def test_forecast_truncate(config=CONFIG):
"""make sure truncate functionality works"""
if platform.system() == 'Darwin':
pytest.xfail('Unable to run fbprophet on mac')
test_data = pd.read_csv(TEST_DATA_PATH)
test_data['date'] = pd.to_datetime(test_data['date'])
max_date = test_data['date'].max()
truncate_range = int(config.get('TEST', 'truncate_range'))
predict_data = forecast_utils.build_forecast(
test_data, int(config.get('TEST', 'forecast_range')), truncate_range)
expected_min_date = max_date - timedelta(days=truncate_range - 1)
actual_min_date = predict_data['date'].min()
assert expected_min_date == actual_min_date
def test_forecast_truncate(config=CONFIG):
"""make sure truncate functionality works"""
test_data = pd.read_csv(TEST_DATA_PATH)
test_data['date'] = pd.to_datetime(test_data['date'])
max_date = test_data['date'].max()
truncate_range = int(config.get('TEST', 'truncate_range'))
predict_data = forecast_utils.build_forecast(
test_data,
int(config.get('TEST', 'forecast_range')),
truncate_range
)
expected_min_date = max_date - timedelta(days=truncate_range-1)
actual_min_date = predict_data['date'].min()
assert expected_min_date == actual_min_date
def test_build_forecast(config=CONFIG):
"""try to build a forecast"""
test_data = pd.read_csv(TEST_DATA_PATH)
test_data['date'] = pd.to_datetime(test_data['date'])
max_date = test_data['date'].max()
expected_rows = [
'date',
'avgPrice',
'yhat',
'yhat_low',
'yhat_high',
'prediction'
]
predict_data = forecast_utils.build_forecast(
test_data,
int(config.get('TEST', 'forecast_range'))
)
headers = list(predict_data.columns.values)
assert set(expected_rows) == set(headers)
assert predict_data['date'].max() == \
max_date + timedelta(days=int(config.get('TEST', 'forecast_range')))
expected_prediction = pd.read_csv(TEST_PREDICT_PATH)
expected_prediction['date'] = pd.to_datetime(expected_prediction['date'])
float_limit = float(config.get('TEST', 'float_limit'))
for key in expected_rows:
print(key)
print(predict_data[key].dtype)
if predict_data[key].dtype == np.float64:
pass
#TODO: ubuntu systems have >0.1 spread on values
#unique_vals = predict_data[key] - expected_prediction[key]
#for val in unique_vals.values:
# assert (abs(val) < float_limit) or (np.isnan(val)) #f*****g floats
else:
assert predict_data[key].equals(expected_prediction[key])
def test_build_forecast(config=CONFIG):
"""try to build a forecast"""
if platform.system() == 'Darwin':
pytest.xfail('Unable to run fbprophet on mac')
test_data = pd.read_csv(TEST_DATA_PATH)
test_data['date'] = pd.to_datetime(test_data['date'])
max_date = test_data['date'].max()
expected_rows = [
'date', 'avgPrice', 'yhat', 'yhat_low', 'yhat_high', 'prediction'
]
predict_data = forecast_utils.build_forecast(
test_data, int(config.get('TEST', 'forecast_range')))
headers = list(predict_data.columns.values)
assert set(expected_rows) == set(headers)
assert predict_data['date'].max() == \
max_date + timedelta(days=int(config.get('TEST', 'forecast_range')))
expected_prediction = pd.read_csv(TEST_PREDICT_PATH)
expected_prediction['date'] = pd.to_datetime(expected_prediction['date'])
float_limit = float(config.get('TEST', 'float_limit'))
for key in expected_rows:
print(key)
print(predict_data[key].dtype)
if predict_data[key].dtype == np.float64:
pass
#TODO: ubuntu systems have >0.1 spread on values
#unique_vals = predict_data[key] - expected_prediction[key]
#for val in unique_vals.values:
# assert (abs(val) < float_limit) or (np.isnan(val)) #f*****g floats
else:
assert predict_data[key].equals(expected_prediction[key])
def get(self, return_type):
args = self.reqparse.parse_args()
LOGGER.info('Prophet {0} Request: {1}'.format(return_type, args))
if return_type not in return_supported_types():
return 'INVALID RETURN FORMAT', 405
mode = api_config.SwitchCCPSource(
api_config.CONFIG.get('GLOBAL', 'crest_or_esi'))
forecast_range = api_config.DEFAULT_RANGE
if 'range' in args:
forecast_range = args.get('range')
## Validate inputs ##
try:
api_utils.check_key(args.get('api'),
throw_on_fail=True,
logger=LOGGER)
crest_utils.validate_id('map_regions',
args.get('regionID'),
config=api_config.CONFIG,
mode=mode,
logger=LOGGER)
crest_utils.validate_id('inventory_types',
args.get('typeID'),
config=api_config.CONFIG,
mode=mode,
logger=LOGGER)
forecast_range = forecast_utils.check_requested_range(
forecast_range,
max_range=api_config.MAX_RANGE,
raise_for_status=True)
except exceptions.ValidatorException as err:
LOGGER.warning('ERROR: unable to validate type/region ids' +
'\n\targs={0}'.format(args),
exc_info=True)
return err.message, err.status
except Exception: #pragma: no cover
LOGGER.error('ERROR: unable to validate type/region ids' +
'args={0}'.format(args),
exc_info=True)
return 'UNHANDLED EXCEPTION', 500
## check cache ##
cache_data = forecast_utils.check_prediction_cache(
args.get('regionID'), args.get('typeID'))
LOGGER.debug(cache_data)
if cache_data is not None:
LOGGER.info('returning cached forecast')
message = forecast_reporter(cache_data, forecast_range,
return_type, LOGGER)
return message
## No cache, get data ##
try:
if args.get('typeID') in api_config.SPLIT_INFO:
LOGGER.info('FORK: using split utility')
data = split_utils.fetch_split_history(
args.get('regionID'),
args.get('typeID'),
mode,
data_range=api_config.MAX_RANGE,
config=api_config.CONFIG,
logger=LOGGER)
data.sort_values(by='date', ascending=True, inplace=True)
else:
data = forecast_utils.fetch_extended_history(
args.get('regionID'),
args.get('typeID'),
mode=mode,
data_range=api_config.MAX_RANGE,
config=api_config.CONFIG,
logger=LOGGER)
data = forecast_utils.build_forecast(data, api_config.MAX_RANGE)
except exceptions.ValidatorException as err:
#FIX ME: testing?
LOGGER.warning('ERROR: unable to generate forecast' +
'\n\targs={0}'.format(args),
exc_info=True)
return err.message, err.status
except Exception: #pragma: no cover
LOGGER.error('ERROR: unable to generate forecast' +
'\n\targs={0}'.format(args),
exc_info=True)
return 'UNHANDLED EXCEPTION', 500
## Update cache ##
forecast_utils.write_prediction_cache(args.get('regionID'),
args.get('typeID'),
data,
logger=LOGGER)
try:
message = forecast_reporter(data, forecast_range, return_type,
LOGGER)
except Exception as err_msg: #pragma: no cover
LOGGER.error('invalid format requested' +
'\n\targs={0}'.format(args) +
'\n\treturn_type={0}'.format(return_type),
exc_info=True)
return 'UNABLE TO GENERATE REPORT', 500
return message
def get(self, return_type):
args = self.reqparse.parse_args()
self.logger.info('Prophet %s Request: %s', return_type, args)
if return_type not in return_supported_types():
return 'INVALID RETURN FORMAT', 405
forecast_range = api_config.DEFAULT_RANGE
if 'range' in args:
forecast_range = args.get('range')
## Validate inputs ##
try:
api_utils.check_key(
args.get('api'),
throw_on_fail=True,
logger=self.logger,
)
crest_utils.validate_id(
'map_regions',
args.get('regionID'),
config=api_config.CONFIG,
logger=self.logger,
)
crest_utils.validate_id(
'inventory_types',
args.get('typeID'),
config=api_config.CONFIG,
logger=self.logger,
)
forecast_range = forecast_utils.check_requested_range(
forecast_range,
max_range=api_config.MAX_RANGE,
raise_for_status=True
)
except exceptions.ValidatorException as err:
self.logger.warning(
'ERROR: unable to validate type/region ids\n\targs=%s',
args,
exc_info=True
)
return err.message, err.status
except Exception: #pragma: no cover
self.logger.error(
'ERROR: unable to validate type/region ids\n\targs=%s',
args,
exc_info=True
)
return 'UNHANDLED EXCEPTION', 500
## check cache ##
cache_data = forecast_utils.check_prediction_cache(
args.get('regionID'),
args.get('typeID')
)
self.logger.debug(cache_data)
if cache_data is not None:
self.logger.info('returning cached forecast')
message = forecast_reporter(
cache_data,
forecast_range,
return_type,
self.logger,
)
return message
## No cache, get data ##
try:
if args.get('typeID') in api_config.SPLIT_INFO:
LOGGER.info('FORK: using split utility')
data = split_utils.fetch_split_history(
args.get('regionID'),
args.get('typeID'),
data_range=api_config.MAX_RANGE,
config=api_config.CONFIG,
logger=self.logger,
)
data.sort_values(
by='date',
ascending=True,
inplace=True
)
else:
data = forecast_utils.fetch_extended_history(
args.get('regionID'),
args.get('typeID'),
data_range=api_config.MAX_RANGE,
config=api_config.CONFIG,
logger=self.logger,
)
data = forecast_utils.build_forecast(
data,
api_config.MAX_RANGE
)
except exceptions.ValidatorException as err:
#FIX ME: testing?
self.logger.warning(
'ERROR: unable to generate forecast\n\targs=%s',
args,
exc_info=True
)
return err.message, err.status
except Exception: #pragma: no cover
LOGGER.error(
'ERROR: unable to generate forecast\n\targs=%s',
args,
exc_info=True
)
return 'UNHANDLED EXCEPTION', 500
## Update cache ##
forecast_utils.write_prediction_cache(
args.get('regionID'),
args.get('typeID'),
data,
logger=self.logger,
)
try:
message = forecast_reporter(
data,
forecast_range,
return_type,
self.logger,
)
except Exception as err_msg: #pragma: no cover
LOGGER.error(
'invalid format requested'
'\n\targs=%s'
'\n\treturn_type=%s',
args, return_type,
exc_info=True
)
return 'UNABLE TO GENERATE REPORT', 500
return message