Initial SQL-only 1C adapter baseline

2026-07-22 03:03:47 +03:00
commit e2503b77e7
545 changed files with 184711 additions and 0 deletions
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+#!/usr/bin/env python3
+from __future__ import annotations
+
+import argparse
+import json
+from pathlib import Path
+from typing import Any
+
+
+ACTION_PRIORITY = {
+    "run_before_after_learning_for_parameter": 10,
+    "collect_allowed_values_and_smoke": 20,
+    "run_before_after_learning_for_named_scalar": 30,
+    "learn_reference_write_rule": 80,
+    "do_not_generic_write": 100,
+}
+
+
+def load_rows(path: Path) -> tuple[str, list[dict[str, Any]]]:
+    data = json.loads(path.read_text(encoding="utf-8"))
+    schema = str(data.get("schema") or "")
+    if schema == "onec_form_write_scalar_registry.v1":
+        return schema, [row for row in data.get("scalars", []) if isinstance(row, dict)]
+    if schema == "onec_form_write_enum_registry.v1":
+        return schema, [row for row in data.get("properties", []) if isinstance(row, dict)]
+    raise SystemExit(f"Unsupported registry schema: {schema or '<missing>'}")
+
+
+def example_selector(example: dict[str, Any]) -> dict[str, Any]:
+    target = example.get("target")
+    section = example.get("effective_section") or example.get("requested_section")
+    selector: dict[str, Any] = {}
+    if section == "commands":
+        selector["command"] = target
+    elif section == "attributes":
+        selector["attribute"] = target
+    else:
+        selector["element"] = target
+    return selector
+
+
+def learning_case(row: dict[str, Any], index: int) -> dict[str, Any]:
+    examples = row.get("examples") if isinstance(row.get("examples"), list) else []
+    example = examples[0] if examples and isinstance(examples[0], dict) else {}
+    counts = row.get("counts") if isinstance(row.get("counts"), dict) else {}
+    action = str(row.get("recommended_action") or row.get("risk") or "")
+    return {
+        "id": f"learn-{index:03d}",
+        "action": action,
+        "property": row.get("property"),
+        "marker": row.get("marker"),
+        "parameter_index": row.get("parameter_index"),
+        "value_type": row.get("value_type"),
+        "entries": counts.get("entries"),
+        "observed_values": row.get("observed_values"),
+        "selector": example_selector(example),
+        "write_path": example.get("write_path"),
+        "current_value": example.get("old"),
+        "manual_step": {
+            "target": example.get("target"),
+            "section": example.get("effective_section") or example.get("requested_section"),
+            "presentation": example.get("presentation"),
+            "instruction": "Измени это свойство в конфигураторе на другое допустимое значение, сохрани форму, затем запусти capture_after/diff/infer.",
+        },
+    }
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(description="Build ordered before/after learning plan from 1C write registries.")
+    parser.add_argument("--registry", type=Path, required=True, help="Scalar or enum registry JSON path.")
+    parser.add_argument("--output", type=Path, required=True, help="Output learning plan JSON path.")
+    parser.add_argument("--limit", type=int, default=50, help="Maximum cases to include.")
+    parser.add_argument(
+        "--include-actions",
+        nargs="*",
+        default=["run_before_after_learning_for_parameter", "collect_allowed_values_and_smoke", "run_before_after_learning_for_named_scalar"],
+        help="Recommended actions/risks to include.",
+    )
+    args = parser.parse_args()
+
+    schema, rows = load_rows(args.registry)
+    include = set(args.include_actions)
+    filtered = [row for row in rows if str(row.get("recommended_action") or row.get("risk") or "") in include]
+    filtered.sort(
+        key=lambda row: (
+            ACTION_PRIORITY.get(str(row.get("recommended_action") or row.get("risk") or ""), 50),
+            -int((row.get("counts") if isinstance(row.get("counts"), dict) else {}).get("entries") or 0),
+            str(row.get("marker")),
+            str(row.get("parameter_index")),
+            str(row.get("property")),
+        )
+    )
+    cases = [learning_case(row, index + 1) for index, row in enumerate(filtered[: args.limit])]
+    result = {
+        "schema": "onec_form_write_learning_plan.v1",
+        "status": "ok",
+        "source_registry": str(args.registry),
+        "source_schema": schema,
+        "counts": {
+            "cases": len(cases),
+            "available": len(filtered),
+            "included_actions": sorted(include),
+        },
+        "workflow": ["capture_before", "manual_configurator_change", "capture_after", "diff", "infer_rule", "smoke_rule"],
+        "cases": cases,
+    }
+    args.output.parent.mkdir(parents=True, exist_ok=True)
+    args.output.write_text(json.dumps(result, ensure_ascii=False, indent=2) + "\n", encoding="utf-8")
+    print(json.dumps({"schema": result["schema"], "status": "ok", "counts": result["counts"], "path": str(args.output)}, ensure_ascii=False, indent=2))
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())