Generate 'n' unique random numbers within a range [duplicate]
If you just need sampling without replacement:
>>> import random
>>> random.sample(range(1, 100), 3)
[77, 52, 45]
random.sample takes a population and a sample size k
and returns k
random members of the population.
If you have to control for the case where k
is larger than len(population)
, you need to be prepared to catch a ValueError
:
>>> try:
... random.sample(range(1, 2), 3)
... except ValueError:
... print('Sample size exceeded population size.')
...
Sample size exceeded population size
Generate the range of data first and then shuffle it like this
import random
data = range(numLow, numHigh)
random.shuffle(data)
print data
By doing this way, you will get all the numbers in the particular range but in a random order.
But you can use random.sample
to get the number of elements you need, from a range of numbers like this
print random.sample(range(numLow, numHigh), 3)
You could add to a set
until you reach n
:
setOfNumbers = set()
while len(setOfNumbers) < n:
setOfNumbers.add(random.randint(numLow, numHigh))
Be careful of having a smaller range than will fit in n
. It will loop forever, unable to find new numbers to insert up to n
You could use the random.sample
function from the standard library to select k elements from a population:
import random
random.sample(range(low, high), n)
In case of a rather large range of possible numbers, you could use itertools.islice
with an infinite random generator:
import itertools
import random
def random_gen(low, high):
while True:
yield random.randrange(low, high)
gen = random_gen(1, 100)
items = list(itertools.islice(gen, 10)) # Take first 10 random elements
After the question update it is now clear that you need n distinct (unique) numbers.
import itertools
import random
def random_gen(low, high):
while True:
yield random.randrange(low, high)
gen = random_gen(1, 100)
items = set()
# Try to add elem to set until set length is less than 10
for x in itertools.takewhile(lambda x: len(items) < 10, gen):
items.add(x)