def manualNutrientQuery(ingredientName, ingredientId):
filePath = os.path.join(c.PATH_TO_RESOURCES, "manualNutrientQuery.json")
manualDict = {}
getRequest = getNutritionalRequest(ingredientId)
if getRequest is not None:
requestAsJson = json.loads(getRequest.content)
requestAsFormattedDict = nutrientDictFromJSON(requestAsJson)
manualDict[ingredientName] = requestAsFormattedDict
util.dumpJSONDict(filePath, manualDict)
def main(argv):
fileName = filter(lambda s: "file=" in s, argv)[0]
fileName = fileName.split("=")[-1]
filePath = os.path.join(c.PATH_TO_ROOT, fileName.lstrip("/"))
lines = None
with open(filePath, 'r') as f:
lines = f.read().split("\n")
lines = filter(lambda s: s.strip() != "", lines)
lineDict = {"list": lines}
jsonFileName = filePath.split("/")[-1]
jsonFileName = ".".join(jsonFileName.split(".")[:-1]) + ".json"
jsonFilePath = os.path.join(os.path.dirname(filePath), jsonFileName)
util.dumpJSONDict(jsonFilePath, lineDict)
def main(argv):
pathToRecipes = os.path.join(c.PATH_TO_RESOURCES, "jsonrecipes")
# Get the full absolute file paths of all files in /res/jsonrecipes/
# that end in ".json"
jsonRecipes = util.listFilesWithSuffix(pathToRecipes, ".json")
# Load all of these ".json" files into dictionaries and put all
# these dictionaries in a list
listOfJSONDicts = util.loadJSONDicts(jsonRecipes)
# Merge recipes into one dictionary, deleting duplicates
mergedDict = util.naivelyMergeDicts(listOfJSONDicts)
# Write the merged recipe dictionary to a file
allRecipesFilePath = os.path.join(c.PATH_TO_RESOURCES, "allRecipes.json")
util.dumpJSONDict(allRecipesFilePath, mergedDict)
def main(argv):
fileName = filter(lambda s: "file=" in s, argv)[0]
fileName = fileName.split("=")[-1]
filePath = os.path.join(c.PATH_TO_ROOT, fileName.lstrip("/"))
lines = None
with open(filePath, "r") as f:
lines = f.read().split("\n")
lines = filter(lambda s: s.strip() != "", lines)
lineDict = {"list": lines}
jsonFileName = filePath.split("/")[-1]
jsonFileName = ".".join(jsonFileName.split(".")[:-1]) + ".json"
jsonFilePath = os.path.join(os.path.dirname(filePath), jsonFileName)
util.dumpJSONDict(jsonFilePath, lineDict)
def main(argv): print "Merging nutrient IDs" pathToNutrients = os.path.join(c.PATH_TO_RESOURCES, "nutrients", "foundingredients") # Get the full absolute file paths of all files in /res/nutrients/foundingredients # that end in ".json" jsonNutrients = util.listFilesWithSuffix(pathToNutrients, ".json") # Load all of these ".json" files into dictionaries and put all # these dictionaries in a list listOfJSONDicts = util.loadJSONDicts(jsonNutrients) # Merge Nutrients into one dictionary, deleting duplicates mergedDict = util.naivelyMergeDicts(listOfJSONDicts) # Write the merged recipe dictionary to a file nutrientIDsFilePath = os.path.join(c.PATH_TO_RESOURCES, "allNutrientIDs.json") util.dumpJSONDict(nutrientIDsFilePath, mergedDict)
def printClusters(clusterToData, clusterStats, est, dataType, featureList): dict2dump = copy.deepcopy(clusterToData) numtypeFeatures = getListIntersections(featureList, c.KMEANS_NUM_FEATURES) for cluster, recipeList in clusterToData.iteritems(): print 10 * '-' + cluster + ' '+ 10 * '-' clusterData = clusterStats[cluster] for f, v in clusterData.iteritems(): if f in numtypeFeatures or isIngredientContraint(f): if f == c.KMEANS_FEATURE_TOTALTIME: v /= TOTAL_TIME_ADJUSTMENT if f == c.KMEANS_FEATURE_NUM_INGREDIENTS: v /= NUM_INGREDIENT_ADJUSTMENT dict2dump[cluster + ' ' + f + ' average score'] = v print "The cluster's %s average score was: %f" % (f, v) else: dict2dump[cluster + ' ' + f + ' distribution'] = v print "The cluster's %s distribution was: " % f for name, prob in v.iteritems(): print " %s: %f%%" % (name, prob) print for recipe in recipeList: print recipe print dict2dump['command-line'] = COMMAND_LINE tempFilename = dataType + '-cluster-' for f in featureList: tempFilename = tempFilename + f + '&' if tempFilename[-1] == '&': tempFilename = tempFilename[:-1] toFilename = util.string_appendDateAndTime(tempFilename) if dataType == c.KMEANS_RECIPE_DATATYPE: jsonToFilePath = os.path.join(c.PATH_TO_ROOT, "res/kmeans-results/recipe", toFilename) if dataType == c.KMEANS_ALIAS_DATATYPE: jsonToFilePath = os.path.join(c.PATH_TO_ROOT, "res/kmeans-results/alias", toFilename) util.dumpJSONDict(jsonToFilePath, dict2dump) print 'Clustering dumped into: ' + jsonToFilePath
def main(argv):
print "Merging nutrient data"
pathToNutrients = os.path.join(c.PATH_TO_RESOURCES, "nutrients", "nutrientdata")
# Get the full absolute file paths of all files in /res/nutrients/foundingredients
# that end in ".json"
jsonNutrients = util.listFilesWithSuffix(pathToNutrients, ".json")
# Load all of these ".json" files into dictionaries and put all
# these dictionaries in a list
listOfJSONDicts = util.loadJSONDicts(jsonNutrients)
# Merge Nutrients into one dictionary, deleting duplicates
mergedDict = util.naivelyMergeDicts(listOfJSONDicts)
# Write the merged recipe dictionary to a file
nutrientIDsFilePath = os.path.join(c.PATH_TO_RESOURCES, "allNutrientData.json")
util.dumpJSONDict(nutrientIDsFilePath, mergedDict)
#This will prepare the json file of valid ingredients
validIngredientDict = {}
validNutrientDict = {}
for ingredient in mergedDict:
#print ingredient.encode('ascii', errors='ignore')
validIngredientDict[ingredient] = 0
for nutrient in mergedDict[ingredient]['nutrients']:
validNutrientDict[nutrient] = 0
print "There are " + str(len(validIngredientDict)) + " valid ingredients."
print "There are " + str(len(validNutrientDict)) + " valid nutrients."
validIngredientsFilePath = os.path.join(c.PATH_TO_RESOURCES, "validIngredients.json")
validNutrientFilePath = os.path.join(c.PATH_TO_RESOURCES, "validNutrients.json")
util.dumpJSONDict(validIngredientsFilePath, validIngredientDict)
util.dumpJSONDict(validNutrientFilePath, validNutrientDict)
def dumpAliasDataToJSONFiles(aliasData):
dataFileName = util.string_appendDateAndTime("aliasData")
dataFilePath = os.path.join(c.PATH_TO_RESOURCES, "aliasdata", dataFileName)
util.dumpJSONDict(dataFilePath, aliasData)
def main(argv):
global ingredientMassDict
global validAliasDict
global unitCountDict
validIngredientsFilePath = os.path.join(c.PATH_TO_RESOURCES, "validIngredients.json")
validAliasDict = util.loadJSONDict(validIngredientsFilePath)
conversionDict = util.createWaterConversionDict()
allRecipes = []
# Each alias has 3 main fields:
# "count"
# "aliasBuddies"
# "lines"
aliasData = {}
ingredientLineDict = {}
#ingredientMassDict = {}
#unitCountDict = {}
# Read in and parse recipe data structures (dictionaries) from a json file.
extractRecipesFromJSON(allRecipes)
# Convert all string data to lowercase.
lowerAllStrings(allRecipes)
#ndb = ndb.NutrientDatabase()
#Let's f**k around.
unmatched = float(0)
tried = float(0)
for recipe in allRecipes:
# print "Ingredient Lines: " + str(len(recipe['ingredientLines']))
# print recipe['ingredientLines']
# print "\nIngredients: " + str(len(recipe['ingredients']))
# print recipe['ingredients']
for ingredientLineIndex in range(0, len(recipe['ingredientLines'])):
if ingredientLineIndex == len(recipe['ingredients']):
break
ingredientLine = recipe['ingredientLines'][ingredientLineIndex].encode('ascii', errors='ignore')
ingredient = recipe['ingredients'][ingredientLineIndex].encode('ascii', errors='ignore')
if ingredient not in validAliasDict:
continue
if ingredient not in ingredientLineDict:
ingredientLineDict[ingredient] = []
ingredientLineDict[ingredient].append(ingredientLine)
#print ingredientLineDict
for ingredient in ingredientLineDict:
for ingredientLine in ingredientLineDict[ingredient]:
#TIME TO PARSE.
words = ingredientLine.split()
potentialStart = removeHyphen(words[0])
#If the first token is a number, try the next few.
if isPossibleAmount(words[0]):
if '/' in potentialStart:
tokens = potentialStart.split('/')
first = float(tokens[0])
second = float(tokens[1])
potentialStart = first/second
amount = float(potentialStart)
potentialUnit, foundUnit = extractUnit(words, ingredient, conversionDict)
if potentialUnit != None:
#Add both the mass and the unit count
if foundUnit:
massInGrams = amount*ndb.getConversionFactor(ingredient, potentialUnit)
else:
massInGrams = amount*conversionDict[potentialUnit]
if ingredient not in ingredientMassDict:
ingredientMassDict[ingredient] = []
ingredientMassDict[ingredient].append(massInGrams)
if ingredient not in unitCountDict:
unitCountDict[ingredient] = Counter()
unitCountDict[ingredient][potentialUnit] += 1
#print "Amount: " + str(amount) + " Unit: " + potentialUnit
else:
unmatched += 1
#print "Couldn't match unit for ingredient: " + ingredient
#print words
#print
elif not hasAnAmount(words):
if ingredient not in unitCountDict:
unitCountDict[ingredient] = Counter()
unitCountDict[ingredient]['unitless'] += 1
tried += 1
print "Missed amounts for " + str(unmatched) + " / " + str(tried) + " ingredients."
print str((tried-unmatched)/tried*100) + "% Success rate!"
# Get the counts of ingredient short names.
# Create a dictionary storing relationships between the various aliases.
# Create a dictionary with aliases as keys and lists of lines they've been
# associated with as values.
fillAliasData(allRecipes, aliasData)
#Temporarily removed to test.
dumpAliasDataToJSONFiles(aliasData)
#Now create small files
smallAliasData = {}
for _ in range(250):
item = aliasData.popitem()
smallAliasData[item[0]] = item[1]
smallFilePath = os.path.join(c.PATH_TO_RESOURCES, "aliasData_small.json")
util.dumpJSONDict(smallFilePath, smallAliasData)
for _ in range(250):
item = aliasData.popitem()
smallAliasData[item[0]] = item[1]
mediumFilePath = os.path.join(c.PATH_TO_RESOURCES, "aliasData_medium.json")
util.dumpJSONDict(mediumFilePath, smallAliasData)
for _ in range(500):
item = aliasData.popitem()
smallAliasData[item[0]] = item[1]
largeFilePath = os.path.join(c.PATH_TO_RESOURCES, "aliasData_large.json")
util.dumpJSONDict(largeFilePath, smallAliasData)
def writeSegmentedJSONFile(dictionaryToDump, baseFilename, segmentIndex): # Dumps and prints out a .JSON file for every YUM_STEP recipes retrieved. # jsonToWrite = json.dumps(dictionaryToDump, sort_keys=True, indent=4) #Filename is /res/jsonrecipes/jsonrecipe_index, where index is startIndex/100. targetFileName = baseFilename + "_" + str(segmentIndex) + ".json" util.dumpJSONDict(targetFileName, dictionaryToDump)
