# Data Retrieval - Bars
This section contains 3 examples for Data Retrieval - Bars using the `onetick-py`.
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Each example is a self-contained script that can be run against the OneTick Cloud sample databases.
```default
# 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__'
```
## Daily Trade Bars
Retrieve Daily OHLC Records from the `US_COMP_SAMPLE_DAILY` database, and `DAY` table.
```ipython3
import onetick.py as otp
data = otp.DataSource(db='US_COMP_SAMPLE_DAILY', tick_type='DAY')
result = otp.run(data,
start=otp.dt(2024, 1, 1),
end=otp.dt(2024, 2, 1),
timezone='America/New_York',
symbols='CSCO')
result
```
```myst-ansi
Time EXCHANGE OPEN HIGH LOW CLOSE VOLUME \
0 2024-01-02 20:15:00 A 50.460 50.830 50.27 50.550 62688
1 2024-01-02 20:15:00 B 50.420 50.830 50.29 50.530 40416
2 2024-01-02 20:15:00 C 50.505 50.800 50.26 50.520 82490
3 2024-01-02 20:15:00 D 50.470 50.860 50.25 50.530 7404940
4 2024-01-02 20:15:00 H 50.490 50.830 50.26 50.530 136771
.. ... ... ... ... ... ... ...
373 2024-01-31 20:15:00 V 51.865 51.905 50.12 50.175 1038760
374 2024-01-31 20:15:00 X 51.770 51.770 50.12 50.180 76701
375 2024-01-31 20:15:00 Y 51.340 51.340 50.12 50.180 186667
376 2024-01-31 20:15:00 Z 51.810 51.850 50.11 50.170 1519391
377 2024-01-31 20:15:00 51.850 51.940 50.07 50.180 29311787
VWAP PRICE_OPENING_AUCTION VOLUME_OPENING_AUCTION \
0 50.420217 NaN 0
1 50.508402 NaN 0
2 50.477827 NaN 0
3 50.551240 NaN 0
4 50.464547 NaN 0
.. ... ... ...
373 50.556664 NaN 0
374 50.567621 NaN 0
375 50.425931 NaN 0
376 50.477362 NaN 0
377 50.479861 NaN 267748
PRICE_CLOSING_AUCTION VOLUME_CLOSING_AUCTION VOLUME_MAIN_SESSION \
0 NaN 0 61348
1 NaN 0 40416
2 NaN 0 82486
3 NaN 0 6164089
4 NaN 0 136771
.. ... ... ...
373 NaN 0 1038570
374 NaN 0 76701
375 NaN 0 186667
376 NaN 0 1516783
377 NaN 5533800 21851859
VOLUME_PRE_MARKET VOLUME_POST_MARKET VOLUME_ODD_LOT VOLUME_ROUND_LOT \
0 1340 0 4804 57884
1 0 0 8160 32256
2 4 0 17930 64560
3 4769 1236082 478272 6926668
4 0 0 23687 113084
.. ... ... ... ...
373 190 0 66001 972759
374 0 0 5555 71146
375 0 0 28118 158549
376 2579 29 180563 1338828
377 51439 1606941 2071248 27240539
VOLUME_OFF_EXCHANGE OMDSEQ
0 0 30021
1 0 30022
2 0 30023
3 7404940 30024
4 0 30025
.. ... ...
373 0 29789
374 0 29790
375 0 29791
376 0 29792
377 10210813 29793
[378 rows x 19 columns]
```
## Minute Trade Bars
Retrieve pre-calculated 1 minute Trade Bars from the `US_COMP_SAMPLE_BARS` database, and `TRD_1M` table.
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Bars are calculated at the end of each minute, so setting time range from 09:31 to 16:01.
```ipython3
import onetick.py as otp
data = otp.DataSource(db='US_COMP_SAMPLE_BARS', tick_type='TRD_1M')
result = otp.run(data,
start=otp.dt(2024, 1, 3, 9, 31),
end=otp.dt(2024, 1, 3, 16, 1),
timezone='America/New_York',
symbols='CSCO')
result
```
```myst-ansi
Time FIRST_TIME FIRST FIRST_SIZE \
0 2024-01-03 09:31:00 2024-01-03 09:30:00.127459523 50.1700 100
1 2024-01-03 09:32:00 2024-01-03 09:31:04.039361452 50.1501 210
2 2024-01-03 09:33:00 2024-01-03 09:32:01.135031886 50.0900 100
3 2024-01-03 09:34:00 2024-01-03 09:33:01.573754500 50.0400 100
4 2024-01-03 09:35:00 2024-01-03 09:34:00.147786878 50.0200 100
.. ... ... ... ...
385 2024-01-03 15:56:00 2024-01-03 15:55:00.024403059 50.4800 100
386 2024-01-03 15:57:00 2024-01-03 15:56:00.200203893 50.5100 100
387 2024-01-03 15:58:00 2024-01-03 15:57:00.199711671 50.5150 200
388 2024-01-03 15:59:00 2024-01-03 15:58:00.000316902 50.5200 100
389 2024-01-03 16:00:00 2024-01-03 15:59:00.000861861 50.5300 200
HIGH_TIME HIGH HIGH_SIZE \
0 2024-01-03 09:30:04.203519590 50.2200 100
1 2024-01-03 09:31:04.532601592 50.1750 100
2 2024-01-03 09:32:01.135031886 50.0900 100
3 2024-01-03 09:33:06.244990351 50.0600 100
4 2024-01-03 09:34:45.686497272 50.0400 100
.. ... ... ...
385 2024-01-03 15:55:49.932002214 50.5199 100
386 2024-01-03 15:56:55.714073540 50.5300 290
387 2024-01-03 15:57:10.756235710 50.5450 200
388 2024-01-03 15:58:34.858710440 50.5450 100
389 2024-01-03 15:59:34.102288914 50.5600 100
LOW_TIME LOW LOW_SIZE \
0 2024-01-03 09:30:00.280877749 50.0020 200
1 2024-01-03 09:31:46.066142387 50.0800 100
2 2024-01-03 09:32:58.010510866 50.0301 267
3 2024-01-03 09:33:53.740006921 50.0000 200
4 2024-01-03 09:34:33.162152409 50.0000 100
.. ... ... ...
385 2024-01-03 15:55:00.117020300 50.4700 100
386 2024-01-03 15:56:12.301937097 50.4850 300
387 2024-01-03 15:57:00.675307866 50.5100 100
388 2024-01-03 15:58:09.987777690 50.5100 400
389 2024-01-03 15:59:10.994674253 50.5200 200
LAST_TIME LAST LAST_SIZE VWAP TWAP \
0 2024-01-03 09:30:59.206785096 50.160 100 50.141276 50.147029
1 2024-01-03 09:31:59.457678670 50.090 228 50.124406 50.114364
2 2024-01-03 09:32:59.301339757 50.040 100 50.070231 50.066961
3 2024-01-03 09:33:56.264120820 50.025 100 50.030940 50.031961
4 2024-01-03 09:34:59.152722398 50.020 100 50.022197 50.022726
.. ... ... ... ... ...
385 2024-01-03 15:55:59.409859714 50.505 400 50.499198 50.500819
386 2024-01-03 15:56:59.532887305 50.515 100 50.504659 50.502380
387 2024-01-03 15:57:59.455946880 50.520 100 50.527872 50.530826
388 2024-01-03 15:58:59.649347440 50.530 200 50.531480 50.529147
389 2024-01-03 15:59:59.990217289 50.520 4300 50.540520 50.538417
VOLUME TRADE_CURRENCY TRADE_TICK_COUNT CLOUD_DB OMDSEQ
0 69657 USD 418 NYSE_TAQ 0
1 39792 USD 244 NYSE_TAQ 0
2 26904 USD 187 NYSE_TAQ 0
3 32673 USD 149 NYSE_TAQ 0
4 32783 USD 173 NYSE_TAQ 0
.. ... ... ... ... ...
385 185335 USD 925 NYSE_TAQ 0
386 166268 USD 850 NYSE_TAQ 0
387 346983 USD 1277 NYSE_TAQ 0
388 166368 USD 669 NYSE_TAQ 0
389 627351 USD 2058 NYSE_TAQ 0
[390 rows x 20 columns]
```
## Minute Quote Bars
Retrieve pre-calculated 1 minute Quote Bars from the `US_COMP_SAMPLE_BARS` database, and `QTE_1M` table.
Bars are calculated at the end of each minute, so setting time range from 09:31 to 16:01.
```ipython3
import onetick.py as otp
data = otp.DataSource(db='US_COMP_SAMPLE_BARS', tick_type='QTE_1M')
result = otp.run(data,
start=otp.dt(2024, 1, 3, 9, 31),
end=otp.dt(2024, 1, 3, 16, 1),
timezone='America/New_York',
symbols='CSCO')
result
```
```myst-ansi
Time FIRST_BID_TIME FIRST_BID_PRICE \
0 2024-01-03 09:31:00 2024-01-03 09:30:00.001830617 50.00
1 2024-01-03 09:32:00 2024-01-03 09:31:00.001237971 50.15
2 2024-01-03 09:33:00 2024-01-03 09:32:00.005627484 50.08
3 2024-01-03 09:34:00 2024-01-03 09:33:00.000548600 50.03
4 2024-01-03 09:35:00 2024-01-03 09:34:00.003041083 50.02
.. ... ... ...
385 2024-01-03 15:56:00 2024-01-03 15:55:00.000474694 50.47
386 2024-01-03 15:57:00 2024-01-03 15:56:00.003980007 50.50
387 2024-01-03 15:58:00 2024-01-03 15:57:00.005213668 50.51
388 2024-01-03 15:59:00 2024-01-03 15:58:00.000316689 50.52
389 2024-01-03 16:00:00 2024-01-03 15:59:00.000862449 50.53
FIRST_BID_SIZE FIRST_ASK_TIME FIRST_ASK_PRICE \
0 9 2024-01-03 09:30:00.001830617 50.18
1 5 2024-01-03 09:31:00.001237971 50.17
2 4 2024-01-03 09:32:00.005627484 50.10
3 5 2024-01-03 09:33:00.000548600 50.05
4 7 2024-01-03 09:34:00.003041083 50.03
.. ... ... ...
385 29 2024-01-03 15:55:00.000474694 50.48
386 21 2024-01-03 15:56:00.003980007 50.51
387 60 2024-01-03 15:57:00.005213668 50.52
388 24 2024-01-03 15:58:00.000316689 50.53
389 43 2024-01-03 15:59:00.000862449 50.54
FIRST_ASK_SIZE HIGH_BID_TIME HIGH_BID HIGH_BID_SIZE \
0 2 2024-01-03 09:30:04.009983752 50.22 1
1 7 2024-01-03 09:31:04.425141902 50.17 1
2 5 2024-01-03 09:32:00.005627484 50.08 4
3 7 2024-01-03 09:33:06.134568404 50.06 1
4 1 2024-01-03 09:34:55.666761587 50.04 2
.. ... ... ... ...
385 24 2024-01-03 15:55:45.729449709 50.51 2
386 72 2024-01-03 15:56:54.524957985 50.52 25
387 66 2024-01-03 15:57:10.754109243 50.54 1
388 108 2024-01-03 15:58:34.796592944 50.54 2
389 184 2024-01-03 15:59:28.015286783 50.55 12
... MID_LAST SPREAD_MIN SPREAD_MAX SPREAD_TWAP SPREAD_MEDIAN \
0 ... 50.160 0.0 0.18 0.018177 0.02
1 ... 50.090 0.0 0.02 0.014063 0.01
2 ... 50.040 0.0 0.02 0.014197 0.01
3 ... 50.025 0.0 0.02 0.012603 0.01
4 ... 50.015 0.0 0.02 0.012166 0.01
.. ... ... ... ... ... ...
385 ... 50.505 0.0 0.02 0.009952 0.01
386 ... 50.515 0.0 0.02 0.010000 0.01
387 ... 50.525 0.0 0.02 0.009999 0.01
388 ... 50.535 0.0 0.02 0.010000 0.01
389 ... 50.525 0.0 0.02 0.009978 0.01
SPREAD_LAST QUOTE_CURRENCY QUOTE_TICK_COUNT CLOUD_DB OMDSEQ
0 0.02 USD 10370 NYSE_TAQ 0
1 0.02 USD 6711 NYSE_TAQ 0
2 0.02 USD 4338 NYSE_TAQ 0
3 0.01 USD 2813 NYSE_TAQ 0
4 0.01 USD 3545 NYSE_TAQ 0
.. ... ... ... ... ...
385 0.01 USD 13079 NYSE_TAQ 0
386 0.01 USD 9070 NYSE_TAQ 0
387 0.01 USD 11637 NYSE_TAQ 0
388 0.01 USD 6922 NYSE_TAQ 0
389 0.01 USD 13240 NYSE_TAQ 0
[390 rows x 35 columns]
```