Visualize company sentiment (#422)

Updates the tab and widget "Stimmung"

tests/ui/data_elements_test.py

@@ -4,6 +4,7 @@ import pandas as pd
 from sqlalchemy.orm import Session
 
 from aki_prj23_transparenzregister.ui import data_elements
+from aki_prj23_transparenzregister.utils.enum_types import SentimentLabel
 
 
 def test_import() -> None:
@@ -86,3 +87,27 @@ def test_get_finance_data(full_db: Session) -> None:
         }
     )
     pd.testing.assert_frame_equal(finance_df, test_data)
+
+
+def test_get_news_of_one_company0(news_db: Session) -> None:
+    """Tests what happens if no sentiment can be found."""
+    selected_company_id = 100
+    assert data_elements.get_news_of_one_company(selected_company_id, news_db).empty
+
+
+def test_get_news_of_one_company1(news_db: Session) -> None:
+    """Tests if the sentiments can be collected for a company specified."""
+    selected_company_id = 2
+    sentiment_df = data_elements.get_news_of_one_company(selected_company_id, news_db)
+    assert sentiment_df is not None
+    assert sentiment_df.to_dict(orient="records") == [
+        {
+            "overall_sentiment_certainty": 0.95,
+            "overall_sentiment_label": SentimentLabel.POSITIVE,
+            "source_domain": "example-news.com",
+            "source_url": "http://example-news.com/ai-revolution",
+            "times_named": 2,
+            "timestamp": pd.Timestamp("2023-11-01 15:30:00"),
+            "title": "AI Revolution in Tech",
+        },
+    ]

tests/ui/sentiment_elements_test.py

@@ -0,0 +1,32 @@
+"""Tests for sentiment ui elements."""
+
+from sqlalchemy.orm import Session
+
+from aki_prj23_transparenzregister.ui import data_elements, sentiment_elements
+
+
+def test_sentiment_layout(news_db: Session) -> None:
+    """Checks if the sentiment tab layout of the company page can be created."""
+    selected_company_id = 1
+    sentiment_elements.sentiment_layout(selected_company_id, news_db)
+
+
+def test_sentiment_trend_figure(news_db: Session) -> None:
+    """Checks if the sentiment trend graph can be created."""
+    n = 10
+    company_id = 1
+    articles = data_elements.get_news_of_one_company(company_id, news_db)
+
+    articles["overall_sentiment_label"] = articles["overall_sentiment_label"].apply(
+        lambda _: _.value
+    )
+
+    articles = articles.sort_values(by=["timestamp"], ascending=True)
+    articles["rolling_mean"] = articles["overall_sentiment_label"].rolling(n).mean()
+    sentiment_elements.sentiment_trend_figure(articles, n)
+
+
+def test_sentiment_gauge_figure() -> None:
+    """Checks if the sentiment gauge graph can be created."""
+    sentiment_score = 0.2
+    sentiment_elements.sentiment_gauge_figure(sentiment_score)