GeezerVison

I need to examine how similar error handling is done in the RustPython codebase, particularly around sorting operations that can fail.

🏁 Script executed:

#!/bin/bash
# Look for similar sorting patterns in the codebase that handle PyResult errors
rg -n -A5 -B5 "sort.*rich_compare" --type=rust

# Also look for other uses of rich_compare_bool to see how errors are typically handled
rg -n -A3 -B3 "rich_compare_bool.*unwrap\|unwrap.*rich_compare_bool" --type=rust

# Check for any existing fallible sorting utilities or patterns
rg -n -A5 -B5 "sort.*PyResult\|PyResult.*sort" --type=rust

Length of output: 192

🏁 Script executed:

#!/bin/bash
# Let's look for any existing fallible comparison patterns in the codebase
rg -n -A5 -B5 "rich_compare_bool" --type=rust

# Look for error handling patterns in comparison operations
rg -n -A3 -B3 "PyResult.*bool" --type=rust

# Check for any try_sort or fallible sorting patterns
rg -n "try_sort\|fallible.*sort\|sort.*error" --type=rust

Length of output: 73743

🏁 Script executed:

#!/bin/bash
# Let's look at the specific sort function implementation and see how other similar functions handle errors
rg -n -A10 -B5 "sort_by" vm/src/builtins/list.rs

# Look for other comparison functions that handle PyResult errors properly
rg -n -A5 -B5 "PyResult.*Ordering\|Ordering.*PyResult" --type=rust

# Check if there are any existing error-handling patterns for fallible comparisons in sorting
ast-grep --pattern 'fn $_($$_) -> PyResult<$_> {
  $$$
  sort_by($$$)
  $$$
}'

Length of output: 971

@jackoconnordev No, Rust's builtin sort_by is not a stable sorting algorithm, regardless of what the comparison function returns.

Here are the key points:

1. Inherently Unstable: Rust's sort_by uses an unstable sorting algorithm (pattern-defeating quicksort/pdqsort) by design. If you need stability, you should use sort_by_stable instead.

2. Impact of Never Returning Ordering::Equal: When your comparison function only returns Ordering::Less and Ordering::Greater, you're effectively telling the algorithm that no two elements are equal. This has several implications:

   • The sort will still be unstable
   • Elements that are actually equal (in terms of the sorting key) may not maintain their relative order
   • The algorithm cannot optimize for equal elements, potentially leading to more comparisons than necessary

3. Performance Considerations: By never returning Ordering::Equal, you're preventing the sorting algorithm from taking advantage of optimizations for equal elements, which could result in suboptimal performance.

In the context of your code, if you need stable sorting for Python's list.sort() (which should be stable according to Python's specification), you should consider:

• Using sort_by_stable instead of sort_by
• Allowing the comparison function to return Ordering::Equal when elements are truly equal

The current implementation may not match Python's expected stable sorting behavior.

🌐 Web query:

Rust sort_by algorithm stability when comparison function only returns Ordering::Less and Ordering::Greater never Ordering::Equal

💡 Result:

Short answer: sort_by is stable, but stability only matters for elements that compare equal. If your comparator never returns Ordering::Equal for any two distinct elements, then there are no “ties” to preserve — stability has no observable effect. However, your comparator still must implement a total order (in particular compare(x, x) must return Equal) or sorting may panic / produce unspecified results. (doc.rust-lang.org, rust-lang.github.io)

Details and notes

• The std::slice::sort_by API is described as a stable sort (it "preserves initial order of equal elements"). (doc.rust-lang.org)
• “Stable” means: if compare(a, b) == Equal, the element that was earlier in the slice will remain earlier after sort. If your compare never returns Equal for any pair that you care about, there is nothing for the stability guarantee to preserve. (rust-lang.github.io)
• Important correctness constraint: the comparator must implement a total order (transitive, antisymmetric/reflexive). In particular compare(x, x) is expected to return Equal. If the comparator violates this (for example returns Less or Greater when called with the same element), the sort may panic or produce unspecified results. (doc.rust-lang.org)
• If you only want to ensure a deterministic tie-break (preserve original order for “equal” keys) and you use an unstable sort, a common pattern is to pair values with their original index (or use sort_by and then .then_with/then for tie-breakers).

Example patterns

• Stable sort keeping original order for equal keys:
  • v.sort_by_key(|k| k.some_key); // stable
• If you use unstable sort but want stability you can tag with index:
  • let mut v: Vec<(K, usize)> = v.into_iter().map(|x| (x, idx)).collect();
  • v.sort_unstable_by_key(|(k, idx)| (k.clone(), *idx));

If you want, paste the comparator you’re using and I’ll check whether it properly implements a total order and whether you need to worry about stability or correctness.

Citations:

• 1: https://doc.rust-lang.org/std/primitive.slice.html?utm_source=chatgpt.com
• 2: https://rust-lang.github.io/rfcs/1884-unstable-sort.html?utm_source=chatgpt.com
• 3: https://doc.rust-lang.org/std/primitive.slice.html?utm_source=chatgpt.com
• 4: https://rust-lang.github.io/rfcs/1884-unstable-sort.html?utm_source=chatgpt.com
• 5: https://doc.rust-lang.org/std/primitive.slice.html?utm_source=chatgpt.com

🌐 Web query:

Rust std::slice::sort_by algorithm pdqsort stable unstable behavior documentation

💡 Result:

Short answer

• slice::sort_by is a stable sort (preserves order of equal elements). Its current implementation is a stable algorithm (driftsort variant) and it may allocate auxiliary memory. (doc.rust-lang.org)
• slice::sort_unstable_by (and the other sort_unstable APIs) are unstable (may reorder equal elements), in‑place (no allocation), and implemented using pattern‑defeating quicksort (pdqsort). It has O(n log n) worst case, fast practical performance, and uses a fixed/randomization strategy for degeneracy cases (deterministic seed). (doc.rust-lang.org, docs.rs, rust.docs.kernel.org)

Details and practical notes

• Stability: sort_by / sort / sort_by_key are the stable family — they preserve the relative order of elements that compare equal. Use these when you rely on stability (e.g., multi‑key sorts performed as repeated stable sorts). (doc.rust-lang.org)
• Unstable sorts: sort_unstable / sort_unstable_by / sort_unstable_by_key are the in‑place, unstable family. They are typically faster and use no extra allocation — good for large primitive data or when you don't need stability. (doc.rust-lang.org, rust.docs.kernel.org)
• Algorithms:
  • sort_unstable_by uses pattern‑defeating quicksort (pdqsort) by Orson Peters — a tuned quicksort variant that falls back to worst‑case safe behavior and is optimized for many real‑world patterns. (docs.rs)
  • sort_by (stable) is currently based on a stable algorithm often referenced as driftsort (a mergesort/partial‑run detection + quicksort style hybrid) tuned for stability and certain input patterns. It typically allocates auxiliary memory. (doc.rust-lang.org)
• Complexity and behavior: both APIs offer O(n log n) worst‑case guarantees. pdqsort gives O(n) best case on some inputs and is much faster in many benchmarks; stable sort optimizes comparisons and can be faster on partially sorted data or when comparisons are expensive. (docs.rs, doc.rust-lang.org)
• Panics / ordering requirements: both require the comparator (or key's Ord) to implement a total order; otherwise they may panic or produce unspecified ordering. (doc.rust-lang.org)
• Allocation / no_std: stable sort (slice::sort / sort_by) allocates (so it requires the global allocator / is gated by cfg on OOM handling). sort_unstable is in‑place and works in no_std contexts. (doc.rust-lang.org, docs.rs)

If you want

• Exact doc links or the relevant lines in the Rust source (core/alloc slice implementations) — I can paste the official docs/source snippets.
• Benchmarks comparing pdqsort vs stable sort on particular data types or workloads, or small example code showing when equal elements get reordered (to illustrate stability vs instability). Which would you prefer?

Citations:

• 1: https://doc.rust-lang.org/stable/src/alloc/slice.rs.html?utm_source=chatgpt.com
• 2: https://doc.rust-lang.org/std/primitive.slice.html?utm_source=chatgpt.com
• 3: https://docs.rs/pdqsort/latest/pdqsort/fn.sort_by.html?utm_source=chatgpt.com
• 4: https://rust.docs.kernel.org/6.12/src/core/slice/mod.rs.html?utm_source=chatgpt.com
• 5: https://doc.rust-lang.org/stable/src/alloc/slice.rs.html?utm_source=chatgpt.com
• 6: https://doc.rust-lang.org/std/primitive.slice.html?utm_source=chatgpt.com
• 7: https://rust.docs.kernel.org/6.12/src/core/slice/mod.rs.html?utm_source=chatgpt.com
• 8: https://docs.rs/pdqsort/latest/pdqsort/fn.sort_by.html?utm_source=chatgpt.com
• 9: https://doc.rust-lang.org/stable/src/alloc/slice.rs.html?utm_source=chatgpt.com
• 10: https://docs.rs/crate/pdqsort/latest?utm_source=chatgpt.com
• 11: https://doc.rust-lang.org/stable/src/alloc/slice.rs.html?utm_source=chatgpt.com
• 12: https://doc.rust-lang.org/stable/src/alloc/slice.rs.html?utm_source=chatgpt.com
• 13: https://doc.rust-lang.org/stable/src/alloc/slice.rs.html?utm_source=chatgpt.com
• 14: https://docs.rs/crate/pdqsort/latest?utm_source=chatgpt.com

🏁 Script executed:

#!/bin/bash
# Search for the definition of rich_compare_bool to understand its semantics
rg -n "rich_compare_bool" --type=rust -A 5 -B 5

Length of output: 12093

• File: vm/src/builtins/list.rs

  • Snippet 1: do_sort function (uses rich_compare_bool to implement sorting comparator)

  • Content:
    fn do_sort(
    vm: &VirtualMachine,
    values: &mut Vec,
    key_func: Option,
    reverse: bool,
    ) -> PyResult<()> {
    let op = if reverse {
    PyComparisonOp::Lt
    } else {
    PyComparisonOp::Gt
    };
    let cmp = |a: &PyObjectRef, b: &PyObjectRef| {
    let res = a.rich_compare_bool(b, op, vm).unwrap();
    if res {
    Ordering::Greater
    } else {
    Ordering::Less
    }
    };

    if let Some(ref key_func) = key_func {
        let mut items = values
            .iter()
            .map(|x| Ok((x.clone(), key_func.call((x.clone(),), vm)?)))
            .collect::<Result<Vec<_>, _>>()?;
        // timsort::try_sort_by_gt(&mut items, |a, b| cmp(&a.1, &b.1))?;
        items.sort_by(|a, b| cmp(&a.1, &b.1));
        *values = items.into_iter().map(|(val, _)| val).collect();
    } else {
        // timsort::try_sort_by_gt(values, cmp)?;
        values.sort_by(|a, b| cmp(a, b));
    }
    
    Ok(())
    

    }

  • Snippet 2: PyList cmp implementation (uses rich comparison across elements)

  • Content:
    impl Comparable for PyList {
    fn cmp(
    zelf: &Py,
    other: &PyObject,
    op: PyComparisonOp,
    vm: &VirtualMachine,
    ) -> PyResult {
    if let Some(res) = op.identical_optimization(zelf, other) {
    return Ok(res.into());
    }
    let other = class_or_notimplemented!(Self, other);
    let a = &*zelf.borrow_vec();
    let b = &*other.borrow_vec();
    a.iter()
    .richcompare(b.iter(), op, vm)
    .map(PyComparisonValue::Implemented)
    }
    }