removing unneccessary tests

utils/tests/test_linkage.py

@@ -1,115 +1,13 @@
-import numpy as np
 import pandas as pd
 import pytest
 
 from utils.constants import BASE_FILEPATH
-from utils.linkage import (
-    calculate_row_similarity,
-    calculate_string_similarity,
-    deduplicate_perfect_matches,
-    row_matches,
-)
+from utils.linkage import deduplicate_perfect_matches
 
 """
 Module for testing functions in linkage.py
 """
 
-# Creating a test for calculate_row_similarity and row_matches
-
-# to put in data:
-d = {
-    "name": ["bob von rosevich", "anantarya smith", "bob j vonrosevich"],
-    "address": [
-        "3 Blue Drive, Chicago",
-        "4 Blue Drive, Chicago",
-        "8 Fancy Way, Chicago",
-    ],
-}
-
-test_df = pd.DataFrame(data=d)
-
-
-@pytest.fixture
-def row_similarity_scen_1():
-    return test_df
-
-
-@pytest.fixture
-def row_similarity_scen_2():
-    return test_df
-
-
-def test_row_similarity_scen_1(row_similarity_scen_1):
-    wrong = calculate_row_similarity(
-        row_similarity_scen_1.iloc[[0]],
-        row_similarity_scen_1.iloc[[1]],
-        np.array([0.8, 0.2]),
-        calculate_string_similarity,
-    )
-    right = calculate_row_similarity(
-        row_similarity_scen_1.iloc[[0]],
-        row_similarity_scen_1.iloc[[2]],
-        np.array([0.8, 0.2]),
-        calculate_string_similarity,
-    )
-
-    assert right > wrong
-
-
-def test_row_similarity_scen_2(row_similarity_scen_2):
-    wrong = calculate_row_similarity(
-        row_similarity_scen_2.iloc[[0]],
-        row_similarity_scen_2.iloc[[1]],
-        np.array([0.2, 0.8]),
-        calculate_string_similarity,
-    )
-    right = calculate_row_similarity(
-        row_similarity_scen_2.iloc[[0]],
-        row_similarity_scen_2.iloc[[2]],
-        np.array([0.2, 0.8]),
-        calculate_string_similarity,
-    )
-
-    assert right < wrong
-
-
-d2 = {
-    "name": [
-        "bob von rosevich",
-        "anantarya smith",
-        "bob j vonrosevich",
-        "missy elliot",
-        "mr johnson",
-        "quarantin directino",
-        "missy eliot",
-        "joseph johnson",
-    ],
-    "address": [
-        "3 Blue Drive, Chicago",
-        "4 Blue Drive, Chicago",
-        "8 Fancy Way, Chicago",
-        "8 Fancy Way, Evanston",
-        "17 Regular Road, Chicago",
-        "42 Hollywood Boulevard, Chicago",
-        "8 Fancy Way, Evanston",
-        "17 Regular Road, Chicago",
-    ],
-}
-test_df2 = pd.DataFrame(data=d2)
-
-
-@pytest.fixture
-def row_match_scen1():
-    return test_df2
-
-
-def test_row_matches(row_match_scen1):
-    res = row_matches(
-        row_match_scen1, np.array([0.8, 0.2]), 0.9, calculate_string_similarity
-    )
-
-    assert res == {0: [2], 1: [], 2: [], 3: [6], 4: [], 5: [], 6: [], 7: []}
-
 
 # Test for dedupe function
 @pytest.fixture