layers
37. MapBox
38. Where am I? Demo
39. Q&A
40. hipo.biz @hipolabs
41. Thank you! @taylanpince