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ENI-projet-piscine/apps/backend/alembic/versions/e6d2026091501_create_data_schema.py
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217 lines
9.5 KiB
Python

"""Création des six tables Data et de l'hypertable readings.
Revision ID: e6d2026091501
Revises: 5353c0e4f094
"""
from alembic import op
import sqlalchemy as sa
from sqlalchemy.dialects import postgresql
revision = "e6d2026091501"
down_revision = "5353c0e4f094"
branch_labels = None
depends_on = None
def upgrade() -> None:
# ### commands auto generated by Alembic - please adjust! ###
op.create_table(
"datasets",
sa.Column("dataset_id", sa.BigInteger(), autoincrement=True, nullable=False),
sa.Column("dataset_name", sa.Text(), nullable=False),
sa.Column("archive_sha256", sa.String(length=64), nullable=False),
sa.Column("storage_uri", sa.Text(), nullable=False),
sa.Column("source_timezone", sa.Text(), nullable=True),
sa.Column(
"metadata", postgresql.JSONB(none_as_null=True, astext_type=sa.Text()), nullable=False
),
sa.CheckConstraint("dataset_id > 0", name="ck_datasets_positive_id"),
sa.PrimaryKeyConstraint("dataset_id"),
sa.UniqueConstraint("archive_sha256", name="uq_datasets_archive_sha256"),
)
op.create_table(
"sites",
sa.Column("site_id", sa.Text(), nullable=False),
sa.Column("site_name", sa.Text(), nullable=False),
sa.Column("site_type", sa.Text(), nullable=False),
sa.Column("location", sa.Text(), nullable=True),
sa.Column("capacity_kw", sa.Double(), nullable=True),
sa.Column("status", sa.Text(), nullable=True),
sa.PrimaryKeyConstraint("site_id"),
)
op.create_table(
"predictions",
sa.Column("prediction_id", sa.BigInteger(), autoincrement=True, nullable=False),
sa.Column("site_id", sa.Text(), nullable=False),
sa.Column(
"created_at",
sa.DateTime(timezone=True),
server_default=sa.text("now()"),
nullable=False,
),
sa.Column("target_at", sa.DateTime(timezone=True), nullable=False),
sa.Column("target_metric", sa.Text(), nullable=False),
sa.Column("period_minutes", sa.Integer(), nullable=True),
sa.Column("predicted_value", sa.Double(), nullable=True),
sa.Column("model_reference", sa.Text(), nullable=False),
sa.Column("status", sa.Text(), nullable=False),
sa.Column("failure_reason", sa.Text(), nullable=True),
sa.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 AND failure_reason IS NOT NULL)",
name="ck_predictions_status",
),
sa.CheckConstraint(
"target_metric <> 'consumption_kwh' OR period_minutes IS NOT NULL",
name="ck_predictions_energy_period",
),
sa.CheckConstraint(
"target_metric IN ('consumption_kwh', 'consumption_kw')", name="ck_predictions_metric"
),
sa.CheckConstraint(
"period_minutes IS NULL OR period_minutes > 0", name="ck_predictions_period"
),
sa.ForeignKeyConstraint(
["site_id"], ["sites.site_id"], name="fk_predictions_site", ondelete="RESTRICT"
),
sa.PrimaryKeyConstraint("prediction_id"),
sa.UniqueConstraint("prediction_id", "site_id", name="uq_predictions_id_site"),
)
op.create_index(
"ix_predictions_site_target", "predictions", ["site_id", "target_at"], unique=False
)
op.create_table(
"readings",
sa.Column("reading_id", sa.BigInteger(), autoincrement=True, nullable=False),
sa.Column("site_id", sa.Text(), nullable=False),
sa.Column("timestamp", sa.DateTime(timezone=True), nullable=False),
sa.Column("source", sa.Text(), nullable=False),
sa.Column("dataset_id", sa.BigInteger(), nullable=True),
sa.Column("consumption_kw", sa.Double(), nullable=True),
sa.Column("consumption_kwh", sa.Double(), nullable=True),
sa.Column("consumption_euros", sa.Numeric(precision=14, scale=2), nullable=True),
sa.Column("voltage_v", sa.Double(), nullable=True),
sa.Column("current_a", sa.Double(), nullable=True),
sa.Column("power_factor", sa.Double(), nullable=True),
sa.Column("temperature_celsius", sa.Double(), nullable=True),
sa.Column("humidity_percent", sa.Double(), nullable=True),
sa.Column("solar_irradiance_wm2", sa.Double(), nullable=True),
sa.Column("is_working_hours", sa.Boolean(), nullable=True),
sa.Column("data_quality", sa.Text(), nullable=True),
sa.Column("null_reasons", postgresql.ARRAY(sa.Text()), nullable=True),
sa.Column(
"imputed_values", postgresql.JSONB(none_as_null=True, astext_type=sa.Text()), nullable=True
),
sa.Column("imputation_method", sa.Text(), nullable=True),
sa.Column(
"ingested_at",
sa.DateTime(timezone=True),
server_default=sa.text("now()"),
nullable=False,
),
sa.Column(
"raw_data", postgresql.JSONB(none_as_null=True, astext_type=sa.Text()), nullable=False
),
sa.CheckConstraint(
"(source = 'csv' AND dataset_id IS NOT NULL) OR (source IN ('api_current', 'api_history') AND dataset_id IS NULL)",
name="ck_readings_dataset_source",
),
sa.CheckConstraint(
"data_quality IS NULL OR data_quality IN ('good', 'partial', 'degraded', 'critical')",
name="ck_readings_quality",
),
sa.CheckConstraint(
"source IN ('csv', 'api_current', 'api_history')", name="ck_readings_source"
),
sa.CheckConstraint(
"(imputed_values IS NULL AND imputation_method IS NULL) OR (imputed_values IS NOT NULL AND imputation_method IS NOT NULL)",
name="ck_readings_imputation",
),
sa.ForeignKeyConstraint(
["dataset_id"], ["datasets.dataset_id"], name="fk_readings_dataset", ondelete="RESTRICT"
),
sa.ForeignKeyConstraint(
["site_id"], ["sites.site_id"], name="fk_readings_site", ondelete="RESTRICT"
),
sa.PrimaryKeyConstraint("reading_id", "timestamp"),
)
op.create_index("ix_readings_dataset_id", "readings", ["dataset_id"], unique=False)
op.create_index(
"ix_readings_site_timestamp", "readings", ["site_id", "timestamp"], unique=False
)
op.create_index(
"uq_readings_source",
"readings",
["site_id", "timestamp", "source", sa.literal_column("coalesce(dataset_id, 0)")],
unique=True,
)
op.execute(
"SELECT create_hypertable('readings', by_range('timestamp'), create_default_indexes => FALSE)"
)
op.create_table(
"alerts",
sa.Column("id", sa.BigInteger(), autoincrement=True, nullable=False),
sa.Column("alert_id", sa.Text(), nullable=False),
sa.Column("site_id", sa.Text(), nullable=False),
sa.Column("source", sa.Text(), nullable=False),
sa.Column("timestamp", sa.DateTime(timezone=True), nullable=False),
sa.Column("type", sa.Text(), nullable=False),
sa.Column("severity", sa.Text(), nullable=False),
sa.Column("message", sa.Text(), nullable=False),
sa.Column("value", sa.Double(), nullable=True),
sa.Column("threshold", sa.Double(), nullable=True),
sa.Column("metric", sa.Text(), nullable=True),
sa.Column("prediction_id", sa.BigInteger(), nullable=True),
sa.Column(
"raw_data", postgresql.JSONB(none_as_null=True, astext_type=sa.Text()), nullable=False
),
sa.CheckConstraint(
"severity IN ('low', 'medium', 'high', 'critical')", name="ck_alerts_severity"
),
sa.CheckConstraint("source IN ('api_mock', 'enervision')", name="ck_alerts_source"),
sa.CheckConstraint(
"type IN ('spike', 'threshold', 'anomaly', 'outage', 'sensor')", name="ck_alerts_type"
),
sa.ForeignKeyConstraint(
["prediction_id", "site_id"],
["predictions.prediction_id", "predictions.site_id"],
name="fk_alerts_prediction_site",
ondelete="RESTRICT",
),
sa.ForeignKeyConstraint(
["site_id"], ["sites.site_id"], name="fk_alerts_site", ondelete="RESTRICT"
),
sa.PrimaryKeyConstraint("id"),
sa.UniqueConstraint("source", "site_id", "alert_id", name="uq_alerts_source_site_id"),
)
op.create_index("ix_alerts_site_timestamp", "alerts", ["site_id", "timestamp"], unique=False)
op.create_table(
"recommendations",
sa.Column("recommendation_id", sa.BigInteger(), autoincrement=True, nullable=False),
sa.Column("alert_id", sa.BigInteger(), nullable=False),
sa.Column("action", sa.Text(), nullable=False),
sa.Column("explanation", sa.Text(), nullable=False),
sa.Column("rule_reference", sa.Text(), nullable=False),
sa.Column(
"created_at",
sa.DateTime(timezone=True),
server_default=sa.text("now()"),
nullable=False,
),
sa.ForeignKeyConstraint(
["alert_id"], ["alerts.id"], name="fk_recommendations_alert", ondelete="RESTRICT"
),
sa.PrimaryKeyConstraint("recommendation_id"),
sa.UniqueConstraint("alert_id", "rule_reference", name="uq_recommendations_alert_rule"),
)
# ### end Alembic commands ###
def downgrade() -> None:
op.drop_table("recommendations")
op.drop_table("alerts")
op.drop_table("readings")
op.drop_table("predictions")
op.drop_table("sites")
op.drop_table("datasets")