問題描述

我在 Python 中有一個包含浮點數的變量(例如 num = 24654.123)，我想確定數字的精度和比例值(在 Oracle 意義上)，所以 123.45678應該給我 (8,5)，12.76 應該給我 (4,2)，等等.

I have a variable in Python containing a floating point number (e.g. num = 24654.123), and I'd like to determine the number's precision and scale values (in the Oracle sense), so 123.45678 should give me (8,5), 12.76 should give me (4,2), etc.

我首先考慮使用字符串表示(通過 str 或 repr)，但是對于大數來說這些都失敗了(雖然我現在明白這是浮點的限制表示這是這里的問題):

I was first thinking about using the string representation (via str or repr), but those fail for large numbers (although I understand now it's the limitations of floating point representation that's the issue here):

>>> num = 1234567890.0987654321
>>> str(num) = 1234567890.1
>>> repr(num) = 1234567890.0987654

下面的好點.我應該澄清一下.該數字已經是一個浮點數，并且正在通過 cx_Oracle 推送到數據庫.我試圖在 Python 中盡我所能來處理對于相應數據庫類型來說太大的浮點數，而不是執行 INSERT 和處理 Oracle 錯誤(因為我想處理字段中的數字，而不是記錄，在一次).我猜 map(len, repr(num).split('.')) 是最接近浮點數的精度和比例的?

Good points below. I should clarify. The number is already a float and is being pushed to a database via cx_Oracle. I'm trying to do the best I can in Python to handle floats that are too large for the corresponding database type short of executing the INSERT and handling Oracle errors (because I want to deal with the numbers a field, not a record, at a time). I guess map(len, repr(num).split('.')) is the closest I'll get to the precision and scale of the float?

推薦答案

獲取小數點左邊的位數很簡單:

Getting the number of digits to the left of the decimal point is easy:

int(log10(x))+1

小數點右邊的位數比較棘手，因為浮點值固有的不準確性.我還需要幾分鐘才能弄清楚這一點.

The number of digits to the right of the decimal point is trickier, because of the inherent inaccuracy of floating point values. I'll need a few more minutes to figure that one out.

基于這個原則，這里是完整的代碼.

Based on that principle, here's the complete code.

import math

def precision_and_scale(x):
    max_digits = 14
    int_part = int(abs(x))
    magnitude = 1 if int_part == 0 else int(math.log10(int_part)) + 1
    if magnitude >= max_digits:
        return (magnitude, 0)
    frac_part = abs(x) - int_part
    multiplier = 10 ** (max_digits - magnitude)
    frac_digits = multiplier + int(multiplier * frac_part + 0.5)
    while frac_digits % 10 == 0:
        frac_digits /= 10
    scale = int(math.log10(frac_digits))
    return (magnitude + scale, scale)

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