用快速哈希优化回测内部索引
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@@ -2,6 +2,7 @@ use std::borrow::Cow;
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use std::collections::{BTreeMap, HashMap, HashSet};
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use std::sync::{Arc, OnceLock};
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use ahash::AHashMap;
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use chrono::{NaiveDate, NaiveDateTime};
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use rayon::prelude::*;
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use serde::{Deserialize, Serialize};
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@@ -1136,12 +1137,12 @@ pub struct DataSet {
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execution_quotes_by_date: HashMap<NaiveDate, HashMap<String, Vec<IntradayExecutionQuote>>>,
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order_book_depth_index: HashMap<(NaiveDate, String), Vec<IntradayOrderBookDepthLevel>>,
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benchmark_by_date: BTreeMap<NaiveDate, BenchmarkSnapshot>,
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market_series_by_symbol: Arc<HashMap<String, Arc<SymbolPriceSeries>>>,
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adjusted_close_series_by_symbol: Arc<HashMap<String, Arc<AdjustedCloseSeries>>>,
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market_series_by_symbol: Arc<AHashMap<String, Arc<SymbolPriceSeries>>>,
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adjusted_close_series_by_symbol: Arc<AHashMap<String, Arc<AdjustedCloseSeries>>>,
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market_series_by_symbol_id: Arc<Vec<Option<Arc<SymbolPriceSeries>>>>,
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adjusted_close_series_by_symbol_id: Arc<Vec<Option<Arc<AdjustedCloseSeries>>>>,
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benchmark_series_cache: BenchmarkPriceSeries,
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symbol_id_by_code: Arc<HashMap<String, u32>>,
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symbol_id_by_code: Arc<AHashMap<String, u32>>,
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eligible_universe_by_date: Arc<OnceLock<BTreeMap<NaiveDate, Vec<EligibleUniverseSnapshot>>>>,
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benchmark_code: String,
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futures_params_by_symbol: HashMap<String, Vec<FuturesTradingParameter>>,
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@@ -1305,27 +1306,32 @@ impl DataSet {
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let mut factor_by_date = group_arc_by_date(&factors, |item| item.date);
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sort_arc_groups_by_symbol(&mut factor_by_date, |item| item.symbol.as_str());
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let mut market_rows_by_symbol = HashMap::<String, Vec<&DailyMarketSnapshot>>::new();
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let mut market_rows_by_symbol = AHashMap::<String, Vec<&DailyMarketSnapshot>>::new();
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for row in &market {
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market_rows_by_symbol
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.entry(row.symbol.clone())
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.or_default()
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.push(row.as_ref());
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}
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let market_rows_by_symbol = market_rows_by_symbol.into_iter().collect::<Vec<_>>();
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let market_series_by_symbol = market_rows_by_symbol
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.into_par_iter()
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.map(|(symbol, rows)| {
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let series = Arc::new(SymbolPriceSeries::new(symbol.clone(), rows));
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(symbol, series)
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})
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.collect::<HashMap<_, _>>();
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.collect::<Vec<_>>()
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.into_iter()
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.collect::<AHashMap<_, _>>();
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let adjusted_close_series_by_symbol = market_series_by_symbol
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.par_iter()
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.filter_map(|(symbol, market)| {
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AdjustedCloseSeries::new(market, &factor_by_date)
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.map(|series| (symbol.clone(), Arc::new(series)))
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})
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.collect::<HashMap<_, _>>();
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.collect::<Vec<_>>()
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.into_iter()
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.collect::<AHashMap<_, _>>();
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let factor_texts = factor_texts
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.into_iter()
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.filter_map(|mut item| {
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@@ -3298,7 +3304,7 @@ fn build_symbol_id_index(
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market_by_date: &BTreeMap<NaiveDate, Vec<Arc<DailyMarketSnapshot>>>,
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factor_by_date: &BTreeMap<NaiveDate, Vec<Arc<DailyFactorSnapshot>>>,
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candidate_by_date: &BTreeMap<NaiveDate, Vec<Arc<CandidateEligibility>>>,
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) -> HashMap<String, u32> {
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) -> AHashMap<String, u32> {
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let mut symbols = instruments.keys().cloned().collect::<HashSet<_>>();
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for rows in market_by_date.values() {
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for row in rows {
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@@ -3337,7 +3343,7 @@ fn build_symbol_id_index(
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fn build_group_symbol_ids<T, F>(
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groups: &BTreeMap<NaiveDate, Vec<Arc<T>>>,
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symbol_id_by_code: &HashMap<String, u32>,
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symbol_id_by_code: &AHashMap<String, u32>,
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symbol_of: F,
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) -> BTreeMap<NaiveDate, Vec<u32>>
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where
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@@ -1,7 +1,8 @@
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use std::cell::RefCell;
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use std::collections::{BTreeMap, BTreeSet, HashMap};
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use std::collections::{BTreeMap, BTreeSet};
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use std::sync::Arc;
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use ahash::{AHashMap, AHashSet};
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use chrono::{Datelike, Duration, NaiveDate, NaiveDateTime, NaiveTime};
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use rhai::{AST, Dynamic, Engine, Map, Scope};
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@@ -768,24 +769,19 @@ fn framework_stock_rolling_factor_requirement(key: &str) -> Option<(&'static str
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struct SelectiveExpressionScope<'a> {
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inner: Scope<'static>,
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expression_identifiers: &'a BTreeSet<String>,
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prelude_identifiers: &'a BTreeSet<String>,
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required_identifiers: &'a AHashSet<String>,
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}
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impl<'a> SelectiveExpressionScope<'a> {
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fn new(
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expression_identifiers: &'a BTreeSet<String>,
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prelude_identifiers: &'a BTreeSet<String>,
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) -> Self {
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fn new(required_identifiers: &'a AHashSet<String>) -> Self {
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Self {
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inner: Scope::new(),
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expression_identifiers,
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prelude_identifiers,
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required_identifiers,
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}
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}
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fn requires(&self, name: &str) -> bool {
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self.expression_identifiers.contains(name) || self.prelude_identifiers.contains(name)
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self.required_identifiers.contains(name)
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}
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fn push<T: Into<Dynamic>>(&mut self, name: &str, value: T) -> &mut Self {
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@@ -811,6 +807,7 @@ impl<'a> SelectiveExpressionScope<'a> {
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struct ExpressionEvalPlan {
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identifiers: BTreeSet<String>,
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scope_identifiers: AHashSet<String>,
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runtime_template: Result<RuntimeExpressionTemplate, String>,
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prelude_source: String,
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prelude_identifiers: BTreeSet<String>,
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@@ -910,11 +907,11 @@ pub struct PlatformExprStrategy {
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/// Value 是 Rhai 编译产物。命中后 eval 走 eval_ast_with_scope,避免重复
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/// parsing。一次回测里同一表达式(stock_filter / stop_loss / rank_expr 等)
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/// 会被反复执行,重复解析的常数级开销在大规模回测里不可忽略。
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compiled_cache: RefCell<HashMap<String, AST>>,
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compiled_cache: RefCell<AHashMap<String, AST>>,
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/// 命中计数与未命中计数,便于在 unit test 中验证缓存生效;非生产指标。
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cache_hits: RefCell<u64>,
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cache_misses: RefCell<u64>,
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expression_plan_cache: RefCell<HashMap<String, Arc<ExpressionEvalPlan>>>,
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expression_plan_cache: RefCell<AHashMap<String, Arc<ExpressionEvalPlan>>>,
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prelude_dependency_plan: PreludeDependencyPlan,
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prelude_identifier_candidates: BTreeSet<String>,
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prelude_declared_identifiers: BTreeSet<String>,
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@@ -926,7 +923,7 @@ pub struct PlatformExprStrategy {
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stock_text_factors_required: bool,
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stock_state_cache_date: RefCell<Option<NaiveDate>>,
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stock_state_cache: RefCell<
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HashMap<(NaiveDate, NaiveDate, u32, Option<NaiveTime>, bool), StockExpressionState>,
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AHashMap<(NaiveDate, NaiveDate, u32, Option<NaiveTime>, bool), StockExpressionState>,
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>,
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}
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@@ -1222,10 +1219,10 @@ impl PlatformExprStrategy {
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position_entry_dates: BTreeMap::new(),
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position_holding_days: BTreeMap::new(),
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position_holding_days_last_counted: BTreeMap::new(),
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compiled_cache: RefCell::new(HashMap::new()),
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compiled_cache: RefCell::new(AHashMap::new()),
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cache_hits: RefCell::new(0),
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cache_misses: RefCell::new(0),
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expression_plan_cache: RefCell::new(HashMap::new()),
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expression_plan_cache: RefCell::new(AHashMap::new()),
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prelude_dependency_plan,
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prelude_identifier_candidates,
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prelude_declared_identifiers,
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@@ -1236,7 +1233,7 @@ impl PlatformExprStrategy {
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stock_extra_factor_identifiers,
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stock_text_factors_required,
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stock_state_cache_date: RefCell::new(None),
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stock_state_cache: RefCell::new(HashMap::new()),
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stock_state_cache: RefCell::new(AHashMap::new()),
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}
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}
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@@ -3973,13 +3970,14 @@ impl PlatformExprStrategy {
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day: &DayExpressionState,
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stock: Option<&StockExpressionState>,
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position: Option<&PositionExpressionState>,
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scope_identifiers: &AHashSet<String>,
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identifiers: &BTreeSet<String>,
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prelude_identifiers: &BTreeSet<String>,
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include_day_factors: bool,
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include_factors_map: bool,
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include_process_event_counts: bool,
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) -> Scope<'static> {
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let mut scope = SelectiveExpressionScope::new(identifiers, prelude_identifiers);
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let mut scope = SelectiveExpressionScope::new(scope_identifiers);
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let trade_date = day.date.format("%Y-%m-%d").to_string();
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let decision_date = ctx.decision_date.format("%Y-%m-%d").to_string();
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let execution_date = ctx.execution_date.format("%Y-%m-%d").to_string();
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@@ -4686,7 +4684,8 @@ impl PlatformExprStrategy {
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day,
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stock,
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position,
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&normalized_identifiers,
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&expression_plan.scope_identifiers,
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normalized_identifiers,
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prelude_identifiers,
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include_day_factors,
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include_factors_map,
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@@ -4756,10 +4755,16 @@ impl PlatformExprStrategy {
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.prelude_dependency_plan
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.source_for_expression(&identifiers);
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let prelude_identifiers = Self::extract_identifier_candidates(&prelude_source);
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let scope_identifiers = identifiers
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.iter()
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.chain(&prelude_identifiers)
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.cloned()
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.collect::<AHashSet<_>>();
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let prelude_runtime_template = (!prelude_source.trim().is_empty())
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.then(|| Self::compile_runtime_helper_template(&prelude_source));
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let plan = Arc::new(ExpressionEvalPlan {
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identifiers,
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scope_identifiers,
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runtime_template: Self::compile_runtime_helper_template(&normalized),
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prelude_source,
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prelude_identifiers,
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