Parse values from a block of text based on specific keys [closed]

If your block of text is this string:

text = 'Problem Category: Human Endeavors Problem Subcategory: Space ExplorationProblem Type: Failure to LaunchSoftware Version: 9.8.77.omni.3Problem Details: Issue with signal barrier chamber.'

Then

import re
names = ['Problem Category', 'Problem Subcategory', 'Problem Type', 'Software Version', 'Problem Details']

text = 'Problem Category: Human Endeavors Problem Subcategory: Space ExplorationProblem Type: Failure to LaunchSoftware Version: 9.8.77.omni.3Problem Details: Issue with signal barrier chamber.'

pat = r'({}):'.format('|'.join(names))
data = dict(zip(*[iter(re.split(pat, text, re.MULTILINE)[1:])]*2))
print(data)

yields the dict

{'Problem Category': ' Human Endeavors ',
 'Problem Details': ' Issue with signal barrier chamber.',
 'Problem Subcategory': ' Space Exploration',
 'Problem Type': ' Failure to Launch',
 'Software Version': ' 9.8.77.omni.3'}

So you could assign

text = df_dict['NOTE_DETAILS'][0]
...
df_dict['NOTE_DETAILS'][0] = data

and then you could access the subcategories with dict indexing:

df_dict['NOTE_DETAILS'][0]['Problem_Category']

Caution, though. Deeply nested dicts/DataFrames of lists of dicts is usually a bad design. As the Zen of Python says, Flat is better than nested.

Given that you know the keywords ahead of time, partition the text into "current keyword", "remaining text", then continue to partition the remaining text with the next keyword.

# get input from somewhere
raw = 'Problem Category: Human Endeavors Problem Subcategory: Space ExplorationProblem Type: Failure to LaunchSoftware Version: 9.8.77.omni.3Problem Details: Issue with signal barrier chamber.'

# these are the keys, in order, without the colon, that will be captured
keys = ['Problem Category', 'Problem Subcategory', 'Problem Type', 'Software Version', 'Problem Details']
prev_key = None
remaining = raw
out = {}

for key in keys:
    # get the value from before the key and after the key
    prev_value, _, remaining = remaining.partition(key + ':')

    # start storing values after the first iteration, since we need to partition the second key to get the first value
    if prev_key is not None:
        out[prev_key] = prev_value.strip()

    # what key to store next iteration
    prev_key = key

# capture the final value (since it lags behind the parse loop)
out[prev_key] = remaining.strip()

# out now contains the parsed values, print it out nicely
for key in keys:
    print('{}: {}'.format(key, out[key]))

This prints:

Problem Category: Human Endeavors
Problem Subcategory: Space Exploration
Problem Type: Failure to Launch
Software Version: 9.8.77.omni.3
Problem Details: Issue with signal barrier chamber.

I hate and fear regex, so here's a solution using only built-in methods.

#splits a string using multiple delimiters.
def multi_split(s, delims):
    strings = [s]
    for delim in delims:
        strings = [x for s in strings for x in s.split(delim) if x]
    return strings

s = "Problem Category: Human Endeavors Problem Subcategory: Space ExplorationProblem Type: Failure to LaunchSoftware Version: 9.8.77.omni.3Problem Details: Issue with signal barrier chamber."
categories = ["Problem Category", "Problem Subcategory", "Problem Type", "Software Version", "Problem Details"]
headers = [category + ": " for category in categories]

details = multi_split(s, headers)
print details

details_dict = dict(zip(categories, details))
print details_dict

Result (newlines added by me for readability):

[
    'Human Endeavors ', 
    'Space Exploration', 
    'Failure to Launch', 
    '9.8.77.omni.3', 
    'Issue with signal barrier chamber.'
]

{
    'Problem Subcategory': 'Space Exploration', 
    'Problem Details': 'Issue with signal barrier chamber.', 
    'Problem Category': 'Human Endeavors ', 
    'Software Version': '9.8.77.omni.3', 
    'Problem Type': 'Failure to Launch'
}

That's just the job for general BNF parsing which handles ambiguity nicely. I used perl and Marpa, a general BNF parser. Hope this helps.

use 5.010;
use strict;
use warnings;

use Marpa::R2;

my $g = Marpa::R2::Scanless::G->new( { source => \(<<'END_OF_SOURCE'),

    :default ::= action => [ name, values ]

    pairs ::= pair+

    pair ::= name (' ') value

    name ::= 'Problem Category:'
    name ::= 'Problem Subcategory:'
    name ::= 'Problem Type:'
    name ::= 'Software Version:'
    name ::= 'Problem Details:'

    value ::= [\s\S]+

    :discard ~ whitespace
    whitespace ~ [\s]+

END_OF_SOURCE
} );

my $input = <<EOI;
Problem Category: Human Endeavors Problem Subcategory: Space ExplorationProblem Type: Failure to LaunchSoftware Version: 9.8.77.omni.3Problem Details: Issue with signal barrier chamber.
EOI

my $ast = ${ $g->parse( \$input ) };

my @pairs;

ast_traverse($ast);

for my $pair (@pairs){
    my ($name, $value) = @$pair;
    say "$name = $value";
}

sub ast_traverse{
    my $ast = shift;
    if (ref $ast){
        my ($id, @children) = @$ast;
        if ($id eq 'pair'){

            my ($name, $value) = @children;

            chop $name->[1];

            shift @$value;
            $value = join('', @$value);
            chomp $value;

            push @pairs, [ $name->[1], '"' . $value . '"' ];
        }
        else {
            ast_traverse($_) for @children;
        }
    }
}

This prints:

Problem Category = "Human Endeavors "
Problem Subcategory = "Space Exploration"
Problem Type = "Failure to Launch"
Software Version = "9.8.77.omni.3"
Problem Details = "Issue with signal barrier chamber."