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Donkie
e509378392
The declared floor was ">=3.10", but nothing enforced it: the Docker image has pinned python:3.14-slim-bookworm for amd64/arm64/armv7 for some time, and scripts/install.sh runs "uv sync" without UV_PYTHON_DOWNLOADS=0, so uv fetches a managed interpreter when the system one is too old. Every dependency declares a floor of <=3.10 with no upper cap. Raising it unlocks enum.StrEnum, datetime.UTC and typing.Self for the authentication work that follows. Consequences handled here: - uv.lock regenerated. Four pure-backport packages drop out (async-timeout, backports-asyncio-runner, exceptiongroup, tomli). - ruff target-version follows to py314, which switches on PEP 649 deferred annotations and with them a batch of previously-dormant rules. The safe automatic fixes are applied: datetime.timezone.utc -> datetime.UTC (UP017) and redundant quotes dropped from annotations (UP037). - TC001/TC002/TC003 are ignored rather than applied. They want type-only imports moved into "if TYPE_CHECKING:" blocks, which is wrong here: FastAPI resolves Annotated[AsyncSession, Depends(...)] and websocket parameters at runtime, Pydantic resolves field types at runtime, and SQLAlchemy resolves Mapped[...] at mapper-configuration time. A TYPE_CHECKING-only import is absent from the runtime namespace, so applying them breaks dependency injection. Ruff classifies all 50 as unsafe fixes for that reason. Verified: ruff check/format clean, uv lock --check clean, alembic head resolves, SQLAlchemy mappers configure with all relationships intact and lazy="selectin" preserved on the extra-field collections.
67 lines
2.6 KiB
Python
67 lines
2.6 KiB
Python
"""Functionality for exporting data in various format."""
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import asyncio
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import csv
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import json
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from collections.abc import Iterable
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from typing import TYPE_CHECKING, Any
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from spoolman.database import models
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if TYPE_CHECKING:
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from _typeshed import SupportsWrite
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banned_attrs = {"awaitable_attrs", "metadata", "registry", "spools", "filaments"}
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async def flatten_sqlalchemy_object(obj: models.Base, parent_key: str = "", sep: str = ".") -> dict[str, Any]:
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"""Recursively flattens a SQLAlchemy object into a dictionary with dot-separated keys."""
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fields = {}
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for attr in dir(obj):
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# Check if the attribute is a column or a relationship
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if not attr.startswith("_") and attr not in banned_attrs:
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value = await getattr(obj.awaitable_attrs, attr)
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if attr == "extra":
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# Handle extra fields
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for v in value:
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fields[f"{parent_key}extra.{v.key}"] = v.value
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continue
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# Handle nested SQLAlchemy objects
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if isinstance(value, models.Base):
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nested_fields = await flatten_sqlalchemy_object(value, f"{parent_key}{attr}{sep}", sep=sep)
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fields.update(nested_fields)
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else:
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# Use only columns and simple data types
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fields[f"{parent_key}{attr}"] = value
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return fields
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async def dump_as_csv(sqlalchemy_objects: Iterable[models.Base], writer: SupportsWrite[str]) -> None:
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"""Export a list of objects as CSV to a writer. Nested objects are flattened with dot-separated keys."""
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# Flatten each object and get all column names
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all_flattened = await asyncio.gather(*[flatten_sqlalchemy_object(obj) for obj in sqlalchemy_objects])
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# Collect all unique headers across flattened objects
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headers = set()
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for flattened_obj in all_flattened:
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headers.update(flattened_obj.keys())
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headers = sorted(headers) # Sort headers for consistent column ordering
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# Write to CSV
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csv_writer = csv.DictWriter(writer, fieldnames=headers)
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csv_writer.writeheader()
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for flattened_obj in all_flattened:
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csv_writer.writerow(flattened_obj)
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async def dump_as_json(sqlalchemy_objects: Iterable[models.Base], writer: SupportsWrite[str]) -> None:
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"""Export a list of objects as JSON to a writer. Nested objects are flattened with dot-separated keys."""
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# Flatten each object and get all column names
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all_flattened = await asyncio.gather(*[flatten_sqlalchemy_object(obj) for obj in sqlalchemy_objects])
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# Write to JSON
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json.dump(all_flattened, writer, default=str)
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