def load_market_data():
try:
fp_bm = get_datafile('benchmark.msgpack', "rb")
except IOError:
print """
data msgpacks aren't distribute with source.
Fetching data from Yahoo Finance.
""".strip()
dump_benchmarks()
fp_bm = get_datafile('benchmark.msgpack', "rb")
bm_list = msgpack.loads(fp_bm.read())
bm_returns = []
for packed_date, returns in bm_list:
event_dt = tuple_to_date(packed_date)
#event_dt = event_dt.replace(
# hour=0,
# minute=0,
# second=0,
# tzinfo=pytz.utc
#)
daily_return = risk.DailyReturn(date=event_dt, returns=returns)
bm_returns.append(daily_return)
fp_bm.close()
bm_returns = sorted(bm_returns, key=attrgetter('date'))
try:
fp_tr = get_datafile('treasury_curves.msgpack', "rb")
except IOError:
print """
data msgpacks aren't distribute with source.
Fetching data from data.treasury.gov
""".strip()
dump_treasury_curves()
fp_tr = get_datafile('treasury_curves.msgpack', "rb")
tr_list = msgpack.loads(fp_tr.read())
tr_curves = {}
for packed_date, curve in tr_list:
tr_dt = tuple_to_date(packed_date)
#tr_dt = tr_dt.replace(hour=0, minute=0, second=0, tzinfo=pytz.utc)
tr_curves[tr_dt] = curve
fp_tr.close()
tr_curves = OrderedDict(sorted(
((dt, c) for dt, c in tr_curves.iteritems()),
key=lambda t: t[0]))
return bm_returns, tr_curves
def load_market_data():
try:
fp_bm = get_datafile('benchmark.msgpack', "rb")
except IOError:
print """
data msgpacks aren't distribute with source.
Fetching data from Yahoo Finance.
""".strip()
dump_benchmarks()
fp_bm = get_datafile('benchmark.msgpack', "rb")
bm_list = msgpack.loads(fp_bm.read())
bm_returns = []
for packed_date, returns in bm_list:
event_dt = tuple_to_date(packed_date)
#event_dt = event_dt.replace(
# hour=0,
# minute=0,
# second=0,
# tzinfo=pytz.utc
#)
daily_return = risk.DailyReturn(date=event_dt, returns=returns)
bm_returns.append(daily_return)
fp_bm.close()
bm_returns = sorted(bm_returns, key=attrgetter('date'))
try:
fp_tr = get_datafile('treasury_curves.msgpack', "rb")
except IOError:
print """
data msgpacks aren't distribute with source.
Fetching data from data.treasury.gov
""".strip()
dump_treasury_curves()
fp_tr = get_datafile('treasury_curves.msgpack', "rb")
tr_list = msgpack.loads(fp_tr.read())
tr_curves = {}
for packed_date, curve in tr_list:
tr_dt = tuple_to_date(packed_date)
#tr_dt = tr_dt.replace(hour=0, minute=0, second=0, tzinfo=pytz.utc)
tr_curves[tr_dt] = curve
fp_tr.close()
return bm_returns, tr_curves
def drop_before_date(source_name, last_date):
"""
Loads the msgpack file for the given @source_name and drops values
up to @last_date.
Used so that we can test logic that updates the msgpack's to download
current data if the data isn't current enough.
"""
filename = DATA_SOURCES[source_name]['filename']
data = loader.get_saved_data(filename)
filtered_data = itertools.takewhile(
lambda x: tuple_to_date(x[0]).date() <= last_date.date(), data)
with loader.get_datafile(filename, mode='wb') as fp:
fp.write(msgpack.dumps(list(filtered_data)))
def drop_before_date(source_name, last_date):
"""
Loads the msgpack file for the given @source_name and drops values
up to @last_date.
Used so that we can test logic that updates the msgpack's to download
current data if the data isn't current enough.
"""
filename = DATA_SOURCES[source_name]['filename']
data = loader.get_saved_data(filename)
filtered_data = itertools.takewhile(
lambda x: tuple_to_date(x[0]).date() <= last_date.date(), data)
with loader.get_datafile(filename, mode='wb') as fp:
fp.write(msgpack.dumps(list(filtered_data)))