mirror of
https://github.com/hansjone/netx.git
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615 lines
22 KiB
Python
615 lines
22 KiB
Python
"""PostgreSQL-backed sheet compare (FULL OUTER JOIN) for pushdown-safe sheets.
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Falls back to the Python engine when port-map / complex rules cannot be expressed
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in SQL. See ``can_sql_compare``.
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"""
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from __future__ import annotations
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import logging
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import re
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from typing import Any, Callable, Mapping, Sequence
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from uuid import uuid4
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from sqlalchemy import text
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from sqlalchemy.orm import Session
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from .compare_rules import effective_compare_fields, field_rule_map
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_log = logging.getLogger("netx.biz_state.compare_sql")
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_FIELD_RE = re.compile(r"^[A-Za-z_][A-Za-z0-9_]*$")
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_SQL_FILTER_OPS = frozenset(
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{"eq", "==", "ne", "!=", "in", "not_in", "nin", "contains", "empty", "not_empty", "nonempty", "ci_eq"}
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)
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_SQL_NORMALIZE = frozenset({"", "none", "strip", "lower", "upper", "empty_as_blank"})
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_SQL_COMPARE_MODES = frozenset({"", "eq", "ignore", "skip", "off"})
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_EMPTY_AS_BLANK = ("n/a", "na", "-", "--", "none", "null")
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def _dialect_is_postgres(db: Session) -> bool:
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bind = db.get_bind()
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if bind is None:
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return False
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return str(getattr(bind.dialect, "name", "") or "").lower() in ("postgresql", "postgres")
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def _safe_field(name: str) -> str:
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f = str(name or "").strip()
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if not f or not _FIELD_RE.match(f):
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raise ValueError(f"unsafe_json_field:{name!r}")
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return f
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def _json_text_expr(alias: str, field: str) -> str:
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"""SQL expression: trimmed text from JSONB column ``alias.data`` / ``data_json``."""
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f = _safe_field(field)
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# alias is caller-controlled (_b / data_json) — not user input
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return f"trim(both from coalesce({alias}->>'{f}', ''))"
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def _norm_expr(alias: str, field: str, normalize: str) -> str:
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base = _json_text_expr(alias, field)
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mode = str(normalize or "strip").strip().lower() or "strip"
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if mode in ("", "none", "strip"):
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return base
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if mode == "lower":
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return f"lower({base})"
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if mode == "upper":
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return f"upper({base})"
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if mode == "empty_as_blank":
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opts = ", ".join(f"'{x}'" for x in _EMPTY_AS_BLANK)
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return (
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f"CASE WHEN lower({base}) IN ({opts}) THEN '' ELSE {base} END"
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)
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raise ValueError(f"unsupported_normalize:{mode}")
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def _filters_sql_compatible(filters: Sequence[Mapping[str, Any]] | None) -> bool:
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fl = [f for f in (filters or []) if isinstance(f, dict)]
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return all(_filter_node_compatible(f) for f in fl)
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def _filter_node_compatible(filt: Mapping[str, Any]) -> bool:
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if "any" in filt:
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kids = filt.get("any") or []
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return isinstance(kids, list) and all(
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isinstance(k, dict) and _filter_node_compatible(k) for k in kids
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)
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if "all" in filt:
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kids = filt.get("all") or []
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return isinstance(kids, list) and all(
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isinstance(k, dict) and _filter_node_compatible(k) for k in kids
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)
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field = str(filt.get("field") or "").strip()
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op = str(filt.get("op") or "eq").strip().lower()
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if op not in _SQL_FILTER_OPS:
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return False
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if op in ("empty", "not_empty", "nonempty"):
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return bool(field) and bool(_FIELD_RE.match(field))
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if not field or not _FIELD_RE.match(field):
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return False
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if op in ("in", "not_in", "nin"):
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vals = filt.get("value")
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if vals is None:
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return True
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if not isinstance(vals, (list, tuple)):
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vals = [vals]
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return all(isinstance(x, (str, int, float, bool)) or x is None for x in vals)
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return True
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def _field_rules_sql_compatible(rules: Sequence[Mapping[str, Any]] | None) -> bool:
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for raw in rules or []:
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if not isinstance(raw, dict):
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return False
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name = str(raw.get("field") or "").strip()
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if name and not _FIELD_RE.match(name):
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return False
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mode = str(raw.get("compare") or "eq").strip().lower() or "eq"
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if mode not in _SQL_COMPARE_MODES:
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return False
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if raw.get("ignore") is True:
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continue
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if mode in ("ignore", "skip", "off"):
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continue
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norm = str(raw.get("normalize") or "strip").strip().lower() or "strip"
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if norm not in _SQL_NORMALIZE:
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return False
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return True
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def can_sql_compare(
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db: Session,
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sheet: Mapping[str, Any],
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*,
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port_map: Mapping[str, str] | None = None,
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iface_normalize_rules: Sequence[Mapping[str, str]] | None = None,
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) -> bool:
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"""True when this sheet can run entirely as a PostgreSQL JOIN."""
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if not _dialect_is_postgres(db):
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return False
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if port_map:
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return False
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key_fields = [str(k).strip() for k in (sheet.get("key_fields") or []) if str(k).strip()]
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if not key_fields or any(not _FIELD_RE.match(k) for k in key_fields):
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return False
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iface_fields = [str(f).strip() for f in (sheet.get("iface_fields") or []) if str(f).strip()]
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iface_set = set(iface_fields)
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# Port-rename heuristic / map rewrite cannot be expressed here
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ignore_ports = sheet.get("ignore_port_changes")
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if ignore_ports is True:
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return False
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if ignore_ports is None and iface_set and any(k in iface_set for k in key_fields):
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# Auto path may drop iface from match key — stay on Python
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return False
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field_rules = list(sheet.get("field_rules") or [])
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if not _field_rules_sql_compatible(field_rules):
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return False
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compare_fields = effective_compare_fields(
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list(sheet.get("compare_fields") or []),
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field_rules,
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)
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if any(not _FIELD_RE.match(str(f).strip()) for f in compare_fields if str(f).strip()):
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return False
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used = set(key_fields) | {str(f).strip() for f in compare_fields if str(f).strip()}
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if iface_normalize_rules and (used & iface_set):
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return False
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if not _filters_sql_compatible(list(sheet.get("row_filters") or [])):
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return False
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if not str(sheet.get("metric_id") or "").strip():
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return False
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return True
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def compile_row_filters_sql(
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filters: Sequence[Mapping[str, Any]] | None,
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*,
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json_col: str = "data_json",
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param_prefix: str = "f",
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) -> tuple[str, dict[str, Any]]:
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"""Compile template row_filters to SQL AND-clause + bind params.
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Returns ``(sql_fragment, params)``. Empty filters → ``(\"TRUE\", {})``.
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``json_col`` is the JSONB column/expression name (trusted).
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"""
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fl = [f for f in (filters or []) if isinstance(f, dict)]
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if not fl:
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return "TRUE", {}
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params: dict[str, Any] = {}
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counter = {"n": 0}
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def _next(name: str) -> str:
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counter["n"] += 1
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return f"{param_prefix}_{counter['n']}_{name}"
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def _node(filt: Mapping[str, Any]) -> str:
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if "any" in filt:
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kids = [k for k in (filt.get("any") or []) if isinstance(k, dict)]
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if not kids:
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return "TRUE"
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return "(" + " OR ".join(_node(k) for k in kids) + ")"
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if "all" in filt:
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kids = [k for k in (filt.get("all") or []) if isinstance(k, dict)]
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if not kids:
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return "TRUE"
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return "(" + " AND ".join(_node(k) for k in kids) + ")"
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field = _safe_field(str(filt.get("field") or ""))
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op = str(filt.get("op") or "eq").strip().lower()
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expr = _json_text_expr(json_col, field)
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# _json_text_expr uses alias->> ; for bare column use data_json directly
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if json_col == "data_json":
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expr = f"trim(both from coalesce(data_json->>'{field}', ''))"
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if op in ("empty",):
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return f"({expr} = '')"
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if op in ("not_empty", "nonempty"):
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return f"({expr} <> '')"
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expect = filt.get("value")
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if op in ("eq", "==", "ci_eq"):
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key = _next("v")
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params[key] = str(expect or "").strip()
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if op == "ci_eq" or op in ("eq", "=="):
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# Python eq is case-insensitive via .lower()
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params[key] = str(expect or "").strip().lower()
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return f"(lower({expr}) = :{key})"
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if op in ("ne", "!="):
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key = _next("v")
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params[key] = str(expect or "").strip().lower()
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return f"(lower({expr}) <> :{key})"
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if op == "contains":
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key = _next("v")
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needle = str(expect or "").strip().lower()
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params[key] = f"%{needle}%"
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return f"(lower({expr}) LIKE :{key})"
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if op in ("in", "not_in", "nin"):
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vals = expect
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if vals is None:
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vals = []
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if not isinstance(vals, (list, tuple)):
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vals = [vals]
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clean = [str(x).strip().lower() for x in vals if str(x).strip()]
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if not clean:
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return "FALSE" if op == "in" else "TRUE"
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keys = []
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for i, v in enumerate(clean):
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k = _next(f"in{i}")
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params[k] = v
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keys.append(f":{k}")
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inside = f"lower({expr}) IN ({', '.join(keys)})"
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return f"({inside})" if op == "in" else f"(NOT {inside})"
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raise ValueError(f"unsupported_filter_op:{op}")
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parts = [_node(f) for f in fl]
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return "(" + " AND ".join(parts) + ")", params
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def _rk_sql(key_fields: list[str], *, json_col: str = "data_json") -> str:
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parts = []
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for k in key_fields:
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f = _safe_field(k)
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if json_col == "data_json":
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parts.append(f"trim(both from coalesce(data_json->>'{f}', ''))")
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else:
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parts.append(f"trim(both from coalesce({json_col}->>'{f}', ''))")
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if len(parts) == 1:
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return parts[0]
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return "concat_ws('|', " + ", ".join(parts) + ")"
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def _changed_predicate(
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compare_fields: list[str],
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rules: dict[str, dict[str, Any]],
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*,
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before_alias: str = "b",
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after_alias: str = "a",
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) -> str:
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"""SQL boolean: True when any compare field differs (IS DISTINCT FROM)."""
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if not compare_fields:
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return "FALSE"
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clauses: list[str] = []
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for f in compare_fields:
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name = str(f).strip()
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if not name:
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continue
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rule = rules.get(name) or {}
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mode = str(rule.get("compare") or "eq").strip().lower() or "eq"
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if mode in ("ignore", "skip", "off") or rule.get("ignore") is True:
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continue
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norm = str(rule.get("normalize") or "strip").strip().lower() or "strip"
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bv = _norm_expr(f"{before_alias}.data", name, norm)
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av = _norm_expr(f"{after_alias}.data", name, norm)
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clauses.append(f"({bv} IS DISTINCT FROM {av})")
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if not clauses:
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return "FALSE"
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return "(" + " OR ".join(clauses) + ")"
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def _key_obj_from_data(data: dict[str, Any] | None, key_fields: list[str]) -> dict[str, Any]:
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row = data if isinstance(data, dict) else {}
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return {f: row.get(f, "") for f in key_fields}
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def _changes_from_rows(
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before: dict[str, Any] | None,
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after: dict[str, Any] | None,
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compare_fields: list[str],
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rules: dict[str, dict[str, Any]],
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) -> dict[str, dict[str, Any]]:
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from .compare_rules import explain_diff, values_equal
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out: dict[str, dict[str, Any]] = {}
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b = before or {}
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a = after or {}
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for f in compare_fields:
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rule = rules.get(f)
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bv = b.get(f, "")
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av = a.get(f, "")
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if values_equal(bv, av, rule=rule):
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continue
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entry: dict[str, Any] = {"before": bv, "after": av}
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reason = explain_diff(bv, av, rule=rule)
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if reason:
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entry["reason"] = reason
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out[f] = entry
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return out
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def run_sql_sheet_compare(
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db: Session,
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*,
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sheet: Mapping[str, Any],
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before_batch_id: str,
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after_batch_id: str,
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store_unchanged: str = "auto",
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on_progress: Callable[[str, int], None] | None = None,
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) -> dict[str, Any]:
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"""Compare one sheet via PostgreSQL TEMP tables + FULL OUTER JOIN.
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Returns the same ``{summary, diffs, mapping_stats}`` shape as ``compare_rows``.
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"""
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if not _dialect_is_postgres(db):
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raise RuntimeError("sql_compare_requires_postgres")
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key_fields = [str(k).strip() for k in (sheet.get("key_fields") or []) if str(k).strip()]
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field_rules = list(sheet.get("field_rules") or [])
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rules = field_rule_map(field_rules)
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compare_fields = effective_compare_fields(
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list(sheet.get("compare_fields") or []),
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field_rules,
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)
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row_filters = list(sheet.get("row_filters") or [])
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mid = str(sheet.get("metric_id") or "").strip()
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bid_b = str(before_batch_id or "").strip()
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bid_a = str(after_batch_id or "").strip()
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if not mid or not bid_b or not bid_a or not key_fields:
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raise ValueError("sql_compare_missing_args")
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filter_sql, filter_params = compile_row_filters_sql(row_filters)
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rk = _rk_sql(key_fields)
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tag = uuid4().hex[:8]
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tb = f"_netx_cmp_b_{tag}"
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ta = f"_netx_cmp_a_{tag}"
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# Raw counts (no row_filters)
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raw_b = int(
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db.execute(
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text(
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"SELECT count(*) FROM biz_state_metric_row "
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"WHERE batch_id = :bid AND metric_id = :mid"
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),
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{"bid": bid_b, "mid": mid},
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).scalar()
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or 0
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)
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if on_progress:
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on_progress("before", raw_b)
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raw_a = int(
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db.execute(
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text(
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"SELECT count(*) FROM biz_state_metric_row "
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"WHERE batch_id = :bid AND metric_id = :mid"
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),
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{"bid": bid_a, "mid": mid},
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).scalar()
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or 0
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)
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if on_progress:
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on_progress("after", raw_a)
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base_params = {"bid": bid_b, "mid": mid, **filter_params}
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# Build TEMP sides
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for tname, batch_id in ((tb, bid_b), (ta, bid_a)):
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db.execute(text(f"DROP TABLE IF EXISTS {tname}"))
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params = {**base_params, "bid": batch_id}
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# PRESERVE ROWS: compare progress commits must not drop temps mid-run
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db.execute(
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text(
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f"""
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CREATE TEMP TABLE {tname} ON COMMIT PRESERVE ROWS AS
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SELECT
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id,
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({rk}) AS rk,
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data_json AS data,
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row_number() OVER (
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PARTITION BY ({rk})
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ORDER BY seq ASC, id ASC
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) AS dup_rn
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FROM biz_state_metric_row
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WHERE batch_id = :bid
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AND metric_id = :mid
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AND ({filter_sql})
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"""
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),
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params,
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)
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db.execute(text(f"CREATE INDEX ON {tname} (rk) WHERE dup_rn = 1"))
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before_n = int(
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db.execute(text(f"SELECT count(*) FROM {tb}")).scalar() or 0
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)
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after_n = int(
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db.execute(text(f"SELECT count(*) FROM {ta}")).scalar() or 0
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)
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if on_progress:
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on_progress("after", after_n)
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changed_pred = _changed_predicate(compare_fields, rules)
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kind_expr = f"""
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CASE
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WHEN b.id IS NULL THEN 'added'
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WHEN a.id IS NULL THEN 'removed'
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WHEN {changed_pred} THEN 'changed'
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ELSE 'unchanged'
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END
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"""
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# Aggregate primary match kinds (first-wins keys only)
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agg_rows = db.execute(
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text(
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f"""
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SELECT {kind_expr} AS kind, count(*)::bigint AS n
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FROM (SELECT * FROM {tb} WHERE dup_rn = 1) b
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FULL OUTER JOIN (SELECT * FROM {ta} WHERE dup_rn = 1) a
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ON b.rk = a.rk
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GROUP BY 1
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"""
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)
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).mappings().all()
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counts = {str(r["kind"]): int(r["n"] or 0) for r in agg_rows}
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added = counts.get("added", 0)
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removed = counts.get("removed", 0)
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changed = counts.get("changed", 0)
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unchanged = counts.get("unchanged", 0)
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dup_b = int(
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db.execute(text(f"SELECT count(*) FROM {tb} WHERE dup_rn > 1")).scalar() or 0
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)
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dup_a = int(
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db.execute(text(f"SELECT count(*) FROM {ta} WHERE dup_rn > 1")).scalar() or 0
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)
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duplicate = dup_b + dup_a
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# Lazy import — avoid circular import with compare_service
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from .compare_service import resolve_unchanged_policy
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policy = resolve_unchanged_policy(
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store_unchanged, before_n=before_n, after_n=after_n
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)
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diffs: list[dict[str, Any]] = []
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# Fail + duplicate rows (stream into Python — should be << million)
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fail_sql = text(
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f"""
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SELECT
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{kind_expr} AS kind,
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b.id AS before_row_id,
|
|
a.id AS after_row_id,
|
|
b.data AS before_data,
|
|
a.data AS after_data,
|
|
COALESCE(b.rk, a.rk) AS rk
|
|
FROM (SELECT * FROM {tb} WHERE dup_rn = 1) b
|
|
FULL OUTER JOIN (SELECT * FROM {ta} WHERE dup_rn = 1) a
|
|
ON b.rk = a.rk
|
|
WHERE {kind_expr} IN ('added', 'removed', 'changed')
|
|
"""
|
|
)
|
|
for row in db.execute(fail_sql).mappings():
|
|
kind = str(row["kind"] or "")
|
|
before = dict(row["before_data"] or {}) if row["before_data"] is not None else None
|
|
after = dict(row["after_data"] or {}) if row["after_data"] is not None else None
|
|
key_src = after if kind == "added" else (before or after or {})
|
|
item: dict[str, Any] = {
|
|
"kind": kind,
|
|
"key": _key_obj_from_data(key_src, key_fields),
|
|
"before": before,
|
|
"after": after,
|
|
"mapped_before": before,
|
|
"changes": {},
|
|
"before_row_id": str(row["before_row_id"] or ""),
|
|
"after_row_id": str(row["after_row_id"] or ""),
|
|
}
|
|
if kind == "changed":
|
|
item["changes"] = _changes_from_rows(before, after, compare_fields, rules)
|
|
diffs.append(item)
|
|
|
|
# Duplicate extras
|
|
for side, tname in (("before", tb), ("after", ta)):
|
|
q = text(
|
|
f"""
|
|
SELECT id, data, rk FROM {tname} WHERE dup_rn > 1
|
|
"""
|
|
)
|
|
for row in db.execute(q).mappings():
|
|
data = dict(row["data"] or {})
|
|
diffs.append(
|
|
{
|
|
"kind": "duplicate",
|
|
"side": side,
|
|
"key": _key_obj_from_data(data, key_fields),
|
|
"before": data if side == "before" else None,
|
|
"after": data if side == "after" else None,
|
|
"mapped_before": data if side == "before" else None,
|
|
"changes": {},
|
|
"before_row_id": str(row["id"] or "") if side == "before" else "",
|
|
"after_row_id": str(row["id"] or "") if side == "after" else "",
|
|
}
|
|
)
|
|
|
|
unchanged_listed = 0
|
|
include_u = bool(policy.get("include"))
|
|
compact = bool(policy.get("compact"))
|
|
limit_n = policy.get("limit")
|
|
if include_u and unchanged > 0:
|
|
lim_sql = ""
|
|
params_u: dict[str, Any] = {}
|
|
if limit_n is not None:
|
|
lim_sql = " LIMIT :lim"
|
|
params_u["lim"] = max(0, int(limit_n))
|
|
u_sql = text(
|
|
f"""
|
|
SELECT
|
|
b.id AS before_row_id,
|
|
a.id AS after_row_id,
|
|
b.data AS before_data,
|
|
a.data AS after_data
|
|
FROM (SELECT * FROM {tb} WHERE dup_rn = 1) b
|
|
INNER JOIN (SELECT * FROM {ta} WHERE dup_rn = 1) a
|
|
ON b.rk = a.rk
|
|
WHERE NOT ({changed_pred})
|
|
{lim_sql}
|
|
"""
|
|
)
|
|
for row in db.execute(u_sql, params_u).mappings():
|
|
before = dict(row["before_data"] or {})
|
|
after = dict(row["after_data"] or {})
|
|
unchanged_listed += 1
|
|
if compact:
|
|
diffs.append(
|
|
{
|
|
"kind": "unchanged",
|
|
"key": _key_obj_from_data(before, key_fields),
|
|
"before": {},
|
|
"after": {},
|
|
"mapped_before": {},
|
|
"changes": {},
|
|
"compact": True,
|
|
"before_row_id": str(row["before_row_id"] or ""),
|
|
"after_row_id": str(row["after_row_id"] or ""),
|
|
}
|
|
)
|
|
else:
|
|
diffs.append(
|
|
{
|
|
"kind": "unchanged",
|
|
"key": _key_obj_from_data(before, key_fields),
|
|
"before": before,
|
|
"after": after,
|
|
"mapped_before": before,
|
|
"changes": {},
|
|
"before_row_id": str(row["before_row_id"] or ""),
|
|
"after_row_id": str(row["after_row_id"] or ""),
|
|
}
|
|
)
|
|
|
|
# Cleanup (also ON COMMIT DROP)
|
|
db.execute(text(f"DROP TABLE IF EXISTS {tb}"))
|
|
db.execute(text(f"DROP TABLE IF EXISTS {ta}"))
|
|
|
|
dup_key_list: list[str] = []
|
|
summary = {
|
|
"before_count": before_n,
|
|
"after_count": after_n,
|
|
"added": added,
|
|
"removed": removed,
|
|
"changed": changed,
|
|
"unchanged": unchanged,
|
|
"duplicate": duplicate,
|
|
"match_key_fields": list(key_fields),
|
|
"duplicate_keys_before": dup_b,
|
|
"duplicate_keys_after": dup_a,
|
|
"duplicate_key_list": dup_key_list,
|
|
"unchanged_listed": unchanged_listed,
|
|
"unchanged_truncated": bool(
|
|
include_u and limit_n is not None and unchanged > unchanged_listed
|
|
),
|
|
"unchanged_compact": bool(compact and unchanged_listed > 0),
|
|
"engine": "sql",
|
|
"before_raw_count": raw_b,
|
|
"after_raw_count": raw_a,
|
|
"row_filters": len(row_filters),
|
|
"unchanged_policy": policy,
|
|
}
|
|
mapping_stats = {
|
|
"before_iface_count": 0,
|
|
"after_iface_count": 0,
|
|
"map_pairs": 0,
|
|
"hit_before": [],
|
|
"miss_before": [],
|
|
"hit_after": [],
|
|
"miss_after": [],
|
|
"unused_before_keys": [],
|
|
"ok": True,
|
|
"ignore_port_changes": False,
|
|
"engine": "sql",
|
|
}
|
|
return {"summary": summary, "diffs": diffs, "mapping_stats": mapping_stats}
|