mirror of
https://github.com/OpenBB-finance/OpenBB.git
synced 2026-10-27 12:40:35 +00:00
69b4d117fa
* Fixes * Update stocks_helper.py * update git-actions set-output to new format * Update stocks_helper.py * Update terminal_helper.py * removed LineAnnotateDrawer from qa_view * lint * few changes * updates * sdk auto gen modules done * Update stocks_helper.py * updates to changed imports, and remove first sdk_modules * Update generate_sdk.py * Update generate_sdk.py * pylint * revert stocks_helper * Update generate_sdk.py * Update sdk.py * Update generate_sdk.py * full auto generation, added sdk.py/controllers creation * missed enable forecasting * added running black in subprocess after sdk files generation completes * removed deleted sdk_arg_logger * comment out tests * property doc fix * clean up * Update generate_sdk.py * make trailmap classes useable for doc generation * Update generate_sdk.py * added lineon to trailmap class for linking to func in markdown * changed lineon to dict * added full_path to trailmap for linking in docs * updated portfolio * added func_def to trailmap attributes for markdown in docs, added missing type hints to covid functions * Update generate_sdk.py * Update generate_sdk.py * Update generate_sdk.py * Update generate_sdk.py * merge * update sdk * updates * Update generate_sdk.py * Update generate_sdk.py * dead imports * bump * updates * updates * updated missing * added alt realestate functions to trailmap, logic to clear folders before building * Update __init__.py * Update generate_sdk.py * clean __init__.py files before build * sync website content folder * Update generate_sdk.py * updates + logging * drop pandas inplace. add docstrings * Update trail_map.py * Update generate_sdk.py * Update trail_map.py * stocks/fa PR added * synced trailmap with develop branch * Update CONTRIBUTING.md * Update CONTRIBUTING.md * Update CONTRIBUTING.md * Update sdk_init.py * fix removed keys functions * updates * reqs txt files * forgot to save * up to date with main * made sure help(openbb.trailmap) is preserved * ruff * Update requirements-full.txt --------- Co-authored-by: Colin Delahunty <72827203+colin99d@users.noreply.github.com> Co-authored-by: James Maslek <jmaslek11@gmail.com> Co-authored-by: Chavithra <chavithra@gmail.com>
529 lines
24 KiB
Python
529 lines
24 KiB
Python
"""OpenBB Terminal SDK."""
|
|
# flake8: noqa
|
|
# pylint: disable=unused-import,wrong-import-order
|
|
# pylint: disable=C0302,W0611,R0902,R0903,C0412,C0301,not-callable
|
|
import logging
|
|
|
|
import openbb_terminal.config_terminal as cfg
|
|
from openbb_terminal import helper_funcs as helper # noqa: F401
|
|
from openbb_terminal.base_helpers import load_dotenv_and_reload_configs
|
|
from openbb_terminal.config_terminal import theme
|
|
|
|
from openbb_terminal.cryptocurrency.due_diligence.pycoingecko_model import Coin
|
|
from openbb_terminal.dashboards.dashboards_controller import DashboardsController
|
|
from openbb_terminal.helper_classes import TerminalStyle # noqa: F401
|
|
from openbb_terminal.reports import widget_helpers as widgets # noqa: F401
|
|
from openbb_terminal.reports.reports_controller import ReportController
|
|
|
|
import openbb_terminal.sdk_core.sdk_init as lib
|
|
from openbb_terminal.sdk_core import (
|
|
controllers as ctrl,
|
|
models as model,
|
|
)
|
|
from openbb_terminal.session.user import User
|
|
|
|
if User.is_guest():
|
|
load_dotenv_and_reload_configs()
|
|
|
|
logger = logging.getLogger(__name__)
|
|
theme.applyMPLstyle()
|
|
|
|
|
|
class OpenBBSDK:
|
|
"""OpenBB SDK Class.
|
|
|
|
Attributes:
|
|
`login`: Login and load user info.\n
|
|
`logout`: Logout and clear session.\n
|
|
`news`: Get news for a given term and source. [Source: Feedparser]\n
|
|
`whoami`: Display user info.\n
|
|
"""
|
|
|
|
def __init__(self):
|
|
SDKLogger()
|
|
self.login = lib.sdk_session.login
|
|
self.logout = lib.sdk_session.logout
|
|
self.news = lib.common_feedparser_model.get_news
|
|
self.whoami = lib.sdk_session.whoami
|
|
|
|
@property
|
|
def alt(self):
|
|
"""Alternative Submodule
|
|
|
|
Submodules:
|
|
`covid`: Covid Module
|
|
`oss`: Oss Module
|
|
`realestate`: Realestate Module
|
|
|
|
Attributes:
|
|
`hn`: Get top stories from HackerNews.\n
|
|
`hn_chart`: View top stories from HackerNews.\n
|
|
"""
|
|
|
|
return ctrl.AltController()
|
|
|
|
@property
|
|
def crypto(self):
|
|
"""Cryptocurrency Submodule
|
|
|
|
Submodules:
|
|
`dd`: Due Diligence Module
|
|
`defi`: DeFi Module
|
|
`disc`: Discovery Module
|
|
`nft`: NFT Module
|
|
`onchain`: OnChain Module
|
|
`ov`: Overview Module
|
|
`tools`: Tools Module
|
|
|
|
Attributes:
|
|
`candle`: Plot candle chart from dataframe. [Source: Binance]\n
|
|
`chart`: Load data for Technical Analysis\n
|
|
`find`: Find similar coin by coin name,symbol or id.\n
|
|
`load`: Load crypto currency to get data for\n
|
|
`price`: Returns price and confidence interval from pyth live feed. [Source: Pyth]\n
|
|
"""
|
|
|
|
return ctrl.CryptoController()
|
|
|
|
@property
|
|
def econometrics(self):
|
|
"""Econometrics Submodule
|
|
|
|
Attributes:
|
|
`bgod`: Calculate test statistics for autocorrelation\n
|
|
`bgod_chart`: Show Breusch-Godfrey autocorrelation test\n
|
|
`bols`: The between estimator is an alternative, usually less efficient estimator, can can be used to\n
|
|
`bpag`: Calculate test statistics for heteroscedasticity\n
|
|
`bpag_chart`: Show Breusch-Pagan heteroscedasticity test\n
|
|
`clean`: Clean up NaNs from the dataset\n
|
|
`coint`: Calculate cointegration tests between variable number of input series\n
|
|
`coint_chart`: Estimates long-run and short-run cointegration relationship for series y and x and apply\n
|
|
`comparison`: Compare regression results between Panel Data regressions.\n
|
|
`dwat`: Calculate test statistics for Durbin Watson autocorrelation\n
|
|
`dwat_chart`: Show Durbin-Watson autocorrelation tests\n
|
|
`fdols`: First differencing is an alternative to using fixed effects when there might be correlation.\n
|
|
`fe`: When effects are correlated with the regressors the RE and BE estimators are not consistent.\n
|
|
`get_regression_data`: This function creates a DataFrame with the required regression data as\n
|
|
`granger`: Calculate granger tests\n
|
|
`granger_chart`: Show granger tests\n
|
|
`load`: Load custom file into dataframe.\n
|
|
`norm`: The distribution of returns and generate statistics on the relation to the normal curve.\n
|
|
`norm_chart`: Determine the normality of a timeseries.\n
|
|
`ols`: Performs an OLS regression on timeseries data. [Source: Statsmodels]\n
|
|
`options`: Obtain columns-dataset combinations from loaded in datasets that can be used in other commands\n
|
|
`options_chart`: Plot custom data\n
|
|
`panel`: Based on the regression type, this function decides what regression to run.\n
|
|
`panel_chart`: Based on the regression type, this function decides what regression to run.\n
|
|
`pols`: PooledOLS is just plain OLS that understands that various panel data structures.\n
|
|
`re`: The random effects model is virtually identical to the pooled OLS model except that is accounts for the\n
|
|
`root`: Calculate test statistics for unit roots\n
|
|
`root_chart`: Determine the normality of a timeseries.\n
|
|
"""
|
|
|
|
return model.EconometricsRoot()
|
|
|
|
@property
|
|
def economy(self):
|
|
"""Economy Submodule
|
|
|
|
Attributes:
|
|
`available_indices`: Get available indices\n
|
|
`bigmac`: Display Big Mac Index for given countries\n
|
|
`bigmac_chart`: Display Big Mac Index for given countries\n
|
|
`country_codes`: Get available country codes for Bigmac index\n
|
|
`currencies`: Scrape data for global currencies\n
|
|
`events`: Get economic calendar for countries between specified dates\n
|
|
`fred`: Get Series data. [Source: FRED]\n
|
|
`fred_chart`: Display (multiple) series from https://fred.stlouisfed.org. [Source: FRED]\n
|
|
`fred_ids`: Get Series IDs. [Source: FRED]\n
|
|
`fred_notes`: Get series notes. [Source: FRED]\n
|
|
`future`: Get futures data. [Source: Finviz]\n
|
|
`futures`: Get futures data.\n
|
|
`get_groups`: Get group available\n
|
|
`glbonds`: Scrape data for global bonds\n
|
|
`index`: Get data on selected indices over time [Source: Yahoo Finance]\n
|
|
`index_chart`: Load (and show) the selected indices over time [Source: Yahoo Finance]\n
|
|
`indices`: Get the top US indices\n
|
|
`macro`: This functions groups the data queried from the EconDB database [Source: EconDB]\n
|
|
`macro_chart`: Show the received macro data about a company [Source: EconDB]\n
|
|
`macro_countries`: This function returns the available countries and respective currencies.\n
|
|
`macro_parameters`: This function returns the available macro parameters with detail.\n
|
|
`overview`: Scrape data for market overview\n
|
|
`perfmap`: Opens Finviz map website in a browser. [Source: Finviz]\n
|
|
`performance`: Get group (sectors, industry or country) performance data. [Source: Finviz]\n
|
|
`rtps`: Get real-time performance sector data\n
|
|
`rtps_chart`: Display Real-Time Performance sector. [Source: AlphaVantage]\n
|
|
`search_index`: Search indices by keyword. [Source: FinanceDatabase]\n
|
|
`spectrum`: Display finviz spectrum in system viewer [Source: Finviz]\n
|
|
`treasury`: Get U.S. Treasury rates [Source: EconDB]\n
|
|
`treasury_chart`: Display U.S. Treasury rates [Source: EconDB]\n
|
|
`treasury_maturities`: Get treasury maturity options [Source: EconDB]\n
|
|
`usbonds`: Scrape data for us bonds\n
|
|
`valuation`: Get group (sectors, industry or country) valuation data. [Source: Finviz]\n
|
|
`ycrv`: Gets yield curve data from FRED\n
|
|
`ycrv_chart`: Display yield curve based on US Treasury rates for a specified date.\n
|
|
"""
|
|
|
|
return model.EconomyRoot()
|
|
|
|
@property
|
|
def etf(self):
|
|
"""Etf Submodule
|
|
|
|
Submodules:
|
|
`disc`: Discovery Module
|
|
`scr`: Scr Module
|
|
|
|
Attributes:
|
|
`candle`: Show candle plot of loaded ticker.\n
|
|
`compare`: Compare selected ETFs\n
|
|
`etf_by_category`: Return a selection of ETFs based on category filtered by total assets.\n
|
|
`etf_by_name`: Get an ETF symbol and name based on ETF string to search. [Source: StockAnalysis]\n
|
|
`holdings`: Get ETF holdings\n
|
|
`ld`: Return a selection of ETFs based on description filtered by total assets.\n
|
|
`ln`: Return a selection of ETFs based on name filtered by total assets. [Source: Finance Database]\n
|
|
`load`: Load a symbol to perform analysis using the string above as a template.\n
|
|
`news`: Get news for a given term. [Source: NewsAPI]\n
|
|
`news_chart`: Prints table showing news for a given term. [Source: NewsAPI]\n
|
|
`overview`: Get overview data for selected etf\n
|
|
`symbols`: Gets all etf names and symbols\n
|
|
`weights`: Return sector weightings allocation of ETF. [Source: FinancialModelingPrep]\n
|
|
"""
|
|
|
|
return ctrl.EtfController()
|
|
|
|
@property
|
|
def forecast(self):
|
|
"""Forecasting Submodule
|
|
|
|
Attributes:
|
|
`anom`: Get Quantile Anomaly Detection Data\n
|
|
`anom_chart`: Display Quantile Anomaly Detection\n
|
|
`atr`: Calculate the Average True Range of a variable based on a a specific stock ticker.\n
|
|
`autoarima`: Performs Automatic ARIMA forecasting\n
|
|
`autoarima_chart`: Display Automatic ARIMA model.\n
|
|
`autoces`: Performs Automatic Complex Exponential Smoothing forecasting\n
|
|
`autoces_chart`: Display Automatic Complex Exponential Smoothing Model\n
|
|
`autoets`: Performs Automatic ETS forecasting\n
|
|
`autoets_chart`: Display Automatic ETS (Error, Trend, Sesonality) Model\n
|
|
`autoselect`: Performs Automatic Statistical forecasting\n
|
|
`autoselect_chart`: Display Automatic Statistical Forecasting Model\n
|
|
`brnn`: Performs Block RNN forecasting\n
|
|
`brnn_chart`: Display BRNN forecast\n
|
|
`clean`: Clean up NaNs from the dataset\n
|
|
`combine`: Adds the given column of df2 to df1\n
|
|
`corr`: Returns correlation for a given df\n
|
|
`corr_chart`: Plot correlation coefficients for dataset features\n
|
|
`delete`: Delete a column from a dataframe\n
|
|
`delta`: Calculate the %change of a variable based on a specific column\n
|
|
`desc`: Returns statistics for a given df\n
|
|
`ema`: A moving average provides an indication of the trend of the price movement\n
|
|
`expo`: Performs Probabilistic Exponential Smoothing forecasting\n
|
|
`expo_chart`: Display Probabilistic Exponential Smoothing forecast\n
|
|
`linregr`: Perform Linear Regression Forecasting\n
|
|
`linregr_chart`: Display Linear Regression Forecasting\n
|
|
`load`: Load custom file into dataframe.\n
|
|
`mom`: A momentum oscillator, which measures the percentage change between the current\n
|
|
`mstl`: Performs MSTL forecasting\n
|
|
`mstl_chart`: Display MSTL Model\n
|
|
`nbeats`: Perform NBEATS Forecasting\n
|
|
`nbeats_chart`: Display NBEATS forecast\n
|
|
`nhits`: Performs Nhits forecasting\n
|
|
`nhits_chart`: Display Nhits forecast\n
|
|
`plot`: Plot data from a dataset\n
|
|
`plot_chart`: Plot data from a dataset\n
|
|
`regr`: Perform Regression Forecasting\n
|
|
`regr_chart`: Display Regression Forecasting\n
|
|
`rename`: Rename a column in a dataframe\n
|
|
`rnn`: Perform RNN forecasting\n
|
|
`rnn_chart`: Display RNN forecast\n
|
|
`roc`: A momentum oscillator, which measures the percentage change between the current\n
|
|
`rsi`: A momentum indicator that measures the magnitude of recent price changes to evaluate\n
|
|
`rwd`: Performs Random Walk with Drift forecasting\n
|
|
`rwd_chart`: Display Random Walk with Drift Model\n
|
|
`season_chart`: Plot seasonality from a dataset\n
|
|
`seasonalnaive`: Performs Seasonal Naive forecasting\n
|
|
`seasonalnaive_chart`: Display SeasonalNaive Model\n
|
|
`signal`: A price signal based on short/long term price.\n
|
|
`sto`: Stochastic Oscillator %K and %D : A stochastic oscillator is a momentum indicator comparing a particular closing\n
|
|
`tcn`: Perform TCN forecasting\n
|
|
`tcn_chart`: Display TCN forecast\n
|
|
`tft`: Performs Temporal Fusion Transformer forecasting\n
|
|
`tft_chart`: Display Temporal Fusion Transformer forecast\n
|
|
`theta`: Performs Theta forecasting\n
|
|
`theta_chart`: Display Theta forecast\n
|
|
`trans`: Performs Transformer forecasting\n
|
|
`trans_chart`: Display Transformer forecast\n
|
|
"""
|
|
|
|
return model.ForecastRoot()
|
|
|
|
@property
|
|
def forex(self):
|
|
"""Forex Submodule
|
|
|
|
Submodules:
|
|
`oanda`: Oanda Module
|
|
|
|
Attributes:
|
|
`candle`: Show candle plot for fx data.\n
|
|
`fwd`: Gets forward rates from fxempire\n
|
|
`get_currency_list`: Load AV currency codes from a local file.\n
|
|
`load`: Load forex for two given symbols.\n
|
|
`quote`: Get forex quote.\n
|
|
"""
|
|
|
|
return ctrl.ForexController()
|
|
|
|
@property
|
|
def futures(self):
|
|
"""Futures Submodule
|
|
|
|
Attributes:
|
|
`curve`: Get curve futures [Source: Yahoo Finance]\n
|
|
`curve_chart`: Display curve futures [Source: Yahoo Finance]\n
|
|
`historical`: Get historical futures [Source: Yahoo Finance]\n
|
|
`historical_chart`: Display historical futures [Source: Yahoo Finance]\n
|
|
`search`: Get search futures [Source: Yahoo Finance]\n
|
|
"""
|
|
|
|
return model.FuturesRoot()
|
|
|
|
@property
|
|
def keys(self):
|
|
"""Keys Submodule
|
|
|
|
Attributes:
|
|
`av`: Set Alpha Vantage key\n
|
|
`binance`: Set Binance key\n
|
|
`bitquery`: Set Bitquery key\n
|
|
`cmc`: Set Coinmarketcap key\n
|
|
`coinbase`: Set Coinbase key\n
|
|
`coinglass`: Set Coinglass key.\n
|
|
`cpanic`: Set Cpanic key.\n
|
|
`degiro`: Set Degiro key\n
|
|
`eodhd`: Set Eodhd key.\n
|
|
`ethplorer`: Set Ethplorer key.\n
|
|
`finnhub`: Set Finnhub key\n
|
|
`fmp`: Set Financial Modeling Prep key\n
|
|
`fred`: Set FRED key\n
|
|
`get_keys_info`: Get info on available APIs to use in set_keys.\n
|
|
`github`: Set GitHub key.\n
|
|
`glassnode`: Set Glassnode key.\n
|
|
`messari`: Set Messari key.\n
|
|
`mykeys`: Get currently set API keys.\n
|
|
`news`: Set News key\n
|
|
`oanda`: Set Oanda key\n
|
|
`openbb`: Set OpenBB Personal Access Token.\n
|
|
`polygon`: Set Polygon key\n
|
|
`quandl`: Set Quandl key\n
|
|
`reddit`: Set Reddit key\n
|
|
`rh`: Set Robinhood key\n
|
|
`santiment`: Set Santiment key.\n
|
|
`set_keys`: Set API keys in bundle.\n
|
|
`shroom`: Set Shroom key\n
|
|
`smartstake`: Set Smartstake key.\n
|
|
`stocksera`: Set Stocksera key.\n
|
|
`tokenterminal`: Set Token Terminal key.\n
|
|
`tradier`: Set Tradier key\n
|
|
`twitter`: Set Twitter key\n
|
|
`walert`: Set Walert key\n
|
|
"""
|
|
|
|
return model.KeysRoot()
|
|
|
|
@property
|
|
def portfolio(self):
|
|
"""Portfolio Submodule
|
|
|
|
Submodules:
|
|
`alloc`: Alloc Module
|
|
`metric`: Metric Module
|
|
`po`: Portfolio Optimization Module
|
|
|
|
Attributes:
|
|
`bench`: Load benchmark into portfolio\n
|
|
`distr`: Display daily returns\n
|
|
`distr_chart`: Display daily returns\n
|
|
`dret`: Get daily returns\n
|
|
`dret_chart`: Display daily returns\n
|
|
`es`: Get portfolio expected shortfall\n
|
|
`holdp`: Get holdings of assets (in percentage)\n
|
|
`holdp_chart`: Display holdings of assets (in percentage)\n
|
|
`holdv`: Get holdings of assets (absolute value)\n
|
|
`holdv_chart`: Display holdings of assets (absolute value)\n
|
|
`load`: Get PortfolioEngine object\n
|
|
`maxdd`: Calculate the drawdown (MDD) of historical series. Note that the calculation is done\n
|
|
`maxdd_chart`: Display maximum drawdown curve\n
|
|
`mret`: Get monthly returns\n
|
|
`mret_chart`: Display monthly returns\n
|
|
`om`: Get omega ratio\n
|
|
`om_chart`: Display omega ratio\n
|
|
`perf`: Get portfolio performance vs the benchmark\n
|
|
`rbeta`: Get rolling beta using portfolio and benchmark returns\n
|
|
`rbeta_chart`: Display rolling beta\n
|
|
`rsharpe`: Get rolling sharpe ratio\n
|
|
`rsharpe_chart`: Display rolling sharpe\n
|
|
`rsort`: Get rolling sortino\n
|
|
`rsort_chart`: Display rolling sortino\n
|
|
`rvol`: Get rolling volatility\n
|
|
`rvol_chart`: Display rolling volatility\n
|
|
`show`: Get portfolio transactions\n
|
|
`summary`: Get portfolio and benchmark returns summary\n
|
|
`var`: Get portfolio VaR\n
|
|
`yret`: Get yearly returns\n
|
|
`yret_chart`: Display yearly returns\n
|
|
"""
|
|
|
|
return ctrl.PortfolioController()
|
|
|
|
@property
|
|
def qa(self):
|
|
"""Quantitative Analysis Submodule
|
|
|
|
Attributes:
|
|
`acf`: Plots Auto and Partial Auto Correlation of returns and change in returns\n
|
|
`bw`: Plots box and whisker plots\n
|
|
`calculate_adjusted_var`: Calculates VaR, which is adjusted for skew and kurtosis (Cornish-Fischer-Expansion)\n
|
|
`cdf`: Plots Cumulative Distribution Function\n
|
|
`cusum`: Plots Cumulative sum algorithm (CUSUM) to detect abrupt changes in data\n
|
|
`decompose`: Perform seasonal decomposition\n
|
|
`es`: Gets Expected Shortfall for specified stock dataframe.\n
|
|
`es_chart`: Prints table showing expected shortfall.\n
|
|
`hist`: Plots histogram of data\n
|
|
`kurtosis`: Kurtosis Indicator\n
|
|
`kurtosis_chart`: Plots rolling kurtosis\n
|
|
`line`: Display line plot of data\n
|
|
`normality`: Look at the distribution of returns and generate statistics on the relation to the normal curve.\n
|
|
`normality_chart`: Prints table showing normality statistics\n
|
|
`omega`: Get the omega series\n
|
|
`omega_chart`: Plots the omega ratio\n
|
|
`qqplot`: Plots QQ plot for data against normal quantiles\n
|
|
`quantile`: Overlay Median & Quantile\n
|
|
`quantile_chart`: Plots rolling quantile\n
|
|
`rolling`: Return rolling mean and standard deviation\n
|
|
`rolling_chart`: Plots mean std deviation\n
|
|
`sharpe`: Calculates the sharpe ratio\n
|
|
`sharpe_chart`: Plots Calculated the sharpe ratio\n
|
|
`skew`: Skewness Indicator\n
|
|
`skew_chart`: Plots rolling skew\n
|
|
`sortino`: Calculates the sortino ratio\n
|
|
`sortino_chart`: Plots the sortino ratio\n
|
|
`spread`: Standard Deviation and Variance\n
|
|
`spread_chart`: Plots rolling spread\n
|
|
`summary`: Print summary statistics\n
|
|
`summary_chart`: Prints table showing summary statistics\n
|
|
`unitroot`: Calculate test statistics for unit roots\n
|
|
`unitroot_chart`: Prints table showing unit root test calculations\n
|
|
`var`: Gets value at risk for specified stock dataframe.\n
|
|
`var_chart`: Prints table showing VaR of dataframe.\n
|
|
"""
|
|
|
|
return model.QaRoot()
|
|
|
|
@property
|
|
def stocks(self):
|
|
"""Stocks Submodule
|
|
|
|
Submodules:
|
|
`ba`: Behavioral Analysis Module
|
|
`ca`: Comparison Analysis Module
|
|
`disc`: Discovery Module
|
|
`dps`: Darkpool Shorts Module
|
|
`fa`: Fundamental Analysis Module
|
|
`gov`: Government Module
|
|
`ins`: Insiders Module
|
|
`options`: Options Module
|
|
`qa`: Quantitative Analysis Module
|
|
`screener`: Screener Module
|
|
`sia`: Sector Industry Analysis Module
|
|
`ta`: Technical Analysis Module
|
|
`th`: Trading Hours Module
|
|
|
|
Attributes:
|
|
`candle`: Show candle plot of loaded ticker.\n
|
|
`load`: Load a symbol to perform analysis using the string above as a template.\n
|
|
`process_candle`: Process DataFrame into candle style plot.\n
|
|
`quote`: Gets ticker quote from FMP\n
|
|
`search`: Search selected query for tickers.\n
|
|
`tob`: Get top of book bid and ask for ticker on exchange [CBOE.com]\n
|
|
"""
|
|
|
|
return ctrl.StocksController()
|
|
|
|
@property
|
|
def ta(self):
|
|
"""Technical Analysis Submodule
|
|
|
|
Attributes:
|
|
`ad`: Calculate AD technical indicator\n
|
|
`ad_chart`: Plots AD technical indicator\n
|
|
`adosc`: Calculate AD oscillator technical indicator\n
|
|
`adosc_chart`: Plots AD Osc Indicator\n
|
|
`adx`: ADX technical indicator\n
|
|
`adx_chart`: Plots ADX indicator\n
|
|
`aroon`: Aroon technical indicator\n
|
|
`aroon_chart`: Plots Aroon indicator\n
|
|
`atr`: Average True Range\n
|
|
`atr_chart`: Plots ATR\n
|
|
`bbands`: Calculate Bollinger Bands\n
|
|
`bbands_chart`: Plots bollinger bands\n
|
|
`cci`: Commodity channel index\n
|
|
`cci_chart`: Plots CCI Indicator\n
|
|
`cg`: Center of gravity\n
|
|
`cg_chart`: Plots center of gravity Indicator\n
|
|
`clenow`: Gets the Clenow Volatility Adjusted Momentum. this is defined as the regression coefficient on log prices\n
|
|
`clenow_chart`: Prints table and plots clenow momentum\n
|
|
`demark`: Get the integer value for demark sequential indicator\n
|
|
`demark_chart`: Plot demark sequential indicator\n
|
|
`donchian`: Calculate Donchian Channels\n
|
|
`donchian_chart`: Plots donchian channels\n
|
|
`ema`: Gets exponential moving average (EMA) for stock\n
|
|
`fib`: Calculate Fibonacci levels\n
|
|
`fib_chart`: Plots Calculated fibonacci retracement levels\n
|
|
`fisher`: Fisher Transform\n
|
|
`fisher_chart`: Plots Fisher Indicator\n
|
|
`hma`: Gets hull moving average (HMA) for stock\n
|
|
`kc`: Keltner Channels\n
|
|
`kc_chart`: Plots Keltner Channels Indicator\n
|
|
`ma`: Plots MA technical indicator\n
|
|
`ma_chart`: Plots MA technical indicator\n
|
|
`macd`: Moving average convergence divergence\n
|
|
`macd_chart`: Plots MACD signal\n
|
|
`obv`: On Balance Volume\n
|
|
`obv_chart`: Plots OBV technical indicator\n
|
|
`rsi`: Relative strength index\n
|
|
`rsi_chart`: Plots RSI Indicator\n
|
|
`sma`: Gets simple moving average (SMA) for stock\n
|
|
`stoch`: Stochastic oscillator\n
|
|
`stoch_chart`: Plots stochastic oscillator signal\n
|
|
`vwap`: Gets volume weighted average price (VWAP)\n
|
|
`vwap_chart`: Plots VWMA technical indicator\n
|
|
`wma`: Gets weighted moving average (WMA) for stock\n
|
|
`zlma`: Gets zero-lagged exponential moving average (ZLEMA) for stock\n
|
|
"""
|
|
|
|
return model.TaRoot()
|
|
|
|
|
|
class SDKLogger:
|
|
def __init__(self) -> None:
|
|
self.__check_initialize_logging()
|
|
|
|
def __check_initialize_logging(self):
|
|
if not cfg.LOGGING_SUPPRESS:
|
|
self.__initialize_logging()
|
|
|
|
@staticmethod
|
|
def __initialize_logging() -> None:
|
|
# pylint: disable=C0415
|
|
from openbb_terminal.core.log.generation.settings_logger import log_all_settings
|
|
from openbb_terminal.loggers import setup_logging
|
|
|
|
cfg.LOGGING_SUB_APP = "sdk"
|
|
setup_logging()
|
|
log_all_settings()
|
|
|
|
|
|
openbb = OpenBBSDK()
|