Add chase accounts + chase csv upload

backend/app/services/chase_csv.py

@@ -0,0 +1,69 @@
+import csv
+import io
+from datetime import datetime
+
+
+def parse_chase_csv(content: str, account_type: str) -> tuple[list[dict], list[str]]:
+    """Parse a Chase CSV file into transaction dicts.
+
+    Returns (rows, errors) where rows is a list of dicts with keys:
+    date, amount, category, description.
+    """
+    content = content.lstrip("\ufeff")
+    reader = csv.DictReader(io.StringIO(content))
+
+    if not reader.fieldnames:
+        return [], ["Empty CSV file"]
+
+    first_field = reader.fieldnames[0].strip()
+    if first_field == "Details":
+        return _parse_checking(reader)
+    elif first_field == "Transaction Date":
+        return _parse_credit_card(reader)
+    else:
+        return [], [f"Unrecognized CSV format (first column: '{first_field}')"]
+
+
+def _parse_checking(reader: csv.DictReader) -> tuple[list[dict], list[str]]:
+    """Chase checking/savings: Details,Posting Date,Description,Amount,Type,Balance,Check or Slip #"""
+    rows = []
+    errors = []
+    for i, row in enumerate(reader, start=2):
+        try:
+            date_str = row.get("Posting Date", "").strip()
+            description = row.get("Description", "").strip()
+            amount_str = row.get("Amount", "").strip()
+            if not date_str or not amount_str:
+                continue
+            rows.append({
+                "date": datetime.strptime(date_str, "%m/%d/%Y").date(),
+                "amount": float(amount_str),
+                "category": "Uncategorized",
+                "description": description,
+            })
+        except (ValueError, KeyError) as e:
+            errors.append(f"Row {i}: {e}")
+    return rows, errors
+
+
+def _parse_credit_card(reader: csv.DictReader) -> tuple[list[dict], list[str]]:
+    """Chase credit card: Transaction Date,Post Date,Description,Category,Type,Amount,Memo"""
+    rows = []
+    errors = []
+    for i, row in enumerate(reader, start=2):
+        try:
+            date_str = row.get("Transaction Date", "").strip()
+            description = row.get("Description", "").strip()
+            amount_str = row.get("Amount", "").strip()
+            category = row.get("Category", "").strip() or "Uncategorized"
+            if not date_str or not amount_str:
+                continue
+            rows.append({
+                "date": datetime.strptime(date_str, "%m/%d/%Y").date(),
+                "amount": float(amount_str),
+                "category": category,
+                "description": description,
+            })
+        except (ValueError, KeyError) as e:
+            errors.append(f"Row {i}: {e}")
+    return rows, errors