def test_clean(self):
""" Tests cleaning the database of comments and emotions """
bat = queries.find_media_by_asin('0440419395')
queries.insert_comment(bat.media_id, 11, 7, 0.9, 0.4, -0.5, 0.6, 0.3)
queries.clean_media(bat.media_id)
comments = queries.find_comments_for_media(bat.media_id)
emotions = queries.find_emotions_for_media(bat.media_id)
self.assertEqual(len(comments), 0)
self.assertEqual(len(emotions), 0)
def handleReview(asin, list_of_review_dicts, productapi, producttype):
global i
product_dict = dict()
product_dict["comments"] = list()
try:
product_dict = add_amazon_info_to_dict(asin, product_dict)
except AmazonInfoNotFoundError:
print("Couldn't find amazon info for product", i, " skipping")
return
# add the ASIN to the dict
product_dict["asin"] = asin
product_dict["type"] = producttype
product = queries.find_media_by_asin(asin)
if product is None:
queries.insert_media(product_dict["title"], product_dict["creator"], product_dict["description"], producttype, asin, int(time.time()))
else:
queries.clean_media(product.media_id)
queries.update_media(product.media_id, int(time.time()))
for review in list_of_review_dicts:
comment_dict = dict()
# if these dont exist in some of them, then so help me god
comment_dict["rating"] = review["overall"]
comment_dict["helpful"] = review["helpful"]
comment_dict["unixtime"] = int(review["unixReviewTime"])
comment_dict["text"] = review["reviewText"]
product_dict["comments"].append(comment_dict)
# now process this dict in comment_processing
filename = product_dict["title"] + "$$$" + asin
processed_dict_dict = dict()
try:
processed_dict = calculateVectorsForAllComments(product_dict, g)
except NoEmotionsFoundError:
# REMOVE the media from the table since we don't want it anymore
queries.remove_media(asin)
print("couldnt find any emotions for product: ", i, "Skipping")
return
#create the summary
processed_dict["summary"] = html.unescape(return_summary(processed_dict))
processed_json = json.dumps(processed_dict, indent=4)
print ("Adding product with asin: ", asin, "to S3 ---", i)
push_to_S3(filename, processed_json)