Data Retrieval with Continuous Contracts#

This section contains 6 examples for Data Retrieval with Continuous Contracts using the onetick-py.
Each example is a self-contained script that can be run against the OneTick Cloud sample databases.

# onetick-py WebAPI configuration for OneTick Cloud
import os
os.environ['OTP_WEBAPI'] = '1'
os.environ['OTP_HTTP_ADDRESS'] = 'https://rest.cloud.onetick.com'
os.environ['OTP_ACCESS_TOKEN_URL'] = 'https://cloud-auth.parent.onetick.com/realms/OMD/protocol/openid-connect/token'
os.environ['OTP_CLIENT_ID'] = '__FILL_IN__'
os.environ['OTP_CLIENT_SECRET'] = '__FILL_IN__'

DAY Retrieval Cont Contract by Max Open Interest#

Retrieve the Front Month Continuous Contract based on Maximum Open Interest.
Using Symbol Syntax: [Product Code]_r_oi.

import onetick.py as otp

data = otp.DataSource(db='ICE_EU_COM_SAMPLE_DAILY', tick_type='DAY')
data = data.where(data['UPDATE_TYPE'] == 'Summary')
result = otp.run(data,
                 start=otp.dt(2024, 1, 1),
                 end=otp.dt(2024, 4, 1),
                 timezone='Europe/London',
                 symbols='BRN_r_oi',
                 symbol_date=otp.dt(2024, 4, 1))
result

	Time	UPDATE_TYPE	OPEN	HIGH	LOW	CLOSE	SETTLE_PRICE	SETTLE_DATE	VOLUME	OPEN_INT	OPEN_INT_DATE	OMDSEQ
0	2024-01-01 23:30:00	Summary	NaN	NaN	NaN	NaN	NaN		0.0	NaN		0
1	2024-01-02 23:30:00	Summary	77.39	79.06	75.60	76.04	75.89	20240102	338351.0	552541.0	20231229	0
2	2024-01-03 23:30:00	Summary	76.06	78.67	74.79	78.44	78.25	20240103	361765.0	526073.0	20240102	0
3	2024-01-04 23:30:00	Summary	78.56	79.41	76.50	77.74	77.59	20240104	356646.0	520589.0	20240103	0
4	2024-01-05 23:30:00	Summary	77.71	79.26	77.66	78.90	78.76	20240105	291002.0	499963.0	20240104	0
...	...	...	...	...	...	...	...	...	...	...	...	...
60	2024-03-25 22:30:00	Summary	84.83	86.51	84.79	86.04	86.08	20240325	354261.0	555528.0	20240322	0
61	2024-03-26 22:30:00	Summary	86.16	86.42	85.19	85.27	85.63	20240326	338858.0	583946.0	20240325	0
62	2024-03-27 22:30:00	Summary	85.27	85.70	84.58	85.70	85.41	20240327	369265.0	605142.0	20240326	0
63	2024-03-28 22:30:00	Summary	85.69	87.07	85.50	87.07	87.00	20240328	414238.0	610314.0	20240327	0
64	2024-03-29 22:30:00	Summary	NaN	NaN	NaN	NaN	NaN		0.0	NaN		0

65 rows × 12 columns

DAY Retrieval Cont Contract by Max Volume#

Retrieve the Front Month Continuous Contract based on Maximum Volume.
Using Symbol Syntax: [Product Code]_r_vol.

import onetick.py as otp

data = otp.DataSource(db='ICE_EU_COM_SAMPLE_DAILY', tick_type='DAY')
data = data.where(data['UPDATE_TYPE'] == 'Summary')
result = otp.run(data,
                 start=otp.dt(2024, 1, 1),
                 end=otp.dt(2024, 4, 1),
                 timezone='Europe/London',
                 symbols='BRN_r_vol',
                 symbol_date=otp.dt(2024, 4, 1))
result

	Time	UPDATE_TYPE	OPEN	HIGH	LOW	CLOSE	SETTLE_PRICE	SETTLE_DATE	VOLUME	OPEN_INT	OPEN_INT_DATE	OMDSEQ
0	2024-01-01 23:30:00	Summary	NaN	NaN	NaN	NaN	NaN		0.0	NaN		0
1	2024-01-02 23:30:00	Summary	77.39	79.06	75.60	76.04	75.89	20240102	338351.0	552541.0	20231229	0
2	2024-01-03 23:30:00	Summary	76.06	78.67	74.79	78.44	78.25	20240103	361765.0	526073.0	20240102	0
3	2024-01-04 23:30:00	Summary	78.56	79.41	76.50	77.74	77.59	20240104	356646.0	520589.0	20240103	0
4	2024-01-05 23:30:00	Summary	77.71	79.26	77.66	78.90	78.76	20240105	291002.0	499963.0	20240104	0
...	...	...	...	...	...	...	...	...	...	...	...	...
60	2024-03-25 22:30:00	Summary	84.83	86.51	84.79	86.04	86.08	20240325	354261.0	555528.0	20240322	0
61	2024-03-26 22:30:00	Summary	86.16	86.42	85.19	85.27	85.63	20240326	338858.0	583946.0	20240325	0
62	2024-03-27 22:30:00	Summary	85.27	85.70	84.58	85.70	85.41	20240327	369265.0	605142.0	20240326	0
63	2024-03-28 22:30:00	Summary	85.69	87.07	85.50	87.07	87.00	20240328	414238.0	610314.0	20240327	0
64	2024-03-29 22:30:00	Summary	NaN	NaN	NaN	NaN	NaN		0.0	NaN		0

65 rows × 12 columns

DAY Retrieval Cont Contract by Max Volume with Bloomberg Symbology#

Front Month Continous Contract by Max Volume can be specified with Bloomberg BSYM symbology: [Bloomberg Product code]A.
For example Brent Crude (exchange symbol BRN), has Bloomberg Product code CO.
Instead of BRN_r_vol, COA Comdty can be specified.

import onetick.py as otp

data = otp.DataSource(db='ICE_EU_COM_SAMPLE_DAILY', tick_type='DAY')
data = data.where(data['UPDATE_TYPE'] == 'Summary')
result = otp.run(data,
                 start=otp.dt(2024, 1, 1),
                 end=otp.dt(2024, 4, 1),
                 timezone='Europe/London',
                 symbols='BSYM::::COA Comdty',
                 symbol_date=otp.dt(2024, 4, 1))
result

	Time	UPDATE_TYPE	OPEN	HIGH	LOW	CLOSE	SETTLE_PRICE	SETTLE_DATE	VOLUME	OPEN_INT	OPEN_INT_DATE	OMDSEQ
0	2024-01-01 23:30:00	Summary	NaN	NaN	NaN	NaN	NaN		0.0	NaN		0
1	2024-01-02 23:30:00	Summary	77.39	79.06	75.60	76.04	75.89	20240102	338351.0	552541.0	20231229	0
2	2024-01-03 23:30:00	Summary	76.06	78.67	74.79	78.44	78.25	20240103	361765.0	526073.0	20240102	0
3	2024-01-04 23:30:00	Summary	78.56	79.41	76.50	77.74	77.59	20240104	356646.0	520589.0	20240103	0
4	2024-01-05 23:30:00	Summary	77.71	79.26	77.66	78.90	78.76	20240105	291002.0	499963.0	20240104	0
...	...	...	...	...	...	...	...	...	...	...	...	...
60	2024-03-25 22:30:00	Summary	84.83	86.51	84.79	86.04	86.08	20240325	354261.0	555528.0	20240322	0
61	2024-03-26 22:30:00	Summary	86.16	86.42	85.19	85.27	85.63	20240326	338858.0	583946.0	20240325	0
62	2024-03-27 22:30:00	Summary	85.27	85.70	84.58	85.70	85.41	20240327	369265.0	605142.0	20240326	0
63	2024-03-28 22:30:00	Summary	85.69	87.07	85.50	87.07	87.00	20240328	414238.0	610314.0	20240327	0
64	2024-03-29 22:30:00	Summary	NaN	NaN	NaN	NaN	NaN		0.0	NaN		0

65 rows × 12 columns

DAY Retrieval Cont Contract by Month (1-12)#

Front Month to Twelve Month Continuous Contract can be specified [Product code]\1 to [Product code]\12.
Rolls based on contract expiry.

import onetick.py as otp

data = otp.DataSource(db='ICE_EU_COM_SAMPLE_DAILY', tick_type='DAY')
data = data.where(data['UPDATE_TYPE'] == 'Summary')
result = otp.run(data,
                 start=otp.dt(2024, 1, 1),
                 end=otp.dt(2024, 4, 1),
                 timezone='Europe/London',
                 symbols='BRN\\1',
                 symbol_date=otp.dt(2024, 4, 1))
result

	Time	UPDATE_TYPE	OPEN	HIGH	LOW	CLOSE	SETTLE_PRICE	SETTLE_DATE	VOLUME	OPEN_INT	OPEN_INT_DATE	OMDSEQ
0	2024-01-01 23:30:00	Summary	NaN	NaN	NaN	NaN	NaN		0.0	NaN		0
1	2024-01-02 23:30:00	Summary	77.39	79.06	75.60	76.04	75.89	20240102	338351.0	552541.0	20231229	0
2	2024-01-03 23:30:00	Summary	76.06	78.67	74.79	78.44	78.25	20240103	361765.0	526073.0	20240102	0
3	2024-01-04 23:30:00	Summary	78.56	79.41	76.50	77.74	77.59	20240104	356646.0	520589.0	20240103	0
4	2024-01-05 23:30:00	Summary	77.71	79.26	77.66	78.90	78.76	20240105	291002.0	499963.0	20240104	0
...	...	...	...	...	...	...	...	...	...	...	...	...
60	2024-03-25 22:30:00	Summary	85.50	87.17	85.40	86.68	86.75	20240325	175000.0	206541.0	20240322	0
61	2024-03-26 22:30:00	Summary	86.81	87.06	85.80	85.86	86.25	20240326	126815.0	169162.0	20240325	0
62	2024-03-27 22:30:00	Summary	85.86	86.39	85.17	86.34	86.09	20240327	96507.0	137464.0	20240326	0
63	2024-03-28 22:30:00	Summary	85.69	87.07	85.50	87.07	87.00	20240328	414238.0	610314.0	20240327	0
64	2024-03-29 22:30:00	Summary	NaN	NaN	NaN	NaN	NaN		0.0	NaN		0

65 rows × 12 columns

DAY Retrieval Cont Contract by Tick Data Method#

Retrieve the Front Month Continuous Contract based on Tick Data Methology (only relevant for TDI_FUT).
Using Symbol Syntax: [Product Code]_r_tdi.

import onetick.py as otp

data = otp.DataSource(db='TDI_FUT_SAMPLE_DAILY', tick_type='DAY')
result = otp.run(data,
                 start=otp.dt(2024, 1, 1),
                 end=otp.dt(2024, 4, 1),
                 timezone='Europe/London',
                 symbols='CO_r_tdi',
                 symbol_date=otp.dt(2024, 4, 1))
result

	Time	OPEN	HIGH	LOW	SETTLE_PRICE	VOLUME	OPEN_INT
0	2024-01-02	77.39	79.06	75.60	75.89	338351	552541.0
1	2024-01-03	76.06	78.67	74.79	78.25	361765	526073.0
2	2024-01-04	78.56	79.41	76.50	77.59	356646	520589.0
3	2024-01-05	77.71	79.26	77.66	78.76	291002	499963.0
4	2024-01-08	78.70	78.95	75.26	76.12	342629	494881.0
...	...	...	...	...	...	...	...
61	2024-03-24	84.83	85.10	84.79	85.10	2955	549192.0
62	2024-03-25	84.83	86.51	84.79	86.08	354261	555528.0
63	2024-03-26	86.16	86.42	85.19	85.63	338858	583946.0
64	2024-03-27	85.27	85.70	84.58	85.41	369265	605142.0
65	2024-03-28	85.69	87.07	85.50	87.00	414238	610314.0

66 rows × 7 columns

DAY Retrieval Cont Contract with Bloomberg Symbology#

Front Month to Twelve Month Continuous Contract can be specified with Bloomberg BSYM symbology [Product code]1 to [Product code]12.
Rolls based on contract expiry.
For example Brent Crude (exchange symbol BRN), has Bloomberg Product code CO.

import onetick.py as otp

data = otp.DataSource(db='ICE_EU_COM_SAMPLE_DAILY', tick_type='DAY')
data = data.where(data['UPDATE_TYPE'] == 'Summary')
result = otp.run(data,
                 start=otp.dt(2024, 1, 1),
                 end=otp.dt(2024, 4, 1),
                 timezone='Europe/London',
                 symbols='BSYM::::CO1 Comdty',
                 symbol_date=otp.dt(2024, 4, 1))
result

	Time	UPDATE_TYPE	OPEN	HIGH	LOW	CLOSE	SETTLE_PRICE	SETTLE_DATE	VOLUME	OPEN_INT	OPEN_INT_DATE	OMDSEQ
0	2024-01-01 23:30:00	Summary	NaN	NaN	NaN	NaN	NaN		0.0	NaN		0
1	2024-01-02 23:30:00	Summary	77.39	79.06	75.60	76.04	75.89	20240102	338351.0	552541.0	20231229	0
2	2024-01-03 23:30:00	Summary	76.06	78.67	74.79	78.44	78.25	20240103	361765.0	526073.0	20240102	0
3	2024-01-04 23:30:00	Summary	78.56	79.41	76.50	77.74	77.59	20240104	356646.0	520589.0	20240103	0
4	2024-01-05 23:30:00	Summary	77.71	79.26	77.66	78.90	78.76	20240105	291002.0	499963.0	20240104	0
...	...	...	...	...	...	...	...	...	...	...	...	...
60	2024-03-25 22:30:00	Summary	85.50	87.17	85.40	86.68	86.75	20240325	175000.0	206541.0	20240322	0
61	2024-03-26 22:30:00	Summary	86.81	87.06	85.80	85.86	86.25	20240326	126815.0	169162.0	20240325	0
62	2024-03-27 22:30:00	Summary	85.86	86.39	85.17	86.34	86.09	20240327	96507.0	137464.0	20240326	0
63	2024-03-28 22:30:00	Summary	85.69	87.07	85.50	87.07	87.00	20240328	414238.0	610314.0	20240327	0
64	2024-03-29 22:30:00	Summary	NaN	NaN	NaN	NaN	NaN		0.0	NaN		0

65 rows × 12 columns