Parsing Binary files that contains BCD (Binary Coded Decimal) values using Python Numpy
I have a binary file that has some fields encoded as BCD (Binary Coded Decimal). Example as below.
14 75 26 58 87 7F (Raw bytes in hex format).
I am using (np.void, 6) to read and convert from binary file and below is the output I am getting.
b'x14x75x26x58x87x7F'
But I would like to get the output as '14752658877', without the fill character 'F' using numpy.
Below is the code:
with open (filename, "rb") as f:
while True:
chunk = f.read(chunksize)
if (chunk):
dt = np.dtype([('a','b'), ('b', '>i4'), ('c', 'S15'),('d', np.str, 7),
('e', 'S7'), ('f', np.void, 6)])
x = np.frombuffer (chunk, dtype=dt)
print (x)
else:
break
Also, the input file contains many fixed length binary records. What is the efficient way to convert and store it as ascii file using numpy.
python numpy
asked Nov 21 at 9:28
Raj KB
184
|
show 1 more comment
I have a binary file that has some fields encoded as BCD (Binary Coded Decimal). Example as below.
14 75 26 58 87 7F (Raw bytes in hex format).
I am using (np.void, 6) to read and convert from binary file and below is the output I am getting.
b'x14x75x26x58x87x7F'
But I would like to get the output as '14752658877', without the fill character 'F' using numpy.
Below is the code:
with open (filename, "rb") as f:
while True:
chunk = f.read(chunksize)
if (chunk):
dt = np.dtype([('a','b'), ('b', '>i4'), ('c', 'S15'),('d', np.str, 7),
('e', 'S7'), ('f', np.void, 6)])
x = np.frombuffer (chunk, dtype=dt)
print (x)
else:
break
Also, the input file contains many fixed length binary records. What is the efficient way to convert and store it as ascii file using numpy.
python numpy
asked Nov 21 at 9:28
Raj KB
184
1
Show the example code.
– Ricardo Branco
Nov 21 at 10:42
below is the code:with open (filename, "rb") as f: while True: chunk = f.read(chunksize) if (chunk): dt = np.dtype([('a','b'), ('b', '>i4'), ('c', 'S15'),('d', np.str, 7), ('e', 'S7'), ('f', np.void, 6)]) x = np.frombuffer (chunk, dtype=dt) print (x) else: break
– Raj KB
Nov 21 at 16:24
Please edit your original question adding the above code keeping all the formatting and indentation.
– Ricardo Branco
Nov 21 at 18:10
Hi Ricardo, I have edited the original question to add the code.
– Raj KB
Nov 21 at 21:06
1
F is not a fill character. It is part of the hex value.
– Matt Messersmith
Nov 21 at 21:10
|
show 1 more comment
I have a binary file that has some fields encoded as BCD (Binary Coded Decimal). Example as below.
14 75 26 58 87 7F (Raw bytes in hex format).
I am using (np.void, 6) to read and convert from binary file and below is the output I am getting.
b'x14x75x26x58x87x7F'
But I would like to get the output as '14752658877', without the fill character 'F' using numpy.
Below is the code:
with open (filename, "rb") as f:
while True:
chunk = f.read(chunksize)
if (chunk):
dt = np.dtype([('a','b'), ('b', '>i4'), ('c', 'S15'),('d', np.str, 7),
('e', 'S7'), ('f', np.void, 6)])
x = np.frombuffer (chunk, dtype=dt)
print (x)
else:
break
Also, the input file contains many fixed length binary records. What is the efficient way to convert and store it as ascii file using numpy.
python numpy
asked Nov 21 at 9:28
Raj KB
184
I have a binary file that has some fields encoded as BCD (Binary Coded Decimal). Example as below.
14 75 26 58 87 7F (Raw bytes in hex format).
I am using (np.void, 6) to read and convert from binary file and below is the output I am getting.
b'x14x75x26x58x87x7F'
But I would like to get the output as '14752658877', without the fill character 'F' using numpy.
Below is the code:
with open (filename, "rb") as f:
while True:
chunk = f.read(chunksize)
if (chunk):
dt = np.dtype([('a','b'), ('b', '>i4'), ('c', 'S15'),('d', np.str, 7),
('e', 'S7'), ('f', np.void, 6)])
x = np.frombuffer (chunk, dtype=dt)
print (x)
else:
break
Also, the input file contains many fixed length binary records. What is the efficient way to convert and store it as ascii file using numpy.
python numpy
python numpy
asked Nov 21 at 9:28
Raj KB
184
asked Nov 21 at 9:28
Raj KB
184
edited Nov 21 at 21:05
asked Nov 21 at 9:28
Raj KB
184
asked Nov 21 at 9:28
Raj KB
184
asked Nov 21 at 9:28
Raj KB
184
184
1
Show the example code.
– Ricardo Branco
Nov 21 at 10:42
below is the code:with open (filename, "rb") as f: while True: chunk = f.read(chunksize) if (chunk): dt = np.dtype([('a','b'), ('b', '>i4'), ('c', 'S15'),('d', np.str, 7), ('e', 'S7'), ('f', np.void, 6)]) x = np.frombuffer (chunk, dtype=dt) print (x) else: break
– Raj KB
Nov 21 at 16:24
Please edit your original question adding the above code keeping all the formatting and indentation.
– Ricardo Branco
Nov 21 at 18:10
Hi Ricardo, I have edited the original question to add the code.
– Raj KB
Nov 21 at 21:06
1
F is not a fill character. It is part of the hex value.
– Matt Messersmith
Nov 21 at 21:10
|
show 1 more comment
1
Show the example code.
– Ricardo Branco
Nov 21 at 10:42
below is the code:with open (filename, "rb") as f: while True: chunk = f.read(chunksize) if (chunk): dt = np.dtype([('a','b'), ('b', '>i4'), ('c', 'S15'),('d', np.str, 7), ('e', 'S7'), ('f', np.void, 6)]) x = np.frombuffer (chunk, dtype=dt) print (x) else: break
– Raj KB
Nov 21 at 16:24
Please edit your original question adding the above code keeping all the formatting and indentation.
– Ricardo Branco
Nov 21 at 18:10
Hi Ricardo, I have edited the original question to add the code.
– Raj KB
Nov 21 at 21:06
1
F is not a fill character. It is part of the hex value.
– Matt Messersmith
Nov 21 at 21:10
1
1
Show the example code.
– Ricardo Branco
Nov 21 at 10:42
Show the example code.
– Ricardo Branco
Nov 21 at 10:42
below is the code:with open (filename, "rb") as f: while True: chunk = f.read(chunksize) if (chunk): dt = np.dtype([('a','b'), ('b', '>i4'), ('c', 'S15'),('d', np.str, 7), ('e', 'S7'), ('f', np.void, 6)]) x = np.frombuffer (chunk, dtype=dt) print (x) else: break
– Raj KB
Nov 21 at 16:24
below is the code:with open (filename, "rb") as f: while True: chunk = f.read(chunksize) if (chunk): dt = np.dtype([('a','b'), ('b', '>i4'), ('c', 'S15'),('d', np.str, 7), ('e', 'S7'), ('f', np.void, 6)]) x = np.frombuffer (chunk, dtype=dt) print (x) else: break
– Raj KB
Nov 21 at 16:24
Please edit your original question adding the above code keeping all the formatting and indentation.
– Ricardo Branco
Nov 21 at 18:10
Please edit your original question adding the above code keeping all the formatting and indentation.
– Ricardo Branco
Nov 21 at 18:10
Hi Ricardo, I have edited the original question to add the code.
– Raj KB
Nov 21 at 21:06
Hi Ricardo, I have edited the original question to add the code.
– Raj KB
Nov 21 at 21:06
1
1
F is not a fill character. It is part of the hex value.
– Matt Messersmith
Nov 21 at 21:10
F is not a fill character. It is part of the hex value.
– Matt Messersmith
Nov 21 at 21:10
|
show 1 more comment
1 Answer
1
active
oldest
votes
I don't know if numpy can somehow accelerate this, but a specalized function can be quickly constructed:
fastDict = {16*(i//10)+(i%10):i for i in range(100)}
def bcdToInteger(bcd):
result = 0
while bcd and bcd[0] in fastDict:
result *= 100
result += fastDict[bcd[0]]
bcd = bcd[1:]
if bcd and bcd[0] & 0xf0 <= 0x90:
result *= 10
result += bcd[0]>>4
if bcd[0] & 0xf <= 9:
result *= 10
result += bcd[0] & 0x0f
return result
>>> print (bcdToInteger(b'x14x75x26x58x87x7F')) # your sequence
14752658877
>>> print (bcdToInteger(b'x12x34xA0')) # first invalid nibble ends
1234
>>> print (bcdToInteger(b'x00x00x99')) # and so does an end of string
99
>>> print (bcdToInteger(b'x1F')) # a single nibble value
1
As long as you keep feeding it valid BCD bytes, it multiplies the result by 100 and adds the two new digits. Only the final byte needs some further inspection: if the highest nibble is valid, the result thus far gets multiplied by 10 and that nibble gets added. If the lowest nibble is valid as well, this is repeated.
The fastDict is to speed things up. It's a dictionary that returns the correct value for all 100 hex bytes from 00 to 99 so the number of actual calculations is as small as possible. You can do without the dictionary, but that means you have to do the comparisons and calculations in the if block for every single byte.
answered Nov 21 at 22:24
usr2564301
17.6k73270
Thanks for the solution. I am using binascii.hexlify(bcdvalue).decode('utf-8').rstrip('f') to get the preferred result. But I am looking for highly efficient solution as I have many such columns. Our daily record volumes are nearly 1 Billion records.
– Raj KB
Nov 22 at 9:29
@RajKB: Well, my solution seems pretty efficient to me. As you can see in some other answers, these use an expensive bit-shift-and-compare twice per byte; and my code avoids that. Yet even faster code could be written using a custom extension in C, but I'm not going to attempt that.
– usr2564301
Nov 22 at 10:40
Hi, I am trying your solution. But I got the below error while running the code. Can you please check. File "<ipython-input-9-6b5645ff319b>", line 7, in bcdToInteger if bcd and bcd[0] & 0xf0 <= 0x90: TypeError: unsupported operand type(s) for &: 'str' and 'int'
– Raj KB
Nov 22 at 16:38
Please ignore the above comment.
– Raj KB
Nov 22 at 16:46
Yes it did. Thanks alot for your answer.
– Raj KB
Nov 23 at 10:16
|
show 1 more comment
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I don't know if numpy can somehow accelerate this, but a specalized function can be quickly constructed:
fastDict = {16*(i//10)+(i%10):i for i in range(100)}
def bcdToInteger(bcd):
result = 0
while bcd and bcd[0] in fastDict:
result *= 100
result += fastDict[bcd[0]]
bcd = bcd[1:]
if bcd and bcd[0] & 0xf0 <= 0x90:
result *= 10
result += bcd[0]>>4
if bcd[0] & 0xf <= 9:
result *= 10
result += bcd[0] & 0x0f
return result
>>> print (bcdToInteger(b'x14x75x26x58x87x7F')) # your sequence
14752658877
>>> print (bcdToInteger(b'x12x34xA0')) # first invalid nibble ends
1234
>>> print (bcdToInteger(b'x00x00x99')) # and so does an end of string
99
>>> print (bcdToInteger(b'x1F')) # a single nibble value
1
As long as you keep feeding it valid BCD bytes, it multiplies the result by 100 and adds the two new digits. Only the final byte needs some further inspection: if the highest nibble is valid, the result thus far gets multiplied by 10 and that nibble gets added. If the lowest nibble is valid as well, this is repeated.
The fastDict is to speed things up. It's a dictionary that returns the correct value for all 100 hex bytes from 00 to 99 so the number of actual calculations is as small as possible. You can do without the dictionary, but that means you have to do the comparisons and calculations in the if block for every single byte.
answered Nov 21 at 22:24
usr2564301
17.6k73270
Thanks for the solution. I am using binascii.hexlify(bcdvalue).decode('utf-8').rstrip('f') to get the preferred result. But I am looking for highly efficient solution as I have many such columns. Our daily record volumes are nearly 1 Billion records.
– Raj KB
Nov 22 at 9:29
@RajKB: Well, my solution seems pretty efficient to me. As you can see in some other answers, these use an expensive bit-shift-and-compare twice per byte; and my code avoids that. Yet even faster code could be written using a custom extension in C, but I'm not going to attempt that.
– usr2564301
Nov 22 at 10:40
Hi, I am trying your solution. But I got the below error while running the code. Can you please check. File "<ipython-input-9-6b5645ff319b>", line 7, in bcdToInteger if bcd and bcd[0] & 0xf0 <= 0x90: TypeError: unsupported operand type(s) for &: 'str' and 'int'
– Raj KB
Nov 22 at 16:38
Please ignore the above comment.
– Raj KB
Nov 22 at 16:46
Yes it did. Thanks alot for your answer.
– Raj KB
Nov 23 at 10:16
|
show 1 more comment
I don't know if numpy can somehow accelerate this, but a specalized function can be quickly constructed:
fastDict = {16*(i//10)+(i%10):i for i in range(100)}
def bcdToInteger(bcd):
result = 0
while bcd and bcd[0] in fastDict:
result *= 100
result += fastDict[bcd[0]]
bcd = bcd[1:]
if bcd and bcd[0] & 0xf0 <= 0x90:
result *= 10
result += bcd[0]>>4
if bcd[0] & 0xf <= 9:
result *= 10
result += bcd[0] & 0x0f
return result
>>> print (bcdToInteger(b'x14x75x26x58x87x7F')) # your sequence
14752658877
>>> print (bcdToInteger(b'x12x34xA0')) # first invalid nibble ends
1234
>>> print (bcdToInteger(b'x00x00x99')) # and so does an end of string
99
>>> print (bcdToInteger(b'x1F')) # a single nibble value
1
As long as you keep feeding it valid BCD bytes, it multiplies the result by 100 and adds the two new digits. Only the final byte needs some further inspection: if the highest nibble is valid, the result thus far gets multiplied by 10 and that nibble gets added. If the lowest nibble is valid as well, this is repeated.
The fastDict is to speed things up. It's a dictionary that returns the correct value for all 100 hex bytes from 00 to 99 so the number of actual calculations is as small as possible. You can do without the dictionary, but that means you have to do the comparisons and calculations in the if block for every single byte.
answered Nov 21 at 22:24
usr2564301
17.6k73270
Thanks for the solution. I am using binascii.hexlify(bcdvalue).decode('utf-8').rstrip('f') to get the preferred result. But I am looking for highly efficient solution as I have many such columns. Our daily record volumes are nearly 1 Billion records.
– Raj KB
Nov 22 at 9:29
@RajKB: Well, my solution seems pretty efficient to me. As you can see in some other answers, these use an expensive bit-shift-and-compare twice per byte; and my code avoids that. Yet even faster code could be written using a custom extension in C, but I'm not going to attempt that.
– usr2564301
Nov 22 at 10:40
Hi, I am trying your solution. But I got the below error while running the code. Can you please check. File "<ipython-input-9-6b5645ff319b>", line 7, in bcdToInteger if bcd and bcd[0] & 0xf0 <= 0x90: TypeError: unsupported operand type(s) for &: 'str' and 'int'
– Raj KB
Nov 22 at 16:38
Please ignore the above comment.
– Raj KB
Nov 22 at 16:46
Yes it did. Thanks alot for your answer.
– Raj KB
Nov 23 at 10:16
|
show 1 more comment
I don't know if numpy can somehow accelerate this, but a specalized function can be quickly constructed:
fastDict = {16*(i//10)+(i%10):i for i in range(100)}
def bcdToInteger(bcd):
result = 0
while bcd and bcd[0] in fastDict:
result *= 100
result += fastDict[bcd[0]]
bcd = bcd[1:]
if bcd and bcd[0] & 0xf0 <= 0x90:
result *= 10
result += bcd[0]>>4
if bcd[0] & 0xf <= 9:
result *= 10
result += bcd[0] & 0x0f
return result
>>> print (bcdToInteger(b'x14x75x26x58x87x7F')) # your sequence
14752658877
>>> print (bcdToInteger(b'x12x34xA0')) # first invalid nibble ends
1234
>>> print (bcdToInteger(b'x00x00x99')) # and so does an end of string
99
>>> print (bcdToInteger(b'x1F')) # a single nibble value
1
As long as you keep feeding it valid BCD bytes, it multiplies the result by 100 and adds the two new digits. Only the final byte needs some further inspection: if the highest nibble is valid, the result thus far gets multiplied by 10 and that nibble gets added. If the lowest nibble is valid as well, this is repeated.
The fastDict is to speed things up. It's a dictionary that returns the correct value for all 100 hex bytes from 00 to 99 so the number of actual calculations is as small as possible. You can do without the dictionary, but that means you have to do the comparisons and calculations in the if block for every single byte.
answered Nov 21 at 22:24
usr2564301
17.6k73270
I don't know if numpy can somehow accelerate this, but a specalized function can be quickly constructed:
fastDict = {16*(i//10)+(i%10):i for i in range(100)}
def bcdToInteger(bcd):
result = 0
while bcd and bcd[0] in fastDict:
result *= 100
result += fastDict[bcd[0]]
bcd = bcd[1:]
if bcd and bcd[0] & 0xf0 <= 0x90:
result *= 10
result += bcd[0]>>4
if bcd[0] & 0xf <= 9:
result *= 10
result += bcd[0] & 0x0f
return result
>>> print (bcdToInteger(b'x14x75x26x58x87x7F')) # your sequence
14752658877
>>> print (bcdToInteger(b'x12x34xA0')) # first invalid nibble ends
1234
>>> print (bcdToInteger(b'x00x00x99')) # and so does an end of string
99
>>> print (bcdToInteger(b'x1F')) # a single nibble value
1
As long as you keep feeding it valid BCD bytes, it multiplies the result by 100 and adds the two new digits. Only the final byte needs some further inspection: if the highest nibble is valid, the result thus far gets multiplied by 10 and that nibble gets added. If the lowest nibble is valid as well, this is repeated.
The fastDict is to speed things up. It's a dictionary that returns the correct value for all 100 hex bytes from 00 to 99 so the number of actual calculations is as small as possible. You can do without the dictionary, but that means you have to do the comparisons and calculations in the if block for every single byte.
answered Nov 21 at 22:24
usr2564301
17.6k73270
answered Nov 21 at 22:24
usr2564301
17.6k73270
answered Nov 21 at 22:24
usr2564301
17.6k73270
answered Nov 21 at 22:24
usr2564301
17.6k73270
17.6k73270
Thanks for the solution. I am using binascii.hexlify(bcdvalue).decode('utf-8').rstrip('f') to get the preferred result. But I am looking for highly efficient solution as I have many such columns. Our daily record volumes are nearly 1 Billion records.
– Raj KB
Nov 22 at 9:29
@RajKB: Well, my solution seems pretty efficient to me. As you can see in some other answers, these use an expensive bit-shift-and-compare twice per byte; and my code avoids that. Yet even faster code could be written using a custom extension in C, but I'm not going to attempt that.
– usr2564301
Nov 22 at 10:40
Hi, I am trying your solution. But I got the below error while running the code. Can you please check. File "<ipython-input-9-6b5645ff319b>", line 7, in bcdToInteger if bcd and bcd[0] & 0xf0 <= 0x90: TypeError: unsupported operand type(s) for &: 'str' and 'int'
– Raj KB
Nov 22 at 16:38
Please ignore the above comment.
– Raj KB
Nov 22 at 16:46
Yes it did. Thanks alot for your answer.
– Raj KB
Nov 23 at 10:16
|
show 1 more comment
Thanks for the solution. I am using binascii.hexlify(bcdvalue).decode('utf-8').rstrip('f') to get the preferred result. But I am looking for highly efficient solution as I have many such columns. Our daily record volumes are nearly 1 Billion records.
– Raj KB
Nov 22 at 9:29
@RajKB: Well, my solution seems pretty efficient to me. As you can see in some other answers, these use an expensive bit-shift-and-compare twice per byte; and my code avoids that. Yet even faster code could be written using a custom extension in C, but I'm not going to attempt that.
– usr2564301
Nov 22 at 10:40
Hi, I am trying your solution. But I got the below error while running the code. Can you please check. File "<ipython-input-9-6b5645ff319b>", line 7, in bcdToInteger if bcd and bcd[0] & 0xf0 <= 0x90: TypeError: unsupported operand type(s) for &: 'str' and 'int'
– Raj KB
Nov 22 at 16:38
Please ignore the above comment.
– Raj KB
Nov 22 at 16:46
Yes it did. Thanks alot for your answer.
– Raj KB
Nov 23 at 10:16
Thanks for the solution. I am using binascii.hexlify(bcdvalue).decode('utf-8').rstrip('f') to get the preferred result. But I am looking for highly efficient solution as I have many such columns. Our daily record volumes are nearly 1 Billion records.
– Raj KB
Nov 22 at 9:29
Thanks for the solution. I am using binascii.hexlify(bcdvalue).decode('utf-8').rstrip('f') to get the preferred result. But I am looking for highly efficient solution as I have many such columns. Our daily record volumes are nearly 1 Billion records.
– Raj KB
Nov 22 at 9:29
@RajKB: Well, my solution seems pretty efficient to me. As you can see in some other answers, these use an expensive bit-shift-and-compare twice per byte; and my code avoids that. Yet even faster code could be written using a custom extension in C, but I'm not going to attempt that.
– usr2564301
Nov 22 at 10:40
@RajKB: Well, my solution seems pretty efficient to me. As you can see in some other answers, these use an expensive bit-shift-and-compare twice per byte; and my code avoids that. Yet even faster code could be written using a custom extension in C, but I'm not going to attempt that.
– usr2564301
Nov 22 at 10:40
Hi, I am trying your solution. But I got the below error while running the code. Can you please check. File "<ipython-input-9-6b5645ff319b>", line 7, in bcdToInteger if bcd and bcd[0] & 0xf0 <= 0x90: TypeError: unsupported operand type(s) for &: 'str' and 'int'
– Raj KB
Nov 22 at 16:38
Hi, I am trying your solution. But I got the below error while running the code. Can you please check. File "<ipython-input-9-6b5645ff319b>", line 7, in bcdToInteger if bcd and bcd[0] & 0xf0 <= 0x90: TypeError: unsupported operand type(s) for &: 'str' and 'int'
– Raj KB
Nov 22 at 16:38
Please ignore the above comment.
– Raj KB
Nov 22 at 16:46
Please ignore the above comment.
– Raj KB
Nov 22 at 16:46
Yes it did. Thanks alot for your answer.
– Raj KB
Nov 23 at 10:16
Yes it did. Thanks alot for your answer.
– Raj KB
Nov 23 at 10:16
|
show 1 more comment
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Show the example code.
– Ricardo Branco
Nov 21 at 10:42
below is the code:with open (filename, "rb") as f: while True: chunk = f.read(chunksize) if (chunk): dt = np.dtype([('a','b'), ('b', '>i4'), ('c', 'S15'),('d', np.str, 7), ('e', 'S7'), ('f', np.void, 6)]) x = np.frombuffer (chunk, dtype=dt) print (x) else: break
– Raj KB
Nov 21 at 16:24
Please edit your original question adding the above code keeping all the formatting and indentation.
– Ricardo Branco
Nov 21 at 18:10
Hi Ricardo, I have edited the original question to add the code.
– Raj KB
Nov 21 at 21:06
1
F is not a fill character. It is part of the hex value.
– Matt Messersmith
Nov 21 at 21:10