def preds(api_key): df = pd.read_csv('GOOGL.csv', index_col='Date') preds = pd.DataFrame() for i in np.arange(start=1, stop=6): if preds.empty: preds = pd.DataFrame(data=df['close'].pct_change(1)) preds.columns = ['today'] else: lags = pd.DataFrame(df['close'].pct_change(i)) lags.columns = ['lag{}'.format(i)] preds = preds.join(lags) preds = preds.join(df['volume']) preds = preds.join(df['close']) preds['dir'] = (preds['close'] > preds['close'].shift(1)).shift(-1) filename = 'GOOGL-lags.csv' try: preds.to_csv('{}'.format(filename)) print('GOOGL lags saved successfully as "{}"'.format(filename)) except: print('Unable to save "{}"'.format(filename)) ti = TechIndicators(key=api_key, output_format='pandas') sma, _ = ti.get_sma(symbol='GOOGL', interval='daily', series_type='close') ema, _ = ti.get_ema(symbol='GOOGL', interval='daily', series_type='close') wma, _ = ti.get_wma(symbol='GOOGL', interval='daily', series_type='close') trima, _ = ti.get_trima(symbol='GOOGL', interval='daily', series_type='close') kama, _ = ti.get_kama(symbol='GOOGL', interval='daily', series_type='close') macd, _ = ti.get_macd(symbol='GOOGL', interval='daily', series_type='close') rsi, _ = ti.get_rsi(symbol='GOOGL', interval='daily', series_type='close') adx, _ = ti.get_adx(symbol='GOOGL', interval='daily') apo, _ = ti.get_apo(symbol='GOOGL', interval='daily', series_type='close') stoch, _ = ti.get_stoch(symbol='GOOGL', interval='daily') ppo, _ = ti.get_ppo(symbol='GOOGL', interval='daily') mom, _ = ti.get_mom(symbol='GOOGL', interval='daily', series_type='close') cci, _ = ti.get_cci(symbol='GOOGL', interval='daily') aroon, _ = ti.get_aroon(symbol='GOOGL', interval='daily', series_type='close') mfi, _ = ti.get_mfi(symbol='GOOGL', interval='daily', series_type='close') dx, _ = ti.get_dx(symbol='GOOGL', interval='daily', series_type='close') ad, _ = ti.get_ad(symbol='GOOGL', interval='daily') obv, _ = ti.get_obv(symbol='GOOGL', interval='daily') filename2 = 'GOOGL-techs.csv' try: preds_test = pd.concat([ sma, ema, wma, trima, kama, macd, rsi, adx, apo, stoch, ppo, mom, cci, aroon, mfi, dx, ad, obv ], axis=1) pd.DataFrame(preds_test).to_csv('{}'.format(filename2)) print('Google techs saved as successfully as "{}"'.format(filename2)) except: print('Unable to save "{}"'.format(filename2))
print("Begining") symbol = "ORCL" interval = "1min" ti = TechIndicators(key='1HAYLUHGCB6E0VXC', output_format='pandas') print("Progress: 0% complete...") ad_data, meta_data = ti.get_ad(symbol=symbol, interval=interval) adosc_data, meta_data = ti.get_adosc(symbol=symbol, interval=interval) adx_data, meta_data = ti.get_adx(symbol=symbol, interval=interval) adxr_data, meta_data = ti.get_adxr(symbol=symbol, interval=interval) apo_data, meta_data = ti.get_apo(symbol=symbol, interval=interval) aroon_data, meta_data = ti.get_aroon(symbol=symbol, interval=interval) aroonosc_data, meta_data = ti.get_aroonosc(symbol=symbol, interval=interval) atr_data, meta_data = ti.get_atr(symbol=symbol, interval=interval) bop_data, meta_data = ti.get_bop(symbol=symbol, interval=interval) cci_data, meta_data = ti.get_cci(symbol=symbol, interval=interval) print("Progress: 20% complete...") cmo_data, meta_data = ti.get_cmo(symbol=symbol, interval=interval) dema_data, meta_data = ti.get_dema(symbol=symbol, interval=interval) dx_data, meta_data = ti.get_dx(symbol=symbol, interval=interval) ema_data, meta_data = ti.get_ema(symbol=symbol, interval=interval) ht_dcperiod_data, meta_data = ti.get_ht_dcperiod(symbol=symbol, interval=interval) ht_dcphase_data, meta_data = ti.get_ht_dcphase(symbol=symbol, interval=interval) ht_phasor_data, meta_data = ti.get_ht_phasor(symbol=symbol, interval=interval)
def techIndicatorPull(symbol): interval = "1min" print("Calculating Tech Indicators ...") ti = TechIndicators(key='1HAYLUHGCB6E0VXC', output_format='pandas') print("Progress: 0% complete...") ad_data, meta_data = ti.get_ad(symbol=symbol, interval=interval) adosc_data, meta_data = ti.get_adosc(symbol=symbol, interval=interval) adx_data, meta_data = ti.get_adx(symbol=symbol, interval=interval) adxr_data, meta_data = ti.get_adxr(symbol=symbol, interval=interval) apo_data, meta_data = ti.get_apo(symbol=symbol, interval=interval) aroon_data, meta_data = ti.get_aroon(symbol=symbol, interval=interval) aroonosc_data, meta_data = ti.get_aroonosc(symbol=symbol, interval=interval) atr_data, meta_data = ti.get_atr(symbol=symbol, interval=interval) bop_data, meta_data = ti.get_bop(symbol=symbol, interval=interval) cci_data, meta_data = ti.get_cci(symbol=symbol, interval=interval) print("Progress: 20% complete...") cmo_data, meta_data = ti.get_cmo(symbol=symbol, interval=interval) dema_data, meta_data = ti.get_dema(symbol=symbol, interval=interval) dx_data, meta_data = ti.get_dx(symbol=symbol, interval=interval) ema_data, meta_data = ti.get_ema(symbol=symbol, interval=interval) ht_dcperiod_data, meta_data = ti.get_ht_dcperiod(symbol=symbol, interval=interval) ht_dcphase_data, meta_data = ti.get_ht_dcphase(symbol=symbol, interval=interval) ht_phasor_data, meta_data = ti.get_ht_phasor(symbol=symbol, interval=interval) ht_sine_data, meta_data = ti.get_ht_sine(symbol=symbol, interval=interval) ht_trendline_data, meta_data = ti.get_ht_trendline(symbol=symbol, interval=interval) ht_trendmode_data, meta_data = ti.get_ht_trendmode(symbol=symbol, interval=interval) print("Progress: 40% complete...") kama_data, meta_data = ti.get_kama(symbol=symbol, interval=interval) macd_data, meta_data = ti.get_macd(symbol=symbol, interval=interval) macdext_data, meta_data = ti.get_macdext(symbol=symbol, interval=interval) mama_data, meta_data = ti.get_mama(symbol=symbol, interval=interval) mfi_data, meta_data = ti.get_mfi(symbol=symbol, interval=interval) midpoint_data, meta_data = ti.get_midpoint(symbol=symbol, interval=interval) midprice_data, meta_data = ti.get_midprice(symbol=symbol, interval=interval) minus_di_data, meta_data = ti.get_minus_di(symbol=symbol, interval=interval) mom_data, meta_data = ti.get_mom(symbol=symbol, interval=interval) natr_data, meta_data = ti.get_natr(symbol=symbol, interval=interval) print("Progress: 60% complete...") obv_data, meta_data = ti.get_obv(symbol=symbol, interval=interval) plus_di_data, meta_data = ti.get_plus_di(symbol=symbol, interval=interval) plus_dm_data, meta_data = ti.get_plus_dm(symbol=symbol, interval=interval) ppo_data, meta_data = ti.get_ppo(symbol=symbol, interval=interval) roc_data, meta_data = ti.get_roc(symbol=symbol, interval=interval) rocr_data, meta_data = ti.get_rocr(symbol=symbol, interval=interval) rsi_data, meta_data = ti.get_rsi(symbol=symbol, interval=interval) sar_data, meta_data = ti.get_sar(symbol=symbol, interval=interval) sma_data, meta_data = ti.get_sma(symbol=symbol, interval=interval) stoch_data, meta_data = ti.get_stoch(symbol=symbol, interval=interval) print("Progress: 80% complete...") stochf_data, meta_data = ti.get_stochf(symbol=symbol, interval=interval) stochrsi_data, meta_data = ti.get_stochrsi(symbol=symbol, interval=interval) t3_data, meta_data = ti.get_t3(symbol=symbol, interval=interval) tema_data, meta_data = ti.get_tema(symbol=symbol, interval=interval) trange_data, meta_data = ti.get_trange(symbol=symbol, interval=interval) trima_data, meta_data = ti.get_trima(symbol=symbol, interval=interval) trix_data, meta_data = ti.get_trix(symbol=symbol, interval=interval) ultsoc_data, meta_data = ti.get_ultsoc(symbol=symbol, interval=interval) willr_data, meta_data = ti.get_willr(symbol=symbol, interval=interval) wma_data, meta_data = ti.get_wma(symbol=symbol, interval=interval) bbands_data, meta_data = ti.get_bbands(symbol=symbol, interval=interval) print("Progress: 90% complete...") result = pd.concat([ ad_data, adosc_data, adx_data, adxr_data, apo_data, aroon_data, aroonosc_data, atr_data, bop_data, cci_data, cmo_data, dema_data, dx_data, ema_data, ht_dcperiod_data, ht_dcphase_data, ht_phasor_data, ht_sine_data, ht_trendline_data, ht_trendmode_data, kama_data, macd_data, macdext_data, mama_data, mfi_data, midpoint_data, midprice_data, minus_di_data, mom_data, natr_data, obv_data, plus_di_data, plus_dm_data, ppo_data, roc_data, rocr_data, rsi_data, sar_data, sma_data, stoch_data, stochf_data, stochrsi_data, t3_data, tema_data, trange_data, trima_data, trix_data, ultsoc_data, willr_data, wma_data, bbands_data ], axis=1) result["stockticker"] = symbol result = result.reindex(result.index.rename('timestamp')) result = result.dropna(axis=0, how='any') result = result.round(2) result = result.rename( columns={ 'Chaikin A/D': 'ChaikinAD', 'Aroon Up': 'AroonUp', 'Aroon Down': 'AroonDown', 'LEAD SINE': 'LeadSine', 'Real Upper Band': 'RealUpperBand', 'Real Middle Band': 'RealMiddleBand', 'Real Lower Band': 'RealLowerBand' }) fd = open('results/rawTechIndicatorData.csv', 'w') result.to_csv(fd, index=True, encoding='utf-8') fd.close() print("Progress: 99% complete...") df = pd.read_csv('results/rawTechIndicatorData.csv') insertToOracleDatabase( df, '''insert /*+ ignore_row_on_dupkey_index(stocktechindicator, stocktechindicator_pk) */ into stocktechindicator (timestamp,ChaikinAD,ADOSC,ADX,ADXR, APO,AroonUp,AroonDown,AROONOSC,ATR, BOP,CCI,CMO,DEMA,DX, EMA,DCPERIOD,HT_DCPHASE,QUADRATURE, PHASE, LEADSINE,SINE,HT_TRENDLINE,TRENDMODE,KAMA, MACD,MACD_Hist,MACD_Signal,MACD_Signal2,MACD2, MACD_Hist2,FAMA,MAMA,MFI,MIDPOINT, MIDPRICE,MINUS_DI,MOM,NATR,OBV, PLUS_DI,PLUS_DM,PPO,ROC,ROCR, RSI,SAR,SMA,SlowK,SlowD, FastK,FastD,FastK2,FastD2,T3, TEMA,TRANGE,TRIMA,TRIX,ULTOSC, WILLR,WMA,RealLowerBand,RealUpperBand,RealMiddleBand, stockticker) values (:1, :2, :3, :4, :5, :6, :7, :8, :9, :10, :11, :12, :13, :14, :15, :16, :17, :18, :19, :20, :21, :22, :23, :24, :25, :26, :27, :28, :29, :30, :31, :32, :33, :34, :35, :36, :37, :38, :39, :40, :41, :42, :43, :44, :45, :46, :47, :48, :49, :50, :51, :52, :53, :54, :55, :56, :57, :58, :59, :60, :61, :62, :63, :64, :65, :66)''')
def save_ti(ticker, interval='daily'): ti = TechIndicators(key='WS8K5VM8FZL52BTH', output_format='pandas') ti.get_sma( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_sma.csv') call_check() ti.get_ema( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_ema.csv') call_check() ti.get_wma( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_wma.csv') call_check() ti.get_dema( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_dema.csv') call_check() ti.get_tema( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_tema.csv') call_check() ti.get_trima( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_trima.csv') call_check() ti.get_kama( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_kama.csv') call_check() ti.get_mama( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_mama.csv') call_check() ti.get_t3( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_t3.csv') call_check() ti.get_macd( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_macd.csv') call_check() ti.get_macdext( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_macdext.csv') call_check() ti.get_stoch( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_stoch.csv') call_check() ti.get_stochf( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_stochf.csv') call_check() ti.get_rsi( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_rsi.csv') call_check() ti.get_stochrsi(ticker, interval)[0].to_csv( f'./Stock Data/TI/{ticker}_{interval}_stochris.csv') call_check() ti.get_willr( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_willr.csv') call_check() ti.get_adx( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_adx.csv') call_check() ti.get_adxr( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_adxr.csv') call_check() ti.get_apo( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_apo.csv') call_check() ti.get_ppo( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_ppo.csv') call_check() ti.get_mom( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_mom.csv') call_check() ti.get_bop( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_bop.csv') call_check() ti.get_cci( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_cci.csv') call_check() ti.get_cmo( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_cmo.csv') call_check() ti.get_roc( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_roc.csv') call_check() ti.get_rocr( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_rocr.csv') call_check() ti.get_aroon( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_aroon.csv') call_check() ti.get_aroonosc(ticker, interval)[0].to_csv( f'./Stock Data/TI/{ticker}_{interval}_aroonosc.csv') call_check() ti.get_mfi( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_mfi.csv') call_check() ti.get_trix( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_trix.csv') call_check() ti.get_ultosc( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_ultosc.csv') call_check() ti.get_dx( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_dx.csv') call_check() ti.get_minus_di(ticker, interval)[0].to_csv( f'./Stock Data/TI/{ticker}_{interval}_minus_di.csv') call_check() ti.get_plus_di( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_plus_di.csv') call_check() ti.get_minus_dm(ticker, interval)[0].to_csv( f'./Stock Data/TI/{ticker}_{interval}_minus_dm.csv') call_check() ti.get_plus_dm( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_plus_dm.csv') call_check() ti.get_bbands( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_bbands.csv') call_check() ti.get_midpoint(ticker, interval)[0].to_csv( f'./Stock Data/TI/{ticker}_{interval}_midpoint.csv') call_check() ti.get_midprice(ticker, interval)[0].to_csv( f'./Stock Data/TI/{ticker}_{interval}_midprice.csv') call_check() ti.get_sar( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_sar.csv') call_check() ti.get_trange( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_trange.csv') call_check() ti.get_atr( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_atr.csv') call_check() ti.get_natr( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_natr.csv') call_check() ti.get_ad( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_ad.csv') call_check() ti.get_adosc( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_adosc.csv') call_check() ti.get_obv( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_obv.csv') call_check() ti.get_ht_trendline(ticker, interval)[0].to_csv( f'./Stock Data/TI/{ticker}_{interval}_ht_trendline.csv') call_check() ti.get_ht_sine( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_ht_sine.csv') call_check() ti.get_ht_trendmode(ticker, interval)[0].to_csv( f'./Stock Data/TI/{ticker}_{interval}_ht_trendmode.csv') call_check() ti.get_ht_dcperiod(ticker, interval)[0].to_csv( f'./Stock Data/TI/{ticker}_{interval}_dcperiod.csv') call_check() ti.get_ht_dcphase( ticker, interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_dcphase.csv') call_check() ti.get_ht_phasor(ticker, interval)[0].to_csv( f'./Stock Data/TI/{ticker}_{interval}_ht_phasor.csv')