def test_covariance(self):
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
cache = os.path.abspath(os.path.split(__file__)[0])
cache = os.path.join(cache, "temp_cache_cov")
stocks = [StockPrices("BNP.PA", folder=cache),
StockPrices("CA.PA", folder=cache),
StockPrices("SAF.PA", folder=cache),
]
dates = StockPrices.available_dates(stocks)
ok = dates[dates["missing"] == 0]
stocks = [v.keep_dates(ok) for v in stocks]
cov = StockPrices.covariance(stocks)
assert len(cov) == 3
cor = StockPrices.covariance(stocks, cov=False)
self.assertEqual(len(cor), 3)
assert abs(cor.ix["BNP.PA", "BNP.PA"] - 1) < 1e-5
assert abs(cor.ix[2, 2] - 1) < 1e-5
ret, mat = StockPrices.covariance(stocks, cov=False, ret=True)
self.assertEqual(len(ret), 3)
def test_graph(self) :
"""
This test is failing with Python 3.4 if many pictures are drawn.
"""
fLOG (__file__, self._testMethodName, OutputPrint = __name__ == "__main__")
cache = os.path.abspath(os.path.split(__file__)[0])
cache = os.path.join(cache, "temp_cache2")
stocks = [ StockPrices ("BNP.PA", folder = cache),
StockPrices ("CA.PA", folder = cache),
StockPrices ("SAF.PA", folder = cache),
]
if True:
fig, ax, plt = StockPrices.draw(stocks, figsize=(16,8), field = ["Adj Close", "Close"])
img = os.path.abspath(os.path.join(os.path.split(__file__)[0],"temp_image.png"))
if os.path.exists(img): os.remove(img)
fig.savefig(img)
assert os.path.exists(img)
if True and sys.version_info < (3,4) :
fig, ax, plt = StockPrices.draw(stocks, begin="2010-01-01")
img = os.path.abspath(os.path.join(os.path.split(__file__)[0],"temp_image2.png"))
if os.path.exists(img): os .remove(img)
fig.savefig(img)
assert os.path.exists(img)
if True and sys.version_info < (3,4):
fig, ax, plt = StockPrices.draw(stocks[:1], begin="2010-01-01")
img = os.path.abspath(os.path.join(os.path.split(__file__)[0],"temp_image3.png"))
if os.path.exists(img): os .remove(img)
fig.savefig(img)
assert os.path.exists(img)
def test_graph2(self):
"""
This test is failing with Python 3.4 if many pictures are drawn.
"""
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
if is_travis_or_appveyor() == "appveyor":
return
fix_tkinter_issues_virtualenv()
from matplotlib import pyplot as plt
cache = os.path.abspath(os.path.split(__file__)[0])
cache = os.path.join(cache, "temp_cache2")
stock = StockPrices("BNP.PA", folder=cache)
stock2 = StockPrices("CA.PA", folder=cache)
fig, ax = plt.subplots(figsize=(16, 8))
ax = stock.plot(ax=ax)
ax = stock2.plot(ax=ax)
img = os.path.abspath(
os.path.join(
os.path.split(__file__)[0],
"temp_image2.png"))
if os.path.exists(img):
os.remove(img)
fig.savefig(img)
plt.close('all')
assert os.path.exists(img)
def test_save_stock_datetime(self):
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
temp = get_temp_folder(__file__, "temp_save_stock_datetime")
cache = temp
stock = StockPrices(TestStockFileDatetime.tick, use_dtime=True, folder=cache,
end=datetime.datetime(2014, 1, 15), url=TestStockFileDatetime.source)
file = os.path.join(cache, "save.txt")
if os.path.exists(file):
os.remove(file)
stock.to_csv(file)
self.assertTrue(os.path.exists(file))
stock2 = StockPrices(file, sep="\t", use_dtime=True)
self.assertEqual(stock.dataframe.shape, stock2.dataframe.shape)
df = stock2.dataframe
file = os.path.join(cache, "out_excel.xlsx")
if os.path.exists(file):
os.remove(file)
df.to_excel(file)
self.assertTrue(os.path.exists(file))
def test_save_stock_google(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
cache = os.path.abspath(os.path.split(__file__)[0])
cache = os.path.join(cache, "temp_cache_file_google")
name = os.path.join(cache, "NASDAQ_GOOG.2000-01-03.2014-01-15.txt")
if os.path.exists(name):
os.remove(name)
stock = StockPrices("NASDAQ:GOOG",
url="google",
folder=cache,
end=datetime.datetime(2014, 1, 15))
file = os.path.join(cache, "save.txt")
if os.path.exists(file):
os.remove(file)
stock.to_csv(file)
assert os.path.exists(file)
stock2 = StockPrices(file, sep="\t")
assert stock.dataframe.shape == stock2.dataframe.shape
df = stock2.dataframe
file = os.path.join(cache, "out_excel.xlsx")
if os.path.exists(file):
os.remove(file)
df.to_excel(file)
assert os.path.exists(file)
def test_graph4(self):
"""
This test is failing with Python 3.4 if many pictures are drawn.
"""
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
if is_travis_or_appveyor() == "appveyor":
return
fix_tkinter_issues_virtualenv()
from matplotlib import pyplot as plt
cache = os.path.abspath(os.path.split(__file__)[0])
cache = os.path.join(cache, "temp_cache4")
stock = StockPrices("BNP.PA", folder=cache)
ret = stock.returns()["2012-04-01":"2014-04-15"]
fig, ax = plt.subplots(figsize=(16, 8))
ax = stock.plot(ax=ax)
ax = ret.plot(ax=ax, axis=2)
img = os.path.abspath(
os.path.join(os.path.split(__file__)[0], "temp_image4.png"))
if os.path.exists(img):
os.remove(img)
fig.savefig(img)
plt.close('all')
assert os.path.exists(img)
def test_save_stock_quandl(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
temp = get_temp_folder(__file__, "temp_cache_file_quandl")
cache = temp
try:
stock = StockPrices("EURONEXT/BNP",
url="quandl",
folder=cache,
end=datetime.datetime(2017, 1, 15))
except LimitExceededError:
warnings.warn(
"[test_save_stock_quandl] reached quandl free quota. Stop test."
)
return
file = os.path.join(cache, "save.txt")
if os.path.exists(file):
os.remove(file)
stock.to_csv(file)
self.assertTrue(os.path.exists(file))
stock2 = StockPrices(file, sep="\t")
self.assertEqual(stock.dataframe.shape, stock2.dataframe.shape)
df = stock2.dataframe
file = os.path.join(cache, "out_excel.xlsx")
if os.path.exists(file):
os.remove(file)
df.to_excel(file)
self.assertTrue(os.path.exists(file))
def test_save_stock_yahoo_new(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
temp = get_temp_folder(__file__, "temp_cache_file_yahoo")
cache = temp
stock = StockPrices("AAPL",
folder=cache,
url="yahoo_new",
end=datetime.datetime(2014, 1, 15))
file = os.path.join(cache, "save.txt")
if os.path.exists(file):
os.remove(file)
stock.to_csv(file)
self.assertTrue(os.path.exists(file))
stock2 = StockPrices(file, sep="\t")
self.assertEqual(stock.dataframe.shape, stock2.dataframe.shape)
df = stock2.dataframe
file = os.path.join(cache, "out_excel.xlsx")
if os.path.exists(file):
os.remove(file)
df.to_excel(file)
self.assertTrue(os.path.exists(file))
def test_save_stock_google(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
temp = get_temp_folder(__file__, "temp_cache_file_google")
cache = temp
try:
stock = StockPrices("NASDAQ:MSFT",
folder=cache,
end=datetime.datetime(2014, 1, 15),
url="google")
except StockPricesHTTPException as e:
warnings.warn(str(e))
return
file = os.path.join(cache, "save.txt")
if os.path.exists(file):
os.remove(file)
stock.to_csv(file)
self.assertTrue(os.path.exists(file))
stock2 = StockPrices(file, sep="\t")
self.assertEqual(stock.dataframe.shape, stock2.dataframe.shape)
df = stock2.dataframe
file = os.path.join(cache, "out_excel.xlsx")
if os.path.exists(file):
os.remove(file)
df.to_excel(file)
self.assertTrue(os.path.exists(file))
def test_save_stock_google(self):
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
cache = os.path.abspath(os.path.split(__file__)[0])
cache = os.path.join(cache, "temp_cache_file_google")
name = os.path.join(cache, "NASDAQ_GOOG.2000-01-03.2014-01-15.txt")
if os.path.exists(name):
os.remove(name)
stock = StockPrices(
"NASDAQ:GOOG",
url="google",
folder=cache,
end=datetime.datetime(
2014,
1,
15))
file = os.path.join(cache, "save.txt")
if os.path.exists(file):
os.remove(file)
stock.to_csv(file)
assert os.path.exists(file)
stock2 = StockPrices(file, sep="\t")
assert stock.dataframe.shape == stock2.dataframe.shape
df = stock2.dataframe
file = os.path.join(cache, "out_excel.xlsx")
if os.path.exists(file):
os.remove(file)
df.to_excel(file)
assert os.path.exists(file)
def test_covariance(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
cache = get_temp_folder(__file__, "temp_cache_cov")
stocks = [
StockPrices(t, folder=cache, url=TestStockHttp.source)
for t in TestStockHttp.ticks
]
dates = StockPrices.available_dates(stocks)
ok = dates[dates["missing"] == 0]
stocks = [v.keep_dates(ok) for v in stocks]
cov = StockPrices.covariance(stocks)
self.assertEqual(len(cov), 3)
cor = StockPrices.covariance(stocks, cov=False)
self.assertEqual(len(cor), 3)
t = TestStockHttp.ticks[1]
self.assertTrue(abs(cor.loc[t, t] - 1) < 1e-5)
self.assertTrue(abs(cor.iloc[2, 2] - 1) < 1e-5)
ret, mat = StockPrices.covariance(stocks, cov=False, ret=True)
self.assertEqual(len(ret), 3)
def test_available_dates(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
cache = get_temp_folder(__file__, "temp_cache_dates")
stocks = [
StockPrices(t, folder=cache, url=TestStockHttp.source)
for t in TestStockHttp.ticks
]
av = StockPrices.available_dates(stocks)
self.assertTrue(len(av) > 0)
missing = stocks[-1].missing(av)
self.assertTrue(missing is None or len(missing) > 0)
def test_available_dates(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
cache = os.path.abspath(os.path.split(__file__)[0])
cache = os.path.join(cache, "temp_cache_dates")
stocks = [
StockPrices("BNP.PA", folder=cache),
StockPrices("CA.PA", folder=cache),
StockPrices("SAF.PA", folder=cache),
]
av = StockPrices.available_dates(stocks)
assert len(av) > 0
missing = stocks[-1].missing(av)
assert missing is None or len(missing) > 0
def test_graph3(self) :
"""
This test is failing with Python 3.4 if many pictures are drawn.
"""
fLOG (__file__, self._testMethodName, OutputPrint = __name__ == "__main__")
cache = os.path.abspath(os.path.split(__file__)[0])
cache = os.path.join(cache, "temp_cache3")
stock = StockPrices ("BNP.PA", folder = cache)
stock2 = StockPrices ("CA.PA", folder = cache)
fig, ax, plt = stock.plot(figsize=(16,8))
fig, ax, plt = stock2.plot(existing=(fig,ax), axis=2)
img = os.path.abspath(os.path.join(os.path.split(__file__)[0],"temp_image3.png"))
if os.path.exists(img): os.remove(img)
fig.savefig(img)
assert os.path.exists(img)
def test_covariance(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
cache = os.path.abspath(os.path.split(__file__)[0])
cache = os.path.join(cache, "temp_cache_cov")
stocks = [
StockPrices("BNP.PA", folder=cache),
StockPrices("CA.PA", folder=cache),
StockPrices("SAF.PA", folder=cache),
]
dates = StockPrices.available_dates(stocks)
ok = dates[dates["missing"] == 0]
stocks = [v.keep_dates(ok) for v in stocks]
cov = StockPrices.covariance(stocks)
assert len(cov) == 3
cor = StockPrices.covariance(stocks, cov=False)
self.assertEqual(len(cor), 3)
assert abs(cor.ix["BNP.PA", "BNP.PA"] - 1) < 1e-5
assert abs(cor.ix[2, 2] - 1) < 1e-5
ret, mat = StockPrices.covariance(stocks, cov=False, ret=True)
self.assertEqual(len(ret), 3)
def test_index(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
cache = get_temp_folder(__file__, "temp_cache_index")
stock = StockPrices(TestStockHttp.ticks[0],
folder=cache,
end=datetime.datetime(2014, 1, 15),
url=TestStockHttp.source)
some = stock["2001-01-01":"2002-02-02"]
self.assertTrue(isinstance(some, StockPrices))
self.assertTrue(len(some) < 1000)
def test_index(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
cache = os.path.abspath(os.path.split(__file__)[0])
cache = os.path.join(cache, "temp_cache_index")
stock = StockPrices("BNP.PA",
folder=cache,
end=datetime.datetime(2014, 1, 15))
some = stock["2001-01-01":"2002-02-02"]
assert isinstance(some, StockPrices)
assert len(some) < 1000
def test_graph3(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
fix_tkinter_issues_virtualenv()
from matplotlib import pyplot as plt
cache = os.path.abspath(os.path.split(__file__)[0])
cache = os.path.join(cache, "temp_cache3")
stock = StockPrices(TestStockGraph3.tick[0],
folder=cache,
url=TestStockGraph3.source)
stock2 = StockPrices(TestStockGraph3.tick[1],
folder=cache,
url=TestStockGraph3.source)
fig, ax = plt.subplots(figsize=(16, 8))
ax = stock.plot(ax=ax)
ax = stock2.plot(ax=ax, axis=2)
img = os.path.abspath(
os.path.join(os.path.split(__file__)[0], "temp_image3.png"))
if os.path.exists(img):
os.remove(img)
fig.savefig(img)
plt.close('all')
self.assertExists(img)
def test_available_dates(self) :
fLOG (__file__, self._testMethodName, OutputPrint = __name__ == "__main__")
cache = os.path.abspath(os.path.split(__file__)[0])
cache = os.path.join(cache, "temp_cache2")
stocks = [ StockPrices ("BNP.PA", folder = cache),
StockPrices ("CA.PA", folder = cache),
StockPrices ("SAF.PA", folder = cache),
]
av = StockPrices.available_dates(stocks)
assert len(av)>0
missing = stocks[-1].missing(av)
assert missing is None or len(missing)>0
def test_save_stock_google(self):
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
cache = os.path.abspath(os.path.split(__file__)[0])
cache = os.path.join(cache, "temp_cache_file_google")
name = os.path.join(cache, TestLONGStockFile.tick.replace(
":", "_") + ".2000-01-03.2014-01-15.txt")
if os.path.exists(name):
os.remove(name)
try:
stock = StockPrices(TestLONGStockFile.tick, url=TestLONGStockFile.source,
folder=cache, end=datetime.datetime(2014, 1, 15))
except ImportError as e:
# There is an issue with pandas_datareader on travis.
# Not up to date with the latest pandas.
if is_travis_or_appveyor():
warnings.warn(
"Probably an issue with pandas_datareader.\n" + str(e))
return
else:
raise e
file = os.path.join(cache, "save.txt")
if os.path.exists(file):
os.remove(file)
stock.to_csv(file)
self.assertExists(file)
stock2 = StockPrices(file, sep="\t")
self.assertEqual(stock.dataframe.shape, stock2.dataframe.shape)
df = stock2.dataframe
file = os.path.join(cache, "out_excel.xlsx")
if os.path.exists(file):
os.remove(file)
df.to_excel(file)
self.assertExists(file)
def test_download_stock(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
cache = get_temp_folder(__file__, "temp_cache_download_http")
stock = StockPrices(TestStockHttp.ticks[0],
folder=cache,
end=datetime.datetime(2014, 1, 15),
url=TestStockHttp.source)
u = TestStockHttp.ticks[0].replace(":", "_")
name = os.path.join(cache, u + ".2000-01-03.2014-01-15.txt")
self.assertTrue(os.path.exists(name))
df = stock.dataframe
self.assertTrue(len(df) > 0)
def test_download_stock(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
cache = os.path.abspath(os.path.split(__file__)[0])
cache = os.path.join(cache, "temp_cache_download_http")
name = os.path.join(cache, "BNP.PA.2000-01-03.2014-01-15.txt")
if os.path.exists(name):
os.remove(name)
stock = StockPrices("BNP.PA",
folder=cache,
end=datetime.datetime(2014, 1, 15))
assert os.path.exists(name)
df = stock.dataframe
assert len(df) > 0
def test_no_wifi(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
data = os.path.abspath(os.path.split(__file__)[0])
data = os.path.join(data, "data")
file = os.path.join(data, "BNP.PA.2000-01-03.2014-02-24.txt")
fLOG(os.path.exists(file))
fLOG(file)
try:
StockPrices(file)
except StockPricesException as e:
if "pandas cannot parse the file" not in str(e):
raise Exception("unexpected error (2)") from e
if "Error tokenizing data" in str(e):
raise Exception("unexpected error (3)") from e
def test_download_stock_google(self):
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
cache = get_temp_folder(__file__, "temp_url_google")
try:
stock = StockPrices("NASDAQ:MSFT", folder=cache,
begin=datetime.datetime(2014, 1, 15))
except StockPricesHTTPException as e:
warnings.warn(str(e))
return
df = stock.dataframe
dmin = df.Date.min()
self.assertIn("2014", str(dmin))
self.assertTrue(stock.url_.startswith(
"https://finance.google.com/finance/historical?q=NASDAQ:MSFT&startdate=Jan+15%2C+2014"))
def test_download_stock_yahoo(self):
fLOG(__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
cache = get_temp_folder(__file__, "temp_url_yahoo")
exc = []
for n in range(0, 4):
stock = StockPrices("^FCHI",
folder=cache,
url=TestStockUrlYahoo.source,
begin=datetime.datetime(2014, 1, 15))
df = stock.dataframe
dmin, dmax = df.Date.min(), df.Date.max()
try:
self.assertIn("2014", str(dmin))
self.assertNotEqual(dmin, dmax)
if "^FCHI.2014-01-15" not in stock.url_:
raise AssertionError(stock.url_)
return
except AssertionError as e:
exc.append(e)
if len(exc) > 0:
e = exc[0]
raise AssertionError('nb tries={0}'.format(len(exc))) from e
def test_graph(self):
"""
This test is failing with Python 3.4 if many pictures are drawn.
"""
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
fix_tkinter_issues_virtualenv()
from matplotlib import pyplot as plt
cache = os.path.abspath(os.path.split(__file__)[0])
cache = os.path.join(cache, "temp_cache2")
stocks = [StockPrices("BNP.PA", folder=cache),
StockPrices("CA.PA", folder=cache),
StockPrices("SAF.PA", folder=cache),
]
if True:
fLOG("A", sys.executable)
fig, ax = plt.subplots()
ax = StockPrices.draw(
stocks, figsize=(
16, 8), field=[
"Adj Close", "Close"],
ax=ax)
img = os.path.abspath(
os.path.join(
os.path.split(__file__)[0],
"temp_image.png"))
if os.path.exists(img):
os.remove(img)
fig.savefig(img)
plt.close('all')
assert os.path.exists(img)
if True:
fLOG("B")
fig, ax = plt.subplots()
ax = StockPrices.draw(stocks, begin="2010-01-01", ax=ax)
img = os.path.abspath(
os.path.join(
os.path.split(__file__)[0],
"temp_image2.png"))
if os.path.exists(img):
os .remove(img)
fig.savefig(img)
plt.close('all')
assert os.path.exists(img)
if True:
fLOG("C")
fig, ax = plt.subplots()
ax = StockPrices.draw(stocks[:1], begin="2010-01-01", ax=ax)
img = os.path.abspath(
os.path.join(
os.path.split(__file__)[0],
"temp_image3.png"))
if os.path.exists(img):
os .remove(img)
fig.savefig(img)
plt.close('all')
assert os.path.exists(img)
fLOG("thisend")
def test_graph(self):
"""
This test is failing with Python 3.4 if many pictures are drawn.
"""
fLOG(
__file__,
self._testMethodName,
OutputPrint=__name__ == "__main__")
fix_tkinter_issues_virtualenv()
from matplotlib import pyplot as plt
cache = os.path.abspath(os.path.split(__file__)[0])
cache = os.path.join(cache, "temp_cache2")
stocks = [StockPrices(t, folder=cache, url=TestStockGraph.source)
for t in TestStockGraph.tick]
if True:
fLOG("A", sys.executable)
fig, ax = plt.subplots()
ax = StockPrices.draw(
stocks, figsize=(
16, 8), field=[
"Open", "Close"],
ax=ax)
img = os.path.abspath(
os.path.join(
os.path.split(__file__)[0],
"temp_image.png"))
if os.path.exists(img):
os.remove(img)
fig.savefig(img)
plt.close('all')
self.assertExists(img)
if True:
fLOG("B")
fig, ax = plt.subplots()
ax = StockPrices.draw(stocks, begin="2010-01-01", ax=ax)
img = os.path.abspath(
os.path.join(
os.path.split(__file__)[0],
"temp_image2.png"))
if os.path.exists(img):
os .remove(img)
fig.savefig(img)
plt.close('all')
self.assertExists(img)
if True:
fLOG("C")
fig, ax = plt.subplots()
ax = StockPrices.draw(stocks[:1], begin="2010-01-01", ax=ax)
img = os.path.abspath(
os.path.join(
os.path.split(__file__)[0],
"temp_image3.png"))
if os.path.exists(img):
os .remove(img)
fig.savefig(img)
plt.close('all')
self.assertExists(img)
fLOG("thisend")
