style: run python linter & prettifier on backend code

server/analysis/enrichment.py

@@ -2,6 +2,7 @@ import pandas as pd
 
 from server.analysis.nlp import NLP
 
+
 class DatasetEnrichment:
     def __init__(self, df: pd.DataFrame, topics: dict):
         self.df = self._explode_comments(df)
@@ -10,7 +11,9 @@ class DatasetEnrichment:
 
     def _explode_comments(self, df) -> pd.DataFrame:
         comments_df = df[["id", "comments"]].explode("comments")
-        comments_df = comments_df[comments_df["comments"].apply(lambda x: isinstance(x, dict))]
+        comments_df = comments_df[
+            comments_df["comments"].apply(lambda x: isinstance(x, dict))
+        ]
         comments_df = pd.json_normalize(comments_df["comments"])
 
         posts_df = df.drop(columns=["comments"])
@@ -24,16 +27,16 @@ class DatasetEnrichment:
         df.drop(columns=["post_id"], inplace=True, errors="ignore")
 
         return df
-    
+
     def enrich(self) -> pd.DataFrame:
-        self.df['timestamp'] = pd.to_numeric(self.df['timestamp'], errors='raise')
-        self.df['date'] = pd.to_datetime(self.df['timestamp'], unit='s').dt.date
+        self.df["timestamp"] = pd.to_numeric(self.df["timestamp"], errors="raise")
+        self.df["date"] = pd.to_datetime(self.df["timestamp"], unit="s").dt.date
         self.df["dt"] = pd.to_datetime(self.df["timestamp"], unit="s", utc=True)
         self.df["hour"] = self.df["dt"].dt.hour
         self.df["weekday"] = self.df["dt"].dt.day_name()
-        
+
         self.nlp.add_emotion_cols()
         self.nlp.add_topic_col()
         self.nlp.add_ner_cols()
 
-        return self.df
+        return self.df