remove class mode

src/beaky/cli.py

@@ -28,17 +28,18 @@ def _verdict_str(verdict: TicketVerdict) -> str:
 
 
 _FC = 14   # field column visual width
-_VC = 24   # value column visual width
+_VC = 24   # value column visual width (dual)
-_BET_W = 1 + (_FC + 2) + 1 + (_VC + 2) + 1 + (_VC + 2) + 1  # one bet table width
+_SC = 38   # value column visual width (single classifier)
-_GAP = "  "  # space between side-by-side tables
+_BET_W  = 1 + (_FC + 2) + 1 + (_VC + 2) + 1 + (_VC + 2) + 1  # dual table width
+_BET_WS = 1 + (_FC + 2) + 1 + (_SC + 2) + 1                   # single table width
+_GAP = "  "
 
-_FIELD_LABELS: dict[str, str] = {
+_FIELD_LABELS: dict[str, str] = {"team1Name": "team1", "team2Name": "team2"}
-    "team1Name": "team1",
-    "team2Name": "team2",
-}
 _FIELD_ORDER  = ["type", "team1Name", "team2Name", "date", "league"]
 _SKIP_FIELDS  = {"ticketType"}
+
 _BLANK_ROW  = f"│{' ' * (_FC + 2)}│{' ' * (_VC + 2)}│{' ' * (_VC + 2)}│"
+_BLANK_ROWS = f"│{' ' * (_FC + 2)}│{' ' * (_SC + 2)}│"
 
 
 def _vlen(text: str) -> int:
@@ -58,9 +59,10 @@ def _bet_fields(bet: Bet) -> dict[str, str]:
     return fields
 
 
+# ── dual-column table (compare) ──────────────────────────────────────────────
+
 def _tbl_row(field: str, lval: str, ival: str) -> str:
-    label = _FIELD_LABELS.get(field, field)
+    return f"│ {_vpad(_FIELD_LABELS.get(field, field), _FC)} │ {_vpad(lval, _VC)} │ {_vpad(ival, _VC)} │"
-    return f"│ {_vpad(label, _FC)} │ {_vpad(lval, _VC)} │ {_vpad(ival, _VC)} │"
 
 
 def _tbl_sep(left: str, mid: str, right: str) -> str:
@@ -86,51 +88,76 @@ def _bet_to_lines(idx: int, link_bet: Bet | None, img_bet: Bet | None) -> list[s
         data_rows.append(_tbl_row(key, lval, ival))
 
     header = _vpad(_ansi.bold(_ansi.cyan(f" Bet {idx} ")), _BET_W)
-    return [
+    return [header, _tbl_sep("┌", "┬", "┐"), _tbl_row("", _ansi.bold("link"), _ansi.bold("image")),
-        header,
+            _tbl_sep("├", "┼", "┤"), *data_rows, _tbl_sep("└", "┴", "┘")]
-        _tbl_sep("┌", "┬", "┐"),
+
-        _tbl_row("", _ansi.bold("link classifier"), _ansi.bold("image classifier")),
+
-        _tbl_sep("├", "┼", "┤"),
+# ── single-column table (one classifier) ─────────────────────────────────────
-        *data_rows,
+
-        _tbl_sep("└", "┴", "┘"),
+def _tbl_row_s(field: str, val: str) -> str:
+    return f"│ {_vpad(_FIELD_LABELS.get(field, field), _FC)} │ {_vpad(val, _SC)} │"
+
+
+def _tbl_sep_s(left: str, mid: str, right: str) -> str:
+    return f"{left}{'─' * (_FC + 2)}{mid}{'─' * (_SC + 2)}{right}"
+
+
+def _bet_to_lines_single(idx: int, bet: Bet, col_label: str) -> list[str]:
+    fields = _bet_fields(bet)
+    keys   = [k for k in _FIELD_ORDER if k in fields] + [k for k in fields if k not in _FIELD_ORDER]
+    data_rows = [
+        _tbl_row_s(k, (v[:_SC - 1] + "…" if len(v) > _SC else v))
+        for k, v in ((k, fields[k]) for k in keys)
     ]
+    header = _vpad(_ansi.bold(_ansi.cyan(f" Bet {idx} ")), _BET_WS)
+    return [header, _tbl_sep_s("┌", "┬", "┐"), _tbl_row_s("", _ansi.bold(col_label)),
+            _tbl_sep_s("├", "┼", "┤"), *data_rows, _tbl_sep_s("└", "┴", "┘")]
 
 
-def _pad_to(lines: list[str], target: int) -> list[str]:
+# ── shared grid printer ───────────────────────────────────────────────────────
+
+def _pad_to(lines: list[str], target: int, blank: str) -> list[str]:
     result = list(lines)
     while len(result) < target:
-        result.insert(-1, _BLANK_ROW)
+        result.insert(-1, blank)
     return result
 
 
-def _print_compare(link_ticket: Ticket, img_ticket: Ticket) -> None:
+def _print_bet_grid(ticket_header: str, all_lines: list[list[str]], blank: str, bet_w: int) -> None:
-    n_link = len(link_ticket.bets)
-    n_img  = len(img_ticket.bets)
-    n_max  = max(n_link, n_img)
-
     term_w = shutil.get_terminal_size((120, 24)).columns
-    n_cols = max(1, term_w // (_BET_W + len(_GAP)))
+    n_cols = max(1, term_w // (bet_w + len(_GAP)))
-    row_w  = min(term_w, n_cols * (_BET_W + len(_GAP)) - len(_GAP) + 2)
+    row_w  = min(term_w, n_cols * (bet_w + len(_GAP)) - len(_GAP) + 2)
-
-    header = f"  Ticket {link_ticket.id}  —  link: {n_link} bet{'s' if n_link != 1 else ''}  │  img: {n_img} bet{'s' if n_img != 1 else ''}"
     print(f"\n{'═' * row_w}")
-    print(_ansi.bold(header))
+    print(_ansi.bold(f"  {ticket_header}"))
     print(f"{'═' * row_w}")
-
+    for start in range(0, len(all_lines), n_cols):
-    all_lines = [
-        _bet_to_lines(i + 1, link_ticket.bets[i] if i < n_link else None, img_ticket.bets[i] if i < n_img else None)
-        for i in range(n_max)
-    ]
-
-    for start in range(0, n_max, n_cols):
         chunk  = all_lines[start:start + n_cols]
         max_h  = max(len(b) for b in chunk)
-        padded  = [_pad_to(b, max_h) for b in chunk]
+        padded = [_pad_to(b, max_h, blank) for b in chunk]
         print()
         for row in zip(*padded):
             print("  " + _GAP.join(row))
 
 
+# ── public print functions ────────────────────────────────────────────────────
+
+def _print_compare(link_ticket: Ticket, img_ticket: Ticket) -> None:
+    n_link, n_img = len(link_ticket.bets), len(img_ticket.bets)
+    header = f"Ticket {link_ticket.id}  —  link: {n_link} bet{'s' if n_link != 1 else ''}  │  img: {n_img} bet{'s' if n_img != 1 else ''}"
+    all_lines = [
+        _bet_to_lines(i + 1, link_ticket.bets[i] if i < n_link else None, img_ticket.bets[i] if i < n_img else None)
+        for i in range(max(n_link, n_img))
+    ]
+    _print_bet_grid(header, all_lines, _BLANK_ROW, _BET_W)
+
+
+def _print_single(ticket: Ticket, col_label: str) -> None:
+    n = len(ticket.bets)
+    header = f"Ticket {ticket.id}  —  {col_label}  │  {n} bet{'s' if n != 1 else ''}"
+    all_lines = [_bet_to_lines_single(i + 1, ticket.bets[i], col_label) for i in range(n)]
+    _print_bet_grid(header, all_lines, _BLANK_ROWS, _BET_WS)
+
+
 def load_config(path: str) -> Config | None:
     with open(path) as f:
         config_dict = yaml.safe_load(f)
@@ -145,7 +172,9 @@ def main() -> None:
     parser = argparse.ArgumentParser(prog="beaky")
     parser.add_argument("--config", help="Path to config file.", default="config/application.yml")
     parser.add_argument("--id", type=int, help="Select a single ticket by id.")
-    parser.add_argument("mode", choices=["screen", "parse", "class", "resolve", "compare"], help="Mode of operation.")
+    parser.add_argument("mode", choices=["screen", "parse", "compare", "resolve"], help="Mode of operation.")
+    parser.add_argument("--classifier", choices=["link", "img", "both"], default="both",
+                        help="Which classifier to use in compare mode (default: both).")
 
     args = parser.parse_args()
     config = load_config(args.config)
@@ -179,24 +208,19 @@ def main() -> None:
         for link in selected_links:
             print(link)
 
-    if args.mode == "class":
-        classifier = LinkClassifier()
-        results = []
-        for link in selected_links:
-            results.append(classifier.classify(link))
-            ticket = results[-1]
-            print(f"\n=== Link {ticket.id} ({len(ticket.bets)} bets) ===")
-            for bet in ticket.bets:
-                print(f"  [{type(bet).__name__}]")
-                for k, v in vars(bet).items():
-                    print(f"    {k}: {v}")
-
     if args.mode == "compare":
-        linkclassifier = LinkClassifier()
+        use_link = args.classifier in ("link", "both")
+        use_img  = args.classifier in ("img",  "both")
+        linkclassifier = LinkClassifier() if use_link else None
         for link in selected_links:
-            link_ticket = linkclassifier.classify(link)
+            link_ticket = linkclassifier.classify(link) if use_link else None
-            img_ticket = img_classify([f"./data/screenshots/{link.id}.png"], ticket_id=link.id)
+            img_ticket  = img_classify([f"./data/screenshots/{link.id}.png"], ticket_id=link.id) if use_img else None
+            if args.classifier == "both" and link_ticket and img_ticket:
                 _print_compare(link_ticket, img_ticket)
+            elif link_ticket:
+                _print_single(link_ticket, "link classifier")
+            elif img_ticket:
+                _print_single(img_ticket, "image classifier")
 
     if args.mode == "resolve":
         classifier = LinkClassifier()