# coding=utf-8
from decimal import Decimal, getcontext

# 1.可以傳遞給Decimal整型或者字符串參數，但不能是浮點數據，因為浮點數據本身就不準確。
# 傳入浮點數 5.55
a = Decimal(5.55)
print('a = ', a)
a = a * 100
print('a = ', a)
# 傳入字符串 ‘5.55'
b = Decimal('5.55')*100
print('b = ', b)

>>> a =  5.54999999999999982236431605997495353221893310546875
>>> a =  554.9999999999999822364316060
>>> b =  555.00

# 2.要從浮點數據轉換為Decimal類型
c = Decimal.from_float(22.222)
print('c = ', c)

>>> c =  22.22200000000000130739863379858434200286865234375

# 3.getcontext().prec設置有效數字的個數。
# 通過設定有效數字，限定結果樣式
getcontext().prec = 4
x1 = Decimal(1) / Decimal(3)  # 結果為Decimal('0.3333')，四個有效數字
print('x1 = ', x1)
x2 = Decimal(100) / Decimal(3)
print('x2 = ', x2)
x3 = Decimal(700000)/Decimal(9)
print('x3 = ', x3)

>>> x1 =  0.3333
>>> x2 =  33.33
>>> x3 =  7.778E+4

# 注意：
# 如果prec的長度比數字的長度小的時候，*100得出的數就不對了
num = '88.8888'
f = Decimal(num)
print('f = ', f)
g = f * 100
print('g = ', g)
h = Decimal('999.999')
print('h = ', h)

>>> f =  88.8888
>>> g =  8889
>>> h =  999.999

# 4.四舍五入，保留幾位小數
d = Decimal('50.5679').quantize(Decimal('0.00'))
print('d = ', d)  # 結果為Decimal('50.57')，結果四舍五入保留了兩位小數

>>> d =  50.57

# 5.Decimal 結果轉化為string
e = str(Decimal('3.40').quantize(Decimal('0.0')))
print('e = ', e)

>>> e =  3.4

# 6.decimal模塊進行十進制數學計算
i = Decimal('4.20') + Decimal('2.10') + Decimal('6.30')
print('i = ', i)

>>> i =  12.60
# 當然精度提升的同時，肯定帶來的是性能的損失。在對數據要求特別精確的場合（例如財務結算），這些性能的損失是值得的。
# 但是如果是大規(guī)模的科學計算，就需要考慮運行效率了。畢竟原生的float比Decimal對象肯定是要快很多的。

ROUND_CEILING (towards Infinity),
ROUND_DOWN (towards zero),
ROUND_FLOOR (towards -Infinity),
ROUND_HALF_DOWN (to nearest with ties going towards zero),
ROUND_HALF_EVEN (to nearest with ties going to nearest even integer),
ROUND_HALF_UP (to nearest with ties going away from zero), or
ROUND_UP (away from zero).
ROUND_05UP (away from zero if last digit after rounding towards zero would have been 0 or 5; otherwise towards zero)

x = Decimal('-3.1415926535') + Decimal('-2.7182818285')
print x
print x.quantize(Decimal('1.0000'), ROUND_HALF_EVEN)
print x.quantize(Decimal('1.0000'), ROUND_HALF_DOWN)
print x.quantize(Decimal('1.0000'), ROUND_CEILING)
print x.quantize(Decimal('1.0000'), ROUND_FLOOR)
print x.quantize(Decimal('1.0000'), ROUND_UP)
print x.quantize(Decimal('1.0000'), ROUND_DOWN)

output:
-5.8598744820
-5.8599
-5.8599
-5.8598
-5.8599
-5.8599
-5.8598

https://www.cnblogs.com/piperck/p/5843253.html
https://blog.csdn.net/weixin_37989267/article/details/79473706