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1 | 1 | //! Pick command
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2 | 2 | use super::Command;
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| 3 | +use crate::cache::models::Problem; |
3 | 4 | use crate::err::Error;
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4 | 5 | use async_trait::async_trait;
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5 | 6 | use clap::{Arg, ArgAction, ArgMatches, Command as ClapCommand};
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@@ -136,12 +137,12 @@ impl Command for PickCommand {
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136 | 137 | };
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137 | 138 |
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138 | 139 | let fid = match m.contains_id("name") {
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139 |
| - //check for name specified |
| 140 | + // check for name specified, or closest name |
140 | 141 | true => {
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141 | 142 | match m.get_one::<String>("name").map(|name| name) {
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142 |
| - Some(quesname) => match cache.get_problem_id_from_name(quesname) { |
143 |
| - Ok(p) => p, |
144 |
| - Err(_) => 1, |
| 143 | + Some(quesname) => match closest_named_problem(&problems, quesname) { |
| 144 | + Some(p) => p, |
| 145 | + None => 1, |
145 | 146 | },
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146 | 147 | None => {
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147 | 148 | // Pick random without specify id
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@@ -177,3 +178,69 @@ impl Command for PickCommand {
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177 | 178 | Ok(())
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178 | 179 | }
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179 | 180 | }
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| 181 | + |
| 182 | +// Returns the closest problem according to a scoring algorithm |
| 183 | +// taking into account both the longest common subsequence and the size |
| 184 | +// problem string (to compensate for smaller strings having smaller lcs). |
| 185 | +// Returns None if there are no problems in the problem list |
| 186 | +fn closest_named_problem(problems: &Vec<Problem>, lookup_name: &str) -> Option<i32> { |
| 187 | + let max_name_size: usize = problems.iter().map(|p| p.name.len()).max()?; |
| 188 | + // Init table to the max name length of all the problems to share |
| 189 | + // the same table allocation |
| 190 | + let mut table: Vec<usize> = vec![0; (max_name_size + 1) * (lookup_name.len() + 1)]; |
| 191 | + |
| 192 | + // this is guaranteed because of the earlier max None propegation |
| 193 | + assert!(problems.len() > 0); |
| 194 | + let mut max_score = 0; |
| 195 | + let mut current_problem = &problems[0]; |
| 196 | + for problem in problems { |
| 197 | + // In case bug becomes bugged, always return the matching string |
| 198 | + if problem.name == lookup_name { |
| 199 | + return Some(problem.fid); |
| 200 | + } |
| 201 | + |
| 202 | + let this_lcs = longest_common_subsequence(&mut table, &problem.name, lookup_name); |
| 203 | + let this_score = this_lcs * (max_name_size - problem.name.len()); |
| 204 | + |
| 205 | + if this_score > max_score { |
| 206 | + max_score = this_score; |
| 207 | + current_problem = &problem; |
| 208 | + } |
| 209 | + } |
| 210 | + |
| 211 | + Some(current_problem.fid) |
| 212 | +} |
| 213 | + |
| 214 | +// Longest commong subsequence DP approach O(nm) space and time. Table must be at least |
| 215 | +// (text1.len() + 1) * (text2.len() + 1) length or greater and is mutated every call |
| 216 | +fn longest_common_subsequence(table: &mut Vec<usize>, text1: &str, text2: &str) -> usize { |
| 217 | + assert!(table.len() >= (text1.len() + 1) * (text2.len() + 1)); |
| 218 | + let height: usize = text1.len() + 1; |
| 219 | + let width: usize = text2.len() + 1; |
| 220 | + |
| 221 | + // initialize base cases to 0 |
| 222 | + for i in 0..height { |
| 223 | + table[i * width + (width - 1)] = 0; |
| 224 | + } |
| 225 | + for j in 0..width { |
| 226 | + table[((height - 1) * width) + j] = 0; |
| 227 | + } |
| 228 | + |
| 229 | + let mut i: usize = height - 1; |
| 230 | + let mut j: usize; |
| 231 | + for c0 in text1.chars().rev() { |
| 232 | + i -= 1; |
| 233 | + j = width - 1; |
| 234 | + for c1 in text2.chars().rev() { |
| 235 | + j -= 1; |
| 236 | + if c0.to_lowercase().next() == c1.to_lowercase().next() { |
| 237 | + table[i * width + j] = 1 + table[(i + 1) * width + j + 1]; |
| 238 | + } else { |
| 239 | + let a = table[(i + 1) * width + j]; |
| 240 | + let b = table[i * width + j + 1]; |
| 241 | + table[i * width + j] = std::cmp::max(a, b); |
| 242 | + } |
| 243 | + } |
| 244 | + } |
| 245 | + table[0] |
| 246 | +} |
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