def setUp(self):
db_host = os.environ.get('DB_HOST')
db_url = 'postgresql://{user}:{passwd}@{db_host}/{db}'.format(
user='******', passwd='tester', db_host=db_host, db='idetect_test')
engine = create_engine(db_url)
Session.configure(bind=engine)
Base.metadata.drop_all(engine)
Base.metadata.create_all(engine)
self.session = Session()
def setUp(self):
logger.debug("setUp")
worker_logger = logging.getLogger("idetect.worker")
worker_logger.setLevel(logging.INFO)
logger.debug("Connecting to DB")
db_host = os.environ.get('DB_HOST')
db_port = os.environ.get('DB_PORT', 5432)
db_user = os.environ.get('DB_USER', 'tester')
db_pass = os.environ.get('DB_PASSWORD', 'tester')
db_url = 'postgresql://{user}:{passwd}@{db_host}:{db_port}/{db}'.format(
user=db_user,
passwd=db_pass,
db_host=db_host,
db_port=db_port,
db='idetect')
self.engine = create_engine(db_url, echo=False)
Session.configure(bind=self.engine)
self.session = Session()
self.session.query(FactApi).count()
logger.debug("setUp complete")
from sqlalchemy import create_engine
from idetect.model import db_url, Base, Session, Country, FactKeyword
from idetect.load_data import load_countries, load_terms
import re
import string
import numpy as np
import pandas as pd
from idetect.nlp_models.category import *
from idetect.nlp_models.relevance import *
from idetect.nlp_models.base_model import CustomSklLsiModel
if __name__ == "__main__":
# Create the Database
engine = create_engine(db_url())
Session.configure(bind=engine)
Base.metadata.create_all(engine)
session = Session()
# Load the Countries data if necessary
countries = session.query(Country).all()
if len(countries) == 0:
load_countries(session)
# Load the Keywords if neccessary
keywords = session.query(FactKeyword).all()
if len(keywords) == 0:
load_terms(session)
session.close()