Can PHP's php.ini Precision Setting Guarantee Accurate Two-Digit Monetary Calculations?

Linda Hamilton
Release: 2024-11-06 12:27:03
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 Can PHP's php.ini Precision Setting Guarantee Accurate Two-Digit Monetary Calculations?

Can PHP's php.ini Precision Workaround Address Floating Point Issues?

Floating point calculations can be imprecise due to binary representations of most fractions. The php.ini setting for precision allows you to specify the number of digits to which PHP calculates floating point values.

Reliability of the Workaround

Question 1: Can the workaround be relied upon for precise two-digit monetary calculations?

Answer 1: No. The php.ini precision setting does not guarantee accurate two-digit calculations, as precision length may increase during calculations.

Examples of Failure

Question 2: Can you provide an example where the workaround fails?

Example:

ini_set('precision', 8);
$a = 5.88; // cost per kg
$q = 2.49; // quantity purchased (2.49 kg)
$b = $a * 0.01; // 10% discount on first kg
echo ($a * $q) - $b; // result not precisely two digits
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Best Php.ini.precision Value for Two-Digit Monetary Calculations

Question 3: What php.ini.precision value is suitable for two-digit monetary calculations?

Answer 3: Using php.ini precision for financial calculations is not recommended. Consider alternative solutions like bcmmath or number_format.

Simple Testing

Example Code:

ini_set('precision', 20); // set to 20
$a = 342349.23;
$b = 341765.07;

echo $a - $b, PHP_EOL;
echo floatval(round($a - $b, 2)), PHP_EOL;
echo number_format($a - $b, 2), PHP_EOL;
echo bcsub($a, $b, 2), PHP_EOL;
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Output:

584.15999999997438863
584.15999999999996817    // round is not reliable
584.16
584.15  // bcsub is more precise with precision=20
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Conclusion:

Reliance on the php.ini precision workaround is unreliable for precise two-digit calculations. Consider using bcmmath or number_format for accurate financial calculations.

Update

Question 1: Will the workaround fail for numbers between 0 and 999999.99?

Answer 1: A complete test is impractical due to the large number of combinations. However, a simple test with 0.19 0.16 ... 0.01 produces an unexpected result (1.0408341E-17) with precision set to 8, suggesting that the workaround is not fully reliable.

Question 2: How can we estimate when the workaround will fail?

Answer 2: While mathematical formulas exist, they can be complex and not always practical for determining failure points.

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