Finding the words or sentence that is followed by a search word and put them into a dictionary python

I have to find the words or sentence that follow a search word and put them into a dictionary. My data is in the pdf which I already extract it to a text using PyPDF2 library. I am new to NLP and I don't know how to implement this part of code.
I know how to find 1 word that follows the search word, but sometimes it is a word, sometimes it is sentence which can be identify by \n.

> the text example:
>
> ["CODE: ID\nStudy of Men's brain ID\nBased upon 16", '3 valid cases
> out of 76', '33 total cases.\n•Mean: 54695.29\n•Minimum:
> 8.00\nVariable Type: 'numeric \nHEALTH: h1 - Health in general\n xxx', ' ccc']

import PyPDF2
search_keywords=['CODE','LVI','HEALTH']


pdfFileObj = open('df.pdf', 'rb')
pdfReader = PyPDF2.PdfFileReader(pdfFileObj)
pageObj = pdfReader.getPage(5)
text=(pageObj.extractText())
text=text.split(",")
text

the out put should be :

{"CODE":"ID"
"VIS":none
"HEALTH":"h1 - Health in general"}

You can use:

• str.splitlines to split your text on newlines;
• str.split with maxsplit=1 to split your text on ':'.

Since we never split on spaces, it doesn't matter whether the value after the search word is only one word or a full sentence.

texts = ["CODE: ID\nStudy of Men's brain ID\nBased upon 16",'3 valid cases out of 76','33 total cases.\n * Mean: 54695.29\n* Minimum: 8.00\nVariable Type: numeric\n HEALTH: h1 - Health in general\nxxx', ' ccc']
search_keywords = ['CODE','LVI','HEALTH']

pairs = [tuple(word.strip() for word in sentence.split(':', maxsplit=1)) for text in texts for sentence in text.splitlines()]
pairs_dict = dict(pair for pair in pairs if len(pair) == 2)

result = {k: pairs_dict.get(k) for k in search_keywords}

print(result)
# {'CODE': 'ID', 'LVI': None, 'HEALTH': 'h1 - Health in general'}

You should read up on Regular Expressions, which are implemented in the re module in Python. Regular expressions (AKA regex) let you search for patterns of text in addition to key words. This will be useful for your NLP work. The re documentation is here, and you can find a tutorial here.

This code accomplishes what you're after:

import re
text=["CODE: ID\nStudy of Men's brain ID\nBased upon 16", '3 valid cases out of 76', '33 total cases.\n•Mean: 54695.29\n•Minimum: 8.00\nVariable Type: numeric \nHEALTH: h1 - Health in general\n xxx', ' ccc']

results={}
	
for keyword in ['CODE','LVI','HEALTH']:
	keyword_found=False
	for sentence in text:
		result=re.search(f'({keyword}): (.+)\n',sentence) #this searches for each keyword and captures any text after a colon+space and before \n
		if result:
			keyword_found=True
			results.update({result.group(1):result.group(2)})
			break
	if keyword_found==False:
		results.update({keyword:None})

print(results)

#{'CODE': ' ID', 'LVI': None, 'HEALTH': ' h1 - Health in general'}

If you need to change the search pattern, you need to modify the search parameter in re.search(f'({keyword}): (.+)\n',sentence), e.g. if you want two lines after they keyword, the search parameter would be f'({keyword}): (.+\n.+)\n'.