Pyqt5+pyecharts股票软件stock.rar

import webbrowser from pandas import Series from pyecharts import options as opts from pyecharts.commons.utils import JsCode from calculate import calculate_ma, calcu_rate from pyecharts.charts import Kline, Line, Bar, Grid, Page import requests from bs4 import BeautifulSoup from pyecharts.globals import ThemeType from formula import * from name_opera import stock_name_transfer from price_opera import data_from_database, transferToWeekLine def ren_ming_wang(): webbrowser.open("http://www.people.com.cn/") def dong_fang_cai_fu(): webbrowser.open("https://www.eastmoney.com/") def tushare_help(): webbrowser.open("https://tushare.pro/document/2") def jukuan_help(): webbrowser.open("https://www.joinquant.com/help/api/help?name=JQData") def boke(): webbrowser.open("https://linqingfeng.blog.csdn.net") def hx_news(): webbrowser.open("http://www.hexun.com/") def xinlang_news(): webbrowser.open("https://finance.sina.com.cn/") def toutiao_quick(): url="https://cj.sina.com.cn/k/article/column_article/3" text=requests.get(url) text.encoding=text.apparent_encoding soup=BeautifulSoup(text.text,"lxml") res=soup.find_all("li",{"class":""}) i=[] for li in res: i.append(str(li.a.text)) url="https:"+str(li.a['href']) i.append(url) return i def yield_k_xian(stockindex,start,end): stockname=stock_name_transfer(stockindex) def get_data(): stock_index=stockindex data1=data_from_database(stock_index,start,end) data2=calcu_rate(data1) return split_data(data=data2) def split_data(data): category_data = [] values = [] volumes = [] for i in range(len(data)): category_data.append(data[i][0]) values.append(data[i]) volumes.append([i, data[i][6], 1 if data[i][1] > data[i][2] else -1]) return {"categoryData": category_data, "values": values, "volumes": volumes} def draw_charts(): kline_data = [data[1:-1] for data in chart_data["values"]] # print(kline_data) kline = ( Kline() .add_xaxis(xaxis_data=chart_data["categoryData"]) .add_yaxis( series_name=stockname, y_axis=kline_data, itemstyle_opts=opts.ItemStyleOpts(color="#ec0000", color0="#00da3c"), ) .set_global_opts( title_opts=opts.TitleOpts(title=stockname+" 日线图", pos_left="10",pos_top="10"), legend_opts=opts.LegendOpts( is_show=True, pos_top=10, pos_left="center" ), datazoom_opts=[ opts.DataZoomOpts( is_show=False, type_="inside", xaxis_index=[0, 1], range_start=98, range_end=100, ), opts.DataZoomOpts( is_show=True, xaxis_index=[0, 1], type_="slider", pos_top="95%", range_start=98, range_end=100, ), ], yaxis_opts=opts.AxisOpts( is_scale=True, splitarea_opts=opts.SplitAreaOpts( is_show=False, areastyle_opts=opts.AreaStyleOpts(opacity=1) ), ), tooltip_opts=opts.TooltipOpts( trigger="axis", axis_pointer_type="cross", background_color="rgba(245, 245, 245, 0.8)", border_width=1, border_color="#ccc", textstyle_opts=opts.TextStyleOpts(color="#000"), # formatter="股票代码:{}".format(kline_data) formatter=JsCode( """function (params) { return params[1].value[0]+'<br>'+'open: '+params[0].value[1]+'<br>'+'close: '+params[0].value[2]+'<br>'+'low: '+params[0].value[3]+'<br>'+'high: '+params[0].value[4]+'<br>'+'volume: '+params[5].value[1]+'<br>'+'rate: '+params[0].value[5]; }""" ) ), visualmap_opts=opts.VisualMapOpts( is_show=False, dimension=2, series_index=5, is_piecewise=True, pieces=[ {"value": 1, "color": "#00da3c"}, {"value": -1, "color": "#ec0000"}, ], ), axispointer_opts=opts.AxisPointerOpts( is_show=True, link=[{"xAxisIndex": "all"}], label=opts.LabelOpts(background_color="#777"), ), brush_opts=opts.BrushOpts( x_axis_index="all", brush_link="all", out_of_brush={"colorAlpha": 0.1}, brush_type="lineX", ), ) ) line = ( Line() .add_xaxis(xaxis_data=chart_data["categoryData"]) .add_yaxis( series_name="MA5", y_axis=calculate_ma(day_count=5, data=chart_data), is_smooth=True, # is_hover_animation=False, linestyle_opts=opts.LineStyleOpts(width=3, opacity=0.5), label_opts=opts.LabelOpts(is_show=False), ) .add_yaxis( series_name="MA10", y_axis=calculate_ma(day_count=10, data=chart_data), is_smooth=True, # is_hover_animation=False, linestyle_opts=opts.LineStyleOpts(width=3, opacity=0.5), label_opts=opts.LabelOpts(is_show=False), ) .add_yaxis( series_name="MA20", y_axis=calculate_ma(day_count=20, data=chart_data), is_smooth=True, # is_hover_animation=False, linestyle_opts=opts.LineStyleOpts(width=3, opacity=0.5), label_opts=opts.LabelOpts(is_show=False), ) .add_yaxis( series_name="MA30", y_axis=calculate_ma(day_count=30, data=chart_data), is_smooth=True, # is_hover_animation=False, linestyle_opts=opts.LineStyleOpts(width=3, opacity=0.5), label_opts=opts.LabelOpts(is_show=False), ) .set_global_opts(xaxis_opts=opts.AxisOpts(type_="category")) ) bar = ( Bar() .add_xaxis(xaxis_data=chart_data["categoryData"]) .add_yaxis( series_name="Volume", y_axis=chart_data["volumes"], xaxis_index=1, yaxis_index=1, label_opts=opts.LabelOpts(is_show=False), ) .set_global_opts( xaxis_opts=opts.AxisOpts( type_="category", is_scale=True, grid_index=1, boundary_gap=False, axisline_opts=opts.AxisLineOpts(is_on_zero=False), axistick_opts=opts.AxisTickOpts(is_show=False), splitline_opts=opts.SplitLineOpts(is_show=False), axislabel_opts=opts.LabelOpts(is_show=False), split_number=20, min_="dataMin",