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| use chardetng::EncodingDetector; | |
| use charset_normalizer_rs::consts::CHARDET_CORRESPONDENCE; | |
| use charset_normalizer_rs::entity::{PerformanceArgs, PerformanceResult}; | |
| use charset_normalizer_rs::from_bytes; | |
| use charset_normalizer_rs::utils::get_large_test_datasets; | |
| use clap::Parser; | |
| use encoding::label::encoding_from_whatwg_label; | |
| use encoding::DecoderTrap; | |
| use log::trace; | |
| use std::collections::{BTreeMap, HashMap}; | |
| use std::fs::File; | |
| use std::io::Read; | |
| use std::process; | |
| use std::time::{Duration, Instant}; | |
| // Check result | |
| fn check_result( | |
| correct_encodings: &Vec<String>, | |
| guessed_encoding: &String, | |
| buffer: &Vec<u8>, | |
| ) -> bool { | |
| // check by encoding name | |
| if correct_encodings.iter().any(|e| guessed_encoding == e) { | |
| return true; | |
| } | |
| // if correct encoding wasn't found we will try to decode and compare results | |
| let whatwg_correct_encoding = correct_encodings | |
| .first() | |
| .and_then(|enc| encoding_from_whatwg_label(enc)); | |
| let whatwg_guessed_encoding = encoding_from_whatwg_label(guessed_encoding); | |
| match (whatwg_correct_encoding, whatwg_guessed_encoding) { | |
| (Some(correct_encoding), Some(guessed_encoding)) => { | |
| let correct_decoded = correct_encoding.decode(buffer.as_slice(), DecoderTrap::Strict); | |
| let guessed_decoded = guessed_encoding.decode(buffer.as_slice(), DecoderTrap::Strict); | |
| match (correct_decoded, guessed_decoded) { | |
| (Ok(correct_result), Ok(guessed_result)) => correct_result == guessed_result, | |
| _ => false, | |
| } | |
| } | |
| _ => false, | |
| } | |
| } | |
| // Calculate percentile | |
| fn calc_percentile(results: &Vec<PerformanceResult>, percentile: f64) -> Duration { | |
| let mut sorted_data: Vec<Duration> = results.iter().map(|r| r.duration).collect(); | |
| sorted_data.sort_unstable(); | |
| let index = ((percentile / 100.0) * sorted_data.len() as f64) as usize; | |
| sorted_data[index] | |
| } | |
| // Calculate mean duration | |
| fn calc_stat(results: &Vec<PerformanceResult>) -> (Duration, Duration, f32) { | |
| let durations: Vec<Duration> = results.iter().map(|r| r.duration).collect(); | |
| if durations.is_empty() { | |
| // Handle the case where the input vector is empty (avoid division by zero) | |
| (Duration::new(0, 0), Duration::new(0, 0), 0.0) | |
| } else { | |
| // Calculate the total duration by summing all the durations in the vector | |
| let total_duration: Duration = durations.iter().sum(); | |
| // Divide the total duration by the number of durations to get the mean | |
| let num_durations = durations.len() as u32; | |
| // Accuracy | |
| let accuracy = | |
| 100.0 * results.iter().filter(|r| r.correct).count() as f32 / num_durations as f32; | |
| (total_duration, total_duration / num_durations, accuracy) | |
| } | |
| } | |
| // Performance comparison | |
| fn performance_compare(args: &PerformanceArgs) -> i32 { | |
| // read datasets from /src/tests/data/largesets | |
| let datasets = get_large_test_datasets(); | |
| if datasets.is_err() { | |
| println!("{}", datasets.unwrap_err()); | |
| process::exit(1); | |
| } | |
| let datasets = datasets.unwrap(); | |
| let nof_files = datasets.len(); | |
| println!("Found {} datasets for performance tests", nof_files); | |
| // tested functions | |
| let mut performance_results: HashMap<&str, Vec<PerformanceResult>> = HashMap::new(); | |
| // we need BTreeMap as we need preserve keys order | |
| let mut tested_functions: BTreeMap<&str, Box<dyn Fn(&Vec<u8>) -> String>> = BTreeMap::new(); | |
| ///////////////////////////////////////////////////////////////// | |
| // Tested functions (libraries) | |
| ///////////////////////////////////////////////////////////////// | |
| // charset-normalizer-rs | |
| tested_functions.insert( | |
| "A) charset-normalizer-rs", | |
| Box::new(|bytes: &Vec<u8>| { | |
| if let Some(gb) = from_bytes(bytes, None).get_best() { | |
| gb.encoding().to_string() | |
| } else { | |
| String::from("None") | |
| } | |
| }), | |
| ); | |
| // chardet | |
| tested_functions.insert( | |
| "B) chardet", | |
| Box::new(|bytes: &Vec<u8>| { | |
| let detected = &chardet::detect(bytes).0.to_ascii_lowercase(); | |
| let alternative = CHARDET_CORRESPONDENCE.get(&detected.as_str()); | |
| if let Some(r) = encoding_from_whatwg_label(&detected) { | |
| r.whatwg_name() | |
| .unwrap_or(alternative.unwrap_or(&r.name())) | |
| .to_string() | |
| } else { | |
| String::from("None") | |
| } | |
| }), | |
| ); | |
| // chardetng | |
| tested_functions.insert( | |
| "C) chardetng", | |
| Box::new(|bytes: &Vec<u8>| { | |
| let mut ed = EncodingDetector::new(); | |
| ed.feed(bytes, true); | |
| let found = ed.guess(None, true).name(); | |
| found.to_ascii_lowercase().to_string() | |
| }), | |
| ); | |
| // start tests | |
| for (filename, correct_encodings) in &datasets { | |
| println!("{}", filename); | |
| // read file contents to buffer | |
| let mut file = File::open(filename).expect(&format!("Error opening file {}", filename)); | |
| let mut buffer = Vec::new(); | |
| file.read_to_end(&mut buffer) | |
| .expect(&format!("Error reading from file {}", filename)); | |
| // multiply buffer | |
| buffer = buffer.repeat(args.size_increase as usize); | |
| // traverse tested functions | |
| for (&name, &ref foo) in &tested_functions { | |
| if !performance_results.contains_key(name) { | |
| performance_results.insert(name, vec![]); | |
| } | |
| let duration = Instant::now(); | |
| let guessed_encoding = foo(&buffer); | |
| let duration = duration.elapsed(); | |
| // save result | |
| performance_results | |
| .get_mut(name) | |
| .unwrap() | |
| .push(PerformanceResult { | |
| duration, | |
| correct: check_result(correct_encodings, &guessed_encoding, &buffer), | |
| }); | |
| println!(" --> {}: {:?}", name, duration,); | |
| if !correct_encodings.contains(&guessed_encoding.to_string()) { | |
| trace!( | |
| "{} WRONG DETECTION: {} not in {:?}\nSee {}", | |
| name, | |
| guessed_encoding, | |
| correct_encodings, | |
| filename, | |
| ); | |
| } | |
| } | |
| } | |
| // Statistics | |
| let mut our_accuracy = 0.0; | |
| let mut our_total_time: Duration = Duration::new(0, 0); | |
| for (&name, _) in &tested_functions { | |
| if let Some(results) = performance_results.get(name) { | |
| let (total_duration, mean_duration, accuracy) = calc_stat(results); | |
| println!("\n------------------------------"); | |
| println!("--> {} Conclusions", name); | |
| if name == "A) charset-normalizer-rs" { | |
| our_accuracy = accuracy; | |
| our_total_time = total_duration.clone(); | |
| } else { | |
| // compare speed in % | |
| println!( | |
| " --> Faster than charset-normalizer-rs by {:.1} times", | |
| our_total_time.as_secs_f32() / total_duration.as_secs_f32(), | |
| ); | |
| } | |
| println!(" --> Accuracy: {:.1}%", accuracy); | |
| println!(" --> Total time: {:?}", total_duration); | |
| println!(" --> Avg time: {:?}", mean_duration); | |
| for p in [50.0, 95.0, 99.0] { | |
| println!(" --> {}th: {:?}", p, calc_percentile(results, p)); | |
| } | |
| } | |
| } | |
| // Correct exit code, if charset-normalizer-rs accuracy lower than 95% | |
| if our_accuracy < 97.0 { | |
| println!("LOW ACCURACY!!!"); | |
| 1 | |
| } else { | |
| 0 | |
| } | |
| } | |
| // Main function | |
| pub fn main() { | |
| let args = PerformanceArgs::parse(); | |
| process::exit(performance_compare(&args)); | |
| } | |