feat(apps): cree les six tables data et l'hypertable readings
This commit is contained in:
Meryemel-gham
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"""Création des six tables Data et de l'hypertable readings.
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Revision ID: e6d2026091501
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Revises: 5353c0e4f094
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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 = "5353c0e4f094"
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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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"datasets",
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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_datasets_positive_id"),
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sa.PrimaryKeyConstraint("dataset_id"),
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sa.UniqueConstraint("archive_sha256", name="uq_datasets_archive_sha256"),
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)
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op.create_table(
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"sites",
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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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"predictions",
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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_predictions_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_predictions_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_predictions_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_predictions_period"
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),
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sa.ForeignKeyConstraint(
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["site_id"], ["sites.site_id"], name="fk_predictions_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_predictions_id_site"),
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)
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op.create_index(
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"ix_predictions_site_target", "predictions", ["site_id", "target_at"], unique=False
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)
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op.create_table(
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"readings",
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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_readings_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_readings_quality",
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),
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sa.CheckConstraint(
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"source IN ('csv', 'api_current', 'api_history')", name="ck_readings_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_readings_imputation",
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),
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sa.ForeignKeyConstraint(
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["dataset_id"], ["datasets.dataset_id"], name="fk_readings_dataset", ondelete="RESTRICT"
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),
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sa.ForeignKeyConstraint(
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["site_id"], ["sites.site_id"], name="fk_readings_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_readings_dataset_id", "readings", ["dataset_id"], unique=False)
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op.create_index(
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"ix_readings_site_timestamp", "readings", ["site_id", "timestamp"], unique=False
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)
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op.create_index(
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"uq_readings_source",
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"readings",
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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('readings', by_range('timestamp'), create_default_indexes => FALSE)"
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)
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op.create_table(
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"alerts",
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sa.Column("id", sa.BigInteger(), autoincrement=True, nullable=False),
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sa.Column("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_alerts_severity"
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),
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sa.CheckConstraint("source IN ('api_mock', 'enervision')", name="ck_alerts_source"),
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sa.CheckConstraint(
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"type IN ('spike', 'threshold', 'anomaly', 'outage', 'sensor')", name="ck_alerts_type"
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),
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sa.ForeignKeyConstraint(
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["prediction_id", "site_id"],
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["predictions.prediction_id", "predictions.site_id"],
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name="fk_alerts_prediction_site",
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ondelete="RESTRICT",
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),
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sa.ForeignKeyConstraint(
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["site_id"], ["sites.site_id"], name="fk_alerts_site", ondelete="RESTRICT"
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),
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sa.PrimaryKeyConstraint("id"),
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sa.UniqueConstraint("source", "site_id", "alert_id", name="uq_alerts_source_site_id"),
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)
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op.create_index("ix_alerts_site_timestamp", "alerts", ["site_id", "timestamp"], unique=False)
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op.create_table(
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"recommendations",
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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"], ["alerts.id"], name="fk_recommendations_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_recommendations_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("recommendations")
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op.drop_table("alerts")
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op.drop_table("readings")
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op.drop_table("predictions")
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op.drop_table("sites")
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op.drop_table("datasets")
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@@ -1,2 +1,6 @@
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# Piege : tout modele absent de ce module reste invisible de `alembic revision
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# --autogenerate`, qui genererait alors un drop de sa table.
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from app.models.energy import Alert, Dataset, Prediction, Reading, Recommendation, Site
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__all__ = ["Alert", "Dataset", "Prediction", "Reading", "Recommendation", "Site"]
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@@ -0,0 +1,209 @@
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"""Tables du modèle de données EnerVision (CSV, API Mock et résultats ML)."""
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from datetime import datetime
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from decimal import Decimal
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from typing import Any
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from sqlalchemy import (
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BigInteger,
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Boolean,
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CheckConstraint,
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DateTime,
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Double,
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ForeignKey,
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ForeignKeyConstraint,
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Index,
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Integer,
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Numeric,
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String,
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Text,
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UniqueConstraint,
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func,
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text,
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)
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from sqlalchemy.dialects.postgresql import ARRAY, JSONB
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from sqlalchemy.orm import Mapped, mapped_column
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from app.db.base import Base
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class Dataset(Base):
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__tablename__ = "datasets"
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__table_args__ = (
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CheckConstraint("dataset_id > 0", name="ck_datasets_positive_id"),
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UniqueConstraint("archive_sha256", name="uq_datasets_archive_sha256"),
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)
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dataset_id: Mapped[int] = mapped_column(BigInteger, primary_key=True, autoincrement=True)
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dataset_name: Mapped[str] = mapped_column(Text)
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archive_sha256: Mapped[str] = mapped_column(String(64))
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storage_uri: Mapped[str] = mapped_column(Text)
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source_timezone: Mapped[str | None] = mapped_column(Text)
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# "metadata" est réservé par SQLAlchemy ; le nom SQL reste inchangé.
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dataset_metadata: Mapped[dict[str, Any]] = mapped_column("metadata", JSONB(none_as_null=True))
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class Site(Base):
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__tablename__ = "sites"
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site_id: Mapped[str] = mapped_column(Text, primary_key=True)
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site_name: Mapped[str] = mapped_column(Text)
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site_type: Mapped[str] = mapped_column(Text)
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location: Mapped[str | None] = mapped_column(Text)
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capacity_kw: Mapped[float | None] = mapped_column(Double)
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status: Mapped[str | None] = mapped_column(Text)
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class Reading(Base):
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__tablename__ = "readings"
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__table_args__ = (
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CheckConstraint(
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"source IN ('csv', 'api_current', 'api_history')", name="ck_readings_source"
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),
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CheckConstraint(
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"(source = 'csv' AND dataset_id IS NOT NULL) OR "
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"(source IN ('api_current', 'api_history') AND dataset_id IS NULL)",
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name="ck_readings_dataset_source",
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),
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CheckConstraint(
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"data_quality IS NULL OR data_quality IN ('good', 'partial', 'degraded', 'critical')",
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name="ck_readings_quality",
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),
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CheckConstraint(
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"(imputed_values IS NULL AND imputation_method IS NULL) OR "
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"(imputed_values IS NOT NULL AND imputation_method IS NOT NULL)",
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name="ck_readings_imputation",
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),
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Index("ix_readings_site_timestamp", "site_id", "timestamp"),
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Index("ix_readings_dataset_id", "dataset_id"),
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)
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reading_id: Mapped[int] = mapped_column(BigInteger, primary_key=True, autoincrement=True)
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site_id: Mapped[str] = mapped_column(
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Text, ForeignKey("sites.site_id", name="fk_readings_site", ondelete="RESTRICT")
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)
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timestamp: Mapped[datetime] = mapped_column(DateTime(timezone=True), primary_key=True)
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source: Mapped[str] = mapped_column(Text)
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dataset_id: Mapped[int | None] = mapped_column(
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BigInteger,
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ForeignKey("datasets.dataset_id", name="fk_readings_dataset", ondelete="RESTRICT"),
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)
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consumption_kw: Mapped[float | None] = mapped_column(Double)
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consumption_kwh: Mapped[float | None] = mapped_column(Double)
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consumption_euros: Mapped[Decimal | None] = mapped_column(Numeric(14, 2))
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voltage_v: Mapped[float | None] = mapped_column(Double)
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current_a: Mapped[float | None] = mapped_column(Double)
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power_factor: Mapped[float | None] = mapped_column(Double)
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temperature_celsius: Mapped[float | None] = mapped_column(Double)
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humidity_percent: Mapped[float | None] = mapped_column(Double)
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solar_irradiance_wm2: Mapped[float | None] = mapped_column(Double)
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is_working_hours: Mapped[bool | None] = mapped_column(Boolean)
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data_quality: Mapped[str | None] = mapped_column(Text)
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null_reasons: Mapped[list[str] | None] = mapped_column(ARRAY(Text))
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imputed_values: Mapped[dict[str, Any] | None] = mapped_column(JSONB(none_as_null=True))
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imputation_method: Mapped[str | None] = mapped_column(Text)
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ingested_at: Mapped[datetime] = mapped_column(
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DateTime(timezone=True), server_default=func.now()
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)
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raw_data: Mapped[dict[str, Any]] = mapped_column(JSONB(none_as_null=True))
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Index(
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"uq_readings_source",
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Reading.site_id,
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Reading.timestamp,
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Reading.source,
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func.coalesce(Reading.dataset_id, text("0")),
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unique=True,
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)
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class Prediction(Base):
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__tablename__ = "predictions"
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__table_args__ = (
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UniqueConstraint("prediction_id", "site_id", name="uq_predictions_id_site"),
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Index("ix_predictions_site_target", "site_id", "target_at"),
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CheckConstraint(
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"target_metric IN ('consumption_kwh', 'consumption_kw')",
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name="ck_predictions_metric",
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),
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CheckConstraint(
|
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"period_minutes IS NULL OR period_minutes > 0", name="ck_predictions_period"
|
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),
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CheckConstraint(
|
||||
"target_metric <> 'consumption_kwh' OR period_minutes IS NOT NULL",
|
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name="ck_predictions_energy_period",
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),
|
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CheckConstraint(
|
||||
"(status = 'available' AND predicted_value IS NOT NULL AND failure_reason IS NULL) OR "
|
||||
"(status IN ('insufficient_data', 'error') AND predicted_value IS NULL "
|
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"AND failure_reason IS NOT NULL)",
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name="ck_predictions_status",
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),
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)
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prediction_id: Mapped[int] = mapped_column(BigInteger, primary_key=True, autoincrement=True)
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site_id: Mapped[str] = mapped_column(
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Text, ForeignKey("sites.site_id", name="fk_predictions_site", ondelete="RESTRICT")
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)
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created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), server_default=func.now())
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target_at: Mapped[datetime] = mapped_column(DateTime(timezone=True))
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target_metric: Mapped[str] = mapped_column(Text)
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period_minutes: Mapped[int | None] = mapped_column(Integer)
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predicted_value: Mapped[float | None] = mapped_column(Double)
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model_reference: Mapped[str] = mapped_column(Text)
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status: Mapped[str] = mapped_column(Text)
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failure_reason: Mapped[str | None] = mapped_column(Text)
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class Alert(Base):
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__tablename__ = "alerts"
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__table_args__ = (
|
||||
UniqueConstraint("source", "site_id", "alert_id", name="uq_alerts_source_site_id"),
|
||||
Index("ix_alerts_site_timestamp", "site_id", "timestamp"),
|
||||
ForeignKeyConstraint(
|
||||
["prediction_id", "site_id"],
|
||||
["predictions.prediction_id", "predictions.site_id"],
|
||||
name="fk_alerts_prediction_site",
|
||||
ondelete="RESTRICT",
|
||||
),
|
||||
CheckConstraint("source IN ('api_mock', 'enervision')", name="ck_alerts_source"),
|
||||
CheckConstraint(
|
||||
"type IN ('spike', 'threshold', 'anomaly', 'outage', 'sensor')", name="ck_alerts_type"
|
||||
),
|
||||
CheckConstraint(
|
||||
"severity IN ('low', 'medium', 'high', 'critical')", name="ck_alerts_severity"
|
||||
),
|
||||
)
|
||||
|
||||
id: Mapped[int] = mapped_column(BigInteger, primary_key=True, autoincrement=True)
|
||||
alert_id: Mapped[str] = mapped_column(Text)
|
||||
site_id: Mapped[str] = mapped_column(
|
||||
Text, ForeignKey("sites.site_id", name="fk_alerts_site", ondelete="RESTRICT")
|
||||
)
|
||||
source: Mapped[str] = mapped_column(Text)
|
||||
timestamp: Mapped[datetime] = mapped_column(DateTime(timezone=True))
|
||||
type: Mapped[str] = mapped_column(Text)
|
||||
severity: Mapped[str] = mapped_column(Text)
|
||||
message: Mapped[str] = mapped_column(Text)
|
||||
value: Mapped[float | None] = mapped_column(Double)
|
||||
threshold: Mapped[float | None] = mapped_column(Double)
|
||||
metric: Mapped[str | None] = mapped_column(Text)
|
||||
prediction_id: Mapped[int | None] = mapped_column(BigInteger)
|
||||
raw_data: Mapped[dict[str, Any]] = mapped_column(JSONB(none_as_null=True))
|
||||
|
||||
|
||||
class Recommendation(Base):
|
||||
__tablename__ = "recommendations"
|
||||
__table_args__ = (
|
||||
UniqueConstraint("alert_id", "rule_reference", name="uq_recommendations_alert_rule"),
|
||||
)
|
||||
|
||||
recommendation_id: Mapped[int] = mapped_column(BigInteger, primary_key=True, autoincrement=True)
|
||||
alert_id: Mapped[int] = mapped_column(
|
||||
BigInteger, ForeignKey("alerts.id", name="fk_recommendations_alert", ondelete="RESTRICT")
|
||||
)
|
||||
action: Mapped[str] = mapped_column(Text)
|
||||
explanation: Mapped[str] = mapped_column(Text)
|
||||
rule_reference: Mapped[str] = mapped_column(Text)
|
||||
created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), server_default=func.now())
|
||||
Reference in New Issue
Block a user