Develop Reference

How do I make the code shorter and more efficent?

import time
start_time = time.time()
a = [2]
inp = 2
while inp < 60000:
div = 2
inp += 1
while div <= (inp / 2 + 1):
prime = inp / div
if prime.is_integer() == True:
break
else:
if div >= (inp / 2):
a.append(str(inp))
break
else:
div += 1
print(a)
print(len(a))
print("Process finished --- %s seconds ---" % (time.time()-start_time))
I wrote my first own program to calculate every prime number between 0 and 60000. I am searching for tips how to format it better or improve it.

import math
n = 60000
primes = []
for k in range(2,n):
if k % 2 == 0 and k > 2:
pass
elif all(k % i for i in range(3, int(math.sqrt(k)) + 1, 2)):
print(k)
EDIT
Since even number are not prime except 2, i have modified the anwer again
import math
primes2 = [2]
for k in range(3,n,2):
if all(k % i for i in range(3, int(math.sqrt(k)) + 1, 2)):
primes2.append(k)
Or Liner (It will helps in perforamce as well)
from math import sqrt # Most efficient way to use external libraries
primes = [k for k in range(3,n+1,2) if all(k % i for i in range(3, int(sqrt(k)) + 1, 2))]
primes.insert(0, 2)
# To print
print(*[k for k in range(3,n+1,2) if all(k % i for i in range(3, int(sqrt(k)) + 1, 2))],sep='\n')

this is how i would have done it
def isPrime(n) :
if (n <= 1) :
return False
if (n <= 3) :
return True
if (n % 2 == 0 or n % 3 == 0) :
return False
i = 5
while(i * i <= n) :
if (n % i == 0 or n % (i + 2) == 0) :
return False
i = i + 6
return True
def printPrime(n):
for i in range(2, n + 1):
if isPrime(i):
print (i, end =" ")
n = 60000 <--- you can change n by any value you want
printPrime(n)

Having trouble getting Miller-Rabin primality test in Python

I have been trying to implement Miller-Rabin primality test in Python. Unfortunately there seems to be a problem on some prime numbers. Any help is appreciated.
Code:
def _isPrime(n):
if n % 2 == 0:
return False
a = [2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41]
s, d = _Apart(n) # turns it into 2^s x d
print(s, d)
basePrime = False
isPrime = True
for base in a:
if base >= n-2:
break
if isPrime == False and basePrime == False:
return False
witness = pow(base, d)
if (witness % n) == 1 or (witness % n) == (n-1):
basePrime = True
continue
else:
basePrime = False
for r in range(1, s):
witness = pow(base, pow(2, r) * d)
if (witness % n) != ( n - 1 ):
isPrime = False
return True
Test:
isPrime(17)
Expected:
True
Result:
False

I wrote a Miller Rabin test that is deterministic, no need for random numbers. This implementation is for python 3.7. In python 3.8, llinear_diophantinex can be replaced with pow(x, -1, y). Also i used gmpy2 as it's very fast, but you can just replace the gmpy2 statements with normal pow if you can't use that, and just remove the gmpy2.mpz() wrappers since those are just used to overload operators.
import gmpy2
sinn = 2110229697309202254897383305762150945330987087513434511395506048950594976569434432057019507105035289374307720719984431280856161609820548842778454256113246763860786119268583367543952735347969627478873317341364209555365064365565504232770227619462128918701942169785585423104678142850200975026619010035331023744330713985615650556129731348659986462960062760308034462660525448390420668021248422741300646552941285862310410598374242189448623917196191138254637812716211329113836605859918549332304189053950819346551095911511755911832183789503704294770046935064469435830299623205136625543859303686699678929069468518950480476841246805908501510754550017255944080874819287974625925494008373883250410775902993163965873632474224574883242826458163446781002284368017611606202344050570737818087202137703099075773680753707346415849787963446390136517016131227807076254668461445862154978026041507116570585784569893773262639243954090283224759975513502582494002154146757110676408972377044584495342170277522887809749465855954126593100747444378301829661568735873345178089061677917127496915956539418931430313218084338374827152407795095072639044306222222695685778907958272820576498682506540189586657786292950574081739269257159839589987847266550007783514316481286222515710538845836151864127815058116482680058626451349913138908040817800742009650450811565324184631847563730941344941348929727603343965091116543702880556850922077216848669966268219928808236163268726995495688157209747596437162960244538054993785127947211290438554095851924381172697827312534174244295581184309147813790451951453564726742200569263225639113681905176376701339808868274637448606821696026703034737428319530072483125495383057919894902076566679023694181381398377144302767983385253577700652358431959604517728821603076762965129019244904679015099154368058005173028200266632883632953133017055122970338782493475762548347258351148037427739052271661340801912188203749647918379812483260399614599813650518046331670764766419886619324840045611486524123102046413946014624119568013100078163986683199814025915420877588778260860713148420321896163326473203441644820182490479899368048072263481024886708136521847014624735722333931331098969321911443978386868675912141648200500219168920887757573018380579532261231821382787339600631297820996466930957801607217549420247654458172818940238337170577825003408756362106088558651381993611741503374243481167926898332728164900189941804942580426055589622673679047058619682175301326905577843405270203660160407401675700528981573327582844330828861745574031416926871562443652858767649050943181353635950301154441954046214987718582670685455252774874198771086552440702483933126644594300464549471422237478151976561680719370424626162642534252062987911763456822609569209140676822858933588602318066530038691463577379331113471591913447226829868760176810195567325921301390329055242213842898142597360121925124635965685365925901913816717677946911762631634793638450106377437599347740569467683272089859392249351406815344105961234868327316964137925419770514177021722214309784062017826024217906664090209434553785436385765927274067126192143337589109608949427467825999057058702263715338956534536892852849984934736685814891286495169007648767081688963426768409476169071460997622740467533572971356017575900999100928776382541052696124463195981888715845688808970103527288822088031150716134784735332326775370417950625124642515148342694377095213470544739900830244879573205335578256682901821773047071352497997708791157012233232529777513203024818391621220967964874173106990772425289900446640237659116713251437567138729645677868024033209183367071421651937808005637679844370347367922676824239404492688418047080583797577102267329067247758368597488680401670673861120323439239792549053895366970423259196919428554146265587250617656401028722578111927104663315250291888502226235291264834968061065817079511872899991276288365723969841290984981957389126603952133124328219936785870274843554107325931034103072894378438818494802517594594270034007832922248742746517915210656205746338575621725899098414488628833412591266637224507533934158213117522503993423240638893845121918647788013
def llinear_diophantinex(a, b, divmodx=1, x=1, y=0, offset=0, withstats=False, pow_mod_p2=False):
origa, origb = a, gmpy2.mpz(b)
r=a
q = a//b
prevq=1
if a == 1:
return 1
if withstats == True:
print(f"a = {a}, b = {b}, q = {q}, r = {r}")
while r != 0:
prevr = r
a,r,b = b, b, r
q,r = divmod(a,b)
x, y = y, x - q * y
if withstats == True:
print(f"a = {a}, b = {b}, q = {q}, r = {r}, x = {x}, y = {y}")
y = gmpy2.mpz(1 - origb*x // origa - 1)
if withstats == True:
print(f"x = {x}, y = {y}")
x,y=y,x
modx = (-abs(x)*divmodx)%origb
if withstats == True:
print(f"x = {x}, y = {y}, modx = {modx}")
if pow_mod_p2==False:
return (x*divmodx)%origb, y, modx, (origa)%origb
else:
if x < 0: return (modx*divmodx)%origb
else: return (x*divmodx)%origb
def ffs(x):
"""Returns the index, counting from 0, of the
least significant set bit in `x`.
"""
return (x&-x).bit_length()-1
def MillerRabin(arglist):
N = arglist[0]
primetest = arglist[1]
iterx = arglist[2]
powx = arglist[3]
withstats = arglist[4]
primetest = gmpy2.powmod(primetest, powx, N)
if withstats == True:
print("first: ", primetest)
if primetest == 1 or primetest == N - 1:
return True
else:
for x in range(0, iterx):
primetest = gmpy2.powmod(primetest, 2, N)
if withstats == True:
print("else: ", primetest)
if primetest == N - 1: return True
if primetest == 1: return False
return False
def sfactorint_isprime(N, withstats=False):
N = gmpy2.mpz(N)
from multiprocessing import Pool
if N <= 1: return False
if N == 2:
return True
if N % 2 == 0:
return False
if N < 2:
return False
# Add Trial Factoring here to speed up smaller factored number testing
iterx = ffs(N-1)
""" This k test is an algorithmic test builder instead of using
random numbers. The offset of k, from -2 to +2 produces pow tests
that fail or pass instead of having to use random numbers and more
iterations. All you need are those 5 numbers from k to get a
primality answer.
"""
k = llinear_diophantinex(N, 1<<N.bit_length(), pow_mod_p2=True) - 1
t = N >> iterx
tests = [k-2, k-1, k, k+1, k+2]
for primetest in range(len(tests)):
if tests[primetest] >= N:
tests[primetest] %= N
arglist = []
for primetest in range(len(tests)):
if tests[primetest] >= 2:
arglist.append([N, tests[primetest], iterx, t, withstats])
with Pool(5) as p:
s=p.map(MillerRabin, arglist)
if s.count(True) == len(arglist): return True
else: return False
return s

Recently I also tried to implement this algorithm in the deterministic form, as shown in Miller Test, and ran into the same problem. I couldn't figure out why it failed for some numbers so I decided to implement the 'complete' Miller-Rabin Test and it worked.
I should warn that it gets slow quickly as n increases. It's advised to use some numeric library like Numpy to optimize the calculations.
With some tweaks on your code it can be achieved:
import random
def _isPrime(n):
if n % 2 == 0:
return False
rounds = 40 # Determines the accuracy of the test
s, d = _Apart(n) # Turns it into 2^s x d + 1
for _ in range(rounds):
base = random.randrange(2, n-1) # Randomly selects a base
witness = pow(base, d)
if (witness % n) == 1 or (witness % n) == (n-1):
continue
for _ in range(1, s):
witness = pow(witness, 2) % n
if witness == (n-1):
break
else: # if the for-loop is not 'broken', n is not prime
return False
return True

def is_prime(n):
"""returns True if n is prime else False"""
if n < 5 or n & 1 == 0 or n % 3 == 0:
return 2 <= n <= 3
s = ((n - 1) & (1 - n)).bit_length() - 1
d = n >> s
for a in [2, 325, 9375, 28178, 450775, 9780504, 1795265022]:
p = pow(a, d, n)
if p == 1 or p == n - 1 or a % n == 0:
continue
for _ in range(s):
p = (p * p) % n
if p == n - 1:
break
else:
return False
return True

Is this function i wrote to find prime numbers efficient [duplicate]

This question already has answers here:
Big O, how do you calculate/approximate it?
(24 answers)
Closed 2 years ago.
def is_prime(x):
'''
Function to check if a number is prime
'''
if x == 2:
return True
if x%2 != 0: #Check if number is even since all primes are odd except 2
a = [x % i for i in range(2,x+1)]
b = [i for i in a if i == 0] # Checks to make sure there's only one modulus of 0
if len(b) == 1:
return True
else:
return False
else:
return False
So like yeah please what is the time complexity (all those 0/n things) and how do i find that, a good resource link would be helpful (:

Your complexity is O(x) as you run one loop from 2 to x+1.
You can just check upto sqrt(x). That will bring down the complexity to O(sqrt(x)). (You can break once you find one factor, even though it won't bring down the worst time complexity)
Just change this line -
a = [x % i for i in range(2,math.sqrt(x+1))]
Why up to square root?
You can just google, there are many proofs. The simple one being, if
a = b.c, then the at least there is one divisor of a which is less than sqrt(a), or equal if a is square number a = b*b.
There are many fast heuristic and probabilistic (Miller-Rabin is very famous and frequently used) algorithms for faster prime detection.
Here's one which is deterministic:
The Adleman–Pomerance–Rumely primality test is an algorithm for determining whether a number is prime. Unlike other, more efficient algorithms for this purpose, it avoids the use of random numbers, so it is a deterministic primality test.
It's complexity is log(x)^O(logloglogx)
import copy
import time
from math import gcd # version >= 3.5
# primality test by trial division
def isprime_slow(n):
if n<2:
return False
elif n==2 or n==3:
return True
elif n%2==0:
return False
else:
i = 3
while i*i <= n:
if n%i == 0:
return False
i+=2
return True
# v_q(t): how many time is t divided by q
def v(q, t):
ans = 0
while(t % q == 0):
ans +=1
t//= q
return ans
def prime_factorize(n):
ret = []
p=2
while p*p <= n:
if n%p==0:
num = 0
while n%p==0:
num+=1
n//= p
ret.append((p,num))
p+= 1
if n!=1:
ret.append((n,1))
return ret
# calculate e(t)
def e(t):
s = 1
q_list = []
for q in range(2, t+2):
if t % (q-1) == 0 and isprime_slow(q):
s *= q ** (1+v(q,t))
q_list.append(q)
return 2*s, q_list
# Jacobi sum
class JacobiSum(object):
def __init__(self, p, k, q):
self.p = p
self.k = k
self.q = q
self.m = (p-1)*p**(k-1)
self.pk = p**k
self.coef = [0]*self.m
# 1
def one(self):
self.coef[0] = 1
for i in range(1,self.m):
self.coef[i] = 0
return self
# product of JacobiSum
# jac : JacobiSum
def mul(self, jac):
m = self.m
pk = self.pk
j_ret=JacobiSum(self.p, self.k, self.q)
for i in range(m):
for j in range(m):
if (i+j)% pk < m:
j_ret.coef[(i+j)% pk] += self.coef[i] * jac.coef[j]
else:
r = (i+j) % pk - self.p ** (self.k-1)
while r>=0:
j_ret.coef[r] -= self.coef[i] * jac.coef[j]
r-= self.p ** (self.k-1)
return j_ret
def __mul__(self, right):
if type(right) is int:
# product with integer
j_ret=JacobiSum(self.p, self.k, self.q)
for i in range(self.m):
j_ret.coef[i] = self.coef[i] * right
return j_ret
else:
# product with JacobiSum
return self.mul(right)
# power of JacobiSum（x-th power mod n）
def modpow(self, x, n):
j_ret=JacobiSum(self.p, self.k, self.q)
j_ret.coef[0]=1
j_a = copy.deepcopy(self)
while x>0:
if x%2==1:
j_ret = (j_ret * j_a).mod(n)
j_a = j_a*j_a
j_a.mod(n)
x //= 2
return j_ret
# applying "mod n" to coefficient of self
def mod(self, n):
for i in range(self.m):
self.coef[i] %= n
return self
# operate sigma_x
# verification for sigma_inv
def sigma(self, x):
m = self.m
pk = self.pk
j_ret=JacobiSum(self.p, self.k, self.q)
for i in range(m):
if (i*x) % pk < m:
j_ret.coef[(i*x) % pk] += self.coef[i]
else:
r = (i*x) % pk - self.p ** (self.k-1)
while r>=0:
j_ret.coef[r] -= self.coef[i]
r-= self.p ** (self.k-1)
return j_ret
# operate sigma_x^(-1)
def sigma_inv(self, x):
m = self.m
pk = self.pk
j_ret=JacobiSum(self.p, self.k, self.q)
for i in range(pk):
if i<m:
if (i*x)%pk < m:
j_ret.coef[i] += self.coef[(i*x)%pk]
else:
r = i - self.p ** (self.k-1)
while r>=0:
if (i*x)%pk < m:
j_ret.coef[r] -= self.coef[(i*x)%pk]
r-= self.p ** (self.k-1)
return j_ret
# Is self p^k-th root of unity (mod N)
# if so, return h where self is zeta^h
def is_root_of_unity(self, N):
m = self.m
p = self.p
k = self.k
# case of zeta^h (h<m)
one = 0
for i in range(m):
if self.coef[i]==1:
one += 1
h = i
elif self.coef[i] == 0:
continue
elif (self.coef[i] - (-1)) %N != 0:
return False, None
if one == 1:
return True, h
# case of zeta^h (h>=m)
for i in range(m):
if self.coef[i]!=0:
break
r = i % (p**(k-1))
for i in range(m):
if i % (p**(k-1)) == r:
if (self.coef[i] - (-1))%N != 0:
return False, None
else:
if self.coef[i] !=0:
return False, None
return True, (p-1)*p**(k-1)+ r
# find primitive root
def smallest_primitive_root(q):
for r in range(2, q):
s = set({})
m = 1
for i in range(1, q):
m = (m*r) % q
s.add(m)
if len(s) == q-1:
return r
return None # error
# calculate f_q(x)
def calc_f(q):
g = smallest_primitive_root(q)
m = {}
for x in range(1,q-1):
m[pow(g,x,q)] = x
f = {}
for x in range(1,q-1):
f[x] = m[ (1-pow(g,x,q))%q ]
return f
# sum zeta^(a*x+b*f(x))
def calc_J_ab(p, k, q, a, b):
j_ret = JacobiSum(p,k,q)
f = calc_f(q)
for x in range(1,q-1):
pk = p**k
if (a*x+b*f[x]) % pk < j_ret.m:
j_ret.coef[(a*x+b*f[x]) % pk] += 1
else:
r = (a*x+b*f[x]) % pk - p**(k-1)
while r>=0:
j_ret.coef[r] -= 1
r-= p**(k-1)
return j_ret
# calculate J(p,q)（p>=3 or p,q=2,2）
def calc_J(p, k, q):
return calc_J_ab(p, k, q, 1, 1)
# calculate J_3(q)（p=2 and k>=3）
def calc_J3(p, k, q):
j2q = calc_J(p, k, q)
j21 = calc_J_ab(p, k, q, 2, 1)
j_ret = j2q * j21
return j_ret
# calculate J_2(q)（p=2 and k>=3）
def calc_J2(p, k, q):
j31 = calc_J_ab(2, 3, q, 3, 1)
j_conv = JacobiSum(p, k, q)
for i in range(j31.m):
j_conv.coef[i*(p**k)//8] = j31.coef[i]
j_ret = j_conv * j_conv
return j_ret
# in case of p>=3
def APRtest_step4a(p, k, q, N):
print("Step 4a. (p^k, q = {0}^{1}, {2})".format(p,k,q))
J = calc_J(p, k, q)
# initialize s1=1
s1 = JacobiSum(p,k,q).one()
# J^Theta
for x in range(p**k):
if x % p == 0:
continue
t = J.sigma_inv(x)
t = t.modpow(x, N)
s1 = s1 * t
s1.mod(N)
# r = N mod p^k
r = N % (p**k)
# s2 = s1 ^ (N/p^k)
s2 = s1.modpow(N//(p**k), N)
# J^alpha
J_alpha = JacobiSum(p,k,q).one()
for x in range(p**k):
if x % p == 0:
continue
t = J.sigma_inv(x)
t = t.modpow((r*x)//(p**k), N)
J_alpha = J_alpha * t
J_alpha.mod(N)
# S = s2 * J_alpha
S = (s2 * J_alpha).mod(N)
# Is S root of unity
exist, h = S.is_root_of_unity(N)
if not exist:
# composite!
return False, None
else:
# possible prime
if h%p!=0:
l_p = 1
else:
l_p = 0
return True, l_p
# in case of p=2 and k>=3
def APRtest_step4b(p, k, q, N):
print("Step 4b. (p^k, q = {0}^{1}, {2})".format(p,k,q))
J = calc_J3(p, k, q)
# initialize s1=1
s1 = JacobiSum(p,k,q).one()
# J3^Theta
for x in range(p**k):
if x % 8 not in [1,3]:
continue
t = J.sigma_inv(x)
t = t.modpow(x, N)
s1 = s1 * t
s1.mod(N)
# r = N mod p^k
r = N % (p**k)
# s2 = s1 ^ (N/p^k)
s2 = s1.modpow(N//(p**k), N)
# J3^alpha
J_alpha = JacobiSum(p,k,q).one()
for x in range(p**k):
if x % 8 not in [1,3]:
continue
t = J.sigma_inv(x)
t = t.modpow((r*x)//(p**k), N)
J_alpha = J_alpha * t
J_alpha.mod(N)
# S = s2 * J_alpha * J2^delta
if N%8 in [1,3]:
S = (s2 * J_alpha ).mod(N)
else:
J2_delta = calc_J2(p,k,q)
S = (s2 * J_alpha * J2_delta).mod(N)
# Is S root of unity
exist, h = S.is_root_of_unity(N)
if not exist:
# composite
return False, None
else:
# possible prime
if h%p!=0 and (pow(q,(N-1)//2,N) + 1)%N==0:
l_p = 1
else:
l_p = 0
return True, l_p
# in case of p=2 and k=2
def APRtest_step4c(p, k, q, N):
print("Step 4c. (p^k, q = {0}^{1}, {2})".format(p,k,q))
J2q = calc_J(p, k, q)
# s1 = J(2,q)^2 * q (mod N)
s1 = (J2q * J2q * q).mod(N)
# s2 = s1 ^ (N/4)
s2 = s1.modpow(N//4, N)
if N%4 == 1:
S = s2
elif N%4 == 3:
S = (s2 * J2q * J2q).mod(N)
else:
print("Error")
# Is S root of unity
exist, h = S.is_root_of_unity(N)
if not exist:
# composite
return False, None
else:
# possible prime
if h%p!=0 and (pow(q,(N-1)//2,N) + 1)%N==0:
l_p = 1
else:
l_p = 0
return True, l_p
# in case of p=2 and k=1
def APRtest_step4d(p, k, q, N):
print("Step 4d. (p^k, q = {0}^{1}, {2})".format(p,k,q))
S2q = pow(-q, (N-1)//2, N)
if (S2q-1)%N != 0 and (S2q+1)%N != 0:
# composite
return False, None
else:
# possible prime
if (S2q + 1)%N == 0 and (N-1)%4==0:
l_p=1
else:
l_p=0
return True, l_p
# Step 4
def APRtest_step4(p, k, q, N):
if p>=3:
result, l_p = APRtest_step4a(p, k, q, N)
elif p==2 and k>=3:
result, l_p = APRtest_step4b(p, k, q, N)
elif p==2 and k==2:
result, l_p = APRtest_step4c(p, k, q, N)
elif p==2 and k==1:
result, l_p = APRtest_step4d(p, k, q, N)
else:
print("error")
if not result:
print("Composite")
return result, l_p
def APRtest(N):
t_list = [
2,
12,
60,
180,
840,
1260,
1680,
2520,
5040,
15120,
55440,
110880,
720720,
1441440,
4324320,
24504480,
73513440
]
print("N=", N)
if N<=3:
print("input should be greater than 3")
return False
# Select t
for t in t_list:
et, q_list = e(t)
if N < et*et:
break
else:
print("t not found")
return False
print("t=", t)
print("e(t)=", et, q_list)
# Step 1
print("=== Step 1 ===")
g = gcd(t*et, N)
if g > 1:
print("Composite")
return False
# Step 2
print("=== Step 2 ===")
l = {}
fac_t = prime_factorize(t)
for p, k in fac_t:
if p>=3 and pow(N, p-1, p*p)!=1:
l[p] = 1
else:
l[p] = 0
print("l_p=", l)
# Step 3 & Step 4
print("=== Step 3&4 ===")
for q in q_list:
if q == 2:
continue
fac = prime_factorize(q-1)
for p,k in fac:
# Step 4
result, l_p = APRtest_step4(p, k, q, N)
if not result:
# composite
print("Composite")
return False
elif l_p==1:
l[p] = 1
# Step 5
print("=== Step 5 ===")
print("l_p=", l)
for p, value in l.items():
if value==0:
# try other pair of (p,q)
print("Try other (p,q). p={}".format(p))
count = 0
i = 1
found = False
# try maximum 30 times
while count < 30:
q = p*i+1
if N%q != 0 and isprime_slow(q) and (q not in q_list):
count += 1
k = v(p, q-1)
# Step 4
result, l_p = APRtest_step4(p, k, q, N)
if not result:
# composite
print("Composite")
return False
elif l_p == 1:
found = True
break
i += 1
if not found:
print("error in Step 5")
return False
# Step 6
print("=== Step 6 ===")
r = 1
for t in range(t-1):
r = (r*N) % et
if r!=1 and r!= N and N % r == 0:
print("Composite", r)
return False
# prime!!
print("Prime!")
return True
if __name__ == '__main__':
start_time = time.time()
APRtest(2**521-1) # 157 digit, 18 sec
# APRtest(2**1279-1) # 386 digit, 355 sec
# APRtest(2074722246773485207821695222107608587480996474721117292752992589912196684750549658310084416732550077)
end_time = time.time()
print(end_time - start_time, "sec")
credit: https://github.com/wacchoz/APR_CL/blob/master/APR_CL.py

You only need to test odd numbers, except for 2 which you can test specially before the loop. This doesn't change the complexity, since it's a constant factor, but it reduces the time in half.
You should only test numbers up to math.sqrt(x). This changes the worst case complexity from O(n) to O(sqrt(n)).
You should stop as soon as you find a factor, rather than creating a list of all the x % i. This improves the best case complexity.
import math
def is_prime(x):
'''
Function to check if a number is prime
'''
if x == 2:
return True
if x % 2 == 0:
return False
for i in range(3, int(math.sqrt(x))+1, 2):
if x % i == 0:
return False
return True
Even better than checking all odd numbers is to check only prime numbers, using the Sieve of Eratosthenes.

Fibonacci that takes a list of numbers and returns their fibonacci number

I am trying to implement a function that will print a number of fibonacci numbers. For example if my input was fibonacci([0,1,2,3], the output would be 0,1,1,2.
I am not sure how to proceed.
def fibonacci(n):
if n == 0:
return 0
elif n == 1:
return 1
return fibonacci(n - 1) + fibonacci(n-2)
while True:
n.append(n)
print(fibonacci[5,10,11])

You can refactor your code a bit and get:
def fibonacci(lst):
def getTerm(n):
if n == 0:
return 0
elif n == 1:
return 1
return getTerm(n - 1) + getTerm(n-2)
return [getTerm(x) for x in lst]
Gives output:
>>> fibonacci([0,1,2,3])
[0, 1, 1, 2]
>>> fibonacci([5,10,11])
[5, 55, 89]

Avoiding redundant computations:
def fibonacci(indices):
fibs = {}
set_of_indices = set(indices)
f0 = fibs[0] = 0
f1 = fibs[1] = 1
for i in range(2,max(indices)+1):
f2 = f0+f1
if i in set_of_indices:
fibs[i] = f2
f0,f1=f1,f2
return [fibs[i] for i in indices]

python: list of all factors that calculate a natural number

I'm new in python and I'm trying to figure out how to write a function in python that gives me back a list of all factors that calculate a natural number. The number entered shouldn't come on the result list.
it should look like this:
realfactor(250)
[1, 2, 5, 10, 25, 50, 125]
I probably should start like this:
def realfactor(n):
factorlist = []
I would appreciate the help

A simple iteration through all possible factors to build the list of viable ones:
def realfactor(n):
factorlist = []
for i in range(1, n//2 + 1): # check all 1 <= i <= 1/2 of n
if n % i == 0: # i is a factor of n
factorlist.append(i)
print(factorlist)

def realfactor(n):
factors = [1]
for i in range(2, math.floor( math.sqrt(n) )+1 ):
if n % i == 0:
factors.append(i)
factors.append(i/n)
return sorted(factors)
For very large n, this will be slightly faster than savanto's answer.

1. Solution taken from this post and added import for python 3.x:
from functools import reduce
def factors(n):
return set(reduce(list.__add__,
([i, n//i] for i in range(1, int(n**0.5) + 1) if n % i == 0)))
factors(250)
#~ {1, 2, 5, 10, 50, 25, 250, 125}
Horrible to read!
2. If you don't care about the order, here is a fast one:
def factors(n):
return [val for sublist in [
(i, n//i) for i in range(1, int(n**0.5) + 1) if n % i == 0
] for val in sublist
]
print(factors(250))
#~ [1, 250, 2, 125, 5, 50, 10, 25]
3. Not as efficient, but more readable and pythonic:
def factors(n):
fac_up = []
fac_down = []
for i in range(1, int(n**0.5) + 1):
if n % i == 0:
fac_up.append(i)
fac_down.append(n//i)
fac_up.extend(reversed(fac_down))
return fac_up
print(factors(250))
#~ [1, 2, 5, 10, 25, 50, 125, 250]
Comparison
from timeit import timeit
n = 250
# sorted
def factors_a(n=n):
factorlist = []
for i in range(1, n//2 + 1): # check all 1 <= i <= 1/2 of n
if n % i == 0: # i is a factor of n
factorlist.append(i)
return factorlist
# partially sorted ?!
def factors_b(n=n):
from functools import reduce
return set(reduce(list.__add__,
([i, n//i] for i in range(1, int(n**0.5) + 1) if n % i == 0)))
# unsorted
def factors_c(n=n):
return [val for sublist in [
(i, n//i) for i in range(1, int(n**0.5) + 1) if n % i == 0
] for val in sublist
]
# unsorted
def factors_d(n=n):
factorlist = []
for i in range(1, int(n**0.5) + 1):
if n % i == 0:
factorlist.extend((i, n//i))
return factorlist
# sorted
def factors_e(n=n):
fac_up = []
fac_down = []
for i in range(1, int(n**0.5) + 1):
if n % i == 0:
fac_up.append(i)
fac_down.append(n//i)
fac_up.extend(reversed(fac_down))
return fac_up
# sorted
def factors_f(n=n):
import math
factors = [1]
for i in range(2, math.floor( math.sqrt(n) )+1 ):
if n % i == 0:
factors.append(i)
factors.append(i/n)
return sorted(factors)
def test():
global n
for i in [12, 250, 10000, 99887766554433221100]:
print("--- TEST RUN, n = %i ---" % i)
n = i
for func in (factors_a, factors_b, factors_c, factors_d, factors_e, factors_f):
print(func.__name__, timeit(func, number=50000))
print("--- DONE ---")
test()
Timing
--- TEST RUN, n = 12 ---
factors_a 3.6315924063687817
factors_b 2.066486179519643
factors_c 1.1868003486015368
factors_d 0.9670367921808065
factors_e 1.3348606748124894
factors_f 1.7466818274729121
--- TEST RUN, n = 250 ---
factors_a 3.873070439592084
factors_b 2.060870580367009
factors_c 1.1865506143719813
factors_d 0.9752904229490014
factors_e 1.3438553833548212
factors_f 1.752019469006882
--- TEST RUN, n = 10000 ---
factors_a 3.5701808777132555
factors_b 2.0908904308173533
factors_c 1.2107483217776007
factors_d 0.9822444949425062
factors_e 1.3818273874635452
factors_f 1.75292261745426
--- TEST RUN, n = 99887766554433221100 ---
factors_a 3.4753276265071236
factors_b 2.066540915789119
factors_c 1.203012119807454
factors_d 0.9725134125242221
factors_e 1.362277986697336
factors_f 1.7789864895491974
--- DONE ---