9. 其他實用工具 Other Utilities¶

# 載入 timedelta 模組
from datetime import timedelta

delta = timedelta(
    days=50,
    seconds=27,
    microseconds=10,
    milliseconds=29000,
    minutes=5,
    hours=8,
    weeks=2
)
# Only days, seconds and microseconds are stored internally
delta

ten_years = timedelta(days=365) * 10
ten_years

ten_years.days // 365

# 載入 date 模組
from datetime import date

today = date.today()
today

today.replace(year=2022)

(today - ten_years).isoformat()

# 記得 timedelta 只有天數的概念，沒有年月的概念
date.today() - date(2020, 3, 16)

# 載入 datetime 模組
from datetime import datetime

# 現在的日期時間，返回 datetime 型別
t1 = datetime.now()
t1

# 轉成字串 str 型別
str(t1)

# 現在的日期時間，轉成指定格式的字串
t1.strftime('%m/%d/%Y %H:%M:%S')

# 從日期時間的字串轉成 datetime 型別
t2 = datetime.strptime('2020-10-28  15:10:00', '%Y-%m-%d %H:%M:%S')

# 比較兩個 datetime
if (t1 > t2):
    print('t1 比 t2 晚', t1 - t2)
else:
    print('t2 比 t1 晚', t2 - t1)

# time 模組也有 strftime 可以用來格式化時間字串
import time
time.strftime('%Y%m%d %H%M%S')

# 載入 pickle 物件也改成 context manager 的寫法
with open('record.pkl', 'rb') as pfile:
    record2 = pickle.load(pfile)

record2

# 準備要儲存成 JSON 檔的物件
card = {
    "image": {
        "Width":  600,
        "Height": 800,
        "Title":  "Portrait",
    },
    
    "person": {
        "firstName": "John",
        "lastName": "Doe",
        "isAlive": True,
        "age": 27,
        "phoneNumbers": [
            {
                "type": "home",
                "number": "212 555-1234"
            },
            {
                "type": "office",
                "number": "646 555-4567"
            }
        ],
        "spouse": None
    }
}

card

# 開啟.json檔案，將 JSON 編碼的物件載入轉成 Python 物件
with open('card.json', 'r') as jfile:
    card2 = json.load(jfile)

card2

# 產生 100 個隨機實數數列
Lr = [random.random() for x in range(100)]
print(Lr)

# 產生 100 個隨機整數數列
Li = [random.randint(1, 100) for x in range(100)]
print(Li)

# 從數列中隨機選取 10 個樣本，產生新的隨機數列
[x * y for x, y in zip(random.sample(Lr, 10), random.sample(Li, 10))]

# 內建函式的 sum() 在浮點數運算的精度不足
print(sum([.1, .1, .1, .1, .1, .1, .1, .1, .1, .1]))

# math 模組的 fsum() 可避免精度的誤差
print(math.fsum([.1, .1, .1, .1, .1, .1, .1, .1, .1, .1]))

# cosine 180 度
print('cosine(pi) =', math.cos(math.pi))

# sine 90 度
print('sine(pi/2) =', math.sin(math.radians(90)))

# 載入 math 模組裡要用到的函式
from math import sqrt

# 計算 N 維的歐幾里得距離
def EuclideanDist(p1, p2):
    return sqrt(sum((x1 - x2) ** 2 for x1, x2 in zip(p1, p2)))

m, n = (1, 3, 5, 7, 9), (2, 4, 6, 8, 10)
print('Euclidean distance between {}, {} = {}'.format(m, n, EuclideanDist(m, n)))

# 取得目前工作目錄
pwd = Path.cwd()
print('Current working directory: ', pwd)

# 列出目前工作目錄下所有的檔案及目錄
for f in pwd.iterdir():
    print(f.name)

# 建構 Path 物件可以用不同的表示法
file2remove = [Path(pwd, 'card.json'), Path(pwd / 'record.pkl')]

# 刪除之前建立的測試用檔案
for path in file2remove:
    if path.exists():
        path.unlink()
        print('File "{}"" {} removed.'.format(path.name, 'is not' if path.exists() else 'is'))

# 建立一個記錄檔案名字與副檔名對照的字典
{f.stem:f.suffix for f in pwd.iterdir() if f.is_file()}

# 列出目前工作目錄下所有副檔名是 .ipynb 的檔案
[f.name for f in pwd.glob('*.ipynb')]

# def 函式名稱(參數: 型別) -> 回傳型別
def jiume(who: str) -> str:
    return who + ' >.^ '

jiume('Mary')

def addmyself(myself: int) -> int:
    return myself + myself

addmyself(5)

from typing import Any

def triple(what: Any) -> Any:
    return what * 3

print(triple(jiume('Mary')))
print(triple(addmyself(5)))

from math import fsum

# dot_product() 函式接受兩個 list 當參數
def dot_product(vec1: list, vec2: list) -> float:
    return fsum(c1 * c2 for c1, c2 in zip(vec1, vec2))

# 型別提醒就只是提醒，傳兩個 tuple 還是可以正常運作
vector1, vector2 = (1, 2, 3), (4, 5, 6)
print('{} dot {} = {}'.format(vector1, vector2, dot_product(vector1, vector2)))

a = (1, 2, 3)
b = (3., 2., 1.)
print('distance between points', a, 'and', b, '=', distance3d(a, b))