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If you are looking for a solution to the large number of gibberish strings you get, I don’t think you should try to keep track of the elements within the word. Why? Well, it works in a more straightforward way.
I created a simple loop that goes through all of the strings, and if they are not gibberish, they are grouped in a word.
You can use the following code to do this:
import re

def is_not_gibberish(s):
Only returns true if it does not contain gibberish.
If it contains gibberish, it returns false.
gibberish_regex = re.compile(‘[^\w]+’)
return not

def is_gibberish(s):
Returns true if the string contains gibberish.
gibberish_regex = re.compile(‘[^\w]+’)

def all_gibberish(strings):
Returns a list containing all gibberish strings.
gibberish_strings = []
for string in strings:
if is_gibberish(string):
return gibberish_strings

If you run all_gibberish(your_strings_list), you can see that it contains all gibberish strings.
Then, you can create a new list with all the word/s you care about and then remove all of the gibberish elements.
Here is an example:
raw_gibberish = all_gibberish(your_strings_list)
word_list = []
for i in range(0, len(raw_gibberish)):
if is_not_gibberish(raw_gibberish[i]):

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Oracle PostgreSQL Management Console (PMC) is a web based GUI management tool for the Oracle PostgreSQL database.
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