金融計算程式運用(一)【3】

while loop
- break與continue
if-elif-else判斷式
for loop
Iterations與Comprehension
產生器Generator
bool運算式判斷

📖研習進度

`while` loop

while 條件式:
    主程式區塊
else:               # 非必須
    後置程式區塊      # 非必須

條件式：布林運算式，其結果為True或是Falese
只要條件式為True，主程式區塊就會反覆執行
當條件式為False時，while迴圈會執行後置程式區塊，然後終止

n = 9
r = 1
while n > 0:
  r = r * n
  n = n - 1
else:
  print("後置程式區塊執行完畢，", "且 n =", n, "。")

## 後置程式區塊執行完畢， 且 n = 0 。

x = 'NCCU'
while x:
    print(x, end = '\n')
    x = x[1:]

## NCCU
## CCU
## CU
## U

a = 0; b = 10
while a < b: # One way to code counter loops
    print(a, end=' ')
    a += 1

## 0 1 2 3 4 5 6 7 8 9

break與continue

break與continue敘述可放至while loop之中
如執行break，則立即終止while loop，且不執行後置程式區塊。因為當break中斷while loop時，while條件式仍為True
如執行continue，則會跳過continue後面的程式碼，回到while條件式繼續執行下一個loop

`if-elif-else`判斷式

if 條件式1:
    程式區塊1
elif 條件式2:
    程式區塊2
elif 條件式3:
    程式區塊3
.....    
.....
elif 條件式(n-1):
    程式區塊(n-1)
else:
    程式區塊n

條件式1為True，則會執行程式區塊1；否則，條件式2為True，則會執行程式區塊2，依此類推，直到找到一個條件式為True為止。
若沒有條件式為True時，則會執行else子句的程式區塊n
視使用情況，elif與else子句非必須，可省略。

n = 111
if n > 100:
  result = "success"
else:
  result = "failed"

print(result)

## success

上面程式碼可改寫成單行if條件運算式

result2 = "success" if n >100 else "failed"
print(result2)

## success

if子句後面的程式區塊是必要的。故做程式測試時，可使用pass敘述來佔位以滿足要求

x = 10
if x < 5:
  pass
else:
  x = 5

print(x)

## 5

choice = "ham"

if choice == "spam":
  print(1.25)
elif choice == "ham":
  print(1.99)
elif choice == "eggs":
  print(0.99)
elif choice == "bacon":
  print(1.10)
else:
  print("Bad choice")

## 1.99

choice = "ham"

print({"spam":   1.25,
        "ham":   1.99,
        "eggs":  0.99,
        "bacon": 1.1}[choice])

## 1.99

branch = { "spam": 1.25,
            "ham": 1.99,
           "eggs": 0.99,
          "bacon": 1.1}
branch.get("ham", "Bad choice")

## 1.99

branch.get("HAM", "Bad choice")

## 'Bad choice'

choice = "HAM"
try:
  print(branch[choice])
except KeyError:
  print("Bad choice")

## Bad choice

if choice in branch:
  print(branch[choice])
else:
  print("Bad choice")

## Bad choice

`for` loop

Python的for loop不需要指定索引，而是直接對可迭代物件的元素逐一取出來做處理
可迭代物件包含：list, tuple, set, str, generator, enumerate()等

for item in 可迭代物件:
    主體程式區塊
else:
    後置程式區塊

nums = [60, 70, 200, 80, 90]
for n in nums:
    print(n)
    if n > 100:
        print("There is a number bigger than 100")
        break
else:
    print("Not found!")

## 60
## 70
## 200
## There is a number bigger than 100

`range()`

雖然for loop的運行並不需要索引，但有時仍需要使用索引來進行訪問

x = [1, 2, 4, -7, 19, -4, 7]
for i in range(len(x)):
  if x[i] < 0:
    print("找到負數",x[i], "，其索引值為", i)

## 找到負數 -7 ，其索引值為 3
## 找到負數 -4 ，其索引值為 5

range(1, 11)

## range(1, 11)

type(range(1, 11))

## <class 'range'>

list(range(1, 11))

## [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]

list(range(10))

## [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]

list(range(10, 1))

## []

list(range(10, 1, -1))

## [10, 9, 8, 7, 6, 5, 4, 3, 2]

tuple unpacking

somelist = [(1, 2), (3, 7), (9, 5), (10, 4)]
result = 0
for item in somelist:
  result = result + (item[0] * item[1])
  print(result)

## 2
## 23
## 68
## 108

`enumerate()`

x = ["a", "b", "x"]
enumerate(x)

## <enumerate object at 0x7fd455cb81c0>

list(enumerate(x))

## [(0, 'a'), (1, 'b'), (2, 'x')]

x = [1, 3, -1, 4, 5, -9, 7]
for i, n in enumerate(x):
  if n < 0:
    print("找到負數，", "其索引值為", i)

## 找到負數， 其索引值為 2
## 找到負數， 其索引值為 5

`zip()`

可將兩個可迭代的物件結合在一起

L1 = [1,2,3,4]
L2 = [5,6,7,8]
zip(L1, L2)

## <zip object at 0x7fd455cb9700>

list(zip(L1, L2))

## [(1, 5), (2, 6), (3, 7), (4, 8)]

for (x, y) in zip(L1, L2):
    print(x, "+" , y, '-->', x+y)

## 1 + 5 --> 6
## 2 + 6 --> 8
## 3 + 7 --> 10
## 4 + 8 --> 12

T1, T2, T3 = (1,2,3), (4,5,6), (7,8,9)
T3

## (7, 8, 9)

list(zip(T1, T2, T3))

## [(1, 4, 7), (2, 5, 8), (3, 6, 9)]

S1 = 'abc'
S2 = 'xyz123'
list(zip(S1, S2))   # # Truncates at len(shortest)

## [('a', 'x'), ('b', 'y'), ('c', 'z')]

Iterations與Comprehension

Python針對常見的『循環』另外提供更方便也更有效率的觀念與工具：
- Iteration Protocol
- Iterable object :
  An object is considered iterable if it is either a physically stored sequence, or an object that produces one result at a time in the context of an iteration tool like a for loop.
- List Comprehensions (列表生成、列表推導)
Iterable object (可迭代物件) ==> __ iter __
Iterator object (迭代器物件) ==> __ next __

L = [1, 2, 3]
I = iter(L)      # Obtain an iterator object from an iterable
I.__next__()

## 1

I.__next__()

## 2

I.__next__()
# I.__next__()
# StopIteration: 
# 
# Detailed traceback: 
#   File "<string>", line 1, in <module>

## 3

L = [1, 2, 3]
iter(L) is L

# L.__next__()
# AttributeError: 'list' object has no attribute '__next__'

## False

I = iter(L)
I.__next__()

## 1

next(I)            # Same as I.__next__()

## 2

Manual iteration

L = [1, 2, 3]
for X in L:                        # Automatic iteration
    print(X ** 2, end = ' ')       # Obtains iter, calls __next__, catches exceptions

## 1 4 9

L = [1, 2, 3]
I = iter(L)                        # Manual iteration: what for loops usually do
while True:
    try:                           # try statement catches exceptions
        X = next(I)
    except StopIteration:
        break
    print(X ** 2, end=' ')

## 1 4 9

D = {'a':1, 'b':2, 'c':3}
for key in D.keys():
    print(key, D[key])

## a 1
## b 2
## c 3

D = {'a':1, 'b':2, 'c':3}
I = iter(D)
I.__next__()

## 'a'

next(I)

## 'b'

next(I)
# next(I)
# StopIteration: 
# 
# Detailed traceback: 
#   File "<string>", line 1, in <module>

## 'c'

list comprehensive

list comprehensive (列表推導) 可將⼀個for迴圈 (將list中的元素取出修改) 組成述句，壓縮為⼀⾏簡短易讀程式碼的簡單⽅法
一般來說，list comprehensive執行速度會較for loop快(兩倍)

L = [1, 2, 3, 4, 5]
for i in range(len(L)):
    L[i] += 10
    
L

## [11, 12, 13, 14, 15]

L = [1, 2, 3, 4, 5]
L = [x + 10 for x in L]
L

## [11, 12, 13, 14, 15]

L = [1, 2, 3, 4, 5]
L = [x ** 2 for x in L if x % 2 == 0]
L

## [4, 16]

res = []
for x in ['2020', '2021']:
    for y in ['/一月', '/二月', '/三月']:
        res.append(x + y)
res

## ['2020/一月', '2020/二月', '2020/三月', '2021/一月', '2021/二月', '2021/三月']

res = [x + y for x in ['2020', '2021'] for y in ['/一月', '/二月', '/三月']]
res

## ['2020/一月', '2020/二月', '2020/三月', '2021/一月', '2021/二月', '2021/三月']

dict comprehensive

new_dict = { expr1: expr2 for variable in list if condition }

x = [1, 2, 3, 4]
x_squared_dict = {item: item * item for item in x}
x_squared_dict

## {1: 1, 2: 4, 3: 9, 4: 16}

Multiple Versus Single Pass Iterators

range 支援len與索引取值(indexing)：

R = range(5)
len(R)

## 5

R[0]

## 0

range 支援 Multiple Iterators：

R = range(3)          # range allows multiple iterators

# next(R)
# TypeError: 'range' object is not an iterator

I1 = iter(R)
next(I1)

## 0

next(I1)

## 1

I2 = iter(R)
next(I2)

## 0

next(I2)

## 1

在Python 3.X中，zip , map 則『不』支援Multiple Iterators，為 Single Iterator:

Z = zip((1, 2, 3), (10, 20, 30))
I1 = iter(Z)
I2 = iter(Z)

next(I1)

## (1, 10)

next(I1)

## (2, 20)

next(I2)

## (3, 30)

M = map(abs, (-1, 0, 1))
I1 = iter(M)
I2 = iter(M)
print(next(I1), next(I1), next(I1))

# next(I2)
# StopIteration:

## 1 0 1

R = range(3)
I1, I2 = iter(R), iter(R)
[next(I1), next(I1), next(I1)]

## [0, 1, 2]

next(I2)

## 0

dictionary view iterables

D = {'a': 1, 'b': 2, 'c': 3}
D

## {'a': 1, 'b': 2, 'c': 3}

K = D.keys()
K

# next(K)         # K are not iterators themselves
# TypeError: 'dict_keys' object is not an iterator

## dict_keys(['a', 'b', 'c'])

I = iter(K)
next(I)

## 'a'

next(I)

## 'b'

for k in D.keys(): print(k, end=' ')

## a b c

產生器Generator

產生器(Generator)的語法類似list comprehension，差別只在於使用()替代[]
可透過for loop來存取
使用產生器可不需立即在記憶體中儲存全部資料，可處理大型數據資料

x = [1, 2, 3, 4]
x_square = (item * item for item in x)
type(x_square)

## <class 'generator'>

for square in x_square:
  print(square, end=" ")

## 1 4 9 16

`bool`運算式判斷

數字0, 0.0與0 + 0j均為False，其他數字皆為True
空字串""為False，其他字串皆為True
空list[],空tuple()與空字典{}皆為False
None為False
Short-circuit Evaluation：and與or並不會回傳運算後的布林值，而是會回傳物件。


[2] and [3, 4]

## [3, 4]

[] and [3, 4]

## []

[2] or [3, 4]

## [2]

[] or [3, 4]

## [3, 4]

x = []
if x and myfun(): 
  pass

x = 0
x <= 0 and print("x <= 0")

## x <= 0

x and 1/x
# 1/x

## 0

x and 1/x   # 當x為0時，則1/x不會執行

## 0

2 and 3, 3 and 2

## (3, 2)

[] and {}

## []

3 and []

## []

2 or 3

## 2

3 or 2

## 3

[] or 3

## 3

[] or {}

## {}

X = "A" and '' and "C" and None
X

## ''

bool其他範例

['f', 't'][bool('')]

## 'f'

['f', 't'][bool('spam')]

## 't'

金融計算程式運用(一)【3】

Chen Zheng-Hui

2021/4/28

`while` loop

break與continue

`if-elif-else`判斷式

`for` loop

`range()`

tuple unpacking

`enumerate()`

`zip()`

Iterations與Comprehension

list comprehensive

dict comprehensive

Multiple Versus Single Pass Iterators

dictionary view iterables

產生器Generator

`bool`運算式判斷

金融計算程式運用(一)【3】

Chen Zheng-Hui

2021/4/28

while loop

break與continue

if-elif-else判斷式

for loop

range()

tuple unpacking

enumerate()

zip()

Iterations與Comprehension

list comprehensive

dict comprehensive

Multiple Versus Single Pass Iterators

dictionary view iterables

產生器Generator

bool運算式判斷

`while` loop

`if-elif-else`判斷式

`for` loop

`range()`

`enumerate()`

`zip()`

`bool`運算式判斷