fix: preserve Task 2 command loading contracts
This commit is contained in:
@@ -1,5 +1,4 @@
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"""One-shot preprocessing commands."""
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# ruff: noqa: BLE001
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from __future__ import annotations
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@@ -99,7 +98,6 @@ def run_from_config(config: Path, *, dry_run: bool = False, resume: str | None =
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def gc_from_config(config: Path, *, dry_run: bool = False):
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from tht.adapters.factory import build_evidence_sources, build_vector_store
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from tht.cli.schema_cmd import _load_config_or_exit
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from tht.cli.vector_cmd import make_embedder
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from tht.corpus.chunk import ChunkPolicy
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from tht.corpus.pipeline import CorpusPipeline
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@@ -134,7 +132,7 @@ def evidence_cmd(
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if action == "gc":
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try:
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payload = gc_from_config(config, dry_run=dry_run)
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except Exception:
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except (OSError, RuntimeError, ValueError, TypeError, KeyError):
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payload = {"status": "failed", "error": "evidence cleanup failed"}
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if json_output:
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typer.echo(json.dumps(payload, sort_keys=True))
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@@ -155,7 +153,7 @@ def evidence_cmd(
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raise typer.Exit(code=2)
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try:
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result = run_from_config(config, dry_run=dry_run, resume=resume)
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except Exception:
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except (OSError, RuntimeError, ValueError, TypeError, KeyError):
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payload = {"status": "failed", "error": "preprocessing failed"}
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if json_output:
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typer.echo(json.dumps(payload, sort_keys=True))
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@@ -206,7 +204,7 @@ def dwh_cmd(
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raise typer.Exit(code=2)
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try:
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result = run_dwh_from_config(config, steps=selected, resume=resume)
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except Exception:
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except (OSError, RuntimeError, ValueError, TypeError, KeyError):
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payload = {"status": "failed", "error": "DWH preprocessing failed"}
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if json_output:
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typer.echo(json.dumps(payload, sort_keys=True))
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@@ -1,6 +1,5 @@
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import logging
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import warnings
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from itertools import islice
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from pathlib import Path
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from typing import Literal, TypedDict
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@@ -10,7 +9,7 @@ from pydantic import ValidationError
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from tht.adapters.factory import build_dwh
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from tht.cli.config_cmd import CONFIG_OPT
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from tht.config import ConfigError, load_config
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from tht.config import Config, ConfigError, load_config
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from tht.db.sampling import is_text_type
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from tht.mschema.eligibility import classify_all
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@@ -42,7 +41,7 @@ def _load_config_or_exit(config: Path):
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raise typer.Exit(code=1)
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def physical_path(cfg) -> Path:
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def physical_path(cfg: Config) -> Path:
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from tht.jobs.dwh_pipeline import resolve_dwh_snapshot
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if not (cfg.paths.artifacts.parent / ".tht-dwh").exists():
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@@ -50,7 +49,7 @@ def physical_path(cfg) -> Path:
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return resolve_dwh_snapshot(cfg).physical
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def annotations_path(cfg) -> Path:
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def annotations_path(cfg: Config) -> Path:
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return cfg.paths.artifacts / "mschema" / "annotations.yaml"
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@@ -134,6 +133,15 @@ class _MachineSchemaError(Exception):
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super().__init__(code)
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def _annotations_or_error(cfg: Config):
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from tht.mschema.models import Annotations
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try:
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return Annotations.from_yaml(annotations_path(cfg))
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except (OSError, UnicodeError, TypeError, ValueError, yaml.YAMLError, ValidationError):
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raise _MachineSchemaError("annotations_invalid") from None
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_MAX_STAGED_SQL_BYTES = 1 << 20
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_MAX_STAGED_SQL_TOTAL = 16 << 20
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_MAX_STAGED_SQL_FILES = 32
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@@ -158,7 +166,7 @@ def _load_schema_config(config: Path, *, suppress_legacy_warning: bool = False):
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return load_config(config)
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def _physical_or_error(cfg):
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def _physical_or_error(cfg: Config):
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path = physical_path(cfg)
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if not path.exists():
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raise _MachineSchemaError("physical_schema_missing")
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@@ -173,25 +181,34 @@ def _physical_or_error(cfg):
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def _staged_sql_files(inputs: list[Path] | None) -> list[Path]:
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"""Collect staged SQL paths without traversing beyond the file-count bound."""
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def candidates():
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for item in inputs or []:
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if item.is_file():
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yield item
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elif item.is_dir():
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for path in item.rglob("*.sql"):
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if path.is_file():
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yield path
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else:
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raise _MachineSchemaError("staged_sql_invalid")
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"""Collect distinct staged SQL paths lazily, bounded by distinct files."""
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seen_files: set[Path] = set()
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seen_roots: set[Path] = set()
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ordered: list[Path] = []
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# islice consumes at most the sentinel (33rd) match; unlike a list-producing
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# rglob this never enumerates an unbounded directory before rejecting it.
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files = list(islice(candidates(), _MAX_STAGED_SQL_FILES + 1))
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ordered = sorted(set(files), key=lambda path: path.resolve().as_posix())
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if len(ordered) > _MAX_STAGED_SQL_FILES or len(files) > _MAX_STAGED_SQL_FILES:
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raise _MachineSchemaError("staged_sql_too_many")
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return ordered
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def add(path: Path):
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canonical = path.resolve()
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if canonical in seen_files:
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return
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seen_files.add(canonical)
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ordered.append(canonical)
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if len(ordered) > _MAX_STAGED_SQL_FILES:
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raise _MachineSchemaError("staged_sql_too_many")
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for item in inputs or []:
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canonical_item = item.resolve()
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if item.is_file():
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add(canonical_item)
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elif item.is_dir():
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if canonical_item in seen_roots:
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continue
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seen_roots.add(canonical_item)
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for path in item.rglob("*.sql"):
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if path.is_file():
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add(path)
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else:
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raise _MachineSchemaError("staged_sql_invalid")
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return sorted(ordered, key=Path.as_posix)
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def _read_staged_sql(inputs: list[Path] | None) -> tuple[list[Path], list[str]]:
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@@ -251,11 +268,13 @@ def _candidate_key(fk) -> tuple:
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def suggest_fks_data(
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config: Path,
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config: Config | Path,
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*,
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from_sql: list[Path] | None = None,
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assume: list[str] | None = None,
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suppress_legacy_warning: bool = False,
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physical=None,
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annotations=None,
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) -> SuggestFksResult:
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"""Return deterministic FK candidates without reviewing or mutating annotations."""
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import hashlib
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@@ -263,15 +282,20 @@ def suggest_fks_data(
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from tht.mschema.fkmine import mine_join_pairs
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from tht.mschema.merge import find_orphans
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from tht.mschema.models import Annotations, ForeignKey
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from tht.mschema.models import ForeignKey
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try:
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cfg = _load_schema_config(config, suppress_legacy_warning=suppress_legacy_warning)
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except ConfigError:
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raise _MachineSchemaError("invalid_configuration") from None
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physical = _physical_or_error(cfg)
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if isinstance(config, Path):
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try:
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cfg = _load_schema_config(config, suppress_legacy_warning=suppress_legacy_warning)
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except ConfigError:
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raise _MachineSchemaError("invalid_configuration") from None
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else:
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cfg = config
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if physical is None:
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physical = _physical_or_error(cfg)
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_, sql_contents = _read_staged_sql(from_sql)
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annotations = Annotations.from_yaml(annotations_path(cfg))
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if annotations is None:
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annotations = _annotations_or_error(cfg)
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assumed: dict[str, str] = {}
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for value in assume or []:
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@@ -368,21 +392,22 @@ def suggest_fks_data(
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def check_schema_data(
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config: Path, *, suppress_legacy_warning: bool = False
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config: Config | Path, *, suppress_legacy_warning: bool = False, physical=None, annotations=None
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) -> CheckSchemaResult:
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"""Validate the physical catalog and imported annotations without writing."""
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from tht.mschema.merge import find_orphans
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from tht.mschema.models import Annotations
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try:
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cfg = _load_schema_config(config, suppress_legacy_warning=suppress_legacy_warning)
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except ConfigError:
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raise _MachineSchemaError("invalid_configuration") from None
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physical = _physical_or_error(cfg)
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try:
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annotations = Annotations.from_yaml(annotations_path(cfg))
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except (OSError, UnicodeError, TypeError, ValueError, yaml.YAMLError, ValidationError):
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raise _MachineSchemaError("annotations_invalid") from None
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if isinstance(config, Path):
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try:
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cfg = _load_schema_config(config, suppress_legacy_warning=suppress_legacy_warning)
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except ConfigError:
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raise _MachineSchemaError("invalid_configuration") from None
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else:
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cfg = config
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if physical is None:
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physical = _physical_or_error(cfg)
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if annotations is None:
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annotations = _annotations_or_error(cfg)
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orphans = find_orphans(physical, annotations)
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ignored = [
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f"{table_name}.{column_name} ({column.eligibility_reason})"
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@@ -405,14 +430,25 @@ def check_cmd(
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json_output: bool = typer.Option(False, "--json", help="Emetti JSON puro su stdout."),
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) -> None:
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"""Confronta physical.yaml e annotations.yaml; segnala annotazioni orfane."""
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if json_output:
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try:
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cfg = _load_schema_config(config, suppress_legacy_warning=True)
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except ConfigError:
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_schema_json({"status": "failed", "code": "invalid_configuration"})
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raise typer.Exit(code=1) from None
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else:
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cfg = _load_config_or_exit(config)
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try:
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payload = check_schema_data(config, suppress_legacy_warning=json_output)
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physical = _physical_or_error(cfg)
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annotations = _annotations_or_error(cfg)
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payload = check_schema_data(cfg, physical=physical, annotations=annotations)
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except _MachineSchemaError as error:
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if json_output:
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_schema_json({"status": "failed", "code": error.code})
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raise typer.Exit(code=1) from None
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_render_schema_machine_error(error, config)
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except Exception: # noqa: BLE001 - JSON CLI boundary
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_render_schema_machine_error(error, cfg)
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except Exception:
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logger.exception("Schema check failed")
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if json_output:
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_schema_json({"status": "failed", "code": "schema_check_failed"})
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raise typer.Exit(code=1) from None
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@@ -439,9 +475,8 @@ def check_cmd(
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typer.secho("OK: nessuna annotazione orfana.", fg=typer.colors.GREEN)
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def _render_schema_machine_error(error: _MachineSchemaError, config: Path) -> None:
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def _render_schema_machine_error(error: _MachineSchemaError, cfg) -> None:
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"""Render expected schema failures for the legacy human command contract."""
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cfg = _load_config_or_exit(config)
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if error.code == "physical_schema_missing":
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typer.secho(
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f"ERRORE: {physical_path(cfg)} non trovato. Esegui prima `tht schema introspect`.",
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@@ -471,24 +506,32 @@ def suggest_fks_cmd(
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"""Suggerisce FK logiche per la curazione umana in annotations.yaml."""
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import yaml as _yaml
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from tht.mschema.models import Annotations, TableAnnotation
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from tht.mschema.models import TableAnnotation
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if json_output and write:
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_schema_json({"status": "failed", "code": "write_not_allowed"})
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raise typer.Exit(code=2)
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if json_output:
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try:
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cfg = _load_schema_config(config, suppress_legacy_warning=True)
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except ConfigError:
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_schema_json({"status": "failed", "code": "invalid_configuration"})
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raise typer.Exit(code=1) from None
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else:
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cfg = _load_config_or_exit(config)
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try:
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physical = _physical_or_error(cfg)
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annotations = _annotations_or_error(cfg)
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payload = suggest_fks_data(
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config,
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from_sql=from_sql,
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assume=assume,
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suppress_legacy_warning=json_output,
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cfg, from_sql=from_sql, assume=assume, physical=physical, annotations=annotations
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)
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except _MachineSchemaError as error:
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if json_output:
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_schema_json({"status": "failed", "code": error.code})
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raise typer.Exit(code=1) from None
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_render_schema_machine_error(error, config)
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except Exception: # noqa: BLE001 - JSON CLI boundary
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_render_schema_machine_error(error, cfg)
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except Exception:
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logger.exception("Schema suggestion failed")
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if json_output:
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_schema_json({"status": "failed", "code": "schema_suggestion_failed"})
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raise typer.Exit(code=1) from None
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@@ -519,8 +562,6 @@ def suggest_fks_cmd(
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for item in payload["candidates"]
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}
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if write:
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cfg = _load_config_or_exit(config)
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annotations = Annotations.from_yaml(annotations_path(cfg))
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for table_name, table_payload in candidate_tables.items():
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ann = annotations.tables.setdefault(table_name, TableAnnotation())
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from tht.mschema.models import ForeignKey
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@@ -11,7 +11,13 @@ from tht.cli._guards import (
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require_vector_write_allowed,
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)
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from tht.cli.config_cmd import CONFIG_OPT
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from tht.cli.schema_cmd import _load_config_or_exit, annotations_path, physical_path
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from tht.cli.schema_cmd import (
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_load_config_or_exit,
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_load_schema_config,
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annotations_path,
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physical_path,
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)
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from tht.config import Config, ConfigError
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from tht.ports.vector import VectorWriteRecord
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from tht.vectorstore.store import SyncStats, content_hash
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@@ -154,7 +160,7 @@ class IndexSchemaResult(TypedDict):
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counts: IndexCounts
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def _vector_cfg_or_error(cfg) -> None:
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def _vector_cfg_or_error(cfg: Config) -> None:
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missing = []
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if cfg.embeddings is None:
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missing.append("embeddings")
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@@ -164,24 +170,42 @@ def _vector_cfg_or_error(cfg) -> None:
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raise _MachineVectorError("vector_configuration_missing")
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def _vector_write_or_error(cfg) -> None:
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def _vector_write_or_error(cfg: Config) -> None:
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if cfg.profile == "workstation" and not has_vector_write_rest(cfg):
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raise _MachineVectorError("vector_write_not_allowed")
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def _load_schema_artifacts(cfg: Config):
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import yaml
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from pydantic import ValidationError
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from tht.mschema.models import Annotations, PhysicalSchema
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phys_file = physical_path(cfg)
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if not phys_file.exists():
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raise _MachineVectorError("physical_schema_missing")
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try:
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return (
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PhysicalSchema.from_yaml(phys_file),
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Annotations.from_yaml(annotations_path(cfg)),
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)
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except (OSError, UnicodeError, TypeError, ValueError, yaml.YAMLError, ValidationError):
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raise _MachineVectorError("schema_artifacts_invalid") from None
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def index_schema_data(
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config: Path, *, suppress_legacy_warning: bool = False
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config: Config | Path, *, suppress_legacy_warning: bool = False, physical=None, annotations=None
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) -> IndexSchemaResult:
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"""Synchronize schema records and return a bounded machine result."""
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from tht.cli.schema_cmd import _load_schema_config
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from tht.config import ConfigError
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from tht.mschema.models import Annotations, PhysicalSchema
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from tht.vectorstore.records import schema_records
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try:
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cfg = _load_schema_config(config, suppress_legacy_warning=suppress_legacy_warning)
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except ConfigError:
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raise _MachineVectorError("invalid_configuration") from None
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if isinstance(config, Path):
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try:
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cfg = _load_schema_config(config, suppress_legacy_warning=suppress_legacy_warning)
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except ConfigError:
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raise _MachineVectorError("invalid_configuration") from None
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else:
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cfg = config
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_vector_write_or_error(cfg)
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_vector_cfg_or_error(cfg)
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phys_file = physical_path(cfg)
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@@ -191,8 +215,10 @@ def index_schema_data(
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from pydantic import ValidationError
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try:
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physical = PhysicalSchema.from_yaml(phys_file)
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annotations = Annotations.from_yaml(annotations_path(cfg))
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if physical is None:
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physical = PhysicalSchema.from_yaml(phys_file)
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if annotations is None:
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annotations = Annotations.from_yaml(annotations_path(cfg))
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except (OSError, UnicodeError, TypeError, ValueError, yaml.YAMLError, ValidationError):
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raise _MachineVectorError("schema_artifacts_invalid") from None
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records = schema_records(physical, annotations)
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@@ -226,29 +252,35 @@ def index_schema_cmd(
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if json_output:
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try:
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payload = index_schema_data(config, suppress_legacy_warning=True)
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except _MachineVectorError as error:
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cfg = _load_schema_config(config, suppress_legacy_warning=True)
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except ConfigError:
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typer.echo(json.dumps({"status": "failed", "code": "invalid_configuration"}, sort_keys=True, separators=(",", ":")))
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raise typer.Exit(code=1) from None
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else:
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cfg = _load_config_or_exit(config)
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try:
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physical, annotations = _load_schema_artifacts(cfg)
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payload = index_schema_data(cfg, physical=physical, annotations=annotations)
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except _MachineVectorError as error:
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if json_output:
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typer.echo(json.dumps({"status": "failed", "code": error.code}, sort_keys=True, separators=(",", ":")))
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raise typer.Exit(code=1) from None
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except Exception: # noqa: BLE001 - JSON CLI boundary
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typer.echo(json.dumps({"status": "failed", "code": "schema_index_failed"}, sort_keys=True, separators=(",", ":")))
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raise typer.Exit(code=1) from None
|
||||
typer.echo(json.dumps(payload, sort_keys=True, separators=(",", ":")))
|
||||
return
|
||||
try:
|
||||
payload = index_schema_data(config, suppress_legacy_warning=False)
|
||||
except _MachineVectorError as error:
|
||||
_render_index_schema_error(error, config)
|
||||
_render_index_schema_error(error, cfg)
|
||||
except Exception:
|
||||
logger.exception("Schema indexing failed")
|
||||
if json_output:
|
||||
typer.echo(json.dumps({"status": "failed", "code": "schema_index_failed"}, sort_keys=True, separators=(",", ":")))
|
||||
raise typer.Exit(code=1) from None
|
||||
typer.secho("ERRORE: impossibile indicizzare lo schema.", fg=typer.colors.RED, err=True)
|
||||
raise typer.Exit(code=1) from None
|
||||
if json_output:
|
||||
typer.echo(json.dumps(payload, sort_keys=True, separators=(",", ":")))
|
||||
return
|
||||
_print_stats(payload["counts"])
|
||||
|
||||
|
||||
def _render_index_schema_error(error: _MachineVectorError, config: Path) -> None:
|
||||
def _render_index_schema_error(error: _MachineVectorError, cfg) -> None:
|
||||
"""Render expected failures without changing the old human CLI messages."""
|
||||
cfg = _load_config_or_exit(config)
|
||||
if error.code == "physical_schema_missing":
|
||||
typer.secho(
|
||||
f"ERRORE: {physical_path(cfg)} non trovato. Esegui prima `tht schema introspect`.",
|
||||
|
||||
Reference in New Issue
Block a user