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convert cobol binary file to text file using python script

Pkrishna9494
New Contributor

I'm using below script  cobol binary file how to call it in script snap

Input :צנקננפקנעצףסץס q4Œ @ @@@ ננץ@@@@@@@@@@@@@@@@@@@@@@@@@@@2 <נננננ@@@@@@@@@@@@@@@ @@@@@@@@@@@@@@@@0 e2<  @@@@סננסעע

Out put:

" 00000000000000000000000000000000000607.","0047077581"," 00000000000000000000000000000000000001."," 0000000000000000000000072075.8900000000","0","0"," 0000000000000000000000000000.0000000000",""," 000.","","1240207","0"," 0000000000000000000000000000.0000000000"," 00000000000000000000000000000000000005.",""," 00000000000000000000000000000000032023."," 00000000000000000000000000000000000000."," 00000000000000000000000000000000000000.",""," 00000000000000000000000000000000000000.",""," 00000000000000000000000000000001240101."," 0000000000000000000000000625.6600000000"," 00000000000000000000000000000000000052."," 00000000000000000000000000000000000037.","","10","01","22",""

-----------------------------------------------------------------------------------------------------------------------------------

 

import struct

feild_widths = [10, 20, 30]

record_size = sum(field_widths)

with open('cobol_binary_file.dat', 'rb') as binary_file:
with open('output.txt', 'w') as text_file:
while True:
record_data = binary_file.read(record_size)
if not record_data:
break #End of file
#This converts binary data into feild
fields = [record_data[i:i+width].decode('utf-8').strip() for i, width in enumerate(field_widths)]
#Here it converts binary data to text file and writes it to output file.
text_data = ','.join(fields)
text_file.write(text_data + '\n')
print("Conversion complete. Output written to output.txt")

-

Thank you

2 REPLIES 2

GanguP
New Contributor III

Does this work with packed fields

 

Thanks,

GP

CelvinKlassen
New Contributor

 

To call a COBOL binary file in a script and process it as you described, you can use a Python script to read the binary data, decode it, and write the output to a text file. Here’s an enhanced version of your script to handle the binary data more effectively:

Python Script to Process COBOL Binary File

  1. Import necessary modules:

    • struct for handling binary data.
    • os for file operations.
  2. Define field widths:

    • Create a list of field widths according to your COBOL file layout.
  3. Read and process the binary file:

    • Open the COBOL binary file in read-binary mode.
    • Open an output text file in write mode.
    • Read the binary data and decode it based on the defined field widths.
    • Write the decoded data to the output text file.

Here is the complete script:

import struct

# Define field widths according to your COBOL file layout
field_widths = [10, 20, 30] # Update this list based on your actual field widths
record_size = sum(field_widths)

# Open the COBOL binary file in read-binary mode
with open('cobol_binary_file.dat', 'rb') as binary_file:
# Open the output text file in write mode
with open('output.txt', 'w') as text_file:
while True:
# Read a record of size record_size from the binary file
record_data = binary_file.read(record_size)
if not record_data:
break # End of file

# Decode the binary data into fields based on the field widths
fields = []
offset = 0
for width in field_widths:
field = record_data[offset:offset + width].decode('utf-8').strip()
fields.append(field)
offset += width

# Join the fields with commas and write to the output text file
text_data = ','.join(fields)
text_file.write(text_data + '\n')

print("Conversion complete. Output written to output.txt")

How to Run the Script

  1. Ensure Python is installed on your machine.
  2. Place your COBOL binary file (e.g., cobol_binary_file.dat) in the same directory as your script.
  3. Run the script from the command line or an IDE.

Notes:

  • Field Widths: Make sure to adjust the field_widths list to match the actual widths of the fields in your COBOL file.
  • Character Encoding: The script assumes UTF-8 encoding. Adjust if your file uses a different encoding.
  • Error Handling: Add error handling as needed for robustness, especially if dealing with potentially corrupted files or unexpected data formats.

Experts Opinion.