def recurseSearch(parentNode, principal, comparables, limit, comparableCount):
''' Recursively creates a network of comparable real estate.
Height of the tree = limit. Number of leaf nodes = comparableCount ** (limit - 1) '''
print("Height Level: {}".format(limit))
if limit == 1:
return True
else:
for comp in comparables:
compObj = Property(comp['zpid'],
comp['links'],
comp['address'],
comp['zestimate'],
comp['localRealEstate'],
principal=principal)
tempParent = Node(compObj.zpid, parent=parentNode)
tempPrinciple, tempComparables = compObj.searchComparables(
comparableCount)
recurseSearch(tempParent, tempPrinciple, tempComparables,
limit - 1, comparableCount)
contentDict = xmltodict.parse(response.content)
parentNode = contentDict['Comps:comps']['response']['properties']['principal']
# Comparables are a list of dictionaries
comparables = contentDict['Comps:comps']['response']['properties']['comparables']['comp']
for comp in comparables:
print(comp['@score'], comp['localRealEstate'])
return contentDict
'''
initialNode = searchProperty()
initialProperty = Property(initialNode['zpid'], initialNode['links'],
initialNode['address'], initialNode['zestimate'],
initialNode['localRealEstate'])
first = Node(initialProperty.zpid)
principal, comparables = initialProperty.searchComparables()
# Creating Property objects from list of comparables
levelCount = 0
# {"Tree-Height": parentNode}
NodeDict = {str(levelCount): first}
def recurseSearch(parentNode, principal, comparables, limit, comparableCount):
''' Recursively creates a network of comparable real estate.
Height of the tree = limit. Number of leaf nodes = comparableCount ** (limit - 1) '''
print("Height Level: {}".format(limit))
if limit == 1:
return True
else:
for comp in comparables:
