Do DR calculation in parallel

Approx 5x faster on my machine

Cargo.lock

@@ -131,6 +131,7 @@ dependencies = [
  "prost-reflect",
  "pulldown-cmark 0.13.0",
  "rand 0.9.1",
+ "rayon",
  "regex",
  "reqwest 0.12.20",
  "rusqlite",

Cargo.toml

@@ -110,6 +110,7 @@ prost-types = "0.13"
 pulldown-cmark = "0.13.0"
 pyo3 = { version = "0.25.1", features = ["extension-module", "abi3", "abi3-py39"] }
 rand = "0.9.1"
+rayon = "1.10.0"
 regex = "1.11.1"
 reqwest = { version = "0.12.20", default-features = false, features = ["json", "socks", "stream", "multipart"] }
 rusqlite = { version = "0.36.0", features = ["trace", "functions", "collation", "bundled"] }

rslib/Cargo.toml

@@ -81,6 +81,7 @@ pin-project.workspace = true
 prost.workspace = true
 pulldown-cmark.workspace = true
 rand.workspace = true
+rayon.workspace = true
 regex.workspace = true
 reqwest.workspace = true
 rusqlite.workspace = true

rslib/src/scheduler/fsrs/simulator.rs

@@ -16,6 +16,8 @@ use fsrs::FSRS;
 use itertools::Itertools;
 use rand::rngs::StdRng;
 use rand::Rng;
+use rayon::iter::IntoParallelIterator;
+use rayon::iter::ParallelIterator;
 
 use crate::card::CardQueue;
 use crate::card::CardType;
@@ -276,6 +278,7 @@ impl Collection {
     ) -> Result<SimulateFsrsWorkloadResponse> {
         let (config, cards) = self.simulate_request_to_config(&req)?;
         let dr_workload = (70u32..=99u32)
+            .into_par_iter()
             .map(|dr| {
                 let result = simulate(
                     &config,

rslib/src/timestamp.rs

@@ -93,6 +93,10 @@ impl TimestampMillis {
     pub fn adding_secs(self, secs: i64) -> Self {
         Self(self.0 + secs * 1000)
     }
+
+    pub fn elapsed_millis(self) -> u64 {
+        (Self::now().0 - self.0).max(0) as u64
+    }
 }
 
 fn elapsed() -> time::Duration {