I have some experience using both of these libraries, so I will do my best to explain each of them:
Intl.NumberFormat and decimal.js are both libraries in JavaScript that can be used to format and manipulate numbers. However, while they are similar in some ways, they are very different in others.
Intl.NumberFormat is a built-in JavaScript library that provides localization support for number formatting, including decimal and grouping separators, decimal precision, and currency formatting. It is widely used to format numbers based on a user's language and region.
Decimal.js is a third-party library that provides arbitrary-precision decimal arithmetic for JavaScript. It allows for precise calculations with decimal numbers, which are often required in financial and scientific applications where rounding errors can have significant consequences.
Although Intl.NumberFormat can handle basic currency formatting, it may not be suitable for all use cases. For example, it may not handle more complex currency formatting requirements, such as rounding rules or multiple currencies in the same document. In such cases, decimal.js can provide more precise and flexible currency handling capabilities.
I hope this answered your question!
I agree to Promaster's answer, it's also worth noting that using the decimal.js library may have performance implications, as it is a third-party library that requires additional processing overhead compared to the built-in Intl.NumberFormat library. Therefore, you should consider the specific requirements of your application when deciding whether to use decimal.js or Intl.NumberFormat.
The main benefit of using the decimal.js library over Intl.NumberFormat is the ability to perform precise mathematical operations on decimal numbers. If your application requires this level of precision, then decimal.js may be a better choice. However, if your application only requires formatting numbers for display, then Intl.NumberFormat may be sufficient.
You can use Math.floor to remove floating after decimal:
var val = 11067.64120858936;
var result = Math.floor(val);
console.log(result); // 11067 discard value after decimal
You can use Math.ceil will give you round figure by next digit i.e. 1 increment in case of float number like given example it doesn't matter whether digit after decimal is greater than 5 or not:
var val = 11067.64120858936;
var result = Math.ceil(val);
console.log(result); // result 11068
You can use Math.round will give you fixed digit either by 1+ or 1- depends on value after decimal:
var val = 11067.64120858936;
var result = Math.round(val);
console.log(result); // result 11068 as there is 6 after decimal
To get specific digit after decimal you can try toFixed() method:
var val = 11067.64120858936;
var result = val.toFixed(2); // for two place digit after decimal
console.log(result); // result 11067.64
You can try this in your browser console.
You can also round this value:
Math.round(11067.64120858936)
Output : 11068
Well If you have other value '11067.44120858936' then result will be diffrent.
Math.round(11067.44120858936)
Output : 11067
https://github.com/Patashu/break_infinity.js
I made this library because decimal.js is very slow, both because it focused on arbitrary precision, and because its functions were not coded with performance in mind to begin with.
By relaxing the arbitrary precision requirement (mantissa is now just a javascript Number, rather than an array of strings, and exp and pow only guarantee about 9 decimal places of accuracy), compared to decimal.js, operations of break_infinity.js are anywhere from 50x to 1000x faster.
How fast is it in practice? Antimatter Dimensions swapped from decimal.js to break_infinity.js in its Eternity Update that came out today ( https://www.reddit.com/r/incremental_games/comments/7grvhl/antimatter_dimensions_eternity_update/ ), and in doing so, the time spent in scripts was reduced to 22% of what it used to be. Obviously if your incremental game is not as math-heavy as Antimatter Dimensions it won't benefit to the same extent, but performance is performance.
Like decimal.js, break_infinity.js handles numbers as large as 1e(9e15). Above that (if you even GET that far), you should use break_break_infinity.js instead, which goes up to 1e(1.79e308), though note that it hasn't been thoroughly tested yet, and obviously it will lose on performance compared to break_infinity.js since it uses a big-integer library for the exponent instead of just a Number.
If you find any bugs or wish to contribute, check out the issues on the github repository ( https://github.com/Patashu/break_infinity.js/issues ) or open a pull request (or message me on Reddit, I guess).
Generally no. There are some possible performance implications when a number doesn't fit in a 31b signed int.
A tour of V8: object representation explains
According to the spec, all numbers in JavaScript are 64-bit floating point doubles. We frequently work with integers though, so V8 represents numbers with 31-bit signed integers whenever possible (the low bit is always 0; this helps the garbage collector distinguish numbers from pointers). So objects with the fast small integers elements kind only contain this type of number. If we want to store a fractional number or a larger integer or a special value like -0, then we need to upgrade the array to fast doubles. This involves a potentially expensive copy-and-convert operation, but it doesn't happen often in practice. fast doubles objects are still pretty fast because all of the numbers are stored in an unboxed representation. If we want to store any other kind of value, e.g., a string or an object, we must upgrade to a general array of fast elements.
Does the amount of decimals in the numbers used (precision) affect performance especially in JavaScript? If it does, how?
No. The number type in JavaScript is a 64-bit floating-point value with base 2 and always has the same precision. The computer works on that data bit by bit and it doesn't matter whether that data represents something that looks simple to a human like 1.0 or something seemingly complicated like 123423.5645632. In fact, for base 2 floats, the 'human' values are just as 'hard', because 1.1 is truly represented by a much longer number (sth. like 1.10000000000000054). All this doesn't matter, because the computer truly operates on 64 ones and zeros. There are always some arcane exceptions in floating point, but those usually don't matter in practice.
How about saving numbers in MongoDB: Do precise numbers take more space than less precise ones?
Decimal numbers are stored as doubles (64bit), and it doesn't matter whether that is 1.0 or 1.1221234423. Again, the number of bits is constant for these data types.
The same is true for ints, but MongoDB has support for both 32- and 64-bit ints. So NumberLong is indeed larger than regular 32-bit ints and just as large as doubles.
» npm install decimal.js