6 embedded-hal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 254 51.7 probe-rs and cargo-embed . . . . . . . . . . . . . . . . . . . . . . . . . . 255 51.7.1 偵錯 . . . . . . . . on classical as well as async/await concurrency. 您會需要設定新的 Crate，然後下載並準備執行依附元件。接著就能將範例複製貼上至 src/main.rs， 使用這些範例進行實驗： cargo init concurrency cd concurrency cargo add tokio --features full cargo run 形式 生態系統中使用的標準工具，用於建構及執 行 Rust 應用程式。以下簡要介紹 Cargo，以及如何在更廣大的生態系統和本訓練課程中運用 Cargo。 安裝 請按照 https://rustup.rs/ 中的指示操作。 This will give you the Cargo build tool (cargo) and the Rust compiler (rustc). You will also

記錄。需要注意的是，Python 中 range(a, b) 對應的區間是“左閉右開”的，對應的走訪範圍為 ?, ? + 1, … , ? − 1 ： // === File: iteration.rs === /* for 迴圈 */ fn for_loop(n: i32) -> i32 { let mut res = 0; // 迴圈求和 1, 2, ..., n-1, n for i 迴圈中，程式每輪都會先檢查條件，如果條 件為真，則繼續執行，否則就結束迴圈。 下面我們用 while 迴圈來實現求和 1 + 2 + ⋯ + ? ： // === File: iteration.rs === /* while 迴圈 */ fn while_loop(n: i32) -> i32 { let mut res = 0; let mut i = 1; // 初始化條件變數 // 複雜度分析 www.hello‑algo.com 21 例如在以下程式碼中，條件變數 ? 每輪進行兩次更新，這種情況就不太方便用 for 迴圈實現： // === File: iteration.rs === /* while 迴圈（兩次更新） */ fn while_loop_ii(n: i32) -> i32 { let mut res = 0; let mut i = 1; // 初始化條件變數

prepareStatement("select * from test"); ResultSet rs = statement.executeQuery(); while (rs.next()) System.out.println(rs.getString("mycolumn")); statement.close();

example, we would implement Iterators.Reverse{Squares} methods: julia> Base.iterate(rS::Iterators.Reverse{Squares}, state=rS.itr.count) = state < 1 ? nothing : (state*state, state-1) �→ julia> collect(Iterators of the factorization F can be accessed by indexing: The relation between F and A is F.L*F.U == (F.Rs .* A)[F.p, F.q] F further supports the following functions: • \CHAPTER 79. LINEAR ALGEBRA 1462 Component triangular) part of LU p right permutation Vector q left permutation Vector Rs Vector of scaling factors : (L,U,p,q,Rs) components • det See also lu! Note lu(A::AbstractSparseMatrixCSC) uses the

example, we would implement Iterators.Reverse{Squares} methods: julia> Base.iterate(rS::Iterators.Reverse{Squares}, state=rS.itr.count) = state < 1 ? nothing : (state*state, state-1) �→ julia> collect(Iterators of the factorization F can be accessed by indexing: The relation between F and A is F.L*F.U == (F.Rs .* A)[F.p, F.q] F further supports the following functions: • \CHAPTER 79. LINEAR ALGEBRA 1462 Component triangular) part of LU p right permutation Vector q left permutation Vector Rs Vector of scaling factors : (L,U,p,q,Rs) components • det See also lu! Note lu(A::AbstractSparseMatrixCSC) uses the

example, we would implement Iterators.Reverse{Squares} methods: julia> Base.iterate(rS::Iterators.Reverse{Squares}, state=rS.itr.count) = state < 1 ? nothing : (state*state, state-1) �→ julia> collect(Iterators of the factorization F can be accessed by indexing: The relation between F and A is F.L*F.U == (F.Rs .* A)[F.p, F.q] F further supports the following functions: • \CHAPTER 79. LINEAR ALGEBRA 1462 Component triangular) part of LU p right permutation Vector q left permutation Vector Rs Vector of scaling factors : (L,U,p,q,Rs) components • det See also lu! Note lu(A::AbstractSparseMatrixCSC) uses the

example, we would implement Iterators.Reverse{Squares} methods: julia> Base.iterate(rS::Iterators.Reverse{Squares}, state=rS.itr.count) = state < 1 ? nothing : (state*state, state-1) �→ julia> collect(Iterators part of LU p right permutation Vector q left permutation Vector Rs Vector of scaling factors : (L,U,p,q,Rs) components F.L*F.U == (F.Rs .* A)[F.p, F.q] F further supports the following functions: •

example, we would implement Iterators.Reverse{Squares} methods: julia> Base.iterate(rS::Iterators.Reverse{Squares}, state=rS.itr.count) = state < 1 ? nothing : (state*state, state-1) �→ julia> collect(Iterators part of LU p right permutation Vector q left permutation Vector Rs Vector of scaling factors : (L,U,p,q,Rs) components F.L*F.U == (F.Rs .* A)[F.p, F.q] F further supports the following functions: •

example, we would implement Iterators.Reverse{Squares} methods: julia> Base.iterate(rS::Iterators.Reverse{Squares}, state=rS.itr.count) = state < 1 ? nothing : (state*state, state-1) �→ julia> collect(Iterators permutation Vector q left permutation Vector Rs Vector of scaling factors : (L,U,p,q,Rs) components The relation between F and A is F.L*F.U == (F.Rs .* A)[F.p, F.q] F further supports the following

example, we would implement Iterators.Reverse{Squares} methods: julia> Base.iterate(rS::Iterators.Reverse{Squares}, state=rS.itr.count) = state < 1 ? nothing : (state*state, state-1) �→ julia> collect(Iterators of the factorization F can be accessed by indexing: The relation between F and A is F.L*F.U == (F.Rs .* A)[F.p, F.q] F further supports the following functions: • \CHAPTER 81. LINEAR ALGEBRA 1521 Component triangular) part of LU p right permutation Vector q left permutation Vector Rs Vector of scaling factors : (L,U,p,q,Rs) components • det See also lu! Note lu(A::AbstractSparseMatrixCSC) uses the