Measure whether it is fast enough for your purposes, “randomness” might diminish the more you call it: os.urandom(250). It produces a binary string aka bytes. To avoid “long int too large to convert to float” error don’t use floats. If you need an integer with k random bits instead of a binary string: import random … Read more
Current computers have 32 or 64-bit registers, so doing calculations on bytes is very inefficient. Also, computers work in binary, so using a base that is a power of 2 is more efficient. They’ll use base 232 or 264 like Mysticial said. Each computer word will store a digit of the number and they work … Read more
As Nils Werner already mentioned, numpy’s native ctypes cannot save numbers that large, but python itself can since the int objects use an arbitrary length implementation. So what you can do is tell numpy not to convert the numbers to ctypes but use the python objects instead. This will be slower, but it will work. … Read more
Factorials get really big really fast (scroll down a little to see the list). Even a 64-bit number is only good up to 20!. So you have to do a little preprocessing before you start multiplying. The general idea is to factor the numerator and the denominator, and remove all of the common factors. Since … Read more
Consider System.Numerics.BigInteger.
As Livius points out in his comment, this is an issue with R (and in fact, most programming language), with how numbers are represented in binary. To work with extremely large/small floating point numbers, you can use the Rmpfr library: install.packages(“Rmpfr”) library(“Rmpfr”) x <- c(-2.5e+59, -5.6e+60) y <- mpfr(x, 6) # the second number is … Read more
You can use the NSDecimalNumber class from Cocoa. It is not infinite precision, but it can represent 38 decimal digits of precision, which may be enough for what you need.
As of .NET 4.0 you can use the System.Numerics.BigInteger class. See documentation here: http://msdn.microsoft.com/en-us/library/system.numerics.biginteger(v=vs.110).aspx Another alternative is the IntX class. IntX is an arbitrary precision integers library written in pure C# 2.0 with fast – O(N * log N) – multiplication/division algorithms implementation. It provides all the basic operations on integers like addition, multiplication, comparing, … Read more
It sounds like you’re looking for a way to enter Arbitrary Precision numbers. here are two libraries you could use: GMP and MAPM
Python supports a “bignum” integer type which can work with arbitrarily large numbers. In Python 2.5+, this type is called long and is separate from the int type, but the interpreter will automatically use whichever is more appropriate. In Python 3.0+, the int type has been dropped completely. That’s just an implementation detail, though — … Read more