File size: 8,777 Bytes
6bff5d9 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 | """Database schema introspection (Postgres / MySQL / Supabase).
Reads information_schema for tables/columns/types, samples ~100 rows per table
for `sample_values` and basic stats. Description fields are left empty —
the planner relies on names + samples + stats directly.
Reuses Phase 1 utilities (`database_client_service`, `db_credential_encryption`,
`db_pipeline_service.engine_scope`, `extractor.get_schema/profile_column/get_row_count`)
to avoid reimplementation. The cleanup PR will move those into `security/` and
`pipeline/db_pipeline/` respectively.
"""
import asyncio
import hashlib
from datetime import UTC, datetime
from decimal import Decimal
from typing import Any
from src.database_client.database_client_service import database_client_service
from src.db.postgres.connection import AsyncSessionLocal
from src.middlewares.logging import get_logger
from src.pipeline.db_pipeline import db_pipeline_service
from src.pipeline.db_pipeline.extractor import (
get_row_count,
get_schema,
profile_column,
)
from src.utils.db_credential_encryption import decrypt_credentials_dict
from ..models import Column, ColumnStats, DataType, ForeignKey, Source, Table
from ..pii_detector import PIIDetector
from .base import BaseIntrospector
logger = get_logger("db_introspector")
_DBCLIENT_PREFIX = "dbclient://"
def _stable_id(prefix: str, *parts: str) -> str:
"""Deterministic short ID from joined parts. Survives renames at the
`name` field while preserving identity for cached IRs.
Hash is non-cryptographic (identifier only).
"""
h = hashlib.sha1(
"/".join(parts).encode("utf-8"), usedforsecurity=False
).hexdigest()[:12]
return f"{prefix}{h}"
def _map_sql_type(sql_type: str) -> DataType:
"""Map a stringified SQLAlchemy type to a Catalog DataType.
Matches on substring of the SQLAlchemy type repr (e.g. 'INTEGER',
'TIMESTAMP', 'BOOLEAN'). Conservative — unknowns fall back to "string"
so the column is at least addressable.
"""
s = sql_type.upper()
if "INT" in s:
return "int"
if "FLOAT" in s or "NUMERIC" in s or "DECIMAL" in s or "REAL" in s or "DOUBLE" in s:
return "decimal"
if "BOOL" in s:
return "bool"
if "TIMESTAMP" in s or "DATETIME" in s:
return "datetime"
if "DATE" in s:
return "date"
if "JSON" in s:
return "json"
return "string"
def _normalize(v: Any) -> Any:
"""Coerce non-JSON-native scalars (Decimal, numpy, datetime) to types
that survive the jsonb round-trip when the catalog is persisted.
"""
if v is None:
return None
if isinstance(v, Decimal):
return float(v)
try:
import numpy as np
if isinstance(v, np.generic):
return v.item()
except ImportError:
pass
if isinstance(v, datetime):
return v.isoformat()
return v
class DatabaseIntrospector(BaseIntrospector):
"""Connect to user DB → read information_schema → sample 100 rows/table."""
def __init__(self) -> None:
self._pii = PIIDetector()
async def introspect(self, location_ref: str) -> Source:
if not location_ref.startswith(_DBCLIENT_PREFIX):
raise ValueError(
f"DatabaseIntrospector expects 'dbclient://...' location_ref, "
f"got {location_ref!r}"
)
client_id = location_ref[len(_DBCLIENT_PREFIX):]
if not client_id:
raise ValueError("location_ref is missing client_id after 'dbclient://'")
async with AsyncSessionLocal() as session:
client = await database_client_service.get(session, client_id)
if client is None:
raise ValueError(f"DatabaseClient {client_id!r} not found")
creds = decrypt_credentials_dict(client.credentials)
logger.info(
"introspecting db source",
client_id=client_id,
db_type=client.db_type,
name=client.name,
)
# SQLAlchemy inspect() + pandas read_sql are synchronous — run in a
# threadpool so the event loop stays free.
tables: list[Table] = await asyncio.to_thread(
self._introspect_sync, client.db_type, creds
)
return Source(
source_id=client_id,
source_type="schema",
name=client.name,
location_ref=location_ref,
updated_at=datetime.now(UTC),
tables=tables,
)
def _introspect_sync(self, db_type: str, creds: dict) -> list[Table]:
with db_pipeline_service.engine_scope(db_type, creds) as engine:
schema = get_schema(engine)
tables: list[Table] = []
for table_name, cols in schema.items():
try:
row_count = get_row_count(engine, table_name)
except Exception as e:
logger.error(
"row_count failed; skipping table",
table=table_name,
error=str(e),
)
continue
columns: list[Column] = []
for col in cols:
try:
profile = profile_column(
engine,
table_name,
col["name"],
col.get("is_numeric", False),
row_count,
is_temporal=col.get("is_temporal", False),
)
except Exception as e:
logger.error(
"profile_column failed; skipping column",
table=table_name,
column=col["name"],
error=str(e),
)
continue
columns.append(self._to_column(table_name, col, profile))
foreign_keys = self._extract_foreign_keys(table_name, cols)
tables.append(
Table(
table_id=_stable_id("t_", table_name),
name=table_name,
row_count=row_count,
columns=columns,
foreign_keys=foreign_keys,
)
)
return tables
@staticmethod
def _extract_foreign_keys(
table_name: str, cols: list[dict[str, Any]]
) -> list[ForeignKey]:
"""Convert extractor's `foreign_key: 'target_table.target_col'` strings
into ForeignKey objects with stable IDs (derived deterministically from
names — same scheme used to generate table_id / column_id elsewhere).
"""
fks: list[ForeignKey] = []
for col in cols:
fk_str = col.get("foreign_key")
if not fk_str:
continue
target_table, _, target_col = fk_str.partition(".")
if not target_table or not target_col:
continue
fks.append(
ForeignKey(
column_id=_stable_id("c_", table_name, col["name"]),
target_table_id=_stable_id("t_", target_table),
target_column_id=_stable_id("c_", target_table, target_col),
)
)
return fks
def _to_column(
self, table_name: str, col: dict[str, Any], profile: dict[str, Any]
) -> Column:
name = col["name"]
sample_values: list[Any] | None = [
_normalize(v) for v in (profile.get("sample_values") or [])
] or None
top_raw = profile.get("top_values") or []
top_values: list[Any] | None = [
_normalize(v) for v, _cnt in top_raw
] or None
column = Column(
column_id=_stable_id("c_", table_name, name),
name=name,
data_type=_map_sql_type(str(col["type"])),
nullable=True, # nullable not surfaced by extractor; default permissive
pii_flag=False,
sample_values=sample_values,
stats=ColumnStats(
min=_normalize(profile.get("min")),
max=_normalize(profile.get("max")),
mean=_normalize(profile.get("mean")),
median=_normalize(profile.get("median")),
distinct_count=profile.get("distinct_count"),
top_values=top_values,
),
)
if self._pii.detect(column):
return column.model_copy(update={"pii_flag": True, "sample_values": None})
return column
database_introspector = DatabaseIntrospector()
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