gmpy2 provides access to an experimental integer type called `xmpz`. The `xmpz` type is a mutable integer type. In-place operations (+=, //=, etc.) modify the original object and do not create a new object. Instances of `xmpz` cannot be used as dictionary keys.

```>>> from gmpy2 import xmpz
>>> a = xmpz(123)
>>> b = a
>>> a += 1
>>> a
xmpz(124)
>>> b
xmpz(124)
```

The ability to change an `xmpz` object in-place allows for efficient and rapid bit manipulation.

Individual bits can be set or cleared:

```>>> a[10]=1
>>> a
xmpz(1148)
```

Slice notation is supported. The bits referenced by a slice can be either ‘read from’ or ‘written to’. To clear a slice of bits, use a source value of 0. In 2s-complement format, 0 is represented by an arbitrary number of 0-bits. To set a slice of bits, use a source value of ~0. The tilde operator inverts, or complements the bits in an integer. (~0 is -1 so you can also use -1.) In 2s-complement format, -1 is represented by an arbitrary number of 1-bits.

If a value for stop is specified in a slice assignment and the actual bit-length of the `xmpz` is less than stop, then the destination `xmpz` is logically padded with 0-bits to length stop.

```>>> a=xmpz(0)
>>> a[8:16] = ~0
>>> bin(a)
'0b1111111100000000'
>>> a[4:12] = ~a[4:12]
>>> bin(a)
'0b1111000011110000'
```

Bits can be reversed:

```>>> a = xmpz(1148)
>>> bin(a)
'0b10001111100'
>>> a[::] = a[::-1]
>>> bin(a)
'0b111110001'
```

The `iter_bits()` method returns a generator that returns True or False for each bit position. The methods `iter_clear()`, and `iter_set()` return generators that return the bit positions that are 1 or 0. The methods support arguments start and stop that define the beginning and ending bit positions that are used. To mimic the behavior of slices. the bit positions checked include start but the last position checked is stop - 1.

```>>> a=xmpz(117)
>>> bin(a)
'0b1110101'
>>> list(a.iter_bits())
[True, False, True, False, True, True, True]
>>> list(a.iter_clear())
[1, 3]
>>> list(a.iter_set())
[0, 2, 4, 5, 6]
>>> list(a.iter_bits(stop=12))
[True, False, True, False, True, True, True, False, False, False, False, False]
```

The following program uses the Sieve of Eratosthenes to generate a list of prime numbers.

```import time
import gmpy2

def sieve(limit=1000000):
'''Returns a generator that yields the prime numbers up to limit.'''

# Increment by 1 to account for the fact that slices  do not include
# the last index value but we do want to include the last value for
# calculating a list of primes.
sieve_limit = gmpy2.isqrt(limit) + 1
limit += 1

# Mark bit positions 0 and 1 as not prime.
bitmap = gmpy2.xmpz(3)

# Process 2 separately. This allows us to use p+p for the step size
# when sieving the remaining primes.
bitmap[4 : limit : 2] = -1

# Sieve the remaining primes.
for p in bitmap.iter_clear(3, sieve_limit):
bitmap[p*p : limit : p+p] = -1

return bitmap.iter_clear(2, limit)

if __name__ == "__main__":
start = time.time()
result = list(sieve())
print(time.time() - start)
print(len(result))
```

## The xmpz type

class gmpy2.xmpz(n=0, /)
class gmpy2.xmpz(s, /, base=0)

Return a mutable integer constructed from a numeric value n or a string s made of digits in the given base. Every input, that is accepted by the `mpz` type constructor is also accepted.

Note: This type can be faster when used for augmented assignment (+=, -=, etc), but `xmpz` objects cannot be used as dictionary keys.

__format__(fmt) str

Return a Python string by formatting `mpz` ‘x’ using the format string ‘fmt’. A valid format string consists of:

optional alignment code:

‘<’ -> left shifted in field ‘>’ -> right shifted in field ‘^’ -> centered in field

‘+’ -> always display leading sign ‘-’ -> only display minus sign ‘ ‘ -> minus for negative values, space for positive values

optional base indicator

‘#’ -> precede binary, octal, or hex with 0b, 0o or 0x

optional width

optional conversion code:

‘d’ -> decimal format ‘b’ -> binary format ‘o’ -> octal format ‘x’ -> hex format ‘X’ -> upper-case hex format

The default format is ‘d’.

bit_clear(n, /) mpz

Return a copy of x with the n-th bit cleared.

bit_flip(n, /) mpz

Return a copy of x with the n-th bit inverted.

bit_length() int

Return the number of significant bits in the radix-2 representation of x. Note: mpz(0).bit_length() returns 0.

bit_scan0(n=0, /)

Return the index of the first 0-bit of x with index >= n. n >= 0. If there are no more 0-bits in x at or above index n (which can only happen for x<0, assuming an infinitely long 2’s complement format), then `None` is returned.

bit_scan1(n=0, /)

Return the index of the first 1-bit of x with index >= n. n >= 0. If there are no more 1-bits in x at or above index n (which can only happen for x>=0, assuming an infinitely long 2’s complement format), then `None` is returned.

bit_set(n, /) mpz

Return a copy of x with the n-th bit set.

bit_test(n, /) bool

Return the value of the n-th bit of x.

conjugate() mpz

Return the conjugate of x (which is just a new reference to x since x is not a complex number).

copy() xmpz

Return a copy of a x.

digits(base=10, /) str

Return Python string representing x in the given base. Values for base can range between 2 to 62. A leading ‘-’ is present if x<0 but no leading ‘+’ is present if x>=0.

iter_bits(start=0, stop=-1)

Return `True` or `False` for each bit position in x beginning at ‘start’. If a positive value is specified for ‘stop’, iteration is continued until ‘stop’ is reached. If a negative value is specified, iteration is continued until the last 1-bit. Note: the value of the underlying `xmpz` object can change during iteration.

iter_clear(start=0, stop=-1)

Return every bit position that is clear in x, beginning at ‘start’. If a positive value is specified for ‘stop’, iteration is continued until ‘stop’ is reached. If a negative value is specified, iteration is continued until the last 1-bit. Note: the value of the underlying `xmpz` object can change during iteration.

iter_set(start=0, stop=-1)

Return an iterator yielding the bit position for every bit that is set in x, beginning at ‘start’. If a positive value is specified for ‘stop’, iteration is continued until ‘stop’ is reached. To match the behavior of slicing, ‘stop’ is not included. If a negative value is specified, iteration is continued until the last 1-bit. Note: the value of the underlying `xmpz` object can change during iteration.

limbs_finish(n, /) None

Must be called after writing to the address returned by x.limbs_write(n) or x.limbs_modify(n) to update the limbs of x.

limbs_modify(n, /) int

Returns the address of a mutable buffer representing the limbs of x, resized so that it may hold at least n limbs. Must be followed by a call to x.limbs_finish(n) after writing to the returned address in order for the changes to take effect.

Returns the address of the immutable buffer representing the limbs of x.

limbs_write(n, /) int

Returns the address of a mutable buffer representing the limbs of x, resized so that it may hold at least n limbs. Must be followed by a call to x.limbs_finish(n) after writing to the returned address in order for the changes to take effect. WARNING: this operation is destructive and may destroy the old value of x.

make_mpz() mpz

Return an `mpz` by converting x as quickly as possible.

NOTE: Optimized for speed so the original `xmpz` value is set to 0!

num_digits(base=10, /) int

Return length of string representing the absolute value of x in the given base. Values for base can range between 2 and 62. The value returned may be 1 too large.

num_limbs() int

Return the number of limbs of x.

denominator

the denominator of a rational number in lowest terms

numerator

the numerator of a rational number in lowest terms

real

the real part of a complex number

The following functions are based on mpz_lucas.c and mpz_prp.c by David Cleaver.

A good reference for probable prime testing is http://www.pseudoprime.com/pseudo.html

gmpy2.is_bpsw_prp(n, /) bool

Return `True` if n is a Baillie-Pomerance-Selfridge-Wagstaff probable prime. A BPSW probable prime passes the `is_strong_prp()` test with base 2 and the `is_selfridge_prp()` test.

gmpy2.is_euler_prp(n, a, /) bool

Return `True` if n is an Euler (also known as Solovay-Strassen) probable prime to the base a. Assuming:

gcd(n,a) == 1 n is odd

Then an Euler probable prime requires:

a**((n-1)/2) == (a/n) (mod n)

where (a/n) is the Jacobi symbol.

gmpy2.is_extra_strong_lucas_prp(n, p, /) bool

Return `True` if n is an extra strong Lucas probable prime with parameters (p,1). Assuming:

n is odd D = p*p - 4, D != 0 gcd(n, 2*D) == 1 n = s*(2**r) + Jacobi(D,n), s odd

Then an extra strong Lucas probable prime requires:

lucasu(p,1,s) == 0 (mod n) and lucasv(p,1,s) == +/-2 (mod n) or lucasv(p,1,s*(2**t)) == 0 (mod n) for some t, 0 <= t < r

gmpy2.is_fermat_prp(n, a, /) bool

Return `True` if n is a Fermat probable prime to the base a. Assuming:

gcd(n,a) == 1

Then a Fermat probable prime requires:

a**(n-1) == 1 (mod n)

gmpy2.is_fibonacci_prp(n, p, q, /) bool

Return `True` if n is a Fibonacci probable prime with parameters (p,q). Assuming:

n is odd p > 0, q = +/-1 p*p - 4*q != 0

Then a Fibonacci probable prime requires:

lucasv(p,q,n) == p (mod n).

gmpy2.is_lucas_prp(n, p, q, /) bool

Return `True` if n is a Lucas probable prime with parameters (p,q). Assuming:

n is odd D = p*p - 4*q, D != 0 gcd(n, 2*q*D) == 1

Then a Lucas probable prime requires:

lucasu(p,q,n - Jacobi(D,n)) == 0 (mod n)

gmpy2.is_selfridge_prp(n, /) bool

Return `True` if n is a Lucas probable prime with Selfidge parameters (p,q). The Selfridge parameters are chosen by finding the first element D in the sequence {5, -7, 9, -11, 13, …} such that Jacobi(D,n) == -1. Then let p=1 and q = (1-D)/4. Then perform a Lucas probable prime test.

gmpy2.is_strong_bpsw_prp(n, /) bool

Return `True` if n is a strong Baillie-Pomerance-Selfridge-Wagstaff probable prime. A strong BPSW probable prime passes the `is_strong_prp()` test with base and the `is_strong_selfridge_prp()` test.

gmpy2.is_strong_lucas_prp(n, p, q, /) bool

Return `True` if n is a strong Lucas probable prime with parameters (p,q). Assuming:

n is odd D = p*p - 4*q, D != 0 gcd(n, 2*q*D) == 1 n = s*(2**r) + Jacobi(D,n), s odd

Then a strong Lucas probable prime requires:

lucasu(p,q,s) == 0 (mod n) or lucasv(p,q,s*(2**t)) == 0 (mod n) for some t, 0 <= t < r

gmpy2.is_strong_prp(n, a, /) bool

Return `True` if n is a strong (also known as Miller-Rabin) probable prime to the base a. Assuming:

gcd(n,a) == 1 n is odd n = s*(2**r) + 1, with s odd

Then a strong probable prime requires one of the following is true:

a**s == 1 (mod n) or a**(s*(2**t)) == -1 (mod n) for some t, 0 <= t < r.

gmpy2.is_strong_selfridge_prp(n, /) bool

Return `True` if n is a strong Lucas probable prime with Selfidge parameters (p,q). The Selfridge parameters are chosen by finding the first element D in the sequence {5, -7, 9, -11, 13, …} such that Jacobi(D,n) == -1. Then let p=1 and q = (1-D)/4. Then perform a strong Lucas probable prime test.

gmpy2.lucasu(p, q, k, /) mpz

Return the k-th element of the Lucas U sequence defined by p,q. p*p - 4*q must not equal 0; k must be greater than or equal to 0.

gmpy2.lucasu_mod(p, q, k, n, /) mpz

Return the k-th element of the Lucas U sequence defined by p,q (mod n). p*p - 4*q must not equal 0; k must be greater than or equal to 0; n must be greater than 0.

gmpy2.lucasv(p, q, k, /) mpz

Return the k-th element of the Lucas V sequence defined by p,q. p*p - 4*q must not equal 0; k must be greater than or equal to 0.

gmpy2.lucasv_mod(p, q, k, n, /) mpz

Return the k-th element of the Lucas V sequence defined by p,q (mod n). p*p - 4*q must not equal 0; k must be greater than or equal to 0; n must be greater than 0.