小狐狸事務所: 10月 2018

2018年10月31日星期三

購買旺德二代口譯雙向翻譯機

上周小舅媽從沖繩玩回來之後, 要我幫她找哪一種翻譯機比較好, 我以為是傳統翻譯機, 聽她解釋才知在沖繩等車時看到有人脖子上掛著一台小機器, 用說的就能雙向翻譯. 我上網搜尋赫然發現現在很多人出國都帶這種口譯機, 不懂韓文照樣暢遊首爾.

這麼多機種中, 我覺得台灣旺德的口譯機在實用性與價格方面最優, 知名的 486 團購網也是推這支, 參考 486 大哥的評測影片 :

# 486大哥 12支口譯翻譯機實測

還有一台 Ten 口譯機也不錯, 優點是具有 SIM 卡插槽與熱點分享功能, 到國外時可以購買當地 SIM 卡上網並分享給手機電腦等設備, 有 38 國語言對譯功能 :

# https://www.youtube.com/watch?v=t_llnuJS5PI

這台 MOMO 賣 3890 :

# 【TEN】4G翻譯機 AI智能口譯即時雙向翻譯 2吋螢幕 4G+WIFI 即時語音翻譯同步顯示翻譯詞句 $3890

但考慮最後還是買旺德這款, PCHome 賣 6490 元, 但 486 團購價一支是 5490 元, 買 2 台 1 組總價 10198, 使用 200 元折價券後總價 9998, 平均一台 4994 元, 比 PCHome 便宜 1500 元左右.

註冊 486 團購會員時卡在住址欄, 打電話問客服才知中間不能有空格, 我建議他們找程式設計師改掉這個限制.

口譯機平時可用來學外語, 出國可派上用場, 所以我就答應小舅媽幫她一起買, 週五應可到貨帶回鄉下給她, 相信她已迫不急待這台機器.

參考 :

# 【實測片】出國免驚　4大雙向翻譯機旺德最直覺
# 【團購最低價】wonder旺德ai雙向語言翻譯機好用嗎?評價、開箱、同時跟翻譯APP實測
# 2018年語音翻譯機排行，第一名竟然是這台…

成敗之鑑

今天在 Youtube 看到下面這個影片 :

# 蔣介石為什麼敗退台灣？這位國民黨幕後大佬終於道出真因

裡面提到陳立夫晚年在其回憶錄中總結國民黨最後失去大陸政權的原因有兩個 :

軍事上 :
其一, 何應欽沒有採納其意見, 要求日本投降軍先守住鐵路線, 讓國軍迅速鐵運至東北, 反而從上海海運貽誤軍機. 其二, 中央沒有接納敵後游擊武力, 導致其投共
財政上 :
宋子文金融處置錯誤, 以 200:1 比率兌換淪陷區偽幣, 淪陷區人民資產縮水民怨滔滔.

或許陳立夫歸咎於何應欽, 宋子文是出於其個人對他們的不對盤, 但身為國民黨高層身歷其境應該是第一手資料. 這本書市圖可借 :

# 成敗之鑑 :陳立夫回憶錄

2018年10月30日星期二

南山投資型保單贖回與組合變更

最近因為在研究 Fintech, 想起呂先生 2009 年向我招攬的南山伴我一生投資型保單, 剛開始呂先生幫我操作組合, 但有一年因南山要求變更密碼, 之後他就無法登入, 結果多年來停留在兩檔美元基金 (賺), 以及一檔黃金基金 (對折), 都是因為我不懂如何操作, 也沒時間去操作之故.

由於明年經濟展望不佳, 因此決定將兩檔賺錢的美元基金贖回, 但還是持續扣款, 投資組合可能也需要調整. 但從來沒操作過, 這幾天研究了一下, 將南山網站的基金贖回與投資組合操作方式記錄如下, 首先登入南山客戶園地 :

# https://www.nanshanlife.com.tw

先按上方 "保單變更/借款", 再按右下方 "我要申請保單變更", 點選投資型保單 :

點選 "部分提領 (贖回部分) 保單價值" 或 "變更投資標的組合" :

點選欲贖回之保單 :

將富達與瑞銀兩檔美元基金全部贖回, 腰斬的貝萊德黃金保留不動, 讓帳戶上保有 1 萬元以上資金, 這好像是大部分投資型保單普遍的規定 :

按底下試算會估算此次所贖回金額 :

如果上面是按變更投資組合, 則會出現下列頁面, 可調整現有組合之配比或增加新的標的 :

參考 :

# 變更投資標的操作小幫手

2018年10月29日星期一

Python 學習筆記 : pexpect 模組測試

上周為了評估上級新交辦任務, 花了些時間研究 Python 網路通訊功能中關於 telnet 與 ssh 協定的相關模組, 在下面這篇文章看到關於 pexpect 模組的介紹, 覺得它功能很多, 且很容易實現 telnet 與 ssh 協定通訊 :

# [ Python 文章收集 ] python Pexpect

我在下面這本書看到 Python 模組 pexpect 的介紹 :

# Mastering Python Networking 2nd Edition (Packt)

此模組常用函數如下 :

我在 Win10 上的 Python 3.6.1 版安裝 pexpect 過程如下 :

Python 3.6.1 (C:\Python36\python.exe)
C:\Users\user>pip3 install pexpect
Collecting pexpect
Downloading https://files.pythonhosted.org/packages/89/e6/b5a1de8b0cc4e07ca1b305a4fcc3f9806025c1b651ea302646341222f88b/pexpect-4.6.0-py2.py3-none-any.whl (57kB)
Collecting ptyprocess>=0.5 (from pexpect)
Downloading https://files.pythonhosted.org/packages/d1/29/605c2cc68a9992d18dada28206eeada56ea4bd07a239669da41674648b6f/ptyprocess-0.6.0-py2.py3-none-any.whl
Installing collected packages: ptyprocess, pexpect
Successfully installed pexpect-4.6.0 ptyprocess-0.6.0

可見 pexpect 相依於 ptyprocess 模組, 離線安裝必須同時下載 ptyprogress 與 pexpect 的 whl 安裝檔, 而且要先安裝 ptyprogress 再安裝 pexpect. 但安裝完後呼叫 pexpect.spawn() 欲建立 telnet 連線卻出現錯誤訊息 :

>>> import pexpect
>>> child=pexpect.spawn("telnet 127.0.0.1")
Traceback (most recent call last):
File "<pyshell>", line 1, in <module>
AttributeError: module 'pexpect' has no attribute 'spawn'

用 Python 內建函數 dir() 檢視 pexpect 模組之內容, 發現裡面並無 spawn() 方法 :

>>> dir(pexpect)
['EOF', 'ExceptionPexpect', 'Expecter', 'PY3', 'TIMEOUT', '__all__', '__builtins__', '__cached__', '__doc__', '__file__', '__loader__', '__name__', '__package__', '__path__', '__revision__', '__spec__', '__version__', 'exceptions', 'expect', 'is_executable_file', 'searcher_re', 'searcher_string', 'split_command_line', 'sys', 'utils', 'which']

搜尋上面之錯誤訊息才知 pexpect 目前僅支援 Linux/Unix 系列作業系統, 還沒有完全支援 Windows, 參考 :

# Cannot import name 'spawn' for pexpect while using pxssh
# pxssh import issue #339

我在樹莓派安裝 pexpect 後用 dir() 檢視發現在 Linux 上確實可用 :

pi@raspberrypi:~ $ sudo pip3 install pexpect (務必要用 sudo)
Collecting pexpect
Downloading https://files.pythonhosted.org/packages/89/e6/b5a1de8b0cc4e07ca1b305a4fcc3f9806025c1b651ea302646341222f88b/pexpect-4.6.0-py2.py3-none-any.whl (57kB)
Collecting ptyprocess>=0.5 (from pexpect)
Downloading https://files.pythonhosted.org/packages/d1/29/605c2cc68a9992d18dada28206eeada56ea4bd07a239669da41674648b6f/ptyprocess-0.6.0-py2.py3-none-any.whl
Installing collected packages: ptyprocess, pexpect
Successfully installed pexpect-4.6.0 ptyprocess-0.6.0
pi@raspberrypi:~ $ python3
Python 3.4.2 (default, Oct 19 2014, 13:31:11)
[GCC 4.9.1] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import pexpect
>>> dir(pexpect)
['EOF', 'ExceptionPexpect', 'Expecter', 'PY3', 'TIMEOUT', '__all__', '__builtins__', '__cached__', '__doc__', '__file__', '__loader__', '__name__', '__package__', '__path__', '__revision__', '__spec__', '__version__', 'exceptions', 'expect', 'is_executable_file', 'pty_spawn', 'run', 'runu', 'searcher_re', 'searcher_string', 'spawn', 'spawnbase', 'spawnu', 'split_command_line', 'sys', 'utils', 'which']

在 Portable Python v3.7 上線上安裝 pexpect :

D:\PortablePython37>python -m pip install pexpect
Collecting pexpect
Downloading https://files.pythonhosted.org/packages/89/e6/b5a1de8b0cc4e07ca1b305a4fcc3f9806025c1b651ea302646341222f88b/pexpect-4.6.0-py2.py3-none-any.whl (57kB)
Collecting ptyprocess>=0.5 (from pexpect)
Downloading https://files.pythonhosted.org/packages/d1/29/605c2cc68a9992d18dada28206eeada56ea4bd07a239669da41674648b6f/ptyprocess-0.6.0-py2.py3-none-any.whl
Installing collected packages: ptyprocess, pexpect
Successfully installed pexpect-4.6.0 ptyprocess-0.6.0

但後來在 Portable Python 3.7.0 上離線安裝 pexpect (有相依模組 ptyprocess) :

Microsoft Windows [版本 6.3.9600]
(c) 2013 Microsoft Corporation. All rights reserved.

C:\Python37>python -m pip install ptyprocess-0.6.0-py2.py3-none-any.whl
Processing c:\python37\ptyprocess-0.6.0-py2.py3-none-any.whl
Installing collected packages: ptyprocess
Successfully installed ptyprocess-0.6.0
C:\Python37>python -m pip install pexpect-4.6.0-py2.py3-none-any.whl
Processing c:\python37\pexpect-4.6.0-py2.py3-none-any.whl
Requirement already satisfied: ptyprocess>=0.5 in c:\python37\app\python\lib\sit
e-packages (from pexpect==4.6.0) (0.6.0)
Installing collected packages: pexpect
Successfully installed pexpect-4.6.0

卻發現它有與樹莓派上一樣完整的功能 :

>>> import pexpect
>>> dir(pexpect)
['EOF', 'ExceptionPexpect', 'Expecter', 'PY3', 'TIMEOUT', '__all__', '__builtins__', '__cached__', '__doc__', '__file__', '__loader__', '__name__', '__package__', '__path__', '__revision__', '__spec__', '__version__', 'exceptions', 'expect', 'is_executable_file', 'pty_spawn', 'run', 'runu', 'searcher_re', 'searcher_string', 'spawn', 'spawnbase', 'spawnu', 'split_command_line', 'sys', 'utils', 'which']

所以 Pythoin 3.7 似乎可用 pexpect 了.

參考 :

# Python安装使用命令行交互模块pexpect的基础教程

2018年10月28日星期日

2018 年第 43 周記事

最近入夜後開始轉涼, 換季穿長袖了. 玉兔颱風偏向菲律賓, 週三恐變天. 小舅與舅媽周三從沖繩回來, 昨日來訪送來沖繩土產蜂蜜蛋糕一盒, 蠻好吃的, 不像台灣的那麼甜. 不過小舅說自由行不好玩, 心思都花在下一站怎麼走, 擔心耽誤時間, 不如跟團讓導遊操心行程, 單純當自在的傻遊客就好. 而且做廉航其實沒便宜多少錢, 登機環境好像難民, 沒空橋, 走好遠, 商店三兩家, 行李秤重收費, ... 連一張面紙也沒有, 說以後出國玩絕不再自由行, 比跟團還累. 我也這麼覺得.

由於今天要去吃喜酒 (單位主管娶媳婦), 故早上 10:30 便從鄉下回高雄, 12:00 到福華竟然還是我們那桌最早到的. 爸本來這周想回鄉下住, 但瘡的傷口還剩一小洞還需換藥, 我說再住一周好了. 吃完喜酒去長明街找金手指插座, 沒找到 20 pin 的只好作罷, 順路去茂訊看筆電, 覺得 Acer Swift 5 還真是輕啊, 與我的 Inhon 筆電一樣都是 970g, 若沒買新 MacBook Air 就考慮 Swift 5, MSI 的 MSI PS42 8M-402TW. LG Gram 續航雖長, 但太貴了. 不過 Inhon 筆電還堪用, 若買新機這台不就變成閒置資產?

本周追劇進度, "九號房間" 中, 張華娑知道母親是被馬代表用酒瓶砸頭導致失憶一時憤怒也用酒瓶砸馬代表致死, 但被奇會長掩護未被揭發. 張華娑想利用為奇會長之子奇讚成撞死人一案辯護的機會讓奇會長失去現在的一切, 回到剛認識她時一無所有的樣子. "我身後的陶斯" 裡, 陶斯去 J 國際欲取回李容泰的沙漏來救高愛琳, 卻被權世英次長的人盯上追捕, 赫然發現魔法師 K 竟然也在權次長的行列中, 急忙從橋上躍下時手臂被 K 擊中一槍沉入河底, 心急如焚的高愛琳跳下河將陶斯救上來. 李容泰因 J 國際曝光而被神秘的上級被清除, 遭到 K 的追殺, 所幸陶斯及時趕到救回一命. "百日的郎君" 世子回宮後漸漸找回過去記憶, 從找回的小木箱中的髮帶想起洪心就是自己一直在尋找的尹瑞利而相認, 但這卻讓洪心陷入危機中 ...

2018年10月27日星期六

大學多元入學說明會

今天早上去鳳中參加學校舉辦的大學多元入學說明會, 從 9 點到 12 點整整 3 小時, 主要介紹繁星, 申請入學, 指考等多元入學方案, 制度看似複雜, 但其實重點就是 :

校排很前面且心儀科系很明確就爭取繁星 (名額非常少).
參與活動或訓練, 競賽等經驗豐富就準備申請入學資料, 當然學測成績要好看
以上皆非就乖乖準備指考

姊姊以前是美術班, 比較特殊, 這一套制度我其實沒有很了解. 姊姊班排前五名所以參加了繁星推薦, 可惜學測國文沒考好, 繁星上台藝大古蹟修復系, 因不是第一志願高師大視覺設計, 且一直沒時間準備作品集, 所以繁星與申請入學都放棄, 直接準備指考, 反而考上台師大. 二哥念普通高中, 所以這回得仔細搞清楚遊戲規則了. 二哥班排中上在 6~15 名之間, 繁星應該沒機會, 所以必須拚申請入學了.

2018年10月26日星期五

Python 學習筆記 : SSH 模組 paramiko 測試

前幾天上面交辦了一件自動化任務, 希望我寫個程式來解決. 此任務主要是透過 ssh 連線遠端主機後向其發送自動產生的指令. 我想用正在學習的 Python tkinter 來撰寫 UI, 而 SSH 連線部分原本想用 Putty, 但我覺得 Python 應該有自己的解決方案, 便上網找到 Paramiko 這個模組.

Paramiko 是以純 Python 實作 SSH v2 加密協定的第三方模組, 底層以 C 擴充函式庫 cryptography 達成低階加密驗證功能, 提供遠端安全連線服務. 最早是由 Jeff Forcier 所創建, 實作並高階封裝了 SSH 協定, 後來開放原始碼成為 Python 底下知名的 SSH 專案, 其首頁, API, 與 GitHub 網址如下 :

# http://www.paramiko.org
# http://docs.paramiko.org (API)
# https://github.com/paramiko/paramiko

Paramiko 需先用 pip 安裝才能匯入使用, 安裝過程如下 :

D:\Python\pip3 install paramiko
Collecting paramiko
Downloading https://files.pythonhosted.org/packages/cf/ae/94e70d49044ccc234bfdba20114fa947d7ba6eb68a2e452d89b920e62227/paramiko-2.4.2-py2.py3-none-any.whl (193kB)
Collecting pyasn1>=0.1.7 (from paramiko)
Downloading https://files.pythonhosted.org/packages/d1/a1/7790cc85db38daa874f6a2e6308131b9953feb1367f2ae2d1123bb93a9f5/pyasn1-0.4.4-py2.py3-none-any.whl (72kB)
Collecting pynacl>=1.0.1 (from paramiko)
Downloading https://files.pythonhosted.org/packages/b5/0f/5f21bd04c8f45685c7b72013fc8efaf0e25baf3b77e62b3b915b5b43a7b6/PyNaCl-1.3.0-cp36-cp36m-win_amd64.whl (188kB)
Requirement already satisfied: cryptography>=1.5 in c:\python36\lib\site-packages (from paramiko) (2.3.1)
Collecting bcrypt>=3.1.3 (from paramiko)
Downloading https://files.pythonhosted.org/packages/4b/c0/c0550e4b98e0536d3a8b8753b68aa0d3c03af654c43a58328d0bf2c06747/bcrypt-3.1.4-cp36-cp36m-win_amd64.whl
Requirement already satisfied: cffi>=1.4.1 in c:\python36\lib\site-packages (from pynacl>=1.0.1->paramiko) (1.11.5)
Requirement already satisfied: six in c:\python36\lib\site-packages (from pynacl>=1.0.1->paramiko) (1.11.0)
Requirement already satisfied: asn1crypto>=0.21.0 in c:\python36\lib\site-packages (from cryptography>=1.5->paramiko) (0.24.0)
Requirement already satisfied: idna>=2.1 in c:\python36\lib\site-packages (from cryptography>=1.5->paramiko) (2.6)
Requirement already satisfied: pycparser in c:\python36\lib\site-packages (from cffi>=1.4.1->pynacl>=1.0.1->paramiko) (2.19)
Installing collected packages: pyasn1, pynacl, bcrypt, paramiko
Successfully installed bcrypt-3.1.4 paramiko-2.4.2 pyasn1-0.4.4 pynacl-1.3.0

可見 paramiko 有 pyasnl, PyNaCl, bcrypt, asn1crypto, pycparser 等相依模組, 如果是本地安裝, 需先下載安裝這些相依模組後才能順利安裝 paramiko. 我在 Python 3.6.0 (32 位元) 上離線安裝結果如下 :

D:\>pip3 install pyasn1-0.4.4-py2.py3-none-any.whl
Processing d:\pyasn1-0.4.4-py2.py3-none-any.whl
Installing collected packages: pyasn1
Successfully installed pyasn1-0.4.4

D:\>pip3 install bcrypt-3.1.4-cp27-cp27m-win32.whl
bcrypt-3.1.4-cp27-cp27m-win32.whl is not a supported wheel on this platform.

D:\>pip3 install idna-2.7-py2.py3-none-any.whl
Processing d:\idna-2.7-py2.py3-none-any.whl
Installing collected packages: idna
Successfully installed idna-2.7

D:\>pip3 install pycparser-2.19.tar.gz
Processing d:\pycparser-2.19.tar.gz
Installing collected packages: pycparser
Running setup.py install for pycparser ... done
Successfully installed pycparser-2.19

D:\>pip3 install six-1.11.0-py2.py3-none-any.whl
Processing d:\six-1.11.0-py2.py3-none-any.whl
Installing collected packages: six
Successfully installed six-1.11.0

D:\>pip3 install bcrypt-3.1.4-cp36-cp36m-win32.whl
Processing d:\bcrypt-3.1.4-cp36-cp36m-win32.whl
Requirement already satisfied: cffi>=1.1 in c:\python3\lib\site-packages (from b
crypt==3.1.4)
Requirement already satisfied: six>=1.4.1 in c:\python3\lib\site-packages (from
bcrypt==3.1.4)
Requirement already satisfied: pycparser in c:\python3\lib\site-packages (from c
ffi>=1.1->bcrypt==3.1.4)
Installing collected packages: bcrypt
Successfully installed bcrypt-3.1.4

D:\>pip3 install PyNaCl-1.3.0-cp36-cp36m-win32.whl
Processing d:\pynacl-1.3.0-cp36-cp36m-win32.whl
Requirement already satisfied: six in c:\python3\lib\site-packages (from PyNaCl=
=1.3.0)
Requirement already satisfied: cffi>=1.4.1 in c:\python3\lib\site-packages (from
PyNaCl==1.3.0)
Requirement already satisfied: pycparser in c:\python3\lib\site-packages (from c
ffi>=1.4.1->PyNaCl==1.3.0)
Installing collected packages: PyNaCl
Successfully installed PyNaCl-1.3.0

D:\>pip3 install asn1crypto-0.24.0-py2.py3-none-any.whl
Processing d:\asn1crypto-0.24.0-py2.py3-none-any.whl
Installing collected packages: asn1crypto
Successfully installed asn1crypto-0.24.0

D:\>pip3 install cryptography-2.3.1-cp36-cp36m-win32.whl
Processing d:\cryptography-2.3.1-cp36-cp36m-win32.whl
Requirement already satisfied: six>=1.4.1 in c:\python3\lib\site-packages (from
cryptography==2.3.1)
Requirement already satisfied: idna>=2.1 in c:\python3\lib\site-packages (from c
ryptography==2.3.1)
Requirement already satisfied: asn1crypto>=0.21.0 in c:\python3\lib\site-package
s (from cryptography==2.3.1)
Requirement already satisfied: cffi!=1.11.3,>=1.7 in c:\python3\lib\site-package
s (from cryptography==2.3.1)
Requirement already satisfied: pycparser in c:\python3\lib\site-packages (from c
ffi!=1.11.3,>=1.7->cryptography==2.3.1)
Installing collected packages: cryptography
Successfully installed cryptography-2.3.1

D:\>pip3 install paramiko-2.4.2-py2.py3-none-any.whl
Processing d:\paramiko-2.4.2-py2.py3-none-any.whl
Requirement already satisfied: pynacl>=1.0.1 in c:\python3\lib\site-packages (fr
om paramiko==2.4.2)
Requirement already satisfied: cryptography>=1.5 in c:\python3\lib\site-packages
(from paramiko==2.4.2)
Requirement already satisfied: bcrypt>=3.1.3 in c:\python3\lib\site-packages (fr
om paramiko==2.4.2)
Requirement already satisfied: pyasn1>=0.1.7 in c:\python3\lib\site-packages (fr
om paramiko==2.4.2)
Requirement already satisfied: cffi>=1.4.1 in c:\python3\lib\site-packages (from
pynacl>=1.0.1->paramiko==2.4.2)
Requirement already satisfied: six in c:\python3\lib\site-packages (from pynacl>
=1.0.1->paramiko==2.4.2)
Requirement already satisfied: asn1crypto>=0.21.0 in c:\python3\lib\site-package
s (from cryptography>=1.5->paramiko==2.4.2)
Requirement already satisfied: idna>=2.1 in c:\python3\lib\site-packages (from c
ryptography>=1.5->paramiko==2.4.2)
Requirement already satisfied: pycparser in c:\python3\lib\site-packages (from c
ffi>=1.4.1->pynacl>=1.0.1->paramiko==2.4.2)
Installing collected packages: paramiko
Successfully installed paramiko-2.4.2

連線 ssh 主機首先要呼叫 SSHClient() 方法建立 SSHClient 物件, 然後呼叫 load_system_host_keys() 載入 ssh 系統主機鍵以便驗證, 再呼叫 connect() 傳入帳號密碼連線遠端主機, 最後呼叫 exec_command() 指令對主機下命令, 它會傳回 3 個元素的 tuple : (stdin, stdout, stderr), 前兩者都是 ChannelFile 物件; 而 stderr 則是 ChannelStderrFile 物件, 利用其 redlines() 方法可讀取命令之回應.

下面範例是以鄉下那台 Pi 3 為遠端主機, 本地則使用 paramiko 來建立 ssh 連線, 並向主機傳送 "ls -al" 指令, 例如 :

Python 3.6.4 (C:\Python36\python.exe)
>>> import paramiko
>>> ssh=paramiko.SSHClient()
>>> ssh.load_system_host_keys()
>>> ssh.connect(hostname="114.27.111.273", username="pi", password="pi")
>>> ssh_stdin, ssh_stdout, ssh_stderr=ssh.exec_command('ls -al')
>>> print(''.join(ssh_stdout.readlines()))
total 64040
drwxr-xr-x 31 pi pi 4096 Oct 23 07:34 .
drwxr-xr-x 3 root root 4096 Mar 3 2017 ..
-rw-r--r-- 1 pi pi 741773 Dec 24 2017 2017-12-24-204625_1280x1024_scrot.png
-rw-r--r-- 1 pi pi 1139579 Jan 21 2018 2018-01-21-161652_1280x1024_scrot.png
-rw-r--r-- 1 pi pi 1126447 Jan 21 2018 2018-01-21-161711_1280x1024_scrot.png
-rw-r--r-- 1 pi pi 137558 Jan 21 2018 2018-01-21-162138_1280x1024_scrot.png
-rw------- 1 pi pi 7796 Oct 16 15:59 .bash_history
-rw-r--r-- 1 pi pi 220 Mar 3 2017 .bash_logout
-rw-r--r-- 1 pi pi 3512 Mar 3 2017 .bashrc
drwxr-xr-x 8 pi pi 4096 Jun 23 20:43 .cache
-rw-r--r-- 1 pi pi 70 Dec 31 2017 checkwifi.sh
drwx------ 2 pi pi 4096 Sep 5 16:17 .chewing
drwx------ 20 pi pi 4096 Jun 30 23:33 .config
-rw-r--r-- 1 pi pi 1786 Feb 22 2017 crontab.txt
-rw-r--r-- 1 pi pi 0 Apr 29 07:34 db.sqlite
drwx------ 3 pi pi 4096 Mar 4 2017 .dbus
-rw-r--r-- 1 pi pi 4924423 Oct 24 22:40 dead.letter
drwxr-xr-x 2 pi pi 4096 Sep 17 2017 Desktop
drwxr-xr-x 5 pi pi 4096 Mar 3 2017 Documents
drwxr-xr-x 2 pi pi 4096 Feb 16 2018 Downloads
drwx------ 2 pi pi 4096 Jul 1 14:56 .gconf
drwx------ 3 pi pi 4096 Sep 16 2017 .gnome
drwxr-xr-x 2 pi pi 4096 Mar 4 2017 .gstreamer-0.10
-rw-r--r-- 1 pi pi 26 Jun 30 22:09 .gtkrc-2.0
drwxr-xr-x 2 pi pi 4096 Apr 1 2017 .idlerc
-rw-r--r-- 1 root root 523 Mar 31 2017 interfaces
-rw-r--r-- 1 pi pi 375 Sep 24 2017 interfaces_fix
-rw-r--r-- 1 pi pi 430 Jan 23 2017 interfaces_kao
-rw-r--r-- 1 pi pi 428 Sep 24 2017 interfaces_mei
-rw-r--r-- 1 pi pi 428 Jan 24 2017 interfaces_mob
drwxr-xr-x 3 pi pi 4096 Apr 14 2018 .keras
-rw-r--r-- 1 pi pi 28 Oct 22 14:30 lastip.txt
drwxr-xr-x 3 pi pi 4096 Mar 3 2017 .local
drwxr-xr-x 2 pi pi 4096 Mar 4 2017 Music
-rw------- 1 pi pi 34 Mar 24 2018 .node_repl_history
drwxr-xr-x 6 pi pi 4096 Dec 12 2017 node-v9.3.0-linux-armv6l
-rw-r--r-- 1 pi pi 16930799 Dec 12 2017 node-v9.3.0-linux-armv6l.tar.gz
-rw-r--r-- 1 pi pi 21 Jan 26 2017 phpinfo.php
-rw-r--r-- 1 pi pi 8151264 Jan 24 2017 phpMyAdmin-4.6.6-all-languages.tar.bz2
drwxr-xr-x 2 pi pi 4096 Mar 4 2017 Pictures
drwxr-xr-x 2 pi pi 4096 Jan 7 2018 .pip
drwx------ 3 pi pi 4096 Aug 6 2017 .pki
-rw-r--r-- 1 pi pi 675 Mar 3 2017 .profile
drwxr-xr-x 2 pi pi 4096 Mar 4 2017 Public
drwxr-xr-x 2 pi pi 4096 Mar 3 2017 python_games
-rw------- 1 pi pi 0 Oct 23 07:34 .python_history
-rw------- 1 pi pi 17 Jun 23 20:42 .python_history-
-rw-r--r-- 1 pi pi 2960 Dec 10 2017 reportip2.py
-rw-r--r-- 1 pi pi 2866 Dec 8 2017 reportip3.py
-rw-r--r-- 1 pi pi 2928 Dec 3 2017 reportip.py
-rw-r--r-- 1 pi pi 2173 Apr 22 2017 rpi-benchmark.sh
drwx------ 2 pi pi 4096 Oct 22 2017 .scim
-rw-r--r-- 1 pi pi 66 Dec 9 2017 .selected_editor
-rw-r--r-- 1 pi pi 671 Feb 26 2017 ssmtp.conf
drwxr-xr-x 5 pi pi 4096 May 13 16:03 ta-lib
-rw-r--r-- 1 pi pi 1330299 May 13 15:04 ta-lib-0.4.0-src.tar.gz
drwxr-xr-x 2 pi pi 4096 Mar 4 2017 Templates
-rw-r--r-- 1 pi pi 28584139 May 26 2017 tensorflow-1.1.0-cp34-cp34m-linux_armv7l.whl
-rw-r--r-- 1 pi pi 281 Feb 25 2018 tensorflow.txt
drwxr-xr-x 4 pi pi 4096 Feb 19 2018 test
drwxr-xr-x 3 pi pi 4096 Mar 4 2017 .themes
drwx------ 5 pi pi 4096 Jun 30 23:38 .thonny
drwx------ 4 pi pi 4096 Aug 6 2017 .thumbnails
-rw-r--r-- 1 pi pi 2235652 Feb 22 2017 tony_20170222.zip
drwxr-xr-x 2 pi pi 4096 Mar 4 2017 Videos
drwx------ 4 pi pi 4096 Dec 11 2017 .vnc
-rw------- 1 root root 153 Mar 31 2017 wpa_supplicant.conf
-rw------- 1 pi pi 266 Sep 5 16:17 .Xauthority
-rw------- 1 pi pi 1187 Sep 5 16:17 .xsession-errors
-rw------- 1 pi pi 1187 Aug 12 17:17 .xsession-errors.old

exec_command() 的傳回值 ssh_stdout 與 ssh_stdin 均為 ChannelFile 物件; 而 ssh_stderr 則是 ChannelStderrFile 物件 :

>>> type(ssh_stdout)
<class 'paramiko.channel.ChannelFile'>
>>> type(ssh_stdin)
<class 'paramiko.channel.ChannelFile'>
>>> type(ssh_stderr)
<class 'paramiko.channel.ChannelStderrFile'>

參考 :

# Python Paramiko基本使用

# Paramiko在Python執行 SSH 小記
# 系統運維工程師的法寶：python paramiko

2018年10月25日星期四

Python 學習筆記 : PortablePython 安裝模組的方法

Portable Python 是一個綠色的 Python 執行與開發環境, 適合用在沒有軟體安裝權限的電腦, 特別是如今各行各業都非常重視資安, 通常都會限制只有管理員才有安裝權限, 使得在這種電腦環境無法執行或開發 Python 軟體. 不過 Portable Python 原創者封裝到 v2.7.6.1 與 v3.2.5 後已停止繼續開發, 參考 ;

# https://portablepython.com/
# https://portablepython.com/wiki/Download/

還好有一位專家 Aman Ansari 繼續封裝 v3.7.0, 可從 Source Forge 下載 :

# https://sourceforge.net/projects/portable-python/

此為 64 位元版, 下載的 zip 檔大約 32MB, 解開後約 110MB, 可放在隨身碟中執行, 其目錄結構如下 :

其中有四個開啟程式 (Launcher) :

Python_Launcher.exe : 開啟命令提示字元視窗執行 Python.exe
IDLE-Launcher.exe : 開啟 IDLE 介面
PyScripter-Launcher.exe : 開啟 PyScripter 編輯器
Console-Launcher.exe : 開啟命令提示字元視窗

檔案 how to use PIP.txt 描述在 Portable Python 下使用 pip 相關指令是在前面加上 "python -m" :

python -m pip install package_name (安裝套件模組)
python -m pip install --upgrade pip (升版 pip)
python -m pip list (檢視已安裝套件模組)
python -m pip uninstall package_name (移除套件模組)
python -m pip list --outdated (顯示過時套件模組)
python -m pip search "package_name" (搜尋套件模組)

執行 Console-Launcher.exe 開啟命令提示字元視窗 (不要用 Windows 本身的), 下 python -m pip list 會列出目前已安裝模組 :

Microsoft Windows [版本 10.0.17134.345]
(c) 2018 Microsoft Corporation. 著作權所有，並保留一切權利。

D:\PortablePython37<python -m pip list
Package Version
---------- -------
pip 10.0.1
setuptools 39.0.1
You are using pip version 10.0.1, however version 18.1 is available.
You should consider upgrading via the 'python -m pip install --upgrade pip' command.

可見預設只安裝了 pip 與 setuptools 這兩個模組而已, 在網路暢通環境下可用 python -m pip install 指令安裝所需要的模組. 但在離線或有防火牆阻擋環境下, 則需要用到 App\Python\Scripts 下的 setup_tools.exe 安裝已下載的模組檔案 (whl 或 gz 檔) :

# 如何在 Portable Python 離線安裝模組

不過由於模組相依問題, 離線安裝通常要準備全部相依的模組才能順利安裝, 作者建議在網路暢通環境下安裝全部用得到的模組較省事. 我常用的模組安裝指令如下, 主要是機器學習與網路爬蟲等相關之模組 :

python -m pip install scipy
python -m pip install pandas
python -m pip install matplotlib
python -m pip install scikit-learn
~~python -m pip install --upgrade tensorflow~~
~~python -m pip install keras~~
python -m pip install requests
python -m pip install beautifulsoup4
python -m pip install lxml
python -m pip install html5lib
python -m pip install selenium
python -m pip install pymysql
python -m pip install mysqlclient
python -m pip install xlrd
python -m pip install fix_yahoo_finance
python -m pip install openpyxl
python -m pip install "django<1.9"
python -m pip install virtualenv
python -m pip install paramiko

注意 :

如果電腦中原本已安裝了 Python, 則必須到 "系統/進階設定" 中將 path 中的 Python 路徑 (例如 C:\Python36\Scripts\, C:\Python36\) 暫時移除, 否則 pip install 安裝時會安裝到原本的 Python 安裝目錄裡, 而不是 Portable Python 裡, 安裝完再恢復 path 原設定. 另外, Numpy 於安裝 Scipy 時會一併安裝, 不需單獨安裝.

上面的模組除了 mysqlclient 外均順利安裝完成, mysqlclient 則出現如下錯誤訊息 :

D:\PortablePython37>python -m pip install mysqlclient
Collecting mysqlclient
Using cached https://files.pythonhosted.org/packages/ec/fd/83329b9d3e14f7344d1cb31f128e6dbba70c5975c9e57896815dbb1988ad/mysqlclient-1.3.13.tar.gz
Installing collected packages: mysqlclient
Running setup.py install for mysqlclient ... error
Complete output from command D:\PortablePython37\App\Python\python.exe -u -c "import setuptools, tokenize;__file__='C:\\Users\\TONYHU~1\\AppData\\Local\\Temp\\pip-install-0cfu1z52\\mysqlclient\\setup.py';f=getattr(tokenize, 'open', open)(__file__);code=f.read().replace('\r\n', '\n');f.close();exec(compile(code, __file__, 'exec'))" install --record C:\Users\TONYHU~1\AppData\Local\Temp\pip-record-tzrl7s3z\install-record.txt --single-version-externally-managed --compile:
D:\PortablePython37\App\Python\lib\distutils\dist.py:274: UserWarning: Unknown distribution option: 'long_description_content_type'
warnings.warn(msg)
running install
running build
running build_py
creating build
creating build\lib.win-amd64-3.7
copying _mysql_exceptions.py -> build\lib.win-amd64-3.7
creating build\lib.win-amd64-3.7\MySQLdb
copying MySQLdb\__init__.py -> build\lib.win-amd64-3.7\MySQLdb
copying MySQLdb\compat.py -> build\lib.win-amd64-3.7\MySQLdb
copying MySQLdb\connections.py -> build\lib.win-amd64-3.7\MySQLdb
copying MySQLdb\converters.py -> build\lib.win-amd64-3.7\MySQLdb
copying MySQLdb\cursors.py -> build\lib.win-amd64-3.7\MySQLdb
copying MySQLdb\release.py -> build\lib.win-amd64-3.7\MySQLdb
copying MySQLdb\times.py -> build\lib.win-amd64-3.7\MySQLdb
creating build\lib.win-amd64-3.7\MySQLdb\constants
copying MySQLdb\constants\__init__.py -> build\lib.win-amd64-3.7\MySQLdb\constants
copying MySQLdb\constants\CLIENT.py -> build\lib.win-amd64-3.7\MySQLdb\constants
copying MySQLdb\constants\CR.py -> build\lib.win-amd64-3.7\MySQLdb\constants
copying MySQLdb\constants\ER.py -> build\lib.win-amd64-3.7\MySQLdb\constants
copying MySQLdb\constants\FIELD_TYPE.py -> build\lib.win-amd64-3.7\MySQLdb\constants
copying MySQLdb\constants\FLAG.py -> build\lib.win-amd64-3.7\MySQLdb\constants
copying MySQLdb\constants\REFRESH.py -> build\lib.win-amd64-3.7\MySQLdb\constants
running build_ext
building '_mysql' extension
error: Microsoft Visual C++ 14.0 is required. Get it with "Microsoft Visual C++ Build Tools": http://landinghub.visualstudio.com/visual-cpp-build-tools

----------------------------------------
Command "D:\PortablePython37\App\Python\python.exe -u -c "import setuptools, tokenize;__file__='C:\\Users\\TONYHU~1\\AppData\\Local\\Temp\\pip-install-0cfu1z52\\mysqlclient\\setup.py';f=getattr(tokenize, 'open', open)(__file__);code=f.read().replace('\r\n', '\n');f.close();exec(compile(code, __file__, 'exec'))" install --record C:\Users\TONYHU~1\AppData\Local\Temp\pip-record-tzrl7s3z\install-record.txt --single-version-externally-managed --compile" failed with error code 1 in C:\Users\TONYHU~1\AppData\Local\Temp\pip-install-0cfu1z52\mysqlclient\

有看沒有懂, 這模組就算了, 反正有 PyMySQL 就可以了.

另外, 因 tensorflow 目前僅支援到 Python 3.6, 而此 Portable Python 為 3.7.0 版, 因此用 pip 安裝時會報 "No matching distribution found" 錯誤, 所以就先不安裝, 等以後支援了再說, 連帶 Keras 也是以後再安裝 :

D:\PortablePython37>python -m pip install tensorflow
Collecting tensorflow
Could not find a version that satisfies the requirement tensorflow (from versions: )
No matching distribution found for tensorflow

最後用 pip list 查看已安裝模組如下 :

D:\PortablePython37>python -m pip list

Package Version

----------------- ----------

asn1crypto 0.24.0

bcrypt 3.1.4

beautifulsoup4 4.6.3

certifi 2018.10.15

cffi 1.11.5

chardet 3.0.4

cryptography 2.3.1

cycler 0.10.0

Django 1.8.19

et-xmlfile 1.0.1

fix-yahoo-finance 0.0.22

html5lib 1.0.1

idna 2.7

jdcal 1.4

kiwisolver 1.0.1

lxml 4.2.5

matplotlib 3.0.0

multitasking 0.0.7

numpy 1.15.3

openpyxl 2.5.9

pandas 0.23.4

paramiko 2.4.2

pip 18.1

pyasn1 0.4.4

pycparser 2.19

PyMySQL 0.9.2

PyNaCl 1.3.0

pyparsing 2.2.2

python-dateutil 2.7.3

pytz 2018.6

requests 2.20.0

scikit-learn 0.20.0

scipy 1.1.0

selenium 3.14.1

setuptools 39.0.1

six 1.11.0

urllib3 1.24

webencodings 0.5.1

xlrd 1.1.0

安裝完後約 350MB, 沒想到這些模組加起來竟然這麼大! 重新壓縮後的 ZIP 檔也膨脹到 150MB 左右, 這樣就可以移到無法線上安裝的電腦使用了.

2018-10-26 補充 :

安裝完所需模組移到網內使用時若仍發現缺了那些模組, 不用回網外電腦安裝後再搬檔案, 只要去 PyPi 網站下載該模組之 whl 檔 (以及所有相依模組) 安裝即可, 例如今天發現 pexpect 好用沒安裝到, 於是下載了 pexpect 及其相依模組 ptyprocess 以 pip 安裝m 例如 :

C:\Python37>python -m pip install ptyprocess-0.6.0-py2.py3-none-any.whl
Processing c:\python37\ptyprocess-0.6.0-py2.py3-none-any.whl
Installing collected packages: ptyprocess
Successfully installed ptyprocess-0.6.0

C:\Python37>python -m pip install pexpect-4.6.0-py2.py3-none-any.whl
Processing c:\python37\pexpect-4.6.0-py2.py3-none-any.whl
Requirement already satisfied: ptyprocess>=0.5 in c:\python37\app\python\lib\sit
e-packages (from pexpect==4.6.0) (0.6.0)
Installing collected packages: pexpect
Successfully installed pexpect-4.6.0

2018年10月23日星期二

Python Fintech 學習筆記 : 用 twder 模組擷取台銀外匯報價

最近勤加練習 Python 應用, 發現 Python 應用實在既深且廣, 不斷的有高手將爬蟲寫成模組分享出來, 在 PyPi 網站隨時都有驚奇出現. 今天在 "行銷資料科學 (Medium)" 看到下面這拚文章, 介紹用 twder 模組抓取台銀即時外匯報價的方法, 省去自行撰寫網頁爬蟲的麻煩, 真是 Fintech 的好工具 :

# 一秒就上手！馬上幫您爬取匯率價格！掌控最新貿易匯損！（附python 程式碼）

此模組作者為 Jimms Hsieh, 並將其發布在 PyPi 網站 :

# https://pypi.org/project/twder/

線上安裝過程 :

D:\Python\E_14_1>pip3 install twder
Collecting twder
Downloading https://files.pythonhosted.org/packages/03/3b/49ab585b6cd2734afee4227f5a344a110419e3eba298269eb87a943a980b/twder-0.1.1-py2.py3-none-any.whl
Requirement already satisfied: lxml in c:\python36\lib\site-packages (from twder) (4.2.1)
Requirement already satisfied: requests in c:\python36\lib\site-packages (from twder) (2.18.4)
Requirement already satisfied: idna<2 .7="">=2.5 in c:\python36\lib\site-packages (from requests->twder) (2.6)
Requirement already satisfied: chardet<3 .1.0="">=3.0.2 in c:\python36\lib\site-packages (from requests->twder) (3.0.4)
Requirement already satisfied: urllib3<1 .23="">=1.21.1 in c:\python36\lib\site-packages (from requests->twder) (1.22)
Requirement already satisfied: certifi>=2017.4.17 in c:\python36\lib\site-packages (from requests->twder) (2018.4.16)
Installing collected packages: twder
Successfully installed twder-0.1.1

從安裝過程可知, 此模組使用 requests 與 lxml 等等來爬台銀外匯報價網頁. 如果因為防火牆無法用 pip 安裝, 可到 Pypi 網站下載 whl 安裝檔 twder-0.1.1-py2.py3-none-any.whl :

# https://pypi.org/project/twder/#files

本地安裝過程 :

D:\Python>pip3 install twder-0.1.1-py2.py3-none-any.whl
Processing d:\python\twder-0.1.1-py2.py3-none-any.whl
Requirement already satisfied: requests in c:\python36\lib\site-packages (from twder==0.1.1) (2.13.0
)
Collecting lxml (from twder==0.1.1)

安裝好 twder 模組即可利用其 API 抓取台銀匯率報價, 使用方法見作者之 GitHub :

# https://github.com/jimms/twder

從 twder 目錄裡面的 api.py 可窺知其爬蟲做法 (高手不吝分享的絕技非常值得學習), 擷取對象是台銀外匯報價網頁 :

# http://rate.bot.com.tw/xrt?Lang=zh-TW (即時)

擷取歷史匯價的 URL 格式如下 :

http://rate.bot.com.tw/xrt/quote/{range}/{currency}

其中 range 為 "年-月", 例如 2018-10; 而 currency 為貨幣代號, 例如 USD (美金), JPY (日元), CNY (人民幣), EUR (歐元) 等等. 例如擷取 2018 年 10 月之美元歷史匯率報價, 其 URL 為 :

http://rate.bot.com.tw/xrt/quote/2018-10/USD

使用 twder 前須先匯入模組 :

import twder

此模組提供如下函數 :

twder 模組的函數	說明
currencies()	傳回全部外幣代號 (list)
currency_name_dict()	傳回全部外幣代號與其中文名稱 (dict)
now(currency)	傳回指定外幣目前之報價 (tuple)
now_all()	傳回全部外幣目前之報價 (dict)
past_day(currency)	傳回指定外幣昨日全部報價 (list)
past_six_month(currency)	傳回指定外幣過去半年每天之收盤價 (list)
specify_month(currency, year, month)	傳回指定外幣在指定年月每天之收盤價 (list)

1 : 列出台銀可交易之外幣代號

currencies() 只傳回幣別代號串列, 而 currency_name_dict() 則附上外幣中文名稱字典.

>>> import twder
>>> twder.currencies()
['USD', 'HKD', 'GBP', 'AUD', 'CAD', 'SGD', 'CHF', 'JPY', 'ZAR', 'SEK', 'NZD', 'THB', 'PHP', 'IDR', 'EUR', 'KRW', 'VND', 'MYR', 'CNY']
>>> twder.currency_name_dict()
{'USD': '美金 (USD)', 'HKD': '港幣 (HKD)', 'GBP': '英鎊 (GBP)', 'AUD': '澳幣 (AUD)', 'CAD': '加拿大幣 (CAD)', 'SGD': '新加坡幣 (SGD)', 'CHF': '瑞士法郎 (CHF)', 'JPY': '日圓 (JPY)', 'ZAR': '南非幣 (ZAR)', 'SEK': '瑞典幣 (SEK)', 'NZD': '紐元 (NZD)', 'THB': '泰幣 (THB)', 'PHP': '菲國比索 (PHP)', 'IDR': '印尼幣 (IDR)', 'EUR': '歐元 (EUR)', 'KRW': '韓元 (KRW)', 'VND': '越南盾 (VND)', 'MYR': '馬來幣 (MYR)', 'CNY': '人民幣 (CNY)'}

可見總共有 19 種可交易外幣

2. 查詢指定貨幣目前的即時報價

>>> twder.now('USD')
('2018/10/23 16:01', '30.54', '31.23', '30.91', '31.01')

傳回之 tuple 有五個元素 :

(時間, 現金買入, 現金賣出, 即期買入, 即期賣出)

3. 查詢全部貨幣目前的即時報價

>>> twder.now_all()
{'USD': ('2018/10/23 16:01', '30.54', '31.23', '30.91', '31.01'), 'HKD': ('2018/10/23 16:01', '3.783', '3.999', '3.919', '3.979'), 'GBP': ('2018/10/23 16:01', '39.01', '41.13', '40.01', '40.43'), 'AUD': ('2018/10/23 16:01', '21.55', '22.33', '21.82', '22.05'), 'CAD': ('2018/10/23 16:01', '23.16', '24.07', '23.55', '23.77'), 'SGD': ('2018/10/23 16:01', '21.88', '22.79', '22.37', '22.55'), 'CHF': ('2018/10/23 16:01', '30.29', '31.49', '30.95', '31.24'), 'JPY': ('2018/10/23 16:01', '0.2663', '0.2791', '0.2736', '0.2776'), 'ZAR': ('2018/10/23 16:01', '-', '-', '2.11', '2.19'), 'SEK': ('2018/10/23 16:01', '3.05', '3.57', '3.39', '3.49'), 'NZD': ('2018/10/23 16:01', '19.85', '20.7', '20.23', '20.43'), 'THB': ('2018/10/23 16:01', '0.819', '1.007', '0.9276', '0.9676'), 'PHP': ('2018/10/23 16:01', '0.5018', '0.6348', '-', '-'), 'IDR': ('2018/10/23 16:01', '0.00168', '0.00238', '-', '-'), 'EUR': ('2018/10/23 16:01', '34.69', '36.03', '35.31', '35.71'), 'KRW': ('2018/10/23 16:01', '0.02551', '0.02941', '-', '-'), 'VND': ('2018/10/23 16:01', '0.00095', '0.00145', '-', '-'), 'MYR': ('2018/10/23 16:01', '6.344', '7.974', '-', '-'), 'CNY': ('2018/10/23 16:01', '4.36', '4.522', '4.432', '4.482')}

4. 查詢指定貨幣昨日全部報價

>>> twder.past_day('USD')
[('2018/10/23 09:01:01', '30.52', '31.21', '30.89', '30.99'), ('2018/10/23 09:02:55', '30.525', '31.215', '30.895', '30.995'), ('2018/10/23 09:04:30', '30.535', '31.225', '30.905', '31.005'), ('2018/10/23 09:05:43', '30.54', '31.23', '30.91', '31.01'), ('2018/10/23 09:07:02', '30.53', '31.22', '30.9', '31'), ('2018/10/23 09:12:28', '30.525', '31.215', '30.895', '30.995'), ('2018/10/23 09:15:49', '30.525', '31.215', '30.895', '30.995'), ('2018/10/23 09:17:17', '30.52', '31.21', '30.89', '30.99'), ('2018/10/23 09:21:57', '30.515', '31.205', '30.885', '30.985'), ('2018/10/23 09:24:32', '30.51', '31.2', '30.88', '30.98'), ('2018/10/23 09:28:09', '30.515', '31.205', '30.885', '30.985'), ('2018/10/23 09:35:59', '30.51', '31.2', '30.88', '30.98'), ('2018/10/23 09:38:46', '30.51', '31.2', '30.88', '30.98'), ('2018/10/23 09:40:44', '30.51', '31.2', '30.88', '30.98'), ('2018/10/23 09:48:51', '30.52', '31.21', '30.89', '30.99'), ('2018/10/23 09:50:10', '30.525', '31.215', '30.895', '30.995'), ('2018/10/23 09:52:31', '30.525', '31.215', '30.895', '30.995'), ('2018/10/23 09:58:44', '30.525', '31.215', '30.895', '30.995'), ('2018/10/23 10:05:43', '30.525', '31.215', '30.895', '30.995'), ('2018/10/23 10:15:33', '30.52', '31.21', '30.89', '30.99'), ('2018/10/23 10:21:54', '30.525', '31.215', '30.895', '30.995'), ('2018/10/23 10:26:31', '30.525', '31.215', '30.895', '30.995'), ('2018/10/23 10:28:29', '30.53', '31.22', '30.9', '31'), ('2018/10/23 10:30:59', '30.53', '31.22', '30.9', '31'), ('2018/10/23 10:45:50', '30.53', '31.22', '30.9', '31'), ('2018/10/23 10:59:00', '30.54', '31.23', '30.91', '31.01'), ('2018/10/23 10:59:46', '30.545', '31.235', '30.915', '31.015'), ('2018/10/23 11:01:47', '30.535', '31.225', '30.905', '31.005'), ('2018/10/23 11:20:48', '30.54', '31.23', '30.91', '31.01'), ('2018/10/23 11:36:05', '30.54', '31.23', '30.91', '31.01'), ('2018/10/23 11:44:24', '30.54', '31.23', '30.91', '31.01'), ('2018/10/23 11:54:21', '30.545', '31.235', '30.915', '31.015'), ('2018/10/23 11:57:05', '30.54', '31.23', '30.91', '31.01'), ('2018/10/23 12:21:57', '30.54', '31.23', '30.91', '31.01'), ('2018/10/23 12:30:55', '30.54', '31.23', '30.91', '31.01'), ('2018/10/23 12:47:50', '30.54', '31.23', '30.91', '31.01'), ('2018/10/23 13:06:57', '30.54', '31.23', '30.91', '31.01'), ('2018/10/23 13:21:23', '30.54', '31.23', '30.91', '31.01'), ('2018/10/23 13:41:52', '30.54', '31.23', '30.91', '31.01'), ('2018/10/23 13:52:33', '30.54', '31.23', '30.91', '31.01'), ('2018/10/23 13:59:38', '30.54', '31.23', '30.91', '31.01'), ('2018/10/23 14:02:10', '30.545', '31.235', '30.915', '31.015'), ('2018/10/23 14:03:06', '30.55', '31.24', '30.92', '31.02'), ('2018/10/23 14:11:39', '30.56', '31.25', '30.93', '31.03'), ('2018/10/23 14:19:02', '30.57', '31.26', '30.94', '31.04'), ('2018/10/23 14:23:07', '30.565', '31.255', '30.935', '31.035'), ('2018/10/23 14:24:54', '30.56', '31.25', '30.93', '31.03'), ('2018/10/23 14:26:10', '30.555', '31.245', '30.925', '31.025'), ('2018/10/23 14:33:29', '30.55', '31.24', '30.92', '31.02'), ('2018/10/23 14:34:03', '30.545', '31.235', '30.915', '31.015'), ('2018/10/23 14:42:06', '30.545', '31.235', '30.915', '31.015'), ('2018/10/23 14:44:05', '30.545', '31.235', '30.915', '31.015'), ('2018/10/23 14:46:08', '30.55', '31.24', '30.92', '31.02'), ('2018/10/23 14:54:23', '30.555', '31.245', '30.925', '31.025'), ('2018/10/23 14:55:39', '30.555', '31.245', '30.925', '31.025'), ('2018/10/23 14:56:56', '30.555', '31.245', '30.925', '31.025'), ('2018/10/23 14:58:30', '30.55', '31.24', '30.92', '31.02'), ('2018/10/23 14:59:08', '30.545', '31.235', '30.915', '31.015'), ('2018/10/23 14:59:53', '30.54', '31.23', '30.91', '31.01'), ('2018/10/23 14:59:56', '30.54', '31.23', '30.91', '31.01'), ('2018/10/23 15:02:22', '30.545', '31.235', '30.915', '31.015'), ('2018/10/23 15:04:53', '30.55', '31.24', '30.92', '31.02'), ('2018/10/23 15:20:15', '30.55', '31.24', '30.92', '31.02'), ('2018/10/23 15:21:26', '30.545', '31.235', '30.915', '31.015'), ('2018/10/23 15:33:32', '30.545', '31.235', '30.915', '31.015'), ('2018/10/23 15:37:56', '30.545', '31.235', '30.915', '31.015'), ('2018/10/23 15:38:09', '30.545', '31.235', '30.915', '31.015'), ('2018/10/23 15:42:42', '30.54', '31.23', '30.91', '31.01'), ('2018/10/23 16:01:16', '30.54', '31.23', '30.91', '31.01')]

5. 查詢指定貨幣過去半年每天收盤價

>>> twder.past_six_month('USD')
[('2018/10/23', '30.54', '31.23', '30.91', '31.01'), ('2018/10/22', '30.495', '31.185', '30.865', '30.965'), ('2018/10/19', '30.53', '31.22', '30.9', '31'), ('2018/10/18', '30.53', '31.22', '30.9', '31'), ('2018/10/17', '30.41', '31.1', '30.78', '30.88'), ('2018/10/16', '30.485', '31.175', '30.855', '30.955'), ('2018/10/15', '30.5', '31.19', '30.87', '30.97'), ('2018/10/12', '30.44', '31.13', '30.81', '30.91'), ('2018/10/11', '30.68', '31.37', '31.05', '31.15'), ('2018/10/09', '30.54', '31.23', '30.91', '31.01'), ('2018/10/08', '30.505', '31.195', '30.875', '30.975'), ('2018/10/05', '30.405', '31.095', '30.775', '30.875'), ('2018/10/04', '30.36', '31.05', '30.73', '30.83'), ('2018/10/03', '30.24', '30.93', '30.61', '30.71'), ('2018/10/02', '30.245', '30.935', '30.615', '30.715'), ('2018/10/01', '30.11', '30.8', '30.48', '30.58'), ('2018/09/28', '30.105', '30.795', '30.475', '30.575'), ('2018/09/27', '30.17', '30.86', '30.54', '30.64'), ('2018/09/26', '30.27', '30.96', '30.64', '30.74'), ('2018/09/25', '30.24', '30.93', '30.61', '30.71'), ('2018/09/21', '30.28', '30.97', '30.65', '30.75'), ('2018/09/20', '30.37', '31.06', '30.74', '30.84'), ('2018/09/19', '30.36', '31.05', '30.73', '30.83'), ('2018/09/18', '30.385', '31.075', '30.755', '30.855'), ('2018/09/17', '30.38', '31.07', '30.75', '30.85'), ('2018/09/14', '30.32', '31.01', '30.69', '30.79'), ('2018/09/13', '30.38', '31.07', '30.75', '30.85'), ('2018/09/12', '30.385', '31.075', '30.755', '30.855'), ('2018/09/11', '30.385', '31.075', '30.755', '30.855'), ('2018/09/10', '30.39', '31.08', '30.76', '30.86'), ('2018/09/07', '30.345', '31.035', '30.715', '30.815'), ('2018/09/06', '30.37', '31.06', '30.74', '30.84'), ('2018/09/05', '30.375', '31.065', '30.745', '30.845'), ('2018/09/04', '30.33', '31.02', '30.7', '30.8'), ('2018/09/03', '30.28', '30.97', '30.65', '30.75'), ('2018/08/31', '30.295', '30.985', '30.665', '30.765'), ('2018/08/30', '30.255', '30.945', '30.625', '30.725'), ('2018/08/29', '30.275', '30.965', '30.645', '30.745'), ('2018/08/28', '30.3', '30.99', '30.67', '30.77'), ('2018/08/27', '30.345', '31.035', '30.715', '30.815'), ('2018/08/24', '30.355', '31.045', '30.725', '30.825'), ('2018/08/23', '30.36', '31.05', '30.73', '30.83'), ('2018/08/22', '30.305', '30.995', '30.675', '30.775'), ('2018/08/21', '30.3', '30.99', '30.67', '30.77'), ('2018/08/20', '30.34', '31.03', '30.71', '30.81'), ('2018/08/17', '30.375', '31.065', '30.745', '30.845'), ('2018/08/16', '30.425', '31.115', '30.795', '30.895'), ('2018/08/15', '30.43', '31.12', '30.8', '30.9'), ('2018/08/14', '30.385', '31.075', '30.755', '30.855'), ('2018/08/13', '30.39', '31.08', '30.76', '30.86'), ('2018/08/10', '30.28', '30.97', '30.65', '30.75'), ('2018/08/09', '30.2', '30.89', '30.57', '30.67'), ('2018/08/08', '30.195', '30.885', '30.565', '30.665'), ('2018/08/07', '30.19', '30.88', '30.56', '30.66'), ('2018/08/06', '30.205', '30.895', '30.575', '30.675'), ('2018/08/03', '30.28', '30.97', '30.65', '30.75'), ('2018/08/02', '30.25', '30.94', '30.62', '30.72'), ('2018/08/01', '30.18', '30.87', '30.55', '30.65'), ('2018/07/31', '30.185', '30.875', '30.555', '30.655'), ('2018/07/30', '30.18', '30.87', '30.55', '30.65'), ('2018/07/27', '30.165', '30.855', '30.535', '30.635'), ('2018/07/26', '30.14', '30.83', '30.51', '30.61'), ('2018/07/25', '30.2', '30.89', '30.57', '30.67'), ('2018/07/24', '30.28', '30.97', '30.65', '30.75'), ('2018/07/23', '30.22', '30.91', '30.59', '30.69'), ('2018/07/20', '30.285', '30.975', '30.655', '30.755'), ('2018/07/19', '30.205', '30.895', '30.575', '30.675'), ('2018/07/18', '30.155', '30.845', '30.525', '30.625'), ('2018/07/17', '30.08', '30.77', '30.45', '30.55'), ('2018/07/16', '30.15', '30.84', '30.52', '30.62'), ('2018/07/13', '30.13', '30.82', '30.5', '30.6'), ('2018/07/12', '30.11', '30.8', '30.48', '30.58'), ('2018/07/11', '30.045', '30.735', '30.415', '30.515'), ('2018/07/10', '29.965', '30.655', '30.335', '30.435'), ('2018/07/09', '29.95', '30.64', '30.32', '30.42'), ('2018/07/06', '30.07', '30.76', '30.44', '30.54'), ('2018/07/05', '30.1', '30.79', '30.47', '30.57'), ('2018/07/04', '30.065', '30.755', '30.435', '30.535'), ('2018/07/03', '30.16', '30.85', '30.53', '30.63'), ('2018/07/02', '30.09', '30.78', '30.46', '30.56'), ('2018/06/29', '30.11', '30.652', '30.41', '30.51'), ('2018/06/28', '30.225', '30.767', '30.525', '30.625'), ('2018/06/27', '30.095', '30.637', '30.395', '30.495'), ('2018/06/26', '30.05', '30.592', '30.35', '30.45'), ('2018/06/25', '30.035', '30.577', '30.335', '30.435'), ('2018/06/22', '29.95', '30.492', '30.25', '30.35'), ('2018/06/21', '29.935', '30.477', '30.235', '30.335'), ('2018/06/20', '29.79', '30.332', '30.09', '30.19'), ('2018/06/19', '29.83', '30.372', '30.13', '30.23'), ('2018/06/15', '29.635', '30.177', '29.935', '30.035'), ('2018/06/14', '29.58', '30.122', '29.88', '29.98'), ('2018/06/13', '29.53', '30.072', '29.83', '29.93'), ('2018/06/12', '29.495', '30.037', '29.795', '29.895'), ('2018/06/11', '29.46', '30.002', '29.76', '29.86'), ('2018/06/08', '29.455', '29.997', '29.755', '29.855'), ('2018/06/07', '29.365', '29.907', '29.665', '29.765'), ('2018/06/06', '29.375', '29.917', '29.675', '29.775'), ('2018/06/05', '29.455', '29.997', '29.755', '29.855'), ('2018/06/04', '29.465', '30.007', '29.765', '29.865'), ('2018/06/01', '29.49', '30.032', '29.79', '29.89'), ('2018/05/31', '29.6', '30.142', '29.9', '30'), ('2018/05/30', '29.68', '30.222', '29.98', '30.08'), ('2018/05/29', '29.63', '30.172', '29.93', '30.03'), ('2018/05/28', '29.58', '30.122', '29.88', '29.98'), ('2018/05/25', '29.595', '30.137', '29.895', '29.995'), ('2018/05/24', '29.57', '30.112', '29.87', '29.97'), ('2018/05/23', '29.61', '30.152', '29.91', '30.01'), ('2018/05/22', '29.55', '30.092', '29.85', '29.95'), ('2018/05/21', '29.635', '30.177', '29.935', '30.035'), ('2018/05/18', '29.555', '30.097', '29.855', '29.955'), ('2018/05/17', '29.545', '30.087', '29.845', '29.945'), ('2018/05/16', '29.525', '30.067', '29.825', '29.925'), ('2018/05/15', '29.5', '30.042', '29.8', '29.9'), ('2018/05/14', '29.38', '29.922', '29.68', '29.78'), ('2018/05/11', '29.41', '29.952', '29.71', '29.81'), ('2018/05/10', '29.51', '30.052', '29.81', '29.91'), ('2018/05/09', '29.575', '30.117', '29.875', '29.975'), ('2018/05/08', '29.43', '29.972', '29.73', '29.83'), ('2018/05/07', '29.405', '29.947', '29.705', '29.805'), ('2018/05/04', '29.355', '29.897', '29.655', '29.755'), ('2018/05/03', '29.375', '29.917', '29.675', '29.775'), ('2018/05/02', '29.385', '29.927', '29.685', '29.785'), ('2018/04/30', '29.255', '29.797', '29.555', '29.655'), ('2018/04/27', '29.27', '29.812', '29.57', '29.67'), ('2018/04/26', '29.355', '29.897', '29.655', '29.755'), ('2018/04/25', '29.3', '29.842', '29.6', '29.7'), ('2018/04/24', '29.26', '29.802', '29.56', '29.66')]

6. 查詢指定貨幣於指定月份每天收盤價

>>> twder.specify_month('USD', 2018, 10)
[('2018/10/23', '30.54', '31.23', '30.91', '31.01'), ('2018/10/22', '30.495', '31.185', '30.865', '30.965'), ('2018/10/19', '30.53', '31.22', '30.9', '31'), ('2018/10/18', '30.53', '31.22', '30.9', '31'), ('2018/10/17', '30.41', '31.1', '30.78', '30.88'), ('2018/10/16', '30.485', '31.175', '30.855', '30.955'), ('2018/10/15', '30.5', '31.19', '30.87', '30.97'), ('2018/10/12', '30.44', '31.13', '30.81', '30.91'), ('2018/10/11', '30.68', '31.37', '31.05', '31.15'), ('2018/10/09', '30.54', '31.23', '30.91', '31.01'), ('2018/10/08', '30.505', '31.195', '30.875', '30.975'), ('2018/10/05', '30.405', '31.095', '30.775', '30.875'), ('2018/10/04', '30.36', '31.05', '30.73', '30.83'), ('2018/10/03', '30.24', '30.93', '30.61', '30.71'), ('2018/10/02', '30.245', '30.935', '30.615', '30.715'), ('2018/10/01', '30.11', '30.8', '30.48', '30.58')]

嗯, 這套件很棒.

購買創見 64GB SD 卡

因換 Note8 手機後移過去的 16GB 卡似乎有點小 (照相因解析度變高, 檔案大小也變大了), 所以上露天買了一張 64GB 的 SD 卡 :

# SanDisk 64GB 64G microSDXC【Ultra 80MB/s】micro SD SDXC C10 $277

加運費 55 元共 332 元. 本來有考慮買 128GB, 但想到 INHON 筆電的 D 碟也才 64GB 用到現在還 OK, 手機若用 128GB 不是比筆電記憶體還多嗎? 實在很奇怪. 參考 :

# SanDisk 128GB 128G microSDXC【80MB/s Ultra】microSD SDXC 記憶卡 $568
# SanDisk Ultra microSDXC UHS-I (A1) 64G 記憶卡 $890

清朝影像 China Qing Dynasty film

今天在 Youtube 看到名為 "清朝影像" 的一系列黑白紀錄片, 下方的留言說這是清朝時期法國電影公司 GAUMONT 拍攝, 又有人說是法國駐昆明領事方蘇雅所拍攝, 總之是難得的歷史紀錄片, 使吾人得以一窺清朝人的樣子.

# 清朝影像 China Qing Dynasty film 1
# 清朝影像 China Qing Dynasty film 2
# 清朝影像 China Qing Dynasty film 3
# 清朝影像 China Qing Dynasty film 4
# 清朝影像 China Qing Dynasty film 5
# 清朝影像 China Qing Dynasty film 6
# 清朝影像 China Qing Dynasty film 7
# 清朝影像 China Qing Dynasty film 8

默片只能看到動作, 如果當時有錄下聲音就好了. 當時的人交通工具只有走路, 騎馬, 坐轎, 還有人力車, 百餘年後的今天到處是風馳電掣的汽車, 如果真能穿越時空, 他們一定會嚇一跳吧?

2018年10月22日星期一

Python Fintech 學習筆記 : 從 Yahoo Finance 擷取台股成交資料

上周利用 "Python 網頁程式交易 APP 實作" 第 14 章的程式去下載 Google Finance 台股歷史資料, 測試結果失敗, 因為 Google 已經關閉了歷史資料下載功能, 只提供線型瀏覽. 殘念! 不過另一個抓 Yahoo Finance 的範例程式倒是可用, 以下為測試紀錄.

Python Fintech 測試系列此前文章參考 :

# Python Fintech 學習筆記 : 安裝技術指標套件 TA-Lib
# Python Fintech 學習筆記 : Google Finance 無法下載歷史資料

"Python 網頁程式交易 APP 實作" 範例程式下載連結 :

# https://github.com/letylin/pyptbook

我下載的是第二版範例 :

# 二版課本範例程式.zip

Yahoo 版抓取程式為其中的 E_14_1.py, 但在我的電腦直接執行時卻出現缺少 pymysql, xlrd, fix_yahoo_finance 與 openpyxl 等模組之錯誤訊息, 須用 pip3 安裝 :

D:\Python\E_14_1>pip3 install pymysql
Collecting pymysql
Downloading https://files.pythonhosted.org/packages/a7/7d/682c4a7da195a678047c8f1c51bb7682aaedee1dca7547883c3993ca9282/PyMySQL-0.9.2-py2.py3-none-any.whl (47kB)
Collecting cryptography (from pymysql)
Downloading https://files.pythonhosted.org/packages/f1/01/a144ec664d3f9ae5837bd72c4d11bdd2d8d403318898e4092457e8af9272/cryptography-2.3.1-cp36-cp36m-win_amd64.whl (1.3MB)
Requirement already satisfied: six>=1.4.1 in c:\python36\lib\site-packages (from cryptography->pymysql) (1.11.0)
Requirement already satisfied: idna>=2.1 in c:\python36\lib\site-packages (from cryptography->pymysql) (2.6)
Collecting asn1crypto>=0.21.0 (from cryptography->pymysql)
Downloading https://files.pythonhosted.org/packages/ea/cd/35485615f45f30a510576f1a56d1e0a7ad7bd8ab5ed7cdc600ef7cd06222/asn1crypto-0.24.0-py2.py3-none-any.whl (101kB)
Collecting cffi!=1.11.3,>=1.7 (from cryptography->pymysql)
Downloading https://files.pythonhosted.org/packages/2f/85/a9184548ad4261916d08a50d9e272bf6f93c54f3735878fbfc9335efd94b/cffi-1.11.5-cp36-cp36m-win_amd64.whl (166kB)
Collecting pycparser (from cffi!=1.11.3,>=1.7->cryptography->pymysql)
Downloading https://files.pythonhosted.org/packages/68/9e/49196946aee219aead1290e00d1e7fdeab8567783e83e1b9ab5585e6206a/pycparser-2.19.tar.gz (158kB)
Building wheels for collected packages: pycparser
Running setup.py bdist_wheel for pycparser: started
Running setup.py bdist_wheel for pycparser: finished with status 'done'
Stored in directory: C:\Users\Tony\AppData\Local\pip\Cache\wheels\f2\9a\90\de94f8556265ddc9d9c8b271b0f63e57b26fb1d67a45564511
Successfully built pycparser
Installing collected packages: asn1crypto, pycparser, cffi, cryptography, pymysql
Successfully installed asn1crypto-0.24.0 cffi-1.11.5 cryptography-2.3.1 pycparser-2.19 pymysql-0.9.2

D:\Python\E_14_1>pip3 install xlrd
Collecting xlrd
Downloading https://files.pythonhosted.org/packages/07/e6/e95c4eec6221bfd8528bcc4ea252a850bffcc4be88ebc367e23a1a84b0bb/xlrd-1.1.0-py2.py3-none-any.whl (108kB)
Installing collected packages: xlrd
Successfully installed xlrd-1.1.0

D:\Python\E_14_1>pip3 install fix_yahoo_finance
Collecting fix_yahoo_finance
Downloading https://files.pythonhosted.org/packages/0a/96/d44330e427f5368cb8abd25997b72956a31b52073d285c4d5cd56e5fdc17/fix-yahoo-finance-0.0.22.tar.gz
Requirement already satisfied: pandas in c:\python36\lib\site-packages (from fix_yahoo_finance) (0.22.0)
Requirement already satisfied: numpy in c:\python36\lib\site-packages (from fix_yahoo_finance) (1.14.1)
Requirement already satisfied: requests in c:\python36\lib\site-packages (from fix_yahoo_finance) (2.18.4)
Collecting multitasking (from fix_yahoo_finance)
Downloading https://files.pythonhosted.org/packages/ac/1a/0750416c5e3683d170757e423f097fdf78ceb9ccdc65658b24341664e53e/multitasking-0.0.7.tar.gz
Requirement already satisfied: python-dateutil>=2 in c:\python36\lib\site-packages (from pandas->fix_yahoo_finance) (2.6.1)
Requirement already satisfied: pytz>=2011k in c:\python36\lib\site-packages (from pandas->fix_yahoo_finance) (2018.3)
Requirement already satisfied: chardet<3 .1.0="">=3.0.2 in c:\python36\lib\site-packages (from requests->fix_yahoo_finance) (3.0.4)
Requirement already satisfied: certifi>=2017.4.17 in c:\python36\lib\site-packages (from requests->fix_yahoo_finance) (2018.4.16)
Requirement already satisfied: urllib3<1 .23="">=1.21.1 in c:\python36\lib\site-packages (from requests->fix_yahoo_finance) (1.22)
Requirement already satisfied: idna<2 .7="">=2.5 in c:\python36\lib\site-packages (from requests->fix_yahoo_finance) (2.6)
Requirement already satisfied: six>=1.5 in c:\python36\lib\site-packages (from python-dateutil>=2->pandas->fix_yahoo_finance) (1.11.0)
Building wheels for collected packages: fix-yahoo-finance, multitasking
Running setup.py bdist_wheel for fix-yahoo-finance: started
Running setup.py bdist_wheel for fix-yahoo-finance: finished with status 'done'
Stored in directory: C:\Users\Tony\AppData\Local\pip\Cache\wheels\2c\ca\ce\218a19aaecf63fd74c75d6a6772b1a799fa05826d8762bfd83
Running setup.py bdist_wheel for multitasking: started
Running setup.py bdist_wheel for multitasking: finished with status 'done'
Stored in directory: C:\Users\Tony\AppData\Local\pip\Cache\wheels\41\e4\48\af808a1c57f43f104042abdaf80fa623ab213ca0268ba4189c
Successfully built fix-yahoo-finance multitasking
Installing collected packages: multitasking, fix-yahoo-finance
Successfully installed fix-yahoo-finance-0.0.22 multitasking-0.0.7

D:\Python\E_14_1>pip3 install openpyxl
Collecting openpyxl
Downloading https://files.pythonhosted.org/packages/e5/0a/e0a095149a23cedd9c8db6cdde2af7f82105e219e14edea0c31a19aeff9e/openpyxl-2.5.8.tar.gz (1.9MB)
Collecting jdcal (from openpyxl)
Downloading https://files.pythonhosted.org/packages/a0/38/dcf83532480f25284f3ef13f8ed63e03c58a65c9d3ba2a6a894ed9497207/jdcal-1.4-py2.py3-none-any.whl
Collecting et_xmlfile (from openpyxl)
Downloading https://files.pythonhosted.org/packages/22/28/a99c42aea746e18382ad9fb36f64c1c1f04216f41797f2f0fa567da11388/et_xmlfile-1.0.1.tar.gz
Building wheels for collected packages: openpyxl, et-xmlfile
Running setup.py bdist_wheel for openpyxl ... done
Stored in directory: C:\Users\Tony Huang\AppData\Local\pip\Cache\wheels\3f\37\28\5ab3dffb7ff261e6fa21455ec9d157f95958e818c6b89f024c
Running setup.py bdist_wheel for et-xmlfile ... done
Stored in directory: C:\Users\Tony Huang\AppData\Local\pip\Cache\wheels\2a\77\35\0da0965a057698121fc7d8c5a7a9955cdbfb3cc4e2423cad39
Successfully built openpyxl et-xmlfile
Installing collected packages: jdcal, et-xmlfile, openpyxl
Successfully installed et-xmlfile-1.0.1 jdcal-1.4 openpyxl-2.5.8

另外還需要 pandas 模組處理 DataFrame 物件以儲存所擷取之資料, 需用 pip3 安裝 pandas, 但我電腦之前已安裝過, 因此不會有找不到 pandas 問題.

書中範例 E_14_1.py 中我只改了要抓取的起迄日期 :

start = datetime.datetime(2017,10,1)
end = datetime.datetime(2018,10,19)

執行結果如下 :

D:\Python\E_14_1>python E_14_1.py

[*********************100%***********************] 1 of 1 downloaded
Date Open High Low Close Volume
0 2007-10-01 45.558601 46.860199 45.233200 45.558601 16490774
1 2007-10-02 45.558601 46.372101 44.907700 45.151798 10906577
2 2007-10-03 45.151798 45.883999 43.524700 44.419601 17748233
3 2007-10-04 43.931499 43.931499 41.409500 41.979000 22471999
4 2007-10-05 41.816200 43.036598 41.490799 42.792500 18974962
5 2007-10-08 43.117901 43.768799 42.711201 43.524700 9772038
6 2007-10-09 43.117901 43.199299 41.653500 43.199299 8877189
7 2007-10-11 43.199299 46.209400 43.199299 46.209400 38372764
8 2007-10-12 46.209400 47.917900 45.151798 45.151798 25902660
9 2007-10-15 45.558601 46.778900 44.500900 45.151798 12476249
10 2007-10-16 44.419601 44.826401 43.850101 44.175499 10468987
11 2007-10-17 43.931499 44.338200 42.873901 43.850101 10294442
12 2007-10-18 43.850101 44.744999 43.117901 44.338200 7405852
13 2007-10-19 44.338200 44.744999 43.850101 44.012798 4603306
14 2007-10-22 42.304401 42.467098 41.490799 42.223000 11138894
15 2007-10-23 42.223000 42.711201 41.979000 42.385700 8129844
16 2007-10-24 42.711201 43.850101 41.897598 41.897598 10767679
17 2007-10-25 42.385700 43.036598 41.897598 41.897598 7598835
18 2007-10-26 42.304401 43.524700 42.223000 43.524700 11097101
19 2007-10-29 43.768799 44.744999 43.117901 44.744999 11185603
20 2007-10-30 44.582298 44.582298 43.605999 43.687401 5092522
21 2007-10-31 43.687401 43.768799 42.060299 42.629799 8389202
22 2007-11-01 43.280602 43.443298 40.514599 40.921299 12767567
23 2007-11-02 40.270500 40.270500 38.968800 39.050201 16188394
24 2007-11-05 38.684101 38.684101 38.236599 38.562099 15356235
25 2007-11-06 39.457001 39.863701 38.765499 39.457001 14665432
26 2007-11-07 40.270500 40.473900 39.619701 39.945099 11753487
27 2007-11-08 39.212898 39.212898 38.318001 38.846802 7270642
28 2007-11-09 38.846802 39.538300 37.870602 39.538300 9424178
29 2007-11-12 38.236599 38.562099 36.772301 37.016300 10525529
... ... ... ... ... ... ...
2442 2017-08-21 27.200001 27.350000 27.049999 27.250000 1832333
2443 2017-08-22 27.299999 27.400000 27.250000 27.299999 1246889
2444 2017-08-23 27.400000 27.400000 27.100000 27.250000 1961836
2445 2017-08-24 27.200001 27.450001 27.150000 27.450001 1893695
2446 2017-08-25 27.500000 27.549999 27.350000 27.350000 2735921
2447 2017-08-28 27.450001 27.450001 27.350000 27.400000 2451080
2448 2017-08-29 27.400000 27.400000 27.250000 27.400000 3203620
2449 2017-08-30 26.600000 27.000000 26.600000 26.900000 3838522
2450 2017-08-31 27.000000 27.350000 27.000000 27.350000 3695972
2451 2017-09-01 27.400000 27.600000 27.299999 27.450001 3451475
2452 2017-09-04 27.299999 27.450001 27.150000 27.450001 1711265
2453 2017-09-05 27.450001 27.600000 27.299999 27.450001 2508250
2454 2017-09-06 27.350000 27.350000 27.100000 27.200001 2100535
2455 2017-09-07 27.200001 27.200001 26.950001 27.100000 2700381
2456 2017-09-08 27.100000 27.400000 27.000000 27.299999 2028684
2457 2017-09-11 27.299999 27.350000 27.100000 27.200001 1863056
2458 2017-09-12 27.250000 27.250000 27.049999 27.150000 1988872
2459 2017-09-13 27.100000 27.100000 26.950001 26.950001 1732912
2460 2017-09-14 26.799999 27.250000 26.799999 27.250000 1714303
2461 2017-09-15 27.250000 27.500000 27.000000 27.500000 3562428
2462 2017-09-18 27.500000 27.650000 27.299999 27.650000 3323904
2463 2017-09-19 27.700001 27.700001 27.450001 27.600000 2012329
2464 2017-09-20 27.299999 27.600000 27.250000 27.549999 1858452
2465 2017-09-21 27.500000 27.500000 27.200001 27.250000 1967469
2466 2017-09-22 27.200001 27.200001 26.950001 26.950001 2382746
2467 2017-09-25 26.950001 27.450001 26.850000 27.350000 2749546
2468 2017-09-26 27.400000 27.400000 27.049999 27.250000 1039137
2469 2017-09-27 27.049999 27.200001 27.000000 27.049999 1616491
2470 2017-09-28 27.049999 27.100000 26.650000 26.700001 4079153
2471 2017-09-29 26.700001 26.950001 26.650000 26.750000 1903258

[2472 rows x 6 columns]
C:\Python36\lib\site-packages\pandas\io\excel.py:784: DeprecationWarning: Call to deprecated function remove_sheet (Use wb.remove(worksheet) or del wb[sheetname]).
self.book.remove_sheet(self.book.worksheets[0])
程式執行時間 = 5秒

如果擷取失敗會出現下列訊息 :

D:\Python\test\E_14_1>python E_14_1.py
[*********************100%***********************] 1 of 1 downloaded
zero-size array to reduction operation maximum which has no identity
Traceback (most recent call last):
File "E_14_1.py", line 33, in <module>
df = main(stkno,start,end) #呼叫主程式
File "E_14_1.py", line 21, in main
RowData =gf.getstock(True)
File "D:\Python\test\E_14_1\ProgramTrade\class_GetYahooFinance.py", line 54, in getstock
if len(Data) != 0: #有取得資料才進行轉換
UnboundLocalError: local variable 'Data' referenced before assignment

範例程式 E_14_1.py 將擷取網頁與儲存等功能寫成 GetYahooFinance.py 類別, 然後在
E_14_1.py 中建立物件來抓取網頁資料, 這使得程式閱讀起來很彆扭. 事實上此程式是利用第三方模組 fix_yahoo_finance 與 pandas_datareader 來抓資料, 垂回 Pandas 的 DataFrame 物件.

我將其中的核心部分改寫成函數 get_yahoo_twstock(), 如下列範例所示 :

import datetime
import pandas as pd
import fix_yahoo_finance as yf
from pandas_datareader import data as pdr

def get_yahoo_twstock(stock_no, start_date, end_date):
start=datetime.datetime.strptime(start_date,'%Y%m%d')
end=datetime.datetime.strptime(end_date,'%Y%m%d')
yf.pdr_override()
df=pdr.get_data_yahoo(stock_no + '.tw', start, end)
del df['Adj Close']
df=df.reset_index()
return df

stock_no='0050'
start_date='20170101'
end_date='20181022'
data=get_yahoo_twstock(stock_no, start_date, end_date)
print(data)
print(type(data))

注意, get_yahoo_twstock() 的三個參數都是字串, 起訖日期在函數裡面要用 datetime.datetime.strptime() 將字串轉成 datetime.datetime 物件.

執行結果如下 :

>>> %Run test.py

[ 0% ]
[*********************100%***********************] 1 of 1 downloaded
Date Open High Low Close Volume
0 2018-10-01 86.900002 87.400002 86.900002 87.349998 5912234
1 2018-10-02 87.250000 87.250000 86.000000 86.050003 5434332
2 2018-10-03 86.050003 86.300003 85.800003 85.949997 4369690
3 2018-10-04 85.699997 85.699997 84.800003 84.900002 9736968
4 2018-10-05 84.500000 84.500000 83.000000 83.449997 26744096
5 2018-10-08 82.949997 83.400002 82.500000 83.000000 46512204
6 2018-10-09 83.050003 83.400002 82.800003 83.250000 20530897
7 2018-10-11 80.150002 80.150002 77.349998 77.400002 68551624
<class 'pandas.core.frame.DataFrame'>

可見它沒辦法抓到今天為止的歷史資料, 只能到 11 天前左右, 而且有時候會執行失敗, 但這樣總比 Google Finance 完全不能下載歷史資料好吧! 就是沒辦法抓到今天為止的歷史資料有點可惜, 只能用在回測.

購買小米手環 3

因我的小米手環 2 螢幕變暗, 只有在黑暗時才能看清, 燈光亮的地方有帶跟沒帶是一樣的. 參考 :

# 小米手環 2 亮度變暗問題

剛好同事與清潔公司打掃的阿桑也要買,找到露天一個三件免運的賣家, 比官網多送一個錶帶 + 2 個保護貼 :

# 【送5大好禮台灣公司貨】小米手環3 繁體版本運動智慧型手錶小米米家智慧手錶智慧手環生日 $839

839*3=2517 元算整數 2510 元.

訂閱：文章 ( Atom )

小狐狸事務所

2018年10月31日星期三

購買旺德二代口譯雙向翻譯機

成敗之鑑

2018年10月30日星期二

南山投資型保單贖回與組合變更

2018年10月29日星期一

Python 學習筆記 : pexpect 模組測試

2018年10月28日星期日

2018 年第 43 周記事

2018年10月27日星期六

大學多元入學說明會

2018年10月26日星期五

Python 學習筆記 : SSH 模組 paramiko 測試

2018年10月25日星期四

Python 學習筆記 : PortablePython 安裝模組的方法

2018年10月23日星期二

Python Fintech 學習筆記 : 用 twder 模組擷取台銀外匯報價

購買創見 64GB SD 卡

清朝影像 China Qing Dynasty film

2018年10月22日星期一

Python Fintech 學習筆記 : 從 Yahoo Finance 擷取台股成交資料

購買小米手環 3

文章標籤

常用連結

2018年10月31日 星期三

2018年10月30日 星期二

2018年10月29日 星期一

2018年10月28日 星期日

2018年10月27日 星期六

2018年10月26日 星期五

2018年10月25日 星期四

2018年10月23日 星期二

2018年10月22日 星期一

2018年10月31日星期三

2018年10月30日星期二

2018年10月29日星期一

2018年10月28日星期日

2018年10月27日星期六

2018年10月26日星期五

2018年10月25日星期四

2018年10月23日星期二

2018年10月22日星期一