how to pass portions of text to tuple/list in python based on word

Question

i have following sample text and need to pass all lines of text to tuple/list based on a word "ALL Banks Report".. the raw text as follows

%Bank PARSED MESSAGE FILE
%VERSION   : PIL 98.7
%nex MODULE   : SIL 98

2018 Jan 31  16:44:53.050 ALL Banks Report SBI
name id ID = 0,  ID = 58
    Freq = 180

    conserved NEXT:
      message c1 : ABC1 : 
          {
            XYZ2
           }
2018 Jan 31  16:44:43.050 ALL Banks Report HDFC
conserved LATE:

World ::= 
{
  Asia c1 : EastAsia : 
      {
        India
       }
}

...like so many repitions i want to pass tuple/List/array based on a word "ALL Banks Report" so that in list[0] the following goes

2018 Jan 31  16:44:53.050 ALL Banks Report SBI
name id ID = 0,  ID = 58
    Freq = 180

    conserved NEXT:
      message c1 : ABC1 : 
          {
            XYZ2
           }

and in list[1] the rest goes like below

2018 Jan 31  16:44:43.050 ALL Banks Report HDFC
conserved LATE:

World ::= 
{
  Asia c1 : EastAsia : 
      {
        India
       }
}

Answer 1

IMO, there's no particular advantage to the use of pyparsing here. It's easy to process this file using an old-fashioned algorithm.

output_list = []
items = []
with open('spark.txt') as spark:
    for line in spark:
        line = line.rstrip()
        if line and not line.startswith('%'):
            if 'ALL Banks Report' in line:
                if items:
                    output_list.extend(items)
                items = [line]
            else:
                items.append(line)
if items:
    output_list.extend(items)

for item in output_list:
    print (item)

Output:

2018 Jan 31  16:44:53.050 ALL Banks Report SBI
name id ID = 0,  ID = 58
    Freq = 180
    conserved NEXT:
      message c1 : ABC1 :
          {
            XYZ2
           }
2018 Jan 31  16:44:43.050 ALL Banks Report HDFC
conserved LATE:
World ::=
{
  Asia c1 : EastAsia :
      {
        India
       }
}

Incidentally, I have avoided the use of list as an identifier, since it's a Python keyword.