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)))
def last_date(source_name, args):
data = loader.get_saved_data(DATA_SOURCES[source_name]['filename'])
date = tuple_to_date(data[-1][0])
print "Last saved {source_name} date is {date}".format(
source_name=source_name, date=date)
def load_market_data(bm_symbol='^GSPC'):
try:
fp_bm = get_datafile(get_benchmark_filename(bm_symbol), "rb")
except IOError:
print("""
data msgpacks aren't distributed with source.
Fetching data from Yahoo Finance.
""").strip()
dump_benchmarks(bm_symbol)
fp_bm = get_datafile(get_benchmark_filename(bm_symbol), "rb")
bm_list = msgpack.loads(fp_bm.read())
# Find the offset of the last date for which we have trading data in our
# list of valid trading days
last_bm_date = tuple_to_date(bm_list[-1][0])
last_bm_date_offset = trading_days.searchsorted(
last_bm_date.strftime('%Y/%m/%d'))
# If more than 1 trading days has elapsed since the last day where
# we have data,then we need to update
if len(trading_days) - last_bm_date_offset > 1:
update_benchmarks(bm_symbol, last_bm_date)
fp_bm = get_datafile(get_benchmark_filename(bm_symbol), "rb")
bm_list = msgpack.loads(fp_bm.read())
bm_returns = []
for packed_date, returns in bm_list:
event_dt = tuple_to_date(packed_date)
daily_return = 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 distributed 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())
# Find the offset of the last date for which we have trading data in our
# list of valid trading days
last_tr_date = tuple_to_date(tr_list[-1][0])
last_tr_date_offset = trading_days.searchsorted(
last_tr_date.strftime('%Y/%m/%d'))
# If more than 1 trading days has elapsed since the last day where
# we have data,then we need to update
if len(trading_days) - last_tr_date_offset > 1:
update_treasury_curves(last_tr_date)
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, microsecond=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 last_date(source_name, args):
data = loader.get_saved_data(DATA_SOURCES[source_name]['filename'])
date = tuple_to_date(data[-1][0])
print "Last saved {source_name} date is {date}".format(
source_name=source_name, date=date)
