def test_creation_default_date_range():
db = sdm.StockDBMgr('./stock_db/test')
df = db.get_symbol_data('SPY')
start = datetime.date(2020, 3, 16)
stop = datetime.date(2020, 3, 20)
assert df.iloc[0].name.date() < start
assert df.iloc[-1].name.date() > stop
def test_get_symbol_data():
db = sdm.StockDBMgr('./stock_db/test')
df1 = db.get_symbol_data('SPY')
df2 = db.get_symbol_data('SPY')
assert (df1 == df2).all().all()
assert len(df1) == len(df2)
assert df1 is df2
def test_download_data():
db = sdm.StockDBMgr('./stock_db/test')
assert 'SPY' not in db._dic
db.get_symbol_data('SPY')
assert 'SPY' in db._dic
db.download_data('SPY')
assert 'SPY' not in db._dic
def test_creation_custom_date_range():
start = datetime.date(2020, 3, 16)
stop = datetime.date(2020, 3, 20)
db = sdm.StockDBMgr('./stock_db/test', start, stop)
df = db.get_symbol_data('SPY')
assert df.iloc[0].name.date() == start
assert df.iloc[-1].name.date() == stop
def test_update_all_symbols():
db = sdm.StockDBMgr('./stock_db/empty')
assert 'SPY' not in db._dic
# Get a single symbol
db.get_symbol_data('SPY')
assert 'SPY' in db._dic
db.update_all_symbols()
assert 'SPY' not in db._dic
def test_get_all_symbol_single_data_item():
db = sdm.StockDBMgr('./stock_db/test')
df = db.get_all_symbol_single_data_item('Close')
for s in db.get_all_symbols():
assert s in df
df = db.get_all_symbol_single_data_item('BadData')
assert df is None
def load_data():
print("load_data()")
global dic
global db
db = sdm.StockDBMgr(data_dir, start_date, end_date)
dic = db.get_all_symbol_data()
def test_get_all_symbol_single_data_item():
db = sdm.StockDBMgr('./stock_db/test')
df1 = db.get_symbol_data(db.get_all_symbols()[0])
for p in df1.columns:
df = db.get_all_symbol_single_data_item(p)
for s in db.get_all_symbols():
assert s in df
df = db.get_all_symbol_single_data_item('BadData')
assert df is None
def _main():
db = sdm.StockDBMgr('../stock_db/test', datetime.date(2017, 1, 1),
datetime.date(2018, 1, 1))
symbol_list = db.get_all_symbols()
print(symbol_list)
# Work with first symbol only
s = symbol_list[0]
if False:
# To test caching
df = db.get_symbol_data(s)
df = db.get_symbol_data(s)
db.download_data(s)
df = db.get_symbol_data(s)
db.update_all_symbols()
df = db.get_symbol_data(s)
if True:
print("Validating symbols")
for s in db.get_all_symbols():
if not db.validate_symbol_data(s):
print("{} failed validation".format(s))
if True:
print("Loading all symbols to a dict")
# To test caching
dd = db.get_all_symbol_data()
dd = db.get_all_symbol_data()
print(dd.keys())
df = db.get_all_symbol_single_data_item('Close')
print(df.head())
df = db.get_all_symbol_single_data_item('Volume')
print(df.head())
if True:
db = sdm.StockDBMgr('../stock_db/test', datetime.date(2017, 1, 1),
datetime.date(2018, 1, 1), False)
df = db.get_symbol_data(symbol_list[0])
print(df.describe())
def indicator_test():
db = sdm.StockDBMgr('./stock_db/tsx', startdate, enddate)
print("Loading all symbols...")
df = db.get_all_symbol_single_data_item('Close')
print("Loading done.")
rp = (df.iloc[-1] - df.min()) / (df.max() - df.min())
rps = 2.0 * rp - 1.0
rr = (df.max() - df.min()) / df.max()
t = rps * rr.pow(0.1)
# Price in the floor (5% tolerance) & 15% drop
print(t.loc[(rp < 0.05) & (rr > 0.15)])
def correlation_test():
db = sdm.StockDBMgr('./stock_db/qt', startdate, enddate)
df = db.get_all_symbol_single_data_item('Close')
df.dropna(axis=1, how='any', inplace=True)
symbols = list(df.columns)
n = len(symbols)
dfc = pd.DataFrame(index=symbols, data=np.zeros((n, n)), columns=symbols)
for s1 in symbols:
for s2 in symbols:
c = sps.pearsonr(df.loc[:, s1], df.loc[:, s2])[0]
dfc.loc[s1, s2] = c
#print(dfc)
# Find inverse correlation
print(dfc.min())
print(dfc.idxmin())
def check_db(path):
# Create data base:
db = sdm.StockDBMgr('./stock_db/' + path, startdate, enddate)
# db.update_all_symbols()
inv = []
symbolList = db.get_all_symbols()
print(len(symbolList))
print(symbolList)
for s in symbolList:
if False:
print("symbol:{}, yield:{}, name:{}".format(
s, sq.get_dividend_yield(s), sq.get_name(s)))
if not db.validate_symbol_data(s):
inv.append(s)
continue
# Only applies if recent download...
if True:
df = db.get_symbol_data(s)
t = startdate
if df is not None and len(df) > 0:
# t = r[-1].date
t = df.iloc[-1].name.date()
else:
inv.append(s)
continue
if (today - t) > datetime.timedelta(4):
inv.append(s)
print("%s: len = %d" % (s, len(df)))
print("Invalid list:")
for s in inv:
print(s)
import datetime
import numpy as np
import matplotlib.dates as mdates
import matplotlib.ticker as mticker
import matplotlib.pyplot as plt
import matplotlib.font_manager as font_manager
import stock_db_mgr as sdm
startdate = datetime.date(2019, 1, 1)
enddate = datetime.date.today()
ticker = 'SPY'
db = sdm.StockDBMgr('../stock_db/test', startdate, enddate)
def moving_average(x, n, moving_average_type='simple'):
"""Compute an n period moving average.
type is 'simple' | 'exponential'
"""
x = np.asarray(x)
if moving_average_type == 'simple':
weights = np.ones(n)
else:
weights = np.exp(np.linspace(-1., 0., n))
weights /= weights.sum()
a = np.convolve(x, weights, mode='full')[:len(x)]
from pylab import figure, show
from matplotlib.dates import YearLocator, MonthLocator, DateFormatter
import datetime
import stock_db_mgr as sdm
# format the coords message box
def price(x):
return '$%1.2f' % x
date1 = datetime.date(1995, 1, 1)
date2 = datetime.date(2004, 4, 12)
db = sdm.StockDBMgr('../stock_db/test', date1, date2)
years = YearLocator() # every year
months = MonthLocator() # every month
yearsFmt = DateFormatter('%Y')
df = db.get_symbol_data('SPY')
dates = [d for d in df.index]
opens = [o for o in df.loc[:, 'Open'].values]
fig = figure()
ax = fig.add_subplot(111)
ax.plot_date(dates, opens, '-')
# format the ticks
import virtual_account as va
import stock_db_mgr as sdm
db = sdm.StockDBMgr('./stock_db/test')
def test_virtual_account():
assert db
a = va.VirtualAccount(100000.0, db.get_all_symbol_data())
assert a
assert a.get_cash() == 100000.0
a.delta_cash(200)
assert a.get_cash() == 100200.0
a.delta_cash(-100)
assert a.get_cash() == 100100.0
assert len(a.get_all_positions()) == 0
assert len(a.get_open_positions()) == 0
assert len(a.get_close_positions()) == 0
assert len(a.get_all_positions('SPY')) == 0
assert len(a.get_open_positions('SPY')) == 0
assert len(a.get_close_positions('SPY')) == 0
a.buy_at_market(0, 'SPY', 100)
assert len(a.get_all_positions()) == 1
assert len(a.get_open_positions()) == 1
assert len(a.get_close_positions()) == 0
assert len(a.get_all_positions('SPY')) == 1
assert len(a.get_open_positions('SPY')) == 1
def test_get_all_symbol_data():
db = sdm.StockDBMgr('./stock_db/test')
dic = db.get_all_symbol_data()
for s in db.get_all_symbols():
assert s in dic
def test_get_symbol_data_bad():
db = sdm.StockDBMgr('./stock_db/bad')
df = db.get_symbol_data('BAD')
assert (df is None)
def test_get_symbol_data_bad2():
db = sdm.StockDBMgr('./stock_db/bad')
df = db.get_symbol_data('XXXZZZ') # Invalid ticker
assert (df is None)
def test_validate():
db = sdm.StockDBMgr('./stock_db/test')
for s in db.get_all_symbols():
assert db.validate_symbol_data(s)
def test_get_all_symbols():
db = sdm.StockDBMgr('./stock_db/test', datetime.date(2017, 1, 1),
datetime.date(2018, 1, 1))
symbol_list = db.get_all_symbols()
assert len(symbol_list) > 3
from __future__ import print_function
import datetime
import stock_db_mgr as sdm
import tmxstockquote as tsq
startdate = datetime.date(1900, 1, 1)
today = datetime.date.today()
# Pick one:
#enddate = datetime.date(2018, 2, 22)
enddate = today
# Create data base:
db = sdm.StockDBMgr('./stock_db/qt', startdate, enddate)
#db = sdm.StockDBMgr('./stock_db/tsx')
#db = sdm.StockDBMgr('./stock_db/sp500')
#db = sdm.StockDBMgr('./stock_db/test')
#db.update_all_symbols()
inv = []
symbolList = db.get_all_symbols()
print(len(symbolList))
print(symbolList)
for s in symbolList:
print("symbol:{}, yield:{}, name:{}".format(s, tsq.get_dividend_yield(s),
tsq.get_name(s)))
