def _ms_bounds(local_symbol, day):
"""Return the inclusive starting and exclusive ending time bounds in
milliseconds for the specified date.
This is just a sample function. In practice, there would likely be a
configuration file that specified different time intervals (trading
windows) for different instruments. The SPY will trade at a different time
than the USD/JPY pair for instance.
Keyword arguments:
local_symbol -- ticker symbol
day -- day in 'yyyy-mm-dd' form
"""
milliseconds = ds.str_to_ms(day, TIMEZONE, '%Y-%m-%d')
weekday = ds.ms_to_datetime(milliseconds, TIMEZONE).weekday()
# Don't support weekends
if weekday > 4:
return 0, 0
start_time, end_time = 0, 0
# For this example, we assume a '.' in the symbol refers to a currency so
# we trade between 06:00 and 20:00 in the specified timezone
if '.' in local_symbol:
start_time = '06:00'
end_time = '20:00'
# Otherwise, we'll assume it's an equity and trade 09:30 to 16:00
else:
start_time = '09:30'
end_time = '16:00'
min_time = '{0} {1}:00.000'.format(day, start_time)
min_ms = ds.str_to_ms(min_time, TIMEZONE)
max_time = '{0} {1}:00.000'.format(day, end_time)
max_ms = ds.str_to_ms(max_time, TIMEZONE)
return min_ms, max_ms
def create_bar_data(start_date, end_date, min_time, max_time, timezone):
"""Create a list of the form [(bar_time, bar_count), ...] with each
element in the list representing the timeframe for a historical data
request. This is calculated using the known constraints that will prevent a
pacing violation.
Keyword arguments:
start_date -- start date in yyyy-mm-dd format
end_date -- end date in yyyy-mm-dd format
min_time -- minimum inclusive session starting time in hh:mm form
max_time -- maximum exclusive session ending time in hh:mm form
timezone -- time zone
"""
# Append times to the dates
min_hour, min_minute = [int(z) for z in min_time.split(':')]
max_hour, max_minute = [int(z) for z in max_time.split(':')]
start_time = '{0} {1}:{2}'.format(start_date, min_hour, min_minute)
end_time = '{0} {1}:{2}'.format(end_date, max_hour, max_minute)
# Convert our time to milliseconds
start_ms = ds.str_to_ms(start_time, timezone, '%Y-%m-%d %H:%M')
end_ms = ds.str_to_ms(end_time, timezone, '%Y-%m-%d %H:%M')
# Enumerate each day as a start:end pair
span_min = (max_hour * 60 + max_minute) - (min_hour * 60 + min_minute)
span_ms = span_min * 60 * 1000
days = []
first_ms, last_ms = start_ms, start_ms + span_ms
while first_ms < end_ms:
dtime = ds.ms_to_datetime(last_ms, timezone)
# Only allow Monday through Friday
if dtime.weekday() < 5:
days.append((first_ms, last_ms))
first_ms += DAY_MS
last_ms += DAY_MS
# Break each day into blocks of MAX_BLOCK_SIZE
blocks = []
for day in days:
total_span_secs = (day[1] - day[0]) / 1000
total_bars = total_span_secs / config.BAR_SIZE_SECONDS
last_ms = day[0]
while total_bars > 0:
bars = min(total_bars, config.MAX_BLOCK_SIZE)
span_ms = int(bars * config.BAR_SIZE_SECONDS * 1000)
blocks.append((last_ms + span_ms, bars))
total_bars -= config.MAX_BLOCK_SIZE
last_ms += span_ms
return blocks
