以下內容，都是 shioaji 的官網文件的內容，只是加了一些我自己的理解，感謝永豐提供這麼完整的 sample code

繪圖會用到 numpy, pandas, bqplot...等套件，如果之前沒有安裝，可以先行安裝

pip install numpy pandas bqplot

• 引用套件

import json
import datetime as dt
import numpy as np
import pandas as pd
import bqplot as bq
import shioaji as sj

• 登入 shioaji

api = sj.Shioaji()
api.login(person_id="帳號", passwd="密碼")

• 建立表格的資料集

bid_color = '#ff0000'
ask_color = '#03ba00'
x_bar_data = np.zeros(10)
y_bar_data = np.zeros(10, dtype=np.int64)
color_bar_data = np.array(['#000000' for i in range(10)])
y_bar_data_diff = np.zeros(10, dtype=np.int64)

• 建立繪圖的方法

def bidask_bar_chart():
    global x_bar_data, y_bar_data, color_bar_data, y_data_diff
    global bar_bidask, bar_bidask_diff
    x_ord = bq.OrdinalScale()
    y_sc = bq.LinearScale()
    stroke_color = '#000000'
    
    bar_bidask = bq.Bars(
        x = x_bar_data,
        y = y_bar_data,
        scales = {'x': x_ord, 'y': y_sc},
        stroke = stroke_color,
        color_mode = 'group',
        padding = 0,
        colors = color_bar_data.tolist(),
        type = 'stacked',
        orientation = 'horizontal',
        opacities = [0.7 for _ in x_bar_data]
    )

    bar_bidask_diff = bq.Bars(
        x = x_bar_data,
        y = y_bar_data_diff,
        scale = {'x': x_ord, 'y': y_sc},
        stroke = stroke_color, 
        color_mode = 'group', 
        padding = 0, 
        colors = color_bar_data.tolist()[::-1],
        type = 'stacked', 
        orientation = 'horizontal',
        opacities=[0.7 for _ in x_bar_data],
    )
    
    ax_x = bq.Axis(scale=x_ord, orientation='vertical')
    ax_y = bq.Axis(scale=y_sc, tick_format='0.0f')

    fig = bq.Figure(marks=[bar_bidask, bar_bidask_diff])

    return fig

• 建立資料處理方法

def proc_ask_bid_bardata(topic, quote_msg):
    global x_bar_data, y_bar_data, color_bar_data, y_data_diff
    ask_price = quote_msg.get('AskPrice', [0])[0]
    bid_price = quote_msg.get('BidPrice', [0])[0]

    x_bar_data[:5] = quote_msg['BidPrice'][::-1]
    x_bar_data[5:] = quote_msg['AskPrice']

    y_bar_data[:5] = quote_msg['BidVolume'][::-1]
    y_bar_data[5:] = quote_msg['AskVolume']
    y_bar_data[5:] *= -1
    
    y_bar_data_diff[5:] = quote_msg["DiffAskVol"]
    y_bar_data_diff[:5] = quote_msg["DiffBidVol"][::-1]
    color_bar_data[:5] = bid_color
    color_bar_data[5:] = ask_color

• 建立圖表更新方法

def update_barchart(x_bar_data, y_bar_data, color_bar_data, y_bar_data_diff):
    global bar_bidask, bar_bidask_diff
    with bar_bidask.hold_sync() and bar_bidask_diff.hold_sync():
        bar_bidask.x = x_bar_data.copy()
        bar_bidask.y = y_bar_data.copy()
        bar_bidask.colors = color_bar_data.tolist()
        bar_bidask_diff.x = x_bar_data.copy()
        bar_bidask_diff.y = y_bar_data_diff.copy()
        bar_bidask_diff.colors = color_bar_data.tolist()[::-1]

• 建立取得價格後的回呼方法

@sj.on_quote
def quote_callback(topic, quote_msg):
    global x_bar_data, y_bar_data, color_bar_data, y_data_diff
    if topic.startswith('Q'):
        proc_ask_bid_bardata(topic, quote_msg)
        update_barchart(x_bar_data, y_bar_data, color_bar_data, y_bar_data_diff)

• 建立 solace 事件回呼方法

@sj.on_event
def event_callback(resp_code, event_code, event):
    print("Response Code: {} | Event Code: {} | Event: {}".format(resp_code, event_code, event))

• 設定回呼方法

api.quote.set_callback(quote_callback)
api.quote.set_event_callback(event_callback)

• 繪圖

bidask_bar_chart()

• 訂閱報價

stock2330 = api.Contracts.Stocks["2330"]
api.quote.subscribe(stock2330, quote_type="bidask")

因為我是在盤後才跑這個程式，所以沒有辦法取得即資料，所以暫時不確定以上的程式能不能正確運行，之後如果有機會在交易時間跑的話，會再驗證，如果有問題的話，會再修改。