In PHP, is_nan() and is_null() are two commonly used functions. Their functions involve the judgment of data types, but their functions are different in terms of functions and uses. Understanding the difference between these two functions and knowing how to use them ingeniously is very helpful for processing data in data validation and null value judgment. This article will analyze these two functions in detail and explore how to effectively use is_nan() to handle data verification and null value judgment.
is_nan() is a way to check whether a value is "NaN" (Not-a-Number). NaN is a special value of the floating point type, representing a result that cannot be represented as a number, which usually occurs in mathematical operations, such as: 0/0 or square root operation applied to negative numbers.
$var = sqrt(-1); // turn outNaN
if (is_nan($var)) {
echo "This is aNaNvalue";
} else {
echo "This is notNaNvalue";
}
In the above code, sqrt(-1) returns a NaN value, and is_nan() is used to detect whether the variable is NaN.
is_nan() only works with floating point types (floats). If you use them on a non-numeric variable, the result returned is false .
is_null() is a function used to determine whether a variable is null . In PHP, null is a special data type that means a variable has no value or is not defined.
$var = null;
if (is_null($var)) {
echo "This is anullvalue";
} else {
echo "This is notnullvalue";
}
Here, is_null() is used to determine whether the variable $var is null . If the value of the variable is null , is_null() will return true , otherwise false .
is_null() will only detect whether the variable is null and cannot be used to determine an empty string, 0, false, or other value that is considered "empty".
From the above explanation, it can be seen that is_nan() and is_null() respectively detect two different situations:
is_nan() is used to check whether a value is a floating point type NaN (Not-a-Number), which is a special value that may appear in mathematical operations.
is_null() is used to check whether a value is null , that is, the variable has no value or is not initialized.
$var1 = sqrt(-1); // NaN
$var2 = null; // null
if (is_nan($var1)) {
echo "var1 yes NaN\n";
} else {
echo "var1 不yes NaN\n";
}
if (is_null($var2)) {
echo "var2 yes null\n";
} else {
echo "var2 不yes null\n";
}
Output:
var1 yes NaN
var2 yes null
In practical applications, we often encounter scenarios where we need to verify whether the data is empty or whether it is a valid numerical value. In this case, is_nan() can be used to verify whether the number is valid, while is_null() is used to check whether the variable is empty.
Suppose you have a variable from the user input, which may be a numeric value, a string, or a null . Before performing math operations, we want to first verify that the variable is a valid number and not null .
function validateInput($input) {
if (is_null($input)) {
return "The input cannot be empty";
}
if (is_nan($input)) {
return "输入value无效,不能yesNaN";
}
// 假设需要验证输入yes否为number
if (!is_numeric($input)) {
return "输入value必须yes一个number";
}
return "The input is valid";
}
$input1 = null;
$input2 = sqrt(-1); // NaN
$input3 = "abc"; // Non-digital
$input4 = 123; // number
echo validateInput($input1) . "\n"; // The input cannot be empty
echo validateInput($input2) . "\n"; // 输入value无效,不能yesNaN
echo validateInput($input3) . "\n"; // 输入value必须yes一个number
echo validateInput($input4) . "\n"; // The input is valid
is_null($input) is used to check whether the user input is empty.
is_nan($input) is used to check whether the user input is an invalid number (NaN).
is_numeric($input) is used to verify whether the user input is a number.
This method combines the characteristics of is_nan() and is_null() , helping us to handle various input situations more flexibly and ensure that data verification is more comprehensive and accurate.
In summary, is_nan() and is_null() are two very useful functions in PHP. They are used to determine whether a value is NaN and null respectively. Understanding their differences and using them in combination can greatly improve the flexibility and accuracy of data verification and null value judgment, and avoid unnecessary errors when processing data.