import tornado.ioloop
import tornado.web
import json
import argparse
import memcache
from allergy_assassin import settings, search, dish, allergies, logger
from allergy_assassin.logger import log_request
logger = logger.init("allergy_assassin.api.handler")
def get_argument(request, argument_name):
"""Fetch argument from request.arguments"""
arg_list = request.arguments.get(argument_name, [None])
return arg_list[-1]
def cache(responder):
"""
Decorator for responders making use of cache
"""
cache = memcache.Client(settings.MEMCACHED_SERVERS)
def wrapped(handler):
cache_key = handler.request.uri
cache_item = cache.get(cache_key)
if cache_item is None:
cache_item = responder(handler)
cache.set(cache_key, cache_item, time=settings.CACHE_TIME)
else:
logger.info("Using cache for '%s' query" % cache_key)
return cache_item
"""
This file maps abstract allergies (which don't by name refer to a concrete
ingredient, to a set of concrete ingredients.
The fixtures in this file are also used to generate the allergies
autocompletion list, which explains the 1->1 mappings also listed here.
"""
from allergy_assassin import db, logger
import re
logger = logger.init("allergy_assassin.allergies")
fixtures = [
(('peanut',), ('peanut')),
(('nut',), ('peanut', 'hazelnut', 'cashew nut', 'brazil nut',
'almond', 'walnut', 'pecan', 'pistachio')),
(('shellfish',), ('prawn', 'clam', 'oyster', 'crab', 'lobster',
'crayfish', 'mussel', 'winkle', 'scallop',
'shrimp')),
(('seafood',), ('prawn', 'clam', 'oyster', 'crab', 'lobster',
'crayfish', 'mussel', 'winkle', 'scallop',
'shrimp', 'squid', 'calamari', 'octopus',
'fish', 'cod', 'scampi', 'haddock', 'mackerel'
'tuna', 'sardine', 'anchovy')),
(('dairy',), ('milk', 'yoghurt', 'cheese', 'cream', 'butter')),
(('egg',), ('egg')),
(('lime',), ('lime')),
(('kidney bean',), ('kidney bean')),
(('gluten','wheat'), ('bread', 'flour', 'pasta')),
(('barley',), ('barley')),
from bson import Code, SON
from allergy_assassin import settings, logger
from allergy_assassin.db import requests
logger = logger.init("allergy_assassin.metrics.users_per_day")
m = Code(
"""function () {
var rd = this.request.request_time;
if (typeof rd == 'object') {
var date = rd.toISOString().split('T')[0];
emit(date, 1);
}
};"""
)
r = Code(
"""function (key, values) {
return Array.sum(values);
};"""
)
def generate():
logger.debug("Beginning dish users per day mapreduce job")
requests.map_reduce(m, r, out=SON([("replace", settings.USERS_PER_DAY_COLLECTION), ("db", settings.METRICS_DB)]))
logger.debug("Mapreduce query completed")
if __name__ == "__main__":
generate()
from bson.code import Code
from allergy_assassin import db, settings, logger, allergies
logger = logger.init("allergy_assassin.search")
class AllergenPresenceSearch:
def __init__(self, allergens, terms):
self.abstract_allergens = allergens
self.terms = terms
self.allergens = allergies.get_real_allergens(allergens)
self._validate_search()
def _validate_search(self):
self.terms = self.terms.strip()
self.allergens = [allergen.strip() for allergen in self.allergens]
def search(self):
self.results = []
for allergen in self.allergens:
# query
spec = self._get_query_spec()
matching_recipes = self._query_recipes(spec)
full_count = matching_recipes.count()
allergen_presence = self._query_allergen_presence(matching_recipes, allergen)
allergen_presence_count = allergen_presence.count()
logger.info("%d results of %d containing allergen '%s'" %
(allergen_presence_count, full_count, allergen))
result = AllergenPresenceResult(allergen,
from bson import Code
from allergy_assassin import settings, logger
from allergy_assassin.db import recipes, dish
logger = logger.init("allergy_assassin.dish.autocomplete")
m = Code("""function () {
emit(this.recipe_name, {sources: [this.source], source_count: 1});
};""")
r = Code("""function (key, values) {
var result = { 'sources': [], source_count: 0};
values.forEach(function(value) {
value.sources.forEach(function(source) {
if ( result.sources.indexOf(source) == -1 ) {
//if value not in result
result.sources.push(source);
result.source_count++;
}
});
});
return result;
};""")
def generate():
logger.debug("Beginning dish autocompletion list mapreduce job")
results = recipes.map_reduce(m, r, out={'replace': dish.name})
logger.debug("Mapreduce query completed, removing items below threshold...")
dish.remove({'value.source_count': {'$lt': settings.DISH_AUTOCOMPLETION_MIN_SOURCES}}, safe=True)
