So i need to unpack an extremely long byte stream (from USB) into 4 byte values.
Currently i got it working, but i feel there's a better way to do this.
Currently i got:
l=[]
for i in range(int(len(mybytes)/4)):
l.append(struct.unpack_from('>i',mybytes,i*4))
So this feels like very resource expensive, and im doing this for 16k bytes A LOT.
I also feel like this has probably been asked before i just don't really know how to word it for searching
You could also try the array module which has the ability to load directly from binary data:
import array
arr = array.array("I",mybytes) # "I" stands for unsigned integer
arr.byteswap() # only if you're reading endian coding different from your platform
l = list(arr)
You can specify a size for the integers to unpack (Python 3.6+):
>>> import struct
>>> mybytes = bytes([1,2,3,4,5,6,7,8])
>>> struct.unpack(f'>2i',mybytes)
(16909060, 84281096)
>>> n = len(mybytes) // 4
>>> struct.unpack(f'>{n}i',mybytes) # Python 3.6+ f-strings
(16909060, 84281096)
>>> struct.unpack('>{}i'.format(n),mybytes) # Older Pythons
(16909060, 84281096)
>>> [hex(i) for i in _]
['0x1020304', '0x5060708']
Wrap it in a BytesIO object, then use iter to call its read method until it returns an empty bytes value.
>>> import io, struct
>>> bio = io.BytesIO(b'abcdefgh')
>>> int_fmt = struct.Struct(">i")
>>> list(map(int_fmt.unpack, iter(lambda: bio.read(4), b'')))
[(1633837924,), (1701209960,)]
You can tweak this to extract the single int value from each tuple, or switch to the from_bytes class method.
>>> bio = io.BytesIO(b'abcdefgh')
>>> list(map(lambda i: int.from_bytes(i, 'big'), iter(lambda: bio.read(4), b'')))
[1633837924, 1701209960]
I have various problems with my assigned data types after read from any binary file with np.fromfile and np.memmap.
I am reading the following:
openfile = open(mypath,'rb')
openfile.seek(start_byte)
myvalue = np.fromfile(openfile, dtype = np.uint64, count=1)
print myvalue
return:
myvalue = [1234]
myvalue has 8 bytes and is interpreted as an ndarray, but I want just an uint64-value using it as an index.
1) How to prevent np.fromfile to write in an ndarray?
If I am trying: myvalue = myvalue[0] myvalue loses it's data type completely.
2) Why does myvalue looses it's data type when I am accessing the first
I have to do something like that with my arrays:
data.extend([myvalue for l in range(myvalue)])
Try to assign again a data type: myvalue = myvalue[0].astype(np.uint64). Now I get:
self.data_array[count:count+myvalue,0] = data[count:count+myvalue]
TypeError: slice indices must be integers or None or have an __index__ method
3) What is going wrong here?
If I am assigning myvalue as: myvalue = myvalue[0].astype(np.int32) The data is interpreted wrongly and I get: -35566848567 etc.
4) Why can myvalue still be wrongly interpreted by the programme after read in since
myvalue = myvalue[0].astype(np.int32)
IS NOT
myvalue = myvalue[0].astype(np.uint64)
Forgive the possible non-answer, but it's easier to post code this way...
Why do you think that myvalue loses its type information? It doesn't do that when I try it here (Python 2.7):
>>> myvalue = np.array([1234], np.uint64)
>>> myvalue = myvalue[0]
>>> type(myvalue)
<type 'numpy.uint64'>
There is a warning about using fromfile in its docs:
Notes
----- Do not rely on the combination of tofile and fromfile for data storage, as the binary files generated are are not platform
independent. In particular, no byte-order or data-type information is
saved. Data can be stored in the platform independent .npy format
using save and load instead.
I was trying to build this bytes object in Python 3:
b'3\r\n'
so I tried the obvious (for me), and found a weird behaviour:
>>> bytes(3) + b'\r\n'
b'\x00\x00\x00\r\n'
Apparently:
>>> bytes(10)
b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
I've been unable to see any pointers on why the bytes conversion works this way reading the documentation. However, I did find some surprise messages in this Python issue about adding format to bytes (see also Python 3 bytes formatting):
http://bugs.python.org/issue3982
This interacts even more poorly with oddities like bytes(int) returning zeroes now
and:
It would be much more convenient for me if bytes(int) returned the ASCIIfication of that int; but honestly, even an error would be better than this behavior. (If I wanted this behavior - which I never have - I'd rather it be a classmethod, invoked like "bytes.zeroes(n)".)
Can someone explain me where this behaviour comes from?
From python 3.2 you can use to_bytes:
>>> (1024).to_bytes(2, byteorder='big')
b'\x04\x00'
def int_to_bytes(x: int) -> bytes:
return x.to_bytes((x.bit_length() + 7) // 8, 'big')
def int_from_bytes(xbytes: bytes) -> int:
return int.from_bytes(xbytes, 'big')
Accordingly, x == int_from_bytes(int_to_bytes(x)).
Note that the above encoding works only for unsigned (non-negative) integers.
For signed integers, the bit length is a bit more tricky to calculate:
def int_to_bytes(number: int) -> bytes:
return number.to_bytes(length=(8 + (number + (number < 0)).bit_length()) // 8, byteorder='big', signed=True)
def int_from_bytes(binary_data: bytes) -> Optional[int]:
return int.from_bytes(binary_data, byteorder='big', signed=True)
That's the way it was designed - and it makes sense because usually, you would call bytes on an iterable instead of a single integer:
>>> bytes([3])
b'\x03'
The docs state this, as well as the docstring for bytes:
>>> help(bytes)
...
bytes(int) -> bytes object of size given by the parameter initialized with null bytes
You can use the struct's pack:
In [11]: struct.pack(">I", 1)
Out[11]: '\x00\x00\x00\x01'
The ">" is the byte-order (big-endian) and the "I" is the format character. So you can be specific if you want to do something else:
In [12]: struct.pack("<H", 1)
Out[12]: '\x01\x00'
In [13]: struct.pack("B", 1)
Out[13]: '\x01'
This works the same on both python 2 and python 3.
Note: the inverse operation (bytes to int) can be done with unpack.
Python 3.5+ introduces %-interpolation (printf-style formatting) for bytes:
>>> b'%d\r\n' % 3
b'3\r\n'
See PEP 0461 -- Adding % formatting to bytes and bytearray.
On earlier versions, you could use str and .encode('ascii') the result:
>>> s = '%d\r\n' % 3
>>> s.encode('ascii')
b'3\r\n'
Note: It is different from what int.to_bytes produces:
>>> n = 3
>>> n.to_bytes((n.bit_length() + 7) // 8, 'big') or b'\0'
b'\x03'
>>> b'3' == b'\x33' != b'\x03'
True
The documentation says:
bytes(int) -> bytes object of size given by the parameter
initialized with null bytes
The sequence:
b'3\r\n'
It is the character '3' (decimal 51) the character '\r' (13) and '\n' (10).
Therefore, the way would treat it as such, for example:
>>> bytes([51, 13, 10])
b'3\r\n'
>>> bytes('3', 'utf8') + b'\r\n'
b'3\r\n'
>>> n = 3
>>> bytes(str(n), 'ascii') + b'\r\n'
b'3\r\n'
Tested on IPython 1.1.0 & Python 3.2.3
The ASCIIfication of 3 is "\x33" not "\x03"!
That is what python does for str(3) but it would be totally wrong for bytes, as they should be considered arrays of binary data and not be abused as strings.
The most easy way to achieve what you want is bytes((3,)), which is better than bytes([3]) because initializing a list is much more expensive, so never use lists when you can use tuples. You can convert bigger integers by using int.to_bytes(3, "little").
Initializing bytes with a given length makes sense and is the most useful, as they are often used to create some type of buffer for which you need some memory of given size allocated. I often use this when initializing arrays or expanding some file by writing zeros to it.
I was curious about performance of various methods for a single int in the range [0, 255], so I decided to do some timing tests.
Based on the timings below, and from the general trend I observed from trying many different values and configurations, struct.pack seems to be the fastest, followed by int.to_bytes, bytes, and with str.encode (unsurprisingly) being the slowest. Note that the results show some more variation than is represented, and int.to_bytes and bytes sometimes switched speed ranking during testing, but struct.pack is clearly the fastest.
Results in CPython 3.7 on Windows:
Testing with 63:
bytes_: 100000 loops, best of 5: 3.3 usec per loop
to_bytes: 100000 loops, best of 5: 2.72 usec per loop
struct_pack: 100000 loops, best of 5: 2.32 usec per loop
chr_encode: 50000 loops, best of 5: 3.66 usec per loop
Test module (named int_to_byte.py):
"""Functions for converting a single int to a bytes object with that int's value."""
import random
import shlex
import struct
import timeit
def bytes_(i):
"""From Tim Pietzcker's answer:
https://stackoverflow.com/a/21017834/8117067
"""
return bytes([i])
def to_bytes(i):
"""From brunsgaard's answer:
https://stackoverflow.com/a/30375198/8117067
"""
return i.to_bytes(1, byteorder='big')
def struct_pack(i):
"""From Andy Hayden's answer:
https://stackoverflow.com/a/26920966/8117067
"""
return struct.pack('B', i)
# Originally, jfs's answer was considered for testing,
# but the result is not identical to the other methods
# https://stackoverflow.com/a/31761722/8117067
def chr_encode(i):
"""Another method, from Quuxplusone's answer here:
https://codereview.stackexchange.com/a/210789/140921
Similar to g10guang's answer:
https://stackoverflow.com/a/51558790/8117067
"""
return chr(i).encode('latin1')
converters = [bytes_, to_bytes, struct_pack, chr_encode]
def one_byte_equality_test():
"""Test that results are identical for ints in the range [0, 255]."""
for i in range(256):
results = [c(i) for c in converters]
# Test that all results are equal
start = results[0]
if any(start != b for b in results):
raise ValueError(results)
def timing_tests(value=None):
"""Test each of the functions with a random int."""
if value is None:
# random.randint takes more time than int to byte conversion
# so it can't be a part of the timeit call
value = random.randint(0, 255)
print(f'Testing with {value}:')
for c in converters:
print(f'{c.__name__}: ', end='')
# Uses technique borrowed from https://stackoverflow.com/q/19062202/8117067
timeit.main(args=shlex.split(
f"-s 'from int_to_byte import {c.__name__}; value = {value}' " +
f"'{c.__name__}(value)'"
))
The behaviour comes from the fact that in Python prior to version 3 bytes was just an alias for str. In Python3.x bytes is an immutable version of bytearray - completely new type, not backwards compatible.
From bytes docs:
Accordingly, constructor arguments are interpreted as for bytearray().
Then, from bytearray docs:
The optional source parameter can be used to initialize the array in a few different ways:
If it is an integer, the array will have that size and will be initialized with null bytes.
Note, that differs from 2.x (where x >= 6) behavior, where bytes is simply str:
>>> bytes is str
True
PEP 3112:
The 2.6 str differs from 3.0’s bytes type in various ways; most notably, the constructor is completely different.
int (including Python2's long) can be converted to bytes using following function:
import codecs
def int2bytes(i):
hex_value = '{0:x}'.format(i)
# make length of hex_value a multiple of two
hex_value = '0' * (len(hex_value) % 2) + hex_value
return codecs.decode(hex_value, 'hex_codec')
The reverse conversion can be done by another one:
import codecs
import six # should be installed via 'pip install six'
long = six.integer_types[-1]
def bytes2int(b):
return long(codecs.encode(b, 'hex_codec'), 16)
Both functions work on both Python2 and Python3.
Although the prior answer by brunsgaard is an efficient encoding, it works only for unsigned integers. This one builds upon it to work for both signed and unsigned integers.
def int_to_bytes(i: int, *, signed: bool = False) -> bytes:
length = ((i + ((i * signed) < 0)).bit_length() + 7 + signed) // 8
return i.to_bytes(length, byteorder='big', signed=signed)
def bytes_to_int(b: bytes, *, signed: bool = False) -> int:
return int.from_bytes(b, byteorder='big', signed=signed)
# Test unsigned:
for i in range(1025):
assert i == bytes_to_int(int_to_bytes(i))
# Test signed:
for i in range(-1024, 1025):
assert i == bytes_to_int(int_to_bytes(i, signed=True), signed=True)
For the encoder, (i + ((i * signed) < 0)).bit_length() is used instead of just i.bit_length() because the latter leads to an inefficient encoding of -128, -32768, etc.
Credit: CervEd for fixing a minor inefficiency.
As you want to deal with binary representation, the best is to use ctypes.
import ctypes
x = ctypes.c_int(1234)
bytes(x)
You must use the specific integer representation (signed/unsigned and the number of bits: c_uint8, c_int8, c_unit16,...).
Some answers don't work with large numbers.
Convert integer to the hex representation, then convert it to bytes:
def int_to_bytes(number):
hrepr = hex(number).replace('0x', '')
if len(hrepr) % 2 == 1:
hrepr = '0' + hrepr
return bytes.fromhex(hrepr)
Result:
>>> int_to_bytes(2**256 - 1)
b'\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff'
I think you can convert the int to str first, before you convert to byte.
That should produce the format you want.
bytes(str(your_number),'UTF-8') + b'\r\n'
It works for me in py3.8.
If the question is how to convert an integer itself (not its string equivalent) into bytes, I think the robust answer is:
>>> i = 5
>>> i.to_bytes(2, 'big')
b'\x00\x05'
>>> int.from_bytes(i.to_bytes(2, 'big'), byteorder='big')
5
More information on these methods here:
https://docs.python.org/3.8/library/stdtypes.html#int.to_bytes
https://docs.python.org/3.8/library/stdtypes.html#int.from_bytes
>>> chr(116).encode()
b't'
Actually, I'm trying to convert ctypes arrays to python lists and back.
If found this thread. But it assumes that we know the type at compile time.
But is it possible to retrieve a ctypes type for an element?
I have a python list that contains at least one element. I want to do something like that
import ctypes
arr = (type(pyarr[0]) * len(pyarr))(*pyarr)
This obviously doesn't work because type() doesn't return a ctypes compatible class. But even if the list contains object created directly from ctypes, the above code doesn't work because its an object instance of the type.
Is there any way to perform this task?
[EDIT]
Ok, here is the code that works for me. I'm using it to convert input paraters from comtypes server method to python lists and return values to array pointers:
def list(count, p_items):
"""Returns a python list for the given times represented by a pointer and the number of items"""
items = []
for i in range(count):
items.append(p_items[i])
return items
def p_list(items):
"""Returns a pointer to a list of items"""
c_items = (type(items[0])*len(items))(*items)
p_items = cast(c_items, POINTER(type(items[0])))
return p_items
As explained before, p_list(items) requires at least one element.
I don't think that's directly possible, because multiple ctypes types map to single Python types. For example c_int/c_long/c_ulong/c_ulonglong all map to Python int. Which type would you choose? You could create a map of your preferences:
>>> D = {int:c_int,float:c_double}
>>> pyarr = [1.2,2.4,3.6]
>>> arr = (D[type(pyarr[0])] * len(pyarr))(*pyarr)
>>> arr
<__main__.c_double_Array_3 object at 0x023540D0>
>>> arr[0]
1.2
>>> arr[1]
2.4
>>> arr[2]
3.6
Also, the undocumented _type_ can tell the type of a ctypes array.
>>> arr._type_
<class 'ctypes.c_double'>
I have a string buffer: b = create_string_buffer(numb) where numb is a number of bytes.
In my wrapper I need to splice up this buffer. When calling a function that expects a POINTER(c_char) I can do: myfunction(self, byref(b, offset)) but in a Structure:
class mystruct(Structure):
_fields_ = [("buf", POINTER(c_char))]
I am unable to do this, getting an argument type exception. So my question is: how can I assign .buf to be an offset into b. Direct assignment works so .buf = b, however this is unsuitable. (Python does not hold up to well against ~32,000 such buffers being created every second, hence my desire to use a single spliced buffer.)
ctypes.cast
>>> import ctypes
>>> b = ctypes.create_string_buffer(500)
>>> b[:6] = 'foobar'
>>> ctypes.cast(ctypes.byref(b, 4), ctypes.POINTER(ctypes.c_char))
<ctypes.LP_c_char object at 0x100756e60>
>>> _.contents
c_char('a')