fix: harden Task 2 schema quality boundaries

harness/tests/test_schema_fk_annotations.py

@@ -1,10 +1,13 @@
 # ruff: noqa: DTZ001
+import warnings
 from datetime import datetime
 
+import pytest
 import yaml
 from typer.testing import CliRunner
 
 from tht.cli import app
+from tht.cli.schema_cmd import check_schema_data
 from tht.mschema.merge import find_orphans
 from tht.mschema.models import (
     Annotations,
@@ -163,6 +166,10 @@ def test_suggest_fks_skips_generic_and_ambiguous_pks(tmp_path):
     assert res.exit_code == 0, res.output
     assert "nessuna FK da suggerire" in res.output  # id generico, cod_x ambigua
     assert "cod_x" in res.output  # segnalata come ambigua saltata
+    exact = CliRunner().invoke(
+        app, ["schema", "suggest-fks", "--json", "-c", str(cfg)]
+    )
+    assert yaml.safe_load(exact.stdout)["ambiguous_columns"] == ["cod_x"]
 
     # --assume disambigua la PK multi-proprietario
     res2 = CliRunner().invoke(
@@ -205,6 +212,18 @@ def test_suggest_fks_from_sql_mines_joins(tmp_path):
     assert "ref_table: dim_patient" in res.output
 
 
+def test_suggest_fks_reports_staged_file_without_mined_joins(tmp_path):
+    cfg = _write_workspace(tmp_path)
+    staged = tmp_path / "approved"
+    staged.mkdir()
+    (staged / "no-joins.sql").write_text("SELECT 1")
+    response = CliRunner().invoke(
+        app, ["schema", "suggest-fks", "-c", str(cfg), "--from-sql", str(staged)]
+    )
+    assert response.exit_code == 0, response.output
+    assert "Minati 0 equi-join da 1 file SQL" in response.output
+
+
 def test_suggest_fks_write_merges_and_is_idempotent(tmp_path):
     cfg = _write_workspace(tmp_path)
     ann_path = tmp_path / "artifacts" / "mschema" / "annotations.yaml"
@@ -435,3 +454,59 @@ def test_schema_human_suggest_missing_config_has_original_error(tmp_path):
     assert response.exit_code == 1
     assert response.output
     assert "ERRORE:" in response.output
+
+
+def test_human_config_keeps_legacy_warning_but_json_suppresses_it(tmp_path):
+    cfg = _write_workspace(tmp_path)
+    with pytest.warns(FutureWarning, match="legacy workspace resource keys"):
+        check_schema_data(cfg)
+    with warnings.catch_warnings(record=True) as caught:
+        warnings.simplefilter("always")
+        check_schema_data(cfg, suppress_legacy_warning=True)
+    assert not [item for item in caught if issubclass(item.category, FutureWarning)]
+
+
+def test_staged_sql_enumeration_stops_at_count_sentinel(tmp_path, monkeypatch):
+    from tht.cli.schema_cmd import _MachineSchemaError, _staged_sql_files
+
+    staged = tmp_path / "staged"
+    staged.mkdir()
+    files = [staged / f"q{i:03d}.sql" for i in range(100)]
+    for path in files:
+        path.write_text("SELECT 1")
+    yielded = 0
+
+    def bounded_rglob(_self, _pattern):
+        nonlocal yielded
+        for path in files:
+            yielded += 1
+            yield path
+
+    monkeypatch.setattr(type(staged), "rglob", bounded_rglob)
+    with pytest.raises(_MachineSchemaError, match="staged_sql_too_many"):
+        _staged_sql_files([staged])
+    assert yielded == 33
+
+
+def test_staged_sql_oversize_read_is_bounded(tmp_path, monkeypatch):
+    from tht.cli.schema_cmd import _MachineSchemaError, _read_staged_sql
+
+    staged = tmp_path / "oversize.sql"
+    staged.write_bytes(b"unused")
+    reads = []
+
+    class BoundedReader:
+        def __enter__(self):
+            return self
+
+        def __exit__(self, *_args):
+            return False
+
+        def read(self, size):
+            reads.append(size)
+            return b"x" * size
+
+    monkeypatch.setattr(type(staged), "open", lambda *_args, **_kwargs: BoundedReader())
+    with pytest.raises(_MachineSchemaError, match="staged_sql_too_large"):
+        _read_staged_sql([staged])
+    assert reads == [(1 << 20) + 1]

harness/tht/cli/schema_cmd.py

@@ -1,10 +1,12 @@
-# ruff: noqa: BLE001, S110, B008
 import logging
 import warnings
+from itertools import islice
 from pathlib import Path
-from typing import TypedDict
+from typing import Literal, TypedDict
 
 import typer
+import yaml
+from pydantic import ValidationError
 
 from tht.adapters.factory import build_dwh
 from tht.cli.config_cmd import CONFIG_OPT
@@ -25,7 +27,7 @@ def _add_examples(dwh, phys, examples) -> None:
                 sampled = dwh.sample_column(
                     table_name, column_name, limit=examples.max_per_column
                 )
-            except Exception as exc:
+            except Exception as exc:  # noqa: BLE001 - sampling adapter boundary
                 logger.warning("Campionamento saltato per %s.%s: %s",
                                table_name, column_name, exc)
                 continue
@@ -87,8 +89,8 @@ def introspect_cmd(
 
         try:
             cached = PhysicalSchema.from_yaml(out)
-        except Exception:
+        except (OSError, UnicodeError, TypeError, ValueError, yaml.YAMLError, ValidationError) as exc:
-            pass  # catalogo illeggibile: procedi con la re-introspezione
+            logger.debug("Catalogo cache non leggibile: %s", exc)
         else:
             ts = cached.introspected_at
             if ts.tzinfo is None:
@@ -109,7 +111,7 @@ def introspect_cmd(
             raise RuntimeError("DWH preprocessing failed")
         out = physical_path(cfg)
         phys = PhysicalSchema.from_yaml(out)
-    except Exception as e:
+    except Exception as e:  # noqa: BLE001 - introspection CLI boundary
         typer.secho(f"ERRORE: {e}", fg=typer.colors.RED, err=True)
         raise typer.Exit(code=1)
     n_cols = sum(len(t.columns) for t in phys.tables.values())
@@ -143,20 +145,17 @@ def _schema_json(payload: dict) -> None:
     typer.echo(json.dumps(payload, ensure_ascii=False, sort_keys=True, separators=(",", ":")))
 
 
-def _machine_config(config: Path):
+def _load_schema_config(config: Path, *, suppress_legacy_warning: bool = False):
-    # Legacy resource keys remain accepted, but their deprecation warning is not part of
+    """Load configuration, optionally hiding the legacy-key warning for JSON callers."""
-    # the JSON machine contract.  Keep this filter scoped to this call so human commands
+    if not suppress_legacy_warning:
-    # (and unrelated warnings/errors) retain their existing behavior.
+        return load_config(config)
     with warnings.catch_warnings():
         warnings.filterwarnings(
             "ignore",
             message=r"^DEPRECATION: legacy workspace resource keys are deprecated;",
             category=FutureWarning,
         )
-        try:
+        return load_config(config)
-            return load_config(config)
-        except ConfigError:
-            raise _MachineSchemaError("invalid_configuration") from None
 
 
 def _physical_or_error(cfg):
@@ -169,22 +168,28 @@ def _physical_or_error(cfg):
         return PhysicalSchema.from_yaml(path)
     except _MachineSchemaError:
         raise
-    except Exception:
+    except (OSError, UnicodeError, TypeError, ValueError, yaml.YAMLError, ValidationError):
         raise _MachineSchemaError("physical_schema_invalid") from None
 
 
 def _staged_sql_files(inputs: list[Path] | None) -> list[Path]:
-    files: list[Path] = []
+    """Collect staged SQL paths without traversing beyond the file-count bound."""
-    for item in inputs or []:
+    def candidates():
-        if item.is_file():
+        for item in inputs or []:
-            files.append(item)
+            if item.is_file():
-        elif item.is_dir():
+                yield item
-            files.extend(path for path in item.rglob("*.sql") if path.is_file())
+            elif item.is_dir():
-        else:
+                for path in item.rglob("*.sql"):
-            raise _MachineSchemaError("staged_sql_invalid")
+                    if path.is_file():
-    # Resolve only for ordering; content remains read from the caller's staged path.
+                        yield path
+            else:
+                raise _MachineSchemaError("staged_sql_invalid")
+
+    # islice consumes at most the sentinel (33rd) match; unlike a list-producing
+    # rglob this never enumerates an unbounded directory before rejecting it.
+    files = list(islice(candidates(), _MAX_STAGED_SQL_FILES + 1))
     ordered = sorted(set(files), key=lambda path: path.resolve().as_posix())
-    if len(ordered) > _MAX_STAGED_SQL_FILES:
+    if len(ordered) > _MAX_STAGED_SQL_FILES or len(files) > _MAX_STAGED_SQL_FILES:
         raise _MachineSchemaError("staged_sql_too_many")
     return ordered
 
@@ -194,11 +199,13 @@ def _read_staged_sql(inputs: list[Path] | None) -> tuple[list[Path], list[str]]:
     contents: list[str] = []
     total = 0
     for path in paths:
+        allowance = min(_MAX_STAGED_SQL_BYTES, _MAX_STAGED_SQL_TOTAL - total)
         try:
-            raw = path.read_bytes()
+            with path.open("rb") as stream:
+                raw = stream.read(allowance + 1)
         except (OSError, UnicodeError):
             raise _MachineSchemaError("staged_sql_invalid") from None
-        if len(raw) > _MAX_STAGED_SQL_BYTES or total + len(raw) > _MAX_STAGED_SQL_TOTAL:
+        if len(raw) > allowance:
             raise _MachineSchemaError("staged_sql_too_large")
         total += len(raw)
         try:
@@ -220,8 +227,8 @@ class FKCandidate(TypedDict):
 
 
 class SuggestFksResult(TypedDict):
-    status: str
+    status: Literal["succeeded", "failed"]
-    code: str
+    code: Literal["ok"]
     candidates: list[FKCandidate]
     candidate_count: int
     candidate_digest: str
@@ -232,8 +239,8 @@ class SuggestFksResult(TypedDict):
 
 
 class CheckSchemaResult(TypedDict):
-    status: str
+    status: Literal["succeeded", "failed"]
-    code: str
+    code: Literal["ok", "annotation_orphans"]
     orphan_count: int
     orphans: list[str]
     ignored: list[str]
@@ -243,8 +250,13 @@ def _candidate_key(fk) -> tuple:
     return (tuple(fk.columns), fk.ref_table, tuple(fk.ref_columns))
 
 
-def suggest_fks_data(config: Path, *, from_sql: list[Path] | None = None,
+def suggest_fks_data(
-                     assume: list[str] | None = None) -> SuggestFksResult:
+    config: Path,
+    *,
+    from_sql: list[Path] | None = None,
+    assume: list[str] | None = None,
+    suppress_legacy_warning: bool = False,
+) -> SuggestFksResult:
     """Return deterministic FK candidates without reviewing or mutating annotations."""
     import hashlib
     import json
@@ -253,7 +265,10 @@ def suggest_fks_data(config: Path, *, from_sql: list[Path] | None = None,
     from tht.mschema.merge import find_orphans
     from tht.mschema.models import Annotations, ForeignKey
 
-    cfg = _machine_config(config)
+    try:
+        cfg = _load_schema_config(config, suppress_legacy_warning=suppress_legacy_warning)
+    except ConfigError:
+        raise _MachineSchemaError("invalid_configuration") from None
     physical = _physical_or_error(cfg)
     _, sql_contents = _read_staged_sql(from_sql)
     annotations = Annotations.from_yaml(annotations_path(cfg))
@@ -316,11 +331,13 @@ def suggest_fks_data(config: Path, *, from_sql: list[Path] | None = None,
                 if assumed[column_name] != table_name:
                     add(table_name, column_name, assumed[column_name], column_name)
                 continue
+            if column_name in _GENERIC_PK_NAMES:
+                continue
             owners = [owner for owner in pk_owners.get(column_name, []) if owner != table_name]
             if len(pk_owners.get(column_name, [])) > 1:
                 ambiguous_columns.add(column_name)
                 continue
-            if not owners or column_name in _GENERIC_PK_NAMES:
+            if not owners:
                 continue
             add(table_name, column_name, owners[0], column_name)
 
@@ -350,16 +367,21 @@ def suggest_fks_data(config: Path, *, from_sql: list[Path] | None = None,
     }
 
 
-def check_schema_data(config: Path) -> CheckSchemaResult:
+def check_schema_data(
+    config: Path, *, suppress_legacy_warning: bool = False
+) -> CheckSchemaResult:
     """Validate the physical catalog and imported annotations without writing."""
     from tht.mschema.merge import find_orphans
     from tht.mschema.models import Annotations
 
-    cfg = _machine_config(config)
+    try:
+        cfg = _load_schema_config(config, suppress_legacy_warning=suppress_legacy_warning)
+    except ConfigError:
+        raise _MachineSchemaError("invalid_configuration") from None
     physical = _physical_or_error(cfg)
     try:
         annotations = Annotations.from_yaml(annotations_path(cfg))
-    except Exception:
+    except (OSError, UnicodeError, TypeError, ValueError, yaml.YAMLError, ValidationError):
         raise _MachineSchemaError("annotations_invalid") from None
     orphans = find_orphans(physical, annotations)
     ignored = [
@@ -384,13 +406,13 @@ def check_cmd(
 ) -> None:
     """Confronta physical.yaml e annotations.yaml; segnala annotazioni orfane."""
     try:
-        payload = check_schema_data(config)
+        payload = check_schema_data(config, suppress_legacy_warning=json_output)
     except _MachineSchemaError as error:
         if json_output:
             _schema_json({"status": "failed", "code": error.code})
             raise typer.Exit(code=1) from None
         _render_schema_machine_error(error, config)
-    except Exception:
+    except Exception:  # noqa: BLE001 - JSON CLI boundary
         if json_output:
             _schema_json({"status": "failed", "code": "schema_check_failed"})
             raise typer.Exit(code=1) from None
@@ -441,8 +463,8 @@ def _render_schema_machine_error(error: _MachineSchemaError, config: Path) -> No
 @schema_app.command("suggest-fks")
 def suggest_fks_cmd(
     config: Path = CONFIG_OPT,
-    from_sql: list[Path] = typer.Option(None, "--from-sql", help="Directory/file SQL approvati (ripetibile)."),
+    from_sql: list[Path] = typer.Option(None, "--from-sql", help="Directory/file SQL approvati (ripetibile)."),  # noqa: B008
-    assume: list[str] = typer.Option(None, "--assume", help="Disambigua una PK: col=tabella."),
+    assume: list[str] = typer.Option(None, "--assume", help="Disambigua una PK: col=tabella."),  # noqa: B008
     write: bool = typer.Option(False, "--write", help="Fonde i suggerimenti in annotations.yaml."),
     json_output: bool = typer.Option(False, "--json", help="Emetti JSON puro su stdout."),
 ) -> None:
@@ -455,13 +477,18 @@ def suggest_fks_cmd(
         _schema_json({"status": "failed", "code": "write_not_allowed"})
         raise typer.Exit(code=2)
     try:
-        payload = suggest_fks_data(config, from_sql=from_sql, assume=assume)
+        payload = suggest_fks_data(
+            config,
+            from_sql=from_sql,
+            assume=assume,
+            suppress_legacy_warning=json_output,
+        )
     except _MachineSchemaError as error:
         if json_output:
             _schema_json({"status": "failed", "code": error.code})
             raise typer.Exit(code=1) from None
         _render_schema_machine_error(error, config)
-    except Exception:
+    except Exception:  # noqa: BLE001 - JSON CLI boundary
         if json_output:
             _schema_json({"status": "failed", "code": "schema_suggestion_failed"})
             raise typer.Exit(code=1) from None
@@ -472,7 +499,7 @@ def suggest_fks_cmd(
         return
 
     # Human mode remains the original renderer over the pure result.
-    if payload["mined_join_count"]:
+    if payload["staged_sql_count"]:
         typer.secho(
             f"Minati {payload['mined_join_count']} equi-join da {payload['staged_sql_count']} file SQL.",
             fg=typer.colors.BLUE, err=True,
@@ -524,10 +551,10 @@ def render_cmd(
     format: str = typer.Option(
         "markdown", "--format", "-f", help="Formato: markdown | mschema-text | schema-dict"
     ),
-    tables: list[str] = typer.Option(
+    tables: list[str] = typer.Option(  # noqa: B008
         None, "--table", "-t", help="Limita alle tabelle indicate (ripetibile)."
     ),
-    output: Path = typer.Option(None, "--output", "-o", help="File di output (default stdout)."),
+    output: Path = typer.Option(None, "--output", "-o", help="File di output (default stdout)."),  # noqa: B008
 ) -> None:
     """Serializza mschema (physical + annotations) nel formato richiesto."""
     import json

harness/tht/cli/vector_cmd.py

@@ -1,6 +1,7 @@
-# ruff: noqa: BLE001
+import logging
+from collections.abc import Mapping
 from pathlib import Path
-from typing import TypedDict
+from typing import Literal, TypedDict
 
 import typer
 
@@ -15,6 +16,7 @@ from tht.ports.vector import VectorWriteRecord
 from tht.vectorstore.store import SyncStats, content_hash
 
 vector_app = typer.Typer(help="Indice semantico Qdrant (derivato, rigenerabile)")
+logger = logging.getLogger(__name__)
 
 
 def make_embedder(embeddings_cfg):
@@ -80,10 +82,19 @@ def sync_canonical_records(collection, records, *, store, embedder):
     return stats
 
 
-def _print_stats(stats) -> None:
+def _print_stats(stats: SyncStats | Mapping[str, int]) -> None:
+    if isinstance(stats, SyncStats):
+        counts = {
+            "added": stats.added,
+            "updated": stats.updated,
+            "deleted": stats.deleted,
+            "unchanged": stats.unchanged,
+        }
+    else:
+        counts = stats
     typer.secho(
-        f"OK: {stats.added} nuovi, {stats.updated} aggiornati, "
+        f"OK: {counts['added']} nuovi, {counts['updated']} aggiornati, "
-        f"{stats.deleted} rimossi, {stats.unchanged} invariati",
+        f"{counts['deleted']} rimossi, {counts['unchanged']} invariati",
         fg=typer.colors.GREEN,
     )
 
@@ -138,8 +149,8 @@ class IndexCounts(TypedDict):
 
 
 class IndexSchemaResult(TypedDict):
-    status: str
+    status: Literal["succeeded", "failed"]
-    code: str
+    code: Literal["ok"]
     counts: IndexCounts
 
 
@@ -158,26 +169,31 @@ def _vector_write_or_error(cfg) -> None:
         raise _MachineVectorError("vector_write_not_allowed")
 
 
-def index_schema_data(config: Path) -> IndexSchemaResult:
+def index_schema_data(
+    config: Path, *, suppress_legacy_warning: bool = False
+) -> IndexSchemaResult:
     """Synchronize schema records and return a bounded machine result."""
-    from tht.cli.schema_cmd import _machine_config
+    from tht.cli.schema_cmd import _load_schema_config
+    from tht.config import ConfigError
     from tht.mschema.models import Annotations, PhysicalSchema
     from tht.vectorstore.records import schema_records
 
     try:
-        cfg = _machine_config(config)
+        cfg = _load_schema_config(config, suppress_legacy_warning=suppress_legacy_warning)
-    except Exception:
+    except ConfigError:
-        # Keep this helper free of Typer rendering while preserving a stable code.
         raise _MachineVectorError("invalid_configuration") from None
     _vector_write_or_error(cfg)
     _vector_cfg_or_error(cfg)
     phys_file = physical_path(cfg)
     if not phys_file.exists():
         raise _MachineVectorError("physical_schema_missing")
+    import yaml
+    from pydantic import ValidationError
+
     try:
         physical = PhysicalSchema.from_yaml(phys_file)
         annotations = Annotations.from_yaml(annotations_path(cfg))
-    except Exception:
+    except (OSError, UnicodeError, TypeError, ValueError, yaml.YAMLError, ValidationError):
         raise _MachineVectorError("schema_artifacts_invalid") from None
     records = schema_records(physical, annotations)
     from tht.adapters.factory import build_vector_store
@@ -210,23 +226,24 @@ def index_schema_cmd(
 
     if json_output:
         try:
-            payload = index_schema_data(config)
+            payload = index_schema_data(config, suppress_legacy_warning=True)
         except _MachineVectorError as error:
             typer.echo(json.dumps({"status": "failed", "code": error.code}, sort_keys=True, separators=(",", ":")))
             raise typer.Exit(code=1) from None
-        except Exception:
+        except Exception:  # noqa: BLE001 - JSON CLI boundary
             typer.echo(json.dumps({"status": "failed", "code": "schema_index_failed"}, sort_keys=True, separators=(",", ":")))
             raise typer.Exit(code=1) from None
         typer.echo(json.dumps(payload, sort_keys=True, separators=(",", ":")))
         return
     try:
-        payload = index_schema_data(config)
+        payload = index_schema_data(config, suppress_legacy_warning=False)
     except _MachineVectorError as error:
         _render_index_schema_error(error, config)
     except Exception:
+        logger.exception("Schema indexing failed")
         typer.secho("ERRORE: impossibile indicizzare lo schema.", fg=typer.colors.RED, err=True)
         raise typer.Exit(code=1) from None
-    _print_stats(type("Stats", (), payload["counts"])())
+    _print_stats(payload["counts"])
 
 
 def _render_index_schema_error(error: _MachineVectorError, config: Path) -> None: