Add rqalpha-style scheduler primitives
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@@ -6,7 +6,8 @@ use chrono::NaiveDate;
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use fidc_core::{
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BacktestConfig, BacktestEngine, BenchmarkSnapshot, BrokerSimulator, CandidateEligibility,
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ChinaAShareCostModel, ChinaEquityRuleHooks, DailyFactorSnapshot, DailyMarketSnapshot, DataSet,
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Instrument, PriceField, Strategy, StrategyContext, StrategyDecision,
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Instrument, PriceField, ScheduleRule, ScheduleStage, Strategy, StrategyContext,
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StrategyDecision,
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};
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fn d(year: i32, month: u32, day: u32) -> NaiveDate {
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@@ -115,6 +116,42 @@ impl Strategy for AuctionOrderStrategy {
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}
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}
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struct ScheduledProbeStrategy {
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log: Rc<RefCell<Vec<String>>>,
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}
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impl Strategy for ScheduledProbeStrategy {
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fn name(&self) -> &str {
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"scheduled-probe"
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}
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fn schedule_rules(&self) -> Vec<ScheduleRule> {
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vec![
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ScheduleRule::daily("daily_auction", ScheduleStage::OpenAuction),
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ScheduleRule::weekly_by_weekday("friday_on_day", 5, ScheduleStage::OnDay),
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ScheduleRule::monthly("first_trading_day_on_day", 1, ScheduleStage::OnDay),
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]
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}
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fn on_scheduled(
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&mut self,
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ctx: &StrategyContext<'_>,
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rule: &ScheduleRule,
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) -> Result<StrategyDecision, fidc_core::BacktestError> {
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self.log
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.borrow_mut()
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.push(format!("scheduled:{}:{}", rule.name, ctx.execution_date));
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Ok(StrategyDecision::default())
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}
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fn on_day(
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&mut self,
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_ctx: &StrategyContext<'_>,
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) -> Result<StrategyDecision, fidc_core::BacktestError> {
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Ok(StrategyDecision::default())
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}
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}
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#[test]
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fn engine_runs_strategy_hooks_in_daily_order() {
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let date1 = d(2025, 1, 2);
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@@ -381,3 +418,221 @@ fn engine_executes_open_auction_decisions_before_on_day() {
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assert_eq!(result.fills[0].reason, "auction_buy");
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assert_eq!(result.fills[0].quantity, 100);
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}
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#[test]
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fn engine_runs_scheduled_rules_for_daily_weekly_and_monthly_triggers() {
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let date1 = d(2025, 1, 30);
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let date2 = d(2025, 1, 31);
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let date3 = d(2025, 2, 3);
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let data = DataSet::from_components(
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vec![Instrument {
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symbol: "000001.SZ".to_string(),
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name: "Anchor".to_string(),
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board: "SZ".to_string(),
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round_lot: 100,
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listed_at: Some(d(2020, 1, 1)),
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delisted_at: None,
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status: "active".to_string(),
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}],
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vec![
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DailyMarketSnapshot {
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date: date1,
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symbol: "000001.SZ".to_string(),
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timestamp: Some("2025-01-30 09:25:00".to_string()),
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day_open: 10.0,
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open: 10.0,
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high: 10.1,
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low: 9.9,
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close: 10.0,
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last_price: 10.0,
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bid1: 10.0,
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ask1: 10.0,
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prev_close: 9.9,
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volume: 100_000,
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tick_volume: 100_000,
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bid1_volume: 100_000,
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ask1_volume: 100_000,
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trading_phase: Some("open_auction".to_string()),
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paused: false,
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upper_limit: 11.0,
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lower_limit: 9.0,
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price_tick: 0.01,
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},
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DailyMarketSnapshot {
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date: date2,
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symbol: "000001.SZ".to_string(),
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timestamp: Some("2025-01-31 09:25:00".to_string()),
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day_open: 10.1,
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open: 10.1,
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high: 10.2,
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low: 10.0,
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close: 10.1,
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last_price: 10.1,
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bid1: 10.1,
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ask1: 10.1,
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prev_close: 10.0,
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volume: 110_000,
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tick_volume: 110_000,
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bid1_volume: 110_000,
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ask1_volume: 110_000,
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trading_phase: Some("open_auction".to_string()),
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paused: false,
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upper_limit: 11.1,
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lower_limit: 9.1,
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price_tick: 0.01,
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},
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DailyMarketSnapshot {
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date: date3,
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symbol: "000001.SZ".to_string(),
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timestamp: Some("2025-02-03 09:25:00".to_string()),
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day_open: 10.2,
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open: 10.2,
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high: 10.3,
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low: 10.1,
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close: 10.2,
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last_price: 10.2,
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bid1: 10.2,
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ask1: 10.2,
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prev_close: 10.1,
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volume: 120_000,
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tick_volume: 120_000,
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bid1_volume: 120_000,
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ask1_volume: 120_000,
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trading_phase: Some("open_auction".to_string()),
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paused: false,
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upper_limit: 11.2,
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lower_limit: 9.2,
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price_tick: 0.01,
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},
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],
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vec![
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DailyFactorSnapshot {
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date: date1,
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symbol: "000001.SZ".to_string(),
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market_cap_bn: 20.0,
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free_float_cap_bn: 18.0,
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pe_ttm: 10.0,
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turnover_ratio: Some(1.0),
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effective_turnover_ratio: Some(1.0),
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extra_factors: BTreeMap::new(),
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},
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DailyFactorSnapshot {
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date: date2,
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symbol: "000001.SZ".to_string(),
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market_cap_bn: 21.0,
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free_float_cap_bn: 19.0,
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pe_ttm: 10.0,
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turnover_ratio: Some(1.0),
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effective_turnover_ratio: Some(1.0),
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extra_factors: BTreeMap::new(),
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},
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DailyFactorSnapshot {
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date: date3,
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symbol: "000001.SZ".to_string(),
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market_cap_bn: 22.0,
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free_float_cap_bn: 20.0,
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pe_ttm: 10.0,
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turnover_ratio: Some(1.0),
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effective_turnover_ratio: Some(1.0),
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extra_factors: BTreeMap::new(),
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},
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],
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vec![
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CandidateEligibility {
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date: date1,
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symbol: "000001.SZ".to_string(),
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is_st: false,
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is_new_listing: false,
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is_paused: false,
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allow_buy: true,
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allow_sell: true,
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is_kcb: false,
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is_one_yuan: false,
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},
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CandidateEligibility {
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date: date2,
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symbol: "000001.SZ".to_string(),
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is_st: false,
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is_new_listing: false,
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is_paused: false,
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allow_buy: true,
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allow_sell: true,
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is_kcb: false,
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is_one_yuan: false,
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},
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CandidateEligibility {
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date: date3,
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symbol: "000001.SZ".to_string(),
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is_st: false,
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is_new_listing: false,
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is_paused: false,
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allow_buy: true,
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allow_sell: true,
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is_kcb: false,
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is_one_yuan: false,
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},
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],
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vec![
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BenchmarkSnapshot {
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date: date1,
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benchmark: "000300.SH".to_string(),
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open: 100.0,
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close: 100.0,
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prev_close: 99.0,
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volume: 1_000_000,
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},
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BenchmarkSnapshot {
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date: date2,
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benchmark: "000300.SH".to_string(),
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open: 101.0,
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close: 101.0,
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prev_close: 100.0,
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volume: 1_100_000,
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},
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BenchmarkSnapshot {
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date: date3,
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benchmark: "000300.SH".to_string(),
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open: 102.0,
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close: 102.0,
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prev_close: 101.0,
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volume: 1_200_000,
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},
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],
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)
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.expect("dataset");
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let log = Rc::new(RefCell::new(Vec::new()));
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let strategy = ScheduledProbeStrategy { log: log.clone() };
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let broker = BrokerSimulator::new_with_execution_price(
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ChinaAShareCostModel::default(),
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ChinaEquityRuleHooks::default(),
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PriceField::DayOpen,
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);
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let mut engine = BacktestEngine::new(
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data,
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strategy,
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broker,
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BacktestConfig {
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initial_cash: 100_000.0,
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benchmark_code: "000300.SH".to_string(),
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start_date: Some(date1),
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end_date: Some(date3),
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decision_lag_trading_days: 0,
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execution_price_field: PriceField::DayOpen,
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},
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);
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engine.run().expect("backtest run");
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assert_eq!(
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log.borrow().as_slice(),
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[
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"scheduled:daily_auction:2025-01-30",
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"scheduled:first_trading_day_on_day:2025-01-30",
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"scheduled:daily_auction:2025-01-31",
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"scheduled:friday_on_day:2025-01-31",
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"scheduled:daily_auction:2025-02-03",
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"scheduled:first_trading_day_on_day:2025-02-03",
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]
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);
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}
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