mirror of
https://github.com/wassname/pandas-ta.git
synced 2026-06-27 16:10:07 +08:00
Kevin Johnson
117 lines
3.6 KiB
Python
117 lines
3.6 KiB
Python
name = "pandas_ta"
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"""
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.. moduleauthor:: Kevin Johnson
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"""
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from importlib.util import find_spec
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from pathlib import Path
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from pkg_resources import get_distribution, DistributionNotFound
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_dist = get_distribution("pandas_ta")
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try:
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# Normalize case for Windows systems
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here = Path(_dist.location) / __file__
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if not here.exists():
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# not installed, but there is another version that *is*
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raise DistributionNotFound
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except DistributionNotFound:
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__version__ = "Please install this project with setup.py"
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version = __version__ = _dist.version
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Imports = {
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"alphaVantage-api": find_spec("alphaVantageAPI") is not None,
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"matplotlib": find_spec("matplotlib") is not None,
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"mplfinance": find_spec("mplfinance") is not None,
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"numba": find_spec("numba") is not None,
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"yaml": find_spec("yaml") is not None,
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"scipy": find_spec("scipy") is not None,
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"sklearn": find_spec("sklearn") is not None,
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"statsmodels": find_spec("statsmodels") is not None,
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"stochastic": find_spec("stochastic") is not None,
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"talib": find_spec("talib") is not None,
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"tqdm": find_spec("tqdm") is not None,
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"vectorbt": find_spec("vectorbt") is not None,
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"yfinance": find_spec("yfinance") is not None,
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}
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# Not ideal and not dynamic but it works.
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# Will find a dynamic solution later.
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Category = {
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# Candles
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"candles": [
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"cdl_pattern", "cdl_z", "ha"
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],
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# Cycles
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"cycles": ["ebsw"],
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# Momentum
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"momentum": [
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"ao", "apo", "bias", "bop", "brar", "cci", "cfo", "cg", "cmo",
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"coppock", "cti", "er", "eri", "fisher", "inertia", "kdj", "kst", "macd",
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"mom", "pgo", "ppo", "psl", "pvo", "qqe", "roc", "rsi", "rsx", "rvgi",
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"slope", "smi", "squeeze", "squeeze_pro", "stc", "stoch", "stochrsi", "td_seq", "trix",
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"tsi", "uo", "willr"
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],
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# Overlap
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"overlap": [
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"alma", "dema", "ema", "fwma", "hilo", "hl2", "hlc3", "hma", "ichimoku",
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"jma", "kama", "linreg", "mcgd", "midpoint", "midprice", "ohlc4",
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"pwma", "rma", "sinwma", "sma", "ssf", "supertrend", "swma", "t3",
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"tema", "trima", "vidya", "vwap", "vwma", "wcp", "wma", "zlma"
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],
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# Performance
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"performance": ["log_return", "percent_return"],
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# Statistics
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"statistics": [
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"entropy", "kurtosis", "mad", "median", "quantile", "skew", "stdev",
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"tos_stdevall", "variance", "zscore"
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],
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# Trend
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"trend": [
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"adx", "amat", "aroon", "chop", "cksp", "decay", "decreasing", "dpo",
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"increasing", "long_run", "psar", "qstick", "short_run", "tsignals",
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"ttm_trend", "vhf", "vortex", "xsignals"
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],
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# Volatility
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"volatility": [
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"aberration", "accbands", "atr", "bbands", "donchian", "hwc", "kc", "massi",
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"natr", "pdist", "rvi", "thermo", "true_range", "ui"
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],
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# Volume, "vp" or "Volume Profile" is unique
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"volume": [
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"ad", "adosc", "aobv", "cmf", "efi", "eom", "kvo", "mfi", "nvi", "obv",
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"pvi", "pvol", "pvr", "pvt"
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],
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}
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CANGLE_AGG = {
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"open": "first",
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"high": "max",
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"low": "min",
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"close": "last",
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"volume": "sum"
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}
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# https://www.worldtimezone.com/markets24.php
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EXCHANGE_TZ = {
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"NZSX": 12, "ASX": 11,
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"TSE": 9, "HKE": 8, "SSE": 8, "SGX": 8,
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"NSE": 5.5, "DIFX": 4, "RTS": 3,
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"JSE": 2, "FWB": 1, "LSE": 1,
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"BMF": -2, "NYSE": -4, "TSX": -4
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}
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RATE = {
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"DAYS_PER_MONTH": 21,
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"MINUTES_PER_HOUR": 60,
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"MONTHS_PER_YEAR": 12,
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"QUARTERS_PER_YEAR": 4,
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"TRADING_DAYS_PER_YEAR": 252, # Keep even
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"TRADING_HOURS_PER_DAY": 6.5,
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"WEEKS_PER_YEAR": 52,
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"YEARLY": 1,
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}
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from pandas_ta.core import *
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