From 480131e327e1bfc185ee73213b68622009cae904 Mon Sep 17 00:00:00 2001
From: Ethanfel <ethan.fel@ts-pc.fr>
Date: Thu, 19 Mar 2026 00:19:44 +0100
Subject: [PATCH] Add load_full_data method to reconstruct data from DB

Replaces slow JSON file parsing with fast DB queries for file loading.
Returns the same dict structure as load_json (top-level + batch_data +
history_tree).

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
---
 db.py | 42 ++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 42 insertions(+)

diff --git a/db.py b/db.py
index 7a9e2cc..9e79eb0 100644
--- a/db.py
+++ b/db.py
@@ -405,6 +405,48 @@ class ProjectDB:
                 pass
             raise
 
+    # ------------------------------------------------------------------
+    # Full data reconstruction (replaces load_json for DB-backed files)
+    # ------------------------------------------------------------------
+
+    def load_full_data(self, project_name: str, file_name: str) -> dict | None:
+        """Reconstruct the full data dict from DB, matching load_json format.
+
+        Returns None if the project or file doesn't exist in the DB.
+        Result has the same structure as a JSON file: top-level keys +
+        batch_data list + history_tree dict.
+        """
+        t0 = time.time()
+        df = self.get_data_file_by_names(project_name, file_name)
+        if not df:
+            return None
+
+        # Start with top-level keys
+        data = df.get("top_level", {})
+        if isinstance(data, str):
+            data = json.loads(data)
+
+        # Load all sequences as batch_data
+        rows = self.conn.execute(
+            "SELECT data FROM sequences WHERE data_file_id = ? ORDER BY sequence_number",
+            (df["id"],),
+        ).fetchall()
+        batch_data = []
+        for row in rows:
+            seq = json.loads(row["data"])
+            self._migrate_lora_keys(seq)
+            batch_data.append(seq)
+        data["batch_data"] = batch_data
+
+        # Load history tree
+        tree = self.get_history_tree(df["id"])
+        if tree:
+            data["history_tree"] = tree
+
+        logger.info("load_full_data %s/%s (%d seqs): %.3fs",
+                     project_name, file_name, len(batch_data), time.time() - t0)
+        return data
+
     # ------------------------------------------------------------------
     # Query helpers (for REST API)
     # ------------------------------------------------------------------