def random_intalpha(startdate='20140103', freq='30min', n=None):
if not n >= 0:
n = np.random.randint(10, 20)
dates = dateutil.get_startfrom(DATES,
dateutil.compliment_datestring(str(startdate), -1, True),
n)
times = dateutil.generate_intervals(int(freq[:-3])*60)
dts = pd.to_datetime([d+' '+t for d in dates for t in times])
df = pd.DataFrame(np.random.randn(len(dts), len(SIDS)), index=dts, columns=SIDS)
return df
class IntervalFetcher(KMinFetcher):
"""Class to fetch TinySoft minute-bar data.
:param str freq: Frequency of minute-bar data, currently only supports: ('30min', '5min', '1min')
"""
collections = {
'30min': DB.ts_30min,
'5min': DB.ts_5min,
'1min': DB.ts_1min,
}
intervals = {
'30min': dateutil.generate_intervals(1800),
'5min': dateutil.generate_intervals(300),
'1min': dateutil.generate_intervals(60),
}
dnames = DB.ts_30min.distinct('dname')
freqs = ('30min', '5min', '1min')
def __init__(self, freq, **kwargs):
if freq not in IntervalFetcher.freqs:
raise ValueError(
'No minute-bar data of frequency {0!r} exists'.format(freq))
self._freq = freq
self.collection = IntervalFetcher.collections[freq]
self.intervals = IntervalFetcher.intervals[freq]
super(IntervalFetcher, self).__init__(**kwargs)
@property
def freq(self):
"""Property."""
return self._freq
@freq.setter
def freq(self, freq):
if freq not in IntervalFetcher.freqs:
self.warning(
'No minute-bar data of frequency {0!r} exists. Nothing has changed'
.format(freq))
return
self._freq = freq
self.collection = IntervalFetcher.collections[freq]
self.intervals = IntervalFetcher.intervals[freq]
class IntervalReturnsFetcher(KMinFetcher):
"""Class to fetch TinySoft interval returns data.
:param str freq: Frequency of interval returns, currently only supports: ('1min', '5min', '15min', '30min', '60min', '120min')
"""
freqs = ('1min', '5min', '15min', '30min', '60min', '120min')
intervals = {
'1min': dateutil.generate_intervals(60),
'5min': dateutil.generate_intervals(300),
'15min': dateutil.generate_intervals(15 * 60),
'30min': dateutil.generate_intervals(30 * 60),
'60min': dateutil.generate_intervals(60 * 60),
'120min': dateutil.generate_intervals(120 * 60),
}
def __init__(self, freq, **kwargs):
if freq is not None and freq not in IntervalReturnsFetcher.freqs:
raise ValueError(
'No interval returns of frequency {0!r} exists'.format(freq))
self._freq = freq
self._dname = 'returns' + freq[:-3]
self.collection = DB.ts_ret
self.intervals = IntervalReturnsFetcher.intervals[freq]
super(IntervalReturnsFetcher, self).__init__(**kwargs)
@property
def freq(self):
"""Property."""
return self._freq
@freq.setter
def freq(self, freq):
if freq not in IntervalReturnsFetcher.freqs:
self.warning(
'No interval returns of frequency {0!r} exists. Nothing has changed'
.format(freq))
return
self._freq = freq
self._dname = 'returns' + freq[:-3]
self.intervals = IntervalReturnsFetcher.intervals[freq]
def fetch(self, *args, **kwargs):
"""A variant of :py:meth:`orca.mongo.base.KMinFetcher.fetch`: when ``dname`` is omitted, it uses the :py:attr:`IntervalReturnsFetcher.freq` to determine which data to fetch."""
if isinstance(args[0],
str) and args[0][:7] == 'returns': # dname is given
return super(IntervalReturnsFetcher, self).fetch(*args, **kwargs)
else:
return super(IntervalReturnsFetcher,
self).fetch(*((self._dname, ) + args), **kwargs)
def fetch_window(self, *args, **kwargs):
"""A variant of :py:meth:`orca.mongo.base.KMinFetcher.fetch_window`: when ``dname`` is omitted, it uses the :py:attr:`IntervalReturnsFetcher.freq` to determine which data to fetch."""
if isinstance(args[0], str): # dname is given
return super(IntervalReturnsFetcher,
self).fetch_window(*args, **kwargs)
else:
return super(IntervalReturnsFetcher,
self).fetch_window(*((self._dname, ) + args),
**kwargs)
def fetch_history(self, *args, **kwargs):
"""A variant of :py:meth:`orca.mongo.base.KMinFetcher.fetch_history`: when ``dname`` is omitted, it uses the :py:attr:`IntervalReturnsFetcher.freq` to determine which data to fetch."""
if isinstance(args[0],
str) and args[0][:7] == 'returns': # dname is given
return super(IntervalReturnsFetcher,
self).fetch_history(*args, **kwargs)
else:
return super(IntervalReturnsFetcher,
self).fetch_history(*((self._dname, ) + args),
**kwargs)
def fetch_daily(self, *args, **kwargs):
"""A variant of :py:meth:`orca.mongo.base.KMinFetcher.fetch_daily`: when ``dname`` is omitted, it uses the :py:attr:`IntervalReturnsFetcher.freq` to determine which data to fetch."""
if isinstance(args[0],
str) and args[0][:7] == 'returns': # dname is given
return super(IntervalReturnsFetcher,
self).fetch_daily(*args, **kwargs)
else:
return super(IntervalReturnsFetcher,
self).fetch_daily(*((self._dname, ) + args), **kwargs)
def fetch_intervals(self, *args, **kwargs):
"""A variant of :py:meth:`orca.mongo.base.KMinFetcher.fetch_daily`: when ``dname`` is omitted, it uses the :py:attr:`IntervalReturnsFetcher.freq` to determine which data to fetch."""
if isinstance(args[0],
str) and args[0][:7] == 'returns': # dname is given
return super(IntervalReturnsFetcher,
self).fetch_intervals(*args, **kwargs)
else:
return super(IntervalReturnsFetcher,
self).fetch_intervals(*((self._dname, ) + args),
**kwargs)
def __init__(self, timeout=60):
UpdaterBase.__init__(self, timeout=timeout)
self.interval = IntervalFetcher('1min')
self.quote = QuoteFetcher()
self.indexquote = IndexQuoteFetcher()
self.times = dateutil.generate_intervals(60)
"""
.. moduleauthor:: Li, Wang <*****@*****.**>
"""
import os
from datetime import datetime, timedelta
import numpy as np
import pandas as pd
import warnings
warnings.simplefilter(action='ignore', category=pd.core.common.SettingWithCopyWarning)
from base import UpdaterBase
from orca.utils.dateutil import generate_intervals
times_1min = generate_intervals(1*60, begin='091500', end='151500')
times_5min = generate_intervals(5*60, begin='091500', end='151500')
columns = ['dt', 'price', 'volume', 'bid1', 'ask1', 'bds1', 'aks1', 'open_interest']
dnames = ['price', 'volume', 'open_interest', 'bid1', 'bds1', 'ask1', 'aks1']
columns1 = ['dt', 'price', 'volume']
dnames1 = ['price', 'volume']
class IFUpdater(UpdaterBase):
"""The updater class for collection 'IF'."""
def __init__(self, timeout=1200):
super(IFUpdater, self).__init__(timeout=timeout)
self.sids = set()
def pre_update(self):
def __init__(self, freq, **kwargs):
super(IntervalAlphaBase, self).__init__(**kwargs)
if freq not in IntervalAlphaBase.freqs:
raise ValueError('Frequency {0!r} is currently not supported'.format(freq))
self.freq = 60 * int(freq[:-3])
self.times = dateutil.generate_intervals(self.freq)
def __init__(self, timeout=60):
UpdaterBase.__init__(self, timeout=timeout)
self.interval = IntervalFetcher('1min')
self.quote = QuoteFetcher()
self.indexquote = IndexQuoteFetcher()
self.times = dateutil.generate_intervals(60)
class IFIntervalFetcher(KDayFetcher):
"""Class to fetch TinySoft futures minute-bar data.
:param str freq: Frequency of minute-bar data, currently only supports: ('5min', '1min')
"""
collections = {
'5min': DB.IF_5min,
'1min': DB.IF_1min,
}
intervals = {
'5min': dateutil.generate_intervals(5 * 60,
begin='091500',
end='151500'),
'1min': dateutil.generate_intervals(1 * 60,
begin='091500',
end='151500'),
}
dnames = DB.IF_5min.distinct('dname')
freqs = ('30min', '5min', '1min')
def __init__(self, freq, **kwargs):
if freq not in IFIntervalFetcher.freqs:
raise ValueError(
'No minute-bar data of frequency {0!r} exists'.format(freq))
self._freq = freq
self.collection = IFIntervalFetcher.collections[freq]
self.intervals = IFIntervalFetcher.intervals[freq]
super(IFIntervalFetcher, self).__init__(**kwargs)
@property
def freq(self):
"""Property."""
return self._freq
@freq.setter
def freq(self, freq):
if freq not in IFIntervalFetcher.freqs:
self.warning(
'No minute-bar data of frequency {0!r} exists. Nothing has changed'
.format(freq))
return
self._freq = freq
self.collection = IFIntervalFetcher.collections[freq]
self.intervals = IFIntervalFetcher.intervals[freq]
def fetch_window(self, dname, window, sid=None, **kwargs):
assert sid
datetime_index = kwargs.get('datetime_index', self.datetime_index)
reindex = kwargs.get('reindex', self.reindex)
query = {
'sid': sid,
'dname': dname,
'date': {
'$gte': window[0],
'$lte': window[-1]
}
}
proj = {'_id': 0, 'dvalue': 1, 'date': 1}
cursor = self.collection.find(query, proj)
df = pd.DataFrame({row['date']: row['dvalue'] for row in cursor}).T
del cursor
if reindex:
ser = df.T.unstack()
ser.index = pd.to_datetime([d + t for d, t in ser.index])
return ser
if datetime_index:
df.index = pd.to_datetime(df.index)
return df
def fetch(self, dname, startdate=None, **kwargs):
if startdate is None:
startdate = '20100416'
return super(IFIntervalFetcher, self).fetch(dname, startdate, **kwargs)