Modify the Levenshtein-based suggestions to include imports
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@@ -24,7 +24,7 @@ use parse::token;
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use parse::token::{InternedString, intern, str_to_ident};
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use ptr::P;
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use util::small_vector::SmallVector;
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use util::lev_distance::{lev_distance, max_suggestion_distance};
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use util::lev_distance::find_best_match_for_name;
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use ext::mtwt;
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use fold::Folder;
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@@ -780,15 +780,8 @@ impl<'a> ExtCtxt<'a> {
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}
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pub fn suggest_macro_name(&mut self, name: &str, span: Span) {
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let mut min: Option<(Name, usize)> = None;
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let max_dist = max_suggestion_distance(name);
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for macro_name in self.syntax_env.names.iter() {
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let dist = lev_distance(name, ¯o_name.as_str());
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if dist <= max_dist && (min.is_none() || min.unwrap().1 > dist) {
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min = Some((*macro_name, dist));
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}
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}
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if let Some((suggestion, _)) = min {
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let names = &self.syntax_env.names;
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if let Some(suggestion) = find_best_match_for_name(names.iter(), name, None) {
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self.fileline_help(span, &format!("did you mean `{}!`?", suggestion));
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}
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}
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@@ -8,50 +8,64 @@
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// option. This file may not be copied, modified, or distributed
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// except according to those terms.
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use ast::Name;
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use std::cmp;
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use parse::token::InternedString;
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pub fn lev_distance(me: &str, t: &str) -> usize {
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if me.is_empty() { return t.chars().count(); }
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if t.is_empty() { return me.chars().count(); }
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/// To find the Levenshtein distance between two strings
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pub fn lev_distance(a: &str, b: &str) -> usize {
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// cases which don't require further computation
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if a.is_empty() {
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return b.chars().count();
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} else if b.is_empty() {
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return a.chars().count();
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}
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let mut dcol: Vec<_> = (0..t.len() + 1).collect();
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let mut dcol: Vec<_> = (0..b.len() + 1).collect();
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let mut t_last = 0;
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for (i, sc) in me.chars().enumerate() {
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for (i, sc) in a.chars().enumerate() {
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let mut current = i;
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dcol[0] = current + 1;
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for (j, tc) in t.chars().enumerate() {
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for (j, tc) in b.chars().enumerate() {
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let next = dcol[j + 1];
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if sc == tc {
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dcol[j + 1] = current;
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} else {
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dcol[j + 1] = cmp::min(current, next);
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dcol[j + 1] = cmp::min(dcol[j + 1], dcol[j]) + 1;
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}
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current = next;
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t_last = j;
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}
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}
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dcol[t_last + 1]
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} dcol[t_last + 1]
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}
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pub fn max_suggestion_distance(name: &str) -> usize {
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use std::cmp::max;
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// As a loose rule to avoid obviously incorrect suggestions, clamp the
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// maximum edit distance we will accept for a suggestion to one third of
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// the typo'd name's length.
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max(name.len(), 3) / 3
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/// To find the best match for a given string from an iterator of names
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/// As a loose rule to avoid the obviously incorrect suggestions, it takes
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/// an optional limit for the maximum allowable edit distance, which defaults
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/// to one-third of the given word
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pub fn find_best_match_for_name<'a, T>(iter_names: T,
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lookup: &str,
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dist: Option<usize>) -> Option<InternedString>
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where T: Iterator<Item = &'a Name> {
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let max_dist = dist.map_or_else(|| cmp::max(lookup.len(), 3) / 3, |d| d);
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iter_names
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.filter_map(|name| {
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let dist = lev_distance(lookup, &name.as_str());
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match dist <= max_dist { // filter the unwanted cases
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true => Some((name.as_str(), dist)),
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false => None,
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}
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})
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.min_by_key(|&(_, val)| val) // extract the tuple containing the minimum edit distance
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.map(|(s, _)| s) // and return only the string
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}
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#[test]
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fn test_lev_distance() {
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use std::char::{ from_u32, MAX };
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use std::char::{from_u32, MAX};
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// Test bytelength agnosticity
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for c in (0..MAX as u32)
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.filter_map(|i| from_u32(i))
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