def SAP_process_table(table, fields, options, columns_dict, model):
session = Session()
df = SAP_get_table(table, fields, options)
df.rename(columns=columns_dict, inplace=True)
session.execute(model.__table__.insert(), df.to_dict(orient="records"))
session.commit()
session.close()
return df
def __init__(self):
print 'Initializing Driver'
session = Session()
self.modules = session.query(LightModule).all()
self.strips = {s.name: s for s in session.query(Strip).all()}
session.close()
print 'starting engine'
self.engine = LightEngine(self.modules)
print 'engine running'
self.sp = Spotify()
print 'spotify loaded'
if SIM:
self.sim = Client('127.0.0.1:7890')
def process_input(header=True):
csv_file = open(tmp_file, 'r', encoding='utf-8')
csv_reader = None
try:
csv_reader = list(csv.reader(csv_file, delimiter=','))
except:
print("Error in opening csv file. Please check the format/encoding!!")
quit()
line_no = 0
if header:
line_no += 1
csv_reader = csv_reader[1:]
session = Session()
all_reviews = session.query(Review).all()
reviews_set = {(review.product_id, str(review.review_text).lower())
for review in all_reviews}
reviews_in_file = set()
print("Processing input file..")
for line in csv_reader:
line_no += 1
review_text = line[0]
product_id = line[4]
search_key = (product_id, str(review_text).lower())
if search_key in reviews_set:
print("Review at line: {} is already in db!!".format(line_no))
elif search_key in reviews_in_file:
print("Review at line: {} is duplicate in file!!".format(line_no))
else:
review_ob = Review(product_id, review_text)
session.add(review_ob)
reviews_in_file.add(search_key)
print("Committing data...")
session.commit()
session.close()
try:
# Remove downloaded file
os.remove(tmp_file)
except:
pass
def process_reviews():
session = Session()
client = language.LanguageServiceClient()
reviews_to_analyze = session.query(Review).filter_by(
review_analyzed=False).all()
total = len(reviews_to_analyze)
processed = 0
step = 1
throttle_limit = 500
print("Processing Reviews...")
print("Processed {}/{} ".format(processed, total), end='\r')
start_time = time.time()
one_minute = 60
for review in reviews_to_analyze:
try:
analyze_review(client, review, session)
except:
pass
review.review_analyzed = True
session.add(review)
processed += 1
# if processed % step == 0:
print("Processed {}/{} ".format(processed, total), end='\r')
if processed % throttle_limit == 0:
end_time = time.time()
time_taken = end_time - start_time
if time_taken < one_minute:
time.sleep(one_minute - time_taken)
start_time = time.time()
print("Processed {}/{} ".format(processed, total))
print("Committing data...")
session.commit()
session.close()
print("Processed data stored successfully!!")
def SAP_notification_process(date, end_date):
# Get all notifications from the VIQMEL
print('Processing notifications')
#df_notification = SAP_process_table('VIQMEL',['QMNUM','IWERK','QMART','AUFNR','EQUNR','QMTXT','STRMN','LTRMN','ERDAT','PRIOK','ERNAM','TPLNR','ARBPL', 'OBJNR'],\
# "IWERK EQ 'TR01' AND ERDAT >= '" + date + "' and ERDAT <= '"+end_date+"'",notification_columns, Notification)
df_notification = pd.read_sql_table("SAP_notifications", con=engine)
# Get all notifications´ types TQ80
print('Processing notifications type')
#SAP_process_table('TQ80', ['QMART','STSMA'], "MANDT EQ '020'",notification_type_columns, Notification_Type)
df_type = pd.read_sql_table("SAP_notification_type", con=engine)
# Get all notifications´ additional texts or comments QMFE
print('Processing notifications text')
#SAP_process_table('QMFE', ['QMNUM','FETXT'], "FETXT NE '' AND ERDAT >= '" + date + "'",notification_text_columns, Notification_Text)
# Get all notifications' activities from the QMMA
print('Processing notifications activities')
#SAP_process_table('QMMA', ['MANDT','QMNUM','MATXT','MNGRP','MNCOD','MNKAT'], "MANDT EQ '020' AND ERDAT >= '" + date + "'", notification_activity_columns, Notification_Activity)
# Get all notification´s activities header for the QPCD
print('Processing notifications activities header')
#SAP_process_table('QPCT', ['MANDT','CODEGRUPPE','CODE','KURZTEXT','KATALOGART'], "MANDT EQ '020' AND INAKTIV EQ ''", notification_activity_header_columns, Notification_Activity_Header)
# Get all notification´s catalog types for the TQ15
print('Processing notifications catalog')
#SAP_process_table('TQ15T', ['MANDT','KATALOGART','KATALOGTXT'], "MANDT EQ '020' AND SPRACHE EQ 'S'", notification_catalog_columns, Notification_Catalog)
# Get all notifications' causes from the QMUR
print('Processing notifications causes')
#SAP_process_table('QMUR', ['MANDT','QMNUM','URTXT'], "MANDT EQ '020' AND ERDAT >= '" + date + "'", notification_cause_columns, Notification_Cause)
# Get all TRANSELCA´s equipment (K: Equipos Transelca - L: MAF Transelca)
print('Processing equipments')
#SAP_process_table('EQUI', ['MANDT','EQUNR','EQART','HERST','TYPBZ'], "EQTYP EQ 'K' OR EQTYP EQ 'L'", equipment_columns, Equipment)
# Get all equipments´ descriptions
print('Processing equipments description')
#SAP_process_table('EQKT', ['MANDT','EQUNR','EQKTX'], "MANDT EQ '020'", equipment_text_columns, Equipment_Text)
# Get all TRANSELCA's workplaces
print('Processing workplaces')
#df_workplace_id = SAP_get_table('CRHD',['MANDT','OBJID','ARBPL'],"MANDT EQ '020' AND WERKS EQ 'TR01'")
#df_workplace_text = SAP_get_table('CRTX',['MANDT','OBJID','KTEXT'],"MANDT EQ '020' AND SPRAS EQ 'S'")
#df_workplace = pd.merge(df_workplace_id, df_workplace_text, how='inner', on=['OBJID']) # filter per values in df_system
#df_workplace.rename(columns=work_center_columns,inplace=True)
#session = Session()
#session.execute(Work_Center.__table__.insert(),df_workplace.to_dict(orient="records"))
#session.commit()
#session.close()
# Get all TRANSELCA's functional location
print('Processing functional location')
#session = Session()
#print(df_notification['func_location'].unique().shape)
#df_func = SAP_get_table_by_data('IFLOS',['TPLNR','STRNO', 'ACTVS','TPLKZ','ERDAT','VERSN','ERNAM'],"ACTVS EQ 'X' AND TPLNR EQ '#field#'",df_notification['func_location'].unique())
#df_func = df_func.drop_duplicates()
#df_func.rename(columns=func_location_columns,inplace=True)
#session.execute(Functional_Location.__table__.insert(),df_func.to_dict(orient="records"))
#session.commit()
#session.close()
# Get System Status
print('Processing System Status Header')
#df_system = SAP_process_table('TJ02T', ['ISTAT','TXT04','TXT30'], "SPRAS EQ 'S'", system_columns, System_Status)
df_system = pd.read_sql_table("SAP_system_status", con=engine)
# Get User Status Header
print('Processing User Status Header')
#df_user = SAP_process_table('TJ30T', ['STSMA','ESTAT','TXT04','TXT30'], "MANDT EQ '020' AND SPRAS EQ 'S'", user_columns, User_Status)
df_user = pd.read_sql_table("SAP_user_status", con=engine)
# Get all statuses
print(df_notification.shape)
print('GET STATUSES START')
#session = Session()
#df_status = SAP_get_table_by_data('JEST',['MANDT','OBJNR','STAT','INACT'],"MANDT EQ '020' AND OBJNR EQ '#field#'",df_notification['obj_nr'])
#df_status = df_status.drop_duplicates()
#df_status.rename(columns=status_columns,inplace=True)
#df_status_system = pd.merge(df_status, df_system, how='inner', on=['status_id']) # filter per values in df_system
#df_status_user = pd.merge(df_status, df_user['status_id'].drop_duplicates(), how='inner', on=['status_id']) # filter per values in df_user
#df_notification_2 = pd.merge(df_notification, df_type, how='inner', on=['type_n']) # filter per values in df_user
#df_status_user_x = pd.merge(df_status_user, df_notification_2[['obj_nr','status_schema']], how='inner', on=['obj_nr'])
#session.execute(Notification_System_Status.__table__.insert(),df_status_system.to_dict(orient="records"))
#session.execute(Notification_User_Status.__table__.insert(),df_status_user_x.to_dict(orient="records"))
#session.commit()
#session.close()
# Get log statuses
print('GET LOG STATUSES START')
session = Session()
df_status_system = pd.read_sql_table('SAP_notification_system_status',
con=engine)
df_status_user_x = pd.read_sql_table('SAP_notification_user_status',
con=engine)
df_log_status = SAP_get_table_by_data(
'JCDS', [
'MANDT', 'OBJNR', 'STAT', 'USNAM', 'UDATE', 'UTIME', 'TCODE',
'CDTCODE', 'INACT', 'CHIND'
], "MANDT EQ '020' AND UDATE >='" + date + "' AND OBJNR EQ '#field#'",
df_notification['obj_nr'])
df_log_status = df_log_status.drop_duplicates()
df_log_status.rename(columns=log_columns, inplace=True)
df_log_status_system = pd.merge(df_log_status,
df_status_system[['obj_nr', 'status_id']],
how='inner',
on=['obj_nr', 'status_id'])
df_log_status_user = pd.merge(
df_log_status,
df_status_user_x[['obj_nr', 'status_id', 'status_schema']],
how='inner',
on=['obj_nr', 'status_id']) # filter
session.execute(Notification_Log_User.__table__.insert(),
df_log_status_user.to_dict(orient="records"))
session.execute(Notification_Log_System.__table__.insert(),
df_log_status_system.to_dict(orient="records"))
session.commit()
session.close()
from lighting.basic import Intensity, Color
from lighting.strobe import Strobe, SmoothStrobe
from lighting.kf_intensities import KFIntensities
from lighting.ripple import Ripple
from config import Session
import time
if __name__ == '__main__':
session = Session()
modules = session.query(LightModule).all()
strips = session.query(Strip).all()
session.close()
# time.sleep(2)
# engine = LightEngine(modules)
# print 'beginning test'
# for i in range(5):
# for strip in strips:
# strip.effects.append(Wave(length=strip.length))
# time.sleep(3)
time.sleep(1)
engine = LightEngine(modules, refresh_rate=60)
print 'beginning test'
r = Ripple(speed=2)
for strip in strips:
strip.add_intensity_control(Ripple(speed=1, center = 60))
class ScriptTestCase(unittest.TestCase):
def setUp(self):
self.session = Session()
def tearDown(self):
self.session.close()
def test_replace_literals(self):
script_in = '%{사람}'
script = replace_literals(script_in, self.session)
self.assertNotEqual(script, script_in)
def test_replace_literals_unknown(self):
script_in = '%{XXXX}'
script = replace_literals(script_in, self.session)
self.assertEqual(script_in, script)
def test_find_literals(self):
script = '%{사람 %{사람} } %{랜덤} literals'
literals = list(find_literals(script))
self.assertEqual(literals, ['%{사람}', '%{랜덤}'])
script = '%{1000-2030}'
literals = list(find_literals(script))
self.assertEqual(literals, ['%{1000-2030}'])
def test_find_literals_matchall(self):
script = '%{{사람}} literals'
literals = list(find_literals(script))
self.assertEqual(literals, ['%{{사람}}'])
def test_particles(self):
script = '%{{사람}}(이)가 어쨌다고요'
script = compile_script(script, self.session)
self.assertFalse('(' in script)
script = '서울 대표(%{1900-1901})'
script = compile_script(script, self.session)
self.assertEqual(script, '서울 대표(1900)')
script = '서울 대표(%{1900-1901}-%{1949-1950})'
script = compile_script(script, self.session)
self.assertEqual(script, '서울 대표(1900-1949)')
script = '서울 대표(%{장소})'
script = compile_script(script, self.session)
self.assertTrue(script.startswith('서울 대표('))
self.assertTrue(script.endswith(')'))
def test_numbered_literal(self):
script = '%{사람}%{1}'
script = compile_script(script, self.session)
split = int(len(script) / 2)
self.assertEqual(script[:split], script[split:])
def test_numbered_literal_particle(self):
script = '%{{사람}} %{1}(이)라고'
script = compile_script(script, self.session)
self.assertFalse('(' in script)
def get_db():
try:
db = Session()
yield db
finally:
db.close()
