#!/usr/bin/env python
# coding: utf-8

# # Splitting 'ref' into book, chapter, verse and word 
# 
# The XML source data contains a tag called 'ref' which contains information related to book, chapter, verse and word. See following sniplet:
# 
# ```
#     <w role="v"
#     ref="MAT 25:10!18"
#     after=" "
#     class="verb"
#     xml:id="n40025010018"
#     lemma="κλείω"
#     normalized="ἐκλείσθη"
#     strong="2808"
#     number="singular"
#     person="third"
#     tense="aorist"
#     voice="passive"
#     mood="indicative"
#     gloss="was shut"
#     domain="079024"
#     ln="79.112"
#     morph="V-API-3S"
#     unicode="ἐκλείσθη"
#     frame="A1:n40025010020">ἐκλείσθη</w>
# ```
# 
# This small Jupyter Notebook explains how this compound variable 'ref' is split into 4 values:

# In[1]:


import re
input="MAT 25:10!18"
x= re.sub(r'[!: ]'," ", input).split()
print (x)


# ## Explanation of the code:
# 
# The code begins by importing the regular expression module re to work with regular expressions.
# 
# * The variable input is initialized with the string "MAT 1:1!1". This string contains various punctuation marks and spaces.
# 
# * The re.sub() function is used to substitute certain characters in the input string with a space character (" "). The regular expression pattern [!: ] matches any occurrence of either a colon (:), an exclamation mark (!), or a space character. The matched characters are replaced with a space.
# 
# * The result of the substitution operation is assigned to the variable x. This variable now holds the modified string where the matched characters have been replaced with spaces.
# 
# * The split() method is then called on the modified string x. This method splits the string into a list of substrings based on whitespace. Since no specific delimiter is provided to the split() method, it uses whitespace (spaces) as the default delimiter.
# 
# * The resulting list, containing the substrings after the split operation, is printed using the print() function.

# The following site can be used to build and verify a regular expression: [regex101.com](https://regex101.com/) (choose the 'Pyton flavor') 

# In[ ]: