from functools import partial
import pandas as pd
import onetick.py as otp
import onetick.query as otq
from onetick.py import utils
from onetick.py.sources import _start_doc, _end_doc, _symbol_doc
from onetick.py.docs.utils import docstring
COMMON_SOURCE_DOC_PARAMS = [_start_doc, _end_doc, _symbol_doc]
def _modify_query_times(src):
src.sink(otq.ModifyQueryTimes(
start_time=('parse_time("%Y%m%d %H:%M:%S.%q", '
'time_format("%Y%m%d", _START_TIME, _TIMEZONE) + " 00:00:00.000", "GMT")'),
end_time=('parse_time("%Y%m%d %H:%M:%S.%q", '
'time_format("%Y%m%d", _END_TIME, _TIMEZONE) + " 24:00:00.000", "GMT")'),
output_timestamp='min(max(TIMESTAMP,_START_TIME),_END_TIME)'
))
[docs]class OHLCV(otp.Source):
"""OneQuantData™ source to retrieve a time series of unadjusted
prices for a symbol for one particular pricing exchange of daily OHLCV data.
Output ticks have fields: OPEN, HIGH, LOW, CLOSE, VOLUME, CURRENCY, EXCH.
Parameters
----------
exch : `str`, 'all', 'main'
The OneQuantData exchange code for the desired price series. Possible values:
- 'all'
return data for all exchanges;
- 'main'
return data main pricing exchange;
- any other string value will treated as exchange name to filter data.
Default: 'all'.
Examples
--------
>>> src = otp.oqd.sources.OHLCV(exch="USPRIM")
>>> otp.run(src,
... symbols='BTKR::::GOOGL US',
... start=otp.dt(2018, 8, 1),
... end=otp.dt(2018, 8, 2),
... symbol_date=otp.dt(2018, 8, 1))
Time OID EXCH CURRENCY OPEN HIGH LOW CLOSE VOLUME
0 2018-08-01 00:00:00 74143 USPRIM USD 1242.73 1245.72 1225.00 1232.99 605680.0
1 2018-08-01 20:00:00 74143 USPRIM USD 1219.69 1244.25 1218.06 1241.13 596960.0
"""
@docstring(parameters=COMMON_SOURCE_DOC_PARAMS, add_self=True)
def __init__(
self,
exch='all',
symbol=utils.adaptive,
start=utils.adaptive,
end=utils.adaptive,
**kwargs
):
if self._try_default_constructor(**kwargs):
return
super().__init__(
_symbols=symbol,
_start=start,
_end=end,
_base_ep_func=partial(self.build, exch=exch)
)
self.schema.set(OID=str,
EXCH=str,
CURRENCY=str,
OPEN=float,
HIGH=float,
LOW=float,
CLOSE=float,
VOLUME=float)
def build(self, exch):
ep = None
if exch == 'all':
ep = otp.oqd.eps.OqdSourceDprcAll()
elif exch == 'main':
ep = otp.oqd.eps.OqdSourceDprcMain()
else:
ep = otp.oqd.eps.OqdSourceDprcExch(exch=exch)
src = otp.Source(ep)
src.tick_type('OQD::*')
_modify_query_times(src)
return src
[docs]class CorporateActions(otp.Source):
"""
OneQuantData™ source EP to retrieve a time series of corporate
actions for a symbol.
This source will return all corporate action fields available for a symbol
with EX-Dates between the query start time and end time. The
timestamp of the series is equal to the EX-Date of the corporate
action with a time of 0:00:00 GMT.
Examples
--------
>>> src = otp.oqd.sources.CorporateActions()
>>> otp.run(src,
... symbols='TDEQ::::AAPL',
... start=otp.dt(2021, 1, 1),
... end=otp.dt(2021, 8, 6),
... symbol_date=otp.dt(2021, 2, 18),
... timezone='GMT')
Time OID ACTION_ID ACTION_TYPE ACTION_ADJUST ACTION_CURRENCY ANN_DATE EX_DATE PAY_DATE REC_DATE\
TERM_NOTE TERM_RECORD_TYPE ACTION_STATUS
0 2021-02-05 9706 16799540 CASH_DIVIDEND 0.205 USD 20210127 20210205 20210211 20210208\
CASH:0.205@USD NORMAL
1 2021-05-07 9706 17098817 CASH_DIVIDEND 0.220 USD 20210428 20210507 20210513 20210510\
CASH:0.22@USD NORMAL
2 2021-08-06 9706 17331864 CASH_DIVIDEND 0.220 USD 20210727 20210806 20210812 20210809\
CASH:0.22@USD NORMAL
"""
@docstring(parameters=COMMON_SOURCE_DOC_PARAMS, add_self=True)
def __init__(
self,
symbol=utils.adaptive,
start=utils.adaptive,
end=utils.adaptive,
**kwargs
):
if self._try_default_constructor(**kwargs):
return
super().__init__(
_symbols=symbol,
_start=start,
_end=end,
_base_ep_func=partial(self.build)
)
self.schema.set(OID=str,
ACTION_ID=int,
ACTION_TYPE=str,
ACTION_ADJUST=float,
ACTION_CURRENCY=str,
ANN_DATE=int,
EX_DATE=int,
PAY_DATE=int,
REC_DATE=int,
TERM_NOTE=str,
TERM_RECORD_TYPE=str,
ACTION_STATUS=str)
def build(self):
ep = otp.oqd.eps.OqdSourceCacs()
src = otp.Source(ep)
src.tick_type('OQD::*')
_modify_query_times(src)
return src
[docs]class DescriptiveFields(otp.Source):
"""OneQuantData™ source to retrieve a time series of descriptive fields for a symbol.
There will only be ticks on days when some field in the descriptive data changes.
Output ticks will have fields:
OID, END_DATE, COUNTRY, EXCH, NAME,
ISSUE_DESC, ISSUE_CLASS, ISSUE_TYPE, ISSUE_STATUS,
SIC_CODE, IDSYM, TICKER, CALENDAR.
Note: currently actual fields have 9999 year in END_DATE, but it could not fit the
nanosecond timestamp, so it is replaced with 2035-01-01 date.
Examples
--------
>>> src = otp.oqd.sources.DescriptiveFields()
>>> otp.run(src,
... symbols='1000001589',
... start=otp.dt(2020, 3, 1),
... end=otp.dt(2023, 3, 2),
... timezone='GMT').iloc[:6]
Time OID END_DATE COUNTRY EXCH NAME ISSUE_DESC\
ISSUE_CLASS ISSUE_TYPE ISSUE_STATUS SIC_CODE IDSYM TICKER CALENDAR
0 2020-03-01 1000001589 2020-03-23 LUX EL^X INVESTEC GLOBAL ST EUROPEAN HIGH YLD BD INC 2\
FUND NORMAL B2PT4G9
1 2020-03-23 1000001589 2020-04-01 LUX EL^X NINETY ONE LIMITED EUROPEAN HIGH YLD BD INC 2\
FUND NORMAL B2PT4G9
2 2020-04-01 1000001589 2021-01-01 LUX EL^X NINETY ONE LUX S.A EUROPEAN HIGH YLD BD INC 2\
FUND NORMAL B2PT4G9
3 2021-01-01 1000001589 2021-06-18 LUX EL^X NINETY ONE LUX S.A EUROPEAN HIGH YLD BD INC 2\
FUND NORMAL B2PT4G9
4 2021-06-18 1000001589 2022-01-01 LUX EL^X NINETY ONE LUX S.A GSF GBL HIGH YLD A2 EUR DIS\
FUND NORMAL B2PT4G9
5 2022-01-01 1000001589 2022-01-28 LUX EL^X NINETY ONE LUX S.A GSF GBL HIGH YLD A2 EUR DIS\
FUND NORMAL B2PT4G9
"""
@docstring(parameters=COMMON_SOURCE_DOC_PARAMS, add_self=True)
def __init__(
self,
symbol=utils.adaptive,
start=utils.adaptive,
end=utils.adaptive,
**kwargs
):
if self._try_default_constructor(**kwargs):
return
super().__init__(
_symbols=symbol,
_start=start,
_end=end,
_base_ep_func=partial(self.build)
)
self.schema.set(
OID=str,
END_DATE=otp.nsectime,
COUNTRY=str,
EXCH=str,
NAME=str,
ISSUE_DESC=str,
ISSUE_CLASS=str,
ISSUE_TYPE=str,
ISSUE_STATUS=str,
SIC_CODE=str,
IDSYM=str,
TICKER=str,
CALENDAR=str,)
def build(self):
ep = otp.oqd.eps.OqdSourceDes()
src = otp.Source(ep)
src.tick_type('OQD::*')
_modify_query_times(src)
# work-around to resolve problem with pandas timestamp out of bounds
pd_max = pd.Timestamp.max.strftime('%Y%m%d%H%M%S')
src.sink(otq.UpdateFields(
set='END_DATE=PARSE_NSECTIME("%Y-%m-%d", "2035-01-01", _TIMEZONE)',
where=f'AS_YYYYMMDDHHMMSS(END_DATE) > {pd_max}'))
return src
[docs]class SharesOutstanding(otp.Source):
"""
Logic is implemented in OQD_SOURCE_SHO EP to retrieve a time series of shares
outstanding for a stock.
The source retrieves a time series of shares outstanding
for a stock. This source only applies to stocks or securities that have
published shares outstanding data.
The series represents total shares outstanding and is not free float
adjusted.
Note: currently actual fields have 9999 year in END_DATE, but it could not fit the
nanosecond timestamp, so it is replaced with 2035-01-01 date.
Examples
--------
>>> src = otp.oqd.sources.SharesOutstanding()
>>> otp.run(src,
... symbols='TDEQ::::AAPL',
... start=otp.dt(2021, 1, 1),
... end=otp.dt(2021, 8, 6),
... symbol_date=otp.dt(2021, 2, 18),
... timezone='GMT')
Time OID END_DATE REPORT_MONTH SHARES
0 2021-01-01 9706 2021-01-06 202009 1.700180e+10
1 2021-01-06 9706 2021-01-29 202009 1.682326e+10
2 2021-01-29 9706 2021-05-03 202012 1.678810e+10
3 2021-05-03 9706 2021-07-30 202103 1.668763e+10
4 2021-07-30 9706 2021-10-29 202106 1.653017e+10
"""
@docstring(parameters=COMMON_SOURCE_DOC_PARAMS, add_self=True)
def __init__(
self,
symbol=otp.utils.adaptive,
start=otp.utils.adaptive,
end=otp.utils.adaptive,
**kwargs
):
if self._try_default_constructor(**kwargs):
return
super().__init__(
_symbols=symbol,
_start=start,
_end=end,
_base_ep_func=partial(self.build)
)
self.schema.set(OID=str,
END_DATE=otp.nsectime,
REPORT_MONTH=int,
SHARES=int)
def build(self):
ep = otp.oqd.eps.OqdSourceSho()
src = otp.Source(ep)
src.tick_type('OQD::*')
_modify_query_times(src)
# work-around to resolve problem with pandas timestamp out of bounds
pd_max = pd.Timestamp.max.strftime('%Y%m%d%H%M%S')
src.sink(otq.UpdateFields(
set='END_DATE=PARSE_NSECTIME("%Y-%m-%d", "2035-01-01", _TIMEZONE)',
where=f'AS_YYYYMMDDHHMMSS(END_DATE) > {pd_max}'))
return src