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back_chart.py
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back_chart.py
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#-*- coding: utf-8 -*-
#
# FinaceDataReader chart.py
# (c)2018-2024 FinaceData.KR
from FinanceDataReader.chart import (plot, candle, line)
# import numpy as np
# import pandas as pd
# from datetime import datetime, date
# import itertools
# plotly_install_msg = f'''
# {'-' * 80}
# FinanceDataReade.chart.plot() dependen on plotly
# plotly not installed please install as follows
# pip install plotly
# FinanceDataReade.chart.plot()는 plotly에 의존성이 있습니다.
# 명령창에서 다음과 같이 plotly를 설치하세요
# pip install plotly
# '''
# try:
# import plotly.graph_objects as go
# from plotly.subplots import make_subplots
# except ModuleNotFoundError as e:
# raise ModuleNotFoundError(plotly_install_msg)
# ## holiday Calendar
# holidays_url_base = 'https://raw.githubusercontent.com/FinanceData/FinanceDataReader/master/calendars'
# holidays_krx,holidays_hyse = None, None
# ## Chart plot
# def plot(df, tools=None, layout=None):
# '''
# plot candle chart with DataFrame
# * df: OHLCV data(DataFrame)
# * updates: additional chart configurations
# '''
# global holidays_krx, holidays_hyse
# if holidays_krx is None:
# holidays_krx = pd.read_csv(f'{holidays_url_base}/holidays-krx.csv')['date'].values
# if holidays_hyse is None:
# holidays_hyse = pd.read_csv(f'{holidays_url_base}/holidays-nyse.csv')['date'].values
# tools = {'SMA': [10, 20, 60]} if not tools else tools
# layout = dict() if not layout else layout
# x_ticks = df.index
# change = df["Close"].pct_change()
# oc_ratio = (df["Close"]-df["Open"])/df["Open"]
# oh_ratio = (df["High"]-df["Open"])/df["Open"]
# hover_text = [f'DoD: {chg:.1%} OC: {oc:.1%}, OH: {oh:.1%}' for chg, oc, oh in zip(change, oc_ratio, oh_ratio)]
# # OHLC candle chart
# candle = go.Candlestick(
# x=x_ticks,
# open=df["Open"], high=df["High"], low=df["Low"], close=df["Close"],
# name='',
# text = hover_text,
# increasing_fillcolor = 'red',
# decreasing_fillcolor = 'blue',
# increasing_line_color = 'red',
# decreasing_line_color = 'blue',
# increasing_line_width = 1.5,
# decreasing_line_width = 1.5,
# showlegend = False,
# opacity=0.75,
# )
# # volume bar chart
# vol_colors = np.where(df['Close'].shift(1) > df['Close'], 'blue', 'red')
# vol_bar = go.Bar(
# x=x_ticks,
# y=df['Volume'],
# showlegend=False,
# name='',
# opacity = 0.5,
# marker={'color': vol_colors},
# )
# fig = make_subplots(rows=2, cols=1,
# shared_xaxes=True,
# vertical_spacing=0,
# row_width=[0.3, 0.7])
# fig.add_trace(candle, row=1, col=1)
# fig.add_trace(vol_bar, row=2, col=1)
# # hide rangeslider
# fig.update_xaxes(rangeslider_visible=False)
# # holidays
# holidays = holidays_krx
# if df.attrs.get('exchange') != 'KRX':
# holidays = holidays_hyse
# # Remove non-business days
# fig.update_xaxes(rangebreaks = [
# dict(bounds=['sat','mon']), # remove weekend
# dict(values=holidays), # remove non biz days
# # dict(bounds=[15.5, 9], pattern='hour'), # remove non biz hours
# ])
# # draw axes and grid
# fig.update_xaxes(showline=True, linewidth=1, linecolor='black', gridcolor='lightgray')
# fig.update_yaxes(showline=True, linewidth=1, linecolor='black', gridcolor='lightgray')
# # x-axis tick format
# fig.update_xaxes(tickformat='%Y-%m-%d', row=2, col=1)
# fig.update_xaxes(tickangle=45)
# # y-axis tick format
# fig.update_yaxes(tickformat=',', row='all', col=1)
# # spikes
# fig.update_xaxes(showspikes=True, spikethickness=1, spikedash="dot", spikecolor="lightgray", spikemode="across", spikesnap='cursor')
# # fig.update_traces(xaxis="x2") # binding x-axis
# # bgcolor
# fig.update_layout(plot_bgcolor='white')
# fig.update_layout(paper_bgcolor='white')
# ## tools (tools: indicators and annotations)
# # available_tools
# available_tools = ['SMA', 'EMA', 'HLINE', 'VLINE', 'VRECT']
# for key in tools:
# if key.upper() not in available_tools:
# raise ValueError(f"Unsupport tool: {key}")
# tools = {key.upper(): tools[key] for key in tools} # keys to upper case
# # default tools
# # default_ma_params = [10, 20, 60] # default moving averages params
# # if all(x not in tools.keys() for x in ['SMA', 'EMA']):
# # tools['SMA'] = default_ma_params
# line_dashes = ['solid', 'dot', 'dash', 'longdash', 'dashdot', 'longdashdot']
# line_colors = ['darkmagenta', 'gold', 'limegreen', 'maroon', 'chocolate', 'seagreen', 'coral']
# line_style_cycler = itertools.cycle(itertools.product(line_dashes, line_colors))
# default_line_width = 0.75
# if 'SMA' in tools: # SMA: simple moving average
# args = tools.pop('SMA')
# for arg in args:
# line_dash, line_color = next(line_style_cycler)
# ma_args = dict()
# ma_args['line_width'] = default_line_width
# if type(arg) == int:
# window = arg
# ma_args['line_dash'] = line_dash
# ma_args['line_color'] = line_color
# ma_args['line_width'] = default_line_width
# elif type(arg) == dict:
# window = arg['window']
# ma_args['line_dash'] = arg['line_dash'] if 'line_dash' in arg else line_dash
# ma_args['line_color'] = arg['line_color'] if 'line_color' in arg else line_color
# ma_args['line_width'] = arg['line_width'] if 'line_width' in arg else default_line_width
# ma_price = df['Close'].rolling(window).mean().round(0)
# ma_args['x'] = ma_price.index
# ma_args['y'] = ma_price
# ma_args['name'] = f'SMA_{window}'
# fig.add_trace(go.Scatter(**ma_args), row=1, col=1)
# if 'EMA' in tools: # EMA: exponential moving average
# args = tools.pop('EMA')
# for arg in args:
# line_dash, line_color = next(line_style_cycler)
# ma_args = dict()
# ma_args['line_width'] = default_line_width
# if type(arg) == int:
# window = arg
# ma_args['line_dash'] = line_dash
# ma_args['line_color'] = line_color
# ma_args['line_width'] = default_line_width
# elif type(arg) == dict:
# window = arg['window']
# ma_args.update(arg)
# ma_args['line_dash'] = arg['line_dash'] if 'line_dash' in arg else line_dash
# ma_args['line_color'] = arg['line_color'] if 'line_color' in arg else line_color
# ma_args['line_width'] = arg['line_width'] if 'line_width' in arg else default_line_width
# ma_price = df['Close'].ewm(span=window).mean()
# ma_args['x'] = ma_price.index
# ma_args['y'] = ma_price
# ma_args['name'] = f'EMA_{window}'
# fig.add_trace(go.Scatter(**ma_args), row=1, col=1)
# if 'HLINE' in tools: # HLINE: Horizontal line
# hline_args = dict(line_width=1.5, line_dash="dot", line_color="tomato", layer="below")
# hline_value = tools.pop('HLINE')
# if hasattr(hline_value, '__iter__'):
# for hline in hline_value:
# if type(hline) in [int, float]:
# hline_args['y'] = hline
# elif type(hline) == dict:
# hline_args.update(hline)
# else:
# raise ValueError("'HLINE' must be list of str or list of dict")
# fig.add_hline(**hline_args)
# else:
# hline_args['y'] = hline_value
# fig.add_hline(**hline_args) # just one value
# if 'VLINE' in tools: # VLINE: vertical line
# vline_args = dict(line_width=1.5, line_dash="dot", line_color="tomato", layer="below")
# vline_value = tools.pop('VLINE')
# if hasattr(vline_value, '__iter__'):
# for vline in vline_value:
# if type(vline) in [pd.Timestamp, str, datetime, date]:
# vline_args['x'] = pd.to_datetime(vline).timestamp() * 1000
# elif type(vline) == dict:
# vline_args.update(vline)
# vline_args['x'] = pd.to_datetime(vline_args['x']).timestamp() * 1000
# else:
# raise ValueError("'VLINE' must be list of str or list of dict")
# fig.add_vline(**vline_args)
# else:
# vline_args['y'] = vline_value
# fig.add_hline(**vline_args) # just one value
# if 'VRECT' in tools: # VRECT: highlighting period
# vrect_list = tools.pop('VRECT') if 'VRECT' in tools else {}
# for vrect in vrect_list:
# vrect_args = dict(fillcolor="LightSalmon", opacity=0.3, layer="below", line_width=0)
# if type(vrect) == tuple:
# vrect_args['x0'] = str(vrect[0])
# vrect_args['x1'] = str(vrect[1])
# elif type(vrect) == dict:
# vrect_args.update(vrect)
# else:
# raise ValueError("'vrect' must be list of tuple or list of dict")
# fig.add_vrect(**vrect_args)
# ## update_layout
# layout_defaults = {
# 'hovermode': 'x', # available hovermodes: 'closest', 'x', 'x unified', 'y', 'y unified'
# 'margin': go.layout.Margin(l=0, r=0, b=0, t=0), # margins
# 'width': 1280,
# 'height': 640,
# }
# layout.update(layout_defaults)
# fig.update_layout(layout)
# return fig