main.py

import os
import yaml
import logging
import shutil

from datetime import datetime 
from sqlalchemy.engine.url import URL
from sqlalchemy.pool import NullPool

from triage.util.db import create_engine
from triage.component.timechop import Timechop
from triage.component.timechop.plotting import visualize_chops
from triage.component.architect.feature_generators import FeatureGenerator
from triage.experiments import MultiCoreExperiment, SingleThreadedExperiment


# import os
# os.chdir('donors-choose')
now = datetime.now()
logger = logging.getLogger()
logger.setLevel(logging.INFO)
formatter = logging.Formatter('%(name)-30s  %(asctime)s %(levelname)10s %(process)6d  %(filename)-24s  %(lineno)4d: %(message)s', '%d/%m/%Y %I:%M:%S %p')
fh = logging.FileHandler(f'triage_{now}.log', mode='w')
fh.setFormatter(formatter)
logger.addHandler(fh)

# creating database engine
# dbfile = 'database.yaml'

# with open(dbfile, "r") as f:
#     dbconfig = yaml.safe_load(f)

# db_url = URL(
#             'postgres',
#             host=dbconfig['host'],
#             username=dbconfig['user'],
#             database=dbconfig['db'],
#             password=dbconfig['pass'],
#             port=dbconfig['port'],
#         )

# TODO - Create a function that either uses the environmental variables or a database.yaml file
db_url = URL(
    'postgres',
    host=os.getenv('PGHOST'),
    username=os.getenv('PGUSER'),
    database=os.getenv('PGDATABASE'),
    password=os.getenv('PGPASSWORD'),
    port=os.getenv('PGPORT'),
)

db_engine = create_engine(db_url)

# loading config file
config_file = 'donors-choose-config.yaml'

# config_file = 'donors-choose-config-small.yaml'
with open(config_file, 'r') as fin:
    config = yaml.safe_load(fin)

# generating temporal config plot
chopper = Timechop(**config['temporal_config'])

# We aren't interested in seeing the entire feature_start_time represented
# in our timechop plot. That would hide the interesting information. So we
# set it to equal label_start_time for the plot.

chopper.feature_start_time = chopper.label_start_time 

visualize_chops(chopper, save_target = 'triage_output/timechop.png')

# creating experiment object

# experiment = MultiCoreExperiment(
#     config = config,
#     db_engine = db_engine,
#     project_path = 's3://dsapp-education-migrated/donors-choose',
#     n_processes=4,
#     n_db_processes=2,
#     replace=False,
#     save_predictions=False
# )

experiment = SingleThreadedExperiment(
    config = config,
    db_engine = db_engine,
    project_path = 's3://dsapp-education-migrated/donors-choose',
    replace=False,
    save_predictions=False
)

experiment.validate()
experiment.run()


# Creating the Triage experiment Report
template_path = 'notebooks/triage_experiment_report_template.ipynb'

timestamp = datetime.now().strftime('%Y%m%d_%H%M')
output_path = f'notebooks/triage_experiment_report_{timestamp}.ipynb'
shutil.copyfile(template_path, output_path)
os.system(f'jupyter nbconvert --inplace --execute --to notebook {output_path}')
os.system(f'jupyter nbconvert --to html {output_path}')