1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
|
// Copyright (c) 2017-2025, University of Cincinnati, developed by Henry Schreiner
// under NSF AWARD 1414736 and by the respective contributors.
// All rights reserved.
//
// SPDX-License-Identifier: BSD-3-Clause
// Code inspired by discussion from https://github.com/CLIUtils/CLI11/issues/1149
#include <algorithm>
#include <iostream>
#include <numeric>
#include <string>
#include <utility>
#include <vector>
#include <CLI/CLI.hpp>
// only works with C++14 or higher
// Levenshtein distance function code generated by chatgpt/copilot
std::size_t levenshteinDistance(const std::string &s1, const std::string &s2) {
std::size_t len1 = s1.size(), len2 = s2.size();
if(len1 == 0 || len2 == 0) {
return (std::max)(len1, len2);
}
std::vector<std::size_t> prev(len2 + 1), curr(len2 + 1);
std::iota(prev.begin(), prev.end(), 0); // Fill prev with {0, 1, ..., len2}
for(std::size_t ii = 1; ii <= len1; ++ii) {
curr[0] = ii;
for(std::size_t jj = 1; jj <= len2; ++jj) {
// If characters match, no substitution cost; otherwise, cost is 1.
std::size_t cost = (s1[ii - 1] == s2[jj - 1]) ? 0 : 1;
// Compute the minimum cost between:
// - Deleting a character from `s1` (prev[jj] + 1)
// - Inserting a character into `s1` (curr[jj - 1] + 1)
// - Substituting a character (prev[jj - 1] + cost)
curr[jj] = (std::min)({prev[jj] + 1, curr[jj - 1] + 1, prev[jj - 1] + cost});
}
prev = std::exchange(curr, prev); // Swap vectors efficiently
}
return prev[len2];
}
// Finds the closest string from a list (modified from chat gpt code)
std::pair<std::string, std::size_t> findClosestMatch(const std::string &input,
const std::vector<std::string> &candidates) {
std::string closest;
std::size_t minDistance{std::string::npos};
for(const auto &candidate : candidates) {
std::size_t distance = levenshteinDistance(input, candidate);
if(distance < minDistance) {
minDistance = distance;
closest = candidate;
}
}
return {closest, minDistance};
}
void addSubcommandCloseMatchDetection(CLI::App *app, std::size_t minDistance = 3) {
// if extras are not allowed then there will be no remaining
app->allow_extras(true);
// generate a list of subcommand names
auto subs = app->get_subcommands(nullptr);
CLI::results_t list;
for(const auto *sub : subs) {
if(!sub->get_name().empty()) {
list.emplace_back(sub->get_name());
}
const auto &aliases = sub->get_aliases();
if(!aliases.empty()) {
list.insert(list.end(), aliases.begin(), aliases.end());
}
}
// add a callback that runs before a final callback and loops over the remaining arguments for subcommands
app->parse_complete_callback([app, minDistance, list = std::move(list)]() {
for(auto &extra : app->remaining()) {
if(!extra.empty() && extra.front() != '-') {
auto closest = findClosestMatch(extra, list);
if(closest.second <= minDistance) {
std::cout << "unmatched command \"" << extra << "\", closest match is " << closest.first << "\n";
}
}
}
});
}
/** This example demonstrates the use of close match detection to detect invalid commands that are close matches to
* existing ones
*/
int main(int argc, const char *argv[]) {
int value{0};
CLI::App app{"App for testing prefix matching and close string matching"};
// turn on prefix matching
app.allow_subcommand_prefix_matching();
app.add_option("-v", value, "value");
app.add_subcommand("install", "");
app.add_subcommand("upgrade", "");
app.add_subcommand("remove", "");
app.add_subcommand("test", "");
// enable close matching for subcommands
addSubcommandCloseMatchDetection(&app, 5);
CLI11_PARSE(app, argc, argv);
auto subs = app.get_subcommands();
for(const auto &sub : subs) {
std::cout << sub->get_name() << "\n";
}
return 0;
}
|
