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https://github.com/nushell/nushell.git
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2ae9ad8676
# Description This adds a `SharedCow` type as a transparent copy-on-write pointer that clones to unique on mutate. As an initial test, the `Record` within `Value::Record` is shared. There are some pretty big wins for performance. I'll post benchmark results in a comment. The biggest winner is nested access, as that would have cloned the records for each cell path follow before and it doesn't have to anymore. The reusability of the `SharedCow` type is nice and I think it could be used to clean up the previous work I did with `Arc` in `EngineState`. It's meant to be a mostly transparent clone-on-write that just clones on `.to_mut()` or `.into_owned()` if there are actually multiple references, but avoids cloning if the reference is unique. # User-Facing Changes - `Value::Record` field is a different type (plugin authors) # Tests + Formatting - 🟢 `toolkit fmt` - 🟢 `toolkit clippy` - 🟢 `toolkit test` - 🟢 `toolkit test stdlib` # After Submitting - [ ] use for `EngineState` - [ ] use for `Value::List`
362 lines
13 KiB
Rust
362 lines
13 KiB
Rust
use crate::completions::{
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Completer, CompletionOptions, MatchAlgorithm, SemanticSuggestion, SuggestionKind,
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};
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use nu_engine::{column::get_columns, eval_variable};
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use nu_protocol::{
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engine::{EngineState, Stack, StateWorkingSet},
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Span, Value,
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};
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use reedline::Suggestion;
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use std::{str, sync::Arc};
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#[derive(Clone)]
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pub struct VariableCompletion {
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engine_state: Arc<EngineState>, // TODO: Is engine state necessary? It's already a part of working set in fetch()
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stack: Stack,
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var_context: (Vec<u8>, Vec<Vec<u8>>), // tuple with $var and the sublevels (.b.c.d)
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}
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impl VariableCompletion {
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pub fn new(
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engine_state: Arc<EngineState>,
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stack: Stack,
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var_context: (Vec<u8>, Vec<Vec<u8>>),
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) -> Self {
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Self {
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engine_state,
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stack,
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var_context,
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}
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}
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}
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impl Completer for VariableCompletion {
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fn fetch(
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&mut self,
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working_set: &StateWorkingSet,
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prefix: Vec<u8>,
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span: Span,
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offset: usize,
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_: usize,
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options: &CompletionOptions,
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) -> Vec<SemanticSuggestion> {
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let mut output = vec![];
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let builtins = ["$nu", "$in", "$env"];
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let var_str = std::str::from_utf8(&self.var_context.0).unwrap_or("");
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let var_id = working_set.find_variable(&self.var_context.0);
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let current_span = reedline::Span {
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start: span.start - offset,
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end: span.end - offset,
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};
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let sublevels_count = self.var_context.1.len();
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// Completions for the given variable
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if !var_str.is_empty() {
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// Completion for $env.<tab>
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if var_str == "$env" {
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let env_vars = self.stack.get_env_vars(&self.engine_state);
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// Return nested values
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if sublevels_count > 0 {
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// Extract the target var ($env.<target-var>)
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let target_var = self.var_context.1[0].clone();
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let target_var_str =
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str::from_utf8(&target_var).unwrap_or_default().to_string();
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// Everything after the target var is the nested level ($env.<target-var>.<nested_levels>...)
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let nested_levels: Vec<Vec<u8>> =
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self.var_context.1.clone().into_iter().skip(1).collect();
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if let Some(val) = env_vars.get(&target_var_str) {
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for suggestion in nested_suggestions(val, &nested_levels, current_span) {
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if options.match_algorithm.matches_u8_insensitive(
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options.case_sensitive,
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suggestion.suggestion.value.as_bytes(),
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&prefix,
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) {
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output.push(suggestion);
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}
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}
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return output;
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}
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} else {
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// No nesting provided, return all env vars
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for env_var in env_vars {
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if options.match_algorithm.matches_u8_insensitive(
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options.case_sensitive,
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env_var.0.as_bytes(),
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&prefix,
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) {
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output.push(SemanticSuggestion {
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suggestion: Suggestion {
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value: env_var.0,
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description: None,
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style: None,
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extra: None,
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span: current_span,
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append_whitespace: false,
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},
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kind: Some(SuggestionKind::Type(env_var.1.get_type())),
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});
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}
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}
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return output;
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}
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}
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// Completions for $nu.<tab>
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if var_str == "$nu" {
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// Eval nu var
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if let Ok(nuval) = eval_variable(
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&self.engine_state,
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&self.stack,
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nu_protocol::NU_VARIABLE_ID,
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nu_protocol::Span::new(current_span.start, current_span.end),
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) {
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for suggestion in nested_suggestions(&nuval, &self.var_context.1, current_span)
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{
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if options.match_algorithm.matches_u8_insensitive(
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options.case_sensitive,
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suggestion.suggestion.value.as_bytes(),
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&prefix,
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) {
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output.push(suggestion);
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}
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}
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return output;
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}
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}
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// Completion other variable types
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if let Some(var_id) = var_id {
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// Extract the variable value from the stack
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let var = self.stack.get_var(var_id, Span::new(span.start, span.end));
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// If the value exists and it's of type Record
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if let Ok(value) = var {
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for suggestion in nested_suggestions(&value, &self.var_context.1, current_span)
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{
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if options.match_algorithm.matches_u8_insensitive(
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options.case_sensitive,
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suggestion.suggestion.value.as_bytes(),
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&prefix,
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) {
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output.push(suggestion);
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}
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}
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return output;
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}
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}
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}
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// Variable completion (e.g: $en<tab> to complete $env)
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for builtin in builtins {
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if options.match_algorithm.matches_u8_insensitive(
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options.case_sensitive,
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builtin.as_bytes(),
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&prefix,
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) {
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output.push(SemanticSuggestion {
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suggestion: Suggestion {
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value: builtin.to_string(),
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description: None,
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style: None,
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extra: None,
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span: current_span,
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append_whitespace: false,
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},
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// TODO is there a way to get the VarId to get the type???
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kind: None,
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});
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}
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}
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// TODO: The following can be refactored (see find_commands_by_predicate() used in
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// command_completions).
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let mut removed_overlays = vec![];
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// Working set scope vars
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for scope_frame in working_set.delta.scope.iter().rev() {
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for overlay_frame in scope_frame.active_overlays(&mut removed_overlays).rev() {
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for v in &overlay_frame.vars {
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if options.match_algorithm.matches_u8_insensitive(
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options.case_sensitive,
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v.0,
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&prefix,
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) {
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output.push(SemanticSuggestion {
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suggestion: Suggestion {
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value: String::from_utf8_lossy(v.0).to_string(),
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description: None,
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style: None,
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extra: None,
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span: current_span,
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append_whitespace: false,
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},
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kind: Some(SuggestionKind::Type(
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working_set.get_variable(*v.1).ty.clone(),
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)),
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});
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}
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}
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}
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}
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// Permanent state vars
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// for scope in &self.engine_state.scope {
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for overlay_frame in self.engine_state.active_overlays(&removed_overlays).rev() {
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for v in &overlay_frame.vars {
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if options.match_algorithm.matches_u8_insensitive(
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options.case_sensitive,
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v.0,
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&prefix,
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) {
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output.push(SemanticSuggestion {
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suggestion: Suggestion {
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value: String::from_utf8_lossy(v.0).to_string(),
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description: None,
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style: None,
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extra: None,
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span: current_span,
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append_whitespace: false,
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},
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kind: Some(SuggestionKind::Type(
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working_set.get_variable(*v.1).ty.clone(),
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)),
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});
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}
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}
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}
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output.dedup(); // TODO: Removes only consecutive duplicates, is it intended?
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output
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}
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}
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// Find recursively the values for sublevels
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// if no sublevels are set it returns the current value
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fn nested_suggestions(
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val: &Value,
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sublevels: &[Vec<u8>],
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current_span: reedline::Span,
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) -> Vec<SemanticSuggestion> {
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let mut output: Vec<SemanticSuggestion> = vec![];
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let value = recursive_value(val, sublevels).unwrap_or_else(Value::nothing);
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let kind = SuggestionKind::Type(value.get_type());
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match value {
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Value::Record { val, .. } => {
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// Add all the columns as completion
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for col in val.columns() {
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output.push(SemanticSuggestion {
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suggestion: Suggestion {
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value: col.clone(),
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description: None,
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style: None,
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extra: None,
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span: current_span,
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append_whitespace: false,
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},
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kind: Some(kind.clone()),
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});
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}
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output
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}
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Value::LazyRecord { val, .. } => {
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// Add all the columns as completion
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for column_name in val.column_names() {
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output.push(SemanticSuggestion {
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suggestion: Suggestion {
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value: column_name.to_string(),
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description: None,
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style: None,
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extra: None,
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span: current_span,
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append_whitespace: false,
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},
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kind: Some(kind.clone()),
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});
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}
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output
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}
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Value::List { vals, .. } => {
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for column_name in get_columns(vals.as_slice()) {
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output.push(SemanticSuggestion {
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suggestion: Suggestion {
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value: column_name,
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description: None,
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style: None,
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extra: None,
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span: current_span,
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append_whitespace: false,
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},
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kind: Some(kind.clone()),
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});
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}
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output
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}
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_ => output,
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}
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}
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// Extracts the recursive value (e.g: $var.a.b.c)
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fn recursive_value(val: &Value, sublevels: &[Vec<u8>]) -> Result<Value, Span> {
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// Go to next sublevel
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if let Some((sublevel, next_sublevels)) = sublevels.split_first() {
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let span = val.span();
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match val {
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Value::Record { val, .. } => {
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if let Some((_, value)) = val.iter().find(|(key, _)| key.as_bytes() == sublevel) {
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// If matches try to fetch recursively the next
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recursive_value(value, next_sublevels)
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} else {
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// Current sublevel value not found
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Err(span)
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}
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}
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Value::LazyRecord { val, .. } => {
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for col in val.column_names() {
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if col.as_bytes() == *sublevel {
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let val = val.get_column_value(col).map_err(|_| span)?;
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return recursive_value(&val, next_sublevels);
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}
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}
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// Current sublevel value not found
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Err(span)
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}
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Value::List { vals, .. } => {
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for col in get_columns(vals.as_slice()) {
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if col.as_bytes() == *sublevel {
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let val = val.get_data_by_key(&col).ok_or(span)?;
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return recursive_value(&val, next_sublevels);
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}
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}
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// Current sublevel value not found
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Err(span)
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}
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_ => Ok(val.clone()),
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}
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} else {
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Ok(val.clone())
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}
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}
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impl MatchAlgorithm {
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pub fn matches_u8_insensitive(&self, sensitive: bool, haystack: &[u8], needle: &[u8]) -> bool {
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if sensitive {
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self.matches_u8(haystack, needle)
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} else {
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self.matches_u8(&haystack.to_ascii_lowercase(), &needle.to_ascii_lowercase())
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}
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}
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}
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