def setTModel(mtype):
(reviews, names) = data.getTrainData()
dataset = pandas.DataFrame(data = reviews, columns=names)
print ("num train samples " + str(dataset.shape))
# first column of dataset contains ids
# the next 10 columns contain the feature vector
array=dataset.values
I = array[:,0]
# in a supervised model the 2nd column is the expected result, else,
# column where the result will be populated
R = array[:,1]
X = array[:,2:]
validation_size = 0.20
seed = 7
X_train, X_validation, Y_train, Y_validation = \
cross_validation.train_test_split(X, R, test_size=validation_size,
random_state=seed)
num_folds = 10
num_instances = len(X_train)
scoring = 'accuracy'
if (mtype == 1): # do unsupervised Kmeans
tmodel = KMeans(n_clusters = 2, random_state = 0).fit(X)
data.updateResult(list(zip(tmodel.labels_, I)))
data.commit()
elif (mtype == 3): # supervised NB
tmodel = GaussianNB()
tmodel.fit(X_train, Y_train)
else:
tmodel = ()
return tmodel
def create_product():
if not request.get_json(force=True) or not 'asin' in request.get_json(force=True):
abort(400)
prod_id = request.get_json(force=True)['asin']
cat_id = request.get_json(force=True)['cid']
pname = request.get_json(force=True)['title']
url = request.get_json(force=True)['imurl']
price = request.get_json(force=True)['price']
rank = request.get_json(force=True)['rank']
if len(prod_id) == 0:
abort(404)
# need to check if product is in the product table, if not create it, else throw error
if data.existProduct(prod_id):
abort(405)
product = {'pid': prod_id, 'cid': cat_id, 'pname': pname, 'imurl': url, 'price': price, 'rank': rank}
data.insertProductFeatures(product)
reviews = request.get_json(force=True)['reviews']
for r in reviews:
ret = requests.post(sa_url, data=json.dumps({'review': r, 'product': product}))
review = json.loads(ret.text)
if data.existReview(prod_id, review['rid']):
abort(405)
# review with that prod_id and reviewer_id should not exist, but if they
# do throw error
print(review)
data.commit()
(uneval_reviews, names) = data.getUnevalReviews(prod_id)
print('found some uneval reviews')
if uneval_reviews is not None:
print(json.dumps({'reviews': uneval_reviews, 'names': names}))
r = requests.post(ml_url, data=json.dumps({'reviews': uneval_reviews, 'names': names}))
result = json.loads(r.text)['result']
data.updateResult(result)
product = data.getProductInfo(prod_id)
return jsonify({'product': product[0]})
def post(self, msg, img=None, reply=True, pin=False):
reply_id = self.last_status_id() if reply and len(self.status) > 0 else None
media_id = None
if img:
fileim = BytesIO()
img.save(fileim, 'png')
fileim.seek(0)
media_id = self.api.media_post(fileim, mime_type='image/png').id
tags = ''
for tag in CONFIGS['sns']['hashtags']:
tags += '\n#%s' % tag
if tags:
msg += '\n' + tags
status = self.api.status_post(msg, in_reply_to_id=reply_id, media_ids=media_id)
SnsStatus(status_id=status.id, sns_api=self.id)
commit()
if pin:
self.pin(status.id)
return status.id
def post(self, msg, img=None, reply=True, pin=False):
reply_id = self.last_status_id() if reply and len(
self.status) > 0 else None
media_id = None
if img:
fileim = NamedTemporaryFile(suffix='.png', delete=False)
img.save(fileim, 'png')
fileim.close()
media = self.api.media_upload(fileim.name)
media_id = [media.media_id]
os.unlink(fileim.name)
tags = ''
for tag in CONFIGS['sns']['hashtags']:
tags += '\n#%s' % tag
if tags:
msg += '\n' + tags
status = self.api.update_status(msg,
in_reply_to_status_id=reply_id,
media_ids=media_id)
SnsStatus(status_id=status.id, sns_api=self.id)
commit()
if pin:
self.pin(status.id)
return status.id
return None
#----- create product table
cnt = 0
products = []
for line in datautil.parse(product_file):
line = datautil.dataCleanup(line)
pdata = datautil.dataInJson(line)
if pdata is not None:
product = extractProductFields(pdata)
if product is not None:
cnt += 1
products.append(product)
data.insertProductFeatures(product)
data.commit()
#----- create review table
cnt = 0
bad_cnt = 0
reviews = []
rff = open(review_feature_file, 'wt')
for line in datautil.parse(review_file):
print(line)
rdata = datautil.dataInJson(line)
json.dump(rdata, open('post.txt', 'wt'))
if rdata is not None:
cnt += 1
pdata = [
product for product in products if product['pid'] == rdata['asin']
]
def new(cls, battle=None, twitter_api=twitter_api):
api = cls(battle=battle)
api.set_api(twitter_api)
commit()
return api
def event(user_id, event_name):
sql = "INSERT INTO events (user_id, timestamp, event_value_id) VALUES (%s, %s, %s)"
cursor = get_cursor()
cursor.execute(sql, (user_id, time.time(), event_value_ids[event_name]))
commit()
close()
def new(cls, battle=None, mstdn_api=mstdn_api):
api = cls(battle=battle)
api.set_api(mstdn_api)
commit()
return api
