def setUp(self):
self.app = create_app('testing')
self.app_context = self.app.app_context()
self.app_context.push()
self.client = self.app.test_client()
# An inverted index, mapping UTM (Universal Transverse Mercator) lat/lng
# values geolocating each film, to a LIST of films that were filmed
# at that location.
#
# IMPORTANT!: This is a shared data-structure, built only at startup,
# that is READ-ONLY by all, and so can be safely shared.
invertedPointLocationIndex = InvertedPointLocationIndex()
invertedPointLocationIndex.build_inverted_location_index()
# A KD tree, implemented using the scipy package's kdtree implementation
# under the hood, to allow for fast O(ln) queries of 2D point data. The
# points that it stores are geocoded locations coded in UTM to allow them
# to be treated as 2D points to an approximation.
#
# IMPORTANT!: This is a shared data-structure, built only at startup,
# that is READ-ONLY by all, and so can be safely shared.
filmLocationsKDTree = LocationsKDTree()
filmLocationsKDTree.load_point_data()
filmLocationsKDTree.build_kd_tree()
self.app_context.g.filmlocationsKDTree = filmLocationsKDTree
self.app_context.g.invertedPointLocationIndex = invertedPointLocationIndex
# at that location.
#
# IMPORTANT!: This is a shared data-structure, built only at startup,
# that is READ-ONLY by all, and so can be safely shared.
invertedPointLocationIndex = InvertedPointLocationIndex()
invertedPointLocationIndex.build_inverted_location_index()
# A KD tree, implemented using the scipy package's kdtree implementation
# under the hood, to allow for fast O(ln) queries of 2D point data. The
# points that it stores are geocoded locations coded in UTM to allow them
# to be treated as 2D points to an approximation.
#
# IMPORTANT!: This is a shared data-structure, built only at startup,
# that is READ-ONLY by all, and so can be safely shared.
filmLocationsKDTree = LocationsKDTree()
filmLocationsKDTree.load_point_data()
filmLocationsKDTree.build_kd_tree()
# If the request is for the endpoint 'films_near_me,' which is seeking
# the 7 films closest to a user's location, only then do we bother to
# load the request with the globally existing KD tree and inverted
# index.
@app.before_request
def before_request():
print "before request ..."
if request.endpoint == 'films_near_me':
g.filmlocationsKDTree = filmLocationsKDTree
g.invertedPointLocationIndex = invertedPointLocationIndex
def make_shell_context():
return dict(app=app)
