711 lines
26 KiB
Python
711 lines
26 KiB
Python
import logging
|
|
import warnings
|
|
from pathlib import Path
|
|
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
|
|
from tht.config import Config, ConfigError, load_config
|
|
from tht.db.sampling import is_text_type
|
|
from tht.mschema.eligibility import classify_all
|
|
|
|
schema_app = typer.Typer(help="Gestione mschema (rappresentazione canonica dello schema)")
|
|
logger = logging.getLogger(__name__)
|
|
|
|
|
|
def _add_examples(dwh, phys, examples) -> None:
|
|
for table_name, table in phys.tables.items():
|
|
for column_name, column in table.columns.items():
|
|
if not is_text_type(column.type):
|
|
continue
|
|
try:
|
|
sampled = dwh.sample_column(
|
|
table_name, column_name, limit=examples.max_per_column
|
|
)
|
|
except Exception as exc: # noqa: BLE001 - sampling adapter boundary
|
|
logger.warning("Campionamento saltato per %s.%s: %s",
|
|
table_name, column_name, exc)
|
|
continue
|
|
column.examples = [str(value) for value in sampled if value not in (None, "")]
|
|
|
|
|
|
def _load_config_or_exit(config: Path):
|
|
try:
|
|
return load_config(config)
|
|
except ConfigError as e:
|
|
typer.secho(f"ERRORE: {e}", fg=typer.colors.RED, err=True)
|
|
raise typer.Exit(code=1)
|
|
|
|
|
|
def physical_path(cfg: Config) -> Path:
|
|
from tht.jobs.dwh_pipeline import resolve_dwh_snapshot
|
|
|
|
if not (cfg.paths.artifacts.parent / ".tht-dwh").exists():
|
|
return cfg.paths.artifacts / "mschema" / "physical.yaml"
|
|
return resolve_dwh_snapshot(cfg).physical
|
|
|
|
|
|
def annotations_path(cfg: Config) -> Path:
|
|
return cfg.paths.artifacts / "mschema" / "annotations.yaml"
|
|
|
|
|
|
def refresh_catalog(cfg, *, dwh=None, output_path: Path | None = None):
|
|
"""Run the existing catalog algorithm and persist its canonical output."""
|
|
target = dwh if dwh is not None else build_dwh(cfg)
|
|
physical = target.introspect()
|
|
_add_examples(target, physical, cfg.examples)
|
|
classify_all(physical, cfg.eligibility)
|
|
physical.to_yaml(output_path or (cfg.paths.artifacts / "mschema" / "physical.yaml"))
|
|
return physical
|
|
|
|
|
|
@schema_app.command("introspect")
|
|
def introspect_cmd(
|
|
config: Path = CONFIG_OPT,
|
|
refresh: bool = typer.Option(
|
|
False,
|
|
"--refresh",
|
|
help="Forza la re-introspezione del DWH anche se physical.yaml esiste già.",
|
|
),
|
|
) -> None:
|
|
"""Introspeziona lo schema target e genera artifacts/mschema/physical.yaml.
|
|
|
|
Se physical.yaml esiste già, esce subito (cache); usa --refresh per rigenerarlo.
|
|
"""
|
|
cfg = _load_config_or_exit(config)
|
|
dwh_root = cfg.paths.artifacts.parent / ".tht-dwh"
|
|
out = cfg.paths.artifacts / "mschema" / "physical.yaml"
|
|
if dwh_root.exists() or dwh_root.is_symlink():
|
|
out = physical_path(cfg)
|
|
if (dwh_root.exists() or dwh_root.is_symlink()) and out.exists() and not refresh:
|
|
from datetime import UTC, datetime
|
|
|
|
from tht.mschema.models import PhysicalSchema
|
|
|
|
try:
|
|
cached = PhysicalSchema.from_yaml(out)
|
|
except (OSError, UnicodeError, TypeError, ValueError, yaml.YAMLError, ValidationError) as exc:
|
|
logger.debug("Catalogo cache non leggibile: %s", exc)
|
|
else:
|
|
ts = cached.introspected_at
|
|
if ts.tzinfo is None:
|
|
ts = ts.replace(tzinfo=UTC)
|
|
age_days = (datetime.now(UTC) - ts).days
|
|
typer.secho(
|
|
f"OK (cache): {out} esistente ({len(cached.tables)} tabelle, "
|
|
f"età {age_days}g). Re-introspezione solo con --refresh (manutenzione).",
|
|
fg=typer.colors.GREEN,
|
|
)
|
|
return
|
|
try:
|
|
from tht.cli.preprocess_cmd import run_dwh_from_config
|
|
from tht.mschema.models import PhysicalSchema
|
|
|
|
report = run_dwh_from_config(config, steps=("introspect",))
|
|
if report.status != "succeeded":
|
|
raise RuntimeError("DWH preprocessing failed")
|
|
out = physical_path(cfg)
|
|
phys = PhysicalSchema.from_yaml(out)
|
|
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())
|
|
n_ignored = sum(
|
|
1 for t in phys.tables.values() for c in t.columns.values() if not c.eligible
|
|
)
|
|
typer.secho(
|
|
f"OK: {len(phys.tables)} tabelle, {n_cols} colonne "
|
|
f"({n_ignored} ignorate: testo ampio) -> {out}",
|
|
fg=typer.colors.GREEN,
|
|
)
|
|
|
|
|
|
class _MachineSchemaError(Exception):
|
|
"""An expected schema CLI failure with a stable public code."""
|
|
|
|
def __init__(self, code: str, detail: str = ""):
|
|
self.code = code
|
|
self.detail = detail
|
|
super().__init__(code)
|
|
|
|
|
|
def _annotations_or_error(cfg: Config):
|
|
from tht.mschema.models import Annotations
|
|
|
|
try:
|
|
return Annotations.from_yaml(annotations_path(cfg))
|
|
except (OSError, UnicodeError, TypeError, ValueError, yaml.YAMLError, ValidationError):
|
|
raise _MachineSchemaError("annotations_invalid") from None
|
|
|
|
|
|
_MAX_STAGED_SQL_BYTES = 1 << 20
|
|
_MAX_STAGED_SQL_TOTAL = 16 << 20
|
|
_MAX_STAGED_SQL_FILES = 32
|
|
|
|
|
|
def _schema_json(payload: dict) -> None:
|
|
import json
|
|
|
|
typer.echo(json.dumps(payload, ensure_ascii=False, sort_keys=True, separators=(",", ":")))
|
|
|
|
|
|
def _load_schema_config(config: Path, *, suppress_legacy_warning: bool = False):
|
|
"""Load configuration, optionally hiding the legacy-key warning for JSON callers."""
|
|
if not suppress_legacy_warning:
|
|
return load_config(config)
|
|
with warnings.catch_warnings():
|
|
warnings.filterwarnings(
|
|
"ignore",
|
|
message=r"^DEPRECATION: legacy workspace resource keys are deprecated;",
|
|
category=FutureWarning,
|
|
)
|
|
return load_config(config)
|
|
|
|
|
|
def _physical_or_error(cfg: Config):
|
|
path = physical_path(cfg)
|
|
if not path.exists():
|
|
raise _MachineSchemaError("physical_schema_missing")
|
|
try:
|
|
from tht.mschema.models import PhysicalSchema
|
|
|
|
return PhysicalSchema.from_yaml(path)
|
|
except _MachineSchemaError:
|
|
raise
|
|
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]:
|
|
"""Collect distinct staged SQL paths lazily, bounded by distinct files."""
|
|
seen_files: set[Path] = set()
|
|
seen_roots: set[Path] = set()
|
|
ordered: list[Path] = []
|
|
|
|
def add(path: Path):
|
|
canonical = path.resolve()
|
|
if canonical in seen_files:
|
|
return
|
|
seen_files.add(canonical)
|
|
ordered.append(canonical)
|
|
if len(ordered) > _MAX_STAGED_SQL_FILES:
|
|
raise _MachineSchemaError("staged_sql_too_many")
|
|
|
|
for item in inputs or []:
|
|
canonical_item = item.resolve()
|
|
if item.is_file():
|
|
add(canonical_item)
|
|
elif item.is_dir():
|
|
if canonical_item in seen_roots:
|
|
continue
|
|
seen_roots.add(canonical_item)
|
|
for path in item.rglob("*.sql"):
|
|
if path.is_file():
|
|
add(path)
|
|
else:
|
|
raise _MachineSchemaError("staged_sql_invalid")
|
|
return sorted(ordered, key=Path.as_posix)
|
|
|
|
|
|
def _read_staged_sql(inputs: list[Path] | None) -> tuple[list[Path], list[str]]:
|
|
paths = _staged_sql_files(inputs)
|
|
contents: list[str] = []
|
|
total = 0
|
|
for path in paths:
|
|
allowance = min(_MAX_STAGED_SQL_BYTES, _MAX_STAGED_SQL_TOTAL - total)
|
|
try:
|
|
with path.open("rb") as stream:
|
|
raw = stream.read(allowance + 1)
|
|
except (OSError, UnicodeError):
|
|
raise _MachineSchemaError("staged_sql_invalid") from None
|
|
if len(raw) > allowance:
|
|
raise _MachineSchemaError("staged_sql_too_large")
|
|
total += len(raw)
|
|
try:
|
|
contents.append(raw.decode("utf-8"))
|
|
except UnicodeDecodeError:
|
|
raise _MachineSchemaError("staged_sql_invalid") from None
|
|
return paths, contents
|
|
|
|
|
|
class CandidateForeignKey(TypedDict):
|
|
columns: list[str]
|
|
ref_table: str
|
|
ref_columns: list[str]
|
|
|
|
|
|
class FKCandidate(TypedDict):
|
|
table: str
|
|
foreign_keys: list[CandidateForeignKey]
|
|
|
|
|
|
class SuggestFksResult(TypedDict):
|
|
status: Literal["succeeded", "failed"]
|
|
code: Literal["ok"]
|
|
candidates: list[FKCandidate]
|
|
candidate_count: int
|
|
candidate_digest: str
|
|
orphan_count: int
|
|
staged_sql_count: int
|
|
mined_join_count: int
|
|
ambiguous_columns: list[str]
|
|
|
|
|
|
class CheckSchemaResult(TypedDict):
|
|
status: Literal["succeeded", "failed"]
|
|
code: Literal["ok", "annotation_orphans"]
|
|
orphan_count: int
|
|
orphans: list[str]
|
|
ignored: list[str]
|
|
|
|
|
|
def _candidate_key(fk) -> tuple:
|
|
return (tuple(fk.columns), fk.ref_table, tuple(fk.ref_columns))
|
|
|
|
|
|
def suggest_fks_data(
|
|
config: Config | Path,
|
|
*,
|
|
from_sql: list[Path] | None = None,
|
|
assume: list[str] | None = None,
|
|
suppress_legacy_warning: bool = False,
|
|
physical=None,
|
|
annotations=None,
|
|
) -> SuggestFksResult:
|
|
"""Return deterministic FK candidates without reviewing or mutating annotations."""
|
|
import hashlib
|
|
import json
|
|
|
|
from tht.mschema.fkmine import mine_join_pairs
|
|
from tht.mschema.merge import find_orphans
|
|
from tht.mschema.models import ForeignKey
|
|
|
|
if isinstance(config, Path):
|
|
try:
|
|
cfg = _load_schema_config(config, suppress_legacy_warning=suppress_legacy_warning)
|
|
except ConfigError:
|
|
raise _MachineSchemaError("invalid_configuration") from None
|
|
else:
|
|
cfg = config
|
|
if physical is None:
|
|
physical = _physical_or_error(cfg)
|
|
_, sql_contents = _read_staged_sql(from_sql)
|
|
if annotations is None:
|
|
annotations = _annotations_or_error(cfg)
|
|
|
|
assumed: dict[str, str] = {}
|
|
for value in assume or []:
|
|
col, sep, ref = value.partition("=")
|
|
if not sep or not col or ref not in physical.tables:
|
|
raise _MachineSchemaError("assumption_invalid", value)
|
|
assumed[col] = ref
|
|
|
|
def single_pk(table) -> str | None:
|
|
pks = [name for name, column in table.columns.items() if column.pk]
|
|
return pks[0] if len(pks) == 1 else None
|
|
|
|
pk_owners: dict[str, list[str]] = {}
|
|
for table_name in sorted(physical.tables):
|
|
pk = single_pk(physical.tables[table_name])
|
|
if pk:
|
|
pk_owners.setdefault(pk, []).append(table_name)
|
|
dim_time_pk = single_pk(physical.tables["dim_time"]) if "dim_time" in physical.tables else None
|
|
|
|
known: dict[str, set] = {}
|
|
for table_name in physical.tables:
|
|
keys = {
|
|
_candidate_key(fk)
|
|
for fk in physical.tables[table_name].foreign_keys
|
|
}
|
|
annotation = annotations.tables.get(table_name)
|
|
if annotation:
|
|
keys.update(_candidate_key(fk) for fk in annotation.foreign_keys)
|
|
known[table_name] = keys
|
|
|
|
suggested: dict[str, list[ForeignKey]] = {}
|
|
|
|
def add(table_name: str, column: str, ref_table: str, ref_column: str) -> None:
|
|
key = ((column,), ref_table, (ref_column,))
|
|
if key in known[table_name]:
|
|
return
|
|
known[table_name].add(key)
|
|
suggested.setdefault(table_name, []).append(
|
|
ForeignKey(columns=[column], ref_table=ref_table, ref_columns=[ref_column])
|
|
)
|
|
|
|
mined_total = 0
|
|
for sql_text in sql_contents:
|
|
pairs = mine_join_pairs(sql_text, physical)
|
|
mined_total += sum(pairs.values())
|
|
for src_table, src_column, ref_table, ref_column in sorted(pairs):
|
|
add(src_table, src_column, ref_table, ref_column)
|
|
|
|
ambiguous_columns: set[str] = set()
|
|
for table_name in sorted(physical.tables):
|
|
table = physical.tables[table_name]
|
|
for column_name in sorted(table.columns):
|
|
if dim_time_pk and column_name.endswith("time_key") and table_name != "dim_time":
|
|
add(table_name, column_name, "dim_time", dim_time_pk)
|
|
continue
|
|
if column_name in assumed:
|
|
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:
|
|
continue
|
|
add(table_name, column_name, owners[0], column_name)
|
|
|
|
candidates = [
|
|
{
|
|
"table": table_name,
|
|
"foreign_keys": [
|
|
fk.model_dump(exclude_defaults=True)
|
|
for fk in sorted(fks, key=_candidate_key)
|
|
],
|
|
}
|
|
for table_name, fks in sorted(suggested.items())
|
|
]
|
|
canonical = json.dumps(candidates, ensure_ascii=False, sort_keys=True, separators=(",", ":"))
|
|
digest = "sha256:" + hashlib.sha256(canonical.encode("utf-8")).hexdigest()
|
|
orphan_count = len(find_orphans(physical, annotations))
|
|
return {
|
|
"status": "succeeded",
|
|
"code": "ok",
|
|
"candidates": candidates,
|
|
"candidate_count": sum(len(item["foreign_keys"]) for item in candidates),
|
|
"candidate_digest": digest,
|
|
"orphan_count": orphan_count,
|
|
"staged_sql_count": len(sql_contents),
|
|
"mined_join_count": mined_total,
|
|
"ambiguous_columns": sorted(ambiguous_columns),
|
|
}
|
|
|
|
|
|
def check_schema_data(
|
|
config: Config | Path, *, suppress_legacy_warning: bool = False, physical=None, annotations=None
|
|
) -> CheckSchemaResult:
|
|
"""Validate the physical catalog and imported annotations without writing."""
|
|
from tht.mschema.merge import find_orphans
|
|
|
|
if isinstance(config, Path):
|
|
try:
|
|
cfg = _load_schema_config(config, suppress_legacy_warning=suppress_legacy_warning)
|
|
except ConfigError:
|
|
raise _MachineSchemaError("invalid_configuration") from None
|
|
else:
|
|
cfg = config
|
|
if physical is None:
|
|
physical = _physical_or_error(cfg)
|
|
if annotations is None:
|
|
annotations = _annotations_or_error(cfg)
|
|
orphans = find_orphans(physical, annotations)
|
|
ignored = [
|
|
f"{table_name}.{column_name} ({column.eligibility_reason})"
|
|
for table_name, table in physical.tables.items()
|
|
for column_name, column in table.columns.items()
|
|
if not column.eligible
|
|
]
|
|
return {
|
|
"status": "succeeded" if not orphans else "failed",
|
|
"code": "ok" if not orphans else "annotation_orphans",
|
|
"orphan_count": len(orphans),
|
|
"orphans": orphans,
|
|
"ignored": ignored,
|
|
}
|
|
|
|
|
|
@schema_app.command("check")
|
|
def check_cmd(
|
|
config: Path = CONFIG_OPT,
|
|
json_output: bool = typer.Option(False, "--json", help="Emetti JSON puro su stdout."),
|
|
) -> None:
|
|
"""Confronta physical.yaml e annotations.yaml; segnala annotazioni orfane."""
|
|
if json_output:
|
|
try:
|
|
cfg = _load_schema_config(config, suppress_legacy_warning=True)
|
|
except ConfigError:
|
|
_schema_json({"status": "failed", "code": "invalid_configuration"})
|
|
raise typer.Exit(code=1) from None
|
|
else:
|
|
cfg = _load_config_or_exit(config)
|
|
try:
|
|
physical = _physical_or_error(cfg)
|
|
annotations = _annotations_or_error(cfg)
|
|
payload = check_schema_data(cfg, physical=physical, annotations=annotations)
|
|
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, cfg)
|
|
except Exception:
|
|
logger.exception("Schema check failed")
|
|
if json_output:
|
|
_schema_json({"status": "failed", "code": "schema_check_failed"})
|
|
raise typer.Exit(code=1) from None
|
|
typer.secho("ERRORE: impossibile verificare le annotazioni.", fg=typer.colors.RED, err=True)
|
|
raise typer.Exit(code=1) from None
|
|
if json_output:
|
|
# ``ignored`` is human diagnostic context, not part of the machine contract.
|
|
_schema_json({key: payload[key] for key in ("status", "code", "orphan_count", "orphans")})
|
|
if payload["status"] != "succeeded":
|
|
raise typer.Exit(code=3)
|
|
return
|
|
if payload["ignored"]:
|
|
typer.secho(
|
|
f"Colonne ignorate (testo ampio, {len(payload['ignored'])}):",
|
|
fg=typer.colors.YELLOW,
|
|
)
|
|
for line in payload["ignored"]:
|
|
typer.echo(f" - {line}")
|
|
if payload["orphan_count"]:
|
|
typer.secho(f"ATTENZIONE: {payload['orphan_count']} annotazioni orfane:", fg=typer.colors.YELLOW)
|
|
for orphan in payload["orphans"]:
|
|
typer.echo(f" - {orphan}")
|
|
raise typer.Exit(code=3)
|
|
typer.secho("OK: nessuna annotazione orfana.", fg=typer.colors.GREEN)
|
|
|
|
|
|
def _render_schema_machine_error(error: _MachineSchemaError, cfg) -> None:
|
|
"""Render expected schema failures for the legacy human command contract."""
|
|
if error.code == "physical_schema_missing":
|
|
typer.secho(
|
|
f"ERRORE: {physical_path(cfg)} non trovato. Esegui prima `tht schema introspect`.",
|
|
fg=typer.colors.RED,
|
|
err=True,
|
|
)
|
|
elif error.code == "assumption_invalid":
|
|
detail = getattr(error, "detail", "")
|
|
typer.secho(
|
|
f"ERRORE: --assume '{detail}' non valido (atteso col=tabella nel catalogo).",
|
|
fg=typer.colors.RED,
|
|
err=True,
|
|
)
|
|
else:
|
|
typer.secho("ERRORE: impossibile elaborare il catalogo.", fg=typer.colors.RED, err=True)
|
|
raise typer.Exit(code=1) from None
|
|
|
|
|
|
@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)."), # noqa: B008
|
|
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:
|
|
"""Suggerisce FK logiche per la curazione umana in annotations.yaml."""
|
|
import yaml as _yaml
|
|
|
|
from tht.mschema.models import TableAnnotation
|
|
|
|
if json_output and write:
|
|
_schema_json({"status": "failed", "code": "write_not_allowed"})
|
|
raise typer.Exit(code=2)
|
|
if json_output:
|
|
try:
|
|
cfg = _load_schema_config(config, suppress_legacy_warning=True)
|
|
except ConfigError:
|
|
_schema_json({"status": "failed", "code": "invalid_configuration"})
|
|
raise typer.Exit(code=1) from None
|
|
else:
|
|
cfg = _load_config_or_exit(config)
|
|
try:
|
|
physical = _physical_or_error(cfg)
|
|
annotations = _annotations_or_error(cfg)
|
|
payload = suggest_fks_data(
|
|
cfg, from_sql=from_sql, assume=assume, physical=physical, annotations=annotations
|
|
)
|
|
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, cfg)
|
|
except Exception:
|
|
logger.exception("Schema suggestion failed")
|
|
if json_output:
|
|
_schema_json({"status": "failed", "code": "schema_suggestion_failed"})
|
|
raise typer.Exit(code=1) from None
|
|
typer.secho("ERRORE: impossibile elaborare il catalogo.", fg=typer.colors.RED, err=True)
|
|
raise typer.Exit(code=1) from None
|
|
if json_output:
|
|
_schema_json(payload)
|
|
return
|
|
|
|
# Human mode remains the original renderer over the pure result.
|
|
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,
|
|
)
|
|
if payload["ambiguous_columns"]:
|
|
typer.secho(
|
|
"PK ambigue saltate dalla regola same-name (piu' tabelle proprietarie): "
|
|
+ ", ".join(payload["ambiguous_columns"])
|
|
+ ". Se servono, aggiungile a mano o passa --from-sql.",
|
|
fg=typer.colors.YELLOW, err=True,
|
|
)
|
|
if not payload["candidates"]:
|
|
typer.secho("OK: nessuna FK da suggerire.", fg=typer.colors.GREEN)
|
|
return
|
|
candidate_tables = {
|
|
item["table"]: {"foreign_keys": item["foreign_keys"]}
|
|
for item in payload["candidates"]
|
|
}
|
|
if write:
|
|
for table_name, table_payload in candidate_tables.items():
|
|
ann = annotations.tables.setdefault(table_name, TableAnnotation())
|
|
from tht.mschema.models import ForeignKey
|
|
ann.foreign_keys.extend(ForeignKey(**fk) for fk in table_payload["foreign_keys"])
|
|
annotations.to_yaml(annotations_path(cfg))
|
|
typer.secho(
|
|
f"OK: {payload['candidate_count']} FK suggerite aggiunte a {annotations_path(cfg)} "
|
|
f"({len(candidate_tables)} tabelle). Rivedile a mano prima dell'uso.",
|
|
fg=typer.colors.GREEN,
|
|
)
|
|
return
|
|
typer.echo(_yaml.safe_dump({"tables": candidate_tables}, sort_keys=False, allow_unicode=True))
|
|
typer.secho(
|
|
f"{payload['candidate_count']} FK candidate ({len(candidate_tables)} tabelle). "
|
|
"Usa --write per fonderle in annotations.yaml, poi curale a mano.",
|
|
fg=typer.colors.YELLOW,
|
|
)
|
|
|
|
|
|
# PK con questi nomi sono identificatori generici: la regola same-name non si applica
|
|
# (nel DWH reale `id` e' la PK di ~50 tabelle e produrrebbe migliaia di falsi positivi).
|
|
_GENERIC_PK_NAMES = {"id", "key", "code"}
|
|
|
|
|
|
@schema_app.command("render")
|
|
def render_cmd(
|
|
config: Path = CONFIG_OPT,
|
|
format: str = typer.Option(
|
|
"markdown", "--format", "-f", help="Formato: markdown | mschema-text | schema-dict"
|
|
),
|
|
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)."), # noqa: B008
|
|
) -> None:
|
|
"""Serializza mschema (physical + annotations) nel formato richiesto."""
|
|
import json
|
|
|
|
from tht.mschema.models import Annotations, PhysicalSchema
|
|
from tht.mschema.render import to_markdown, to_mschema_text, to_schema_dict
|
|
|
|
cfg = _load_config_or_exit(config)
|
|
phys_file = physical_path(cfg)
|
|
if not phys_file.exists():
|
|
typer.secho(
|
|
f"ERRORE: {phys_file} non trovato. Esegui prima `tht schema introspect`.",
|
|
fg=typer.colors.RED, err=True,
|
|
)
|
|
raise typer.Exit(code=1)
|
|
physical = PhysicalSchema.from_yaml(phys_file)
|
|
annotations = Annotations.from_yaml(annotations_path(cfg))
|
|
table_filter = list(tables) if tables else None
|
|
|
|
if format == "markdown":
|
|
out = to_markdown(physical, annotations)
|
|
elif format == "mschema-text":
|
|
out = to_mschema_text(physical, annotations, tables=table_filter)
|
|
elif format == "schema-dict":
|
|
out = json.dumps(to_schema_dict(physical, annotations), ensure_ascii=False, indent=2)
|
|
else:
|
|
typer.secho(f"ERRORE: formato sconosciuto: {format}", fg=typer.colors.RED, err=True)
|
|
raise typer.Exit(code=1)
|
|
|
|
if output:
|
|
output.parent.mkdir(parents=True, exist_ok=True)
|
|
output.write_text(out)
|
|
typer.secho(f"OK: scritto {output}", fg=typer.colors.GREEN)
|
|
else:
|
|
typer.echo(out)
|
|
|
|
|
|
@schema_app.command("columns")
|
|
def columns_cmd(
|
|
table: str = typer.Argument(..., help="Nome tabella (chiave in physical.yaml)."),
|
|
json_out: bool = typer.Option(False, "--json", help="Emetti JSON puro su stdout."),
|
|
config: Path = CONFIG_OPT,
|
|
) -> None:
|
|
"""Elenca nome/descrizione/tipo/pk delle colonne di una tabella dal catalogo."""
|
|
import json as _json
|
|
|
|
from tht.mschema.models import PhysicalSchema
|
|
|
|
cfg = _load_config_or_exit(config)
|
|
phys_file = physical_path(cfg)
|
|
if not phys_file.exists():
|
|
typer.secho(
|
|
f"ERRORE: {phys_file} non trovato. Esegui prima `tht schema introspect`.",
|
|
fg=typer.colors.RED, err=True,
|
|
)
|
|
raise typer.Exit(code=1)
|
|
physical = PhysicalSchema.from_yaml(phys_file)
|
|
|
|
def _payload(name, tbl):
|
|
return {
|
|
"table": name,
|
|
"description": tbl.comment,
|
|
"columns": [
|
|
{"name": n, "description": col.comment, "type": col.type, "pk": col.pk}
|
|
for n, col in tbl.columns.items()
|
|
],
|
|
}
|
|
|
|
def _emit_human(p):
|
|
typer.echo(f"{p['table']}: {p['description']}")
|
|
for c in p["columns"]:
|
|
typer.echo(f" {'*' if c['pk'] else ' '} {c['name']} ({c['type']}) — {c['description']}")
|
|
|
|
# Glob-friendly: a pattern (containing * ? [) resolves to every matching catalog
|
|
# table, so a model can ask for a whole family (e.g. fact_sost_impianto_*) in one
|
|
# call instead of stalling on an unknown wildcard. Exact names keep the original
|
|
# single-object contract; JSON for a pattern is an array of per-table objects.
|
|
if any(ch in table for ch in "*?["):
|
|
from fnmatch import fnmatch
|
|
|
|
matches = sorted(n for n in physical.tables if fnmatch(n, table))
|
|
if not matches:
|
|
typer.secho(
|
|
f"ERRORE: nessuna tabella corrisponde al pattern: {table}",
|
|
fg=typer.colors.RED, err=True,
|
|
)
|
|
raise typer.Exit(code=1)
|
|
payloads = [_payload(n, physical.tables[n]) for n in matches]
|
|
if json_out:
|
|
typer.echo(_json.dumps(payloads, ensure_ascii=False))
|
|
return
|
|
for i, p in enumerate(payloads):
|
|
if i:
|
|
typer.echo("")
|
|
_emit_human(p)
|
|
return
|
|
|
|
tbl = physical.tables.get(table)
|
|
if tbl is None:
|
|
# Aid recovery: suggest catalog tables that share the leading segment.
|
|
prefix = table.rsplit("_", 1)[0] + "_" if "_" in table else table
|
|
hints = sorted(n for n in physical.tables if n.startswith(prefix))[:12]
|
|
msg = f"ERRORE: tabella non nel catalogo: {table}"
|
|
if hints:
|
|
msg += f" (forse: {', '.join(hints)})"
|
|
typer.secho(msg, fg=typer.colors.RED, err=True)
|
|
raise typer.Exit(code=1)
|
|
payload = _payload(table, tbl)
|
|
if json_out:
|
|
typer.echo(_json.dumps(payload, ensure_ascii=False))
|
|
return
|
|
_emit_human(payload)
|