Seperate main.py and main functionalities

python3/distance.py

@@ -0,0 +1,68 @@
+"""
+
+"""
+
+def recursive_lev(a:str, b:str) -> int:
+    if len(a) == 0: return len(b)
+    if len(b) == 0: return len(a)
+    if a[0] == b[0]: return recursive_lev(a[1:], b[1:])
+    return 1 + min([
+        recursive_lev(a[1:], b),
+        recursive_lev(a, b[1:]),
+        recursive_lev(a[1:], b[1:])
+    ])
+
+
+def iterative_lev(a:str, b:str, print_matrix:bool = False) -> int:
+    a_len = len(a)
+    b_len = len(b)
+
+    if a_len == 0: return len(b)
+    if b_len == 0: return len(a)
+
+    d = [[0 for _ in range(b_len + 1)] for _ in range(a_len + 1)]
+
+    for i in range(1, a_len + 1):
+        d[i][0] = i
+
+    for j in range(1, b_len + 1):
+        d[0][j] = j
+
+    for i in range(1, a_len + 1):
+        for j in range(1, b_len + 1):
+            sub_cost = 1
+            if a[i - 1] == b[j - 1]: sub_cost = 0
+            d[i][j] = min([
+                d[i - 1][j] + 1,
+                d[i][j - 1] + 1,
+                d[i - 1][j - 1] + sub_cost
+            ])
+
+    if print_matrix:
+        for i in range(a_len + 1):
+            for j in range(b_len + 1):
+                print(d[i][j], end=' ')
+            print()
+        print(f'Distance: {d[a_len][b_len]}')
+    return d[a_len][b_len]
+
+
+def simplyfy(s_input:str) -> str:
+    from unicodedata import normalize
+    normalized = normalize('NFKD', s_input)
+    reencoded = normalized.encode('ascii', 'ignore').decode('utf-8')
+    return reencoded.lower()
+
+
+def similarity_percentage(a:str, b:str) -> float:
+    if len(a) == 0 or len(b) == 0: return 0
+    a = simplyfy(a)
+    b = simplyfy(b)
+    return 1 - iterative_lev(a, b) / max(len(a), len(b))
+
+
+def word_in_word(word:str, word_in:str) -> bool:
+    if len(word) == 0 or len(word_in) == 0: return False
+    word = simplyfy(word)
+    word_in = simplyfy(word_in)
+    return word in word_in

python3/main.py

@@ -1,67 +1,8 @@
-def recursive_lev(a:str, b:str) -> int:
-    if len(a) == 0: return len(b)
-    if len(b) == 0: return len(a)
-    if a[0] == b[0]: return recursive_lev(a[1:], b[1:])
-    return 1 + min([
-        recursive_lev(a[1:], b),
-        recursive_lev(a, b[1:]),
-        recursive_lev(a[1:], b[1:])
-    ])
+from distance import similarity_percentage, word_in_word, simplyfy
+import os
 
-
-def iterative_lev(a:str, b:str, print_matrix:bool = False) -> int:
-    a_len = len(a)
-    b_len = len(b)
-
-    if a_len == 0: return len(b)
-    if b_len == 0: return len(a)
-
-    d = [[0 for _ in range(b_len + 1)] for _ in range(a_len + 1)]
-
-    for i in range(1, a_len + 1):
-        d[i][0] = i
-
-    for j in range(1, b_len + 1):
-        d[0][j] = j
-
-    for i in range(1, a_len + 1):
-        for j in range(1, b_len + 1):
-            sub_cost = 1
-            if a[i - 1] == b[j - 1]: sub_cost = 0
-            d[i][j] = min([
-                d[i - 1][j] + 1,
-                d[i][j - 1] + 1,
-                d[i - 1][j - 1] + sub_cost
-            ])
-
-    if print_matrix:
-        for i in range(a_len + 1):
-            for j in range(b_len + 1):
-                print(d[i][j], end=' ')
-            print()
-        print(f'Distance: {d[a_len][b_len]}')
-    return d[a_len][b_len]
-
-
-def simplyfy(s_input:str) -> str:
-    from unicodedata import normalize
-    normalized = normalize('NFKD', s_input)
-    reencoded = normalized.encode('ascii', 'ignore').decode('utf-8')
-    return reencoded.lower()
-
-
-def similarity_percentage(a:str, b:str) -> float:
-    if len(a) == 0 or len(b) == 0: return 0
-    a = simplyfy(a)
-    b = simplyfy(b)
-    return 1 - iterative_lev(a, b) / max(len(a), len(b))
-
-
-def word_in_word(word:str, word_in:str) -> bool:
-    if len(word) == 0 or len(word_in) == 0: return False
-    word = simplyfy(word)
-    word_in = simplyfy(word_in)
-    return word in word_in
+SCRIPT_DIR = os.path.dirname(os.path.realpath(__file__))
+NEWS_PATH = os.path.join(SCRIPT_DIR, '../local_data/security_news.csv')
 
 
 def check_word_eng_dict(word:str):
@@ -74,7 +15,7 @@ def check_word_eng_dict(word:str):
 
 
 def check_word_news(word:str, limit:int = 0.72) -> None:
-    with open('../../local_data/security_news.csv', 'r') as file:
+    with open(NEWS_PATH, 'r') as file:
         for line in file:
             line = line.split(';;')
             title_pieces = line[0].split()