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77 lines
4.3 KiB
Python
77 lines
4.3 KiB
Python
"""Add Sprint 7A vector feature and QA persistence foundation."""
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from alembic import op
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import sqlalchemy as sa
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from geoalchemy2 import Geometry
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revision = "202606120700"
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down_revision = "202606120001"
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branch_labels = None
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depends_on = None
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def upgrade() -> None:
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op.create_table(
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"vector_features",
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sa.Column("id", sa.UUID(as_uuid=True), primary_key=True),
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sa.Column("dataset_id", sa.UUID(as_uuid=True), sa.ForeignKey("datasets.id", ondelete="CASCADE"), nullable=False),
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sa.Column("feature_class", sa.Text(), nullable=True),
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sa.Column("source_feature_id", sa.Text(), nullable=True),
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sa.Column("properties_json", sa.JSON(), nullable=True),
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sa.Column("geometry", Geometry("GEOMETRY", srid=4326, spatial_index=False), nullable=False),
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sa.Column("created_at", sa.DateTime(timezone=True), server_default=sa.text("NOW()")),
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)
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op.create_index("ix_vector_features_dataset_id", "vector_features", ["dataset_id"])
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op.create_index("ix_vector_features_geometry", "vector_features", ["geometry"], postgresql_using="gist")
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op.create_table(
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"quality_checks",
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sa.Column("id", sa.UUID(as_uuid=True), primary_key=True),
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sa.Column("project_id", sa.UUID(as_uuid=True), sa.ForeignKey("projects.id", ondelete="CASCADE"), nullable=False),
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sa.Column("job_id", sa.UUID(as_uuid=True), sa.ForeignKey("jobs.id", ondelete="SET NULL"), nullable=True),
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sa.Column("analysis_run_id", sa.UUID(as_uuid=True), sa.ForeignKey("analysis_runs.id", ondelete="SET NULL"), nullable=True),
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sa.Column("candidate_dataset_id", sa.UUID(as_uuid=True), sa.ForeignKey("datasets.id", ondelete="SET NULL"), nullable=True),
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sa.Column("reference_dataset_id", sa.UUID(as_uuid=True), sa.ForeignKey("datasets.id", ondelete="CASCADE"), nullable=False),
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sa.Column("check_type", sa.Text(), nullable=False),
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sa.Column("status", sa.Text(), nullable=False),
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sa.Column("score", sa.Float(), nullable=True),
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sa.Column("parameters_json", sa.JSON(), nullable=True),
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sa.Column("findings_json", sa.JSON(), nullable=True),
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sa.Column("created_at", sa.DateTime(timezone=True), server_default=sa.text("NOW()")),
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sa.Column("completed_at", sa.DateTime(timezone=True), nullable=True),
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)
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op.create_index("ix_quality_checks_project_id", "quality_checks", ["project_id"])
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op.create_index("ix_quality_checks_reference_dataset_id", "quality_checks", ["reference_dataset_id"])
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op.create_index("ix_quality_checks_candidate_dataset_id", "quality_checks", ["candidate_dataset_id"])
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op.create_index("ix_quality_checks_analysis_run_id", "quality_checks", ["analysis_run_id"])
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op.create_table(
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"metrics",
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sa.Column("id", sa.UUID(as_uuid=True), primary_key=True),
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sa.Column("quality_check_id", sa.UUID(as_uuid=True), sa.ForeignKey("quality_checks.id", ondelete="CASCADE"), nullable=True),
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sa.Column("analysis_run_id", sa.UUID(as_uuid=True), sa.ForeignKey("analysis_runs.id", ondelete="SET NULL"), nullable=True),
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sa.Column("metric_key", sa.Text(), nullable=False),
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sa.Column("metric_value", sa.Float(), nullable=True),
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sa.Column("metric_unit", sa.Text(), nullable=True),
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sa.Column("label", sa.Text(), nullable=True),
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sa.Column("metadata_json", sa.JSON(), nullable=True),
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sa.Column("created_at", sa.DateTime(timezone=True), server_default=sa.text("NOW()")),
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)
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op.create_index("ix_metrics_quality_check_id", "metrics", ["quality_check_id"])
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op.create_index("ix_metrics_analysis_run_id", "metrics", ["analysis_run_id"])
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def downgrade() -> None:
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op.drop_index("ix_metrics_analysis_run_id", table_name="metrics")
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op.drop_index("ix_metrics_quality_check_id", table_name="metrics")
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op.drop_table("metrics")
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op.drop_index("ix_quality_checks_analysis_run_id", table_name="quality_checks")
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op.drop_index("ix_quality_checks_candidate_dataset_id", table_name="quality_checks")
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op.drop_index("ix_quality_checks_reference_dataset_id", table_name="quality_checks")
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op.drop_index("ix_quality_checks_project_id", table_name="quality_checks")
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op.drop_table("quality_checks")
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op.drop_index("ix_vector_features_geometry", table_name="vector_features", postgresql_using="gist")
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op.drop_index("ix_vector_features_dataset_id", table_name="vector_features")
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op.drop_table("vector_features")
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