The so-called thousands form of numbers, that is, starting from the single digit, add a comma between every three digits. For example "10,000". In response to this requirement, I initially wrote a function like this:
Method 1 is relatively clear and easy to understand, and has been used in the project for some time. But my intuition tells me that its performance is not good.
Method 2 - string version of method 1
Method 3 - Loop to match the last three numbers
Method 3 is a completely different algorithm. It loops through regular expressions to match the three numbers at the end. Each time it matches, the comma and the matched content are inserted into the beginning of the result string, and then the matching target (num) Assign the value to the content that has not yet been matched (RegExp.leftContext). Also, note:
1. If the number of digits is a multiple of 3, the last matched content must be three digits, but there is no need to add commas before the first three digits;
2. If the number of digits in the number is not a multiple of 3, then there will definitely be 1 or 2 numbers left in the num variable at the end. After the loop, the remaining numbers should be inserted into the beginning of the result string.
Although method three reduces the number of loops (processing three characters in one loop), it increases consumption to a certain extent due to the use of regular expressions.
Method 4 - String version of method 3
In fact, the function of intercepting the last three characters can be achieved through the slice, substr or substring method of the string type. This way you avoid using regular expressions.
Method Five - Grouping and Merging Method
First complement the number of digits to a multiple of 3, use regular expressions to cut it into groups of three digits, then add commas through the join method, and finally remove the complemented 0s.
Method Six - The Lazy Man's Method
Test results
数字 | 执行5000次消耗的时间(ms) | |||||
---|---|---|---|---|---|---|
方法一 | 方法二 | 方法三 | 方法四 | 方法五 | 方法六 | |
1 | 4 | 1 | 3 | 1 | 14 | 2 |
10 | 14 | 1 | 3 | 0 | 7 | 2 |
100 | 12 | 1 | 2 | 4 | 5 | 3 |
1000 | 13 | 2 | 3 | 2 | 9 | 5 |
10000 | 21 | 4 | 3 | 1 | 6 | 3 |
100000 | 21 | 3 | 2 | 1 | 5 | 6 |
The strong comparison between Method 1 and Method 2 shows that the efficiency of string operations is much higher than that of array operations; the test results of Method 6 tell us that the length of the code has nothing to do with the performance. Method 4 has the best overall performance (but why the performance is reduced when num is 100, I really don’t understand). The main reason is:
1. Comparing methods one and two, each operation uses 3 characters instead of 1 character to reduce the number of loops;
2. Compared with methods three, five and six, regular expressions are not used, which reduces consumption.
Finally, I chose method four as the final optimization solution. If readers have better implementation methods or suggestions for improvement, you can leave comments.