zipora 3.1.5

High-performance Rust implementation providing advanced data structures and compression algorithms with memory safety guarantees. Features LRU page cache, sophisticated caching layer, fiber-based concurrency, real-time compression, secure memory pools, SIMD optimizations, and complete C FFI for migration from C++.
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
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
use zipora::entropy::*;
use zipora::error::Result;
use std::time::Instant;

/// Comprehensive performance test suite for entropy algorithms
/// Only runs in release mode to ensure accurate performance measurements

#[cfg(not(debug_assertions))]
mod performance_tests {
    use super::*;

    fn generate_test_datasets() -> Vec<(&'static str, Vec<u8>)> {
        vec![
            // Low entropy data
            ("low_entropy_1kb", vec![42u8; 1024]),
            ("low_entropy_64kb", vec![123u8; 65536]),
            
            // Medium entropy data
            ("medium_entropy_1kb", (0..=255u8).cycle().take(1024).collect()),
            ("medium_entropy_64kb", (0..=255u8).cycle().take(65536).collect()),
            
            // High entropy data (pseudo-random)
            ("high_entropy_1kb", {
                let mut data = Vec::new();
                for i in 0..1024 {
                    data.push(((i * 31 + 17) % 256) as u8);
                }
                data
            }),
            ("high_entropy_64kb", {
                let mut data = Vec::new();
                for i in 0..65536 {
                    data.push(((i * 31 + 17) % 256) as u8);
                }
                data
            }),
            
            // Textual data (realistic compression scenario)
            ("text_data_1kb", "Lorem ipsum dolor sit amet, consectetur adipiscing elit. ".repeat(19).into_bytes()),
            ("text_data_64kb", "The quick brown fox jumps over the lazy dog. ".repeat(1456).into_bytes()),
            
            // Binary patterns
            ("binary_pattern_1kb", {
                let mut data = Vec::new();
                for i in 0..256 {
                    data.extend_from_slice(&[i as u8, !i as u8, i as u8, !i as u8]);
                }
                data
            }),
            ("binary_pattern_64kb", {
                let mut data = Vec::new();
                for _ in 0..64 {
                    for i in 0..256 {
                        data.extend_from_slice(&[i as u8, !i as u8, i as u8, !i as u8]);
                    }
                }
                data
            }),
        ]
    }

    #[test]
    fn test_huffman_performance_comprehensive() -> Result<()> {
        println!("\n=== Huffman Algorithms Performance Test ===");
        
        let datasets = generate_test_datasets();
        
        for (name, data) in datasets {
            println!("\nDataset: {} ({} bytes)", name, data.len());
            
            // Basic Huffman
            let start = Instant::now();
            let basic_encoder = HuffmanEncoder::new(&data)?;
            let basic_compressed = basic_encoder.encode(&data)?;
            let basic_time = start.elapsed();
            let basic_ratio = data.len() as f64 / basic_compressed.len() as f64;
            
            println!("  Basic Huffman: {:.2}x compression, {:.2}ms, {:.2} MB/s", 
                     basic_ratio, basic_time.as_millis(), 
                     (data.len() as f64 / 1024.0 / 1024.0) / basic_time.as_secs_f64());
            
            // Contextual Huffman Order-1
            let start = Instant::now();
            let ctx1_encoder = ContextualHuffmanEncoder::new(&data, HuffmanOrder::Order1)?;
            let ctx1_compressed = ctx1_encoder.encode(&data)?;
            let ctx1_time = start.elapsed();
            let ctx1_ratio = data.len() as f64 / ctx1_compressed.len() as f64;
            
            println!("  Order-1 Huffman: {:.2}x compression, {:.2}ms, {:.2} MB/s", 
                     ctx1_ratio, ctx1_time.as_millis(),
                     (data.len() as f64 / 1024.0 / 1024.0) / ctx1_time.as_secs_f64());
            
            // Contextual Huffman Order-2
            if data.len() >= 3 {
                let start = Instant::now();
                let ctx2_encoder = ContextualHuffmanEncoder::new(&data, HuffmanOrder::Order2)?;
                let ctx2_compressed = ctx2_encoder.encode(&data)?;
                let ctx2_time = start.elapsed();
                let ctx2_ratio = data.len() as f64 / ctx2_compressed.len() as f64;
                
                println!("  Order-2 Huffman: {:.2}x compression, {:.2}ms, {:.2} MB/s", 
                         ctx2_ratio, ctx2_time.as_millis(),
                         (data.len() as f64 / 1024.0 / 1024.0) / ctx2_time.as_secs_f64());
            }
        }
        
        Ok(())
    }

    #[test]
    fn test_rans_performance_comprehensive() -> Result<()> {
        println!("\n=== rANS Algorithms Performance Test ===");
        
        let datasets = generate_test_datasets();
        
        for (name, data) in datasets {
            println!("\nDataset: {} ({} bytes)", name, data.len());
            
            // Calculate frequencies
            let mut frequencies = [1u32; 256];
            for &byte in &data {
                frequencies[byte as usize] += 1;
            }
            
            // Enhanced rANS 64-bit single stream
            let start = Instant::now();
            let rans_encoder = Rans64Encoder::<ParallelX1>::new(&frequencies)?;
            let rans_compressed = rans_encoder.encode(&data)?;
            let rans_time = start.elapsed();
            let rans_ratio = data.len() as f64 / rans_compressed.len() as f64;
            
            println!("  rANS 64-bit: {:.2}x compression, {:.2}ms, {:.2} MB/s", 
                     rans_ratio, rans_time.as_millis(),
                     (data.len() as f64 / 1024.0 / 1024.0) / rans_time.as_secs_f64());
            
            // Parallel rANS x2
            let start = Instant::now();
            let rans_x2_encoder = Rans64Encoder::<ParallelX2>::new(&frequencies)?;
            let rans_x2_compressed = rans_x2_encoder.encode(&data)?;
            let rans_x2_time = start.elapsed();
            let rans_x2_ratio = data.len() as f64 / rans_x2_compressed.len() as f64;
            
            println!("  rANS x2: {:.2}x compression, {:.2}ms, {:.2} MB/s", 
                     rans_x2_ratio, rans_x2_time.as_millis(),
                     (data.len() as f64 / 1024.0 / 1024.0) / rans_x2_time.as_secs_f64());
            
            // Parallel rANS x4
            let start = Instant::now();
            let rans_x4_encoder = Rans64Encoder::<ParallelX4>::new(&frequencies)?;
            let rans_x4_compressed = rans_x4_encoder.encode(&data)?;
            let rans_x4_time = start.elapsed();
            let rans_x4_ratio = data.len() as f64 / rans_x4_compressed.len() as f64;
            
            println!("  rANS x4: {:.2}x compression, {:.2}ms, {:.2} MB/s", 
                     rans_x4_ratio, rans_x4_time.as_millis(),
                     (data.len() as f64 / 1024.0 / 1024.0) / rans_x4_time.as_secs_f64());
        }
        
        Ok(())
    }

    #[test]
    fn test_fse_performance_comprehensive() -> Result<()> {
        println!("\n=== FSE Algorithms Performance Test ===");
        
        let datasets = generate_test_datasets();
        
        for (name, data) in datasets {
            println!("\nDataset: {} ({} bytes)", name, data.len());
            
            // Enhanced FSE Default
            let start = Instant::now();
            let mut fse_encoder = FseEncoder::new(FseConfig::default())?;
            let fse_compressed = fse_encoder.compress(&data)?;
            let fse_time = start.elapsed();
            let fse_ratio = data.len() as f64 / fse_compressed.len() as f64;
            
            println!("  FSE Default: {:.2}x compression, {:.2}ms, {:.2} MB/s", 
                     fse_ratio, fse_time.as_millis(),
                     (data.len() as f64 / 1024.0 / 1024.0) / fse_time.as_secs_f64());
            
            // Enhanced FSE Fast
            let start = Instant::now();
            let mut fse_fast_encoder = FseEncoder::new(FseConfig::fast_compression())?;
            let fse_fast_compressed = fse_fast_encoder.compress(&data)?;
            let fse_fast_time = start.elapsed();
            let fse_fast_ratio = data.len() as f64 / fse_fast_compressed.len() as f64;
            
            println!("  FSE Fast: {:.2}x compression, {:.2}ms, {:.2} MB/s", 
                     fse_fast_ratio, fse_fast_time.as_millis(),
                     (data.len() as f64 / 1024.0 / 1024.0) / fse_fast_time.as_secs_f64());
            
            // Enhanced FSE High Compression
            let start = Instant::now();
            let mut fse_high_encoder = FseEncoder::new(FseConfig::high_compression())?;
            let fse_high_compressed = fse_high_encoder.compress(&data)?;
            let fse_high_time = start.elapsed();
            let fse_high_ratio = data.len() as f64 / fse_high_compressed.len() as f64;
            
            println!("  FSE High: {:.2}x compression, {:.2}ms, {:.2} MB/s", 
                     fse_high_ratio, fse_high_time.as_millis(),
                     (data.len() as f64 / 1024.0 / 1024.0) / fse_high_time.as_secs_f64());
        }
        
        Ok(())
    }

    #[test]
    fn test_parallel_encoding_performance() -> Result<()> {
        println!("\n=== Parallel Encoding Performance Test ===");
        
        let large_datasets = vec![
            ("large_low_entropy", vec![77u8; 262144]),
            ("large_medium_entropy", (0..=255u8).cycle().take(262144).collect()),
            ("large_high_entropy", {
                let mut data = Vec::new();
                for i in 0..262144 {
                    data.push(((i * 37 + 23) % 256) as u8);
                }
                data
            }),
        ];
        
        for (name, data) in large_datasets {
            println!("\nDataset: {} ({} KB)", name, data.len() / 1024);
            
            // Test different parallel configurations
            let configs = vec![
                ("x2", ParallelConfig::low_latency()),
                ("x4", ParallelConfig::balanced()),
                ("x8", ParallelConfig::high_throughput()),
            ];
            
            for (config_name, config) in configs {
                let start = Instant::now();
                let mut encoder = ParallelHuffmanEncoder::<ParallelX4Variant>::new(config)?;
                encoder.train(&data)?;
                let compressed = encoder.encode(&data)?;
                let elapsed = start.elapsed();
                let ratio = data.len() as f64 / compressed.len() as f64;
                
                println!("  Parallel {} Config: {:.2}x compression, {:.2}ms, {:.2} MB/s", 
                         config_name, ratio, elapsed.as_millis(),
                         (data.len() as f64 / 1024.0 / 1024.0) / elapsed.as_secs_f64());
            }
            
            // Test adaptive encoding
            let start = Instant::now();
            let mut adaptive_encoder = AdaptiveParallelEncoder::new()?;
            let adaptive_compressed = adaptive_encoder.encode_adaptive(&data)?;
            let adaptive_elapsed = start.elapsed();
            let adaptive_ratio = data.len() as f64 / adaptive_compressed.len() as f64;
            
            println!("  Adaptive Parallel: {:.2}x compression, {:.2}ms, {:.2} MB/s", 
                     adaptive_ratio, adaptive_elapsed.as_millis(),
                     (data.len() as f64 / 1024.0 / 1024.0) / adaptive_elapsed.as_secs_f64());
        }
        
        Ok(())
    }

    #[test]
    fn test_bit_operations_performance() -> Result<()> {
        println!("\n=== Bit Operations Performance Test ===");
        
        let bit_ops = BitOps::new();
        let entropy_bit_ops = EntropyBitOps::new();
        let test_values: Vec<u64> = (0..10000).map(|i| i * 0x123456789ABCDEF).collect();
        
        // Test popcount performance
        let start = Instant::now();
        let mut sum = 0u64;
        for &value in &test_values {
            sum += bit_ops.popcount64(value) as u64;
        }
        let popcount_time = start.elapsed();
        println!("  Popcount (10k values): {} bits total, {:.2}ms, {:.2} M ops/s", 
                 sum, popcount_time.as_millis(),
                 (test_values.len() as f64 / 1_000_000.0) / popcount_time.as_secs_f64());
        
        // Test reverse bits performance (using 32-bit since 64-bit is not available)
        let start = Instant::now();
        for &value in &test_values {
            let _ = entropy_bit_ops.reverse_bits32(value as u32);
        }
        let reverse_time = start.elapsed();
        println!("  Reverse bits 32 (10k values): {:.2}ms, {:.2} M ops/s", 
                 reverse_time.as_millis(),
                 (test_values.len() as f64 / 1_000_000.0) / reverse_time.as_secs_f64());
        
        // Test BMI2 operations if available
        if bit_ops.features().has_bmi2 {
            println!("  BMI2 Instructions Available");
            
            let start = Instant::now();
            for &value in &test_values {
                let _ = bit_ops.parallel_deposit64(value, 0xAAAAAAAAAAAAAAAA);
            }
            let pdep_time = start.elapsed();
            println!("  PDEP (10k values): {:.2}ms, {:.2} M ops/s", 
                     pdep_time.as_millis(),
                     (test_values.len() as f64 / 1_000_000.0) / pdep_time.as_secs_f64());
            
            let start = Instant::now();
            for &value in &test_values {
                let _ = bit_ops.parallel_extract64(value, 0xAAAAAAAAAAAAAAAA);
            }
            let pext_time = start.elapsed();
            println!("  PEXT (10k values): {:.2}ms, {:.2} M ops/s", 
                     pext_time.as_millis(),
                     (test_values.len() as f64 / 1_000_000.0) / pext_time.as_secs_f64());
        } else {
            println!("  BMI2 Instructions Not Available");
        }
        
        Ok(())
    }

    #[test]
    fn test_entropy_context_performance() -> Result<()> {
        println!("\n=== Entropy Context Performance Test ===");
        
        let context = EntropyContext::new();
        
        let buffer_sizes = vec![1024, 8192, 65536, 262144];
        
        for &size in &buffer_sizes {
            // Test buffer allocation performance
            let start = Instant::now();
            for _ in 0..1000 {
                let _buffer = context.alloc(size)?;
            }
            let alloc_time = start.elapsed();
            
            println!("  Buffer allocation ({} bytes, 1k times): {:.2}ms, {:.2} M allocs/s", 
                     size, alloc_time.as_millis(),
                     (1000.0 / 1_000_000.0) / alloc_time.as_secs_f64());
            
            // Test zeroed buffer performance
            let start = Instant::now();
            for _ in 0..1000 {
                let _buffer = context.alloc_zeroed(size)?;
            }
            let temp_time = start.elapsed();
            
            println!("  Zeroed buffer allocation ({} bytes, 1k times): {:.2}ms, {:.2} M allocs/s", 
                     size, temp_time.as_millis(),
                     (1000.0 / 1_000_000.0) / temp_time.as_secs_f64());
        }
        
        let stats = context.stats()?;
        println!("  Context Stats: {} cached buffers, {} total capacity, {} max capacity", 
                 stats.cached_buffers, stats.total_capacity, stats.max_capacity);
        
        Ok(())
    }

    #[test]
    fn test_algorithm_comparison_performance() -> Result<()> {
        println!("\n=== Algorithm Comparison Performance Test ===");
        
        let test_data = "This is a comprehensive test of various entropy encoding algorithms. ".repeat(1000);
        let data = test_data.as_bytes();
        
        println!("Test data: {} bytes", data.len());
        
        // Huffman
        let start = Instant::now();
        let huffman_encoder = HuffmanEncoder::new(data)?;
        let huffman_compressed = huffman_encoder.encode(data)?;
        let huffman_time = start.elapsed();
        let huffman_ratio = data.len() as f64 / huffman_compressed.len() as f64;
        
        // rANS
        let mut frequencies = [1u32; 256];
        for &byte in data {
            frequencies[byte as usize] += 1;
        }
        let start = Instant::now();
        let rans_encoder = Rans64Encoder::<ParallelX1>::new(&frequencies)?;
        let rans_compressed = rans_encoder.encode(data)?;
        let rans_time = start.elapsed();
        let rans_ratio = data.len() as f64 / rans_compressed.len() as f64;
        
        // FSE
        let start = Instant::now();
        let mut fse_encoder = FseEncoder::new(FseConfig::default())?;
        let fse_compressed = fse_encoder.compress(data)?;
        let fse_time = start.elapsed();
        let fse_ratio = data.len() as f64 / fse_compressed.len() as f64;
        
        // Adaptive Parallel
        let start = Instant::now();
        let mut adaptive_encoder = AdaptiveParallelEncoder::new()?;
        let adaptive_compressed = adaptive_encoder.encode_adaptive(data)?;
        let adaptive_time = start.elapsed();
        let adaptive_ratio = data.len() as f64 / adaptive_compressed.len() as f64;
        
        println!("\nComparison Results:");
        println!("Algorithm        | Ratio | Time (ms) | Speed (MB/s)");
        println!("-----------------|-------|-----------|-------------");
        println!("Huffman          | {:.2}x  | {:7.2} | {:10.2}", 
                 huffman_ratio, huffman_time.as_millis(),
                 (data.len() as f64 / 1024.0 / 1024.0) / huffman_time.as_secs_f64());
        println!("rANS 64          | {:.2}x  | {:7.2} | {:10.2}", 
                 rans_ratio, rans_time.as_millis(),
                 (data.len() as f64 / 1024.0 / 1024.0) / rans_time.as_secs_f64());
        println!("Enhanced FSE     | {:.2}x  | {:7.2} | {:10.2}", 
                 fse_ratio, fse_time.as_millis(),
                 (data.len() as f64 / 1024.0 / 1024.0) / fse_time.as_secs_f64());
        println!("Adaptive Parallel| {:.2}x  | {:7.2} | {:10.2}", 
                 adaptive_ratio, adaptive_time.as_millis(),
                 (data.len() as f64 / 1024.0 / 1024.0) / adaptive_time.as_secs_f64());
        
        Ok(())
    }
}

// Stub tests for debug builds
#[cfg(debug_assertions)]
mod debug_build_stubs {
    use super::*;
    
    #[test]
    fn debug_build_notice() {
        println!("Performance tests are only available in release builds.");
        println!("Run with: cargo test --release entropy_performance");
    }
}