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90 lines
3.1 KiB
Python
90 lines
3.1 KiB
Python
# -*- coding: utf-8 -*-
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from typing import List
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from dataclasses import dataclass, field
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from pandas_ta.utils._time import get_time
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# Study DataClass
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@dataclass
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class Study:
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"""Study DataClass
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Class to name and group indicators for processing
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Args:
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name (str): Some short memorable string. Note: Case-insensitive "All" is reserved.
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ta (list of dicts): A list of dicts containing keyword arguments where "kind" is the indicator.
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description (str): A more detailed description of what the Study tries to capture. Default: None
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created (str): At datetime string of when it was created. Default: Automatically generated. *Subject to change*
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Example TA:
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ta = [
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{"kind": "sma", "length": 200},
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{"kind": "sma", "close": "volume", "length": 50},
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{"kind": "bbands", "length": 20},
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{"kind": "rsi"},
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{"kind": "macd", "fast": 8, "slow": 21},
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{"kind": "sma", "close": "volume", "length": 20, "prefix": "VOLUME"},
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]
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"""
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name: str # = None # Required.
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ta: List = field(default_factory=list) # Required.
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description: str = "" # Helpful. More descriptive version or notes or w/e.
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created: str = get_time(to_string=True) # Optional. Gets Exchange Time and Local Time execution time
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def __post_init__(self):
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req_args = ["[X] Study requires the following argument(s):"]
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if self._is_name():
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req_args.append(' - name. Must be a string. Example: "My TA". Note: "all" is reserved.')
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if self.ta is None:
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self.ta = None
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elif not self._is_ta():
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s = " - ta. Format is a list of dicts. Example: [{'kind': 'sma', 'length': 10}]"
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s += "\n Check the indicator for the correct arguments if you receive this error."
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req_args.append(s)
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if len(req_args) > 1:
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[print(_) for _ in req_args]
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return None
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def _is_name(self):
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return self.name is None or not isinstance(self.name, str)
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def _is_ta(self):
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if isinstance(self.ta, list) and self.total_ta() > 0:
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# Check that all elements of the list are dicts.
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# Does not check if the dicts values are valid indicator kwargs
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# User must check indicator documentation for all indicators args.
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return all([isinstance(_, dict) and len(_.keys()) > 0 for _ in self.ta])
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return False
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def total_ta(self):
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return len(self.ta) if self.ta is not None else 0
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# All Study
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AllStudy = Study(
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name="All",
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description="All the indicators with their default settings. Pandas TA default.",
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ta=None,
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)
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# Default (Example) Study.
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CommonStudy = Study(
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name="Common Price and Volume SMAs",
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description="Common Price SMAs: 10, 20, 50, 200 and Volume SMA: 20.",
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ta=[
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{"kind": "sma", "length": 10},
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{"kind": "sma", "length": 20},
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{"kind": "sma", "length": 50},
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{"kind": "sma", "length": 200},
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{"kind": "sma", "close": "volume", "length": 20, "prefix": "VOL"}
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]
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)
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# Temporary Strategy DataClass Alias
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Strategy = Study
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AllStrategy = AllStudy
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CommonStrategy = CommonStudy |