From 5889d6ac8ee7f71728d9fac7e508a7254c90af72 Mon Sep 17 00:00:00 2001
From: AditiR-42 <aditisanram@gmail.com>
Date: Wed, 11 Dec 2024 20:52:35 -0500
Subject: [PATCH] increase recommend coverage

---
 .../tests/integration/test_api_endpoints.py   | 115 +++++++++++++++++-
 1 file changed, 113 insertions(+), 2 deletions(-)

diff --git a/src/models/tests/integration/test_api_endpoints.py b/src/models/tests/integration/test_api_endpoints.py
index edba5e59..590a3da5 100644
--- a/src/models/tests/integration/test_api_endpoints.py
+++ b/src/models/tests/integration/test_api_endpoints.py
@@ -3,8 +3,9 @@
 import io
 from unittest.mock import patch, MagicMock
 from api_service.api.routers.summarize import process_pdf, get_grade
+from api_service.api.routers.recommend import filter_dataframe, GenerativeModel
 import pandas as pd
-from fastapi import UploadFile, HTTPException
+from fastapi import UploadFile
 from io import BytesIO
 
 BASE_URL = "http://localhost:9000" 
@@ -514,4 +515,114 @@ async def test_get_grade_success(mock_privacy_grader):
         "overall_grade": "A",
         "overall_score": 95,
         "category_scores": {"Category1": 90, "Category2": 100}
-    }
\ No newline at end of file
+    }
+
+@pytest.fixture
+def sample_df():
+    return pd.DataFrame({
+        'Service': ['App1', 'App2', 'App3'],
+        'Genre': ['Social', 'Music', 'Productivity'],
+        'privacy_rating': ['A', 'B', 'C'],
+        'Content Rating': ['Everyone', 'Teen', 'Mature'],
+        'app_score': [4.5, 4.0, 3.5],
+        'Installs': [1000000, 500000, 100000],
+        'num_ratings': [10000, 5000, 1000],
+        'num_reviews': [5000, 2500, 500],
+        'Free': [True, False, True],
+        'Contains Ads': [True, False, True]
+    })
+
+@pytest.fixture
+def mock_model():
+    mock = MagicMock(spec=GenerativeModel)
+    mock.generate_content.return_value = MagicMock(text="social")
+    return mock
+
+def test_filter_by_genre(sample_df, mock_model):
+    with patch('your_module.df', sample_df), \
+         patch('your_module.model', mock_model):
+        criteria = {'Genre': 'Social Media'}
+        result = filter_dataframe(criteria)
+        assert len(result) == 1
+        assert result.iloc[0]['Service'] == 'App1'
+
+def test_filter_by_privacy_rating(sample_df):
+    with patch('your_module.df', sample_df):
+        criteria = {'privacy_rating': 'B'}
+        result = filter_dataframe(criteria)
+        assert len(result) == 2
+        assert set(result['Service']) == {'App1', 'App2'}
+
+def test_filter_by_content_rating(sample_df):
+    with patch('your_module.df', sample_df):
+        criteria = {'Content Rating': 'Teen'}
+        result = filter_dataframe(criteria)
+        assert len(result) == 1
+        assert result.iloc[0]['Service'] == 'App2'
+
+def test_filter_by_app_score(sample_df):
+    with patch('your_module.df', sample_df):
+        criteria = {'app_score': 4.0}
+        result = filter_dataframe(criteria)
+        assert len(result) == 2
+        assert set(result['Service']) == {'App1', 'App2'}
+
+def test_filter_by_installs(sample_df):
+    with patch('your_module.df', sample_df):
+        criteria = {'Installs': 500000}
+        result = filter_dataframe(criteria)
+        assert len(result) == 2
+        assert set(result['Service']) == {'App1', 'App2'}
+
+def test_filter_by_num_ratings(sample_df):
+    with patch('your_module.df', sample_df):
+        criteria = {'num_ratings': 5000}
+        result = filter_dataframe(criteria)
+        assert len(result) == 2
+        assert set(result['Service']) == {'App1', 'App2'}
+
+def test_filter_by_num_reviews(sample_df):
+    with patch('your_module.df', sample_df):
+        criteria = {'num_reviews': 2500}
+        result = filter_dataframe(criteria)
+        assert len(result) == 2
+        assert set(result['Service']) == {'App1', 'App2'}
+
+def test_filter_by_free(sample_df):
+    with patch('your_module.df', sample_df):
+        criteria = {'Free': 'True'}
+        result = filter_dataframe(criteria)
+        assert len(result) == 2
+        assert set(result['Service']) == {'App1', 'App3'}
+
+def test_filter_by_contains_ads(sample_df):
+    with patch('your_module.df', sample_df):
+        criteria = {'Contains Ads': 'False'}
+        result = filter_dataframe(criteria)
+        assert len(result) == 1
+        assert result.iloc[0]['Service'] == 'App2'
+
+def test_multiple_criteria(sample_df):
+    with patch('your_module.df', sample_df):
+        criteria = {
+            'privacy_rating': 'B',
+            'Free': 'False',
+            'app_score': 3.5
+        }
+        result = filter_dataframe(criteria)
+        assert len(result) == 1
+        assert result.iloc[0]['Service'] == 'App2'
+
+def test_no_matching_results(sample_df):
+    with patch('your_module.df', sample_df):
+        criteria = {'privacy_rating': 'D'}
+        result = filter_dataframe(criteria)
+        assert len(result) == 0
+
+def test_service_criterion_updates_genre_and_privacy_rating(sample_df):
+    with patch('your_module.df', sample_df):
+        criteria = {'Service': 'App2'}
+        result = filter_dataframe(criteria)
+        assert len(result) == 1
+        assert result.iloc[0]['Genre'] == 'Music'
+        assert result.iloc[0]['privacy_rating'] == 'B'