Updated version

README.md

@@ -156,6 +156,7 @@ In finmarketpy/examples you will find several examples, including some simple tr
 
 # Release Notes
 
+* 0.11.10 - finmarketpy (06 Oct 2021)
 * 0.11.9 - finmarketpy (01 Jun 2021)
 * 0.11.8 - finmarketpy (25 Jan 2021)
 * 0.11.7 - finmarketpy (20 Oct 2020)

finmarketpy/economics/eventstudy.py

@@ -24,8 +24,7 @@ class EventStudy(object):
  """
 
  def __init__(self):
- self.logger = LoggerManager().getLogger(__name__)
- return
+ pass
 
  def get_economic_event_ret_over_custom_event_day(self, data_frame_in, event_dates, name, event, start, end,
  lagged=False, NYC_cutoff=10):
@@ -278,7 +277,6 @@ def __init__(self, df=None):
  super(EventStudy, self).__init__()
 
  self.config = ConfigManager()
- self.logger = LoggerManager().getLogger(__name__)
  self.filter = Filter()
  self.io_engine = IOEngine()
  self.speed_cache = SpeedCache()
@@ -523,7 +521,6 @@ def get_surprise_against_intraday_moves_over_event(self, data_frame_cross_orig,
 class HistEconDataFactory(object):
 
  def __init__(self, market_data_generator=None):
- self.logger = LoggerManager().getLogger(__name__)
 
  self._all_econ_tickers = pandas.read_csv(DataConstants().all_econ_tickers)
  self._econ_country_codes = pandas.read_csv(DataConstants().econ_country_codes)
@@ -537,6 +534,8 @@ def __init__(self, market_data_generator=None):
  def get_economic_data_history(self, start_date, finish_date, country_group, data_type,
  source='alfred', cache_algo="internet_load_return"):
 
+ logger = LoggerManager().getLogger(__name__)
+
  # vendor_country_codes = self.fred_country_codes[country_group]
  # vendor_pretty_country = self.fred_nice_country_codes[country_group]
 
@@ -559,7 +558,7 @@ def get_economic_data_history(self, start_date, finish_date, country_group, data
 
  if vendor_ticker == []:
  vendor_ticker = None
- self.logger.error('Could not find match for ' + pretty_ticker)
+ logger.error('Could not find match for ' + pretty_ticker)
  else:
  vendor_ticker = vendor_ticker[0]
 

setup.py

@@ -4,7 +4,7 @@
 trading strategies using a simple to use API, which has prebuilt templates for you to define backtest."""
 
 setup(name='finmarketpy',
- version='0.11.9',
+ version='0.11.10',
  description='finmarketpy is a Python based library for backtesting trading strategies',
  author='Saeed Amen',
  author_email='[email protected]',