long <-> str binary conversion
Is there any lib that convert very long numbers to string just copying the data?
These one-liners are too slow:
def xlong(s):
return sum([ord(c) << e*8 for e,c in enumerate(s)])
def xstr(x):
return chr(x&255) + xstr(x >> 8) if x else ''
print xlong('abcd'*1024) % 666
print xstr(13**666)
Asked by: Sam913 | Posted: 27-01-2022
Answer 1
You want the struct module.
packed = struct.pack('l', 123456)
assert struct.unpack('l', packed)[0] == 123456
Answer 2
How about
from binascii import hexlify, unhexlify
def xstr(x):
hex = '%x' % x
return unhexlify('0'*(len(hex)%2) + hex)[::-1]
def xlong(s):
return int(hexlify(s[::-1]), 16)
I didn't time it but it should be faster and also work on larger numbers, since it doesn't use recursion.
Answered by: Darcy338 | Posted: 28-02-2022Answer 3
In fact, I have a lack of long(s,256) . I lurk more and see that there are 2 function in Python CAPI file "longobject.h":
PyObject * _PyLong_FromByteArray( const unsigned char* bytes, size_t n, int little_endian, int is_signed);
int _PyLong_AsByteArray(PyLongObject* v, unsigned char* bytes, size_t n, int little_endian, int is_signed);
They do the job. I don't know why there are not included in some python module, or correct me if I'am wrong.
Answered by: Chester246 | Posted: 28-02-2022Answer 4
If you need fast serialization use marshal module. It's around 400x faster than your methods.
Answered by: Brad444 | Posted: 28-02-2022Answer 5
I'm guessing you don't care about the string format, you just want a serialization? If so, why not use Python's built-in serializer, the cPickle module? The dumps function will convert any python object including a long integer to a string, and the loads function is its inverse. If you're doing this for saving out to a file, check out the dump and load functions, too.
>>> import cPickle
>>> print cPickle.loads(cPickle.dumps(13**666)) % 666
73
>>> print (13**666) % 666
73
Answer 6
Performance of cPickle vs. marshal (Python 2.5.2, Windows):
python -mtimeit -s"from cPickle import loads,dumps;d=13**666" "loads(dumps(d))"
1000 loops, best of 3: 600 usec per loop
python -mtimeit -s"from marshal import loads,dumps;d=13**666" "loads(dumps(d))"
100000 loops, best of 3: 7.79 usec per loop
python -mtimeit -s"from pickle import loads,dumps;d= 13**666" "loads(dumps(d))"
1000 loops, best of 3: 644 usec per loop
marshal is much faster.
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