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‎.gitignore‎

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*.h5
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*.ipynb
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.pytest_cache/
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.vscode/
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tests/unused/*
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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]
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*$py.class
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.idea/
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# C extensions
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*.so
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# Distribution / packaging
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.Python
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env/
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build/
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develop-eggs/
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dist/
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downloads/
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eggs/
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.eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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*.egg-info/
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.installed.cfg
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*.egg
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# PyInstaller
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# Usually these files are written by a python script from a template
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# before PyInstaller builds the exe, so as to inject date/other infos into it.
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*.manifest
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*.spec
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# Installer logs
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pip-log.txt
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pip-delete-this-directory.txt
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# Unit test / coverage reports
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htmlcov/
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.tox/
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.coverage
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.coverage.*
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.cache
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nosetests.xml
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coverage.xml
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*,cover
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.hypothesis/
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# Translations
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*.mo
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*.pot
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# Django stuff:
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*.log
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local_settings.py
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# Flask instance folder
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instance/
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# Scrapy stuff:
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.scrapy
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# Sphinx documentation
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docs/_build/
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# PyBuilder
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target/
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# IPython Notebook
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.ipynb_checkpoints
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# pyenv
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.python-version
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# celery beat schedule file
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celerybeat-schedule
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# dotenv
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.env
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# virtualenv
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venv/
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ENV/
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# Spyder project settings
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.spyderproject
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# Rope project settings
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.ropeproject
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# =========================
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# Operating System Files
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# =========================
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# OSX
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# =========================
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.DS_Store
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.AppleDouble
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.LSOverride
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# Thumbnails
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._*
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# Files that might appear in the root of a volume
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.DocumentRevisions-V100
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.fseventsd
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.Spotlight-V100
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.TemporaryItems
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.Trashes
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.VolumeIcon.icns
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# Directories potentially created on remote AFP share
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.AppleDB
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.AppleDesktop
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Network Trash Folder
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Temporary Items
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.apdisk
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# Windows
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# =========================
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# Windows image file caches
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Thumbs.db
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ehthumbs.db
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# Folder config file
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Desktop.ini
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# Recycle Bin used on file shares
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$RECYCLE.BIN/
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# Windows Installer files
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*.cab
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*.msi
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*.msm
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*.msp
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# Windows shortcuts
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*.lnk

‎backtrader_app.py‎

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import datetime
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import akshare as ak
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import backtrader as bt
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import backtrader.analyzers as btanalyzers
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import pandas as pd
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import streamlit as st
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import yaml
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from streamlit_echarts import st_pyecharts
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from charts import draw_pro_kline, draw_result_bar
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from frames import akshare_selector_ui, backtrader_selector_ui, params_selector_ui
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from modules.schemas import StrategyBase
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# from utils.logs import LOGGER
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st.set_page_config(page_title="backtrader")
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def main():
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ak_params = akshare_selector_ui()
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backtrader_params = backtrader_selector_ui()
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if ak_params["symbol"]:
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stock_df = gen_stock_df(ak_params)
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st.subheader("Kline")
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# kline = draw_pro_kline(stock_df)
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# st_pyecharts(kline, height="500px")
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st.subheader("Strategy")
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name = st.selectbox("strategy", list(strategys.keys()))
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submitted, params = params_selector_ui(strategys[name])
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if submitted:
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backtrader_params.update(
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{
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"stock_df": stock_df.iloc[:, :6],
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"strategy": StrategyBase(name=name, params=params),
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}
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)
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par_df = run_backtrader(**backtrader_params)
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st.dataframe(par_df.style.highlight_max(subset=par_df.columns[-3:]))
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bar = draw_result_bar(par_df)
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st_pyecharts(bar, height="500px")
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@st.cache(allow_output_mutation=True)
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def gen_stock_df(ak_params: dict) -> pd.DataFrame:
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"""generate stock data
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:param ak_params: dict.
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:return: pd.DataFrame.
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"""
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return ak.stock_zh_a_hist(**ak_params)
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@st.cache
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def run_backtrader(
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stock_df: pd.DataFrame,
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start_date: datetime.datetime,
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end_date: datetime.datetime,
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start_cash: int,
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commission_fee: float,
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stake: int,
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strategy: StrategyBase,
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) -> pd.DataFrame:
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"""run backtrader
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:param stock_df: pd.DataFrame. stock data
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:param start_date: datetime.datetime. back trader from date
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:param end_date: datetime.datetime. back trader end date
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:param start_cash: int. back trader start cash
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:param commission_fee: float. commission fee
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:param stake: int. stake
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:param strategy: StrategyBase. strategy name an params
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:return: None.
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"""
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cerebro = bt.Cerebro()
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stock_df.columns = [
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"date",
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"open",
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"close",
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"high",
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"low",
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"volume",
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]
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stock_df.index = pd.to_datetime(stock_df["date"])
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data = bt.feeds.PandasData(dataname=stock_df, fromdate=start_date, todate=end_date)
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cerebro.adddata(data)
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cerebro.broker.setcash(start_cash)
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cerebro.broker.setcommission(commission=commission_fee)
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cerebro.addsizer(bt.sizers.FixedSize, stake=stake)
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cerebro.addanalyzer(btanalyzers.SharpeRatio, _name="sharpe")
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cerebro.addanalyzer(btanalyzers.DrawDown, _name="drawdown")
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cerebro.addanalyzer(btanalyzers.Returns, _name="returns")
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print("start cash: %.2f" % cerebro.broker.getvalue())
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strategy_cli = getattr(__import__(f"strategy"), f"{strategy.name}Strategy")
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cerebro.optstrategy(strategy_cli, **strategy.params)
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back = cerebro.run()
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par_list = []
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for x in back:
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par = []
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for param in strategy.params.keys():
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par.append(x[0].params._getkwargs()[param])
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par.extend(
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[
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x[0].analyzers.returns.get_analysis()["rnorm100"],
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x[0].analyzers.drawdown.get_analysis()["max"]["drawdown"],
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x[0].analyzers.sharpe.get_analysis()["sharperatio"],
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]
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)
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par_list.append(par)
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columns = list(strategy.params.keys())
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columns.extend(["return", "dd", "sharpe"])
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par_df = pd.DataFrame(par_list, columns=columns)
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print("end cash: %.2f" % cerebro.broker.getvalue())
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return par_df
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def load_strategys(yaml_file):
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with open(yaml_file, "r") as f:
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strategys = yaml.safe_load(f)
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return strategys
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strategys = load_strategys("./config/strategy.yaml")
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if __name__ == "__main__":
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main()

‎charts/__init__.py‎

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from .results import draw_result_bar
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from .stock import draw_pro_kline
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__all__ = ["draw_pro_kline", "draw_result_bar"]

‎charts/results.py‎

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import pandas as pd
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from pyecharts import options as opts
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from pyecharts.charts import Bar
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def draw_result_bar(df: pd.DataFrame, n_scors=3):
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params_columns = df.columns[:-n_scors]
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scores_columns = df.columns[-n_scors:]
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x_data = (
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df[params_columns]
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.apply(
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lambda x: "\n".join(
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[f"{name}_{value}" for name, value in zip(params_columns, x)]
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),
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axis=1,
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)
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.values.tolist()
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)
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bar = (
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Bar()
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.add_xaxis(x_data)
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.set_global_opts(
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tooltip_opts=opts.TooltipOpts(trigger="axis"),
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legend_opts=opts.LegendOpts(selected_mode="single"),
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)
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)
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for col in scores_columns:
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bar.add_yaxis(col, df[col].values.tolist())
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bar.set_series_opts(
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label_opts=opts.LabelOpts(is_show=False),
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markpoint_opts=opts.MarkPointOpts(
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data=[
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opts.MarkPointItem(type_="max", name="最大值"),
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opts.MarkPointItem(type_="min", name="最小值"),
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]
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),
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)
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return bar

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