How to Generate N random numbers in Python 3 between 0 to infinity
Question:
How do I generate n random numbers in python 3? n is a to be determined variable. preferably natural numbers (integers > 0),
All answers I’ve found take random integers from a range, however I don’t want to generate numbers from a range. (unless the range is 0 to infinity)
Answers:
To paraphrase Wittgenstein, the limits of your machine is the limits of your language. i.e. There is no such thing as infinity in computers/computation world. However, regarding the maximum supported size of data structures you can use sys.maxsize (sys.maxint in python 2) to get that limit which for example could be used as the maximum list index or string length etc. You could also pass it to random.randint function in order to get an arbitrary very large random integer but still you may be able to increase that threshold based on your machine’s processing power.
>>> import sys
>>> sys.maxsize
9223372036854775807
>>> random.randint(0,sys.maxsize)
7512061515276834201
And for generating multiple random numbers you can use a list comprehension like following:
>>> N = 10
>>> [random.randint(0,sys.maxsize) for _ in range(N)]
[3275729488497352533, 7487884953907275260, 36555221619119354, 1813061054215861082, 619640952660975257, 9041692448390670491, 5863449945569266108, 8061742194513906273, 1435436865777681895, 8761466112930659544]
For more info about the difference of sys.maxint and sys.maxsize in python 2.X and 3.X:
The sys.maxint constant was removed, since there is no longer a
limit to the value of integers. However, sys.maxsize can be used as an
integer larger than any practical list or string index. It conforms to
the implementation’s “natural” integer size and is typically the same
as sys.maxint in previous releases on the same platform (assuming the
same build options).
I think you probably need to rethink what it is you’re trying to do with the random number you want. In particular, what distribution are you sampling the number from?
If you want your random numbers uniformly distributed (equal probability of each number being chosen), you can’t: you’d need an infinite amount of memory (or time, or both).
Of course, if you allow for non-uniform distributions, here are some random numbers between 1 and (roughly) the largest float my system allows, but there are gaps due to the way that such numbers are represented. And you may feel that the probability of “large” numbers being selected falls away rather quicker than you’d like…
In [254]: [int(1./random.random()) for i in range(10)]
Out[254]: [1, 1, 2, 1, 1, 117, 1, 3, 2, 6]
Here we have a memory limitation, so we can get the random numbers to the maximum a system can reach. Just place the n-digit numbers you want in the condition, and you can get the desired result. As an example, I tried for 6-digit random numbers. One can try as per the requirements. Hope this solves your question to an extent.
import sys
from random import *
for i in range(sys.maxsize):
print(randint(0,9),randint(0,9),randint(0,9),randint(0,9),randint(0,9),randint(0,9),sep='')
How do I generate n random numbers in python 3? n is a to be determined variable. preferably natural numbers (integers > 0),
All answers I’ve found take random integers from a range, however I don’t want to generate numbers from a range. (unless the range is 0 to infinity)
To paraphrase Wittgenstein, the limits of your machine is the limits of your language. i.e. There is no such thing as infinity in computers/computation world. However, regarding the maximum supported size of data structures you can use sys.maxsize (sys.maxint in python 2) to get that limit which for example could be used as the maximum list index or string length etc. You could also pass it to random.randint function in order to get an arbitrary very large random integer but still you may be able to increase that threshold based on your machine’s processing power.
>>> import sys
>>> sys.maxsize
9223372036854775807
>>> random.randint(0,sys.maxsize)
7512061515276834201
And for generating multiple random numbers you can use a list comprehension like following:
>>> N = 10
>>> [random.randint(0,sys.maxsize) for _ in range(N)]
[3275729488497352533, 7487884953907275260, 36555221619119354, 1813061054215861082, 619640952660975257, 9041692448390670491, 5863449945569266108, 8061742194513906273, 1435436865777681895, 8761466112930659544]
For more info about the difference of sys.maxint and sys.maxsize in python 2.X and 3.X:
The
sys.maxintconstant was removed, since there is no longer a
limit to the value of integers. However,sys.maxsizecan be used as an
integer larger than any practical list or string index. It conforms to
the implementation’s “natural” integer size and is typically the same
assys.maxintin previous releases on the same platform (assuming the
same build options).
I think you probably need to rethink what it is you’re trying to do with the random number you want. In particular, what distribution are you sampling the number from?
If you want your random numbers uniformly distributed (equal probability of each number being chosen), you can’t: you’d need an infinite amount of memory (or time, or both).
Of course, if you allow for non-uniform distributions, here are some random numbers between 1 and (roughly) the largest float my system allows, but there are gaps due to the way that such numbers are represented. And you may feel that the probability of “large” numbers being selected falls away rather quicker than you’d like…
In [254]: [int(1./random.random()) for i in range(10)]
Out[254]: [1, 1, 2, 1, 1, 117, 1, 3, 2, 6]
Here we have a memory limitation, so we can get the random numbers to the maximum a system can reach. Just place the n-digit numbers you want in the condition, and you can get the desired result. As an example, I tried for 6-digit random numbers. One can try as per the requirements. Hope this solves your question to an extent.
import sys
from random import *
for i in range(sys.maxsize):
print(randint(0,9),randint(0,9),randint(0,9),randint(0,9),randint(0,9),randint(0,9),sep='')