DOC watchlist edit TST strategy analysis

This commit is contained in:
Kevin Johnson
2020-09-21 08:44:20 -07:00
parent b0229cafc4
commit fbe5f72ba1
3 changed files with 16 additions and 13 deletions
+13 -9
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@@ -50,20 +50,24 @@ def colors(colors: str = None, default: str = "GrRd"):
class Watchlist(object):
"""Watchlist Class (** This is subject to change! **)
============================================================================
"""
# Watchlist Class (** This is subject to change! **)
A simple Class to load/download financial market data and automatically
apply Technical Analysis indicators with a Pandas TA Strategy. Default
Strategy: pandas_ta.AllStrategy.
apply Technical Analysis indicators with a Pandas TA Strategy.
Requirements:
Default Strategy: pandas_ta.AllStrategy.
## Package Support:
### Data Source (Default: AlphaVantage)
- AlphaVantage (pip install alphaVantage-api).
- Python Binance (pip install python-binance). # Future Support
- Yahoo Finance (pip install yfinance). # Almost Supported
# Technical Analysis:
- Pandas TA (pip install pandas_ta)
- AlphaVantage (pip install alphaVantage-api) for the Default Data Source.
To use another Data Source, update the load() method after AV.
Required Arguments:
## Required Arguments:
- tickers: A list of strings containing tickers. Example: ['SPY', 'AAPL']
============================================================================
"""
def __init__(
self,
+1 -1
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@@ -23,7 +23,7 @@ from pandas_ta.volatility import *
from pandas_ta.volume import *
from pandas_ta.utils import *
version = ".".join(("0", "2", "10b"))
version = ".".join(("0", "2", "11b"))
# Strategy DataClass
+2 -3
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@@ -22,7 +22,7 @@ class TestStrategyMethods(TestCase):
@classmethod
def setUpClass(cls):
cls.data = sample_data
# cls.data.ta.cores = cores
cls.data.ta.cores = cores
cls.speed_test = DataFrame()
@classmethod
@@ -37,7 +37,6 @@ class TestStrategyMethods(TestCase):
print(f"[i] Total Datapoints: {cls.data.shape[0]}")
print(cls.speed_test)
del cls.data
def setUp(self):
@@ -96,7 +95,7 @@ class TestStrategyMethods(TestCase):
{"kind": "sma", "length": 200}, # 1
{"kind": "bbands", "length": 20}, # 3
{"kind": "log_return", "cumulative": True}, # 1
{"kind": "sma", "close": "CUMLOGRET_1", "length": 5, "suffix": "CUMLOGRET"}, # 1
{"kind": "ema", "close": "CUMLOGRET_1", "length": 5, "suffix": "CLR"}
]
custom = pandas_ta.Strategy(