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# Description This PR adds an internal representation language to Nushell, offering an alternative evaluator based on simple instructions, stream-containing registers, and indexed control flow. The number of registers required is determined statically at compile-time, and the fixed size required is allocated upon entering the block. Each instruction is associated with a span, which makes going backwards from IR instructions to source code very easy. Motivations for IR: 1. **Performance.** By simplifying the evaluation path and making it more cache-friendly and branch predictor-friendly, code that does a lot of computation in Nushell itself can be sped up a decent bit. Because the IR is fairly easy to reason about, we can also implement optimization passes in the future to eliminate and simplify code. 2. **Correctness.** The instructions mostly have very simple and easily-specified behavior, so hopefully engine changes are a little bit easier to reason about, and they can be specified in a more formal way at some point. I have made an effort to document each of the instructions in the docs for the enum itself in a reasonably specific way. Some of the errors that would have happened during evaluation before are now moved to the compilation step instead, because they don't make sense to check during evaluation. 3. **As an intermediate target.** This is a good step for us to bring the [`new-nu-parser`](https://github.com/nushell/new-nu-parser) in at some point, as code generated from new AST can be directly compared to code generated from old AST. If the IR code is functionally equivalent, it will behave the exact same way. 4. **Debugging.** With a little bit more work, we can probably give control over advancing the virtual machine that `IrBlock`s run on to some sort of external driver, making things like breakpoints and single stepping possible. Tools like `view ir` and [`explore ir`](https://github.com/devyn/nu_plugin_explore_ir) make it easier than before to see what exactly is going on with your Nushell code. The goal is to eventually replace the AST evaluator entirely, once we're sure it's working just as well. You can help dogfood this by running Nushell with `$env.NU_USE_IR` set to some value. The environment variable is checked when Nushell starts, so config runs with IR, or it can also be set on a line at the REPL to change it dynamically. It is also checked when running `do` in case within a script you want to just run a specific piece of code with or without IR. # Example ```nushell view ir { |data| mut sum = 0 for n in $data { $sum += $n } $sum } ``` ```gas # 3 registers, 19 instructions, 0 bytes of data 0: load-literal %0, int(0) 1: store-variable var 904, %0 # let 2: drain %0 3: drop %0 4: load-variable %1, var 903 5: iterate %0, %1, end 15 # for, label(1), from(14:) 6: store-variable var 905, %0 7: load-variable %0, var 904 8: load-variable %2, var 905 9: binary-op %0, Math(Plus), %2 10: span %0 11: store-variable var 904, %0 12: load-literal %0, nothing 13: drain %0 14: jump 5 15: drop %0 # label(0), from(5:) 16: drain %0 17: load-variable %0, var 904 18: return %0 ``` # Benchmarks All benchmarks run on a base model Mac Mini M1. ## Iterative Fibonacci sequence This is about as best case as possible, making use of the much faster control flow. Most code will not experience a speed improvement nearly this large. ```nushell def fib [n: int] { mut a = 0 mut b = 1 for _ in 2..=$n { let c = $a + $b $a = $b $b = $c } $b } use std bench bench { 0..50 | each { |n| fib $n } } ``` IR disabled: ``` ╭───────┬─────────────────╮ │ mean │ 1ms 924µs 665ns │ │ min │ 1ms 700µs 83ns │ │ max │ 3ms 450µs 125ns │ │ std │ 395µs 759ns │ │ times │ [list 50 items] │ ╰───────┴─────────────────╯ ``` IR enabled: ``` ╭───────┬─────────────────╮ │ mean │ 452µs 820ns │ │ min │ 427µs 417ns │ │ max │ 540µs 167ns │ │ std │ 17µs 158ns │ │ times │ [list 50 items] │ ╰───────┴─────────────────╯ ```  ## [gradient_benchmark_no_check.nu](https://github.com/nushell/nu_scripts/blob/main/benchmarks/gradient_benchmark_no_check.nu) IR disabled: ``` ╭───┬──────────────────╮ │ 0 │ 27ms 929µs 958ns │ │ 1 │ 21ms 153µs 459ns │ │ 2 │ 18ms 639µs 666ns │ │ 3 │ 19ms 554µs 583ns │ │ 4 │ 13ms 383µs 375ns │ │ 5 │ 11ms 328µs 208ns │ │ 6 │ 5ms 659µs 542ns │ ╰───┴──────────────────╯ ``` IR enabled: ``` ╭───┬──────────────────╮ │ 0 │ 22ms 662µs │ │ 1 │ 17ms 221µs 792ns │ │ 2 │ 14ms 786µs 708ns │ │ 3 │ 13ms 876µs 834ns │ │ 4 │ 13ms 52µs 875ns │ │ 5 │ 11ms 269µs 666ns │ │ 6 │ 6ms 942µs 500ns │ ╰───┴──────────────────╯ ``` ## [random-bytes.nu](https://github.com/nushell/nu_scripts/blob/main/benchmarks/random-bytes.nu) I got pretty random results out of this benchmark so I decided not to include it. Not clear why. # User-Facing Changes - IR compilation errors may appear even if the user isn't evaluating with IR. - IR evaluation can be enabled by setting the `NU_USE_IR` environment variable to any value. - New command `view ir` pretty-prints the IR for a block, and `view ir --json` can be piped into an external tool like [`explore ir`](https://github.com/devyn/nu_plugin_explore_ir). # Tests + Formatting All tests are passing with `NU_USE_IR=1`, and I've added some more eval tests to compare the results for some very core operations. I will probably want to add some more so we don't have to always check `NU_USE_IR=1 toolkit test --workspace` on a regular basis. # After Submitting - [ ] release notes - [ ] further documentation of instructions? - [ ] post-release: publish `nu_plugin_explore_ir`
247 lines
7.4 KiB
Rust
247 lines
7.4 KiB
Rust
use crate::SpanId;
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use miette::SourceSpan;
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use serde::{Deserialize, Serialize};
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use std::ops::Deref;
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pub trait GetSpan {
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fn get_span(&self, span_id: SpanId) -> Span;
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}
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/// A spanned area of interest, generic over what kind of thing is of interest
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#[derive(Clone, Copy, Debug, Serialize, Deserialize, PartialEq, Eq)]
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pub struct Spanned<T> {
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pub item: T,
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pub span: Span,
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}
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impl<T> Spanned<T> {
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/// Map to a spanned reference of the inner type, i.e. `Spanned<T> -> Spanned<&T>`.
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pub fn as_ref(&self) -> Spanned<&T> {
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Spanned {
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item: &self.item,
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span: self.span,
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}
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}
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/// Map to a mutable reference of the inner type, i.e. `Spanned<T> -> Spanned<&mut T>`.
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pub fn as_mut(&mut self) -> Spanned<&mut T> {
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Spanned {
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item: &mut self.item,
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span: self.span,
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}
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}
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/// Map to the result of [`.deref()`](std::ops::Deref::deref) on the inner type.
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///
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/// This can be used for example to turn `Spanned<Vec<T>>` into `Spanned<&[T]>`.
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pub fn as_deref(&self) -> Spanned<&<T as Deref>::Target>
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where
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T: Deref,
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{
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Spanned {
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item: self.item.deref(),
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span: self.span,
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}
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}
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/// Map the spanned item with a function.
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pub fn map<U>(self, f: impl FnOnce(T) -> U) -> Spanned<U> {
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Spanned {
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item: f(self.item),
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span: self.span,
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}
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}
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}
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impl<T, E> Spanned<Result<T, E>> {
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/// Move the `Result` to the outside, resulting in a spanned `Ok` or unspanned `Err`.
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pub fn transpose(self) -> Result<Spanned<T>, E> {
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match self {
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Spanned {
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item: Ok(item),
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span,
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} => Ok(Spanned { item, span }),
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Spanned {
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item: Err(err),
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span: _,
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} => Err(err),
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}
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}
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}
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/// Helper trait to create [`Spanned`] more ergonomically.
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pub trait IntoSpanned: Sized {
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/// Wrap items together with a span into [`Spanned`].
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///
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/// # Example
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///
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/// ```
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/// # use nu_protocol::{Span, IntoSpanned};
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/// # let span = Span::test_data();
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/// let spanned = "Hello, world!".into_spanned(span);
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/// assert_eq!("Hello, world!", spanned.item);
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/// assert_eq!(span, spanned.span);
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/// ```
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fn into_spanned(self, span: Span) -> Spanned<Self>;
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}
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impl<T> IntoSpanned for T {
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fn into_spanned(self, span: Span) -> Spanned<Self> {
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Spanned { item: self, span }
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}
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}
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/// Spans are a global offset across all seen files, which are cached in the engine's state. The start and
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/// end offset together make the inclusive start/exclusive end pair for where to underline to highlight
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/// a given point of interest.
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#[derive(Clone, Copy, Debug, PartialEq, Eq, PartialOrd, Ord, Serialize, Deserialize)]
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pub struct Span {
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pub start: usize,
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pub end: usize,
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}
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impl Span {
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pub fn new(start: usize, end: usize) -> Self {
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debug_assert!(
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end >= start,
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"Can't create a Span whose end < start, start={start}, end={end}"
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);
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Self { start, end }
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}
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pub const fn unknown() -> Self {
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Self { start: 0, end: 0 }
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}
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/// Note: Only use this for test data, *not* live data, as it will point into unknown source
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/// when used in errors.
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pub const fn test_data() -> Self {
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Self::unknown()
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}
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pub fn offset(&self, offset: usize) -> Self {
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Self::new(self.start - offset, self.end - offset)
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}
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pub fn contains(&self, pos: usize) -> bool {
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self.start <= pos && pos < self.end
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}
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pub fn contains_span(&self, span: Self) -> bool {
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self.start <= span.start && span.end <= self.end
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}
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/// Point to the space just past this span, useful for missing values
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pub fn past(&self) -> Self {
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Self {
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start: self.end,
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end: self.end,
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}
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}
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/// Returns the minimal [`Span`] that encompasses both of the given spans.
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///
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/// The two `Spans` can overlap in the middle,
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/// but must otherwise be in order by satisfying:
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/// - `self.start <= after.start`
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/// - `self.end <= after.end`
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///
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/// If this is not guaranteed to be the case, use [`Span::merge`] instead.
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pub fn append(self, after: Self) -> Self {
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debug_assert!(
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self.start <= after.start && self.end <= after.end,
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"Can't merge two Spans that are not in order"
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);
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Self {
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start: self.start,
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end: after.end,
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}
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}
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/// Returns the minimal [`Span`] that encompasses both of the given spans.
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///
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/// The spans need not be in order or have any relationship.
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///
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/// [`Span::append`] is slightly more efficient if the spans are known to be in order.
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pub fn merge(self, other: Self) -> Self {
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Self {
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start: usize::min(self.start, other.start),
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end: usize::max(self.end, other.end),
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}
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}
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/// Returns the minimal [`Span`] that encompasses all of the spans in the given slice.
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///
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/// The spans are assumed to be in order, that is, all consecutive spans must satisfy:
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/// - `spans[i].start <= spans[i + 1].start`
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/// - `spans[i].end <= spans[i + 1].end`
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///
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/// (Two consecutive spans can overlap as long as the above is true.)
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///
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/// Use [`Span::merge_many`] if the spans are not known to be in order.
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pub fn concat(spans: &[Self]) -> Self {
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// TODO: enable assert below
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// debug_assert!(!spans.is_empty());
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debug_assert!(spans.windows(2).all(|spans| {
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let &[a, b] = spans else {
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return false;
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};
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a.start <= b.start && a.end <= b.end
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}));
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Self {
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start: spans.first().map(|s| s.start).unwrap_or(0),
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end: spans.last().map(|s| s.end).unwrap_or(0),
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}
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}
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/// Returns the minimal [`Span`] that encompasses all of the spans in the given iterator.
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///
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/// The spans need not be in order or have any relationship.
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///
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/// [`Span::concat`] is more efficient if the spans are known to be in order.
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pub fn merge_many(spans: impl IntoIterator<Item = Self>) -> Self {
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spans
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.into_iter()
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.reduce(Self::merge)
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.unwrap_or(Self::unknown())
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}
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}
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impl From<Span> for SourceSpan {
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fn from(s: Span) -> Self {
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Self::new(s.start.into(), s.end - s.start)
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}
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}
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/// An extension trait for `Result`, which adds a span to the error type.
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pub trait ErrSpan {
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type Result;
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/// Add the given span to the error type `E`, turning it into a `Spanned<E>`.
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///
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/// Some auto-conversion methods to `ShellError` from other error types are available on spanned
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/// errors, to give users better information about where an error came from. For example, it is
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/// preferred when working with `std::io::Error`:
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///
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/// ```no_run
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/// use nu_protocol::{ErrSpan, ShellError, Span};
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/// use std::io::Read;
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///
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/// fn read_from(mut reader: impl Read, span: Span) -> Result<Vec<u8>, ShellError> {
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/// let mut vec = vec![];
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/// reader.read_to_end(&mut vec).err_span(span)?;
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/// Ok(vec)
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/// }
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/// ```
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fn err_span(self, span: Span) -> Self::Result;
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}
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impl<T, E> ErrSpan for Result<T, E> {
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type Result = Result<T, Spanned<E>>;
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fn err_span(self, span: Span) -> Self::Result {
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self.map_err(|err| err.into_spanned(span))
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}
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}
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