Linux 學習筆記

2023年2月23日星期四

BDU v1.2.0 BIOS Debug Utility for UEFI Shell

BDU v1.2.0 supports the following new BIOS debug features :

1. Support Aspeed Super I/O
2. Support NcT5577D Super I/O
3. Dump full PCI scan registers including (similar to linux command lspci -vvv)
a) PCI list
b) PCI Express Capabilities (DevCap, DevCtl, LnkCap, and LnkSta)
c) PCI Express Extended Capabilities

d) PCI Configuration Space registers (256 or 4096 bytes)

e) Byte Word DWord format
and will auto generate REG_LIST.txt file
4. Fix exception for Intel Denverton chipset
5. Add Intel Purley chipset support
6. Add Intel Whitely chipset support
7. Add Intel Eagle Stream chipset support
8. Add progress bar when generating REG_LIST.txt

REG_LIST.txt include PCI List, each PCI/PCIE device register, specified memory, I/O space and ISA space.

Download bdux64.efi => BDUEFI_V_1_2_0.zip

BDU
https://spyker729.blogspot.com/search/label/BDU

Dump BootOrder
https://spyker729.blogspot.com/2018/05/dump-bios-boot-order-tool-in-uefi-shell.html

Dump SMBIOS
https://spyker729.blogspot.com/2017/12/dump-smbios-tools-for-uefi-shell.html

2021年6月8日星期二

【台灣台北大安】壽司美登利，去東京必吃的美味壽司店 !

美登利壽司來台灣開店已經一段時間了，剛開幕時人潮很多遲遲沒有機會用餐

超級特選握壽司

剛好最近有時間去"偽出國"一下

因為疫情太久沒去日本了，非常懷念在東京的美登利

跟日本的相比生菜比較多的蟹膏沙拉

✅超級特選握壽司 850元

只要進去點這份就對了，因為其他都不划算，CP值最高的餐點😎

這份餐點在日本的售價是 2000日幣，吃的到鮪魚的大腹肉、中腹肉、鰤魚、帆立貝、海膽、玉子燒、天使紅蝦、鮭魚卵、鮭魚肚、星鰻、鮪魚泥手卷

超級特選握壽司

鮪魚泥手卷

鮭魚卵軍艦

鮭魚肚

海膽軍艦

星鰻

天使紅蝦

鮪魚大腹肉

😨炙燒壽司拼盤 350元

這個價位還有品項，個人覺得蠻雷的，寧可單點店內的壽司或是去點爭鮮

一共有 5貫壽司，有鮭魚、花枝、蝦子、比目魚、鮪魚

壽司美登利的價位並沒有非常親民，但用餐時段人潮很多

因為是現場排隊，掃完QR code就可以去附近逛街了

等差不多的用餐時間再回來比較輕鬆

<店家資訊>

店名：壽司美登利台北大安店
菜單：https://www.sushinomidori-tw.com.tw/h/Service?key=w6ne4&set=7
地圖：https://goo.gl/maps/kkBiajJDhE2WZnpJ8
FB粉絲團：https://bit.ly/2Ff7ayB
地址：台北市大安區大安路一段81號1F
電話：02-8772-9966
營業時間：11:00-22:00
備註：收10%服務費、限時90分、可刷卡、不提供電話預約

如果發現有盜圖、盜文的事宜，將依法處理 !

2019年5月16日星期四

[Python] 如何用 pandas-datareader 抓取台股資料

Environment : Windows + Jupyter

#需要的套件
import pandas as pd
import pandas_datareader as pdr
import datetime as datetime
import matplotlib.pyplot as plt

#國泰金控(2882)為範例
stock_number = '2882.TW'
start = datetime.datetime(2018,1,1)
end   = datetime.datetime(2018,6,1)
DataFrame = pdr.DataReader(stock_number, 'yahoo', start, end)

print DataFrame

#畫圖
fig = plt.figure(figsize=(5, 5))
AX  = fig.add_axes([0.1,0.5,1,0.2])
AX2 = fig.add_axes([0.1,0.1,1,0.2])

#表格標題
AX.set_title(stock_number)
AX2.set_title(stock_number)

#收盤價
AX.plot(DataFrame['Close'], label='Close', color='B')
#成交量
AX2.bar(DataFrame.index, DataFrame['Volume'], label='Volume', color='R')

AX.legend();
AX2.legend();

                 High        Low       Open      Close    Volume  Adj Close
Date                                                                       
2018-01-02  54.400002  53.299999  53.400002  54.200001  15815336  51.762951
2018-01-03  55.400002  54.299999  54.799999  55.200001  31833721  52.717987
2018-01-04  55.400002  54.500000  55.299999  55.400002  17321761  52.908997
2018-01-05  55.799999  55.000000  55.299999  55.700001  22221913  53.195503
2018-01-08  55.799999  55.000000  55.799999  55.700001  22253987  53.195503
2018-01-09  55.799999  55.200001  55.700001  55.799999  12742940  53.291008
2018-01-10  56.700001  55.599998  56.500000  55.599998  32365670  53.099998
2018-01-11  55.900002  55.000000  55.799999  55.400002  16238278  52.908997
2018-01-12  55.900002  55.299999  55.500000  55.599998  11693485  53.099998
2018-01-15  56.599998  55.900002  56.000000  56.500000  24899376  53.959534
2018-01-16  56.799999  56.200001  56.500000  56.599998  16594879  54.055035
2018-01-17  56.400002  55.799999  56.299999  56.299999  17042147  53.768524
2018-01-18  56.500000  55.799999  56.500000  55.900002  14582079  53.386513
2018-01-19  56.200001  55.599998  55.700001  56.000000  10183237  53.482014
2018-01-22  56.099998  55.200001  55.799999  55.599998  18754752  53.099998
2018-01-23  56.500000  55.299999  55.799999  56.000000  15109737  53.482014
2018-01-24  55.900002  55.000000  55.799999  55.700001  18367391  53.195503
2018-01-25  56.099998  55.200001  55.700001  55.599998  17297427  53.099998
2018-01-26  55.299999  54.500000  55.299999  54.700001  22318756  52.240471
2018-01-29  55.200001  54.599998  55.000000  55.200001  15710037  52.717987
2018-01-30  55.099998  54.400002  55.000000  54.400002  13049295  51.953960
2018-01-31  55.000000  53.799999  54.000000  54.599998  16946736  52.144962
2018-02-01  55.200001  54.599998  54.700001  54.799999  10666353  52.335972
2018-02-02  55.000000  54.400002  54.500000  54.700001   9381541  52.240471
2018-02-05  54.099998  53.500000  53.500000  54.099998  14671051  51.667446
2018-02-06  52.500000  50.500000  52.099998  50.799999  38452497  48.515827
2018-02-07  53.500000  52.000000  52.400002  52.700001  27209771  50.330399
2018-02-08  53.500000  52.799999  53.299999  53.299999  14356310  50.903416
2018-02-09  53.299999  52.000000  52.099998  52.799999  22072666  50.425900
2018-02-12  53.799999  53.000000  53.799999  53.000000  17578655  50.616909
...               ...        ...        ...        ...       ...        ...
2018-04-20  52.799999  52.200001  52.799999  52.500000  10233680  50.139389
2018-04-23  52.799999  52.200001  52.200001  52.500000  10406015  50.139389
2018-04-24  52.900002  52.400002  52.799999  52.500000  10370094  50.139389
2018-04-25  52.500000  51.700001  52.299999  52.200001  23868687  49.852879
2018-04-26  52.799999  52.000000  52.599998  52.799999  21040927  50.425900
2018-04-27  53.700001  53.099998  53.200001  53.500000  19589914  51.094425
2018-04-30  54.000000  53.400002  53.799999  53.500000  10100426  51.094425
2018-05-02  53.799999  53.099998  53.200001  53.500000  12811907  51.094425
2018-05-03  53.799999  52.799999  53.299999  52.900002  11531521  50.521404
2018-05-04  53.000000  52.700001  52.700001  52.799999   7078223  50.425900
2018-05-07  53.400002  52.799999  53.400002  53.000000  14149062  50.616909
2018-05-08  53.500000  52.900002  53.000000  53.500000  13892667  51.094425
2018-05-09  53.799999  53.500000  53.500000  53.599998  13431774  51.189926
2018-05-10  53.799999  53.099998  53.599998  53.299999  16613918  50.903416
2018-05-11  54.700001  53.599998  53.599998  54.599998  26920084  52.144962
2018-05-14  55.000000  54.599998  54.799999  55.000000  14683155  52.526978
2018-05-15  55.099998  54.000000  55.000000  54.000000  18238343  51.571941
2018-05-16  55.000000  54.400002  54.599998  54.900002  18765990  52.431477
2018-05-17  55.400002  54.500000  55.000000  54.900002  14350081  52.431477
2018-05-18  54.900002  54.400002  54.900002  54.400002  15288612  51.953960
2018-05-21  55.000000  54.500000  54.599998  55.000000  11385495  52.526978
2018-05-22  55.000000  54.700001  54.900002  54.700001   9028106  52.240471
2018-05-23  55.099998  53.900002  55.000000  54.000000  12280601  51.571941
2018-05-24  54.500000  54.000000  54.400002  54.200001  10071640  51.762951
2018-05-25  54.400002  53.900002  54.299999  53.900002   9832938  51.476440
2018-05-28  54.200001  53.799999  53.900002  54.099998  10468660  51.667446
2018-05-29  54.400002  53.799999  54.099998  54.099998   8982523  51.667446
2018-05-30  53.500000  52.700001  53.500000  52.900002  26424947  50.521404
2018-05-31  53.799999  53.299999  53.500000  53.599998  34098025  51.189926
2018-06-01  53.700001  53.099998  53.599998  53.500000  10980132  51.094425

[98 rows x 6 columns]