The Python decimal documentation explains decimal representation and rounding controls. The following is a general data processing design. Actual systems may also adopt other implementations suitable for precise calculations.
The original expression and the canonical value are saved at the same time
Simulating the quotation, "about two thousand yuan" and "2000.00 yuan" express different degrees of certainty. The system should retain the original sentence and record the value, unit, currency and pending confirmation status respectively. It cannot automatically delete the word "appropriate" and turn the estimate into an accurate commitment.
Calculation rules are predefined by the business
The decimal places, rounding timing and aggregation range need to be clear, and the model cannot be left to decide on its own every time. Calculations use deterministic procedures and check input types; converting values resulting from floating point errors to decimal does not necessarily restore the original intent.
Test bounds instead of just integer fields
Add negative numbers, zero values, different units, missing currencies, and examples that require rounding to check whether errors are returned. For formal business information, the responsible person still needs to check the original vouchers. This article does not constitute an accounting or tax conclusion, nor does it guarantee that any analytical results are inherently accurate.
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