def test_AskHorse(self, sendEmail): self._createStrategy() args = "-n unitTest".split() askHorse(args) self.assertTrue(sendEmail.called) self.assertEqual(len(sendEmail.call_args[0][0]), 3)
cbaEquityData.query("Date > '2015-01-01 00:00:00'").plot(y=['upperband','middleband','lowerband','Close'], title='CBA BBAND 2015') import pyswing.database import sqlite3 from pandas.io.sql import read_sql_query connection = sqlite3.connect("output/TestMultipleIndicatorRule.db") query = "select e.Date, Close, SMA_200 from Equities e inner join Indicator_SMA i on e.Date = i.Date and e.Code = i.Code" cbaEquityData = read_sql_query(query, connection, 'Date') connection.close() cbaEquityData.query("Date > '2015-06-01 00:00:00'").plot(y=['Close','SMA_200'], title='Testing') from pyswing.AskHorse import askHorse args = "-n asx".split() askHorse(args) from pyswing.AnalyseStrategies import analyseStrategies args = "-n ftse -s v1.2 -r 0.4 -t 500".split analyseStrategies(args) # Run me to populate (emptying to begin with) the historic trades table using the strategies in active strategies (which must be put in there manually)... from pyswing.GenerateHistoricTradesForActiveStrategies import generateHistoricTradesForActiveStrategies args = "-n ftse".split() generateHistoricTradesForActiveStrategies(args) # Run me to chart the (distinct) results in active strategy import pyswing.database
y=['upperband', 'middleband', 'lowerband', 'Close'], title='CBA BBAND 2015') import pyswing.database import sqlite3 from pandas.io.sql import read_sql_query connection = sqlite3.connect("output/TestMultipleIndicatorRule.db") query = "select e.Date, Close, SMA_200 from Equities e inner join Indicator_SMA i on e.Date = i.Date and e.Code = i.Code" cbaEquityData = read_sql_query(query, connection, 'Date') connection.close() cbaEquityData.query("Date > '2015-06-01 00:00:00'").plot( y=['Close', 'SMA_200'], title='Testing') from pyswing.AskHorse import askHorse args = "-n asx".split() askHorse(args) from pyswing.AnalyseStrategies import analyseStrategies args = "-n ftse -s v1.2 -r 0.4 -t 500".split analyseStrategies(args) # Run me to populate (emptying to begin with) the historic trades table using the strategies in active strategies (which must be put in there manually)... from pyswing.GenerateHistoricTradesForActiveStrategies import generateHistoricTradesForActiveStrategies args = "-n ftse".split() generateHistoricTradesForActiveStrategies(args) # Run me to chart the (distinct) results in active strategy import pyswing.database import sqlite3 from pandas.io.sql import read_sql_query from pandas import expanding_sum