def test_date_range_BST(tickstore_lib):
DUMMY_DATA = [
{'a': 1.,
'b': 2.,
'index': dt(2013, 6, 1, 12, 00, tzinfo=mktz('Europe/London'))
},
{'a': 3.,
'b': 4.,
'index': dt(2013, 6, 1, 13, 00, tzinfo=mktz('Europe/London'))
},
]
tickstore_lib.chunk_size = 1
tickstore_lib.write('SYM', DUMMY_DATA)
df = tickstore_lib.read('SYM', columns=None)
assert_array_equal(df['b'].values, np.array([2., 4.]))
# df = tickstore_lib.read('SYM', columns=None, date_range=DateRange(dt(2013, 6, 1, 12),
# dt(2013, 6, 1, 13)))
# assert_array_equal(df['b'].values, np.array([2., 4.]))
df = tickstore_lib.read('SYM', columns=None, date_range=DateRange(dt(2013, 6, 1, 12, tzinfo=mktz('Europe/London')),
dt(2013, 6, 1, 13, tzinfo=mktz('Europe/London'))))
assert_array_equal(df['b'].values, np.array([2., 4.]))
df = tickstore_lib.read('SYM', columns=None, date_range=DateRange(dt(2013, 6, 1, 12, tzinfo=mktz('UTC')),
dt(2013, 6, 1, 13, tzinfo=mktz('UTC'))))
assert_array_equal(df['b'].values, np.array([4., ]))
def test_delete_daterange(tickstore_lib):
DUMMY_DATA = [
{'a': 1.,
'b': 2.,
'index': dt(2013, 1, 1, tzinfo=mktz('Europe/London'))
},
{'a': 3.,
'b': 4.,
'index': dt(2013, 2, 1, tzinfo=mktz('Europe/London'))
},
]
tickstore_lib._chunk_size = 1
tickstore_lib.write('SYM', DUMMY_DATA)
# Delete with a date-range
deleted = tickstore_lib.delete(
'SYM',
DateRange(
dt(2013, 1, 1, tzinfo=mktz('Europe/London')),
dt(2013, 2, 1, tzinfo=mktz('Europe/London')),
CLOSED_OPEN
)
)
assert deleted.deleted_count == 1
df = tickstore_lib.read('SYM', columns=None)
assert np.allclose(df['b'].values, np.array([4.]))
def test_date_range_default_timezone(tickstore_lib, tz_name):
"""
We assume naive datetimes are user-local
"""
DUMMY_DATA = [
{'a': 1.,
'b': 2.,
'index': dt(2013, 1, 1, tzinfo=mktz(tz_name))
},
# Half-way through the year
{'b': 3.,
'c': 4.,
'index': dt(2013, 7, 1, tzinfo=mktz(tz_name))
},
]
with patch('arctic.date._mktz.DEFAULT_TIME_ZONE_NAME', tz_name):
tickstore_lib._chunk_size = 1
tickstore_lib.write('SYM', DUMMY_DATA)
df = tickstore_lib.read('SYM', date_range=DateRange(20130101, 20130701), columns=None)
assert len(df) == 2
assert df.index[1] == dt(2013, 7, 1, tzinfo=mktz(tz_name))
assert df.index.tz == mktz(tz_name)
df = tickstore_lib.read('SYM', date_range=DateRange(20130101, 20130101), columns=None)
assert len(df) == 1
df = tickstore_lib.read('SYM', date_range=DateRange(20130701, 20130701), columns=None)
assert len(df) == 1
def test_delete(tickstore_lib):
DUMMY_DATA = [
{'a': 1.,
'b': 2.,
'index': dt(2013, 1, 1, tzinfo=mktz('Europe/London'))
},
{'a': 3.,
'b': 4.,
'index': dt(2013, 1, 30, tzinfo=mktz('Europe/London'))
},
]
tickstore_lib._chunk_size = 1
tickstore_lib.write('SYM', DUMMY_DATA)
deleted = tickstore_lib.delete('SYM')
assert deleted.deleted_count == 2
with pytest.raises(NoDataFoundException):
tickstore_lib.read('SYM', date_range=DateRange(20130102), columns=None)
# Delete with a date-range
tickstore_lib.write('SYM', DUMMY_DATA)
deleted = tickstore_lib.delete(
'SYM',
DateRange(
dt(2013, 1, 1, tzinfo=mktz('Europe/London')),
dt(2013, 1, 2, tzinfo=mktz('Europe/London'))
)
)
assert deleted.deleted_count == 1
df = tickstore_lib.read('SYM', columns=None)
assert np.allclose(df['b'].values, np.array([4.]))
def test_datetime_roundtrip_est_tz():
pdt = datetime.datetime(2012, 6, 12, 12, 12, 12, 123000, tzinfo=mktz('EST'))
pdt2 = ms_to_datetime(datetime_to_ms(pdt))
assert pdt2.replace(tzinfo=mktz()) == pdt
pdt = datetime.datetime(2012, 1, 12, 12, 12, 12, 123000, tzinfo=mktz('EST'))
pdt2 = ms_to_datetime(datetime_to_ms(pdt))
assert pdt2.replace(tzinfo=mktz()) == pdt
def test_datetime_roundtrip_lon_tz():
pdt = datetime.datetime(2012, 6, 12, 12, 12, 12, 123000, tzinfo=mktz('Europe/London'))
pdt2 = ms_to_datetime(datetime_to_ms(pdt))
assert pdt2 == pdt.replace(tzinfo=None)
pdt = datetime.datetime(2012, 1, 12, 12, 12, 12, 123000, tzinfo=mktz('Europe/London'))
pdt2 = ms_to_datetime(datetime_to_ms(pdt))
assert pdt2 == pdt.replace(tzinfo=None)
def test_daterange_closedclosed_no_tz():
date_range = DateRange(dt(2013, 1, 1),
dt(2014, 2, 1), OPEN_OPEN)
expected = DateRange(dt(2013, 1, 1, 0, 0, 0, 1000, tzinfo=mktz()),
dt(2014, 1, 31, 23, 59, 59, 999000, tzinfo=mktz()),
CLOSED_CLOSED)
act = to_pandas_closed_closed(date_range)
assert act == expected
def test_read_strings(tickstore_lib):
df = pd.DataFrame(data={'data': ['A', 'B', 'C']},
index=pd.Index(data=[dt(2016, 1, 1, 00, tzinfo=mktz('UTC')),
dt(2016, 1, 2, 00, tzinfo=mktz('UTC')),
dt(2016, 1, 3, 00, tzinfo=mktz('UTC'))], name='date'))
tickstore_lib.write('test', df)
read_df = tickstore_lib.read('test')
assert(all(read_df['data'].values == df['data'].values))
def test_datetime_roundtrip_local_tz():
pdt = datetime.datetime(2012, 6, 12, 12, 12, 12, 123000, tzinfo=mktz(DEFAULT_TIME_ZONE_NAME))
pdt2 = ms_to_datetime(datetime_to_ms(pdt))
assert pdt2 == pdt.replace(tzinfo=None)
pdt = datetime.datetime(2012, 1, 12, 12, 12, 12, 123000, tzinfo=mktz(DEFAULT_TIME_ZONE_NAME))
pdt2 = ms_to_datetime(datetime_to_ms(pdt))
assert pdt2 == pdt.replace(tzinfo=None)
def test_read_unicode_strings(tickstore_lib):
df = pd.DataFrame(data={'data': [u'一', u'二', u'三']}, # Chinese character [one, two , three]
index=pd.Index(data=[dt(2016, 1, 1, 00, tzinfo=mktz('UTC')),
dt(2016, 1, 2, 00, tzinfo=mktz('UTC')),
dt(2016, 1, 3, 00, tzinfo=mktz('UTC'))], name='date'))
tickstore_lib.write('test', df)
read_df = tickstore_lib.read('test')
assert(all(read_df['data'].values == df['data'].values))
def test_datetime_roundtrip_local_tz():
pdt = datetime.datetime(2012, 6, 12, 12, 12, 12, 123000, tzinfo=mktz())
pdt2 = ms_to_datetime(datetime_to_ms(pdt))
assert pdt2 == pdt
pdt = datetime.datetime(2012, 1, 12, 12, 12, 12, 123000, tzinfo=mktz())
pdt2 = ms_to_datetime(datetime_to_ms(pdt))
assert pdt2 == pdt
def test_ts_write_pandas(tickstore_lib):
data = DUMMY_DATA
tickstore_lib.write('SYM', data)
data = tickstore_lib.read('SYM', columns=None).tz_localize(mktz('Europe/London'))
tickstore_lib.delete('SYM')
tickstore_lib.write('SYM', data)
read = tickstore_lib.read('SYM', columns=None).tz_localize(mktz('Europe/London'))
assert_frame_equal(read, data, check_names=False)
def assert_roundtrip(tz):
ts = datetime.datetime(1982, 7, 1, 16, 5)
ts1 = ts.replace(tzinfo=tz)
ts2 = ms_to_datetime(datetime_to_ms(ts1.astimezone(mktz("UTC"))), tz)
ts1 = ts1.replace(tzinfo=None) if tz == mktz() else ts1
#logger.info(ts2.tzinfo)
assert(ts2.hour == ts1.hour)
# assert(ts2.tzinfo == ts1.tzinfo)
assert ts2 == ts1
def test_mktz():
tz = mktz("Europe/London")
d = dt(2012, 2, 2, tzinfo=tz)
assert d.tzname() == 'GMT'
d = dt(2012, 7, 2, tzinfo=tz)
assert d.tzname() == 'BST'
tz = mktz('UTC')
d = dt(2012, 2, 2, tzinfo=tz)
assert d.tzname() == 'UTC'
d = dt(2012, 7, 2, tzinfo=tz)
assert d.tzname() == 'UTC' # --------replace_empty_timezones_with_default -----------------
def test_read_out_of_order(tickstore_lib):
data = [{'A': 120, 'D': 1}, {'A': 122, 'B': 2.0}, {'A': 3, 'B': 3.0, 'D': 1}]
tick_index = [dt(2013, 6, 1, 12, 00, tzinfo=mktz('UTC')),
dt(2013, 6, 1, 11, 00, tzinfo=mktz('UTC')), # Out-of-order
dt(2013, 6, 1, 13, 00, tzinfo=mktz('UTC'))]
data = pd.DataFrame(data, index=tick_index)
tickstore_lib._chunk_size = 3
tickstore_lib.write('SYM', data)
tickstore_lib.read('SYM', columns=None)
assert len(tickstore_lib.read('SYM', columns=None, date_range=DateRange(dt(2013, 6, 1, tzinfo=mktz('UTC')), dt(2013, 6, 2, tzinfo=mktz('UTC'))))) == 3
assert len(tickstore_lib.read('SYM', columns=None, date_range=DateRange(dt(2013, 6, 1, tzinfo=mktz('UTC')), dt(2013, 6, 1, 12, tzinfo=mktz('UTC'))))) == 2
def test_read_with_image(tickstore_lib):
DUMMY_DATA = [
{'a': 1.,
'index': dt(2013, 1, 1, 11, 00, tzinfo=mktz('Europe/London'))
},
{
'b': 4.,
'index': dt(2013, 1, 1, 12, 00, tzinfo=mktz('Europe/London'))
},
]
# Add an image
tickstore_lib.write('SYM', DUMMY_DATA)
tickstore_lib._collection.update_one({},
{'$set':
{'im': {'i':
{'a': 37.,
'c': 2.,
},
't': dt(2013, 1, 1, 10, tzinfo=mktz('Europe/London'))
}
}
}
)
dr = DateRange(dt(2013, 1, 1), dt(2013, 1, 2))
# tickstore_lib.read('SYM', columns=None)
df = tickstore_lib.read('SYM', columns=None, date_range=dr)
assert df['a'][0] == 1
# Read with the image as well
df = tickstore_lib.read('SYM', columns=None, date_range=dr, include_images=True)
assert set(df.columns) == set(('a', 'b', 'c'))
assert_array_equal(df['a'].values, np.array([37, 1, np.nan]))
assert_array_equal(df['b'].values, np.array([np.nan, np.nan, 4]))
assert_array_equal(df['c'].values, np.array([2, np.nan, np.nan]))
assert df.index[0] == dt(2013, 1, 1, 10)
assert df.index[1] == dt(2013, 1, 1, 11)
assert df.index[2] == dt(2013, 1, 1, 12)
df = tickstore_lib.read('SYM', columns=('a', 'b'), date_range=dr, include_images=True)
assert set(df.columns) == set(('a', 'b'))
assert_array_equal(df['a'].values, np.array([37, 1, np.nan]))
assert_array_equal(df['b'].values, np.array([np.nan, np.nan, 4]))
assert df.index[0] == dt(2013, 1, 1, 10)
assert df.index[1] == dt(2013, 1, 1, 11)
assert df.index[2] == dt(2013, 1, 1, 12)
df = tickstore_lib.read('SYM', columns=['c'], date_range=dr, include_images=True)
assert set(df.columns) == set(['c'])
assert_array_equal(df['c'].values, np.array([2, np.nan, np.nan]))
assert df.index[0] == dt(2013, 1, 1, 10)
assert df.index[1] == dt(2013, 1, 1, 11)
assert df.index[2] == dt(2013, 1, 1, 12)
def test_should_list_symbols_from_the_underlying_library(toplevel_tickstore, arctic, start, end, startr, endr):
arctic.initialize_library('FEED_2010.LEVEL1', tickstore.TICK_STORE_TYPE)
arctic.initialize_library('FEED_2011.LEVEL1', tickstore.TICK_STORE_TYPE)
toplevel_tickstore.add(DateRange(start=dt(2010, 1, 1), end=dt(2010, 12, 31, 23, 59, 59, 999000)), 'FEED_2010.LEVEL1')
toplevel_tickstore.add(DateRange(start=dt(2011, 1, 1), end=dt(2011, 12, 31, 23, 59, 59, 999000)), 'FEED_2011.LEVEL1')
dtstart = dt(2010, 1, 1, tzinfo=mktz('Europe/London'))
for i in range(10):
dates = pd.date_range(dtstart, periods=50, tz=mktz('Europe/London'))
df = pd.DataFrame(np.random.randn(50, 4), index=dates, columns=list('ABCD'))
dtstart = dates[-1] + dtd(days=1)
toplevel_tickstore.write('sym' + str(i), df)
expected_symbols = ['sym' + str(i) for i in range(startr, endr)]
assert expected_symbols == toplevel_tickstore.list_symbols(DateRange(start=start, end=end))
def test_should_write_top_level_with_list_of_dicts(arctic):
arctic.initialize_library('FEED_2010.LEVEL1', tickstore.TICK_STORE_TYPE)
arctic.initialize_library('FEED_2011.LEVEL1', tickstore.TICK_STORE_TYPE)
arctic.initialize_library('FEED.LEVEL1', toplevel.TICK_STORE_TYPE)
toplevel_tickstore = arctic['FEED.LEVEL1']
dates = pd.date_range('20101201', periods=57, tz=mktz('Europe/London'))
data = [{'index': dates[i], 'a': i} for i in range(len(dates))]
expected = pd.DataFrame(np.arange(57, dtype=np.float64), index=dates, columns=list('a'))
toplevel_tickstore.write('blah', data)
res = toplevel_tickstore.read('blah', DateRange(start=dt(2010, 12, 1), end=dt(2011, 2, 1)), columns=list('a'))
assert_frame_equal(expected, res.tz_convert(mktz('Europe/London')))
lib2010 = arctic['FEED_2010.LEVEL1']
res = lib2010.read('blah', DateRange(start=dt(2010, 12, 1), end=dt(2011, 1, 1)))
assert_frame_equal(expected[dt(2010, 12, 1): dt(2010, 12, 31)], res.tz_convert(mktz('Europe/London')))
def test_objects_fail(tickstore_lib):
class Fake(object):
def __init__(self, val):
self.val = val
def fake(self):
return self.val
df = pd.DataFrame(data={'data': [Fake(1), Fake(2)]},
index=pd.Index(data=[dt(2016, 1, 1, 00, tzinfo=mktz('UTC')),
dt(2016, 1, 2, 00, tzinfo=mktz('UTC'))], name='date'))
with pytest.raises(Exception) as e:
tickstore_lib.write('test', df)
assert('Casting object column to string failed' in str(e))
def test_read_utf8_strings(tickstore_lib):
data = ['一', '二', '三'] # Chinese character [one, two , three]
if six.PY2:
utf8_data = data
unicode_data = [s.decode('utf8') for s in data]
else:
utf8_data = [s.encode('utf8') for s in data]
unicode_data = data
df = pd.DataFrame(data={'data': utf8_data},
index=pd.Index(data=[dt(2016, 1, 1, 00, tzinfo=mktz('UTC')),
dt(2016, 1, 2, 00, tzinfo=mktz('UTC')),
dt(2016, 1, 3, 00, tzinfo=mktz('UTC'))], name='date'))
tickstore_lib.write('test', df)
read_df = tickstore_lib.read('test')
assert(all(read_df['data'].values == np.array(unicode_data)))
def test_should_return_data_when_date_range_falls_in_a_single_underlying_library(toplevel_tickstore, arctic):
arctic.initialize_library('FEED_2010.LEVEL1', tickstore.TICK_STORE_TYPE)
tstore = arctic['FEED_2010.LEVEL1']
arctic.initialize_library('test_current.toplevel_tickstore', tickstore.TICK_STORE_TYPE)
tickstore_current = arctic['test_current.toplevel_tickstore']
toplevel_tickstore._collection.insert_one({'start': dt(2010, 1, 1),
'end': dt(2010, 12, 31, 23, 59, 59),
'library_name': 'FEED_2010.LEVEL1'})
dates = pd.date_range('20100101', periods=6, tz=mktz('Europe/London'))
df = pd.DataFrame(np.random.randn(6, 4), index=dates, columns=list('ABCD'))
tstore.write('blah', df)
tickstore_current.write('blah', df)
res = toplevel_tickstore.read('blah', DateRange(start=dt(2010, 1, 1), end=dt(2010, 1, 6)), list('ABCD'))
assert_frame_equal(df, res.tz_convert(mktz('Europe/London')))
def test_should_write_top_level_with_correct_timezone(arctic):
# Write timezone aware data and read back in UTC
utc = mktz('UTC')
arctic.initialize_library('FEED_2010.LEVEL1', tickstore.TICK_STORE_TYPE)
arctic.initialize_library('FEED_2011.LEVEL1', tickstore.TICK_STORE_TYPE)
arctic.initialize_library('FEED.LEVEL1', toplevel.TICK_STORE_TYPE)
toplevel_tickstore = arctic['FEED.LEVEL1']
dates = pd.date_range('20101230220000', periods=10, tz=mktz('America/New_York')) # 10pm New York time is 3am next day UTC
data = [{'index': dates[i], 'a': i} for i in range(len(dates))]
expected = pd.DataFrame(np.arange(len(dates), dtype=np.float64), index=dates.tz_convert(utc), columns=list('a'))
toplevel_tickstore.write('blah', data)
res = toplevel_tickstore.read('blah', DateRange(start=dt(2010, 1, 1), end=dt(2011, 12, 31)), columns=list('a')).tz_convert(utc)
assert_frame_equal(expected, res)
lib2010 = arctic['FEED_2010.LEVEL1']
# Check that only one point was written into 2010 being 3am on 31st
assert len(lib2010.read('blah', DateRange(start=dt(2010, 12, 1), end=dt(2011, 1, 1)))) == 1
def test_should_return_data_when_date_range_spans_libraries(toplevel_tickstore, arctic):
arctic.initialize_library('FEED_2010.LEVEL1', tickstore.TICK_STORE_TYPE)
arctic.initialize_library('FEED_2011.LEVEL1', tickstore.TICK_STORE_TYPE)
tickstore_2010 = arctic['FEED_2010.LEVEL1']
tickstore_2011 = arctic['FEED_2011.LEVEL1']
toplevel_tickstore.add(DateRange(start=dt(2010, 1, 1), end=dt(2010, 12, 31, 23, 59, 59, 999000)), 'FEED_2010.LEVEL1')
toplevel_tickstore.add(DateRange(start=dt(2011, 1, 1), end=dt(2011, 12, 31, 23, 59, 59, 999000)), 'FEED_2011.LEVEL1')
dates = pd.date_range('20100101', periods=6, tz=mktz('Europe/London'))
df_10 = pd.DataFrame(np.random.randn(6, 4), index=dates, columns=list('ABCD'))
tickstore_2010.write('blah', df_10)
dates = pd.date_range('20110101', periods=6, tz=mktz('Europe/London'))
df_11 = pd.DataFrame(np.random.randn(6, 4), index=dates, columns=list('ABCD'))
tickstore_2011.write('blah', df_11)
res = toplevel_tickstore.read('blah', DateRange(start=dt(2010, 1, 2), end=dt(2011, 1, 4)), list('ABCD'))
expected_df = pd.concat([df_10[1:], df_11[:4]])
assert_frame_equal(expected_df, res.tz_convert(mktz('Europe/London')))
def test_read(tickstore_lib):
data = [{'ASK': 1545.25,
'ASKSIZE': 1002.0,
'BID': 1545.0,
'BIDSIZE': 55.0,
'CUMVOL': 2187387.0,
'DELETED_TIME': 0,
'INSTRTYPE': 'FUT',
'PRICE': 1545.0,
'SIZE': 1.0,
'TICK_STATUS': 0,
'TRADEHIGH': 1561.75,
'TRADELOW': 1537.25,
'index': 1185076787070},
{'CUMVOL': 354.0,
'DELETED_TIME': 0,
'PRICE': 1543.75,
'SIZE': 354.0,
'TRADEHIGH': 1543.75,
'TRADELOW': 1543.75,
'index': 1185141600600}]
tickstore_lib.write('FEED::SYMBOL', data)
df = tickstore_lib.read('FEED::SYMBOL', columns=['BID', 'ASK', 'PRICE'])
assert_array_equal(df['ASK'].values, np.array([1545.25, np.nan]))
assert_array_equal(df['BID'].values, np.array([1545, np.nan]))
assert_array_equal(df['PRICE'].values, np.array([1545, 1543.75]))
assert_array_equal(df.index.values.astype('object'), np.array([1185076787070000000, 1185141600600000000]))
assert tickstore_lib._collection.find_one()['c'] == 2
assert df.index.tzinfo == mktz()
async def process_order(orders):
async for order in orders.group_by(Order.model_id):
print("1. ORDER recevied.")
if not order.testing:
# [order.symbol]
model_account = orders_for_account[order.model_id]
print("1. Send to Arctic DB")
data = order.asdict()
data["index"] = datetime.datetime.fromtimestamp(
int(order.timestamps) * 1000, tzinfo=mktz("UTC+8"))
lib.write(symbol=f"ORDER:{Order.model_id}", data=[order.asdict()])
await test_order.order_send_to_db.send(order)
account = model_account.account
if account.get(order.symbol, None) is None:
account[order.symbol] = Position(amount=0, price=0) + order
else:
account[order.symbol] += order
model_account.account = account
orders_for_account[order.model_id] = model_account
await test_order.order_executed.send(order.id)
yield order
def test_list_versions_localTime():
# Object ID's are stored in UTC. We need to ensure that the returned times
# for versions are in the local TimeZone
vs = create_autospec(VersionStore, instance=True,
_versions=Mock())
vs._find_snapshots.return_value = 'snap'
date = dt(2013, 4, 1, 9, 0)
vs._versions.find.return_value = [{'_id': bson.ObjectId.from_datetime(date),
'symbol': 's', 'version': 10}]
version = list(VersionStore.list_versions(vs, "symbol"))[0]
local_date = date.replace(tzinfo=mktz("UTC")).astimezone(mktz()).replace(tzinfo=None)
assert version == {'symbol': version['symbol'], 'version': version['version'],
# We return naive datetimes in 'default' time, which is London for us
'date': local_date,
'snapshots': 'snap'}
def test_list_versions_localTime():
# Object ID's are stored in UTC. We need to ensure that the returned times
# for versions are in the local TimeZone
vs = create_autospec(VersionStore,
instance=True,
_versions=Mock(),
_snapshots=Mock())
mocked_snap_resp = [{'_id': 'abcde', 'name': 'snap'}]
vs._snapshots.find.return_value = mocked_snap_resp
vs._snapshots.find_one.return_value = mocked_snap_resp
date = dt(2013, 4, 1, 9, 0)
vs._versions.find.return_value = [{
'_id': bson.ObjectId.from_datetime(date),
'symbol': 's',
'version': 10,
'metadata': None,
'parent': [mocked_snap_resp[0]['_id']]
}]
version = list(VersionStore.list_versions(vs, "symbol"))[0]
local_date = date.replace(tzinfo=mktz("UTC"))
assert version == {
'symbol': version['symbol'],
'version': version['version'],
# We return naive datetimes in 'default' time, which is London for us
'date': local_date,
'snapshots': ['snap'],
'deleted': False
}
def test_should_return_data_when_date_range_spans_libraries_even_if_one_returns_nothing(toplevel_tickstore, arctic):
arctic.initialize_library('FEED_2010.LEVEL1', tickstore.TICK_STORE_TYPE)
arctic.initialize_library('FEED_2011.LEVEL1', tickstore.TICK_STORE_TYPE)
tickstore_2010 = arctic['FEED_2010.LEVEL1']
tickstore_2011 = arctic['FEED_2011.LEVEL1']
toplevel_tickstore.add(DateRange(start=dt(2010, 1, 1), end=dt(2010, 12, 31, 23, 59, 59, 999000)), 'FEED_2010.LEVEL1')
toplevel_tickstore.add(DateRange(start=dt(2011, 1, 1), end=dt(2011, 12, 31, 23, 59, 59, 999000)), 'FEED_2011.LEVEL1')
dates = pd.date_range('20100101', periods=6, tz=mktz('Europe/London'))
df_10 = pd.DataFrame(np.random.randn(6, 4), index=dates, columns=list('ABCD'))
tickstore_2010.write('blah', df_10)
dates = pd.date_range('20110201', periods=6, tz=mktz('Europe/London'))
df_11 = pd.DataFrame(np.random.randn(6, 4), index=dates, columns=list('ABCD'))
tickstore_2011.write('blah', df_11)
res = toplevel_tickstore.read('blah', DateRange(start=dt(2010, 1, 2), end=dt(2011, 1, 4)), list('ABCD'))
expected_df = df_10[1:]
assert_frame_equal(expected_df, res.tz_convert(mktz('Europe/London')))
def test_read_longs(tickstore_lib):
DUMMY_DATA = [
{'a': 1,
'index': dt(2013, 6, 1, 12, 00, tzinfo=mktz('Europe/London'))
},
{
'b': 4,
'index': dt(2013, 6, 1, 13, 00, tzinfo=mktz('Europe/London'))
},
]
tickstore_lib.chunk_size = 3
tickstore_lib.write('SYM', DUMMY_DATA)
tickstore_lib.read('SYM', columns=None)
read = tickstore_lib.read('SYM', columns=None, date_range=DateRange(dt(2013, 6, 1), dt(2013, 6, 2)))
assert read['a'][0] == 1
assert np.isnan(read['b'][0])
def test_should_write_top_level_with_correct_timezone(arctic):
# Write timezone aware data and read back in UTC
utc = mktz('UTC')
arctic.initialize_library('FEED_2010.LEVEL1', tickstore.TICK_STORE_TYPE)
arctic.initialize_library('FEED_2011.LEVEL1', tickstore.TICK_STORE_TYPE)
arctic.initialize_library('FEED.LEVEL1', toplevel.TICK_STORE_TYPE)
toplevel_tickstore = arctic['FEED.LEVEL1']
dates = pd.date_range('20101230220000', periods=10, tz=mktz('America/New_York')) # 10pm New York time is 3am next day UTC
data = [{'index': dates[i], 'a': i} for i in range(len(dates))]
expected = pd.DataFrame(np.arange(len(dates), dtype=np.float64), index=dates.tz_convert(utc), columns=list('a'))
toplevel_tickstore.write('blah', data)
res = toplevel_tickstore.read('blah', DateRange(start=dt(2010, 1, 1), end=dt(2011, 12, 31)), columns=list('a')).tz_convert(utc)
assert_frame_equal(expected, res)
lib2010 = arctic['FEED_2010.LEVEL1']
# Check that only one point was written into 2010 being 3am on 31st
assert len(lib2010.read('blah', DateRange(start=dt(2010, 12, 1), end=dt(2011, 1, 1)))) == 1
def test_utc_dt_to_local_dt():
with pytest.raises(ValueError):
assert (utc_dt_to_local_dt(
dt(2000, 1, 1, 0, 0, 0, tzinfo=mktz("Asia/Shanghai"))))
utc_time = dt(2000, 1, 1, 10, 0, 0)
pek_time = utc_dt_to_local_dt(utc_time) # GMT +0800
assert (pek_time.hour - utc_time.hour == 8)
def assert_roundtrip(tz):
ts = datetime.datetime(1982, 7, 1, 16, 5)
ts1 = ts.replace(tzinfo=tz)
ts2 = ms_to_datetime(datetime_to_ms(ts1.astimezone(mktz("UTC"))), tz)
assert(ts2.hour == ts1.hour)
assert ts2 == ts1
def assert_roundtrip(tz):
ts = datetime.datetime(1982, 7, 1, 16, 5)
ts1 = ts.replace(tzinfo=tz)
ts2 = ms_to_datetime(datetime_to_ms(ts1.astimezone(mktz("UTC"))), tz)
assert (ts2.hour == ts1.hour)
assert ts2 == ts1
def test_read_out_of_order(tickstore_lib):
DUMMY_DATA = [
{
'a': 1.,
'b': 2.,
'index': dt(2013, 6, 1, 12, 00, tzinfo=mktz('UTC'))
},
{
'a': 3.,
'b': 4.,
'index': dt(2013, 6, 1, 11, 00, tzinfo=mktz('UTC')) # Out-of-order
},
{
'a': 3.,
'b': 4.,
'index': dt(2013, 6, 1, 13, 00, tzinfo=mktz('UTC'))
},
]
tickstore_lib.chunk_size = 3
tickstore_lib.write('SYM', DUMMY_DATA)
tickstore_lib.read('SYM', columns=None)
assert len(
tickstore_lib.read('SYM',
columns=None,
date_range=DateRange(
dt(2013, 6, 1, tzinfo=mktz('UTC')),
dt(2013, 6, 2, tzinfo=mktz('UTC'))))) == 3
assert len(
tickstore_lib.read('SYM',
columns=None,
date_range=DateRange(
dt(2013, 6, 1, tzinfo=mktz('UTC')),
dt(2013, 6, 1, 12, tzinfo=mktz('UTC'))))) == 2
def test_read_out_of_order(tickstore_lib):
data = [{
'A': 120,
'D': 1
}, {
'A': 122,
'B': 2.0
}, {
'A': 3,
'B': 3.0,
'D': 1
}]
tick_index = [
dt(2013, 6, 1, 12, 00, tzinfo=mktz('UTC')),
dt(2013, 6, 1, 11, 00, tzinfo=mktz('UTC')), # Out-of-order
dt(2013, 6, 1, 13, 00, tzinfo=mktz('UTC'))
]
data = pd.DataFrame(data, index=tick_index)
tickstore_lib._chunk_size = 3
tickstore_lib.write('SYM', data)
tickstore_lib.read('SYM', columns=None)
assert len(
tickstore_lib.read('SYM',
columns=None,
date_range=DateRange(
dt(2013, 6, 1, tzinfo=mktz('UTC')),
dt(2013, 6, 2, tzinfo=mktz('UTC'))))) == 3
assert len(
tickstore_lib.read('SYM',
columns=None,
date_range=DateRange(
dt(2013, 6, 1, tzinfo=mktz('UTC')),
dt(2013, 6, 1, 12, tzinfo=mktz('UTC'))))) == 2
def test_read_as_of_NotNaive():
# When we do a read, with naive as_of, that as_of is treated in London Time.
vs = create_autospec(VersionStore, instance=True,
_versions=Mock(), _allow_secondary=False)
VersionStore._read_metadata(vs, 'symbol', dt(2013, 4, 1, 9, 0, tzinfo=mktz('Europe/Paris')))
versions = vs._versions.with_options.return_value
versions.find_one.assert_called_once_with({'symbol':'symbol', '_id':
{'$lt': bson.ObjectId.from_datetime(dt(2013, 4, 1, 9, 0, tzinfo=mktz('Europe/Paris')) + dtd(seconds=1))}},
sort=[('_id', pymongo.DESCENDING)])
def test_utc_dt_to_local_dt():
with pytest.raises(ValueError):
assert(utc_dt_to_local_dt(
dt(2000, 1, 1, 0, 0, 0, tzinfo=mktz("Asia/Shanghai"))
))
utc_time = dt(2000, 1, 1, 10, 0, 0)
pek_time = utc_dt_to_local_dt(utc_time) # GMT +0800
assert(pek_time.hour - utc_time.hour == 8)
def test_objects_fail(tickstore_lib):
class Fake(object):
def __init__(self, val):
self.val = val
def fake(self):
return self.val
df = pd.DataFrame(data={'data': [Fake(1), Fake(2)]},
index=pd.Index(data=[
dt(2016, 1, 1, 00, tzinfo=mktz('UTC')),
dt(2016, 1, 2, 00, tzinfo=mktz('UTC'))
],
name='date'))
with pytest.raises(Exception) as e:
tickstore_lib.write('test', df)
assert ('Casting object column to string failed' in str(e.value))
def test_delete_daterange(tickstore_lib):
DUMMY_DATA = [
{'a': 1.,
'b': 2.,
'index': dt(2013, 1, 1, tzinfo=mktz('Europe/London'))
},
{'a': 3.,
'b': 4.,
'index': dt(2013, 2, 1, tzinfo=mktz('Europe/London'))
},
]
tickstore_lib.chunk_size = 1
tickstore_lib.write('SYM', DUMMY_DATA)
# Delete with a date-range
tickstore_lib.delete('SYM', DateRange(dt(2013, 1, 1, tzinfo=mktz('Europe/London')), dt(2013, 2, 1, tzinfo=mktz('Europe/London')), CLOSED_OPEN))
df = tickstore_lib.read('SYM', columns=None)
assert np.allclose(df['b'].values, np.array([4.]))
def test_date_range_end_not_in_range(tickstore_lib):
DUMMY_DATA = [
{'a': 1.,
'b': 2.,
'index': dt(2013, 1, 1, tzinfo=mktz('Europe/London'))
},
{'b': 3.,
'c': 4.,
'index': dt(2013, 1, 2, 10, 1, tzinfo=mktz('Europe/London'))
},
]
tickstore_lib.chunk_size = 1
tickstore_lib.write('SYM', DUMMY_DATA)
with patch.object(tickstore_lib._collection, 'find', side_effect=tickstore_lib._collection.find) as f:
df = tickstore_lib.read('SYM', date_range=DateRange(20130101, dt(2013, 1, 2, 9, 0)), columns=None)
assert_array_equal(df['b'].values, np.array([2.]))
assert tickstore_lib._collection.find(f.call_args_list[-1][0][0]).count() == 1
def test_date_range_end_not_in_range(tickstore_lib):
DUMMY_DATA = [
{'a': 1.,
'b': 2.,
'index': dt(2013, 1, 1, tzinfo=mktz('Europe/London'))
},
{'b': 3.,
'c': 4.,
'index': dt(2013, 1, 2, 10, 1, tzinfo=mktz('Europe/London'))
},
]
tickstore_lib._chunk_size = 1
tickstore_lib.write('SYM', DUMMY_DATA)
with patch.object(tickstore_lib._collection, 'find', side_effect=tickstore_lib._collection.find) as f:
df = tickstore_lib.read('SYM', date_range=DateRange(20130101, dt(2013, 1, 2, 9, 0)), columns=None)
assert_array_equal(df['b'].values, np.array([2.]))
assert tickstore_lib._collection.find(f.call_args_list[-1][0][0]).count() == 1
def test_read_utf8_strings(tickstore_lib):
data = ['一', '二', '三'] # Chinese character [one, two , three]
if six.PY2:
utf8_data = data
unicode_data = [s.decode('utf8') for s in data]
else:
utf8_data = [s.encode('utf8') for s in data]
unicode_data = data
df = pd.DataFrame(data={'data': utf8_data},
index=pd.Index(data=[
dt(2016, 1, 1, 00, tzinfo=mktz('UTC')),
dt(2016, 1, 2, 00, tzinfo=mktz('UTC')),
dt(2016, 1, 3, 00, tzinfo=mktz('UTC'))
],
name='date'))
tickstore_lib.write('test', df)
read_df = tickstore_lib.read('test')
assert (all(read_df['data'].values == np.array(unicode_data)))
def test_should_successfully_do_a_roundtrip_write_and_read_spanning_multiple_underlying_libraries(toplevel_tickstore, arctic):
arctic.initialize_library('FEED_2010.LEVEL1', tickstore.TICK_STORE_TYPE)
arctic.initialize_library('FEED_2011.LEVEL1', tickstore.TICK_STORE_TYPE)
arctic.initialize_library('test_current.toplevel_tickstore', tickstore.TICK_STORE_TYPE)
toplevel_tickstore.add(DateRange(start=dt(2010, 1, 1), end=dt(2010, 12, 31, 23, 59, 59, 999000)), 'FEED_2010.LEVEL1')
toplevel_tickstore.add(DateRange(start=dt(2011, 1, 1), end=dt(2011, 12, 31, 23, 59, 59, 999000)), 'FEED_2011.LEVEL1')
tickstore_current = arctic['test_current.toplevel_tickstore']
dates = pd.date_range('20101201', periods=57, tz=mktz('Europe/London'))
data = pd.DataFrame(np.random.randn(57, 4), index=dates, columns=list('ABCD'))
toplevel_tickstore.write('blah', data)
tickstore_current.write('blah', data)
res = toplevel_tickstore.read('blah', DateRange(start=dt(2010, 12, 1), end=dt(2011, 2, 1)), columns=list('ABCD'))
assert_frame_equal(data, res.tz_convert(mktz('Europe/London')))
lib2010 = arctic['FEED_2010.LEVEL1']
res = lib2010.read('blah', DateRange(start=dt(2010, 12, 1), end=dt(2011, 1, 1)), columns=list('ABCD'))
assert_frame_equal(data[dt(2010, 12, 1): dt(2010, 12, 31)], res.tz_convert(mktz('Europe/London')))
lib2011 = arctic['FEED_2011.LEVEL1']
res = lib2011.read('blah', DateRange(start=dt(2011, 1, 1), end=dt(2011, 2, 1)), columns=list('ABCD'))
assert_frame_equal(data[dt(2011, 1, 1): dt(2011, 2, 1)], res.tz_convert(mktz('Europe/London')))
def test_read_with_image(tickstore_lib):
DUMMY_DATA = [
{
'a': 1.,
'index': dt(2013, 6, 1, 12, 00, tzinfo=mktz('Europe/London'))
},
{
'b': 4.,
'index': dt(2013, 6, 1, 13, 00, tzinfo=mktz('Europe/London'))
},
]
# Add an image
tickstore_lib.write('SYM', DUMMY_DATA)
tickstore_lib._collection.update_one({}, {
'$set': {
'im': {
'i': {
'a': 37.,
'c': 2.,
},
't': dt(2013, 6, 1, 11, 0)
}
}
})
tickstore_lib.read('SYM', columns=None)
read = tickstore_lib.read('SYM',
columns=None,
date_range=DateRange(dt(2013, 6, 1),
dt(2013, 6, 2)))
assert read['a'][0] == 1
# Read with the image as well
read = tickstore_lib.read('SYM',
columns=None,
date_range=DateRange(dt(2013, 6, 1),
dt(2013, 6, 2)),
include_images=True)
assert read['a'][0] == 37
assert read['a'][1] == 1
assert np.isnan(read['b'][0])
assert read['b'][2] == 4
assert read.index[0] == dt(2013, 6, 1, 11)
def test_read_longs(tickstore_lib):
DUMMY_DATA = [
{
'a': 1,
'index': dt(2013, 6, 1, 12, 00, tzinfo=mktz('Europe/London'))
},
{
'b': 4,
'index': dt(2013, 6, 1, 13, 00, tzinfo=mktz('Europe/London'))
},
]
tickstore_lib._chunk_size = 3
tickstore_lib.write('SYM', DUMMY_DATA)
tickstore_lib.read('SYM', columns=None)
read = tickstore_lib.read('SYM',
columns=None,
date_range=DateRange(dt(2013, 6, 1),
dt(2013, 6, 2)))
assert read['a'][0] == 1
assert np.isnan(read['b'][0])
def test_no_min_max_date(arctic):
arctic.initialize_library('FEED_2010.LEVEL1', tickstore.TICK_STORE_TYPE)
tstore = arctic['FEED_2010.LEVEL1']
dates = pd.date_range('20100101', periods=6, tz=mktz('Europe/London'))
df = pd.DataFrame(np.random.randn(6, 4), index=dates, columns=list('ABCD'))
tstore.write('blah', df)
with pytest.raises(NoDataFoundException):
tstore.min_date('unknown-symbol')
with pytest.raises(NoDataFoundException):
tstore.max_date('unknown-symbol')
def test_min_max_date(arctic):
arctic.initialize_library('FEED_2010.LEVEL1', tickstore.TICK_STORE_TYPE)
tstore = arctic['FEED_2010.LEVEL1']
dates = pd.date_range('20100101', periods=6, tz=mktz('Europe/London'))
df = pd.DataFrame(np.random.randn(6, 4), index=dates, columns=list('ABCD'))
tstore.write('blah', df)
min_date = tstore.min_date('blah')
max_date = tstore.max_date('blah')
assert min_date == dates[0].to_pydatetime()
assert max_date == dates[-1].to_pydatetime()
def test_read_with_metadata(tickstore_lib):
metadata = {'metadata': 'important data'}
tickstore_lib.write(
'test', [{
'index': dt(2013, 6, 1, 13, 00, tzinfo=mktz('Europe/London')),
'price': 100.50,
'ticker': 'QQQ'
}],
metadata=metadata)
m = tickstore_lib.read_metadata('test')
assert (metadata == m)
def test_read_all_cols_all_dtypes(tickstore_lib, chunk_size):
data = [
{
'f': 0.1,
'of': 0.2,
's': 's',
'os': 'os',
'l': 1,
'ol': 2,
'index': dt(1970, 1, 1, tzinfo=mktz('UTC')),
},
{
'f': 0.3,
'nf': 0.4,
's': 't',
'ns': 'ns',
'l': 3,
'nl': 4,
'index': dt(1970, 1, 1, 0, 0, 1, tzinfo=mktz('UTC')),
},
]
tickstore_lib._chunk_size = chunk_size
tickstore_lib.write('sym', data)
df = tickstore_lib.read('sym', columns=None)
# The below is probably more trouble than it's worth, but we *should*
# be able to roundtrip data and get the same answer...
# Ints become floats
data[0]['l'] = float(data[0]['l'])
# Treat missing strings as None
data[0]['ns'] = None
data[1]['os'] = None
index = DatetimeIndex([
dt(1970, 1, 1, tzinfo=mktz('UTC')),
dt(1970, 1, 1, 0, 0, 1, tzinfo=mktz('UTC'))
], )
index.tz = mktz()
expected = pd.DataFrame(data, index=index)
expected = expected[df.columns]
assert_frame_equal(expected, df, check_names=False)
def test_ts_write_pandas(tickstore_lib):
data = DUMMY_DATA
tickstore_lib.write('SYM', data)
data = tickstore_lib.read('SYM', columns=None)
assert data.index[0] == dt(2013, 1, 1, tzinfo=mktz('Europe/London'))
assert data.a[0] == 1
tickstore_lib.delete('SYM')
tickstore_lib.write('SYM', data)
read = tickstore_lib.read('SYM', columns=None)
assert_frame_equal(read, data, check_names=False)
def test_should_write_top_level_with_list_of_dicts(arctic):
arctic.initialize_library('FEED_2010.LEVEL1', tickstore.TICK_STORE_TYPE)
arctic.initialize_library('FEED_2011.LEVEL1', tickstore.TICK_STORE_TYPE)
arctic.initialize_library('FEED.LEVEL1', toplevel.TICK_STORE_TYPE)
toplevel_tickstore = arctic['FEED.LEVEL1']
dates = pd.date_range('20101201', periods=57, tz=mktz('Europe/London'))
data = [{'index': dates[i], 'a': i} for i in range(len(dates))]
expected = pd.DataFrame(np.arange(57, dtype=np.float64),
index=dates,
columns=list('a'))
toplevel_tickstore.write('blah', data)
res = toplevel_tickstore.read('blah',
DateRange(start=dt(2010, 12, 1),
end=dt(2011, 2, 1)),
columns=list('a'))
assert_frame_equal(expected, res.tz_convert(mktz('Europe/London')))
lib2010 = arctic['FEED_2010.LEVEL1']
res = lib2010.read('blah',
DateRange(start=dt(2010, 12, 1), end=dt(2011, 1, 1)))
assert_frame_equal(expected[dt(2010, 12, 1):dt(2010, 12, 31)],
res.tz_convert(mktz('Europe/London')))
def test_get_library_metadata(arctic):
arctic.initialize_library('FEED_2010.LEVEL1', tickstore.TICK_STORE_TYPE)
arctic.initialize_library('FEED_2011.LEVEL1', tickstore.TICK_STORE_TYPE)
arctic.initialize_library('FEED.LEVEL1', toplevel.TICK_STORE_TYPE)
toplevel_tickstore = arctic['FEED.LEVEL1']
symbol = "USD"
tzinfo=mktz('Asia/Chongqing')
with pytest.raises(NoDataFoundException):
toplevel_tickstore.read(symbol, DateRange(start=dt(2010, 1, 1, tzinfo=tzinfo),
end=dt(2011, 1, 2, tzinfo=tzinfo)),
columns=None)
def test_date_range_default_timezone(tickstore_lib, tz_name):
"""
We assume naive datetimes are user-local
"""
DUMMY_DATA = [
{'a': 1.,
'b': 2.,
'index': dt(2013, 1, 1, tzinfo=mktz(tz_name))
},
# Half-way through the year
{'b': 3.,
'c': 4.,
'index': dt(2013, 7, 1, tzinfo=mktz(tz_name))
},
]
with patch('tzlocal.get_localzone', return_value=Mock(zone=tz_name)):
tickstore_lib._chunk_size = 1
tickstore_lib.write('SYM', DUMMY_DATA)
df = tickstore_lib.read('SYM', date_range=DateRange(20130101, 20130701), columns=None)
assert df.index.tzinfo == mktz()
assert len(df) == 2
assert df.index[1] == dt(2013, 7, 1, tzinfo=mktz(tz_name))
df = tickstore_lib.read('SYM', date_range=DateRange(20130101, 20130101), columns=None)
assert len(df) == 1
assert df.index.tzinfo == mktz()
df = tickstore_lib.read('SYM', date_range=DateRange(20130701, 20130701), columns=None)
assert len(df) == 1
assert df.index.tzinfo == mktz()
def test_list_versions_localTime():
# Object ID's are stored in UTC. We need to ensure that the returned times
# for versions are in the local TimeZone
vs = create_autospec(VersionStore, instance=True, _versions=Mock())
vs._find_snapshots.return_value = 'snap'
date = dt(2013, 4, 1, 9, 0)
vs._versions.find.return_value = [{
'_id': bson.ObjectId.from_datetime(date),
'symbol': 's',
'version': 10
}]
version = list(VersionStore.list_versions(vs, "symbol"))[0]
local_date = date.replace(tzinfo=mktz("UTC")).astimezone(
mktz()).replace(tzinfo=None)
assert version == {
'symbol': version['symbol'],
'version': version['version'],
# We return naive datetimes in 'default' time, which is London for us
'date': local_date,
'snapshots': 'snap'
}
def test_delete(tickstore_lib):
DUMMY_DATA = [
{'a': 1.,
'b': 2.,
'index': dt(2013, 1, 1, tzinfo=mktz('Europe/London'))
},
{'a': 3.,
'b': 4.,
'index': dt(2013, 1, 30, tzinfo=mktz('Europe/London'))
},
]
tickstore_lib.chunk_size = 1
tickstore_lib.write('SYM', DUMMY_DATA)
tickstore_lib.delete('SYM')
with pytest.raises(NoDataFoundException):
tickstore_lib.read('SYM', date_range=DateRange(20130102), columns=None)
# Delete with a date-range
tickstore_lib.write('SYM', DUMMY_DATA)
tickstore_lib.delete('SYM', DateRange(dt(2013, 1, 1, tzinfo=mktz('Europe/London')), dt(2013, 1, 2, tzinfo=mktz('Europe/London'))))
df = tickstore_lib.read('SYM', columns=None)
assert np.allclose(df['b'].values, np.array([4.]))
def test_datetime_roundtrip_est_tz():
pdt = datetime.datetime(2012,
6,
12,
12,
12,
12,
123000,
tzinfo=mktz('EST'))
pdt2 = ms_to_datetime(datetime_to_ms(pdt))
assert pdt2.replace(tzinfo=mktz(DEFAULT_TIME_ZONE_NAME)) == pdt
pdt = datetime.datetime(2012,
1,
12,
12,
12,
12,
123000,
tzinfo=mktz('EST'))
pdt2 = ms_to_datetime(datetime_to_ms(pdt))
assert pdt2.replace(tzinfo=mktz(DEFAULT_TIME_ZONE_NAME)) == pdt
def test_datetime_roundtrip_local_tz():
pdt = datetime.datetime(2012,
6,
12,
12,
12,
12,
123000,
tzinfo=mktz(DEFAULT_TIME_ZONE_NAME))
pdt2 = ms_to_datetime(datetime_to_ms(pdt))
assert pdt2 == pdt
pdt = datetime.datetime(2012,
1,
12,
12,
12,
12,
123000,
tzinfo=mktz(DEFAULT_TIME_ZONE_NAME))
pdt2 = ms_to_datetime(datetime_to_ms(pdt))
assert pdt2 == pdt
def test_get_libraries_no_data_raises_exception_tzinfo_given(
toplevel_tickstore, arctic):
tzinfo = mktz('Asia/Chongqing')
date_range = DateRange(start=dt(2009, 1, 1, tzinfo=tzinfo),
end=dt(2010,
12,
31,
23,
59,
59,
999000,
tzinfo=tzinfo))
with pytest.raises(NoDataFoundException):
toplevel_tickstore._get_libraries(date_range)
def test_datetime_to_ms_and_back_microseconds():
pdt = dt(2012, 8, 1, 12, 34, 56, 999999, tzinfo=mktz())
i = datetime_to_ms(pdt)
pdt2 = ms_to_datetime(i)
assert pdt != pdt2
assert pdt.year == pdt2.year
assert pdt.month == pdt2.month
assert pdt.day == pdt2.day
assert pdt.hour == pdt2.hour
assert pdt.minute == pdt2.minute
assert pdt.second == pdt2.second
# Microsecond precision loss inevitable.
assert pdt.microsecond // 1000 == pdt2.microsecond // 1000
