def populate_usergroups(): session = DBSession() with transaction.manager: admins = [(1, 1)] # admin user should be 1 ulist = admins for gid, uid in ulist: row = UserGroup(gid, uid) session.add(row)
def populate_groups(): session = DBSession() groups = ['admin', 'editor', 'manager'] for gname in groups: try: with transaction.manager: group = Group(gname) session.add(group) except IntegrityError: pass
def populate_users(admin_username): from trumpet.security import encrypt_password session = DBSession() with transaction.manager: users = [admin_username] # Using id_count to presume # the user's id, which should work # when filling an empty database. id_count = 0 for uname in users: id_count += 1 user = User(uname) password = encrypt_password(uname) session.add(user) pw = Password(id_count, password) session.add(pw)
def __init__(self, user_id=None): self.session = DBSession() self.user_id = user_id
""" Module for executing calculation about parameters Learning Algorithm - 2015 - Subena """ from compiler.ast import flatten import itertools from sqlalchemy.sql.functions import func from base import DBSession, logging import numpy as np from package.model.tables import Criterion, Value, Stats,Alerts session = DBSession() criteria = session.query(Criterion).all() def execute(): logging.info( "\nStart learning parameters..." ) #calcul all proba dependencies according to proba and their parenthood getProbaForAllMeasures() def getAlertsFromStats(): """ Get alerts from calculated stats (see getProbaForAllMeasures) for each stat if a pattern does not correspond then create an alert """ stats = None