From 8c76476cd3cd739a2bc645b0df900df2ee9bbf79 Mon Sep 17 00:00:00 2001
From: Dylan De Faoite <dylanseandefaoite@gmail.com>
Date: Mon, 23 Feb 2026 18:14:24 +0000
Subject: [PATCH] fix(api): broken analysis calls due to overlap in attribute
 and method names

---
 server/app.py      | 21 +++++++++++++++++----
 server/stat_gen.py | 12 ++++++------
 2 files changed, 23 insertions(+), 10 deletions(-)

diff --git a/server/app.py b/server/app.py
index 760e48d..7118f4c 100644
--- a/server/app.py
+++ b/server/app.py
@@ -55,7 +55,7 @@ def word_frequencies():
         return jsonify({"error": "No data uploaded"}), 400
     
     try:
-        return jsonify(stat_obj.content_analysis()), 200
+        return jsonify(stat_obj.get_content_analysis()), 200
     except ValueError as e:
         return jsonify({"error": f"Malformed or missing data: {str(e)}"}), 400
     except Exception as e:
@@ -80,7 +80,7 @@ def get_time_analysis():
         return jsonify({"error": "No data uploaded"}), 400
     
     try:
-        return jsonify(stat_obj.time_analysis()), 200
+        return jsonify(stat_obj.get_time_analysis()), 200
     except ValueError as e:
         return jsonify({"error": f"Malformed or missing data: {str(e)}"}), 400
     except Exception as e:
@@ -93,7 +93,7 @@ def get_user_analysis():
         return jsonify({"error": "No data uploaded"}), 400
     
     try:
-        return jsonify(stat_obj.user_analysis()), 200
+        return jsonify(stat_obj.get_user_analysis()), 200
     except ValueError as e:
         return jsonify({"error": f"Malformed or missing data: {str(e)}"}), 400
     except Exception as e:
@@ -106,13 +106,26 @@ def get_cultural_analysis():
         return jsonify({"error": "No data uploaded"}), 400
     
     try:
-        return jsonify(stat_obj.cultural_analysis()), 200
+        return jsonify(stat_obj.get_cultural_analysis()), 200
     except ValueError as e:
         return jsonify({"error": f"Malformed or missing data: {str(e)}"}), 400
     except Exception as e:
         print(traceback.format_exc())
         return jsonify({"error": f"An unexpected error occurred: {str(e)}"}), 500
+
+@app.route("/stats/interaction", methods=["GET"])
+def get_interaction_analysis():
+    if stat_obj is None:
+        return jsonify({"error": "No data uploaded"}), 400
     
+    try:
+        return jsonify(stat_obj.get_interactional_analysis()), 200
+    except ValueError as e:
+        return jsonify({"error": f"Malformed or missing data: {str(e)}"}), 400
+    except Exception as e:
+        print(traceback.format_exc())
+        return jsonify({"error": f"An unexpected error occurred: {str(e)}"}), 500
+
 @app.route('/filter/search', methods=["POST"])
 def search_dataset():
     if stat_obj is None:
diff --git a/server/stat_gen.py b/server/stat_gen.py
index 014f95f..209589b 100644
--- a/server/stat_gen.py
+++ b/server/stat_gen.py
@@ -66,14 +66,14 @@ class StatGen:
 
     # topics over time
     # emotions over time
-    def time_analysis(self) -> pd.DataFrame:
+    def get_time_analysis(self) -> pd.DataFrame:
         return {
             "events_per_day": self.temporal_analysis.posts_per_day(),
             "weekday_hour_heatmap": self.temporal_analysis.heatmap()
         }
 
     # average topic duration
-    def content_analysis(self) -> dict:
+    def get_content_analysis(self) -> dict:
         return {
             "word_frequencies": self.linguistic_analysis.word_frequencies(),
             "common_two_phrases": self.linguistic_analysis.ngrams(),
@@ -84,7 +84,7 @@ class StatGen:
     
     # average emotion per user
     # average chain length
-    def user_analysis(self) -> dict:
+    def get_user_analysis(self) -> dict:
         return {
             "top_users": self.interaction_analysis.top_users(),
             "users": self.interaction_analysis.per_user_analysis(),
@@ -94,14 +94,14 @@ class StatGen:
     # average / max thread depth
     # high engagment threads based on volume
 
-    def conversational_analysis(self) -> dict:
+    def get_interactional_analysis(self) -> dict:
         return {
-
+            "average_thread_depth": self.interaction_analysis.average_thread_depth(),
         }
     
     # detect community jargon
     # in-group and out-group linguistic markers
-    def cultural_analysis(self) -> dict:
+    def get_cultural_analysis(self) -> dict:
         return {
             "identity_markers": self.linguistic_analysis.identity_markers()
         }