I want to build a small formatter in python giving me back the numeric
values embedded in lines of hex strings.
It is a central part of my formatter and should be reasonable fast to
format more than 100 lines/sec (each line about ~100 chars).
The code below should give an example where I'm currently blocked.
'data_string_in_orig' shows the given input format. It has to be
byte swapped for each word. The swap from 'data_string_in_orig' to
'data_string_in_swapped' is needed. In the end I need the structure
access as shown. The expected result is within the comment.
Thanks in advance
Wolfgang R
#!/usr/bin/python
import binascii
import struct
## 'uint32 double'
data_string_in_orig = 'b62e000052e366667a66408d'
data_string_in_swapped = '2eb60000e3526666667a8d40'
print data_string_in_orig
packed_data = binascii.unhexlify(data_string_in_swapped)
s = struct.Struct('<Id')
unpacked_data = s.unpack_from(packed_data, 0)
print 'Unpacked Values:', unpacked_data
## Unpacked Values: (46638, 943.29999999943209)
exit(0)
array.arrays have a byteswap method:
import binascii
import struct
import array
x = binascii.unhexlify('b62e000052e366667a66408d')
y = array.array('h', x)
y.byteswap()
s = struct.Struct('<Id')
print(s.unpack_from(y))
# (46638, 943.2999999994321)
The h in array.array('h', x) was chosen because it tells array.array to regard the data in x as an array of 2-byte shorts. The important thing is that each item be regarded as being 2-bytes long. H, which signifies 2-byte unsigned short, works just as well.
This should do exactly what unutbu's version does, but might be slightly easier to follow for some...
from binascii import unhexlify
from struct import pack, unpack
orig = unhexlify('b62e000052e366667a66408d')
swapped = pack('<6h', *unpack('>6h', orig))
print unpack('<Id', swapped)
# (46638, 943.2999999994321)
Basically, unpack 6 shorts big-endian, repack as 6 shorts little-endian.
Again, same thing that unutbu's code does, and you should use his.
edit Just realized I get to use my favorite Python idiom for this... Don't do this either:
orig = 'b62e000052e366667a66408d'
swap =''.join(sum([(c,d,a,b) for a,b,c,d in zip(*[iter(orig)]*4)], ()))
# '2eb60000e3526666667a8d40'
The swap from 'data_string_in_orig' to 'data_string_in_swapped' may also be done with comprehensions without using any imports:
>>> d = 'b62e000052e366667a66408d'
>>> "".join([m[2:4]+m[0:2] for m in [d[i:i+4] for i in range(0,len(d),4)]])
'2eb60000e3526666667a8d40'
The comprehension works for swapping byte order in hex strings representing 16-bit words. Modifying it for a different word-length is trivial. We can make a general hex digit order swap function also:
def swap_order(d, wsz=4, gsz=2 ):
return "".join(["".join([m[i:i+gsz] for i in range(wsz-gsz,-gsz,-gsz)]) for m in [d[i:i+wsz] for i in range(0,len(d),wsz)]])
The input params are:
d : the input hex string
wsz: the word-size in nibbles (e.g for 16-bit words wsz=4, for 32-bit words wsz=8)
gsz: the number of nibbles which stay together (e.g for reordering bytes gsz=2, for reordering 16-bit words gsz = 4)
import binascii, tkinter, array
from tkinter import *
infile_read = filedialog.askopenfilename()
with open(infile, 'rb') as infile_:
infile_read = infile_.read()
x = (infile_read)
y = array.array('l', x)
y.byteswap()
swapped = (binascii.hexlify(y))
This is a 32 bit unsigned short swap i achieved with code very much the same as "unutbu's" answer just a little bit easier to understand. And technically binascii is not needed for the swap. Only array.byteswap is needed.
Related
I want to share memory between a program in C and another in python.
The c program uses the following structure to define the data.
struct Memory_LaserFrontal {
char Data[372]; // original data
float Med[181]; // Measurements in [m]
charD; // 'I': Invalid -- 'V': Valid
charS; // 'L': Clean -- 'S': Dirty
char LaserStatus[2];
};
From python I have managed to read the variable in memory using sysv_ipc but they have no structure and is seen as a data array. How can I restructure them?
python code:
from time import sleep
import sysv_ipc
# Create shared memory object
memory = sysv_ipc.SharedMemory(1234)
# Read value from shared memory
memory_value = memory.read()
print (memory_value)
print (len(memory_value))
while True:
memory_value = memory.read()
print (float(memory_value[800]))
sleep(0.1)
I have captured and printed the data in python, I have modified the sensor reading and the read data is also modified, confirming that the read data corresponds to the data in the sensor's shared memory. But without the proper structure y cant use the data.
You need to unpack your binary data structure into Python types. The Python modules struct and array can do this for you.
import struct
import array
NB: Some C compilers, but not the comomn ones, may pad your member variables to align each of them with the expected width for your CPU ( almost always 4 bytes ). This means that it may add padding bytes. You may have to experiment with the struct format parameter 'x' between the appropriate parts of your struct if this is the case. Python's struct module does not expect aligned or padded types by default, you need to inform it. See my note at the very end for a guess on what the padding might look like. Again, per #Max's comment, this is unlikely.
NB: I think the members charD and charS are really char D; and char S;
Assuming you want the floats as a Python list or equivalent we have to do some more work with the Python array module . Same for the char[] Data.
# Get the initial char array - you can turn it into a string if you need to later.
my_chars = array.array("b") # f for float, b for byteetc.
my_chars.from_bytes(memory_value[:372]) # happens that 372 C chars is 372 bytes.
Data = my_chars.tolist() # Could be bytes list
# advance to the member after Data
end_of_Data = struct.calcsize("372c")
# get the length in bytes that 181 floats take up
end_of_Med = struct.calcsize("181f") + end_of_Data
# now we know where the floats are
floats_as_bytes = memory_value[ end_of_Data : end_of_Med ]
# unpack the remaining parts
( D, S, LaserStatus_1, LaserStatus_2 ) = struct.unpack( "cccc", memory_value[end_of_Med:] )
Now use the array module to unpack to make a Python list
my_floats = array.array("f") # f for float, c for char etc.
my_floats.from_bytes(floats_as_bytes)
Now Data might be a list of Python bytes type that you need to convert to your preferred string encoding. Usually .decode('utf-8') is good enough.
Data_S = "".join(Data).decode('utf-8') # get a usable string in Data_S
Padding
struct Memory_LaserFrontal {
char Data[372]; // 372 is a multiple of 4, probably no padding
float Med[181]; // floats are 4 bytes, probably no padding
charD; // single char, expect 3 padding bytes after
charS; // single char, expect 3 padding bytes after
char LaserStatus[2]; // double char expect 2 padding bytes after.
};
So the last Python line above might be - where the 'x' indicates a padding byte that can be ignored.
( D, S, LaserStatus_1, LaserStatus_2 ) = struct.unpack( "cxxxcxxxccxx", memory_value[end_of_Med:] )
I always like to leave the full source code of the problem solved so others can use it if they have a similar problem.
thanks a lot all!
from time import sleep
import sysv_ipc
import struct
import array
# Create shared memory object
while True:
memory = sysv_ipc.SharedMemory(1234)
# Read value from shared memory
memory_value = memory.read()
#print (memory_value)
#print (len(memory_value))
# Get the initial char array - you can turn it into a string if you need to later.
my_chars = array.array("b") # f for float, c for char etc.
#my_chars.from_bytes(memory_value[:372]) # happens that 372 chars is 372 bytes.
Data = my_chars.tolist() # Could be bytes list
# advance to the member after Data
end_of_Data = struct.calcsize("372c")
# get the length in bytes that 181 floats take up
end_of_Med = struct.calcsize("181f") + end_of_Data
# now we know where the floats are
floats_as_bytes = memory_value[ end_of_Data : end_of_Med ]
# unpack the remaining parts
( D, S, LaserStatus_1, LaserStatus_2 ) = struct.unpack( "cccc", memory_value[end_of_Med:] )
print(len(floats_as_bytes)/4)
a=[]
for i in range(0,len(floats_as_bytes),4):
a.append(struct.unpack('<f', floats_as_bytes[i:i+4]))
print (a[0])
sleep(0.1)
I saved one data set(200 double data values) from Keil, it turns to be a .hex file with IntelHex format, I installed IntelHex in python and load it. Now the problem is I do not know how to interpret it, for example, this post
tells you to use dict, but it does not work for hex file including double data. my code:
from intelhex import IntelHex
ih = IntelHex() # create empty object
ih.loadhex('output.hex')
ihdict = ih.todict()
datastr = ""
startAddress = 536871952
while ihdict.get(startAddress) != None:
datastr += str("%0.2X" %ihdict.get(startAddress))
startAddress += 1
the file output.hex:
:020000042000DA
:0802A8003FB7809F5BC03F409F
:1002B000DFB56EEF5AB73F407F717CBF38BE3F401D
:1002C000DFD369EFE9B43F407F717CBF38BE3F4068
:1002D0003F895E9F44AF3F401F706A0F38B53F4073
:1002E0009F20584F10AC3F405F5F72AF2FB93F4027
:1002F000DFB56EEF5AB73F40DF5B7DEFADBE3F40ED
:10030000BFA364DF51B23F40DF62676FB1B33F40CC
:100310001F9E8C0F4FC63F405F0C6B2F86B53F4032
:10032000BF7542DF3AA13F403F4D689F26B43F4032
:100330009F2742CF13A13F40DF2D5BEF96AD3F409B
:100340009F915ACF48AD3F40DF874CEF43A63F40D7
:100350007FD2573FE9AB3F40FD721E7F398F3F4050
:10036000FF892FFFC4973F409D5311CFA9883F407D
:100370001F706A0F38B53F407F78663F3CB33F40FF
:100380001DFD148F7E8A3F401F954F8FCAA73F40A7
:100390005FC04D2FE0A63F401F0D3C8F069E3F40A3
:1003A0007F4A443F25A23F40DFE13DEFF09E3F40C2
:1003B0003F185C1F0CAE3F403F79379FBC9B3F40CE
:1003C000FF2F3EFF179F3F40DFBC586F5EAC3F40A2
:1003D000FD36287F1B943F403F3D419F9EA03F40FC
:1003E000FFFA317FFD983F409FF2354FF99A3F4029
:1003F0007D0511BF82883F40DF703B6FB89D3F4055
:10040000FF1143FF88A13F40DD60146F308A3F40F9
:100410001F49328F24993F407D230CBF11863F40F6
:100420009DBD29CFDE943F40BFED2EDF76973F4044
:10043000DDBA056FDD823F407D58183F2C8C3F4070
:100440007F3333BF99993F40DD9C0A6F4E853F4013
:100450007F3333BF99993F403DBC171FDE8B3F4030
:10046000BDF4185F7A8C3F403D16091F8B843F40D6
:100470003DE1FC9E707E3F40DD0D0DEF86863F40E6
:100480003F1F469F0FA33F403DFFF79EFF7B3F402E
:10049000DD42196FA18C3F40BDC6F65E637B3F40D5
:1004A0009D5AFB4EAD7D3F40FD4BE6FE25733F4020
:1004B0001D12D30E89693F403D8EF51EC77A3F401D
:1004C0003DBC171FDE8B3F409D7FE0CE3F703F401D
:1004D000BD6C055FB6823F40DD4903EFA4813F401C
:1004E000DD14F76E8A7B3F40DDF6FB6EFB7D3F40FF
:1004F000BD20E85E10743F40DD6EE86E37743F400B
:100500001DB1F78ED87B3F407DFCD33EFE693F4056
:100510009D4C274FA6933F407DD7EEBE6B773F4063
:10052000DDAADE6E556F3F401D55B38EAA593F4080
:100530009DF7CCCE7B663F40DDCFC3EEE7613F4009
:10054000BDF2C55EF9623F40BD7AD95EBD6C3F40E9
:100550005D90D82E486C3F40BD7AD95EBD6C3F405F
:100560003D67BD9EB35E3F403D0DCC9E06663F405D
:10057000BD88AD5EC4563F40BDA6A85E53543F4003
:10058000BDD4CA5E6A653F40FD95B0FE4A583F4003
:100590003DA3B39ED1593F405DF89D2EFC4E3F4098
:1005A000FD69E1FEB4703F40FD59BAFE2C5D3F404D
:1005B000BD63C8DE31643F407DB0B63E585B3F400E
:1005C0001DCD9F8EE64F3F405DEAC92EF5643F404A
:1005D000FD4993FEA4493F405D8E852EC7423F40B2
:1005E0007D4D88BE26443F401D3EA20E1F513F4018
:1005F0003D938C9E49463F40FD7E9F7EBF4F3F40CE
:10060000DDB1C8EE58643F40BD7F70DE3F383F40EB
:100610005DBCA72EDE533F409D4197CEA04B3F408F
:100620003D0B799E853C3F403D0B799E853C3F408C
:10063000BD7F70DE3F383F407D6B83BEB5413F409C
:10064000FD32827E19413F409D2A864E15433F4030
:10065000FDEFA1FEF7503F401DC4620E62313F40E6
:100660003D476F9EA3373F401D98930ECC493F40B6
:100670001D53608E29303F403DF4671EFA333F40E2
:100680003D048F1E82473F407D726D3EB9363F402C
:10069000FDF68B7EFB453F40FD5767FEAB333F4089
:1006A0005D7774AE3B3A3F40BD2C695E96343F4067
:1006B0009DF579CEFA3C3F40DD4C476EA6233F4086
:1006C0001D1E540E0F2A3F407DE36FBEF1373F40A1
:1006D000FD7C4C7E3E263F40DD8153EEC0293F40ED
:1006E0009D034ECE01273F409D1375CE893A3F4072
:1006F000DDC4336EE2193F407D444B3EA2253F40AE
:100700005DD84F2EEC273F407D0F3FBE871F3F40F7
:100710007DF143BEF8213F40BDE04B5EF0253F40F8
:100720005D8548AE42243F405DD84F2EEC273F40C8
:100730007D5B5CBE2D2E3F40FD40567E202B3F4012
:10074000BD514EDE28273F40FD2945FE94223F4003
:100750001DD9208E6C103F409DE552CE72293F403E
:100760003D91399EC81C3F407D16293E8B143F4069
:100770007D6930BE34183F409D9935CECC1A3F403C
:100780005DFD34AE7E1A3F409DB730CE5B183F40D2
:100790003DAF349E571A3F405D8C322E46193F4084
:1007A0003D81129E40093F405DC8282E64143F40A1
:1007B0007D34243E1A123F405DC13EAE601F3F4073
:1007C0003D2E0B1E97053F405D6E372EB71B3F40F9
:1007D0003D09269E04133F403DCD2F9EE6173F4026
:1007E000BD6F49DEB7243F403D5C2D1EAE163F4035
:1007F0001DE00A0E70053F403DBD089E5E043F406F
:100800009D890ECE44073F401D86190EC30C3F4004
:10081000BDD70EDE6B073F401DBB258EDD123F406E
:100820001DBB258EDD123F407D06023E03013F4089
:10083000BDD0245E68123F40FDA81B7ED40D3F4012
:100840005D14462E0A233F40FD12347E091A3F40B4
:100850009D180C4E0C063F401D681E0E340F3F4085
:100860001D510D8EA8063F403DD4191EEA0C3F4095
:100870001B94ED0DCAF63E405D40152EA00A3F4088
:100880009D64294EB2143F407DF82D3EFC163F403A
:100890001DD9208E6C103F405DE6232EF3113F40A2
:1008A0007DA526BE52133F40BDB913DEDC093F4093
:1008B0005D2904AE14023F40BBE5E2DD72F13E402B
:1008C0009D180C4E0C063F40BD84075EC2033F409E
:1008D0005D221A2E110D3F40FDC6167E630B3F4070
:0108E0009D7A
:00000001FF
Assuming the data represents a list of 64-bit floating point numbers that you want to decode, the process is to collect the appropriate number of octets and decode them as a double.
Reusing the structure you presented:
from intelhex import IntelHex
import struct
ih = IntelHex()
ih.loadhex('output.hex')
ihdict = ih.todict()
# Read all the data into a long list of int octets
data = []
startAddress = 536871952
while ihdict.get(startAddress) is not None:
data.append(ihdict.get(startAddress))
startAddress += 1
# slice the list into 8-byte bytearrays
bin_arr = [bytearray(data[n:n+8]) for n in range(0, len(data), 8)]
# unpack each bytearray as a double
# Filter for 8 byte arrays because len(data) is not divisible by 8.
# Is the data properly aligned?
doubles_list = [struct.unpack('d', b) for b in bin_arr if len(b) == 8]
print(doubles_list)
It may be worth mentioning that the above assumes a big endian byte ordering. I believe you can use < as part of the format definition to assume a little endian ordering. More information is available in the struct.unpack docs.
excuse me because my englisch is not good.
I am a tring to decode somme binary messages with unpack in python. but i have a problem
the first message look like this
from struct import *
firstMessage = b'\x00\x00\x00\x00\xff\xff\xff\x00' #without tags
decodeFirstMessage = unpack('1q',firstMessage)
print(decodeFirstMessage[0])
the second message look like this
from struct import *
secondMessage = b'*xxyyzz \x03 \x00\x00\x00\x00\xff\xff\xff\x00 tago1;' #with tags
decodeSecondMessage = unpack('7s1s1B1sq1s6s',firstMessage)
print(decodeSecondMessage [0])
for the first code i get :
72057589742960640
as answer.
for the second code i get:
unpack requires a buffer of 31 bytes
as answer.
i have tried to verify the value of format in the function unpack with this code
print(calcsize('1q'))
print(calcsize('7s1s1B1sq1s6s'))
i get:
8
and
31
I calculated the bytes myself and get
8
and
25
when i change q with b or h in "format" i get the correct value of 18 Bytes or 19 bytes with calcsize()
but for l and q i have problem
what ist wrong in my function or how can is solve this please ?
The reason for this is padding.
Read the whole doc section Byte Order, Size, and Alignment
An example:
>>> print(calcsize('1s1q'))
16
>>> print(calcsize('=1s1q'))
9
The short version is, use this for format instead:
"=7s1s1B1s1q1s6s"
The longer version is, alignment. When using default # meaning "native" for "Byte order", "Size", and "Alignment". The format is interpreted to match what layout of corresponding C struct on the platform would be. Using = the format switches to standard sizes and turns of alignment.
I am trying to read bytes from an image, and get all the int (16 bit) values from that image.
After I parsed the image header, I got to the pixel values. The values that I get when the pair of bytes are like b"\xd4\x00" is incorrect. In this case it should be 54272, not 3392.
This are parts of the code:
I use a generator to get the bytes:
import itertools
def osddef_generator(in_file):
with open(in_file, mode='rb') as f:
dat = f.read()
for byte in dat:
yield byte
def take_slice(in_generator, size):
return ''.join(str(chr(i)) for i in itertools.islice(in_generator, size))
def take_single_pixel(in_generator):
pix = itertools.islice(in_generator, 2)
hex_list = [hex(i) for i in pix]
hex_str = "".join(hex_list)[2:].replace("0x", '')
intval = int(hex_str, 16)
print("hex_list: ", hex_list)
print("hex_str: ", hex_str)
print("intval: ", intval)
After I get the header correctly using the take_slice method, I get to the part with the pixel values, where I use the take_single_pixel method.
Here, I get the bad results.
This is what I get:
hex_list: ['0xd4', '0x0']
hex_str: d40
intval: 3392
But the actual sequence of bytes that should be interpreted is: \xd4\x00, which equals to 54272, so that my hex_list = ['0xd4', '0x00'] and hex_str = d400.
Something happens when I have a sequence of bytes when the second one is \x00.
Got any ideas? Thanks!
There are much better ways of converting bytes to integters:
int.from_bytes() takes bytes input, and a byte order argument:
>>> int.from_bytes(b"\xd4\x00", 'big')
54272
>>> int.from_bytes(b"\xd4\x00", 'little')
212
The struct.unpack() function lets you convert a whole series of bytes to integers following a pattern:
>>> import struct
>>> struct.unpack('!4H', b'\xd4\x00\xd4\x00\xd4\x00\xd4\x00')
(54272, 54272, 54272, 54272)
The array module lets you read binary data representing homogenous integer data into a memory structure efficiently:
>>> array.array('H', fileobject)
However, array can't be told what byte order to use. You'd have to determine the current architecture byte order and call arr.byteswap() to reverse order if the machine order doesn't match the file order.
When reading image data, it is almost always preferable to use the struct module to do the parsing. You generally then use file.read() calls with specific sizes; if the header consists of 10 bytes, use:
headerinfo = struct.unpack('<expected header pattern for 10 bytes>', f.read(10))
and go from there. For examples, look at the Pillow / PIL image plugins source code; here is how the Blizzard Mipmap image format header is read:
def _read_blp_header(self):
self._blp_compression, = struct.unpack("<i", self.fp.read(4))
self._blp_encoding, = struct.unpack("<b", self.fp.read(1))
self._blp_alpha_depth, = struct.unpack("<b", self.fp.read(1))
self._blp_alpha_encoding, = struct.unpack("<b", self.fp.read(1))
self._blp_mips, = struct.unpack("<b", self.fp.read(1))
self._size = struct.unpack("<II", self.fp.read(8))
if self.magic == b"BLP1":
# Only present for BLP1
self._blp_encoding, = struct.unpack("<i", self.fp.read(4))
self._blp_subtype, = struct.unpack("<i", self.fp.read(4))
self._blp_offsets = struct.unpack("<16I", self.fp.read(16 * 4))
self._blp_lengths = struct.unpack("<16I", self.fp.read(16 * 4))
Because struct.unpack() always returns tuples, you can assign individual elements in a tuple to name1, name2, ... names on the left-hand size, including single_name, = assignments to extract a single result.
The separate set of read calls above could also be compressed into fewer calls:
comp, enc, adepth, aenc, mips, *size = struct.unpack("<i4b2I", self.fp.read(16))
if self.magic == b"BLP1":
# Only present for BLP1
enc, subtype = struct.unpack("<2i", self.fp.read(8))
followed by specific attribute assignments.
I have a large string more than 256 bits and and I need to byte swap it by 32 bits. But the string is in a hexadecimal base. When I looked at numpy and array modules I couldnt find the right syntax as to how to do the coversion. Could someone please help me?
An example:(thought the data is much longer.I can use pack but then I would have to convert the little endian to decimal and then to big endian first which seems like a waste):
Input:12345678abcdeafa
Output:78563412faeacdab
Convert the string to bytes, unpack big-endian 32-bit and pack little-endian 32-bit (or vice versa) and convert back to a string:
#!python3
import binascii
import struct
Input = b'12345678abcdeafa'
Output = b'78563412faeacdab'
def convert(s):
s = binascii.unhexlify(s)
a,b = struct.unpack('>LL',s)
s = struct.pack('<LL',a,b)
return binascii.hexlify(s)
print(convert(Input),Output)
Output:
b'78563412faeacdab' b'78563412faeacdab'
Generalized for any string with length multiple of 4:
import binascii
import struct
Input = b'12345678abcdeafa'
Output = b'78563412faeacdab'
def convert(s):
if len(s) % 4 != 0:
raise ValueError('string length not multiple of 4')
s = binascii.unhexlify(s)
f = '{}L'.format(len(s)//4)
dw = struct.unpack('>'+f,s)
s = struct.pack('<'+f,*dw)
return binascii.hexlify(s)
print(convert(Input),Output)
If they really are strings, just do string operations on them?
>>> input = "12345678abcdeafa"
>>> input[7::-1]+input[:7:-1]
'87654321afaedcba'
My take:
slice the string in N digit chunks
reverse each chunk
concatenate everything
Example:
>>> source = '12345678abcdeafa87654321afaedcba'
>>> # small helper to slice the input in 8 digit chunks
>>> chunks = lambda iterable, sz: [iterable[i:i+sz]
for i in range(0, len(iterable), sz)]
>>> swap = lambda source, sz: ''.join([chunk[::-1]
for chunk in chunks(source, sz)])
Output asked in the original question:
>>> swap(source, 8)
'87654321afaedcba12345678abcdeafa'
It is easy to adapt in order to match the required output after icktoofay edit:
>>> swap(swap(source, 8), 2)
'78563412faeacdab21436587badcaeaf'
A proper implementation probably should check if len(source) % 8 == 0.