def on_time(self, timestamp:pd.Timestamp, timestamp_next:pd.Timestamp):
"""
This method is called with every iteration and provides the timestamps
for both current and next iteration. The given interval may be used to
submit orders before a specific point in time.
:param timestamp:
pd.Timestamp, timestamp recorded
:param timestamp_next:
pd.Timestamp, timestamp recorded in next iteration
"""
# close active positions and cancel active orders two minutes before the market closes
if timestamp.time() >= datetime.time(16, 28) and self.time_to_trade:
for market_id, market in self.markets.items():
# cancel active orders for this market
if self.get_filtered_orders(market_id, status="ACTIVE"):
[self.cancel_order(order) for order in self.get_filtered_orders(market_id, status="ACTIVE")]
# close positions for this market
if self.exposure[market_id] > 0:
self.submit_order(market_id, "sell", self.default_quantity)
if self.exposure[market_id] < 0:
self.submit_order(market_id, "buy", self.default_quantity)
# ...
self.time_to_trade = False
# we want to start trading 15 minutes after XETRA has opened
if timestamp.time() >= datetime.time(8, 15) and not self.time_to_trade:
self.time_to_trade = True
def cal_sam_minute(x: pd.Timestamp,
sam_minutes: int,
region: str = REG_CN) -> pd.Timestamp:
"""
align the minute-level data to a down sampled calendar
e.g. align 10:38 to 10:35 in 5 minute-level(10:30 in 10 minute-level)
Parameters
----------
x : pd.Timestamp
datetime to be aligned
sam_minutes : int
align to `sam_minutes` minute-level calendar
region: str
Region, for example, "cn", "us"
Returns
-------
pd.Timestamp:
the datetime after aligned
"""
cal = get_min_cal(C.min_data_shift, region)[::sam_minutes]
idx = bisect.bisect_right(cal, x.time()) - 1
_date, new_time = x.date(), cal[idx]
return concat_date_time(_date, new_time)
def on_time(self, timestamp: pd.Timestamp, timestamp_next: pd.Timestamp):
"""
This method is called with every iteration and provides the timestamps
for both current and next iteration. The given interval may be used to
submit orders before a specific point in time.
:param timestamp:
pd.Timestamp, timestamp recorded
:param timestamp_next:
pd.Timestamp, timestamp recorded in next iteration
"""
# set flag if time is past 16:25, triggered only once
if timestamp.time() >= datetime.time(16, 25) and not self.eod:
for market_id, _ in self.markets.items():
# cancel active orders for this market
[
self.cancel_order(order)
for order in self.get_filtered_orders(market_id,
status="ACTIVE")
]
# close positions for this market
if self.exposure[market_id] > 0:
self.submit_order(market_id, "sell", self.default_quantity)
if self.exposure[market_id] < 0:
self.submit_order(market_id, "buy", self.default_quantity)
# ...
self.eod = True
# unset flag at start of (next) trading day
if timestamp.day != timestamp_next.day:
self.eod = False
def _adjust_date(column: pd.Series, start_from: pd.Timestamp):
validate_data_is_type(column, pd.Series)
validate_data_is_time_column(column)
pre_start = column[column.dt.time < start_from.time()]
post_start = column[column.dt.time >= start_from.time()]
post_start = pd.to_datetime(
post_start.apply(lambda x: f'{start_from.date()} {x.time()}'))
day_after = start_from.date() + pd.Timedelta(days=1)
pre_start = pd.to_datetime(
pre_start.apply(lambda x: f'{day_after} {x.time()}'))
output = pd.concat((pre_start, post_start))
assert output.shape == column.shape
return output
def download_cgi(
dataset: str, variables: List[str], start: pd.Timestamp, end: pd.Timestamp
) -> Iterable[dict]:
if start.time() < time(9):
start -= pd.Timedelta(1, 'D')
request = dict(
daybeg=start.strftime('%d'),
monthbeg=start.strftime('%b'),
yearbeg=start.strftime('%Y'),
dayend=end.strftime('%d'),
monthend=end.strftime('%b'),
yearend=end.strftime('%Y'),
nexttask='retrieve',
)
for variable in variables:
request[variable] = 'y'
response = requests.post(
'https://metdata.reading.ac.uk/cgi-bin/climate_extract.cgi',
data=request
)
content = response.text
try:
download_url = PATTERN.search(content).group(1)
except:
csv_text = content\
.split(MARKER)[-1]\
.replace('\n', '')\
.replace('<br>', '\n')\
.strip() + '\n'
else:
csv_text = requests.get(download_url).text.replace(' ', '')
for row in DictReader(StringIO(csv_text)):
row['TimeStamp'] = str(
datetime(*(int(row.get(i)) for i in ('year', 'month', 'day')), hour=9)+timedelta(days=1)
)
yield row