{"id":7150,"date":"2021-04-26T22:11:08","date_gmt":"2021-04-26T16:41:08","guid":{"rendered":"https:\/\/nuclearrambo.com\/wordpress\/?p=7150"},"modified":"2024-10-03T15:08:54","modified_gmt":"2024-10-03T09:38:54","slug":"converting-a-binary-data-file-into-a-c-array-with-python","status":"publish","type":"post","link":"https:\/\/nuclearrambo.com\/wordpress\/converting-a-binary-data-file-into-a-c-array-with-python\/","title":{"rendered":"Converting a binary data file into a C array with a python script"},"content":{"rendered":"\n

Those working on embedded C\/C++ would know the importance of converting a binary file into a C array. I deal with raw images and ram dumps on daily basis. For example, I may be required to upload a raw image into the RAM connected to the processor for testing the rest of the code. At times, these raw images are simply some graphical elements of the user interface. My previous work flow was quite inefficient. Create an element in GIMP, export it as raw image. HxD<\/a> hex editor helps me convert the raw binary file into a compile-able C-array. A quick tool specifically made for this purpose would have been the perfect solution for me.<\/p>\n\n\n\n

I am a person who likes to remedy the situation. In this case, a quickly written Python script that generates C array from a binary file that can be compiled in any C compiler.<\/p>\n\n\n\n

Read the binary data<\/h2>\n\n\n\n

We can quickly read the binary file with numpy<\/a>. <\/em>The fromfile()<\/span> function makes our life simpler and that’s exactly what I will make use of.<\/p>\n\n\n\n

def read_file(file_name):\n    data = np.fromfile(file_name, dtype='uint8')\n    data = bytearray(data)\n    return data<\/pre>\n\n\n\n
To make the code re-usable, I prefer using functions. Who knows how large this code might grow in future. It’s always better to start with modular code. The read_file() function quickly reads the binary file. I am interpreting the file as a bunch of 8 bit data set. You could interpret it as an int32, float or even double. <\/em>A file is always a bunch of bytes. Its upon us on how it should be interpreted. Finally, I am interpreting the data as a python bytearray<\/a> <\/em>and return the same.<\/p>\n\n\n\n
Writing the data as ascii<\/h2>\n\n\n\n
A C source file is ascii text. We now need to convert our bytearray <\/em>into ascii text. For this, I would be writing another function to do all this. After all, we would also need to format our ascii text. Packing all these tasks into a function would simply look cleaner. Okay, enough talking, lets get to work.<\/p>\n\n\n\n
def write_c_array(file_name, data):\n    c_file = open(file_name + \".c\", \"w\")\n    array_content = \"{{{}}}\".format(\", \".join(bytes_to_c_arr(data)))\n    c_file.write(array_content)<\/pre>\n\n\n\n
Our write_c_array() <\/em>function takes two arguments; the file name and the data. Inside the function, we first create writable file with the file name passed in the argument. The bytes_to_c_array() <\/em>function takes bytearray and returns ascii text that’s representative of the corresponding byte. The usual form is “0xhh” where h can be any value in range of 0 to F.<\/p>\n\n\n\n
def bytes_to_c_arr(data):\n    return [format(b, '#04x') for b in data]\n<\/pre>\n\n\n\n
Finally, we do two things. One is to add a comma and a whitespace after each hex string. Secondly, we encapsulate the whole strong between curly braces. Since, you already know that in C we can define an array with unsigned char x[3] = {0x9, 0x4, 0x1}; <\/em>Similarly, we need to add those curly braces to comply with the C syntax rules.<\/p>\n\n\n\n
Beware, if your file is large, you will end up with a multi-mega-byte C file that requires a better text editor such as notepad++. On linux you should open this with something like Vim. Gedit would simply struggle to open large files.<\/p>\n\n\n\n