feat: add scenario analysis workspace
This commit is contained in:
18
apps/api/migrations/202606240006_scenario_runs.sql
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18
apps/api/migrations/202606240006_scenario_runs.sql
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@@ -0,0 +1,18 @@
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CREATE TABLE IF NOT EXISTS app.scenario_runs (
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scenario_run_id BIGSERIAL PRIMARY KEY,
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name TEXT NOT NULL,
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target_month TEXT NOT NULL CHECK (target_month ~ '^[0-9]{4}-[0-9]{2}$'),
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area_id TEXT REFERENCES silver.areas(area_id),
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interest_rate_delta_bps DOUBLE PRECISION NOT NULL DEFAULT 0,
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policy_signal_delta INTEGER NOT NULL DEFAULT 0 CHECK (policy_signal_delta BETWEEN -4 AND 4),
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supply_delta_pct DOUBLE PRECISION NOT NULL DEFAULT 0 CHECK (supply_delta_pct BETWEEN -100 AND 500),
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rent_delta_pct DOUBLE PRECISION NOT NULL DEFAULT 0 CHECK (rent_delta_pct BETWEEN -80 AND 200),
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notes TEXT NOT NULL DEFAULT '',
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created_at TIMESTAMPTZ NOT NULL DEFAULT now()
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);
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CREATE INDEX IF NOT EXISTS idx_scenario_runs_month
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ON app.scenario_runs(target_month, scenario_run_id DESC);
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CREATE INDEX IF NOT EXISTS idx_scenario_runs_area
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ON app.scenario_runs(area_id, scenario_run_id DESC);
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@@ -9,14 +9,16 @@ use crate::models::{
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AreaProfile, AreaScore, AreaScoreLineage, AreaScoreLineageQuery, AreaScoreModelRunResponse,
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AreaScoreRunDiff, AreaScoreRunDiffItem, AreaScoreSummary, CompareQuery, ComparisonMetric,
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ComparisonMetricValue, CreateAreaScoreModelRun, CreateDataSource, CreateIngestionRun,
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CreateRawArtifact, CreateWatchlistEvent, CreateWatchlistItem, DataSource, DiagnosticMetric,
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FinishIngestionRun, ImportExecutionRequest, ImportExecutionResponse, ImportValidationRequest,
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ImportValidationResponse, IngestionRun, IngestionRunQuery, MarketOverview, ModelRun,
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ModelRunDiffQuery, ModelRunQuery, MonthQuery, Neighborhood, NeighborhoodComparison,
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NeighborhoodComparisonItem, NeighborhoodDetail, NeighborhoodMonthlyMetric, NeighborhoodQuery,
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NeighborhoodScore, NeighborhoodScoreQuery, RawArtifact, RawArtifactQuery, SimilarNeighborhood,
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SimilarNeighborhoodCandidate, SimilarNeighborhoodQuery, SimilarNeighborhoodResponse,
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UpdateWatchlistItem, WatchlistEvent, WatchlistItem, WatchlistQuery,
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CreateRawArtifact, CreateScenarioRun, CreateWatchlistEvent, CreateWatchlistItem, DataSource,
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DiagnosticMetric, FinishIngestionRun, ImportExecutionRequest, ImportExecutionResponse,
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ImportValidationRequest, ImportValidationResponse, IngestionRun, IngestionRunQuery,
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MarketOverview, ModelRun, ModelRunDiffQuery, ModelRunQuery, MonthQuery, Neighborhood,
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NeighborhoodComparison, NeighborhoodComparisonItem, NeighborhoodDetail,
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NeighborhoodMonthlyMetric, NeighborhoodQuery, NeighborhoodScore, NeighborhoodScoreQuery,
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RawArtifact, RawArtifactQuery, ScenarioAreaResult, ScenarioRun, ScenarioRunQuery,
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ScenarioRunResponse, ScenarioVariant, SimilarNeighborhood, SimilarNeighborhoodCandidate,
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SimilarNeighborhoodQuery, SimilarNeighborhoodResponse, UpdateWatchlistItem, WatchlistEvent,
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WatchlistItem, WatchlistQuery,
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};
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use crate::scoring::{compute_area_scores, previous_month, AreaMetricRow, ComputedAreaScore};
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use crate::state::AppState;
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@@ -1749,6 +1751,103 @@ pub async fn create_watchlist_event(
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Ok(Json(event))
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}
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pub async fn list_scenario_runs(
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State(state): State<AppState>,
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Query(query): Query<ScenarioRunQuery>,
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) -> ApiResult<Json<Vec<ScenarioRun>>> {
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if let Some(month) = query.target_month.as_deref() {
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validate_month(month)?;
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}
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if let Some(area_id) = query.area_id.as_deref() {
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validate_identifier(area_id)?;
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}
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let runs = sqlx::query_as::<_, ScenarioRun>(
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r#"
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SELECT
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scenario_run_id,
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name,
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target_month,
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area_id,
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interest_rate_delta_bps,
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policy_signal_delta,
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supply_delta_pct,
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rent_delta_pct,
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notes,
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created_at::text AS created_at
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FROM app.scenario_runs
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WHERE ($1::text IS NULL OR target_month = $1)
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AND ($2::text IS NULL OR area_id = $2)
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ORDER BY scenario_run_id DESC
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LIMIT 50
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"#,
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)
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.bind(query.target_month)
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.bind(query.area_id)
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.fetch_all(&state.pool)
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.await?;
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Ok(Json(runs))
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}
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pub async fn create_scenario_run(
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State(state): State<AppState>,
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Json(payload): Json<CreateScenarioRun>,
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) -> ApiResult<Json<ScenarioRunResponse>> {
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validate_month(&payload.target_month)?;
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payload
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.validate()
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.map_err(|message| ApiError::BadRequest(message.to_string()))?;
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if let Some(area_id) = payload.area_id.as_deref() {
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validate_identifier(area_id)?;
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}
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let mut tx = state.pool.begin().await?;
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let run = sqlx::query_as::<_, ScenarioRun>(
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r#"
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INSERT INTO app.scenario_runs (
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name,
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target_month,
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area_id,
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interest_rate_delta_bps,
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policy_signal_delta,
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supply_delta_pct,
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rent_delta_pct,
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notes
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)
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VALUES ($1, $2, $3, $4, $5, $6, $7, COALESCE($8, ''))
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RETURNING
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scenario_run_id,
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name,
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target_month,
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area_id,
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interest_rate_delta_bps,
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policy_signal_delta,
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supply_delta_pct,
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rent_delta_pct,
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notes,
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created_at::text AS created_at
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"#,
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)
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.bind(payload.name.trim().to_string())
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.bind(payload.target_month.trim().to_string())
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.bind(payload.area_id.clone())
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.bind(payload.interest_rate_delta_bps)
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.bind(payload.policy_signal_delta)
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.bind(payload.supply_delta_pct)
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.bind(payload.rent_delta_pct)
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.bind(payload.notes.clone())
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.fetch_one(&mut *tx)
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.await?;
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let variants = build_scenario_variants(&mut tx, &run)
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.await
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.map_err(ApiError::BadRequest)?;
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tx.commit().await?;
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Ok(Json(ScenarioRunResponse { run, variants }))
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}
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async fn insert_watchlist_event(
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tx: &mut sqlx::Transaction<'_, sqlx::Postgres>,
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watchlist_item_id: i64,
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@@ -1812,6 +1911,252 @@ async fn fetch_area_scores(state: &AppState, month: &str) -> Result<Vec<AreaScor
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.await
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}
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async fn build_scenario_variants(
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tx: &mut sqlx::Transaction<'_, sqlx::Postgres>,
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run: &ScenarioRun,
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) -> Result<Vec<ScenarioVariant>, String> {
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let current_rows = fetch_area_metric_rows(tx, &run.target_month)
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.await
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.map_err(|error| format!("failed to fetch current area metrics: {error}"))?;
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if current_rows.is_empty() {
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return Err(format!(
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"no area metrics found for month {}",
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run.target_month
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));
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}
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let target_rows = current_rows
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.iter()
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.filter(|row| {
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run.area_id
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.as_deref()
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.map(|area_id| row.area_id == area_id)
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.unwrap_or(true)
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})
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.cloned()
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.collect::<Vec<_>>();
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if target_rows.is_empty() {
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return Err("no area metrics found for scenario area".to_string());
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}
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let prior_month =
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previous_month(&run.target_month).ok_or_else(|| "invalid month".to_string())?;
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let prior_rows = fetch_area_metric_rows(tx, &prior_month)
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.await
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.map_err(|error| format!("failed to fetch prior area metrics: {error}"))?;
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let price_history = fetch_area_price_history(tx, &run.target_month)
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.await
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.map_err(|error| format!("failed to fetch area price history: {error}"))?;
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let baseline_scores = compute_area_scores(¤t_rows, &prior_rows, &price_history);
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Ok(vec![
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build_scenario_variant(
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"downside",
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"谨慎",
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1.35,
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&target_rows,
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&prior_rows,
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&price_history,
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&baseline_scores,
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run,
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),
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build_scenario_variant(
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"base",
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"基准",
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1.0,
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&target_rows,
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&prior_rows,
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&price_history,
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&baseline_scores,
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run,
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),
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build_scenario_variant(
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"upside",
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"乐观",
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0.65,
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&target_rows,
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&prior_rows,
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&price_history,
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&baseline_scores,
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run,
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),
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])
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}
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fn build_scenario_variant(
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key: &str,
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name: &str,
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multiplier: f64,
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rows: &[AreaMetricRow],
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prior_rows: &[AreaMetricRow],
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price_history: &std::collections::HashMap<String, Vec<f64>>,
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baseline_scores: &[ComputedAreaScore],
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run: &ScenarioRun,
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) -> ScenarioVariant {
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let adjusted_rows = rows
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.iter()
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.map(|row| adjusted_area_metric_row(row, run, multiplier))
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.collect::<Vec<_>>();
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let projected_scores = compute_area_scores(&adjusted_rows, prior_rows, price_history);
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let baseline_by_area = baseline_scores
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.iter()
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.map(|score| (score.area_id.as_str(), score))
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.collect::<std::collections::HashMap<_, _>>();
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let adjusted_by_area = adjusted_rows
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.iter()
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.map(|row| (row.area_id.as_str(), row))
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.collect::<std::collections::HashMap<_, _>>();
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let items = projected_scores
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.into_iter()
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.filter_map(|projected| {
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let baseline = baseline_by_area.get(projected.area_id.as_str())?;
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let adjusted = adjusted_by_area.get(projected.area_id.as_str())?;
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Some(scenario_area_result(
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baseline, &projected, adjusted, run, multiplier,
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))
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})
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.collect::<Vec<_>>();
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ScenarioVariant {
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key: key.to_string(),
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name: name.to_string(),
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assumptions: scenario_assumptions(run, multiplier),
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items,
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}
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}
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fn adjusted_area_metric_row(
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row: &AreaMetricRow,
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run: &ScenarioRun,
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multiplier: f64,
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) -> AreaMetricRow {
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let price_delta_pct = scenario_price_delta_pct(run, multiplier);
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let transaction_delta_pct = scenario_transaction_delta_pct(run, multiplier);
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let listing_delta_pct = (run.supply_delta_pct * multiplier
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+ run.interest_rate_delta_bps.max(0.0) * 0.08
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- (run.policy_signal_delta.max(0) as f64) * 3.0)
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.clamp(-60.0, 180.0);
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AreaMetricRow {
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transaction_count: adjusted_i32(row.transaction_count, transaction_delta_pct, 1),
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transaction_price_psm: adjusted_f64(row.transaction_price_psm, price_delta_pct, 1.0),
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listing_count: adjusted_i32(row.listing_count, listing_delta_pct, 0),
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listing_price_psm: adjusted_f64(row.listing_price_psm, price_delta_pct * 0.85, 1.0),
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median_days_on_market: adjusted_f64(
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row.median_days_on_market,
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-transaction_delta_pct * 0.45 + listing_delta_pct * 0.25,
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1.0,
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),
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rent_price_psm: adjusted_f64(row.rent_price_psm, run.rent_delta_pct * multiplier, 0.1),
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new_supply_units: adjusted_i32(row.new_supply_units, run.supply_delta_pct * multiplier, 0),
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mortgage_rate_pct: (row.mortgage_rate_pct
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+ run.interest_rate_delta_bps * multiplier / 100.0)
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.max(0.0),
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policy_signal: (row.policy_signal
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+ ((run.policy_signal_delta as f64) * multiplier).round() as i32)
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.clamp(-2, 2),
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..row.clone()
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}
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}
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fn scenario_area_result(
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baseline: &ComputedAreaScore,
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projected: &ComputedAreaScore,
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adjusted: &AreaMetricRow,
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run: &ScenarioRun,
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multiplier: f64,
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) -> ScenarioAreaResult {
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ScenarioAreaResult {
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area_id: projected.area_id.clone(),
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name: projected.name.clone(),
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district: projected.district.clone(),
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baseline_score: baseline.investment_score,
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projected_score: projected.investment_score,
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score_delta: round_to(projected.investment_score - baseline.investment_score, 1),
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baseline_price_psm: baseline.transaction_price_psm,
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projected_price_psm: projected.transaction_price_psm,
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price_delta_pct: round_to(
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safe_percentage(
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projected.transaction_price_psm - baseline.transaction_price_psm,
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baseline.transaction_price_psm,
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),
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1,
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),
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projected_rent_yield_pct: projected.annual_rent_yield_pct,
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projected_liquidity_score: projected.liquidity_score,
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projected_supply_risk_score: projected.supply_risk_score,
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recommendation: projected.recommendation.clone(),
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risk_notes: scenario_risk_notes(projected, adjusted, run, multiplier),
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}
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}
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fn scenario_assumptions(run: &ScenarioRun, multiplier: f64) -> Vec<String> {
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vec![
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format!("利率变动 {:.0}bp", run.interest_rate_delta_bps * multiplier),
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format!(
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"政策信号 {}",
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((run.policy_signal_delta as f64) * multiplier).round() as i32
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),
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format!("新增供应 {:.1}%", run.supply_delta_pct * multiplier),
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format!("租金变化 {:.1}%", run.rent_delta_pct * multiplier),
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format!("价格冲击 {:.1}%", scenario_price_delta_pct(run, multiplier)),
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]
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}
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fn scenario_risk_notes(
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projected: &ComputedAreaScore,
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adjusted: &AreaMetricRow,
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run: &ScenarioRun,
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multiplier: f64,
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) -> Vec<String> {
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let mut notes = Vec::new();
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if projected.supply_risk_score >= 70.0 {
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notes.push("供应压力偏高，需跟踪新增挂牌与去化速度".to_string());
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}
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if projected.liquidity_score < 45.0 {
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notes.push("流动性承压，议价周期可能拉长".to_string());
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}
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if projected.annual_rent_yield_pct < 1.7 {
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notes.push("租金收益率偏低，安全边际不足".to_string());
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}
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if adjusted.mortgage_rate_pct >= 4.5 {
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notes.push("按揭利率处于偏紧区间，购买力敏感".to_string());
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}
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if run.policy_signal_delta < 0 && multiplier >= 1.0 {
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notes.push("政策假设偏谨慎，估值修复可能延后".to_string());
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}
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if notes.is_empty() {
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notes.push("核心风险未显著恶化，适合继续跟踪量价验证".to_string());
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}
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notes
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}
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fn scenario_price_delta_pct(run: &ScenarioRun, multiplier: f64) -> f64 {
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let rate_effect = -0.018 * run.interest_rate_delta_bps;
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let policy_effect = run.policy_signal_delta as f64 * 1.35;
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let supply_effect = -0.035 * run.supply_delta_pct;
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let rent_effect = 0.08 * run.rent_delta_pct;
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((rate_effect + policy_effect + supply_effect + rent_effect) * multiplier).clamp(-35.0, 35.0)
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}
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fn scenario_transaction_delta_pct(run: &ScenarioRun, multiplier: f64) -> f64 {
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let rate_effect = -0.045 * run.interest_rate_delta_bps;
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let policy_effect = run.policy_signal_delta as f64 * 4.5;
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let supply_effect = 0.08 * run.supply_delta_pct;
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let rent_effect = 0.04 * run.rent_delta_pct;
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((rate_effect + policy_effect + supply_effect + rent_effect) * multiplier).clamp(-70.0, 160.0)
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}
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fn adjusted_f64(value: f64, pct_delta: f64, minimum: f64) -> f64 {
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(value * (1.0 + pct_delta / 100.0)).max(minimum)
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}
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fn adjusted_i32(value: i32, pct_delta: f64, minimum: i32) -> i32 {
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((value as f64) * (1.0 + pct_delta / 100.0))
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.round()
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.max(minimum as f64) as i32
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}
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async fn recompute_area_scores_in_tx(
|
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tx: &mut sqlx::Transaction<'_, sqlx::Postgres>,
|
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month: &str,
|
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@@ -2501,6 +2846,21 @@ fn validate_sha256(value: &str) -> ApiResult<()> {
|
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}
|
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}
|
||||
|
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fn validate_identifier(value: &str) -> ApiResult<()> {
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let valid = !value.is_empty()
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&& value.len() <= 80
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&& value
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.chars()
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.all(|item| item.is_ascii_alphanumeric() || item == '_' || item == '-')
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&& !has_sensitive_text(value);
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|
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if valid {
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Ok(())
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} else {
|
||||
Err(ApiError::BadRequest("invalid identifier".to_string()))
|
||||
}
|
||||
}
|
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|
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fn has_sensitive_text(value: &str) -> bool {
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let lower = value.to_ascii_lowercase();
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lower.contains("password")
|
||||
@@ -2515,11 +2875,15 @@ fn has_sensitive_text(value: &str) -> bool {
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use crate::models::{
|
||||
CreateDataSource, CreateIngestionRun, CreateRawArtifact, CreateWatchlistItem,
|
||||
FinishIngestionRun, SimilarNeighborhoodCandidate, UpdateWatchlistItem,
|
||||
CreateDataSource, CreateIngestionRun, CreateRawArtifact, CreateScenarioRun,
|
||||
CreateWatchlistItem, FinishIngestionRun, ScenarioRun, SimilarNeighborhoodCandidate,
|
||||
UpdateWatchlistItem,
|
||||
};
|
||||
|
||||
use super::{parse_compare_ids, similar_neighborhood, validate_month, validate_sha256};
|
||||
use super::{
|
||||
parse_compare_ids, scenario_assumptions, scenario_price_delta_pct,
|
||||
scenario_transaction_delta_pct, similar_neighborhood, validate_month, validate_sha256,
|
||||
};
|
||||
|
||||
#[test]
|
||||
fn accepts_valid_month() {
|
||||
@@ -2712,6 +3076,35 @@ mod tests {
|
||||
.is_err());
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn validates_scenario_run_payload() {
|
||||
assert!(CreateScenarioRun {
|
||||
name: "利率上行压力测试".to_string(),
|
||||
target_month: "2026-05".to_string(),
|
||||
area_id: Some("zhangjiang".to_string()),
|
||||
interest_rate_delta_bps: 50.0,
|
||||
policy_signal_delta: -1,
|
||||
supply_delta_pct: 20.0,
|
||||
rent_delta_pct: 3.0,
|
||||
notes: Some("手工假设".to_string()),
|
||||
}
|
||||
.validate()
|
||||
.is_ok());
|
||||
|
||||
assert!(CreateScenarioRun {
|
||||
name: "bad".to_string(),
|
||||
target_month: "2026-05".to_string(),
|
||||
area_id: None,
|
||||
interest_rate_delta_bps: 500.0,
|
||||
policy_signal_delta: 0,
|
||||
supply_delta_pct: 0.0,
|
||||
rent_delta_pct: 0.0,
|
||||
notes: None,
|
||||
}
|
||||
.validate()
|
||||
.is_err());
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn validates_sha256_query_value() {
|
||||
assert!(validate_sha256(&"0".repeat(64)).is_ok());
|
||||
@@ -2779,4 +3172,24 @@ mod tests {
|
||||
building_age_score: 85.0,
|
||||
}
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn scenario_shocks_have_expected_direction() {
|
||||
let run = ScenarioRun {
|
||||
scenario_run_id: 1,
|
||||
name: "压力测试".to_string(),
|
||||
target_month: "2026-05".to_string(),
|
||||
area_id: None,
|
||||
interest_rate_delta_bps: 50.0,
|
||||
policy_signal_delta: -1,
|
||||
supply_delta_pct: 30.0,
|
||||
rent_delta_pct: 5.0,
|
||||
notes: "".to_string(),
|
||||
created_at: "2026-06-24".to_string(),
|
||||
};
|
||||
|
||||
assert!(scenario_price_delta_pct(&run, 1.0) < 0.0);
|
||||
assert!(scenario_transaction_delta_pct(&run, 1.0) < 0.0);
|
||||
assert_eq!(scenario_assumptions(&run, 1.0).len(), 5);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -59,6 +59,12 @@ pub struct ModelRunDiffQuery {
|
||||
pub candidate_run_id: i64,
|
||||
}
|
||||
|
||||
#[derive(Debug, Deserialize)]
|
||||
pub struct ScenarioRunQuery {
|
||||
pub target_month: Option<String>,
|
||||
pub area_id: Option<String>,
|
||||
}
|
||||
|
||||
#[derive(Debug, Deserialize)]
|
||||
pub struct RawArtifactQuery {
|
||||
pub source_id: Option<i64>,
|
||||
@@ -487,6 +493,100 @@ pub struct SimilarNeighborhoodResponse {
|
||||
pub items: Vec<SimilarNeighborhood>,
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, Serialize, FromRow)]
|
||||
pub struct ScenarioRun {
|
||||
pub scenario_run_id: i64,
|
||||
pub name: String,
|
||||
pub target_month: String,
|
||||
pub area_id: Option<String>,
|
||||
pub interest_rate_delta_bps: f64,
|
||||
pub policy_signal_delta: i32,
|
||||
pub supply_delta_pct: f64,
|
||||
pub rent_delta_pct: f64,
|
||||
pub notes: String,
|
||||
pub created_at: String,
|
||||
}
|
||||
|
||||
#[derive(Debug, Deserialize)]
|
||||
pub struct CreateScenarioRun {
|
||||
pub name: String,
|
||||
pub target_month: String,
|
||||
pub area_id: Option<String>,
|
||||
pub interest_rate_delta_bps: f64,
|
||||
pub policy_signal_delta: i32,
|
||||
pub supply_delta_pct: f64,
|
||||
pub rent_delta_pct: f64,
|
||||
pub notes: Option<String>,
|
||||
}
|
||||
|
||||
impl CreateScenarioRun {
|
||||
pub fn validate(&self) -> Result<(), &'static str> {
|
||||
if self.name.trim().is_empty() {
|
||||
return Err("name is required");
|
||||
}
|
||||
if self.name.len() > 80 {
|
||||
return Err("name is too long");
|
||||
}
|
||||
if !(-300.0..=300.0).contains(&self.interest_rate_delta_bps) {
|
||||
return Err("interest_rate_delta_bps must be between -300 and 300");
|
||||
}
|
||||
if !(-4..=4).contains(&self.policy_signal_delta) {
|
||||
return Err("policy_signal_delta must be between -4 and 4");
|
||||
}
|
||||
if !(-100.0..=500.0).contains(&self.supply_delta_pct) {
|
||||
return Err("supply_delta_pct must be between -100 and 500");
|
||||
}
|
||||
if !(-80.0..=200.0).contains(&self.rent_delta_pct) {
|
||||
return Err("rent_delta_pct must be between -80 and 200");
|
||||
}
|
||||
for value in [
|
||||
Some(self.name.as_str()),
|
||||
self.area_id.as_deref(),
|
||||
self.notes.as_deref(),
|
||||
]
|
||||
.into_iter()
|
||||
.flatten()
|
||||
{
|
||||
if has_sensitive_text(value) {
|
||||
return Err("payload contains sensitive text");
|
||||
}
|
||||
}
|
||||
Ok(())
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(Debug, Serialize)]
|
||||
pub struct ScenarioVariant {
|
||||
pub key: String,
|
||||
pub name: String,
|
||||
pub assumptions: Vec<String>,
|
||||
pub items: Vec<ScenarioAreaResult>,
|
||||
}
|
||||
|
||||
#[derive(Debug, Serialize)]
|
||||
pub struct ScenarioAreaResult {
|
||||
pub area_id: String,
|
||||
pub name: String,
|
||||
pub district: String,
|
||||
pub baseline_score: f64,
|
||||
pub projected_score: f64,
|
||||
pub score_delta: f64,
|
||||
pub baseline_price_psm: f64,
|
||||
pub projected_price_psm: f64,
|
||||
pub price_delta_pct: f64,
|
||||
pub projected_rent_yield_pct: f64,
|
||||
pub projected_liquidity_score: f64,
|
||||
pub projected_supply_risk_score: f64,
|
||||
pub recommendation: String,
|
||||
pub risk_notes: Vec<String>,
|
||||
}
|
||||
|
||||
#[derive(Debug, Serialize)]
|
||||
pub struct ScenarioRunResponse {
|
||||
pub run: ScenarioRun,
|
||||
pub variants: Vec<ScenarioVariant>,
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, Serialize, FromRow)]
|
||||
pub struct DataSource {
|
||||
pub source_id: i64,
|
||||
|
||||
@@ -5,13 +5,13 @@ use tower_http::trace::TraceLayer;
|
||||
|
||||
use crate::handlers::{
|
||||
archive_watchlist_item, compare_areas, compare_neighborhoods, create_area_score_model_run,
|
||||
create_data_source, create_ingestion_run, create_raw_artifact, create_watchlist_event,
|
||||
create_watchlist_item, diff_area_score_model_runs, execute_import, finish_ingestion_run,
|
||||
get_area_detail, get_area_diagnostics, get_area_score_lineage, get_neighborhood,
|
||||
get_neighborhood_detail, get_similar_neighborhoods, health, list_area_scores,
|
||||
create_data_source, create_ingestion_run, create_raw_artifact, create_scenario_run,
|
||||
create_watchlist_event, create_watchlist_item, diff_area_score_model_runs, execute_import,
|
||||
finish_ingestion_run, get_area_detail, get_area_diagnostics, get_area_score_lineage,
|
||||
get_neighborhood, get_neighborhood_detail, get_similar_neighborhoods, health, list_area_scores,
|
||||
list_data_sources, list_ingestion_runs, list_model_runs, list_neighborhood_scores,
|
||||
list_neighborhoods, list_raw_artifacts, list_watchlist_events, list_watchlist_items,
|
||||
market_overview, ready, update_watchlist_item, validate_import,
|
||||
list_neighborhoods, list_raw_artifacts, list_scenario_runs, list_watchlist_events,
|
||||
list_watchlist_items, market_overview, ready, update_watchlist_item, validate_import,
|
||||
};
|
||||
use crate::state::AppState;
|
||||
|
||||
@@ -81,6 +81,10 @@ pub fn build_router(state: AppState) -> Router {
|
||||
.route(
|
||||
"/watchlist/{watchlist_item_id}/events",
|
||||
get(list_watchlist_events).post(create_watchlist_event),
|
||||
)
|
||||
.route(
|
||||
"/scenario-runs",
|
||||
get(list_scenario_runs).post(create_scenario_run),
|
||||
),
|
||||
)
|
||||
.layer(TraceLayer::new_for_http())
|
||||
|
||||
Reference in New Issue
Block a user