Johan LEROY
c733ccfc62
La convention de docs/architecture/40-data.md impose des noms de tables au singulier, que les quatre tables d'authentification respectent déjà. Les six tables data passent donc au singulier, avec leurs contraintes et leurs index. La révision n'étant appliquée que sur des bases locales, elle est modifiée sur place plutôt que doublée d'une migration de renommage. alert_id désignait deux colonnes différentes : la clé métier text de l'API Mock et la clé étrangère bigint de recommendation. La première devient source_alert_id, la seconde pointe désormais vers alert.alert_id.
219 lines
9.5 KiB
Python
219 lines
9.5 KiB
Python
"""Création des six tables Data et de l'hypertable reading.
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Revision ID: e6d2026091501
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Revises: 821f71be74c0
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"""
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from alembic import op
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import sqlalchemy as sa
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from sqlalchemy.dialects import postgresql
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revision = "e6d2026091501"
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down_revision = "821f71be74c0"
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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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# ### commands auto generated by Alembic - please adjust! ###
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op.create_table(
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"dataset",
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sa.Column("dataset_id", sa.BigInteger(), autoincrement=True, nullable=False),
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sa.Column("dataset_name", sa.Text(), nullable=False),
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sa.Column("archive_sha256", sa.String(length=64), nullable=False),
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sa.Column("storage_uri", sa.Text(), nullable=False),
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sa.Column("source_timezone", sa.Text(), nullable=True),
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sa.Column(
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"metadata", postgresql.JSONB(none_as_null=True, astext_type=sa.Text()), nullable=False
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),
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sa.CheckConstraint("dataset_id > 0", name="ck_dataset_positive_id"),
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sa.PrimaryKeyConstraint("dataset_id"),
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sa.UniqueConstraint("archive_sha256", name="uq_dataset_archive_sha256"),
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)
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op.create_table(
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"site",
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sa.Column("site_id", sa.Text(), nullable=False),
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sa.Column("site_name", sa.Text(), nullable=False),
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sa.Column("site_type", sa.Text(), nullable=False),
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sa.Column("location", sa.Text(), nullable=True),
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sa.Column("capacity_kw", sa.Double(), nullable=True),
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sa.Column("status", sa.Text(), nullable=True),
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sa.PrimaryKeyConstraint("site_id"),
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)
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op.create_table(
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"prediction",
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sa.Column("prediction_id", sa.BigInteger(), autoincrement=True, nullable=False),
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sa.Column("site_id", sa.Text(), nullable=False),
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sa.Column(
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"created_at",
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sa.DateTime(timezone=True),
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server_default=sa.text("now()"),
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nullable=False,
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),
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sa.Column("target_at", sa.DateTime(timezone=True), nullable=False),
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sa.Column("target_metric", sa.Text(), nullable=False),
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sa.Column("period_minutes", sa.Integer(), nullable=True),
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sa.Column("predicted_value", sa.Double(), nullable=True),
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sa.Column("model_reference", sa.Text(), nullable=False),
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sa.Column("status", sa.Text(), nullable=False),
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sa.Column("failure_reason", sa.Text(), nullable=True),
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sa.CheckConstraint(
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"(status = 'available' AND predicted_value IS NOT NULL AND failure_reason IS NULL) OR (status IN ('insufficient_data', 'error') AND predicted_value IS NULL AND failure_reason IS NOT NULL)",
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name="ck_prediction_status",
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),
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sa.CheckConstraint(
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"target_metric <> 'consumption_kwh' OR period_minutes IS NOT NULL",
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name="ck_prediction_energy_period",
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),
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sa.CheckConstraint(
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"target_metric IN ('consumption_kwh', 'consumption_kw')", name="ck_prediction_metric"
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),
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sa.CheckConstraint(
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"period_minutes IS NULL OR period_minutes > 0", name="ck_prediction_period"
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),
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sa.ForeignKeyConstraint(
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["site_id"], ["site.site_id"], name="fk_prediction_site", ondelete="RESTRICT"
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),
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sa.PrimaryKeyConstraint("prediction_id"),
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sa.UniqueConstraint("prediction_id", "site_id", name="uq_prediction_id_site"),
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)
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op.create_index(
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"ix_prediction_site_target", "prediction", ["site_id", "target_at"], unique=False
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)
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op.create_table(
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"reading",
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sa.Column("reading_id", sa.BigInteger(), autoincrement=True, nullable=False),
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sa.Column("site_id", sa.Text(), nullable=False),
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sa.Column("timestamp", sa.DateTime(timezone=True), nullable=False),
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sa.Column("source", sa.Text(), nullable=False),
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sa.Column("dataset_id", sa.BigInteger(), nullable=True),
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sa.Column("consumption_kw", sa.Double(), nullable=True),
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sa.Column("consumption_kwh", sa.Double(), nullable=True),
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sa.Column("consumption_euros", sa.Numeric(precision=14, scale=2), nullable=True),
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sa.Column("voltage_v", sa.Double(), nullable=True),
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sa.Column("current_a", sa.Double(), nullable=True),
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sa.Column("power_factor", sa.Double(), nullable=True),
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sa.Column("temperature_celsius", sa.Double(), nullable=True),
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sa.Column("humidity_percent", sa.Double(), nullable=True),
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sa.Column("solar_irradiance_wm2", sa.Double(), nullable=True),
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sa.Column("is_working_hours", sa.Boolean(), nullable=True),
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sa.Column("data_quality", sa.Text(), nullable=True),
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sa.Column("null_reasons", postgresql.ARRAY(sa.Text()), nullable=True),
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sa.Column(
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"imputed_values", postgresql.JSONB(none_as_null=True, astext_type=sa.Text()), nullable=True
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),
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sa.Column("imputation_method", sa.Text(), nullable=True),
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sa.Column(
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"ingested_at",
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sa.DateTime(timezone=True),
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server_default=sa.text("now()"),
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nullable=False,
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),
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sa.Column(
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"raw_data", postgresql.JSONB(none_as_null=True, astext_type=sa.Text()), nullable=False
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),
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sa.CheckConstraint(
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"(source = 'csv' AND dataset_id IS NOT NULL) OR (source IN ('api_current', 'api_history') AND dataset_id IS NULL)",
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name="ck_reading_dataset_source",
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),
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sa.CheckConstraint(
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"data_quality IS NULL OR data_quality IN ('good', 'partial', 'degraded', 'critical')",
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name="ck_reading_quality",
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),
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sa.CheckConstraint(
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"source IN ('csv', 'api_current', 'api_history')", name="ck_reading_source"
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),
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sa.CheckConstraint(
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"(imputed_values IS NULL AND imputation_method IS NULL) OR (imputed_values IS NOT NULL AND imputation_method IS NOT NULL)",
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name="ck_reading_imputation",
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),
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sa.ForeignKeyConstraint(
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["dataset_id"], ["dataset.dataset_id"], name="fk_reading_dataset", ondelete="RESTRICT"
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),
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sa.ForeignKeyConstraint(
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["site_id"], ["site.site_id"], name="fk_reading_site", ondelete="RESTRICT"
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),
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sa.PrimaryKeyConstraint("reading_id", "timestamp"),
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)
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op.create_index("ix_reading_dataset_id", "reading", ["dataset_id"], unique=False)
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op.create_index(
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"ix_reading_site_timestamp", "reading", ["site_id", "timestamp"], unique=False
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)
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op.create_index(
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"uq_reading_source",
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"reading",
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["site_id", "timestamp", "source", sa.literal_column("coalesce(dataset_id, 0)")],
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unique=True,
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)
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op.execute(
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"SELECT create_hypertable('reading', by_range('timestamp'), create_default_indexes => FALSE)"
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)
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op.create_table(
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"alert",
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sa.Column("alert_id", sa.BigInteger(), autoincrement=True, nullable=False),
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sa.Column("source_alert_id", sa.Text(), nullable=False),
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sa.Column("site_id", sa.Text(), nullable=False),
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sa.Column("source", sa.Text(), nullable=False),
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sa.Column("timestamp", sa.DateTime(timezone=True), nullable=False),
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sa.Column("type", sa.Text(), nullable=False),
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sa.Column("severity", sa.Text(), nullable=False),
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sa.Column("message", sa.Text(), nullable=False),
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sa.Column("value", sa.Double(), nullable=True),
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sa.Column("threshold", sa.Double(), nullable=True),
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sa.Column("metric", sa.Text(), nullable=True),
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sa.Column("prediction_id", sa.BigInteger(), nullable=True),
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sa.Column(
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"raw_data", postgresql.JSONB(none_as_null=True, astext_type=sa.Text()), nullable=False
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),
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sa.CheckConstraint(
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"severity IN ('low', 'medium', 'high', 'critical')", name="ck_alert_severity"
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),
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sa.CheckConstraint("source IN ('api_mock', 'enervision')", name="ck_alert_source"),
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sa.CheckConstraint(
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"type IN ('spike', 'threshold', 'anomaly', 'outage', 'sensor')", name="ck_alert_type"
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),
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sa.ForeignKeyConstraint(
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["prediction_id", "site_id"],
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["prediction.prediction_id", "prediction.site_id"],
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name="fk_alert_prediction_site",
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ondelete="RESTRICT",
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),
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sa.ForeignKeyConstraint(
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["site_id"], ["site.site_id"], name="fk_alert_site", ondelete="RESTRICT"
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),
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sa.PrimaryKeyConstraint("alert_id"),
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sa.UniqueConstraint(
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"source", "site_id", "source_alert_id", name="uq_alert_source_reference"
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),
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)
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op.create_index("ix_alert_site_timestamp", "alert", ["site_id", "timestamp"], unique=False)
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op.create_table(
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"recommendation",
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sa.Column("recommendation_id", sa.BigInteger(), autoincrement=True, nullable=False),
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sa.Column("alert_id", sa.BigInteger(), nullable=False),
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sa.Column("action", sa.Text(), nullable=False),
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sa.Column("explanation", sa.Text(), nullable=False),
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sa.Column("rule_reference", sa.Text(), nullable=False),
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sa.Column(
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"created_at",
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sa.DateTime(timezone=True),
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server_default=sa.text("now()"),
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nullable=False,
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),
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sa.ForeignKeyConstraint(
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["alert_id"], ["alert.alert_id"], name="fk_recommendation_alert", ondelete="RESTRICT"
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),
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sa.PrimaryKeyConstraint("recommendation_id"),
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sa.UniqueConstraint("alert_id", "rule_reference", name="uq_recommendation_alert_rule"),
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)
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# ### end Alembic commands ###
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def downgrade() -> None:
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op.drop_table("recommendation")
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op.drop_table("alert")
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op.drop_table("reading")
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op.drop_table("prediction")
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op.drop_table("site")
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op.drop_table("dataset")
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