From 581882a1494235acca661c3910eee70fec4bd292 Mon Sep 17 00:00:00 2001
From: Vladimir <axwitech@gmail.com>
Date: Tue, 7 Jun 2022 17:11:43 +0300
Subject: [PATCH] fix: Fix for the linting issue fix: Fir for the test failure

---
 failure_analysis/failure_analysis.py | 31 ----------------------------
 utest/test_similarity.py             | 17 ++++-----------
 2 files changed, 4 insertions(+), 44 deletions(-)

diff --git a/failure_analysis/failure_analysis.py b/failure_analysis/failure_analysis.py
index 8ff6a69..a9d3742 100644
--- a/failure_analysis/failure_analysis.py
+++ b/failure_analysis/failure_analysis.py
@@ -2,11 +2,8 @@
 import itertools
 import os
 import sys
-from difflib import SequenceMatcher 
 from pathlib import Path
 
-import jellyfish
-import Levenshtein  # type: ignore
 import numpy as np
 import pandas as pd  # type: ignore
 from lxml import etree  # type: ignore
@@ -60,34 +57,15 @@ def score_failures(failures):
     jaros, a list of jaro scores between two items in a tuple
     levens, a list of levenshtein ratio scores between two items in a tuple
     """
-    # sm_ratios = []
     coss = []
-    # jaccards = []
-    # jaros = []
-    # levens = []
-
     for failure in failures:
         str1 = failure[0]
         str2 = failure[1]
 
-        # sm = SequenceMatcher(a=str1, b=str2)
-        # sm_ratios.append(sm.ratio())
-
         vectorizer = CountVectorizer().fit_transform([str1, str2])
         vectors = vectorizer.toarray()
         cos = cosine_sim_vectors(vectors[0], vectors[1])
         coss.append(cos)
-
-        # jaccard = jaccard_similarity(str1, str2)
-        # jaccards.append(jaccard)
-
-        # jaro = jellyfish.jaro_similarity(str1, str2)
-        # jaros.append(jaro)
-
-        # leven = Levenshtein.ratio(str1, str2)
-        # levens.append(leven)
-
-    # return sm_ratios, coss, jaccards, jaros, levens
     return coss
 
 
@@ -113,11 +91,7 @@ def run(path: str):
         filenames,
         testnames,
         classnames,
-        # sm_ratios,
         coss,
-        # jaccards,
-        # jaros,
-        # levens,
         failures,
     ]
 
@@ -134,15 +108,10 @@ def run(path: str):
         "testname2",
         "suitename1",
         "suitename2",
-        # "sm_ratio",
         "cos",
-        # "jaccard",
-        # "jaro",
-        # "leven",
         "failure1",
         "failure2",
     ]
-    # df = df[["failure1", "suitename2", "testname2", "filename2", "cos", "leven"]]
     df = df[["failure1", "suitename2", "testname2", "filename2", "cos"]]
     for failure in np.unique(df["failure1"].values):
         print("============== FAILURE START =================")
diff --git a/utest/test_similarity.py b/utest/test_similarity.py
index 66cac9c..0525074 100644
--- a/utest/test_similarity.py
+++ b/utest/test_similarity.py
@@ -26,11 +26,11 @@ def test_02():
 """
 
 EXPECTED_OUTPUT_END = """============== FAILURE END =================
-                                         cos  leven
+                                         cos
 suitename2    testname2 filename2                  
-tests.test_me test_02   failing_01_.xml  1.0    1.0
-                        failing_02_.xml  1.0    1.0
-                        failing_03_.xml  1.0    1.0
+tests.test_me test_02   failing_01_.xml  1.0
+                        failing_02_.xml  1.0
+                        failing_03_.xml  1.0
 """  # noqa: W291
 
 
@@ -50,18 +50,9 @@ def test_cosine_sim_vectors():
 
 def test_score_failures():
     failures = list(itertools.permutations(["i am failure 1", "i am failure 2", "i am failure 3", "i am failure 4"], 2))
-    #sm_ratios, coss, jaccards, jaros, levens = score_failures(failures)
     coss = score_failures(failures)
-    #sum_sm = np.sum(sm_ratios)
     sum_coss = np.sum(coss)
-    #sum_jaccard = np.sum(jaccards)
-    #sum_jaros = np.sum(jaros)
-    #sum_levens = np.sum(levens)
-    #assert sum_sm > 0
     assert sum_coss > 0
-    #assert sum_jaccard > 0
-    #assert sum_jaros > 0
-    #assert sum_levens > 0
 
 
 def test_invalid_path():