--- file_format: mystnb --- # Real Time and Intraday This section contains 6 examples for Real Time and Intraday using the `onetick-py`. Each example is a self-contained script that can be run against the OneTick Cloud sample databases. ```{literalinclude} webapi_configuration.py ``` ## Latest NBBO Market Snapshot - NBBO Retrieval Across All Symbols in Database The *LATEST* databases provide last value caches, storing the latest prices for each instrument. *LATEST* databases are available for all real time sources. They can only be accessed by those who are entitled to access real time data. The ``SNAP_NBBO`` table includes latest NBBO quote for every symbol. It is only available for Composite databases. Other databases provide ``SNAP_QTE``. Querying by ``SYMBOL_NAME`` returns all symbols. To filter by symbol, please use the ``SYMBOL`` field. ```python import onetick.py as otp data = otp.DataSource(db='US_COMP_LATEST', tick_type='SNAP_NBBO') data = data.limit(1000) result = otp.run(data, # The Start and End Times are set using NOW start=otp.now() - otp.Second(1), end=otp.now(), timezone='America/New_York', symbols='-') result ``` {.dataframe} | | Time | SYMBOL_NAME | BID_PRICE | BID_SIZE | ASK_PRICE | ASK_SIZE | QUOTE_CURRENCY | SYMBOL | TICK_TIME | |----:|------------------------:|------------:|----------:|---------:|----------:|---------:|---------------:|-------:|---------------------------:| | 0 | 2026-08-04 09:40:14.955 | SAP | 192.21 | 100 | 192.33 | 200 | USD | SAP | 2026-08-04 09:40:15.749750 | | 1 | 2026-08-04 09:40:14.955 | XXI | 4.42 | 100 | 4.45 | 100 | USD | XXI | 2026-08-04 09:40:12.181681 | | 2 | 2026-08-04 09:40:14.955 | WSTNU | 10.04 | 5000 | 10.75 | 3000 | USD | WSTNU | 2026-08-04 09:30:01.997604 | | 3 | 2026-08-04 09:40:14.955 | YLDE | 56.75 | 200 | 56.92 | 2100 | USD | YLDE | 2026-08-04 09:40:15.856680 | | 4 | 2026-08-04 09:40:14.955 | VBNK | 19.59 | 300 | 19.91 | 100 | USD | VBNK | 2026-08-04 09:40:14.922921 | | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | | 995 | 2026-08-04 09:40:14.955 | UMDD | 35.84 | 100 | 36.06 | 100 | USD | UMDD | 2026-08-04 09:40:14.794579 | | 996 | 2026-08-04 09:40:14.955 | ULST | 40.29 | 500 | 40.30 | 100 | USD | ULST | 2026-08-04 09:39:59.998443 | | 997 | 2026-08-04 09:40:14.955 | UGE | 18.80 | 200 | 18.91 | 2100 | USD | UGE | 2026-08-04 09:40:14.118550 | | 998 | 2026-08-04 09:40:14.955 | UMC | 20.02 | 900 | 20.03 | 100 | USD | UMC | 2026-08-04 09:40:15.810499 | | 999 | 2026-08-04 09:40:14.955 | ULS | 85.92 | 100 | 86.82 | 200 | USD | ULS | 2026-08-04 09:40:12.596457 | [1000 rows x 9 columns] ## Latest Quote Market Snapshot - Quote Retrieval Across All Symbols in Database The *LATEST* databases provide last value caches, storing the latest prices for each instrument. *LATEST* databases are available for all real time sources. They can only be accessed by those who are entitled to access real time data. The ``SNAP_QTE`` table includes latest quote for every symbol. It is not available for Composite databases which use ``SNAP_NBBO``. Querying by ``SYMBOL_NAME`` returns all symbols. To filter by symbol, please use the ``SYMBOL`` field. ```python import onetick.py as otp data = otp.DataSource(db='CME_GLOBEX_LATEST', tick_type='SNAP_QTE') data = data.limit(1000) result = otp.run(data, # The Start and End Times are set using NOW start=otp.now() - otp.Second(1), end=otp.now(), timezone='America/New_York', # The Symbol is set to any non-empty value to return all symbols. symbols='-') result ``` {.dataframe} | | Time | SYMBOL_NAME | BID_PRICE | BID_SIZE | ASK_PRICE | ASK_SIZE | QUOTE_CURRENCY | SYMBOL | TICK_TIME | |----:|------------------------:|----------------:|----------:|---------:|----------:|---------:|---------------:|----------------:|---------------------------:| | 0 | 2026-08-04 09:50:03.932 | EAD\M26 | 1.6414 | 4 | 1.642 | 4 | AUD | EAD\M26 | 2026-06-15 10:16:00.018016 | | 1 | 2026-08-04 09:50:03.932 | EMD\M26\M27 | 25.0500 | 1 | 199.950 | 1 | USD | EMD\M26\M27 | 2026-06-17 17:57:48.893272 | | 2 | 2026-08-04 09:50:03.932 | EMD\M26\U26 | 32.0000 | 1 | 159.250 | 1 | USD | EMD\M26\U26 | 2026-06-18 09:23:36.429287 | | 3 | 2026-08-04 09:50:03.932 | EMD\M26\H27 | 25.0500 | 1 | 124.950 | 1 | USD | EMD\M26\H27 | 2026-06-17 17:57:48.732984 | | 4 | 2026-08-04 09:50:03.932 | EMD\M26\Z26 | 25.0500 | 1 | 99.900 | 1 | USD | EMD\M26\Z26 | 2026-06-17 17:57:48.773010 | | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | | 995 | 2026-08-04 09:50:03.932 | DC\Z26\Z27 | -0.3300 | 2 | -0.030 | 1 | USD | DC\Z26\Z27 | 2026-08-04 09:39:02.454668 | | 996 | 2026-08-04 09:50:03.932 | CSC\N26\X26 | -0.1730 | 1 | -0.167 | 1 | USD | CSC\N26\X26 | 2026-07-31 14:54:55.028661 | | 997 | 2026-08-04 09:50:03.932 | DC\Z26\G27 | 0.1200 | 3 | 0.190 | 2 | USD | DC\Z26\G27 | 2026-08-04 09:47:11.891593 | | 998 | 2026-08-04 09:50:03.932 | CSC\N26\F27 | -0.1590 | 1 | -0.153 | 1 | USD | CSC\N26\F27 | 2026-07-31 14:23:51.287183 | | 999 | 2026-08-04 09:50:03.932 | GNF\N26\Q26\U26 | 10.6000 | 1 | 13.350 | 1 | USX | GNF\N26\Q26\U26 | 2026-07-31 14:53:20.953447 | 1000 rows x 9 columns ## Latest Market Snapshot - Trade and Quote / NBBO Retrieval Across All Symbols in Database The *LATEST* databases provide last value caches, storing the latest prices for each instrument. *LATEST* databases are available for all real time sources. They can only be accessed by those who are entitled to access real time data. The ``SNAP`` table includes the combined latest trade and quote or NBBO for every symbol. Querying by ``SYMBOL_NAME`` returns all symbols. To filter by symbol, please use the ``SYMBOL`` field. ```python import onetick.py as otp data = otp.DataSource(db='US_COMP_LATEST', tick_type='SNAP') data = data.limit(1000) result = otp.run(data, # The Start and End Times are set using NOW start=otp.now() - otp.Second(1), end=otp.now(), timezone='America/New_York', # The Symbol is set to any non-empty value to return all symbols. symbols='-') result ``` {.dataframe} | | Time | SYMBOL_NAME | PRICE | SIZE | TRADE_CURRENCY | OPEN | CLOSE | ... | HIGH | LOW | SYMBOL | LAST_TRADE_TIME | BID_PRICE | ASK_PRICE | LAST_QUOTE_TIME | |----:|------------------------:|------------:|--------:|-----:|---------------:|------:|------:|----:|--------:|-------:|-------:|---------------------------:|----------:|----------:|---------------------------:| | 0 | 2026-08-04 09:41:33.048 | XXRP | 21.3400 | 240 | USD | 21.20 | 21.34 | ... | 21.3400 | 21.176 | XXRP | 2026-08-04 09:40:06.871326 | 21.29 | 21.34 | 2026-08-04 09:41:32.757718 | | 1 | 2026-08-04 09:41:33.048 | SMUP | 5.3036 | 500 | USD | 5.03 | 4.87 | ... | 5.3900 | 5.030 | SMUP | 2026-08-04 09:38:59.441185 | 5.32 | 5.34 | 2026-08-04 09:41:33.976781 | | 2 | 2026-08-04 09:41:33.048 | SMX | 17.4000 | 284 | USD | 15.01 | 16.53 | ... | NaN | NaN | SMX | 2026-08-04 09:28:41.845362 | 16.26 | 17.40 | 2026-08-04 09:35:02.753155 | | 3 | 2026-08-04 09:41:33.048 | SMU | 6.7600 | 100 | USD | 6.41 | 6.18 | ... | 6.8795 | 6.370 | SMU | 2026-08-04 09:41:25.569900 | 6.75 | 6.77 | 2026-08-04 09:41:33.977176 | | 4 | 2026-08-04 09:41:33.048 | SMR | 9.4500 | 200 | USD | 9.19 | 9.01 | ... | 9.5400 | 9.190 | SMR | 2026-08-04 09:41:33.523574 | 9.44 | 9.45 | 2026-08-04 09:41:34.003923 | | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | | 995 | 2026-08-04 09:41:33.048 | ACDC | 4.0450 | 436 | USD | 4.05 | 4.11 | ... | 4.0600 | 4.000 | ACDC | 2026-08-04 09:40:39.174113 | 4.03 | 4.05 | 2026-08-04 09:41:32.571879 | | 996 | 2026-08-04 09:41:33.048 | ACCS | 6.6500 | 100 | USD | 6.74 | 6.64 | ... | 6.7400 | 6.650 | ACCS | 2026-08-04 09:32:46.931936 | 6.60 | 7.00 | 2026-08-04 09:41:30.002186 | | 997 | 2026-08-04 09:41:33.048 | SPHL | 2.6171 | 189 | USD | 2.64 | 2.60 | ... | NaN | NaN | SPHL | 2026-08-04 09:01:57.854878 | 2.61 | 2.70 | 2026-08-04 09:30:17.000319 | | 998 | 2026-08-04 09:41:33.048 | ATPC | 2.3400 | 132 | USD | 2.30 | 2.32 | ... | 2.4000 | 2.190 | ATPC | 2026-08-04 09:41:05.238407 | 2.33 | 2.36 | 2026-08-04 09:40:46.479959 | | 999 | 2026-08-04 09:41:33.048 | ATOS | 2.2216 | 250 | USD | 2.18 | 2.17 | ... | 2.2800 | 2.180 | ATOS | 2026-08-04 09:36:02.981678 | 2.23 | 2.34 | 2026-08-04 09:41:18.537418 | 1000 rows x 20 columns ## Latest Trade Market Snapshot - Trade Retrieval Across All Symbols in Database The *LATEST* databases provide last value caches, storing the latest prices for each instrument. *LATEST* databases are available for all real time sources. They can only be accessed by those who are entitled to access real time data. The ``SNAP_TRD`` table includes latest trade for every symbol. Querying by ``SYMBOL_NAME`` returns all symbols. To filter by symbol, please use the ``SYMBOL`` field. ```python import onetick.py as otp data = otp.DataSource(db='US_COMP_LATEST', tick_type='SNAP_TRD') data = data.limit(1000) result = otp.run(data, # The Start and End Times are set using NOW start=otp.now() - otp.Second(1), end=otp.now(), timezone='America/New_York', symbols='-') result ``` {.dataframe} | | Time | SYMBOL_NAME | PRICE | SIZE | TRADE_CURRENCY | OPEN | CLOSE | ... | VOLUME | VOLUME_MAIN_SESSION | VOLUME_EXTENDED | HIGH | LOW | SYMBOL | TICK_TIME | |----:|------------------------:|------------:|--------:|-----:|---------------:|------:|------:|----:|--------:|--------------------:|----------------:|--------:|-------:|-------:|---------------------------:| | 0 | 2026-08-04 09:49:14.298 | XXRP | 21.1600 | 200 | USD | 21.20 | 21.34 | ... | 51628 | 42505 | 9123 | 21.3400 | 21.145 | XXRP | 2026-08-04 09:48:54.555459 | | 1 | 2026-08-04 09:49:14.298 | SMUP | 5.2500 | 100 | USD | 5.03 | 4.87 | ... | 29120 | 17116 | 12004 | 5.3900 | 5.030 | SMUP | 2026-08-04 09:44:20.531986 | | 2 | 2026-08-04 09:49:14.298 | SMX | 17.4000 | 284 | USD | 15.01 | 16.53 | ... | 384 | 0 | 384 | NaN | NaN | SMX | 2026-08-04 09:28:41.845362 | | 3 | 2026-08-04 09:49:14.298 | SMU | 6.5700 | 100 | USD | 6.41 | 6.18 | ... | 174156 | 120947 | 53209 | 6.8795 | 6.370 | SMU | 2026-08-04 09:49:12.550636 | | 4 | 2026-08-04 09:49:14.298 | SMR | 9.2950 | 400 | USD | 9.19 | 9.01 | ... | 3241770 | 2754069 | 487701 | 9.5400 | 9.190 | SMR | 2026-08-04 09:49:14.166112 | | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | | 995 | 2026-08-04 09:49:14.298 | ACDC | 4.0600 | 100 | USD | 4.05 | 4.11 | ... | 29697 | 26503 | 3194 | 4.0600 | 4.000 | ACDC | 2026-08-04 09:49:15.084007 | | 996 | 2026-08-04 09:49:14.298 | ACCS | 6.8000 | 100 | USD | 6.74 | 6.64 | ... | 436 | 436 | 0 | 6.8000 | 6.640 | ACCS | 2026-08-04 09:44:14.519060 | | 997 | 2026-08-04 09:49:14.298 | SPHL | 2.6171 | 189 | USD | 2.64 | 2.60 | ... | 189 | 0 | 189 | NaN | NaN | SPHL | 2026-08-04 09:01:57.854878 | | 998 | 2026-08-04 09:49:14.298 | ATPC | 2.3700 | 100 | USD | 2.30 | 2.32 | ... | 4472663 | 136504 | 4336159 | 2.4200 | 2.190 | ATPC | 2026-08-04 09:48:58.605412 | | 999 | 2026-08-04 09:49:14.298 | ATOS | 2.2800 | 700 | USD | 2.18 | 2.17 | ... | 13582 | 13165 | 417 | 2.3321 | 2.180 | ATOS | 2026-08-04 09:44:28.298270 | 1000 rows x 17 columns ## Returns Todays Trades Data will only be returned for those who are entitled to access real time data. ```python import onetick.py as otp # The US_COMP_REPLAY database replays older data, and is available to all. data = otp.DataSource(db='US_COMP_REPLAY', tick_type='TRD') # Limit to First 1000 Trades data = data.limit(1000) result = otp.run(data, # get the current date == start of day start=otp.now().dt.date(), end=otp.now(), timezone='America/New_York', symbols='CSCO') result ``` {.dataframe} | | Time | EXCH_TIME | TRF_TIME | EXCHANGE | ... | COND | TICK_STATUS | DELETED_TIME | OMDSEQ | |----:|---------------------------:|------------------------------:|------------------------------:|---------:|----:|-----:|------------:|--------------------:|-------:| | 0 | 2026-08-03 04:01:04.954767 | 2026-08-03 04:00:00.504781214 | 1969-12-31 19:00:00.000000000 | P | ... | @FTI | 0 | 1969-12-31 19:00:00 | 19 | | 1 | 2026-08-03 04:01:04.995332 | 2026-08-03 04:00:00.545682770 | 1969-12-31 19:00:00.000000000 | P | ... | @ TI | 0 | 1969-12-31 19:00:00 | 10 | | 2 | 2026-08-03 04:01:04.995334 | 2026-08-03 04:00:00.545682770 | 1969-12-31 19:00:00.000000000 | P | ... | @ TI | 0 | 1969-12-31 19:00:00 | 11 | | 3 | 2026-08-03 04:01:05.059417 | 2026-08-03 04:00:00.609225364 | 1969-12-31 19:00:00.000000000 | K | ... | @FTI | 0 | 1969-12-31 19:00:00 | 0 | | 4 | 2026-08-03 04:01:05.083970 | 2026-08-03 04:00:00.546032382 | 2026-08-03 04:00:00.634145519 | D | ... | @ TI | 0 | 1969-12-31 19:00:00 | 8 | | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | | 995 | 2026-08-03 07:35:04.553968 | 2026-08-03 07:34:00.095450601 | 2026-08-03 07:34:00.103777380 | D | ... | @ TI | 0 | 1969-12-31 19:00:00 | 0 | | 996 | 2026-08-03 07:35:35.714718 | 2026-08-03 07:34:31.264478680 | 2026-08-03 07:34:31.264696817 | D | ... | @ TI | 0 | 1969-12-31 19:00:00 | 0 | | 997 | 2026-08-03 07:36:14.709390 | 2026-08-03 07:35:09.695728000 | 2026-08-03 07:35:10.259392851 | D | ... | C TI | 0 | 1969-12-31 19:00:00 | 0 | | 998 | 2026-08-03 07:36:15.090211 | 2026-08-03 07:35:10.509138000 | 2026-08-03 07:35:10.640662687 | D | ... | C TI | 0 | 1969-12-31 19:00:00 | 0 | | 999 | 2026-08-03 07:36:16.067989 | 2026-08-03 07:35:10.597008000 | 2026-08-03 07:35:11.617630548 | D | ... | C TI | 0 | 1969-12-31 19:00:00 | 0 | 1000 rows x 21 columns ## Returns Recent Trades Data will only be returned for those who are entitled to access real time data. ```python import onetick.py as otp # The US_COMP_REPLAY database replays older data, and is available to all. data = otp.DataSource(db='US_COMP_REPLAY', tick_type='TRD') # Limit to First 1000 Trades data = data.limit(1000) result = otp.run(data, # The Start and End Times are set using NOW, and TIMEDELTA and apply the timezone start=otp.now() - otp.Minute(5), end=otp.now(), timezone='America/New_York', symbols='CSCO') result ``` {.dataframe} | | Time | EXCH_TIME | TRF_TIME | EXCHANGE | ... | COND | TICK_STATUS | DELETED_TIME | OMDSEQ | |----:|---------------------------:|------------------------------:|------------------------------:|---------:|----:|-----:|------------:|--------------------:|-------:| | 0 | 2026-08-03 10:16:13.252999 | 2026-08-03 10:15:08.797520000 | 2026-08-03 10:15:08.802919026 | D | ... | @ I | 0 | 1969-12-31 19:00:00 | 5 | | 1 | 2026-08-03 10:16:13.253007 | 2026-08-03 10:15:08.799097000 | 2026-08-03 10:15:08.804125110 | D | ... | @ I | 0 | 1969-12-31 19:00:00 | 13 | | 2 | 2026-08-03 10:16:13.552707 | 2026-08-03 10:15:09.103285249 | 1969-12-31 19:00:00.000000000 | Q | ... | @F I | 0 | 1969-12-31 19:00:00 | 43 | | 3 | 2026-08-03 10:16:13.555496 | 2026-08-03 10:15:09.104806783 | 2026-08-03 10:15:09.105502853 | D | ... | @ | 0 | 1969-12-31 19:00:00 | 837 | | 4 | 2026-08-03 10:16:13.556629 | 2026-08-03 10:15:09.104876699 | 2026-08-03 10:15:09.105857660 | D | ... | @ | 0 | 1969-12-31 19:00:00 | 103 | | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | | 995 | 2026-08-03 10:18:13.720910 | 2026-08-03 10:17:09.270806368 | 2026-08-03 10:17:09.271032293 | D | ... | @ I | 0 | 1969-12-31 19:00:00 | 45 | | 996 | 2026-08-03 10:18:14.218489 | 2026-08-03 10:17:09.768635898 | 2026-08-03 10:17:09.769076138 | D | ... | @4 I | 0 | 1969-12-31 19:00:00 | 20 | | 997 | 2026-08-03 10:18:14.404376 | 2026-08-03 10:17:09.954062918 | 1969-12-31 19:00:00.000000000 | V | ... | @ | 0 | 1969-12-31 19:00:00 | 2 | | 998 | 2026-08-03 10:18:14.407793 | 2026-08-03 10:17:09.957284178 | 2026-08-03 10:17:09.957672243 | D | ... | @4 I | 0 | 1969-12-31 19:00:00 | 60 | | 999 | 2026-08-03 10:18:14.483209 | 2026-08-03 10:17:10.033782135 | 2026-08-03 10:17:10.034163060 | D | ... | @4 W | 0 | 1969-12-31 19:00:00 | 63 | 1000 rows x 21 columns