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Co-authored-by: Mike Bridge <michael.bridge@ext.preset.io> Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
93 lines
3.7 KiB
Python
93 lines
3.7 KiB
Python
# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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"""Continuum-shaped shadow-row writer.
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Two pieces:
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* :data:`CONTINUUM_BOOKKEEPING_COLUMNS` — the set of column names
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Continuum uses for per-row bookkeeping (``transaction_id`` /
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``end_transaction_id`` / ``operation_type``). Re-used outside this
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package as a filter (the change-record listener strips these from
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JSON record values).
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* :func:`insert_baseline_shadow_row` — copies a live row into a
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shadow ``Table`` as a synthetic ``operation_type=0`` baseline at
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the given transaction id. The other modules in this package use it
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for every parent and child baseline insert.
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"""
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from __future__ import annotations
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import logging
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from typing import Any
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import sqlalchemy as sa
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logger = logging.getLogger(__name__)
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# Continuum's per-shadow-row bookkeeping columns. Skipped when copying
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# content from a live row into a synthetic baseline shadow row; set
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# explicitly by the baseline writer so the row reads as a freshly-created
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# live row at the baseline transaction.
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CONTINUUM_BOOKKEEPING_COLUMNS: frozenset[str] = frozenset(
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{"transaction_id", "end_transaction_id", "operation_type"}
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)
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def insert_baseline_shadow_row(
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conn: Any,
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version_table: sa.Table,
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source_row: Any,
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tx_id: int,
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) -> None:
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"""Copy *source_row* into *version_table* as a synthetic baseline
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(``operation_type=0``) shadow row at *tx_id*.
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Content columns are copied through; the three Continuum bookkeeping
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columns are set explicitly so the row reads as a freshly-created
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live row at *tx_id*. Column objects (not names) are used as
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``values()`` keys to avoid the "Unconsumed column names" error that
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a name-based dict hits when a Column's ``.key`` differs from its
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``.name`` — a thing Continuum-generated tables occasionally produce.
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"""
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col_values: dict[Any, Any] = {}
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dropped: list[str] = []
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for col in version_table.columns:
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if col.name in CONTINUUM_BOOKKEEPING_COLUMNS:
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continue
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if col.name in source_row:
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col_values[col] = source_row[col.name]
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else:
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dropped.append(col.name)
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if dropped:
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# A content column present on the shadow table but absent from the
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# live source row means the two schemas have diverged (a Continuum
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# shadow column whose name doesn't match the live column). The value
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# would be stored NULL — a silent history-fidelity gap — so surface
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# it rather than dropping it quietly.
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logger.warning(
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"versioning: baseline shadow row for %s is missing source "
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"values for column(s) %s; they will be stored NULL. This "
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"indicates a name divergence between the live table and its "
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"Continuum shadow table.",
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version_table.name,
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", ".join(dropped),
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)
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col_values[version_table.c.transaction_id] = tx_id
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col_values[version_table.c.end_transaction_id] = None
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col_values[version_table.c.operation_type] = 0
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conn.execute(version_table.insert().values(col_values))
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