Package: live-trading-indicators
live_trading_indicatorsA package for obtaining quotation data from various sources and saving them to a database. Quotes can be quickly extracted and used for calculations and forecasts. It is possible to receive and process data in real time. There are a significant number of ready-to-use indicators.
The integrity of the data stored in the database is carefully monitored.One of the advantages of the live_trading_indicators library is the speed of work. Extracting 31 million quotes in one year on the 1s timeframe takes less than two seconds:performance test.To calculate indicators, you can also use the Pandas Data Frame as a data source.The current version allows you to receive exchange data from:Binance(spot,futures USD-M,futures COIN-M).Many different exchanges viaCCXT(CryptoCurrency eXchange Trading Library)The data can be obtained innumpy ndarrayandDataframe Pandas..Package data from online sources is stored by default in the.ltifolder of the user's home directory. A significant amount of data can be created in this folder, depending on the number of instruments and their timeframes. Only data received from online sources is saved.Version 0.7.5what's new0.7.5New indicator - ChandelierFix some bugs0.7.4New indicator - MFIFix some bugsChange some defaultsettingsduring a new installation0.7.3The quotation database has been optimized (the conversion may take some time at the first launch)Fix some bugs (when ccxt is used for multiple exchanges at the same time)New indicator - Williams %R0.7.2The quotation database has been optimized (the conversion may take some time at the first launch)New indicator - Ichimoku0.7.1Migration of quote storage to sqlite3Added support for three compression algorithms: gzip, bz2 and lz4 (see)Add the depth parameter for ZigZag indicatorprevious releases...Installingpipinstalllive_trading_indicatorsFeedbackDiscussionsIssuesQuick startAll the examples given here can be found injupyter notebook examples.Getting quotes (online / cache)importlive_trading_indicatorsasltiindicators=lti.Indicators('binance')ohlcv=indicators.OHLCV('ethusdt','4h','2022-07-01','2022-07-01')print(ohlcv)Result:<OHLCV data> symbol: ethusdt, timeframe: 4h
date: 2022-07-01T00:00 - 2022-07-01T20:00 (length: 6) 
empty bars: count 0 (0.00 %), max consecutive 0
Values: time, open, high, low, close, volumeNowohlcvcontains quotes innumpy array(ohlcv.time,ohlcv.open,ohlcv.high,ohlcv.low,ohlcv.close,ohlcv.volume).Export in pandas dataframedataframe=ohlcv.pandas()print(dataframe.head())Result:time     open     high      low    close       volume
0 2022-07-01 00:00:00  1071.02  1117.00  1050.46  1054.52  430646.8720
1 2022-07-01 04:00:00  1054.52  1076.43  1045.41  1066.81  275557.9328
2 2022-07-01 08:00:00  1066.81  1086.44  1033.44  1050.22  252105.5665
3 2022-07-01 12:00:00  1050.21  1074.23  1043.00  1056.86  298465.0695
4 2022-07-01 16:00:00  1056.86  1083.10  1054.82  1067.91  158796.2248Example of getting indicator data from Bybit quotes via ccxt (online / cache)importlive_trading_indicatorsasltiindicators=lti.Indicators('ccxt.bybit')macd=indicators.MACD('ETHUSDT','1h','2022-07-01','2022-07-30',period_short=15,period_long=26,period_signal=9)print(macd[40:].pandas().head())Result:time      macd    signal      hist
0 2022-07-02 16:00:00 -1.661969 -3.514499  1.852530
1 2022-07-02 17:00:00 -0.983912 -3.125461  2.141548
2 2022-07-02 18:00:00 -0.081701 -2.617233  2.535532
3 2022-07-02 19:00:00  0.464134 -2.064394  2.528529
4 2022-07-02 20:00:00  0.828222 -1.477419  2.305641Example of getting indicator data from Pandas quotesimportpandasimportlive_trading_indicatorsasltidataframe=pandas.read_csv('tests/data/ETHUSDT-1m-2022-08-15.zip',header=None)dataframe.rename(columns={0:'time',1:'open',2:'high',3:'low',4:'close',5:'volume',},inplace=True)indicators=lti.Indicators(dataframe)macd=indicators.MACD(period_short=15,period_long=26,period_signal=9)print(macd[40:].pandas().head())Result:time      macd    signal      hist
0 2022-08-15 00:40:00  3.403958  2.320975  1.082984
1 2022-08-15 00:41:00  3.540428  2.643593  0.896835
2 2022-08-15 00:42:00  3.594786  2.930063  0.664722
3 2022-08-15 00:43:00  3.684476  3.170449  0.514027
4 2022-08-15 00:44:00  3.763257  3.354183  0.409074Plotting indicators chartsPlotting uses matplotlib. These are optional features, so matplotlib must be installed separately.
There are two methods for plotting: plot() and show(). plot() returns the drawn figure, show() returns None. For jupyter notepad, it is better to use show(), since plot() can draw a figure twice.indicators=lti.Indicators('binance','2022-07-01','2022-07-15')bb=indicators.BollingerBands('btcusdt','4h','2022-07-05','2022-07-15',period=14)bb.show()Result:You can find other examples of chartshere.Getting real-time data (the last 3 minutes on the 1m timeframe without an incomplete bar)To get real-time data, youdon't have to specify an end date.importdatetimeasdtimportlive_trading_indicatorsasltiutcnow=dt.datetime.utcnow()print(f'Now is{utcnow}UTC')indicators=lti.Indicators('binance',utcnow-dt.timedelta(minutes=3))ohlcv=indicators.OHLCV('btcusdt','1m')print(ohlcv.pandas())Result:Now is 2022-11-04 09:32:31.528230 UTC
                 time      open      high       low     close     volume
0 2022-11-04 09:29:00  20594.39  20595.60  20591.06  20592.38  177.35380
1 2022-11-04 09:30:00  20592.38  20600.98  20591.75  20600.30  178.40869
2 2022-11-04 09:31:00  20600.98  20623.93  20600.30  20621.45  431.11917Getting real-time data (the last 3 minutes on the 1m timeframe and an incomplete bar)To get data containing an incomplete bar, you must specifywith_incomplete_bar=Truewhen creatingIndicators.utcnow=dt.datetime.utcnow()print(f'Now is{utcnow}UTC')indicators=lti.Indicators('binance',utcnow-dt.timedelta(minutes=3),with_incomplete_bar=True)ohlcv=indicators.OHLCV('btcusdt','1m')print(ohlcv.pandas())Result:Now is 2022-11-04 09:37:07.372986 UTC
                 time      open      high       low     close     volume
0 2022-11-04 09:34:00  20614.55  20618.50  20610.76  20615.97  263.96754
1 2022-11-04 09:35:00  20615.61  20624.00  20610.29  20616.53  258.53777
2 2022-11-04 09:36:00  20615.69  20617.75  20609.74  20611.46  199.43313
3 2022-11-04 09:37:00  20611.11  20611.89  20608.17  20609.02   15.15800Detailslive-trading-indicators supports the following timeframes: 1s, 1m, 3m, 5m, 10m, 15m, 30m, 1h, 2h, 4h, 6h, 8h, 12h, 1d.
The specific supported timeframes for the source depend on the source.Сhecking quoteslive-trading-indicatorscheck the integrity of quotes when they are loaded.
The fraction of lost quotes should not exceed max_empty_bars_fraction. The number of lost quotes in a row should not exceed max_empty_bars_consecutive.
The values of max_empty_bars_fraction and max_empty_bars_consecutive are set to 0 by default. That is, if there is at least one lost quote, LTIExceptionTooManyEmptyBars will be raised:live_trading_indicators.exceptions.LTIExceptionTooManyEmptyBars: Too many empty bars: fraction 0.014076769406392695, consecutive 79200. Source binance, symbol ethusdt, timeframe 1s, date 2021-01-01T00:00:00.000 - 2021-12-31T23:59:59.000.The values of max_empty_bars_fraction and max_empty_bars_consecutive can be set as follows:import live_trading_indicators as lti
lti.config(max_empty_bars_fraction=0.1, max_empty_bars_consecutive=10)If you don't need integrity control at all, do:import live_trading_indicators as lti
lti.config(max_empty_bars_fraction=-1, max_empty_bars_consecutive=-1)The presence of the first and last bars in the date range is also checked. For more details, seeSettings.Informational messagesBy default, log messages are output to the console, and you will see similar messages:2022-11-04 12:32:31,528 Download using api symbol btcusdt timeframe 1m from 2022-11-04T00:00:00.000...To disable these messages, run the following code and restart python.importlive_trading_indicatorsasltilti.config(print_log=False)IndicatorsWhen getting indicator values fromonlinesource, the first two parameters should besymbolandtimeframe. Further, the period can optionally be specified. Then the parameters of the indicator are specified by name.
When getting indicator valuesofflinefrom Pandas DataFrame parameterssymbolandtimeframearenot specified.Example (online)indicators=lti.Indicators('binance','2022-07-01','2022-08-30')sma=indicators.SMA('ethusdt','1h',period=9)macd=indicators.MACD('ethusdt','1h','2022-07-01','2022-07-30',period_short=15,period_long=26,period_signal=9)Example (offline)dataframe=pandas.readcsv('ETHUSDT-1m-2022-08-15.zip')indicators=lti.Indicators(dataframe)macd=indicators.MACD(period_short=15,period_long=26,period_signal=9)sma=indicators.SMA('2022-08-15T03:00','2022-08-15T06:00',period=9)The list of supported indicators and their parameters can be obtained by calling lti.help(). Parameterssymbol,timeframe,time_start,time_endare omitted for brevity.importlive_trading_indicatorsasltiprint(lti.help())ADL(ma_period=None, ma_type='sma') - Accumulation/distribution line.ADX(period=14, smooth=14, ma_type='mma') - Average directional movement index.ATR(smooth=14, ma_type='mma') - Average true range.Aroon(period=14) - Aroon oscillator.Awesome(period_fast=5, period_slow=34, ma_type_fast='smw', ma_type_slow='sma', normalized=False) - Awesome oscillator.BollingerBands(period=20, deviation=2, ma_type='sma', value='close') - Bollinger bands.CCI(period=) - Commodity channel index.Chandelier(period=22, multiplier=3, use_close=False) - Chandelier Exit.EMA(period=, value='close') - Exponential moving average.Ichimoku(period_short=9, period_mid=26, period_long=52, offset_senkou=26, offset_chikou=26) - Ichimoku indicator.Keltner(period=10, multiplier=1, period_atr=10, ma_type='ema', ma_type_atr='mma') - Keltner channel.MA(period=, value='close', ma_type='sma') - Moving average of different types: 'sma', 'ema', 'mma', 'ema0', 'mma0'MACD(period_short=, period_long=, period_signal=, ma_type='ema', ma_type_signal='sma', value='close') - Moving Average Convergence/Divergence.MFI(period=14) - Money flow index.OBV() - On Balance Volume.OHLCV() - Quotes: open, high, low, close, volume.OHLCVM(timeframe_low='1m', bars_on_bins=6) - Quotes and the price of the maximum volume: open, high, low, close, volume, mv_price.ParabolicSAR(start=0.02, maximum=0.2, increment=0.02) - Parabolic SAR.ROC(period=14, ma_period=14, ma_type='sma', value='close') - Rate of Change.RSI(period=, ma_type='mma', value='close') - Relative strength index.SMA(period=, value='close') - Simple moving average.Stochastic(period=, period_d=, smooth=3, ma_type='sma') - Stochastic oscillator.Supertrend(period=10, multipler=3, ma_type='mma') - Supertrend indicator.TEMA(period=, value='close') - Triple exponential moving average.TRIX(period=, value='close') - TRIX oscillator.VWAP() - Volume-weighted average price.VWMA(period=, value='close') - Volume Weighted Moving Average.VolumeClusters(timeframe_low='1m', bars_on_bins=6) - OHLCVM and volume clusters is determined by the lower timeframe.WilliamsR(period=14) - Williams %R oscillator.ZigZag(delta=0.02, depth=1, type='high_low', end_points=False) - Zig-zag indicator (pivots).Specifying the periodThere are three strategies for specifying a time period:1. The time period is specified when creating Indicators (base period)Indicator values can be obtained for any period within the interval specified forIndicators. When exiting the specified interval, an exception will be raisedLTIExceptionOutOfThePeriod.Exampleindicators=lti.Indicators('binance',20220901,20220930)# the base periodohlcv=indicators.OHLCV('um/ethusdt','1h')# the period is not specified, the base period is usedsma22=indicators.SMA('um/ethusdt','1h',20220905,20220915,period=22)# the period is specifiedsma15=indicators.SMA('um/ethusdt','1h',20220905,20221015,period=15)# ERROR, going beyond the boundaries of the base period2. The time period is not specified when creating IndicatorsIn this variant, when getting indicator data, the period should always be specified. When the interval is extended, data may be updated, this may slow down the work.Exampleindicators=lti.Indicators('binance')# period not specifiedohlcv=indicators.OHLCV('um/ethusdt','1h',20220801,20220815)# the period must be specifiedma22=indicators.SMA('um/ethusdt','1h','close',22,20220905,20220915)# the period must be specified3. Real-time modeIn this variant, when creatingIndicators, only the start date is specified. The data is always received up to the current moment.
When creating Indicators, you can specifywith_incomplete_bar=True, then the data of the last, incomplete bar will be received. See the example above.Binance sourceBinance trading symbol codesFor the spot market, they completely coincide with the code on binance (btcusdt,ethusdt, etc.)For the futures marketUSD-M, codes are prefixed withum/(um/btcusdt,um/ethusdt, etc.)For the futures marketCOIN-M, codes are prefixed withcm/(cm/btcusd_perp,cm/ethusd_perp, etc.)CCXT sourceUsing CCXT, you can download data from a large number of exchanges, currently there are more than 100. The available symbols, their names and timeframes depend on the specific source. More information can be found inthe CCXT documentation.The use of ccxt is optional, so it must be installed separately. It can be done like this:pip install ccxtThen you can use all available ccxt exchanges by specifying them through a dot. To download, for example, from binance via ccxt, you need to specify ccxt.binance. To download from okx, we use ccxt.okx, Bybit - ccxt.bybit, etc.Exampleindicators=lti.Indicators('ccxt.okx')ohlcv=indicators.OHLCV('BTC/USDT','1h',20220701,20220702)live-trading-indicatorshas not been tested with all quotation sources supported byccxt. If you find a problem with some data source, open the problemhere.Sometimes theccxtsource may need additional parameters passed throughparams. In this case, these parameters are passed viaexchange_paramswhen creatingIndicators:indicators=lti.Indicators('ccxt.okx',exchange_params={'limit':300})Types of move averagelive-trading-indicators supports the following types of moving averages:'sma' - simple move average'ema' - classical exponential moving average with alpha = 2 / (n + 1), initialized by SMA (as in binance EMA)'ema0' - classical exponential moving average with alpha = 2 / (n + 1), initialized by the first value'mma' - Modified moving average with alpha = 1 / n, initialized by SMA (as in some binance indicators)'mma0' - Modified moving average с alpha = 1 / n, initialized by the first valuelive_trading_indicators library settingsThe settings can be obtained as dict usingconfig():importlive_trading_indicatorsasltiprint(lti.config())Result:{'cache_folder': '/home/user/.lti/data/timeframe_data', 'sources_folder': '/home/user/.lti/data/sources', 'log_folder': '/home/hal/.lti/logs', 'endpoints_required': True, 'max_empty_bars_fraction': 0.0, 'max_empty_bars_consecutive': 0, 'restore_empty_bars': True, 'print_log': True, 'log_level': 'INFO', 'request_timeout': 10, 'request_trys': 3}config()is also used to change the settings:importlive_trading_indicatorsasltilti.config(request_timeout=15)When creating Indicators, you can specify the settings that will be used instead of the saved ones:indicators=lti.Indicators(test_source,time_begin,time_end,timeout=15,request_trys=5)Settingscache_folderDirectory for storing quotation data.log_folderDirectory of log files.endpoints_requiredControl of the presence of the first and last bar in the selected date range. In the absence of the first or last bar, LTIExceptionQuotationDataNotFound is raised. Default: False.max_empty_bars_fractionThe maximum fraction of lost bars, if exceeded, an error will occur. Default: 1 (100% empty bars are allowed).max_empty_bars_consecutiveThe maximum number of lost bars in a row, if exceeded, LTIExceptionTooManyEmptyBars will be raised. Default: -1 (any number of empty bars in a row is allowed).restore_empty_barsIf True, it restores the lost bars (open=close=close of the previous one, volume=0). The control of the number of lost bars (max_empty_bars_fraction, max_empty_bars_consecutive) is performed BEFORE recovery. Default: True.print_logIf True, outputs log messages to standard output. Default: True.log_levelLog registration level. Default: INFO.request_timeoutTimeout of requests to download quotes, seconds. Default: 30.request_trysThe number of attempts to download quotes. Default: 3.quotation_databasePath to the sqlite3 database for storing quotes.compression_typeThe algorithm for compressing quotes when saving to the database. Can be gzip, bz2, lz4 and auto:bz2 - good compression, slowgzip - medium compression, medium speedlz4 - low compression, high speedauto - automatic selectionDefault: auto