feat: Initial commit of Clutch-IQ project

tools/debug/debug_bomb.py

@@ -0,0 +1,26 @@
+from demoparser2 import DemoParser
+import os
+import pandas as pd
+
+demo_path = os.path.join(os.getcwd(), "data", "demos", "furia-vs-falcons-m1-inferno.dem")
+parser = DemoParser(demo_path)
+
+print("Listing events related to bomb...")
+# Check events
+# parse_events returns a list of tuples or dicts? Or a DataFrame? 
+# The previous error said 'list' object has no attribute 'head', so it returns a list of tuples/dicts?
+# Wait, usually it returns a DataFrame. Let's check type.
+events = parser.parse_events(["bomb_planted", "bomb_defused", "bomb_exploded", "round_start", "round_end"])
+print(f"Type of events: {type(events)}")
+
+if isinstance(events, list):
+    print(events[:5])
+    # Try to convert to DF
+    try:
+        df = pd.DataFrame(events)
+        print(df.head())
+        print(df['event_name'].value_counts())
+    except:
+        pass
+else:
+    print(events.head())

tools/debug/debug_fields.py

@@ -0,0 +1,19 @@
+from demoparser2 import DemoParser
+import os
+
+demo_path = os.path.join(os.getcwd(), "data", "demos", "furia-vs-falcons-m1-inferno.dem")
+parser = DemoParser(demo_path)
+
+potential_fields = ["account", "m_iAccount", "balance", "money", "cash", "score", "mvps"]
+
+print(f"Checking fields in {demo_path}...")
+
+for field in potential_fields:
+    try:
+        df = parser.parse_ticks([field], ticks=[1000]) # Check tick 1000
+        if not df.empty and field in df.columns:
+            print(f"[SUCCESS] Found field: {field}")
+        else:
+            print(f"[FAILED] Field {field} returned empty or missing column")
+    except Exception as e:
+        print(f"[ERROR] Field {field} failed: {e}")

tools/debug/debug_round_end.py

@@ -0,0 +1,13 @@
+
+from demoparser2 import DemoParser
+import pandas as pd
+
+demo_path = "data/demos/furia-vs-falcons-m3-train.dem"
+parser = DemoParser(demo_path)
+
+# Check round_end events
+events = parser.parse_events(["round_end"])
+for name, df in events:
+    if name == "round_end":
+        print("Columns:", df.columns)
+        print(df.head())